FEEDSTOCK AND AMENDMENT EFFECTS ON COMPOST CHARACTERISTICS AND 

USE IN VEGETABLE PRODUCTION 

 
By 
 

Brooke Michele Comer 

 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 

 

 

 

 

A DISSERTATION 

Submitted to 

Michigan State University 

in partial fulfillment of the requirements  

for the degree of 

Horticulture- Doctor of Philosophy 

2020 

 

ABSTRACT 

FEEDSTOCK AND AMENDMENT EFFECTS ON COMPOST CHARACTERISTICS AND 

USE IN VEGETABLE PRODUCTION 

 
By 
 

Brooke Michele Comer 

The research objectives were the production of compost for transplant root media and 

managing fertility and disease in vegetable cropping systems.  The priorities were on using local 

organic materials to capture carbon and nutrients, proliferation of beneficial microorganisms and 

reducing the need for off farm inputs, particularly in an organic certification system.    

Composts were made and the soluble and total nutrients, electrical conductivity, pH, 

percent organic matter, the final C:N ratio and bulk density are reported and correlated to the 

growth of transplants in greenhouse bioassays.  In the first experiments (Chapter I), small-scale 

(1yd3) thermophilic compost piles were constructed with variations in feedstocks to produce ten 

treatments focused primarily on starting carbon to nitrogen ratios, and the feedstock 

contributions observed in the physiochemical characteristics of the finished composts. Fall-

collected leaves and on-farm fresh cut grass (1:1 v:v) as a base recipe and variations thereof by 

adjusting volume ratios of those feedstocks, or adding (1:1:1) dairy/horse manure, coffee 

grounds, shredded office paper, softwood shavings, or sphagnum peat, wrapping the base mix in 

plastic, and a standard mixture developed and used in previous research.  Three species of plants: 

cucumber (Cucumis sativus), kale (Brassica oleracea), and tomato (Solanum lycopersicum) were 

grown and evaluated for dry and wet weights, plant heights, root ratings and number of leaves. 

Growth response in compost substrates were not consistent between species.  Composts 

containing peat as an ingredient had lower pH and generally resulted in better growth of 

transplants while growth was minimal in wood shavings compost.  Cucumber transplants were 

 

 

grown in the composts after storage for 2, 3 or 4 years which identified differences in growth as 

the compost characteristics had changed over time.  A second group of experiments (Chapter II) 

had the same base feedstocks with the addition of biochar (BC) and anaerobic digester effluent 

(ADE), on their own and combined.  For cucumbers grown in these compost mixes, addition of 

biochar improved all metrics of transplant growth; in contrast, addition of ADE reduced several 

metrics of transplant health including shoot dry weight and root ratings. Most of the compost 

media produced acceptable transplants of varying quality without additional fertility added over 

the 3 to 5-week greenhouse production period.  A laboratory vermicomposting bioassay (Chapter 

III) was designed to evaluate the effects of pineapple, melon, onion, carrot, spent coffee grounds 

(SCG) and a mixture of all five kitchen preparation residues from campus food service as 

vermicomposting feedstocks. Data were collected for the impact on worms, finished compost 

chemical characteristics and biota by community level physiological profiling using Biolog 

EcoPlates. SCG as a feedstock had elevated total N but nearly undetectable soluble NO3-N, and 

greater microbial community functional diversity.  Compost teas from three composts (dairy-

manure based and leaf/grass/coffee based thermophilic composts, and food waste based 

vermicompost) were assessed for impacts on tomato leaf mold (Fulvia fulva) and winter squash 

powdery mildew (Podosphaera xanthii) management in a farm setting (Chapter 4). Aerated 

compost teas (CT) were produced for weekly foliar application on two tomato (Solanum 

lycopersicum) varieties and three winter squash varieties (Cucurbita moschata, C. pepo, and C. 

maxima) (five separate experiments).  While there was some efficacy for management of disease 

in some of these plant/pathogen systems, this varied by species/variety; and as disease pressure 

increased over the season CT efficacy ceased.  Use of a spreader-sticker appeared to increase 

disease management in some trials. 

 

 

ACKNOWLEDGEMENTS 

 

I would like to express my sincere gratitude to my major advisor, Dr. John Biernbaum, 

who showed me around beautiful hoophouses full of green vegetables while snow drifts piled up 

after I had spent years in the tropics and I was inspired to come to MSU.  It has been a long 

journey with you over my years here; I have learned so much and cherish the relationship we 

have cemented.  I am also indebted to my committee members Dr. Dan Brainard, Dr. Zachary 

Hayden, and Dr. Lisa Tiemann for providing sage advice and review.  To Jerri Gillett and Dr. 

Annemiek Schilder from my early work with compost tea.  So many other professors and staff 

with whom I may have never worked directly but that had such a positive impact on my time 

here at MSU.  Jon Dahl and all the staff of the SPNL- for teaching me analytical methods and 

processing so many samples!  Many undergraduates I was able to work with and teach 

throughout the years.  Bill Chase, SOF staff, and others at the HTRC.  A huge thanks to Jeff 

Doser and Leo Pham from the MSU Statistical Consulting Center for teaching me R and guiding 

me through analyses and coding.  There are a number of graduate students especially early on in 

my time at MSU that made this such a well-rounded experience, personally and professionally 

such as Alexia Witcombe, Aaron Yoder, Carolyn Lowry, Gayathri Kotamraju, Stefan Cerbin, 

Jesse Traub and Brent Crain.  To the farmers and other wonderful people in the urban agriculture 

movement here in Lansing and throughout the state that I have gotten to know, the community 

around sustainable agriculture and food has uplifted me and taught me so much.  And for my 

particular love of teaching I am especially indebted to Julie Cotton- from her advising in the 

EFFS program, to being introduced to the SAEA community, starting CSS224 with her, and 

finally the use of her house to write so I could get away from my kids and concentrate! 

 

iv 

I am appreciative that MSU has an Office of Campus Sustainability, and their interest in 

funding the work that John and I were doing- I think it is important and we need sustained 

emphasis in this area.  Along with that, thank you to the MSU Surplus Store and staff that I’ve 

worked with over the years.  Additional funding without which none of this would have been 

possible came from the Plant Science Fellowship and CS Mott Fellowship, and a scholarship 

from the Ecological Food and Farming Systems specialization. 

 

None of this would have been possible without the love and support of my husband, 

Donny.  You have been my rock throughout the last eight years of this process, motivating me, 

supporting me and loving me and I would not be here at the finish line without you.  And to get 

to the finish line, my Dad who helped immeasurably with keeping our family going. 

 

And to three people in particular who have made my journey to finishing my dissertation 

more difficult, more rewarding, and provided possibly the most motivation: my mother, Anilie 

and Gaia.  Mom, you are a strong, amazing woman, taken from my life way too soon.  Before 

you left us, you’d try to light a fire under me to have me press on, and since your passing I think 

of you daily and what words of advice and encouragement you would be giving.  Since coming 

to Michigan took me away from you, you’d want me to come away with this win!  Anilie and 

Gaia, you also made the process take a lot longer, having two kids in the midst of my graduate 

career.  But I want to be an example to you two of what you can accomplish if you put your mind 

to it, and for you to be whatever in this world you want to be.   

 

 

v 

 

TABLE OF CONTENTS 

LIST OF TABLES ................................................................................................................... viii 

LIST OF FIGURES .................................................................................................................... x 

INTRODUCTION ...................................................................................................................... 1 

CHAPTER I ............................................................................................................................... 6 
FEEDSTOCK EFFECTS ON FINISHED COMPOST AND FOR GROWING ORGANIC 
VEGETABLE TRANSPLANTS ................................................................................................ 6 
ABSTRACT .................................................................................................................... 7 
INTRODUCTION ........................................................................................................... 8 
MATERIALS AND METHODS ................................................................................... 15 
RESULTS ..................................................................................................................... 23 
DISCUSSION ............................................................................................................... 28 
FUTURE RESEARCH AND CONCLUSIONS............................................................. 34 
APPENDIX ................................................................................................................... 37 
REFERENCES.............................................................................................................. 55 
 

CHAPTER II ............................................................................................................................ 60 
BIOCHAR AND ANAEROBIC DIGESTER EFFLUENT IN COMPOSTING: EFFECTS ON 
FINISHED COMPOST FOR GROWING ORGANIC CUCUMBER TRANSPLANTS............ 60  
ABSTRACT .................................................................................................................. 61 
INTRODUCTION ......................................................................................................... 62 
MATERIALS AND METHODS ................................................................................... 69 
RESULTS ..................................................................................................................... 75 
DISCUSSION ............................................................................................................... 80 
FUTURE RESEARCH AND CONCLUSIONS............................................................. 87 
APPENDIX ................................................................................................................... 90 
REFERENCES............................................................................................................ 100 
 
 

CHAPTER III ......................................................................................................................... 107 
FEEDSTOCK EFFECT ON COMPOSTING WORMS AND VERMICOMPOST  
NUTRIENTS AND BIOLOGY .............................................................................................. 107 
ABSTRACT ................................................................................................................ 108 
INTRODUCTION ....................................................................................................... 108 
MATERIALS AND METHODS ................................................................................. 112 
RESULTS ................................................................................................................... 116 
DISCUSSION ............................................................................................................. 118 
APPENDIX ................................................................................................................. 123 
REFERENCES............................................................................................................ 129 
 

 

vi 

CHAPTER IV ......................................................................................................................... 133 
COMPOST TEA FOR DISEASE SUPPRESSION IN HIGH TUNNEL TOMATO AND  
FIELD GROWN WINTER SQUASH ..................................................................................... 133 
ABSTRACT ................................................................................................................ 134 
INTRODUCTION ....................................................................................................... 134 
MATERIALS AND METHODS ................................................................................. 140 
RESULTS ................................................................................................................... 145 
DISCUSSION ............................................................................................................. 149 
FUTURE RESEARCH AND CONCLUSIONS........................................................... 153 
APPENDIX ................................................................................................................. 155 
REFERENCES............................................................................................................ 164 
 

 

 

 

vii 

 

LIST OF TABLES 

Table 1.1. Compost feedstock recipes. ...................................................................................... 38 
 
Table 1.2. Compost properties of organic matter and carbon content, carbon to nitrogen ratio 
(C:N) and dry bulk density (mean +/- SE, n=3) by compost treatment. Samples collected for 
analysis approximately six months after the start of the thermophilic composting phase. ........... 39 
 
Table 1.3. The pH, EC and water soluble nutrient values (mean +/- SE, n=3) from the saturated 
media extract for compost media. Samples collected for analysis approximately six months  
after the start of the thermophilic composting phase. ................................................................. 40 
 
Table 1.4. Nutrient values (mean +/- SE, n=3) from total nutrient analysis of compost media.  
at 6 months maturity for nutrients with significant differences between treatments. Samples 
collected for analysis approximately six months after the start of the thermophilic composting 
phase......................................................................................................................................... 41 
 
Table 1.5. Emergence rates for cucumber, kale and tomato transplants in the ten compost  
media and control. Mean % (+/- SE), n=3. ................................................................................ 42 
 
Table 1.6. Effect of compost feedstock recipes on plant growth responses of dry weight, wet 
weight, root rating, plant height and number of leaves for cucumber, kale and tomato. Mean 
values (+/- SE), n=3. ................................................................................................................. 43 
 
Table 1.7. Mean values (+/- SE) for five plant metrics of dry weight, wet weight, root rating, 
plant height and number of leaves per plant for cucumber grown in compost treatments at 
different ages. ........................................................................................................................... 45 
 
Table 1.8. Selected chemical characteristics of compost at different ages. ................................. 47 
 
Table 1.9. Mean harvest weights (+/- SE, n=6) of basil, and pH of media from 1-year old 
compost media, grown in 2015.................................................................................................. 49 
 
Table 1.10. Basil harvest weight, root media pH, and recently mature leaf tissue analysis from 
'Control' (with normal leaf coloration) and 'Food' (chlorotic leaf coloration) compost media 
treatments. ................................................................................................................................ 50 
 
Table 2.1. Experiment 1 effects of biochar and liquid anaerobic digester effluent (ADE)  
addition to compost on physical characteristics of dry bulk density and moisture as well as 
organic matter, carbon and C:N. Experiment 2 effects of biochar addition to vermicompost  
on bulk density, moisture, organic matter, carbon and C:N. Mean (+SE, n=3) for all. . .............. 91 
 
 

 

 

viii 

Table 2.2. Experiment 1 effects of biochar and liquid anaerobic digester effluent (ADE)  
addition to compost on compost pH and EC at 5 and 15 months old (mo). Experiment 2 effects 
of biochar addition to vermicompost on pH and EC. Mean (+/- SE, n=3) for all. ....................... 92 
 
Table 2.3. Experiment 1 effects of biochar addition and anaerobic digester effluent (ADE) on 
compost soluble nutrients. Experiment 2 effects of biochar addition to vermicompost on soluble 
nutrients. Mean (+/- SE, n=3) for all.......................................................................................... 93 
 
Table 2.4. Effects of biochar addition and anaerobic digester effluent (ADE) in compost media 
on emergence and plant growth responses. Mean (+/- SE), n=4. ................................................ 94 
 
Table 2.5. Comparison of compost-media treatments with peat-medium control for mean  
(+/- SE, n=12) emergence and plant growth responses. Asterisks indicate significant  
differences between treatments and the peat-based control using Dunnett’s test... ..................... 95 
 
Table 3.1. Microbiology of composts determined by Biolog Ecoplates for species richness, 
Shannon-Wiener Diversity Index, substrate evenness, and AWCD by vermicompost feedstock 
treatment. ................................................................................................................................ 124 
 
Table 3.2. Compost properties of organic matter (%), carbon (%), carbon to nitrogen ratio,  
and moisture by compost treatment after 5 weeks of feeding and 4 weeks of incubation.......... 125 
 
Table 3.3. The pH, EC and water soluble nutrient values from the saturated media extract for 
vermicompost treatments after 5 weeks of feeding and 4 weeks of incubation. ........................ 126 
 
Table 3.4. Total nutrient analysis of vermicomposts after 5 weeks of feeding and 4 weeks of 
incubation. .............................................................................................................................. 127 
 
Table 4.1. Overall severity, incidence, and severity for ‘Big Beef’ and 'Celebrity’ tomatoes 
infestation by F. fulvia. Data taken on 7 August 2016, two months after weekly spraying 
commenced when plants showed moderate signs of disease. ................................................... 156 
 
Table 4.2. Harvest data for 'Big Beef' and 'Celebrity' tomatoes by number of tomatoes  
harvested, total weight harvested, and grams (g) per tomato over the course of the season per 
plant. ....................................................................................................................................... 157 
 
Table 4.3. Overall severity, incidence, and severity for 'Waltham Butternut,' 'Delicata,' and  
'Blue Ballet Hubbard' squash infestation by P. xanthii. Data taken on 5 August 2016, two  
months after weekly spraying commenced when plants showed moderate signs of disease. ..... 158 
 
Table 4.4. Significance (p-value) of the main effects of vermicompost compost tea (VC CT),  
the spreader-sticker NuFilm P, and their interaction on overall severity of Fulvia fulva on 
tomatoes and Podosphaera xanthii on butternut squash. .......................................................... 159 
 
 
 

 

 

ix 

 

LIST OF FIGURES 

Figure 1.1. Principal component analysis biplot of the first and second principal components  
for compost physiochemical properties of A) all thermophilic composts and B) treatments 
grouped by starting C:N ratio.  The percentages of the total variance accounted for by each 
principal component are indicated in parentheses in axis titles.  ................................................ 51 
 
Figure 1.2.  Loading contributions of compost physiochemical characteristics for interpretation 
of PCA values for A) PC1 and B) PC2. ..................................................................................... 52 
 
Figure 1.3.  Plant growth data for all plant species for A) dry weights, B) wet weights, C) root 
rating, D) plant heights and E) number of leaves.  Columns denoted by the same letter within the 
same species are not different according to Tukey’s HSD test (p<0.05). .................................... 53 
 
Figure 1.4.  Linear regression of relationship between pH and basil harvest weight. P<0.001, 
R2=0.50..................................................................................................................................... 54 
 
Figure 2.1.  Root ratings scale for transplant root assessment ranging from 1 to 5 which were 
used in the visual assessment of transplants. .............................................................................. 96 
 
Figure 2.2.  Principal component analysis biplots of the first and second principal components 
for compost physiochemical properties of A) all four thermophilic composts, B) Mix and 
Mix+BC only, C) Mix+AD and Mix+BC+AD only, and D) Vermicomposts.  The percentages 
 of the total variance accounted for by each principal component are indicated in parentheses  
in axis titles. .............................................................................................................................. 97 
 
Figure 2.3. Loading contribution of compost physiochemical characteristics for interpretation  
of PCA values of PC1 and PC2 for A) all four thermophilic composts, B) Mix and Mix+BC 
only, C) Mix+AD and Mix+BC+AD only, and D) Vermicomposts. .......................................... 98 
 
Figure 2.4.  A subset of eight plants from one of the replications from each compost treatment  
A) Mix; B) Mix+BC; C) Mix+ADE; and D) Mix+BC+ADE. .................................................... 99 
 
Figure 3.1.  A) Laboratory set-up for vermicomposting feeding trial with the seven treatments, 
one replication per shelf and a total of four replications and B) Close-up of feeding of  
pineapple on one half of worm bin (back) and covered with ground leaves before being wet  
by misting (front). ................................................................................................................... 128 
 
Figure 4.1.  A) Tomato leaf mold on ‘Celebrity’ tomatoes, B) Close up of tomato leaf infected, 
and C) Powdery mildew symptoms on ‘Blue Ballet Hubbard’ squash.  ................................... 160 
 
 

 

 

x 

Figure 4.2.  Overall severity (incidence*severity) as % leaf area infected by F. fulvia for tomato 
varieties A) ‘Big Beef’ and B) ‘Celebrity’ by compost tea treatment.  Columns labeled with the 
same letter are not significantly different than one another (p<0.05).  LGC = CT from 
leaf/grass/coffee thermophilic compost; DMC = CT from dairy manure based themophilic 
compost; VC = CT from vermicompost (no manure); VC+Nu = VC with NuFilm P added; 
NuFilm = NuFilm P only. ....................................................................................................... 161 
 
Figure 4.3.  Overall severity (% leaf area infected) for the treatments Control  
(- VC, - NuFilm), VC, NuFilm and VC+Nu of F. fulvia on tomato varieties A) ‘Big Beef’ B) 
‘Celebrity’ and of P. xanthii on C) ‘Waltham Butternut’ squash from disease ratings taken on  
5 and 7 August in the early stages of disease. .......................................................................... 162 
 
Figure 4.4.  Overall severity (incidence*severity) as % leaf area infected by P. xanthii for three 
winter squash species/varieties A) (Cucurbitaceae moschata) ‘Waltham Butternut’, B) C. pepo 
‘Delicata‘, and C) C. maxima ‘Blue Ballet Hubbard’ by compost tea treatment.  Columns  
labeled with the same letter are not significantly different than one another (p<0.05).   
LGC = CT from leaf/grass/coffee thermophilic compost; DMC = CT from dairy manure  
based themophilic compost; VC = CT from vermicompost (no manure); VC+Nu = VC with 
NuFilm P added; NuFilm = NuFilm P only. ............................................................................ 163 
 
 
 

 

xi 

INTRODUCTION

 

1 

  

While composting has been used by farmers as a means of increasing soil fertility for 

centuries, in recent times/decades, compost has also been used as a component of root 

media/substrates for container grown plants and as a method of increasing plant resistance to 

insects and diseases through foliar application of compost tea.  The quality and characteristics of 

the composts used for these specific added-value purposes can be managed and enhanced 

through a greater understanding of the effects of specific feedstocks and/or amendments and 

through the use of alternative composting methods such as vermicomposting.   

The objectives of this research project were the production of compost, with a focus on 

locally available materials that might otherwise end up in the waste stream and the use of those 

composts for growing high value crops.  Much of my work was specifically focused on “closing 

the food cycle loop” with thermophilic composting and vermicomposting of food residues from 

campus dining halls, so nutrients and organic matter could be returned back to the land.  One of 

our responsibilities as researchers / academics is anticipating possible future sources of on-farm 

fertility as those currently mined from the earth and oceans or produced with fossil fuels are 

depleted or increase in cost.  Intensive systems such as year-round high tunnels or greenhouses 

that are becoming increasingly popular on small scale diversified specialty crop farms and urban 

agriculture settings, especially in cold climates such as Michigan, are particularly benefited by 

such compost research. 

A primary motivating factor of this research was to increase effective fertility and pest 

management options in organic production for which nutrient and pesticide inputs are limited.  

This research project required a foundation of information from a range of topics including 

 

2 

production of both thermophilic compost and vermicompost, biochar, anaerobic digestion, 

compost teas and vegetable transplant production.   

Transplant production can be an important part of a farm plan, especially for organic 

growers.  Organic transplants can be harder to find commercially available for purchase, and 

even harder to make sure that the timing of transplants being ready for the field is in line with a 

farm’s production plan, particularly for diversified vegetable operations.  Growers/farmers using 

certified organic methods have a more limited set of options for suitable container root media 

and fertility compared to conventional growers.   

Compost use for growing transplants has been dominated by the question of what 

percentage can be added to a media as a replacement for peat, while very few studies have 

assessed compost as the sole media component.  Additionally, target/acceptable ranges for 

nutrients and other physiochemical characteristics of root media are generally geared 

towards peat-based media that would have soluble nutrients routinely added.  Routine addition of 

soluble nutrients is contrary to the principles of organic agriculture.  Such recommendations that 

stem from inert or low CEC media do not take into account the slow release of nutrients from 

compost in a biologically active system and other nutrient cycling dynamics.  Nutrient 

assessment and management recommendations specific for compost-based root media are needed 

as they can be based on the different physical, chemical and biological characteristics.    

Chapters I and II both have two parts: first compost production and then use of compost 

for growing transplants.  The overall objective of this work was not to produce the “best” 

compost and test it, but rather to characterize feedstock benefits to a thermophilic compost 

system intended for use as a plant growing medium.  Proportional effects of these feedstocks 

could then be calculated/estimated to develop a compost root media with the desired 

 

3 

characteristics.  Development of affordable compost-based transplant media using feedstocks 

that are readily available and would be generally consistent throughout the United States could 

increase the adoption of compost based media as an alternative for peat based media and use of 

fertilizers.  Both chapters provide more evidence to the body of knowledge about the effect of 

specific feedstocks/amendments to a composting system and the resultant compost chemical and 

physical characteristics.  Feedstock selection for the first experiment of ten treatments focused 

primarily on starting carbon to nitrogen ratios, while the second experiment had the same base 

recipe for compost as the first but was testing the impacts of biochar (BC) and anaerobic digester 

effluent (ADE), on their own and in tandem.  Chapter III is similarly focused on the effect of 

feedstocks on physical and chemical properties, and additionally biological properties of 

compost made in a laboratory setting using vermicomposting as the composting method to test 

specific food residue feedstocks.  This relates back to the bulk of my farm-scale experimentation 

with vermicomposting systems for a cold climate using food residue for vermicomposting, the 

primary constituents of which were selected as the treatment feedstocks.   

The second parts of Chapters I and II are growing transplants with the composts as the 

root media, often testing the boundaries of what would typically be expected as an acceptable 

range of certain physio-chemical properties such as electrical conductivity.  Using greenhouse 

studies the effect of compost treatment on growth parameters of cucumber (Cucumis sativus), 

kale (Brassica oleracea), and tomato (Solanum lycopersicum) were related this back to the 

compost physio-chemical characteristics.  Research reported in Chapter I used all three plant 

species while only cucumbers were grown in compost made in research reported in Chapter II.  

Most of the compost media used at 100% were able to produce acceptable transplants without 

additional fertility added, but of varying quality. 

 

4 

Still the benefits afforded transplants grown in microbially active compost-based media 

may not be enough to ward off disease once planted out in the field, and then compost designed 

for use as foliar sprays via compost tea could be used.  Compost tea trials both in controlled 

greenhouse settings and in the field have produced varied results that are dependent on the host / 

pathogen system being studied.  This area of compost research needs more experimentation, 

especially into specific diseases that have not yet been studied.  Research reported in Chapter IV 

evaluates three compost teas and a spreader-sticker for their efficacy in management of Fulvia 

fulva on two tomato (Solanum lycopersicum) varieties, and Podosphaera xanthii on three winter 

squash varieties butternut (Cucurbita moschata), delicata (C. pepo), and hubbard (C. maxima). 

Although composting is widely adopted, it is still often considered more of a waste 

management strategy for many organic waste streams generated by society.  Changing that 

paradigm to a resource management strategy requires additional scientific backing of how to best 

valorize the materials that we have.  Marketing of compost to increase its adoption for its 

intended uses at a price that generates profits associated with collection and production is another 

key step in furthering the use of compost.  Knowledge gained from this dissertation contributes 

to a base of information for what compost characteristics a farmer might want, and from which 

locally sourced feedstocks can be calculated and combined to achieve desired outcomes of the 

finished compost product.  Cultivating a circular ecology and economy in which waste streams 

are turned into resource streams that can increase the sustainability of a farming system has been 

a large driver of this work.  This work will hopefully increase adoption of compost for growing 

organic vegetable transplants and compost teas for disease management by providing more 

information to compost producers and growers.  An increased value for the compost product can 

stimulate increased interest in and motivation for the composting process. 

 

 

5 

FEEDSTOCK EFFECTS ON FINISHED COMPOST FOR GROWING ORGANIC 

VEGETABLE TRANSPLANTS 

CHAPTER I 

 

 

6 

ABSTRACT 

 

Thermophilic compost was made in static piles with alterations in feedstocks to adjust 

carbon to nitrogen ratios and other nutrients, with the objective to quantify feedstock effects on 

compost physiochemical characteristics, and on transplant growth in the composts as root media.  

The base recipe for all piles was fresh cut grass and fall collected municipal leaves with 

variations in additional feedstocks primarily designed to alter the starting carbon to nitrogen 

(C:N) ratio.    The ten recipes were made with replication over a period of three consecutive 

years with a similar schedule for start date, turning, and maintenance.  After a period of six 

months from the time of starting the piles samples were taken for nutrient analysis of total and 

water soluble nutrients, and physical characteristics.  Cucumber, kale, and tomato vegetable 

transplants were grown in media comprised of 100% compost from the different feedstocks and a 

commercial transplant medium for comparison.  Transplants were also grown in 100% compost 

from all 3 years simultaneously when the different recipes for feedstocks were of varying ages 

(nearly 2, 3 or 4 years old), and basil was grown in the compost to full maturity for harvest.  

There were distinct differences between composts for many of the physiochemical characteristics 

analyzed, including N, P, K, Ca, Mg, S, Na, Zn, Mn, Cu and B (soluble and total nutrients), EC, 

pH, bulk density, organic matter content and final C:N.  There were differences in transplant 

growth based on compost feedstocks, and also compost age for certain compost recipes but not 

others.  Compared as a proportion of the peat-based control medium, the cucumber, kale and 

tomato transplants had higher above ground biomass and other transplant metrics in all but one 

treatment (which was high in starting and final C:N), displaying similar treatment responses 

regardless of species.  Basil plants were chlorotic in many treatments, though grew in all despite 

alkaline pH, above 8 for most treatments.  While the compost recipes used in this study produced 

 

7 

a compost media that could be used for transplant and containerized production, blending of 

different composts or other medium components to optimize characteristics and enhance growth 

of plants is seen as a next step in development of compost media.    

 
 

INTRODUCTION 

Composting is a managed aerobic process of the biological conversion of organic matter 

into compost, the biodegradation and conversion being mediated by the resident microbial 

community (Stoffella & Kahn, 2001).  Compost is the final product of the composting process; it 

is a humus-rich stable substrate that is free of pathogens (plant and human) and viable seeds.  

Composting has been employed by farmers for centuries, with compost being used to increase 

soil organic matter and nutrients, soil water holding capacity and nutrient retention. With an 

increasing emphasis on organics recycling in the United States, it is important that composting 

make the shift from a waste management strategy to a resource management strategy necessary 

for the sustainability of farming systems, creating a circular economy in which nutrients flow 

back to the land (Peng & Pivato, 2019).  Refinement of the process can result in higher value 

compost products for specific end uses.     

Compost use in root media cultivation of transplants or containerized plant production, 

either at 100% or as a component, provides a regenerative/sustainable system.  Development of 

affordable compost-based transplant media using feedstocks that are readily available and would 

be generally consistent throughout the United States could increase the adoption of compost 

based media and reduce use of fertilizers.  The high water holding capacity and low bulk density 

of compost are generally suitable for such use (Walker et al., 2006).  These are some of the 

positive attributes of peat moss that have made it the prominent media component in the 

 

8 

horticultural industry (Raviv, 2011).  Specific pH, soluble salt, and nutrient balance 

recommendations are needed to improve the probability of success when using compost for 

transplants or as a substrate (Sterrett, 2001; Sullivan & Miller, 2001).  Substrate components for 

growing plants in containers must be standardized, reproducible, available, and economical 

(Pelaez-Samaniego et al., 2017), and the inability to necessarily check all of these boxes has 

hampered the adoption of compost as a substrate.  Transplant/container culture involves a 

restricted root zone, in which sufficient water, nutrients and aeration for the growing transplant 

must be provided (Raviv, 2011).   

Organic agriculture is expanding and with it the demand for root media that are approved 

for use in an organic system.  Fertilization regimen in organic agriculture is limited in options 

from natural sources such as fish emulsion, feather, bone or blood meal, and producers are often 

weighing the benefits against the high costs and environmental footprint of these choices (Clark 

& Cavigelli, 2005; Kuepper & Everett, 2004).  For organic vegetable farmers the general 

recommendation has been to invest in a uniform, high quality transplant growing medium, which 

are most often peat-based, and may or may not include compost, as well as using these limited 

fertilizer options.   

Peat-based root media may be the most commonly used in horticulture, however, there is 

growing demand for an alternative.  The positive physical characteristics of peat that make it an 

ideal media component have been difficult to match.  However, peat harvest may result in 

environmental degradation, the regeneration time is long, and increasing production and 

transportation costs make it increasingly expensive (Clark & Cavigelli, 2005; Lazcano et al., 

2009; Pelaez-Samaniego et al., 2017; Ridout & Tripepi, 2011; Treadwell et al., 2007).  Still, 

 

9 

most container substrates on the market have peat in the range of 80% and upwards (Ceglie et 

al., 2015).   

Compost, whether thermophilic or vermicompost, provides soluble and long term 

nutrients, water holding capacity, and carbon sources for microbes.  Composts with high total 

porosity and air-filled porosity are more likely to be used as a transplant media (Raviv, 2005).  

However, compost variability can be a concern (Beozzi et al., 2017; Michael Raviv, 2011), 

making more careful management of transplants necessary (Burnett et al., 2016).  Concerns with 

compost have been salinity levels, bad physical characteristics such as high of bulk density, 

phytotoxicity, high pH and heavy metals (Beozzi et al., 2017; Ceglie et al., 2015; Rogers, 2017).  

For widespread adoption on a larger scale, growers would need assurances that a compost can 

reliably provide a uniform, stable, and readily available product (Susan B. Sterrett, 2001).  There 

have been numerous studies with compost used in root media.  Many have used compost as a 

component and not at 100%, often using volume percentages to arrive at the “optimal” or cut-off 

at which the negatives outweigh the positives of its inclusion in media.  The goal herein is to 

remove these negatives by investigating compost component characteristics and how those 

compost characteristics affect transplants.  Understanding these shifts by compost component, 

ingredients can then be combined in such a way as to make compost that is based on necessary 

root media characteristics. 

Transplant use provides a number of benefits for vegetable farmers.  By avoiding 

emergence problems encountered with direct seeding, transplants ensure uniform plant 

establishment and dense plant populations (Burnett et al., 2016; Sterrett, 2001).  Keeping young 

plants in one easy to monitor and manage protected location helps with protection from diseases 

and pests until field planting, at which time they should be better able to withstand such 

 

10 

pressures.  This in turn helps with improved ground cover (weed) management.  Use of 

transplants can better ensure predictable harvest times as well.  They shorten the production 

cycle, providing more time for cover crops to improve soil quality.  Nearly every organic 

vegetable farm, regardless of size, uses transplants, but because organic transplants are difficult 

to source, farmers often produce their own, with inherent difficulties.  The qualities of the root 

media generally have long-lasting ramifications on yield (Dufault, 1998; Jack et al., 2011; Raviv 

et al., 1998).   

There are many factors in the production of compost to make it suitable for use as a 

transplant media that can be managed to affect the process and the end product.  For example, 

variations in feedstock (Campitelli & Ceppi, 2008), mixing frequency (Tiquia et al., 2002) and 

storage time (Fracchia et al., 2006) can impact the chemical, biological and physical 

characteristics.  EC increases as composts mature, while conversely pH and carbon to nitrogen 

ratios decrease (Campitelli & Ceppi, 2008; Tognetti et al., 2005).  The relationship between 

nitrate-Nitrogen (NO3-N) and ammoniacal-N (NH4-N) also shifts as NO3 increases and NH4 

decreases with compost maturity (Goyal et al., 2005).  These parameters have cascading 

ramification for the end use of the compost as a microbial inoculant, a source of stable organic 

matter, a supplemental source of fertility, or a sole or substantial component of planting media 

(Waqas et al., 2018).  Additional management factors that influence the process and finished 

product range from the initial feedstocks, feedstock relative ratios and starting particle size, 

temperature, moisture, turning or physical mixing, maturation and curing phases, etc.   Storage 

time and conditions are yet other factors of compost management process quality.  It is important 

that compost be stored under conditions that will maintain both the nutrients present and the 

biota (Fracchia et al., 2006).  Moisture content is of particular concern; if compost is not 

 

11 

protected from rainfall, leaching of nutrients may occur, and/or compost may become 

waterlogged and anaerobic, while excessive drying is also a concern more in relation to the 

active biota present.  

A target carbon to nitrogen ratio (C:N) of approximately 25:1 to 35:1 for mixed feedstock 

materials is desirable (Day & Shaw, 2001).  Low starting C:N (<20:1) can result in N losses 

through ammonia volatilization (Tiquia et al., 2002) which is detected by human smell and 

deleterious to human health at low concentrations (<5ppm), and high starting C:N (>60:1) will 

impede decomposition.  Calculations of mixtures can be made with the %C and %N of each 

feedstock and their relative proportions/weight of the compost recipe.  Examples of carbon 

sources (C:N>30:1) for feedstocks include straw, paper, woodchips, sawdust and bark.  Nitrogen 

sources (C:N<30:1) may include animal manures, sewage sludge, or municipal solid waste 

(MSW) (Neher et al., 2013).  Materials with lower C:N are often higher in other nutrients as 

well.  As the C:N affects the composting process and nutrient content going into a compost pile, 

the resultant compost should display distinct characteristics.   

A primary consideration in treatment selection was alteration of carbon to nitrogen ratios 

(C:N) and the effect this would have on the finished compost characteristics, though additional 

considerations of alteration of pH, better retention of nutrients and moisture, and addition of 

other nutrients from the specific feedstocks were also considered.  Composts can be highly 

variable, but a better understanding of how feedstocks influence compost parameters could 

improve their use in transplant production.  An emphasis was also on local resources that are 

often considered wastes, which would be used in a composting system, such as spent coffee 

grounds (SCG), manure (combination of dairy cow and horse), pine wood shavings, sphagnum 

peat moss, and shredded office paper.  The higher C:N feedstocks and SCG in particular are 

 

12 

more recalcitrant and the effect on the finished C:N ratio is not well understood (Stylianou et al., 

2018).  A motivating question is what makes a good compost for transplants, and if these 

characteristics will be the same for various plant species.  Ultimately, different composts could 

be made and blended depending on the desired characteristics for the specific end use.    

Electrical conductivity is commonly used as a quick test for nutrient content or soluble 

salts of peat and bark-based root media for containers (Nelson, 2011).  A recommended range of 

test values for acceptable plant growth is 1.0 to 3.0 dS/m for root media saturated media extract 

analysis for peat-based media (Warncke & Krauskopf, 1983).  Recommended EC ranges for 

compost-based media are based on peat-based media values and not actual research trials 

measuring plant growth in compost.  Another factor complicating the reliability of EC readings 

for organic fertilizers is the presence of non-fertilizer salts (Na, Cl, etc.) that increase EC without 

increasing nutrient concentration and fertility.  Furthermore, nutrients bound in organic material 

do not affect EC.  Organic anions may also contribute to the measured electrical conductivity 

values.  Research is needed to differentiate compost from other root media for such diagnostic 

tests as EC may be a key in compost use as media for growing transplants. 

The soluble fraction of nutrients is what will be most readily available to plants as a 

nutrient source (Sullivan & Miller, 2001).   Nitrogen content of compost can vary greatly and is 

particularly dependent on the parent feedstocks.  Ranges are typically between 0.5-3% total N.  

Saturated media extract (SME) quantifies inorganic N, which is either in the nitrate (NO3-N) 

form or ammonium (NH4-N) form, which in part can help in the evaluation of compost maturity 

as NH4-N values are generally low in mature compost; if values are high it is an indication a 

compost is not yet mature.  The immediate or first-year nitrogen availability effect of an 

application of compost is generally estimated at less than 15% of the total N; the remainder will 

 

13 

become more slowly available over subsequent years, at a rate of about 2-8% per year (Amlinger 

et al., 2003).  Thus there is a lingering, cumulative slow-release N availability effect of a 

compost application to a field or in container culture.  

The first objective of this study was to characterize the effects of locally available or on-

farm feedstocks with a range of starting C:N ratios.  We hypothesized that the nutrient levels 

(soluble and total) and balance of nutrients (ratios) of the finished compost would be different 

between treatments.  We further hypothesized that there would also be treatment effects on 

finished compost for the pH, EC, bulk density and final C:N.  The second objective was to 

contribute towards the development of affordable compost-based root media for production of 

vegetable transplants or growing plants to full maturity.  We hypothesized that the compost 

media could grow acceptable transplants without modification, and that feedstock treatments 

would result in differences in the transplant morphological features assessed for three species of 

transplants grown (cucumber, kale, and tomato).  Additionally, we hypothesized that compost 

age would affect transplants as compost characteristics change over time, assessed in a separate 

experiment growing cucumber seedlings only.  A third plant growth experiment consisted of 

growing basil to full maturity, with the hypothesis being that there would be differences in 

harvest weights dependent on feedstock treatment. 

The overall objective of this work was not to produce the “best” compost and test it, but 

rather to characterize feedstock benefits to a thermophilic compost system intended for use as a 

plant growing medium.  Proportional effects of these feedstocks could then be 

calculated/estimated to develop a compost root media with the desired characteristics.  

Development of affordable compost-based transplant media using feedstocks that are readily 

 

14 

available and would be generally consistent throughout the United States could increase the 

adoption of compost based media as an alternative for peat based media and use of fertilizers. 

 

MATERIALS AND METHODS 

Compost Treatments and Experimental Design 

Compost was made at the Michigan State University (MSU) Horticulture Teaching and 

Research Center (HTRC) in Holt, MI (42°40” N, 84°28” W).  Experimental treatments consisted 

of ten feedstock combinations (Table 1.1).  The base mix for nine of the ten compost recipes was 

grass freshly cut from organically managed/certified property at the HTRC and municipal leaves 

from the city of East Lansing, MI, at equal parts by volume.  The senesced whole leaves, from 

various tree species, had been collected in the previous fall in large piles that sat over winter, 

covered with plastic tarping most of that time, until use for composting (approximately seven 

months) and were moist from rain.  Volume was measured with 20-gallon black plastic pots, 

compressed by hand to fill space, with grass weighing approximately half as much as leaves of 

equal volume.  Additional feedstocks were added at equal proportions to the grass and leaves of 

the base mix in a 1:1:1 ratio of grass to leaves to other by volume.  The recipe treatments were as 

follows: grass and leaves at 1:1 (‘Base Mix’); base mix plus more leaves (‘More Leaves’); base 

mix plus more grass (‘More Grass’); the base mix wrapped in plastic (‘Wrapped’); base mix plus 

fresh manure, which was comprised of high moisture content dairy manure and low moisture 

content horse manure at 1:1 by volume, both without bedding and mixed thoroughly prior to 

addition to compost piles (‘Manure’); base mix plus used moist SCG (‘SCG); base mix plus 

shredded office paper (‘Paper’); pine wood shavings plus base mix (‘Shavings’); and base mix 

plus sphagnum peat moss (‘Peat’).  A tenth recipe referred to as the ‘Control’ is a recipe 

 

15 

comprised of sphagnum peat moss (3ft3 compressed bale, 53lbs), pine wood shavings (3ft3 

compressed bale, 43lbs), straw (1 standard bale, 30lbs) and hay (2 standard bales, 100lbs) which 

has been a standard compost recipe used for growing organic transplants for over a decade at 

MSU (Jost, 2008).  An additional treatment of the base mix plus food residue (‘Food’) was made 

in year two only and not included for most of the analyses due to the lack of replication, with the 

exception of growing basil to full maturity for harvest.   

Each experimental unit was a static compost pile of approximately a cubic yard at the 

start of composting.  Compost piles were all contained under an open-ended high tunnel for 

protection from rain and wind.  Placement of each treatment was randomized.  Each treatment 

was replicated over time (with approximately the same start date of making the compost piles) 

with one replication in 2013, 2014 and 2015.   

Compost Management and Data Collection 

Composts were made using standard (40”x48”) wooden pallets lined with cardboard 

creating three-sided bays for static piles to allow for approximate size of a cubic yard per piles.  

The feedstock components were layered on the pile by 20 gallon increments (approximately 4” 

layers) and roughly combined by pitchfork to ensure sufficient interaction of all components to 

gain proper heating and create a relatively homogeneous mixture; there were nine total 20-gallon 

layers per pile.  The size of ‘Control Recipe’ treatment was larger at approximately 1.5yd3 with 

five feedstocks divided into four layers for twenty total layers.  The feedstocks of peat, paper, 

shavings, and both hay and straw from the ‘Control’ that were very low in moisture were all 

soaked in water and gravitational water drained, then added to their respective compost piles.  

Other feedstocks were considered to be of adequate moisture, and additional water was added to 

 

16 

piles by a hose with a breaker, approximately one gallon per 12” height of pile.  This was 

intended to achieve desired initial moisture content of the pile of approximately 40-60%.   

The 10 compost piles were maintained under a moveable (sled) open-ended high tunnel 

for rain exclusion.  The experiment was arranged in a randomized complete block design 

(RCBD) with the location of treatments within the tunnel being randomized every year.  Piles 

were turned manually with a pitchfork when internal temperatures fell below 130°F (four times).  

Piles were removed out of the bay to combine and then returned by stacking while adding 

moisture by a hose breaker as needed to adjust moisture (approximately 3 gallons per compost 

pile) and ensuring all material that was on the outside was put into the middle.  Piles were turned 

simultaneously, a total of two times, when average internal temperatures fell below 130°F.  The 

first turn was around day nine, and the second turn 13 days later (approximate, turning schedule 

varied by year depending on compost temperatures). 

During the composting process daily temperatures of all compost piles were recorded.  

Piles were allowed to mature and when composts were approximately six months old composite 

samples of one-gallon volume from ten areas within the freshly turned compost pile were taken 

for laboratory analysis of chemical and physical properties.  Key responses measured from 

mature compost samples were for nutrients including water soluble nutrients using saturated 

media extract (ppm nitrate-N, ammonium-N, P, K, Ca, Mg, Na, Cl), and total nutrients (% N, P, 

K, Ca, Mg, S, Na; ppm Zn, Mn, Fe, Cu, B, Al) and chemical characteristics of electrical 

conductivity (EC), pH, organic matter (%) and physical characteristics of bulk density and 

moisture (%).  Calculations for the percent carbon and the carbon to nitrogen ratio were obtained 

from the data and the percent of each nutrient contribution to the electrical conductivity was also 

calculated using the equation  

 

17 

[1]  % Element  = ((ppm element) / (EC mg/L * 700)) * 100 (Warncke & Krauskopf, 1983). 

At the time compost analysis was done (December of each respective year) the remainder 

of the compost was put into lined crates and moved to a heated head house at MSU HTRC 

maintained at approximately 65°F.  Moisture was checked and water added by mister nozzle to 

surface to maintain a minimum moisture content of approximately 40%.  Compost media were 

maintained this way until being used for transplant production the summer following when it was 

made.  After this time each compost was stored in multiple 5-gallon buckets in an unheated barn 

with lids fastened to all buckets with holes drilled for maintenance of aerobic conditions but 

decrease moisture loss during storage.  At the start of 2017 these were moved again to the same 

heated head house prior to being used to grow cucumber transplants in the compost treatments of 

different ages.   Compost buckets were thoroughly mixed and samples from all three replications 

of each treatment (30 in total) were tested again by saturated media extract for soluble nutrients, 

with each replication being of a different age at the time of analysis.  Ages of composts at this 

time were approximately 2, 3 and 4 years old. 

Plant Experimental Design, Management and Data Collection 

Experiment 1  Effect of compost type on tomatoes, kale and cucumbers.  Finished 

composts (Table 1.1) were used as planting media for organic vegetable transplant production.  

An additional treatment of Sunshine Potting Mix (Sun Gro Horticulture) was used as a control 

substrate, which is approved in organic production systems.  Transplants were grown in 

July/August of 2014, 2015 and 2016 at the MSU Research Greenhouses, with each compost-

based media treatment having been made the previous year (compost aged 1 year).  Three 

species of transplants were grown: tomato cv. Amish Paste (Solanum lycopersicum), kale cv. 

Red Russian (Brassica oleracea var. sabellica), and cucumber cv. Marketmore 76 (Cucumis 

 

18 

sativus).  An experimental unit comprised one 4-cell pack from a 48-cell flat, with four 

replications of each treatment for each of the three plant species.  Design was a randomized 

complete block design (RCBD), each block being arranged on a single greenhouse bench.   

Composts were filled into cells with settling and seeded, planting 2 seeds per cell and 

obtaining emergence data after approximately 1 week (number of seeds germinated out of eight 

possible).  Cells were then thinned to one plant per cell by shoot removal.  Supplemental lighting 

was supplied with three overhead 400W HPS lamps suspended 4’ above a 3’x18’ bench for a 16-

hour photoperiod.  Air temperature was maintained at a minimum heating setpoint of 65°F with 

ventilation at 75°F.  Transplants were watered daily by overhead watering and no supplemental 

fertilizer was added.   

Transplant data was taken at the stage at which each transplant would have been put into 

the field at a transplantable size.  The data collected to assess quality of transplants were above 

ground biomass (both wet and dry weights), root rating (categorical variable 0-5 of qualitative 

rating), average plant height (cm), and number of true leaves.  Cucumber transplants were 

assessed at three weeks, kale at four weeks, and tomatoes at five weeks.  The observational unit 

was all four plants from each experimental unit (4-cell pack).  Plant height was a visual average 

of all plants, while for the other measurements the total number of plants was taken into account 

if less than four and the data was divided by the total number of plants present.  For analysis the 

per plant average were the data used.   

Experiment 2. Effect of compost type and age on cucumber transplants.   Transplants 

were also grown in composts from all 3 years simultaneously when the different treatments for 

feedstocks were of varying ages (nearly 2, 3 or 4 years old) in March of 2017.  In this trial 

cucumber cv. Marketmore 76 (Cucumis sativus) was the only species grown.  The number of 

 

19 

plants in each experimental unit was increased, using one quarter of a 48 cell flat for a total of 

12.  This was again a RCBD arranged in the same manner as the other transplants, but with only 

three replications per treatment and 30 treatments total (3 different ages of the compost 

treatments with the exception of ‘SCG’ at only 2 and 3 years old, and a peat-based control 

media).   

Transplant management and environmental conditions were the same as in Experiment 1.  

Data collection for emergence at one week and plant growth characteristics at 3 weeks was also 

consistent with procedures for Experiment 1, with the exception that data was obtained for eight 

plants instead of four since the experimental unit size had been increased.  Data reflect per plant 

averages within each replication. 

Experiment 3.  Effects of compost type on basil.  Additionally, composts that were made 

in 2014 were used in the summer of 2015 to grow basil cv. Genovese (Ocimum basilicum).  One 

experimental unit was a bulb crate (dimensions 12”x24” x 6” deep), lined with landscape fabric 

and filled with a compost treatment.  In each bulb crate four basil plants were transplanted, 

having been started in the same commercial media three weeks prior.  There were six 

replications of each compost media treatment arranged in a RCBD, blocks being situated on 

individual growing benches.  These were in an unheated hoophouse with no supplemental 

lighting, grown from July through September. 

Basil was grown to full maturity and multiple harvests of top growth collected.  Fresh 

weight of each harvest was recorded on a total of four dates from July to September 2015.  The 

new pH of media samples collected from the root zone within a week after basil were planted 

into bulb crates was measured using a 1:2 dilution with deionized water and pH probe (IQ 150pH 

Meter with ISFET Probe).  Recently matured leaf tissue was analyzed for 4 replicates of two of 

 

20 

the treatments: the ‘Control Compost’ in which the basil was particularly green and healthy 

looking, and the ‘Food’ waste compost in which the basil was chlorotic. 

Statistical Analysis 

Initial chemical and physical properties of the media were analyzed for treatment 

significance by analysis of variance (ANOVA).  Significant differences between means of 

treatments were determined by pairwise comparison using Tukey’s Honestly Significant 

Difference (HSD) test (P≤0.05).  For additional testing of specific hypotheses, Welch’s two 

sample t-test was used to evaluate the differences between specific groupings of treatments 

which were as follows: High Starting C:N which included treatments ‘Paper,’ ‘Shavings,’ and 

‘Peat,’ and Low Starting C:N which included treatments ‘More Grass,’ ‘SCG,’ and ‘Manure.’   

Differences between the two groups was performed to analyze starting C:N on the dependent 

variable of final C:N, total %N, and soluble NO3-N (ppm) of finished compost.   

Principal component analysis (PCA) was conducted on the standardized compost 

physical and chemical characteristics data.  PCA is a standard tool for data compression and used 

to capture the main features and extract information from multivariate, high-dimensional data 

sets.  With the large number of dependent variables, PCA is descriptive technique used to 

explore and visualize the data and differences between treatments.  The PCA was run for 27 

different variables- the soluble and total nutrients, EC, pH, percent organic matter, carbon to 

nitrogen ratio (C:N), bulk density and moisture.  While % soluble salts were calculated from the 

ppm of each nutrient and the EC (Equation 1), these numbers were not included in the PCA 

analysis because this data was already captured by the ppm of each nutrient.  Visual 

representation of the PCA was made by creating bi-plots of the first and second PCs, looking at 

 

21 

treatments individually and by the groupings described above for starting C:N.  Loading 

contribution of compost characteristics to PC1 and PC2 were used for interpretation of the PCA. 

For transplant performance (Experiments 1 and 2) the plant metric data of dry and wet 

weights, plant height, number of leaves, and root rating were analyzed for treatment significance 

by ANOVA.  Species growth data for cucumber, kale and tomato grown in the one-year-old 

composts was also combined, using a 2-factor ANOVA with plant species (3 levels) and 

compost treatment (10 levels) as factors.  Significant differences between treatment means were 

determined by pairwise comparison and separated according to Tukey’s HSD test (P≤0.05). 

An ANOVA was performed for the basil harvest data grown in the year two compost 

only (Experiment 3).  Significant differences between treatment means were determined by 

pairwise comparison and separated according to Tukey’s HSD test (P≤0.05).  The pH data 

collected from the media was used to complete linear regression analysis establishing if there 

was a relationship between basil harvest data and pH.  For the leaf tissue analysis from the two 

treatments ‘Control’ and ‘Food,’ nutrient values were also subject to ANOVA.   

Data analysis was carried out using R statistical software package, and additional 

packages for R including multcomp (glht function) for pairwise comparisons and ggbiplot for 

visualization of PCA (R Core Team, 2019).  Unless otherwise noted, statistical significance is 

determined at a<0.05.  Data were assessed to ensure that ANOVA assumptions were not violated 

and were log transformed when needed prior to analysis.  Sattherthwaite’s degrees of freedom 

was employed to account for potential nonequal variance in the data.  All data presented in 

figures and tables are non-transformed.  

 

 

 

22 

RESULTS 

Composting Temperature 

 

Temperatures curves for the compost pile were not consistent year to year, and timing of 

turning the piles varied slightly so it was not possible to combine the temperature data for 

statistical analysis (data not shown).  The piles in 2013 did not heat as much or for as long as 

piles in the other two years.  Various environmental factors may have come into play, as well as 

maintenance of moisture, etc.  There were, however, some trends that were consistent regarding 

temperature of piles by treatment.  Peat in particular had the lowest temperatures, and only in 

2015 did it go above 130°F at all which was only for a period of four days.   

Compost Physio-chemical Characteristics  

Physical data:  Bulk density of ‘Manure’ at 0.36 g/cc was higher than all other treatments 

except ‘SCG’ and ‘Paper,’ while ‘Shavings’ and ‘Control Compost’ had values at 0.15 and 0.14 

g/cc, respectively, equivalent only to ‘Peat’ (Table 1.2).   Percent moisture ranged from 60% 

(‘More Leaves’) to 73% (‘Wrapped’) with no significant differences between treatments (data 

not shown).  

EC and pH:  ‘Manure’ had the highest EC values at 10.6 ds/m, while the range of values 

for the remaining treatments was from 6.7 (‘More Grass’) to 1.3 (‘Peat’).  The range of pH 

values for all composts that did not contain peat as a feedstock was between 7.7 and 8.8 (Table 

1.3).  The ‘Control’ compost in contrast had a mean pH of 6.3 (~20% peat) and ‘Peat’ compost 

5.7 (~33% peat).    

Soluble nutrients:  The results of the saturated media extract (SME) for soluble nutrients 

displayed differences between treatments for NO3-N (range of 1 - 734ppm), NH4-N (0.6 - 

47ppm), P (6 - 118ppm), K (218 - 2241ppm), Ca (115 - 880ppm), Mg (42 - 199ppm) and Na (25 

 

23 

- 377ppm, Table 1.3).  Soluble Cl (103 - 1210 ppm) was the only one of the soluble nutrients 

with no differences between treatments.  

The ‘Base Mix’ compost NO3-N concentration was within a mid-range of all the 

composts at 250ppm and only significantly lower than ‘Manure’ compost with a mean value of 

734ppm, higher than all the other treatments.  ‘SCG’ had the second lowest value for NO3-N of 

4.5ppm (‘Shavings’ with 1ppm), while also having the highest NH4-N concentration of 47ppm, 

over 700% higher than the treatment with the next highest mean NH4 value of 5.6 (‘Shavings’).  

P levels for ‘SCG’ were higher than all treatments other than ‘Control’ compost with a mean 

value of 118ppm. 

 ‘Manure’ compost also had highest values K (2241ppm), and Na (337ppm) when 

compared to the other treatments.  All nutrient values for ‘Manure’ have a many fold increase as 

compared to the published acceptable ranges for these nutrients in peat-based media (given in 

Table 1.3), with the exception of Ca and Mg for which the recommendation is a minimum 

concentration only. 

For the nutrient balance of soluble nutrients (the degree of contribution to the electrical 

conductivity) no differences between treatments for Na, Cl, Ca and Mg were observed (data not 

shown; calculated by dividing elemental ppm by (EC * 700).   

Total nutrients:  For total nutrients analyzed, of the 13 nutrients 11 displayed significant 

differences between treatments and are presented in Table 1.4.  The ‘SCG’ compost at 3.69% 

total N was greater than all other composts except ‘More Grass’ at 2.55%.  ‘Peat’ compost N 

concentration of 1.34% was lower or equivalent to all other treatments.  Phosphorus values 

ranged between 0.09% (Peat) to 0.52% for Manure which was higher than all other treatments.  

The K concentration ranged from 0.44 to 1.63%.  The ‘Manure’ treatment had values higher or 

 

24 

equivalent to other treatments for nearly all nutrients, of note Mg at 0.95%, Zn at 154%, Mn at 

297%, Cu at 51%, and Na at 0.20%.  ‘Paper’ treatment had the highest % Ca at 8.82%, the range 

of other treatments being from 1.25 to 4.05%.  The higher total Ca did not result in higher 

SME/soluble Ca relative to the other treatments (Table 1.3).  The nutrients with no differences 

between treatments were total Al (263 – 2621 ppm) and Fe (1725 - 3893 ppm, data not shown).   

Nitrogen concentration displayed differences dependent on starting C:N of the compost 

feedstocks.  Final C:N was nearly twice as high in the high starting C:N group with 23.6 versus 

C:N of 12.6 for the low C:N group.  Total N (%) was 1.7 versus 2.8, and soluble NO3-N (ppm) 

was 137 versus 444 for the high versus low C:N starting groups, respectively (significance at 

p<0.001, p=0.001, and p=0.037, respectively). 

The wrapped Mix did not have any odors that would signify anaerobic or putrid 

conditions that would warrant concerns of composters.  While the percent moisture of finished 

compost was not different, the wrapped compost moisture throughout the composting process 

maintained without additions while water had to be added to all other treatments when piles were 

turned (twice).   

Principal Component Analysis: The distribution of the composts in the biplot defined by 

the two PCs resulted in the separation of some of the compost treatments, “SCG”, “Peat”, 

“Manure” and “Control” composts in particular while the other treatments displayed much more 

overlap (Figure 1.1A).  When the treatments were grouped by starting C:N, the differences in 

distribution of these groups in the bi-dimensional space is even more apparent (Figure 1.1B).  

The first and second principal components accounted for 63% of the systems total variability of 

the physiochemical compost variables.  The loadings or correlations between the PC axes and the 

original data are displayed in Figure 1.2.  The first PC which captured 47.1% of the variance is 

 

25 

dominated by EC and soluble nutrients (K, Mg, NO3-N, Na, Cl, Ca) and by C:N, and organic 

matter content in the opposite direction.  This would indicate a potential inverse relationship 

between higher carbon content and soluble nutrient concentrations.  The second PC is dominated 

by total N, P, K, S, moisture, organic matter, and in the opposite (positive) direction by C:N.   

Comparison of Plant Performance 

Experiment 1.  Mean emergence across all species ranged from 71% to 98% depending 

on compost treatment (Table 1.5).  By species, cucumber emergence ranged from 83% in ‘More 

Leaves’ to 98% in ‘Wrapped’ compost; kale exhibited the smallest range of emergence by 

treatment, from 81%  in the ‘SCG’ compost to 91% in the ‘Control’ compost; tomato emergence 

rates ranged from 71% in the ‘Manure’ compost to 92% in the ‘Control media’.   

Data for all transplant characteristic is displayed in Table 1.6.  There were significant 

differences between treatments for all species and all plant growth characteristics (p<0.001 for 

all but plant height for cucumber, for which p=0.009).  For kale and tomato there was high 

correlation between these growth metrics (0.62 - 0.95); however, for cucumber all metrics were 

highly correlated (0.65 - 0.79) except for root rating (correlation of 0.11 - 0.29).  A dominant 

trend in the data was “Shavings” compost consistently having the lowest values for all growth 

parameters, regardless of plant species.  While there were no differences between “Shavings” 

and the control media for any of the metrics for cucumber, for root rating, height and leaves for 

kale and tomato “Shavings” and the control were significantly different.   

The model predicting performance of transplants dry weight as a function of compost 

media treatment displayed differences between treatments (Figure 1.1, Cucumber: F=12.5 (10, 102), 

p=<0.001, Kale: F=18.8 (10, 101), p=<0.001, Tomato: F=6.2 (10, 111), p<0.001).  With the exception 

of the ‘Shavings’ treatment (and ‘SCG’ treatment for Kale), relative to the growth in the control 

 

26 

medium plants had increased dry weight (127% to 246% more for kale, 40% to 89% more for 

cucumbers, 115% to 301% more for tomatoes).  All compost except “Shavings” produced 

transplants with suitable growth characteristics for transplanting and handling.   

Experiment 2. Transplants grown in the ten compost treatments at different ages 

demonstrated a distinct effect of compost age/maturity on transplant performance.  There was a 

significant effect of compost that interacted with year (F=12.8 (8, 52), p<0.001). For four of the 

compost treatments the interaction of compost and year was found to be highly significant 

(p<0.05).  This was most pronounced for ‘Shavings’ and ‘Peat’ where the youngest compost 

(2yo) resulted in less growth (‘Shavings’) or more growth (‘Peat’) for wet/dry weight and plant 

height than the same compost at either 3 or 4 years old.  For the ‘Wrapped’ treatment, the oldest 

compost at 4yo had dry/wet weight values of less than half the transplants from the two younger 

composts (p<0.001).  In the case of the ‘Control’ compost, differences were observed in the 2yo 

versus 4yo compost for shoot dry weight (p<0.05), however neither of these were significantly 

different than the three -year-old compost, making it hard to establish any kind of a trend.  The 

‘SCG’ treatment increased plant growth with age (by 55% in dry weight, 22% for root rating) 

from two versus three years old.   

Experiment 3. For basil grown to full maturity in bulb crates filled with one cubic foot 

100% compost substrate, there was a large range in the average cumulative harvest with 

differences between treatments (Table 1.9, F=66.0 (9, 45), p<0.001).  Cumulative harvest weight 

was lowest for ‘Shavings’ (38g), while the treatment with the next cumulative basil weight was 

the ‘Wrapped’ compost at 134g, which was equivalent to five of other treatments.  The ‘Control’ 

compost had the highest harvest weight (418g) followed by the ‘Peat’ compost at 351g.  

 

27 

Plant tissue analysis for total nutrient content in leaf tissue between the ‘Control’ and 

‘Food’ composts revealed differences in N, P, K, S, B, Zn, Cu and Na (Table 1.10).  The 

nutrients that were not different were Mg, Ca, Mn, Fe and Al.  These two treatments were 

selected for nutrient analysis based upon their difference in appearance with the ‘Food’ treatment 

displaying signs of chlorosis and low harvest weights and the ‘Control’ looking particularly 

green with high harvest weights.   

   

The relationship between the harvest weights and compost media pH was negative 

(Figure 1.4, p<0.001, R2=0.50), further validating the hypothesis of the impact of compost media 

pH on plant growth. 

 

DISCUSSION 

The experiments completed and data collected provide a foundation to consider first the 

impacts of feedstocks on physiochemical properties, and second the impacts of resulting 

physiochemical properties on transplant growth. 

Feedstock and Physio-chemical differences:  ‘SCG’ and ‘Manure’ were hypothesized to 

have higher nutrient levels for multiple nutrients.  This trend is observed in some nutrients but 

not all.  

When compared against the same recipe that was not wrapped (‘Base Mix’) the mean 

values for all nutrients were not different in the ‘Wrapped’ treatment, contradicting our 

hypothesis that ‘Wrapped’ would have had greater nutrient retention.  The hypothesis that 

‘Wrapped’ would also have greater water holding capacity was not supported in the moisture 

content as there were no detectible differences between treatments.  

The pH of composts generally is within the range of 6.0 to 8.0, dependent on feedstocks, 

the composting process and any additional amendments (Sullivan & Miller, 2001).  The only two 

 

28 

compost treatments to have an acidic pH after 6 mos. were the mix with peat (~33% by volume) 

and the control compost recipe that also included peat (~20% by volume).  In general the pH 

values were higher than were expected for finished compost with many treatments remaining at 

alkaline pH (‘Base Mix,’ ‘Wrapped,’ ‘More Leaves,’ ‘Paper’ and ‘Shavings’ all above pH 8.0; 

Table 1.3) and indicate that the composts were not yet fully mature at the time of sampling.  In 

contrast, ammonia levels had decreased to < 5 ppm while nitrate levels had increased, indicating 

compost maturity.  Transplants were grown in the compost media nearly 10 months after these 

data were collected, and pH values would be likely to have dropped (SME of aged compost 

samples displayed a substantial drop in pH, Table 1.8).  The pH values of media impact the 

solubility/availability of nutrients, and so while nutrients may be present in sufficient quantities, 

plants may still display deficiencies.  Nutrient availability in relation to peat-based media pH is 

dependent on the nutrient, with P being particularly sensitive to pH.  In the absence of mineral 

soil (clay, silt, sand) and therefore reduced Al and Fe, P availability increases in peat-based 

media more than in field soil with declining pH.  This relationship needs to be characterized for 

compost-based media that may or may not contain mineral soil. 

Maturity of compost affects the pH, primarily through the process of mineralization and 

nitrification.  Immature compost may test at 8.0 to 8.5, prior to the initiation of ammonification 

and bacterial nitrification.  Decreasing pH with increasing NO3 concentration is common during 

compost maturation as protons are released during the nitrification process (Cooperband et al., 

2003).  The compost samples being analyzed only at one point in this study did not allow us to 

assess our findings in relation to this trend, however.  At early stages (6 mos.) ‘SCG’ compost  

maturation indices appear to be anomalous in regards to progression of nitrification with NO3-N 

levels still near zero and NH4-N levels nearly 50x higher than the other treatments (Table 1.3).  

 

29 

However, in years 2 and 3 of maturation pH and NH4 levels appear to drop, while NO3 increased 

(though this is unreplicated data, Table 1.8).  This would suggest a possible inhibition in 

nitrification in less mature composts that changes with additional curing; there could be 

differences in the biota that are driving these observations, and future research that assesses 

biological differences in the compost treatments may help elucidate these processes. 

Experiment 1:  Transplant differences.   

Although many of the composts proved to be adequate for growing transplants at 100%, 

‘Peat’ and ‘Control’ had some of the highest values for the plant metrics, and it is likely that pH 

may have had one of the biggest roles in this.  P is particularly impacted by alkaline versus acidic 

pH with increased availability at slightly acidic pH versus alkaline, and other nutrients to a lesser 

degree also.  Additionally, the pH of the environment will likely impact the biota which drives 

mineralization. 

Acceptable range numbers for soluble nutrient values, pH and EC of root media are listed 

in Table 1.3 (Warnke and Krauskopf, 1983), but these values are based on SME for peat-based 

media.  Nearly all nutrient concentrations in the composts well exceeded the recommended 

ranges often by a factor of two to four but in more extreme cases by a factor of nine.   

The nutrient reserve of compost-based root media is somewhat buffered, having higher 

total nutrient concentrations and biota for mineralization, may have a greater impact when 

production cycle is longer and no supplemental fertilizer is used.  Cucumbers have a shorter 

production phase as compared with other vegetables such as brassicas or solanaceous transplants 

at four to six weeks, or alliums at 10-12 weeks.  Kaya et al. (2016) reported differential 

responses in plant variables between treatments in which high salt content resulted in dry matter 

and chlorophyll reductions that were more pronounced in pepper transplants as compared with 

 

30 

cucumber.  Our results, however, do not appear to display differences in responses between plant 

species in regards to which media have higher or lower EC or salt content (Figure 1.3). 

Transplants grown in peat-based media are typically fertilized with water soluble 

nutrients at each irrigation or weekly, where these acceptable numbers would provide adequate 

fertility.  A goal with compost-based media could be that supplemental water soluble fertilization 

is not needed due to the higher reserve (CEC), and mineralization of nitrogen from the compost 

over time.  It is important to note when making comparisons that the control peat-based medium 

in this study was low in fertility and would typically be fertilized, however, during this study it 

was not.  Although differences between the control medium and compost treatments could be 

overcome by fertilization, there is a monetary cost associated with this, additional labor, and 

environmental cost both from the production or extraction of nutrients, and also the higher 

potential for nutrient pollution by highly soluble nutrients leaching from substrates.  

Experiment 2: Effects of compost age.   

Changes in soluble nutrients, pH and EC over time are displayed in Table 1.8.  While 

there was no replication of the saturated media extracts for each compost by year, some trends 

can be observed, most notably for pH and EC.  While pH values were quite high in the fresher 

compost tested at less than one year from the time of making, in all of the different ages of the 

aged compost only three samples were pH 8 or above (highest was 2yo Shavings at 8.4).  There 

is a trend observed that pH decreased with age though not consistently.  EC and soluble nitrate 

had the opposite trend, with older composts increasing in EC and NO3-N.  While ammonium 

trended downward over time most levels were quite low even in the fresher compost; ‘SCG,’ 

however, was notable in the original data for having high ammonium concentration (47ppm) and 

so had the most drastic decrease with values of the older compost averaging just 0.8 ppm.  While 

 

31 

there are other interesting potential trends, the lack of replication of the soluble nutrients from 

the compost of the different ages limits what is able to be deduced in regards to relationships 

between the interaction of compost and age of compost.  There are also variables that in 

hindsight should have been accounted for, such as compost storage temperature, moisture, and 

aeration.  While the trends of decreasing pH is well documented in compost research, the rate as 

a function of these and other variables is not as researched or well understood. 

The hypothesis that compost age would affect transplants as the compost characteristics 

changed over time was supported for many of the compost treatments.  How these changes in the 

compost as it aged affected transplant health is exemplified most in the treatments ‘Shavings’ 

and ‘Peat’ which had the starkest differences in regard to compost age.  While ‘Peat’ had some 

of the highest plant metrics in Experiment 1 when composts were 1yo, the positives of this 

compost root media changed over time where there was a trend of a decrease in plant height with 

the older composts, and a decrease in shoot dry weight.  The opposite was true for ‘Shavings’ 

which had the smallest transplants with the least developed root systems at 1yo in Experiment 1, 

in the 3 and 4yo composts of Experiment 2 the plant metrics increased significantly over the 

original 1yo compost and also the 2yo compost.  Many of the other treatments, however, did not 

display an effect, or did not have as clear of a trend, of compost age. 

Experiment 3: Basil to full maturity.   

Our hypothesis of differences observed between treatments in basil grown to maturity 

was supported and is related to pH values.  ‘Control’ and ‘Peat’ had the lowest pH values, both 

of them having acidic sphagnum peat moss as compost feedstocks, and the highest and second 

highest harvest weights.  With the high pH values observed in the compost media overall, it was 

expected that many of the treatments at high pH may have displayed chlorosis and other nutrient 

 

32 

deficiency symptoms, which was evident to varying degrees in ‘Food,’ ‘Shavings,’ ‘More 

Leaves,’ ‘More Grass,’ ‘Paper,’ and ‘Wrapped;’ however, the basil still grew in all treatments.     

The selection of the ‘Control’ and the ‘Food’ compost treatments for further evaluation of 

the basil by leaf tissue analysis was based primarily on the visual difference of plant health, with 

the former being dark green and the latter the treatment with the most apparent chlorosis.  The 

mean cumulative harvest weights were also considerably different at 418g and 197g, 

respectively.  There are interactions between many different factors and this would not be due to 

pH alone but there is substantial evidence that pH is a particularly important factor which is 

observed in the inverse linear relationship between pH and harvest weight (Figure 1.4).  Other 

interactions allowing for growth at high pH may be that the biota are able to influence mineral 

availability more than expected at high pH which could be explored in future research. 

The tissue analysis results were surprising in that, of the nutrients where there was a 

difference in the treatments, the ‘Food’ medium had higher values for all except Zn.  This 

contradicted our hypothesis that the media producing healthier looking, greener plants would 

have higher leaf tissue nutrient concentration.  Mg, Fe and Mn are particularly important to 

chlorophyll production and photosynthesis, but were not reduced in leaves with chlorosis.  

Nutrient concentrations in the media were sufficient to supply the plant, but the EC levels may 

have resulted in a high salt stress that could explain the differences observed between the 

treatments.  

The level of K in the leaf tissue from the ‘Food’ treatment at 10.2% would be considered 

at luxury K consumption levels, and was nearly double that of the basil from the ‘Control’ at 5.5. 

The high K in leaf tissue may cause an antagonism of Mg or Mn availability or an “induced 

deficiency,” despite Mg and Mn levels in the leaf tissue being acceptable.  Dzida et al. (2018) 

 

33 

found that as K increased in basil tissue, both Mg and Ca declined, which is inconsistent with our 

results in which there were no differences in Mg and Ca between the treatments despite the large 

difference in K.  This relationship between K and Ca was also observed by Yermiyahu et al. 

(2015), again in basil.  At higher concentrations, K has an antagonistic effect on uptake of other 

cations, especially Mg (Kabu & Toop, 1970; Nurzynska-Wierdak et al., 2012), but if the Mg is 

still at a normal level in the tissue regardless of K concentration, it is possible that there is an 

antagonism or physiologically induced deficiency happening within the leaves.  The 

relationships between the media and nutrient concentration in leaf tissue warrants more 

investigation.   

Of note is the small amount of power in the experiment due to the number of replications 

and the complicating factor of environmental conditions year to year with replication having 

been done over years.  While there are variations in the means between treatments that may at 

first appear to be substantial, when evaluated using either Tukey’s HSD or Welch’s t-test, there 

is no significant difference between some treatments that may have been initially hypothesized.  

If, however, there was greater power through additional replication, significant differences may 

have been resolved. 

 

FUTURE RESEARCH AND CONCLUSIONS 

Future research to build upon the short-term impact on transplants could be a study of 

transplants planted out into the field to assess long-term ramifications of transplant media on 

harvestable yield and disease presence/severity.  In addition, the compost root media could be 

used for growing plants to full maturity in containers and the impact on yield/health in this 

environment.  Container plant culture in protected environments is a subsector of the specialty 

 

34 

crop industry that is rapidly expanding (Rogers, 2017). Looking beyond yield to changes in the 

microbiome of the plant and soil as well, and how that may cascade to disease resistance. 

 

Additional physical characteristics of the compost media may further demonstrate 

differences created by specific feedstocks.  Water holding capacity, easily available water, water 

buffering capacity, total and volatile solids, particle size distribution, and porosity would all 

warrant investigation and relating these characteristics to other existing composting literature. 

The biological differences resulting from adjustment of starting carbon to nitrogen ratio 

were an initial motivating factor for this research when there was an original intention of using 

the composts for compost tea research.  Analysis of biology, especially of fungal versus bacterial 

populations, would add to the body of knowledge about how bacterial/fungal ratios in compost 

may vary.  More recent advances in testing for biology are opening up this area of compost 

research (St. Martin et al., 2020).  If analyzed to the species level, a similar statistical analysis 

using PCA that was used in this experiment for physio-chemical characteristics could be 

employed to assess differences in the biology of different composts.   Fungal to bacterial ratios 

could also be assessed, as it has been found in multiple studies that higher C:N starting 

feedstocks result in an increase in fungal:bacterial ratios (Eiland et al., 2001) but other aspects of 

feedstocks could also be related to this ratio and assessed by the feedstocks chosen herein. 

Adjustment of specific characteristics of media for future research would help to 

elucidate which aspects of the media are playing a larger role in transplant performance, and the 

target levels of these nutrients or other parameters for a 100% compost-based media.  The high 

pH of these composts may have played a larger role affecting transplant health, superseding the 

effect of EC and specific nutrients.  Isolating just the effect pH by its adjustment with elemental 

S at either the start of composting or at the end of thermophilic composting would help to test pH 

 

35 

specifically.  Similarly, Ca adjustments with gypsum or another form of soluble Ca would affect 

the relative ratios of nutrients that also may be playing a large role in transplant health using the 

media.  Adjustment of specific chemical characteristics such as these in conjunction with 

biological data on the composts would further our understanding of these interactions. 

With the differences observed in transplant growth as affected by compost age, there is 

the indication that physiochemical characteristics linked to the degree of maturity are worth 

exploring further.  More research on trends of maturation beyond one year of storage and the 

effects of specific storage conditions could help the composting industry to expand without fear 

of product losing value.  Inoculation of a stable but not-yet-mature compost with mature compost 

could be assessed for changes in microbial diversity and rate of maturation. 

There were many differences observed between treatments both for the physiochemical 

characteristics and performance of transplants in the compost media.  Based on this research, 

compost can be used as a growing media without additional components (at 100%) successfully.  

Differences in the physiochemical properties could be further adjusted or composts of different 

qualities blended to achieve the most desirable transplant characteristics.  For example, a more 

mature compost with high EC and lower pH could be blended with a less mature compost with 

lower EC and higher pH.  Effects of such compost blends warrants further exploration. 

 

 

 

36 

APPENDIX 

 

37 

Purpose 

Base for comparison 

Higher C:N 
Lower C:N 

Nutrient/Moisture retention 
Lower C:N, more nutrients 
Lower C:N, more nutrients 

Higher C:N 
Higher C:N 

Higher C:N, lower pH 

Tested mix for transplant production, 
combining many of same feedstocks 

from other recipes 

Table 1.1. Compost feedstock recipes. 

Compost 

name 

Base Mix  
(Grass and 

Leaves 50:50) 

Additional 
Feedstock  

(33% by volume) 

100% 
67% 
67% 
100% 
67% 
67% 
67% 
67% 
67% 

Base Mix 

More Leaves 
More Grass 
Wrapped 
Manure 
SCG 
Paper 

Shavings 

Peat 

Control 
Recipe 

 

Dry leaves 
Fresh grass 

Manure 
SCG 
Paper 

Shavings 

Peat 

Peat, shavings,  
2x hay, straw 

 

 

 

38 

 
 

 

Compost 

Manure 
SCG 
More Grass 
Wrapped 
Base Mix 
More Leaves 
Paper 
Shavings 
Control Compost 
Peat 

% 
46 (0.8) 
76 (6.5) 
61 (4.2) 
60 (0.9) 
62 (0.6) 
56 (2.9) 
53 (1.8) 
75 (1.3) 
67 (12.2) 
80 (0.7) 

% 
27 (0.5) 
44 (3.8) 
36 (2.5) 
35 (0.5) 
36 (0.3) 
33 (1.7) 
31 (1.1) 
43 (0.7) 
39 (7.1) 
47 (0.4) 

a 
bc 
abc 
abc 
abc 
ab 
ab 
bc 
abc 
c 

 

a 
a 
11.5 (1.2) 
a 
bc 
11.9 (0.8) 
a 
abc  14.2 (1.6) 
a 
abc  15.9 (0.7) 
abc  19.1 (1.5)  ab 
16.1 (0.6) 
ab 
a 
ab 
18.3 (0.2)  ab 
bc 
c 
31.2 (4.4) 
abc  28.8 (4.9)  bc 
c 
c 

34.7 (0.7) 
<0.001 

g cm-3 
0.36 (0.015) 
0.34 (0.015) 
0.28 (0.003) 
0.26 (0.007) 
0.27 (0.012) 
0.28 (0.012) 
0.31 (0.021) 
0.15 (0.003) 
0.14 (0.028) 
0.20 (0.007) 
<0.001 

d 
cd 
c 
bc 
bc 
c 
cd 
a 
a 
ab 

Table 1.2. Compost properties of organic matter and carbon content, carbon to nitrogen ratio 
(C:N) and dry bulk density (mean +/- SE, n=3) by compost treatment. Samples collected for 
analysis approximately six months after the start of the thermophilic composting phase. 

Organic Matter 

Carbon 

C:N 

Dry Bulk Density 

P 

0.001 

0.001 

* means followed by the same letter in the same column are not statistically different (p<0.05) 
according to Tukey’s HSD test 
 
 

 

 

39 

Manure 

SCG 

Wrapped 

Table 1.3. The pH, EC and water soluble nutrient values (mean +/- SE, n=3) from the saturated media extract for compost 
media. Samples collected for analysis approximately six months after the start of the thermophilic composting phase. 
Na 
ppm 
<115 

Acceptable range* 

K 
ppm 

Compost 

EC 

pH 

Base Mix 

More Grass 

P 
ppm 
6-10 

Ca 
Mg 
Cl 
NO3-N  NH4-N 
ppm 
ppm 
ppm 
ppm 
ppm 
150-249 
>200 
>70 
<180 
0-10 
(326)  c  880 
b  377 
(174)  b  199 
b  1210 
a  2241 
(0.3)  a  40 
(487)  a 
(6) 
(3) 
(8) 
(34)  ab  52 
(406)  ab  308 
ab  130 
a  569 
(52)  b  891 
(15)  b  118 
(281)  a 
(8) 
(8) 
(348)  bc  510 
(45)  ab  92 
(202)  ab  138 
(60)  a  647 
(0.7)  a  45 
a  1505 
(215)  a 
(5) 
(120)  ab  122 
(61)  a  709 
(19)  ab  89 
(139)  bc  480 
a  1381 
(0.2)  a  17 
(175)  a 
(3) 
(50)  a  495  
(12)  ab  80  
(0.3)  a  22  
ab  380  
ab  96  
a  965  
(166)  a 
(68) 
(82) 
(4) 
a  31  
ab  89  
(191)  ab  400  
a  1097  
(0.3)  a  14  
a  636  
(231)  a 
(48) 
(2) 
(3) 
(1) 
(30)  a  696  
ab  126  
ab  102  
(152)  ab  520  
(1.0)  a  6  
a  829  
(295)  a 
(1) 
(95) 
(5) 
a  49  
ab  200  
(4.8)  a  30  
(11)  a  482  
a  56  
(32)  a  242  
a 
(70) 
(43) 
(8) 
(35) 
(151)  a  78  
(231)  ab  245  
(13)  ab  801  
a  231  
(36)  a  31  
(0.6)  a  64  
(7) 
(54) 
(10)  a  103  
(12)  a  25  
(0.1)  a  33  
a  218  
a  115  
a  42  
(23) 
(63) 
(30) 
(7) 
0.003  <0.001  0.124 
<0.001  <0.001 
* Acceptable range numbers are for peat-based root media for container grown plants as a reference for use of compost as root 
media. Adopted from Noguera et al., 2003 and Warncke and Krauskopf, 1983 
** means followed by the same letter in the same column are not statistically different (p<0.05) according to Tukey’s HSD test 

5.2-6.3 
dS m-1 
5.2-6.3 
0.75-3.5 
100-199 
7.9 
(0.1)  c**  10.6 
734 
(132)  c  1.8 
(1.1)  d 
a  47 
(0.2)  abc  4.5 
4.5 
7.8 
(0.6)  bc 
(1.5) 
446 
6.7 
7.7 
bc  1.3 
(0.2)  c 
(1.3)  c 
(68) 
ab  0.8 
323 
6.2 
8.3 
(0.1)  c 
(0.2)  c 
(23) 
(0.2)  abc  250  
8.1  
4.2  
ab  0.8  
(0.2)  c 
(9) 
ab  1.0  
5.0  
8.2  
(0.7)  bc  250  
(0.2)  c 
(44) 
a  1.9  
(0.3)  abc  88  
4.2  
8.8  
(0.3)  c 
(64) 
1.8  
8.1  
(0.2)  ab  1  
a  5.6  
(0.4)  c 
(0.9) 
(110)  ab  3.2  
3.2  
6.3  
(1.2)  abc  208  
(0.2)  ab 
32  
1.3  
5.7  
a  0.6  
(0.3)  a 
(0.3)  a 
(18) 
<0.001 
<0.001 

More Leaves 

Shavings 

<0.001 

0.013 

<0.001 

a 

a 

Paper 

Control 

Peat 

P 

 

40 

 
Table 1.4. Nutrient values (mean +/- SE, n=3) from total nutrient analysis of compost media. at 6 months maturity for nutrients with 
significant differences between treatments. Samples collected for analysis approximately six months after the start of the thermophilic 
composting phase. 
N 
% 

Compost 

Manure 

K 
Ca 
P 
Mg 
S 
% 
% 
% 
% 
% 
1.55  
(0.21)  b  4.05  
2.40  
(0.26)  bc*  0.52  
0.95  
(0.11)  b  0.32  
(0.52)  c 
(0.04)  d 
(0.23)  abc  0.59  
(0.03)  ab  2.33  
(0.01)  bc  1.61  
3.69  
0.32  
(0.01)  ab  0.33  
(0.07)  d 
SCG 
1.63  
2.55  
(0.24)  cd  0.33  
(0.44)  b  3.38  
(0.32)  abc  0.58  
More 
(0.06)  ab  0.32  
(0.06)  c 
Grass 
(0.32)  bc  0.61  
(0.23)  b  3.66  
(0.04)  bc  1.51  
(0.13)  abc  0.26  
Wrapped  2.20  
(0.06)  ab  0.27  
(0.28)  bc  0.65  
(0.10)  ab  3.74  
(0.03)  abc  1.01  
(0.13)  abc  0.24  
Base Mix  1.89  
(0.08)  ab  0.25  
2.03  
More 
(0.13)  abc  0.22  
(0.03)  abc  0.98  
(0.21)  ab  3.49  
(0.42)  abc  0.58  
(0.07)  ab  0.22  
Leaves 
0.59  
(0.10)  ab  8.82  
(0.02)  abc  0.69  
1.68  
(0.06)  abc  0.17  
(0.09)  ab  0.21  
(0.92)  d 
Paper 
(0.06)  a  0.18  
(0.45)  abc  0.42  
(0.11)  ab  2.28  
(0.03)  ab  0.73  
(0.22)  ab  0.15  
Shavings  1.45  
0.53  
1.50  
Control 
(0.42)  ab  0.13  
(0.02)  ab  1.12  
(0.25)  ab  1.25  
(0.19)  ab  0.19  
(0.29)  a 
Compost 
(0.03)  a  0.17  
(0.14)  ab  0.37  
(0.05)  a  1.68  
0.44  
1.34  
0.09  
(0.01)  a 
(0.02)  a 
0.028 
<0.001 
0.006 
<0.001 
<0.001 

Mn 
Cu 
B 
Na 
Zn 
% 
% 
% 
% 
% 
297  
(18)  b  51  
(6)  b  50  
(7)  ab  0.197  
(0.01)  bc  154  
(27)  c 
(0.02) 
(6)  ab  0.05  
(6)  ab  47 
(14)  ab  40  
ab  187  
(0.03)  bc  59  
(0.01) 
(3) 
(3)  ab  20  
(2)  a  62 
(11)  b  0.018  
abc  260  
82  
(0.015)  a 
(0.02)  c 
(4) 
(11)  b  0.021  
(1)  a  68 
(22)  ab  18  
(0.3)  abc  233  
(0.02)  abc  75  
(0.008)  a 
(6)  b  0.018  
(2)  a  60 
(31)  ab  19  
abc  273  
(0.02)  abc  80  
(0.007)  a 
(7) 
(19)  ab  18  
(2)  a  62 
(10)  b  0.021  
(0.01)  abc  76  
abc  273  
(0.001)  a 
(7) 
(9)  ab  0.077  
(2)  a  44 
(12)  ab  17  
(40)  bc  202  
(0.00)  abc  140  
(0.001)  b 
(12)  ab  0.021  
(2)  a  39  
(20)  b  14  
65  
ab  301  
(0.001)  a 
(0.02)  a 
(6) 
215  
(0.07)  ab  42  
(69)  ab  26  
(17)  ab  14  
(6)  a  0.027  
(0.004)  a 
(5) 
(3)  ab  0.032  
(2)  a  24  
(12)  a  12  
154  
41  
(0.00)  a 
(0.004)  ab 
(1) 
<0.001 
0.005 
0.007 
0.025 
0.001 

0.001 

c 

ab 

a 

a 

Peat 

P 

* means followed by the same letter in the same column are not statistically different (p<0.05) according to Tukey’s HSD test 
 

 

41 

Table 1.5. Emergence rates for cucumber, kale and tomato transplants in 
the ten compost media and control. Mean % (+/- SE), n=3. 
Compost 
Manure 
SCG 
More Grass 
Wrapped 
Base Mix 
More Leaves 
Paper 
Shavings 
Control Compost 
Peat 
Control Media 
 
 

Cucumber 
84% (6) 
86% (5) 
95% (2) 
98% (1) 
93% (3) 
83% (5) 
97% (1) 
95% (2) 
96% (2) 
91% (4) 
97% (2) 

Tomato 
71% (7) 
79% (6) 
84% (3) 
82% (4) 
82% (4) 
93% (2) 
93% (2) 
87% (3) 
89% (4) 
82% (5) 
92% (2) 

Kale 

85% (4) 
81% (7) 
87% (2) 
81% (6) 
82% (6) 
88% (4) 
87% (4) 
82% (7) 
91% (2) 
86% (7) 
89% (3) 

 

 

42 

Table 1.6. Effect of compost feedstock recipes on plant growth responses of dry weight, wet weight, root rating, plant height and 
number of leaves for cucumber, kale and tomato. Mean values (+/- SE), n=3. 
 

Shoot Wet Weight (g) 

Shoot Dry Weight (g) 

Root Rating (1-5) 

Kale 

Tomato  Cucumber 

Kale 

 

Manure 

SCG 

More Grass 

Wrapped 

Base Mix 

More Leaves 

Paper 

Shavings 

Peat 
Control 
Compost 
Control 
Media 
P 

c 

c 

c* 

Cucumber 
0.34 
(0.03) 
0.37 
(0.03) 
0.34 
(0.02)  bc 
0.35 
(0.01) 
0.31 
(0.03)  bc 
0.42 
(0.02) 
0.35 
(0.03) 
0.12 
(0.01) 
0.40 
(0.02) 
0.36 
(0.03) 
0.22 
(0.01) 

ab 
<0.0001 

a 

c 

c 

c 

c 

0.23 
(0.02)  d 
0.10 
(0.02)  bc 
0.24 
(0.03)  d 
0.26 
(0.03)  de 
0.24 
(0.02)  de 
0.22 
(0.02)  d 
0.22 
(0.02)  cd 
0.20 
(0.01)  a 
0.33 
(0.03)  e 
0.22 
(0.03)  bcd 
0.10 
(0.02)  b 
<0.0001 

0.27 
(0.04)  bc 
0.26 
(0.02)  bc 
0.30 
(0.03)  bc 
0.22 
(0.02)  bc 
0.31 
(0.03)  bc 
0.29 
(0.03)  bc 
0.23 
(0.02)  bc 
0.01 
(0.00)  a 
0.34 
(0.09)  bc 
0.41 
(0.11)  c 
0.10 
(0.01)  ab 
<0.0001 

3.88 
(0.25) 
3.78 
(0.61) 
3.54 
(0.26) 
4.13 
(0.25) 
3.46 
(0.28) 
3.24 
(0.31) 
3.17 
(0.17) 
0.94 
(0.12) 
3.65 
(0.36) 
3.54 
(0.46) 
1.41 
(0.09) 

b 

b 

b 

b 

b 

b 

b 

a 

b 

b 

2.81 
(0.26)  d 
1.41 
(0.20)  bc 
2.31 
(0.21)  cd 
2.90 
(0.28)  d 
2.65 
(0.23)  cd 
2.08 
(0.25)  bcd 
2.44 
(0.23)  cd 
0.27 
(0.05)  a 
2.95 
(0.29)  d 
2.10 
(0.34)  bcd 
0.90 
(0.22)  ab 
<0.0001 

Tomato 

2.39 
(0.24)  c 
2.31 
(0.39)  bc 
2.65 
(0.30)  c 
2.15 
(0.25)  bc 
2.68 
(0.36)  c 
2.31 
(0.24)  bc 
1.98 
(0.23)  bc 
0.17 
(0.02)  a 
2.68 
(0.64)  c 
2.94 
(0.76)  c 
0.56 
(0.08)  ab 
<0.0001 

Cucumber 

3.43 
(0.30)  abc 
3.22 
(0.45)  ab 
4.23 
(0.19)  cde 
3.67 
(0.30)  abcd 
4.56 
(0.13)  e 
4.30 
(0.33)  cde 
4.08 
(0.24)  bcde 
2.97 
(0.15)  a 
4.39 
(0.13)  de 
4.40 
(0.11)  de 
3.69 
(0.17)  abcde 

<0.0001 

Kale 

2.90 
(0.33)  cd 
1.56 
(0.26)  ab 
3.60 
(0.28)  cde 
3.46 
(0.21)  cde 
3.83 
(0.24)  de 
4.03 
(0.24)  e 
4.00 
(0.26)  e 
1.08 
(0.26)  a 
4.02 
(0.28)  e 
3.35 
(0.22)  cde 
2.51 
(0.16)  bc 
<0.0001 

Tomato 

3.21 
(0.38)  bc 
3.47 
(0.24)  bc 
4.19 
(0.15)  c 
3.14 
(0.28)  bc 
4.09 
(0.25)  c 
3.56 
(0.16)  bc 
3.46 
(0.30)  bc 
0.42 
(0.14)  a 
2.72 
(0.37)  b 
3.46 
(0.40)  bc 
2.44 
(0.25)  b 
<0.0001 

a 
<0.0001 

* means followed by the same letter in the same column are not statistically different (p<0.05) according to Tukey's HSD test 
 

 

43 

Table 1.6 (cont’d) 
 

 

Manure 

SCG 

More Grass 

Wrapped 

Base Mix 

More Leaves 

Paper 

Shavings 

Peat 

Control Compost 

Control Media 
P 

13.6 
(0.97) 
14.2 
(1.38) 
13.5 
(0.70) 
14.8 
(0.65) 
13.9 
(0.68) 
12.0 
(0.94) 
13.7 
(0.78) 
6.1 
(0.32) 
13.1 
(0.35) 
12.9 
(0.64) 
9.0 
(0.34) 

b* 

b 

b 

b 

b 

b 

b 

a 

b 

b 

12.6 
(0.67) 
8.3 
(0.60) 
11.3 
(0.35) 
12.0 
(0.52) 
12.8 
(0.61) 
11.7 
(0.56) 
13.0 
(0.48) 
4.3 
(0.27) 
12.1 
(0.6) 
11.2 
(0.97) 
8.1 
(0.50) 

d 

bc 

cd 

d 

d 

d 

d 

a 

d 

cd 

17.9 
(1.41) 
19.8 
(0.48) 
19.0 
(0.54) 
16.7 
(0.91) 
18.8 
(0.44) 
17.0 
(0.42) 
16.8 
(0.59) 
4.3 
(0.28) 
14.0 
(1.43) 
15.6 
(1.91) 
11.6 
(0.70) 

cd 

d 

d 

bcd 

d 

cd 

bcd 

a 

bc 

bcd 

2.77 
(0.13) 
3.15 
(0.16) 
2.63 
(0.14) 
2.98 
(0.07) 
2.56 
(0.15) 
2.41 
(0.15) 
2.60 
(0.16) 
1.68 
(0.16) 
2.88 
(0.07) 
2.83 
(0.10) 
2.13 
(0.05) 

Plant Height (cm) 

Number of Leaves 

Cucumber 

Kale 

Tomato 

Cucumber 

Kale 

Tomato 

bc 

c 

bc 

c 

bc 

b 

bc 

a 

c 

bc 

5.44 
(0.13) 
4.91 
(0.21) 
5.04 
(0.19) 
5.60 
(0.18) 
5.49 
(0.25) 
5.28 
(0.46) 
5.25 
(0.23) 
2.47 
(0.23) 
5.61 
(0.29) 
4.77 
(0.30) 
3.81 
(0.39) 

c 

bc 

c 

c 

c 

c 

c 

a 

c 

bc 

5.38 
(0.21) 
5.50 
(0.21) 
5.94 
(0.10) 
5.18 
(0.44) 
5.80 
(0.12) 
5.55 
(0.14) 
5.63 
(0.15) 
1.63 
(0.22) 
4.31 
(0.49) 
4.67 
(0.36) 
3.72 
(0.24) 

cde 

cde 

e 

bcde 

de 

cde 

de 

a 

bc 

bcd 

a 
0.009 

b 
<0.0001 

b 
<0.0001 

a 
<0.0001 

b 
<0.0001 

b 
<0.0001 

* means followed by the same letter in the same column are not statistically different (p<0.05) according to Tukey's HSD test 
 

 

 

44 

Table 1.7. Mean values (+/- SE) for five plant metrics of dry weight, wet weight, root rating, plant height 
and number of leaves per plant for cucumber grown in compost treatments at different ages. 

Treatment 

Age 

Manure 

P 

SCG 

P 

More Grass 

P 

Wrapped 

P 

Base Mix 

P 

More Leaves 

P 

2 
3 
4 

2 
3 

2 
3 
4 
 
2 
3 
4 

2 
3 
4 

2 
3 
4 

 

 

 

 

 

Shoot Dry Weight  Shoot Wet Weight 

Root Rating 

Plant Height 

(g) 

0.31 (0.01)  a 
0.38 (0.01)  b 
0.35 (0.02)  ab 

0.024 

0.2 (0.01)  a 
0.31 (0.03)  b 

0.0147 

0.27 (0.01)  a 
0.32 (0.02)  b 
0.33 (0.00)  b 

0.010 

0.33 (0.02)  b 
0.36 (0.01)  b 
0.15 (0.01)  a 

<0.001 
0.35 (0.01)  
0.39 (0.04)  
0.37 (0.05)  

0.78 

0.33 (0.02)  
0.33 (0.02)  
0.30 (0.02)  

0.536 

(1-5) 

4.54 (0.08)  
4.83 (0.11)  
4.79 (0.08)  

0.134 

3.92 (0.04)  a 
4.79 (0.11)  b 

0.002 

4.83 (0.04)  
4.96 (0.04)  
4.88 (0.07)  

0.317 

(cm) 

10.7 (0.65)  
11.6 (0.44)  
11 (0.38)  
0.485 

8.5 (0.54)  
9.8 (1.26)  

0.396 

9.5 (0.91)  
9.6 (0.86)  
10.1 (0.21)  

0.819 

4.42 (0.04)  a 
4.83 (0.04)  a 
4.83 (0.17)  a 

11.5 (1.09)  b 
10.4 (0.15)  b 
6.5 (0.60)  a 

0.043 

0.006 

4.79 (0.04)  
4.67 (0.04)  
4.79 (0.11)  

0.437 

4.63 (0.00)  a 
4.96 (0.04)  b 
4.67 (0.04)  a 

0.003 

11.3 (0.57)  
11.5 (0.83)  
10.9 (0.62)  

0.845 

10.8 (0.43)  
9.4 (0.87)  
9.5 (1.07)  

0.447 

(g) 

2.79 (0.15)  
3.13 (0.19)  
2.96 (0.23)  

0.517 

1.63 (0.07)  
2.58 (0.36)  

0.058 

2.25 (0.19)  
2.21 (0.08)  
2.58 (0.11)  

0.183 

2.88 (0.22)  b 
2.67 (0.08)  b 
1 (0.19)  a 
<0.001 
3.17 (0.15)  
3.17 (0.48)  
2.79 (0.37)  

0.658 

2.75 (0.14)  
2.21 (0.30)  
2.08 (0.22)  

0.176 

45 

 

Table 1.7 (cont’d) 

Treatment 

Age 

Paper 

P 

Shavings 

P 

Peat 

P 

Control Compost 

P 

Control Media 

2 
3 
4 

2 
3 
4 

2 
3 
4 

2 
3 
4 

- 

 

 

 

 

0.32 (0.01)  ab 
0.37 (0.01)  b 
0.31 (0.00)  a 

0.023 

0.10 (0.00)  a 
0.39 (0.03)  b 
0.43 (0.05)  b 

<0.001 
0.38 (0.02)  
0.28 (0.04)  
0.28 (0.01)  

0.056 

0.25 (0.00)  a 
0.25 (0.01)  a 
0.36 (0.03)  b 

0.005 

2.71 (0.15)  
2.58 (0.08)  
2.33 (0.08)  

0.149 

0.58 (0.04)  a 
2.75 (0.38)  b 
3.17 (0.29)  b 

0.001 

2.67 (0.41)  
1.79 (0.36)  
1.75 (0)  
0.148 

1.92 (0.04)  ab 
1.63 (0)  a 
2.71 (0.41)  b 

0.043 

0.26 (0.05)  

1.54 (0.44)  

Plant Height 
(cm) 

10.5 (0.10)  
10.3 (0.35)  
11.1 (0.17)  

0.139 

4.6 (0.27)  a 
10.7 (0.65)  b 
10.9 (0.37)  b 

<0.001 

10.9 (1.09)  b 
7.9 (0.58)  ab 
7.4 (0.15)  a 

0.028 

8.3 (0.38)  a 
8.4 (0.39)  a 
9.5 (0.43)  b 

0.004 

7.3 (1.05) 

  

4.54 (0.11)  
4.88 (0.13)  
4.75 (0.07)  

0.084 

3.88 (0.07)  a 
4.92 (0.08)  b 
4.96 (0.04)  b 

<0.001 
4.83 (0.11)  
4.67 (0.15)  
4.75 (0.13)  

0.679 

4.54 (0.08)  a 
4.83 (0.11)  ab 
4.92 (0.04)  b 

0.043 
5 (0.00)  

Shoot Dry Weight  Shoot Wet Weight  Root Rating 
(1-5) 

(g) 

(g) 

* means followed by the same letter in the same column are not statistically different (p<0.05) according to 
Tukey's HSD 
 
 

 

 

46 

Table 1.8. Selected chemical characteristics of compost at different ages. 

Compost 

Age at 
time of 
sampling 

pH 

EC 

dS / m-1 

NO3-N 
ppm 

NH4-N 
ppm 

P 
ppm 

K 
ppm 

Ca 
ppm 

Mg 
ppm 

Na 
ppm 

Cl 
ppm 

7.9(0.1)  10.6(1.14)  734(132)  1.8(0.2) 

2241(326)  880(174)  199(3)  5.16(0.54) 16.0(5.8) 

39.7(8) 
34.8 
43.3 
240 

0.8 
1.3 
2.2 

4689 
3024 
2835 

47(15.3)  118(52) 
173.3 
120 

0.9 
0.7 

890(405) 

2211 
2403 

580 
456 
380 

1773 
723 
879 

1043 
1113 
1391 
307(8)  130(34) 1.65(0.35) 17.8(8.1) 
261 
470 

450 
531 
900 

189 
300 

80 
96 

987 
381 

<1yo 
2yo 
3yo 
4yo 
<1yo 
2yo 
3yo 
<1yo 
2yo 
3yo 
4yo 
<1yo 
2yo 
3yo 
4yo 
<1yo 
2yo 
3yo 
4yo 

Manure 

SCG 

More 
Grass 

Wrapped 

Base Mix 

 

8 
6.8 
5.9 

20 
17.84 
23.5 

7.6(0.6)  4.5(0.22) 

7.1 
6.1 

7.51 
12 

7.7(0.2)  6.7(1.27) 

8 
7.2 
6.1 

11.27 
11.27 
13.64 

1410 
1776 
2430 
4.5(1.5) 

192 
1080 
446(68) 

498 
1116 
1472 

1.3(0.7)  44.7(5.0)  1505(347)  510(202)  138(45) 1.80(1.10) 12.9(2.9) 

0.7 
1.5 
0.5 

10.5 
22.4 
74.3 

4011 
1647 
1932 

417 
835 
1137 

194 
336 
394 

42 
42 
76 

1118 
369 
493 

8.3(0.2)  6.2(0.07)  323(22.6)  0.8(0.2)  16.6(2.6)  1380(138)  480(120)  122(19) 2.00(1.35) 16.3(3.8) 

7.7 
6.9 
7.9 

13.38 
17.6 
7.03 

882 
1710 
172 

1.0 
5.1 
1.4 

8.1(0.2)  4.2(0.23) 

250(8.6) 

0.8(0.3) 

7.8 
6.8 
7.1 

11.27 
13.38 
11.76 

828 
1320 
1264 

0.7 
5.9 
1.3 

22.4 
20 
10.6 
22(4.0) 
17.9 
22.4 
16.7 

3069 
2529 
1875 
965(68) 
2472 
1836 
1458 

678 
1304 
348 

276 
560 
164 

48 
30 
26 

1400 
827 
818 

380(82)  78(36)  2.67(1.67) 16.5(5.5) 

678 
939 
1053 

276 
365 
384 

48 
42 
112 

1036 
404 
413 

47 

sampling 

 
 
 
 
 
Table 1.8 (cont’d) 
Compost  Age at time of 
More Leaves 
 
 
 
Paper 
 
 
 

Shavings 

Control 
Compost 

Peat 

<1yo 
2yo 
3yo 
4yo 
<1yo 
2yo 
3yo 
4yo 
<1yo 
2yo 
3yo 
4yo 
<1yo 
2yo 
3yo 
4yo 
<1yo 
2yo 
3yo 
4yo 

pH 

EC 

dS / m-1 

NO3-N 
ppm 

NH4-N 
ppm 

P 
ppm 

K 
ppm 

Ca 
ppm 

Mg 
ppm 

Na 
ppm 

Cl 
ppm 

8.2(0.2)  5.0(0.66)  250(44)  1.0(0.3)  13.7(2.2)  1097(191)  400(48)  89(3)  0.93(0.19)  17.8(4.8) 

7.8 
6.9 
6.5 

12 
6.11 
11.75 

984 
576 
1160 

0.6 
1.0 
1.4 

14.5 
28.8 
27 

2133 
909 
1221 

783 
452 
1000 

324 
212 
360 

54 
64 
95 

780 
254 
413 

8.8(0.3)  4.2(0.27)  88(64)  1.9(1.0)  5.9(1.3) 

829(152)  520(95)  102(5)  4.33(1.18)  23.3(9.2) 

7.9 
7.9 
7.9 

10.61 
10 
9.39 

2025 
1307 
1157 
8.1(0.4)  1.8(0.18)  1.1(0.9)  5.6(4.8)  29.6(10.7)  482(70) 

1145 
1030 
915 

1.5 
1.1 
0.7 

7.4 
5.8 
6.2 

991 
870 
913 

342 
290 
328 

270 
145 
195 

2591 
308 
385 

200(43)  49(8)  4.83(2.86)  20.6(4.5) 

8.4 
6.7 
6.7 

2.47 
10 
4.46 

6 
975 
368 

0.1 
1.7 
1.6 

24 
30 
37.2 

732 
1508 
369 

183 
826 
400 

54 
320 
142 

34 
95 
98 

440 
433 
309 

6.3(0.2)  3.2(1.21)  208(110)  3.2(0.6)  64.3(13.2)  801(231)  245(151)  78(36)  1.50(0.20)  11.5(2.5) 

6.2 
4.9 
6.7 

4.69 
6.55 
5.63 

332 
612 
489 

0.1 
33.7 
0.8 

200 
99.7 
41.7 

1518 
789 
837 

157 
383 
339 

91 
232 
174 

58 
56 
72 

207 
277 
190 

5.7(0.3)  1.3(0.27)  32(18)  0.6(0.1)  32.9(7.2) 

217(30) 

115(63)  42(12)  2.77(0.78)  11.4(0.9) 

5.2 
5.5 
7.9 

4.69 
4.0 
11.22 

386 
328 
1260 

0.5 
0.4 
1.9 

129.3 
72.1 
55.7 

729 
446 
446 

174 
243 
365 

141 
142 
147 

36 
68 
116 

273 
185 
287 

* numbers in parenthesis are standard errors for mean values from all 3 years compost was made. All other values based upon 
analysis of a single sample. 

 

48 

Table 1.9. Mean harvest weights (+/- SE, n=6) of basil, and pH of media from 
1-year old compost media, grown in 2015. 

Compost Treatment 

Manure 
Food 
More Grass 
Wrapped 
Base Mix 
More Leaves 
Paper 
Shavings 
Peat 
Control Compost 
P 

Harvest Weight 

pH 

(g) 
175 (15) 
197 (24) 
164 (9) 
134 (18) 
169 (11) 
178 (18) 
137 (13) 
38 (7) 
351 (10) 
418 (21) 

 

bc* 
c 
bc 
b 
bc 
bc 
bc 
a 
d 
e 

8.4 (0.09) 
8.2 (0.09) 
8.6 (0.04) 
8.7 (0.05) 
8.6 (0.05) 
8.7 (0.03) 
8.7 (0.01) 
8.2 (0.10) 
7.4 (0.09) 
7.5 (0.10) 

<0.001 

<0.001 

bcd 
bc 
cde 
e 
de 
e 
e 
b 
a 
a 

* means followed by the same letter in the same column are not statistically 
different (p<0.05) according to Tukey's HSD test 
 
 

 

 

49 

Root Media 

 

Control Compost 

Food Compost 

Table 1.10. Basil harvest weight, root media pH, and recently mature leaf 
tissue analysis from 'Control' (with normal leaf coloration) and 'Food' 
(chlorotic leaf coloration) compost media treatments. 
 
 
Harvest weight 
pH 
N 
P 
K 
S 
Ca 
Mg 
B 
Zn 
Cu 
Mn 
Fe 
Al 
 

220 (31) 
8.3 (0.09) 
5.2 (0.09) 
0.88 (0.04) 
10.2 (0.24) 
0.33 (0.01) 
1.06 (0.07) 
0.49 (0.03) 
23 (1.5) 
59 (2.6) 
4.5 (0.29) 

424 (27) 
7.4 (0.15) 
3.3 (0.19) 
0.57 (0.01) 
5.5 (0.31) 
0.24 (0.01) 
1.00 (0.08) 
0.45 (0.03) 
16 (0.7) 
83 (7.2) 
3.0 (0.41) 

P 

0.003 
0.003 
<0.001 
<0.001 
<0.001 
<0.001 
0.592 
0.367 
0.006 
0.022 
0.024 
0.133 
0.389 
0.434 

54 (7) 
66 (2) 
7.5 (4.5) 

 

70 (6) 
53 (13) 

18.5 (12.3) 

 

50 

 

 
Figure 1.1. Principal component analysis biplot of the first and second principal components for 
compost physiochemical properties of A) all thermophilic composts and B) treatments grouped 
by starting C:N ratio.  The percentages of the total variance accounted for by each principal 
component are indicated in parentheses in axis titles. 

 

 

51 

 
Figure 1.2.  Loading contributions of compost physiochemical characteristics for interpretation 
of PCA values for A) PC1 and B) PC2.  

 

 

52 

 

A) 

B) 

C) 

D) 

 

E) 

Figure 1.3.  Plant growth data for all plant species for A) dry weights, B) wet weights, C) root 
rating, D) plant heights and E) number of leaves.  Columns denoted by the same letter within the 
same species are not different according to Tukey’s HSD test (p<0.05). 

 

53 

 

  

 

 

 

 

Figure 1.4.  Linear regression of relationship between pH and basil harvest weight. P<0.001, 
R2=0.50. 
 
 
 
 
 

 

 

54 

 

 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

REFERENCES

55 

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BIOCHAR AND ANAEROBIC DIGESTER EFFLUENT IN COMPOSTING: EFFECTS 
ON FINISHED COMPOST FOR GROWING ORGANIC CUCUMBER TRANSPLANTS 

CHAPTER II 

 

 

60 

ABSTRACT 

Properly designed and aged compost is a promising alternative to peat based substrates 

for cultivation of transplants and plants in containers.  The objective of these studies was to 

evaluate biochar and liquid anaerobic digester effluent (ADE) as amendments at the start of 

composting, for both the effects on finished compost characteristics and transplant growth using 

compost-based root media.  Thermophilic compost was made in static piles of 1yd3 starting 

volume with a base recipe of equal volumes dried municipal leaves and fresh cut grass for the 

purpose of producing transplant growing root media.  Amendments to the base recipe included 1) 

10% biochar by volume; 2) 20 gallons/cubic yard added liquid anaerobic digester effluent 

(ADE); 3) a combination of 10% BC and 20 gallons ADE; and 4) the base recipe without 

additions as a control.  In a separate experiment, vermicompost was also produced over a period 

of nine months, with and without biochar addition at 10% by volume.  Compost samples were 

analyzed for both total and water soluble nutrients as well as physical properties at five months 

maturity for thermophilic composts and fully mature vermicomposts aged over one year.  The 

two different composting methods were employed to assess if the effects of biochar on the 

physical and chemical characteristics were consistent in both systems.  Differences in finished 

compost characteristics included higher soluble nutrient values driven by the addition of ADE 

but not biochar, while biochar inclusion increased C:N and decreased bulk density for the 

thermophilic composts.  A greenhouse cucumber bioassay was conducted with the finished 

thermophilic composts and a control treatment consisting of a standard peat based medium.  

Cucumber transplants were evaluated one week after seeding for emergence, and at three weeks 

after seeding for above ground biomass, height, number of leaves and root rating, with data 

analyzed as a two-factor ANOVA of biochar and ADE, and with Dunnett’s test for comparisons 

 

61 

to the peat medium.  Transplants in all compost media outperformed the peat-based control for 

all metrics except root rating.  Within compost mixes, addition of biochar improved all metrics 

of transplant growth.  In contrast, addition of ADE reduced several metrics of transplant health 

including shoot dry weight and root ratings. The 100% compost media supplied adequate fertility 

and physical characteristics to grow cucumber seedlings, though the underdeveloped root 

systems would likely cause problems when planting into a field.  The nature of the effect of 

biochar on compost should be reviewed further as results were dependent on what type of 

composting employed (thermophilic or vermicomposting).  In thermophilic compost used as a 

root media, co-composted biochar may be beneficial, though more research is needed to optimize 

the use of this amendment.  

 

INTRODUCTION 

Transplant use provides a number of benefits for vegetable farmers and the quality of 

transplants impact management practices and potentially yield.  By avoiding germination 

problems encountered with direct seeding, transplants ensure uniform plant establishment and 

more dense plant populations (Burnett et al., 2016; Sterrett, 2001).  Keeping young plants in one 

easy to monitor and control location helps with protection from diseases and pests until they are 

ready to be planted out, at which time they should be better able to withstand such pressures.  

This in turn helps with improved ground cover (weed) management.  Use of transplants can 

better ensure predictable harvest times as well.  They shorten the production cycle, providing 

more time for cover crops to improve soil quality.  The shortening of the production cycle is 

particularly important for certain crops based on growing season length in areas such as the 

Midwest.  Nearly every organic vegetable farm, regardless of size, uses transplants, but because 

 

62 

organic transplants can be difficult to source, farmers often produce their own, with inherent 

difficulties. 

The qualities of the root media can have long-lasting ramifications on yield (Dufault, 

1998; Jack et al., 2011; Raviv et al., 1998).  Transplant/container culture involves a restricted 

root zone, in which sufficient water, nutrients and aeration for the growing transplant must be 

provided (Raviv, 2011).  Desired root media characteristics include good water holding capacity, 

high pore space and low bulk density (Sterrett, 2001).   

Organic agriculture is expanding and with it the demand for root media that are approved 

for use in an organic system.  Fertilization regimen in organic agriculture is limited in options 

from natural sources such as fish emulsion, feather, bone or blood meal, and producers are often 

weighing the benefits against the high costs and environmental footprint of these choices (Clark 

& Cavigelli, 2005; Kuepper & Everett, 2004).  For organic vegetable farmers the general 

recommendation has been to invest in a uniform, high quality transplant growing medium, which 

are most often peat-based, and may or may not include compost, as well as using these limited 

fertilizer options.   

Peat-based root media may be the most commonly used in horticulture, however, there is 

growing demand for an alternative.  The positive physical characteristics of peat that make it an 

ideal media component have been difficult to match.  These attributes include its low bulk 

density, high pore space and water holding capacity (Raviv, 2011).  However, peat harvest may 

result in environmental degradation, the regeneration time is long, and increasing production and 

transportation costs make it increasingly expensive (Clark & Cavigelli, 2005; Lazcano et al., 

2009; Pelaez-Samaniego et al., 2017; Ridout & Tripepi, 2011; Treadwell et al., 2007).  Still, 

 

63 

most container substrates on the market have peat in the range of 80% and upwards (Ceglie et 

al., 2015).   

Composting has been employed by farmers for centuries, with compost being used to 

increase soil organic matter and nutrients, soil water holding capacity and nutrient retention, and 

to provide other benefits.  Using local resources to turn what would be a waste stream into a 

valuable resource can help to create a circular economy in which nutrients flow back to the land 

(Peng & Pivato, 2019).  Compost use in root media cultivation, either at 100% or as a 

component, provides a much more regenerative/sustainable system.  Development of affordable 

compost-based transplant media using feedstocks that are readily available and generally 

consistent throughout the United States could increase the adoption of compost based media and 

reduce use of fertilizers. 

Two methods of aerobic composting are thermophilic or “hot” composting which 

employs microorganisms at elevated temperatures (130°F minimum), and vermicomposting 

which employs microorganisms and composting worms at ambient temperatures, to aid in the 

breakdown and humification of feedstock materials (Dominguez & Edwards, 2011; Edwards et 

al., 2010).  Both methods are an effective means of cycling nutrients and produce nutrient-rich 

compost, with vermicompost often having higher nutrient levels but this is based largely upon 

starting feedstocks.  A primary difference often cited between compost derived from these 

methods are the microorganisms present which can have variable effects on plants.   

Compost, whether thermophilic or vermicompost, provides soluble and long-term 

nutrients, water holding capacity, etc.  Composts with high total porosity and air-filled porosity 

are more likely to be used as a transplant media (Raviv, 2005).  However, compost variability 

can be a concern (Beozzi et al., 2017; Michael Raviv, 2011), making more careful management 

 

64 

of transplants necessary (Burnett et al., 2016).  Concerns with compost have been high salinity 

levels, poor physical characteristics such as high bulk density, phytotoxicity, high pH and heavy 

metals (Beozzi et al., 2017; Ceglie et al., 2015; Rogers, 2017).  For widespread adoption on a 

larger scale, growers would need assurances that a compost can reliably provide a uniform, 

stable, and readily available product (Sterrett, 2001).  There have been numerous studies with 

compost used in root media.  Many have used compost as a component and not at 100%, often 

using different percentages to arrive at the optimal or cut-off at which the negatives outweigh the 

positives of its inclusion in media.  The goal herein is to study compost effects on transplants in 

isolation by using 100% compost as a growing media.  Understanding these shifts by individual 

growth media components, in this case different types of compost, will provide information 

helpful for making combinations that optimize root and overall transplant health.  

To develop compost specifically for use as a growing media, biochar is an attractive 

component as it has many of the same characteristics that make peat desirable for growing plants 

in containers such as biological stability, good water holding capacity, and micropores (Lehmann 

& Joseph, 2009).  It has also been compared with perlite/vermiculite for these same reasons.  It 

does, however, convey additional benefits to a root media.  Biochar is pyrolyzed biomass 

consisting primarily of polycyclic aromatic hydrocarbons and is relatively recalcitrant in nature 

(Cheng et al., 2008; D. J. Lehmann & Joseph, 2009).  Some of the physical and chemical 

properties affected by biochar are increases in water holding capacity and soil aggregation, 

modifications of pH, changes in nutrient dynamics, and reduction of bulk density, amongst 

others (Guo et al., 2020; McCormack et al., 2013).  It has many of the same benefits as compost, 

particularly in storing carbon in the soil, raising soil organic matter, increasing water holding 

capacity and nutrient holding capacity.  Biochar can be incorporated into compost as an 

 

65 

amendment prior to the composting process as an effective means of retaining nutrients, though 

results vary (Steiner et al., 2015).  Despite these positive attributes, experimental results are 

inconsistent because biochar varies by feedstock type, pyrolysis temperature, and retention time, 

and interacts differently across different soil types, crops, etc. (Laghari et al., 2016; Sun et al., 

2014).  Depending on the source, biochar can be a relatively expensive input on a farm 

(Mihreteab et al., 2016), and the fine dust-like nature of the material can make it potentially 

dangerous to the applicator depending on the means of land application (Lehmann & Joseph, 

2009).  One means of overcoming these obstacles could be pinpointed application by having the 

biochar in larger percentages at the root zone of plants that are to be transplanted out into the 

field.  As biochar does not easily degrade, there will be eventual accumulation of biochar in the 

soil as new transplants are put into the field each year in the case of an annual cropping system.  

Some past research indicated that biochar can bind up nutrients in the first few years, but co-

composting biochar can alleviate this issue by charging it with nutrients (Jeffery et al., 2011; 

Kammann et al., 2014; Wang et al., 2019).  Similarly, for use in root media, biochar that has not 

been co-composted may bind nutrients and have negative effects on transplant growth as seen by 

Nair and Carpenter (2016).  There is a labile fraction of carbon in biochar that can result in 

immobilization of nutrients, but this fraction is likely to have been consumed during the 

composting process so that the remaining carbon is in the more recalcitrant form (Chan & Xu, 

2009).  While biochar has been researched in compost production, the focus has been biochar 

effects on N retention and organic matter processing with little to no attention paid to other 

macro- and micronutrients (Steiner et al., 2015).  A primary question being addressed in this 

study is the effect of softwood biochar on compost, both thermophilic and vermicompost, and 

biochar effects on plant growth when included as a component of compost-based growing media.  

 

66 

For a plug tray of transplants, the root zone volume is limited and available nutrients are easily 

lost by leaching during irrigation (Bilderback, 2002), but compost and biochar may help to 

alleviate these losses. 

Anaerobic digester effluent (ADE) is a resource that could be better used through 

composting in creation of a circular economy in which nutrients/resources are conserved in the 

agricultural system.  Anaerobic digesters have been growing in popularity as a means of 

generating electricity and decreasing volume of organic matter, especially for dairy facilities in 

the US (Pelaez-Samaniego et al., 2017; US EPA, n.d.).  While much of the carbon is converted 

to methane, the remaining effluent or digestate (solid and liquid fractions, which are generally 

separated) retains nutrients in generally high concentrations, especially for ADE from dairy 

manure (Fuchs & Drosg, 2013; Pan et al., 2018; Tambone et al., 2010).  The liquid ADE is 

particularly high in N and K, while more of the P is retained in the solid fraction (Logan & 

Visvanathan, 2019; Milles, 2014; Möller & Müller, 2012; Peng & Pivato, 2019).  While the 

solids from ADE have been investigated as a composting feedstock, little attention has been paid 

to the liquid ADE fraction.  The liquid is often seen as a negative for ADE facilities primarily 

due to its high water content that makes it expensive for transport (Akhiar et al., 2017; Lin et al., 

2014; Peng & Pivato, 2019).  Other concerns include high ammonia content, potential plant or 

human pathogens, and smell (Alburquerque et al., 2012; Bustamante et al., 2013; Pelaez-

Samaniego et al., 2017; Zeng et al., 2016) which may be alleviated by composting ADE with 

biochar.  Lin et al. (2014) noted that the predominant forms of nitrogen in ADE are NH3 and 

NH4+, which would be more likely to be lost to volatilization or leaching, whereas composted 

ADE in their study was 74% organic nitrogen which leads to more long-term N turnover.  The 

 

67 

biochar in a composting system would be more likely to retain that ammoniacal-N, preventing its 

volatilization and leaching. 

The first objective was to characterize the effects of biochar and anaerobic digester liquid 

effluent on finished compost physical and chemical characteristics.  We hypothesized that 

biochar in both the thermophilic compost and vermicompost experiments would result in greater 

nutrient retention (of both soluble and total nutrients, thereby also increasing EC), and that this 

nutrient retention effect would be more pronounced in the presence of elevated nutrient levels.  

We hypothesized that biochar added to compost would result in an increase in the water holding 

capacity, organic matter/carbon, C:N and pH, while lowering bulk density of the finished 

compost.  We further hypothesized that ADE would elevate nutrient concentration and EC.  The 

second objective was to contribute towards the development of affordable compost-based 

transplant media for production of vegetable transplants by assessment of the composts made in 

Experiment 1 by growing cucumber seedlings.  We hypothesized that the compost media could 

grow acceptable cucumber transplants without modification, and that the amendments added at 

the time of compost production would result in differences in the transplant morphological 

features assessed, with biochar in particular increasing plant growth.   While much of the 

research surrounding compost for root media assesses specific composts and their use for 

growing plants, this research aim is to address how individual components/feedstocks impact the 

finished compost and its use for transplant production in order to guide compost producers or 

farmers to be able to achieve the desired compost characteristics. 

 

 

 

 

68 

MATERIALS AND METHODS 

Experiment 1: Thermophilic Compost Treatments, Experimental Design and Management 

Composts were made at the Michigan State University (MSU) Horticulture Teaching and 

Research Center (HTRC) in Holt, MI (42°40” N, 84°28” W).  Experimental treatments consisted 

of four compost recipe combinations.  The base feedstock mix (“Mix”) was grass freshly cut 

from organically managed/certified property at the HTRC and senesced municipal leaves from 

the city of East Lansing, MI, at equal parts by volume which were thoroughly mixed by layering 

in a PTO-driven manure spreader and ejecting into a pile.  Experimental treatments consisted of 

1) the base recipe without additions; 2) base mix plus biochar at 10% by volume (“Mix+BC”); 3) 

base mix plus liquid ADE (“Mix+ADE”); and 4) base mix plus biochar at 10% and ADE 

(“Mix+BC+ADE”).  

The biochar used in the experiment was from Biogenic Reagents (Circle Pines, MN), 

made from softwood biomass.  Biochar characteristics were supplied by the company and 

guaranteed a minimum surface area of 400 m2/g, minimum carbon at 90%, maximum ash and 

volatile matter both at 5%, and a pH in the range of 7-9.  For each treatment with biochar, 22lbs 

or 22.5 gallons were added and mixed as the base mix was put into the compost bay to make a 

homogeneous pile.  The calculated rate of biochar was approximately 10% by volume at the start 

of composting.   With a volume reduction by the end of the composting process of nearly half, 

the % biochar in the compost would be considerably higher due to its recalcitrance relative to the 

base mix.  Final proportion of biochar may near 20% by volume. 

Anaerobic digester liquid effluent (ADE) was obtained from the MSU Anaerobic 

Digester Research and Education Center (ADREC) located at the MSU Dairy Facility on College 

Road, East Lansing, MI.  The ADREC digester is an electricity co-generation facility with the 

 

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capacity to store two million gallons of ADE.  Twenty gallons of ADE were added to all piles for 

which AD was a part of the treatment; treatments that did not receive ADE were moistened with 

20 gallons of water.   

Compost bays were made using standard (40”x48”) wooden pallets (lined with 

cardboard) to allow for approximate starting size of a cubic yard for each static pile.  The 12 

compost piles were maintained under a moveable (sled) open-ended high tunnel for rain 

exclusion.  Treatments were organized in a randomized complete block design (RCBD).  

Materials were moistened by a hose with a breaker as piles were constructed.  Temperature data 

were manually recorded daily taking the average of two 18in compost thermometers to ensure 

proper turning of all piles based upon thermophilic heating curves.  Piles were turned manually 

with a pitchfork when internal temperatures fell below 130°F (four times).  Compost was started 

in July 2015, turned four times and left to mature/cure at the end of August 2015.   

Experiment 2: Vermicompost Treatments, Experimental Design and Management 

Vermicompost beds were constructed at the same location inside a stationary 30’x72’ 

unheated high tunnel.  A base mix of pre-consumer kitchen preparation food residue, municipal 

leaves, shredded office paper, sphagnum peat, used coffee grounds and spelt dust was pre-

composted for approximately 2 weeks (approximate ratio of 10:10:2:2:1:1 by volume).  The 

uniform mixture was placed in six 21ft2 (3’x7’) vermicomposting beds (static piles) to a depth of 

approximately 1.5 feet, being added in shallow layers (~4” at a time) over a period of a month to 

drop the temperature of the pre-composted mixture and ensure it did not heat again to allow for 

the addition of worms.  Experimental treatments were the base mix on its own, or with biochar 

thoroughly mixed in at approximately 8% by volume.  Volume reduction at the termination of 

vermicomposting averaged 40%; assuming the recalcitrance of biochar left the majority of BC 

 

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intact, the final %BC by volume would be approximately 13%.  The biochar in Experiment 2 

was the same biochar from Biogenic Reagents as used in Experiment 1.  There were three 

replications of each treatment totaling six experimental units, arranged as a randomized complete 

block design (RCBD).   

After the pre-composted material with or without biochar was added to beds, 

approximately twenty pounds of composting worms (Eisenia fetida) were added per bed on top 

to move into the bedding /food mixture.  This is referred to as a “batch” system of 

vermicomposting compared to a “bin” system of vermicomposting where food is added at 

regular intervals to existing bedding (Edwards et al., 2010).  Beds were started in the fall and left 

for nine months (September-May) to be converted by worms into finished vermicompost.  This 

included the winter months, where worms moved to the lower parts of the beds that were 

warmer, and spring months were worms returned to the surface layers.  Worms were extracted 

using crates of fresh pre-composted material on the surface.  The finished vermicompost was 

screened through half inch hardware cloth to provide a uniform product.  Vermicompost samples 

were submitted for laboratory analysis for chemical and physical properties. 

Experiments 1 and 2 Data Collection 

Composite samples from ten areas in each compost pile (thermophilic composts) or bed 

(vermicomposts) immediately after they had been mixed were taken for laboratory analysis of 

chemical and physical properties.  This was approximately five months after composting had 

begun for thermophilic compost, and after nine months being vermicomposted.   Key responses 

measured from mature compost samples were for nutrients including both total nutrients by 

ashing (% N, P, K, Ca, Mg, S, Na; ppm Zn, Mn, Fe, Cu, B, Al) and water soluble nutrients using 

saturated media extract (ppm nitrate-N, ammonium-N, P, K, Ca, Mg, Na, Cl), chemical 

 

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characteristics of electrical conductivity (EC), pH, % organic matter and physical characteristics 

of bulk density and percent moisture.  Calculations for the percent carbon and the carbon to 

nitrogen ratio were obtained from the data and the percent of each nutrient contribution to the 

electrical conductivity was also calculated using the equation  

[1]  % Element  = ((ppm element) / (EC mg/L * 700)) * 100 (Warncke & Krauskopf, 1983). 

For Experiment 1 only, additional data of EC and pH data were collected for all the thermophilic 

composts again using a 1:2 dilution of compost to deionized water (v/v).  This was at the time of 

growing cucumber transplants in the fall of 2016, when compost had additional time to mature to 

approximately 15 months old  

Experiment 3: Transplant Experimental Design, Management and Data Collection 

Finished composts from Experiment 1 (Mix, Mix+ADE, Mix+BC, Mix+BC+ADE) were 

used as planting media (100% compost) for cucumber cv. Marketmore 76 (Cucumis sativus) 

transplants.  An additional treatment of Sunshine Potting Mix (Sun Gro Horticulture) which is a 

peat-based media, commercially available and approved for use in organic production systems, 

was also included.  For the four compost media treatments, there were 12 replications each, (four 

replications from each of the original three compost replications), and four replications from the 

peat-based media, totaling 52 experimental units, each of which consisted of four 4-cell packs, 

totaling 16 plants.  All units were arranged in a randomized complete block design (RCBD), 

each block being arranged on a single greenhouse bench.  Flats were watered daily and no 

supplemental fertilizer was added.   

The experiment was carried out in the research glass greenhouses of MSU in November 

2016 when the compost had been curing for approximately one year, 15 months from starting the 

compost piles.  Supplemental lighting was supplied with three overhead 400W HPS lamps 

 

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suspended 4’ above a 3’x18’ bench for a 16 hour photoperiod.  Air temperature was maintained 

at a minimum heating setpoint of 65F with ventilation at 75F.  Transplants were watered daily by 

overhead watering.  

Compost media were filled into cells with settling and seeded, planting two seeds per 

cell.  Seven days after planting, emergence data were collected with the number not emerged 

seeds being recorded to obtain a percentage for emergence (number of seeds emerged out of 32 

possible per experimental unit).  Delayed emergence led to an additional collection of data for 

emergence at 10 days as well.  Cells were then thinned to one plant per cell by shoot removal.   

Transplant data was taken at three weeks, with a minimum of two fully expanded leaves.  

The data collected to assess quality of transplants were above ground biomass (both wet and dry 

weights), root rating (categorical variable 0-5 of qualitative rating per transplant plug, Figure 

2.1), average plant height (cm) and number of true leaves.  All 16 plants were used for obtaining 

wet and dry weights, and total number of leaves.  Samples were dried in a forced draft oven at 

60°C for 72 hours.  For other metrics the observational unit was a subsample of eight plants 

selected at random from each experimental unit.  Plant height was a visual average of these eight 

plants, while root rating was a cumulative total for the eight plants in the observational unit.  The 

root rating was a proxy for root biomass due to the difficulty of separating roots from the media; 

this also correlates to the ease with which transplants are able to be pulled from a plug tray and 

how well they fill out the volume of the plug.  Data was converted to per plant by dividing by the 

applicable number of plants used to obtain the data.  The ratio of roots to shoots was calculated 

using the root ratings and dry weights, and treatment differences analyzed for this variable as 

well, though this ratio is not reflective of what would typically be reported for root:shoot where 

both variables would have been by mass and not a categorical variable for root rating.   

 

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Statistical Analysis 

For all three experiments, data analysis was carried out using R statistical software 

package, and additional packages for R including lme4 for linear regression, lsmeans for 

pairwise comparisons and ggbiplot for PCA (R Core Team, 2019).  Unless otherwise noted, 

α<0.05 was designated as level of significance.  Data were assessed to ensure that ANOVA 

assumptions were not violated and were log transformed when needed prior to analysis.  

Sattherthwaite’s degrees of freedom was employed to account for potential nonequal variance in 

the data.  All data presented in figures and tables are non-transformed.  

Chemical and physical properties of the thermophilic compost (Experiment 1) and 

transplant data (Experiment 3) were analyzed for treatment significance by two-way analysis of 

variance (ANOVA) with main factors being presence/absence of biochar, and presence/absence 

of ADE.  To account for the blocking effect, a random effect term was included: block (rep) for 

the compost data, and transplant block (rep) nested within compost block for transplant data.  

Significant differences between treatment means were determined by pairwise comparison and 

separated according to Tukey’s highly significant difference (HSD) test (P≤0.05).  The 

transplants from the peat-based media used as a commercially available control were also 

analyzed, comparing this treatment to the compost treatments using Dunnett’s Test. 

The data from Experiment 2 (chemical and physical compost properties) were analyzed 

for treatment significance by one-way analysis of variance (ANOVA).   

Principal component analysis (PCA) was conducted on the standardized compost 

physical and chemical characteristics data (for Experiment 1 and 2, separately).  PCA is a tool 

for data compression, to capture the main features in the data set and to extract information from 

multivariate, high-dimensional data sets.  With the large number of dependent variables, PCA is 

 

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a descriptive technique used to explore and visualize the data for relationships among variables 

(physiochemical characteristics) and potential differences among composts.  The PCA was run 

for 28 different variables- the soluble and total nutrients, EC, pH, percent organic matter, carbon 

to nitrogen ratio (C:N), bulk density and moisture (with two sets of data for EC and pH in 

Experiment 1, taken when compost was 5 and 15 months old).  While % soluble salts were 

calculated from the ppm of each nutrient and the EC (Equation 1), these numbers were not 

included in the PCA analysis because this data was already captured by the ppm of each nutrient.  

Visual representation of the PCA was made by creating bi-plots of the first and second PCs.   

Loading contribution of compost characteristics to PC1 and PC2 were used for interpretation of 

the PCA.  

 

RESULTS 

Experiments 1 and 2: Compost Physiochemical Characteristics 

There were a number of differences observed between treatments for the various 

physiochemical properties of the finished compost (Tables 2.1, 2.2, 2.3).  Dry bulk density was 

negatively correlated with biochar amendment, decreasing from 0.37 to 0.32 g/cc with addition 

of biochar (a 14% decrease) but was not affected by ADE in Experiment 1 (Table 2.1).  

However, the vermicompost did not differ in bulk density values, which were higher at 0.47-0.50 

g/cc compared to the thermophilic composts.  While neither main factor of biochar or ADE were 

significant for moisture level (44% to 54%), the interaction was (p=0.041) with an increase in 

moisture with inclusion of biochar if ADE was not present, but a decrease in moisture with 

inclusion of biochar when ADE was present.  No difference in moisture was detected between 

vermicompost treatments. 

 

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Inclusion of biochar increased the C:N of the finished thermophilic compost (Table 2.1).  

From Experiment 2, vermicompost C:N was also increased with inclusion of biochar.  In both 

experiments the decrease of C:N by biochar was 8-9%.  For both experiments, the magnitude of 

the differences observed was small with values ranging from just 21 to 23 for Experiment 1, and 

11 to 12 for Experiment 2.  Organic matter and carbon content was not changed by biochar 

treatment in either thermophilic or vermi- compost.   

The pH values of the more mature (15mo) composts were influenced by ADE, decreasing 

from 8.3 to 8.1 with the inclusion of ADE in the compost (Table 2.2).  Although there were 

differences between treatments, the magnitude of the differences was quite small.  There were no 

differences for pH values in the composts sampled at 5mo which were higher than the values at 

15mo, indicating the continued maturation of the compost over this time.  Biochar was not 

shown to affect the pH in either the thermophilic or vermi- composts. 

For the EC of the younger compost samples (5mo) ADE increased these values, from 4.3 

to 5.7 dS/m (p=0.035, Table 2.2).  The EC taken at the time of growing the transplants was 

influenced by both biochar and ADE amendments (p=0.016 and p<0.001, respectively).  Here 

again the addition of ADE was the primary driver, with compost mixes without ADE at 7.6, and 

inclusion of ADE increasing EC to 9.9 dS/m.  In Experiment 2, biochar addition to the 

vermicompost decreased EC from 12.0 to 10.8 dS/m (p=0.007).  EC values for both 

vermicompost treatments were very high, in the upper ranges of what we have observed in years 

of composting research and composting literature.   

Regarding soluble nutrients, addition of ADE increased concentration of all nutrients 

except Mg and NH4-N (Table 2.3).  From addition of biochar to the compost, in contrast, no 

differences in any of the nutrients was observed for Experiment 1.  There was an effect of 

 

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biochar in the vermicompost, however, with decreases in soluble NO3-N, K, Ca and Mg.  This 

mirrors the lower EC of the Vermi+BC treatment.  For Experiment 1, differences between 

treatments in nutrient values were detected for only soluble P and Na when looking at pairwise 

comparisons of all four treatments.  Mix+BC+ADE had a mean value of 11.4 ppm P, higher than 

any of the other treatments.  Additionally, soluble P was the only nutrient for which an 

interaction was observed between biochar and ADE, where biochar had no effect in the absence 

of ADE but increased P in the compost with ADE.   Isolating the main effect of ADE then for the 

soluble nutrients, the following percent increases in nutrients were observed with the inclusion of 

ADE in the compost: NO3-N +144%, P +43%, K +21%, Ca +38%, Na +233%, and Cl +30%. 

The only difference observed between treatments for total nutrient values in Experiment 

1 was an increase in zinc with ADE, though a number of other nutrients were marginally 

significant (p<0.1, data not shown).  No differences between total nutrients were observed in 

Experiment 2. 

Principal Component Analysis: PCA explained 59% of the variation in the data when 

taking the first and second principal components together (Figure 2.2a).  Plotted against each 

other, both of the treatments that received ADE are grouped, and those without are grouped 

together.  Presence or absence of biochar appears to be inconsequential or dwarfed by the impact 

of presence/absence of ADE when looking at the physical and chemical characteristics of the 

compost.  The majority of the variables were for nutrient levels.  ADE having the greater impact 

is not surprising as significant elevation of nutrients was expected.   

With further analysis/segregation of the data, however, to isolate the effect of biochar 

only by comparing Mix v Mix+BC and Mix+ADE v Mix+BC+ADE, the trend emerges that the 

treatments are distinctly grouped by presence/absence of biochar in the compost recipe, which is 

 

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also true when evaluating the biochar treatment effect in the vermicompost (Figure 2.2 b, c, d).  

Principal component analysis of the compost characteristics explained approximately 69% of the 

variation in the data when taking the first two principal components together for all three groups 

comparing biochar amended compost to the control.   

The bi-plots of the first and second principal components demonstrate that the treatments 

are different from each other in regards to their physiochemical characteristics as the contrasts in 

the original variables pull the treatments apart in the visualization.  The loadings of each variable 

as to how much each is related to the principal components is inconsistent for the different 

compost pairings displayed (Figure 2.3).    

Experiment 3: Transplant Performance 

 

Transplants grew in all media (Figure 2.4), with differences between treatments observed 

for early emergence and all plant metrics (Table 2.4).  The differences in growth were driven by 

both inclusion of biochar and ADE as both of these main factors were found to be significant, 

with no interaction between biochar and ADE. 

Seedling emergence data taken at seven days after sowing ranged from 91% in the 

Mix+ADE treatment to 96% for Mix+BC+ADE, with these two treatments differing from one 

another but not from the other treatments which were of intermediate percent emergence (Table 

2.5).  Difference between treatments was driven by inclusion of biochar as a compost 

amendment, increasing emergence by just over 3% (Table 2.4).  There was also a marginally 

significant interaction between biochar and ADE (p=0.072) with biochar increasing emergence 

when ADE was also present. Differences, however, did not last as final emergence data taken at 

ten days after sowing displayed no differences for all compost media or control (range from 97-

98.5%, data not shown).   

 

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Compost treatment differences observed were similar for both the shoot dry and wet 

weights (Table 2.4); mixes containing biochar had greater shoot weights than those without, 

however neither ADE nor biochar additions increased shoot weight relative to the control Mix.  

The differences observed between the peat-based medium and the compost media was more 

pronounced in the wet weights where all treatment means were different than this control, 

whereas for dry weight only Mix+BC was different from the peat control at p<0.05 (Table 2.5). 

Within mixes, plant height had a similar trend as the aboveground biomass, with biochar 

increasing plant height by approximately 14%, and ADE decreasing plant height by 10% (Table 

2.4).  As compared with the peat-based medium, all compost media resulted in taller transplants 

(p<0.05 for all, Table 2.5).  

The number of leaves per transplant ranged between 2.15 in the Mix to 2.29 in the 

Mix+BC+ADE (Table 2.4). Within compost mixes, biochar addition resulted in a small increase 

(approximately 5%) in leaf number, but ADE had no detectable effect.  As compared against the 

peat-based medium, however, all compost root media had more leaves (p<0.001 for all, Table 

2.5).   

For root rating between the compost media treatments there were large differences in root 

growth in response to amendment with biochar and ADE (Table 2.4).  Within mixes, biochar 

increased root ratings by 41%, while ADE reduced root ratings by 24%.  Root rating was the one 

transplant metric for which the peat-medium control had a greater value than the compost media 

treatments (p<0.001 when compared against all other treatments), with the highest rating (5) of 

roots for all transplants assessed (Table 2.5).  This contributed further to the higher root rating : 

dry weight ratio of the peat-control which was higher again than all compost-based media 

 

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(p<0.001).  Within the compost media only, biochar increased and ADE decreased this indicator 

by of partitioning to roots relative to shoots (16% and -18%, respectively).   

 

DISCUSSION 

With any study involving biochar or ADE it is important to note the specifications for the 

production of each material, such as feedstocks, production temperatures, etc. because these can 

all change the properties of the resultant biochar or ADE and how they will interact with 

compost (Laghari et al., 2016; Sun et al., 2014).  For our biochar, a feedstock of pine biomass 

residue from forestry operations produced using pyrolytic fractionation has resulted in a biochar 

material that contained little to no nutrients, and had a pH range of 7-9.  While softwood 

biochars have some nutrient content, it is much lower when compared to biochars made from 

manure or sewage sludge (Ippolito et al., 2020).  The same is true for ADE as the ingestate 

material will greatly affect the quality of the digestate effluent.  The primary ingestate for the 

digester from which we sourced the ADE in this study is dairy manure/material with additional 

inputs of food residue, fats, oils and grease.  Solid and liquid fractions of digestate effluent were 

separated by a screw press.  Analysis of fresh liquid ADE provided by ADREC had an average 

of 303ppm N, 67ppm P, and 264ppm K.   

The hypothesis that C:N would increase with the addition of biochar to the compost was 

supported by both Experiment 1 and 2.  The pairwise comparison only revealed differences 

between treatments in the vermicomposts, however, and not the thermophilic composts.  This 

may have been influenced by the small degree of magnitude in the differences observed, low 

power and having multiple comparisons.  C:N values observed (21-23) were slightly higher than 

the typical desired/expected range of 15-20 for finished compost.  The small range in the C:N 

 

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data between thermophilic compost treatments may have been in part due to the compost not 

being fully mature at the time of sampling as C:N ratios decrease with increased compost 

maturity.  C:N is likely to have decreased more over the ensuing 10 months between the compost 

samples being analyzed and the transplants being grown.  Due to the highly recalcitrant nature of 

BC, it is likely that the C:N of those treatments containing biochar would have declined less than 

the other treatments and differences would become more apparent.  The more mature 

vermicompost did display a difference of a higher C:N with addition of biochar, though as 

previously noted the magnitude of the difference was small.   

The hypothesis that dry bulk density would decrease with the inclusion of biochar in 

compost was supported in Experiment 1 but not in Experiment 2.  This is supported by other 

studies as well (Guo et al., 2019; Husni & Samsuri, 2012).  The bulk density of a softwood 

biochar is approximately 0.14-17g/cc (Guo et al., 2020; Harada et al., 2020), so it could be 

further hypothesized that higher percentages of biochar as a compost feedstock would further 

decrease bulk density based on the bulk density of our control compost at 0.39g/cc. 

Contrary to our hypothesis, biochar addition to compost did not affect pH values of the 

finished compost; however, ADE was marginally significant (p=0.057), decreasing pH with its 

addition.  Despite the statistical differences in pH, the spread of the data was very small, with all 

media having a much higher pH than would be typically recommended for a growing media (5.2-

6.3; Warncke & Krauskopf, 1983).  Compost used for transplant media may need to age or 

mature for longer periods of time to reduce pH, or be amended with peat or sulfur, or finished 

with vermicomposting.  

While there was no difference between treatments for EC of the less mature (5mo) 

compost, mean EC of Mix+ADE was higher than the Mix ten months later.  The net increase of 

 

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EC units of the Mix+ADE over the control is 47.5%; a study by Zhang et al. (2016) using straw-

feedstock biochar and poultry manure compost resulted in an increase in EC of 7.0-37.5%.  

Herrera et al. (2008) found a similar result of high EC compost having a negative effect on 

tomato transplants.  Theirs was a substitution experiment with different percentages of a high EC 

municipal solid waste compost with either old peat or white peat.  The higher EC coincides with 

an increase in a number of the elemental nutrient concentrations in the treatment Mix+ADE 

(Table 1.1).  Raw ADE is known to be high in nutrients as previously discussed in the 

introduction, and its addition to the compost was primarily to elevate nutrient levels so these 

results are to be expected.   

For the purpose of this experiment the environmental parameters were managed as much 

as possible which included the exclusion of rain.  However, in many composting settings this 

would not be true and the effects of biochar in compost may be greater as it may reduce nutrient 

leaching from the compost during rain events.  Biochar effects on nitrogen loss in particular from 

composting systems have been documented in a number of different experiments (Guo et al., 

2020; Major et al., 2009; Steiner et al., 2010).  Using composting systems that do not exclude 

rain, the use of biochar may have more of an impact on nutrient retention than seen in the current 

study. 

The nutrient balance of K, Ca and Mg must also be regarded in an evaluation of the 

compost media.  Besides quantity of soluble K, Ca, and Mg in ppm, there are also 

recommendations for percent of the total soluble nutrients to take into account.  Percent K 

recommended range is between 11 and 13% (Warncke & Krauskopf, 1983), whereas these 

values ranged between 25.1% to 27.4% in the thermophilic compost treatments.  Percent Ca was 

nearly in the recommended range of 14-16% with values ranging from 12.5 to 14.1%.  For Mg 

 

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the values ranged between 2.8 to 3.5%, which is lower than the recommended 4 to 6%.  While 

NO3-N is not generally included in nutrient balance recommendations, the values herein were 

lower than recommended, ranging from 3.6 to 6.9%.  Other nutritional analyses of commercially 

available compost-based planting media have been made that generally have a nutrient balance 

higher of Ca to K.  

The treatments with ADE contained higher ppm levels of Zn as well, in particular 

Mix+ADE (Table 2.3), which is the treatment which consistently performed the poorest in all 

metrics of plant health (Table 2.4).  Manure based digestates analyzed by Alburque et al. (2012) 

found high Zn concentrations, which can pose a problem, as well as Cu.  Cu levels were not 

elevated in our study but were highest for the Mix+ADE treatment (21 and 16ppm Cu for 

Mix+ADE and all other treatments, respectively).  There were a number of other factors that 

made the Mix+ADE treatment different than the others that could have contributed towards the 

decreased transplant growth, however. 

Effects of biochar and ADE compost amendments on plant growth 

The hypothesis that transplants could be produced in the 100% compost media and 

display acceptable characteristics was generally supported for cucumbers in this study, though 

individual growers may differ in what they would consider acceptable transplants.  The roots of 

all compost treatments were under-developed relative to the peat-based media.  Increases in root 

volume and branching have a long-term positive impact on post-transplant success in the field as 

plants would have higher capacity to exploit soil resources (López-Bucio et al., 2003).  The peat-

based control in this experiment had the highest ratings for roots and the highest root to shoot 

ratio.  With the lower nutrient concentrations of this peat media this is in line with a number of 

experiments in which nutrient stress from deficiencies and particularly N deficiency stimulated 

 

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more exploratory forms of roots and a higher adsorbing surface area ratio of roots to leaf area 

(Chung, 1983; Winsor & Massey, 1978).  This is contradicted, however, by the findings of 

Lazcano et al. (Lazcano et al., 2009) wherein increasing proportions of compost to peat had a 

positive impact on root growth for treatments using vermicompost.   

The hypothesis that inclusion of biochar in compost would be a primary factor in positive 

transplant growth responses was also supported.  This may be attributed to a number of 

differences observed to be affected by biochar.  The lower bulk density of the treatments with 

biochar and coupled with the positive growth attributes of transplants grown in the compost 

media with biochar provides further support to the need for lower bulk density media for 

transplant growth.  Bulk density is often cited as a negative aspect of inclusion of compost in 

root media due to its high bulk density (Raviv, 2011), however it appears that inclusion of 

biochar then could help to ameliorate this problem for compost adoption in root media.  

Although total pore space was not measured in this study, it is inversely correlated with bulk 

density and this may favor root growth (Ceglie et al., 2015).  In comparison, the Sunshine potting 

medium had a bulk density of 0.20 g/cc. 

Delayed emergence or non-uniformity of emergence can negatively impact a crop 

production plan and transplant growth.  The difference between the day seven seedling 

emergence and day ten emergence in the compost media indicates a delay particularly for the 

Mix+ADE treatment, and this may have had a lingering effect which may account for lower final 

biomass.  The compost media with higher early emergence performed better for nearly all other 

plant metrics measured at day 21.  The higher EC and concentration of certain elements such as 

Na and Cl in treatments with ADE are likely to have contributed to this delayed emergence, 

similar to the findings of Zhu et al. (2008) and Ebrahimi (2014).  

 

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The high EC of all the compost media may be seen as preventing the compost from 

successfully growing transplants without dilution.  While EC above a certain number is 

considered prohibitively high, the composition of the ions contributing to EC should be taken 

into account.  EC that is high due to the presence of Na and Cl may be detrimental to plant 

growth, high EC due to plant nutrients such as N, K and Ca may not be as detrimental.  An SME 

EC value above 5 for a root medium is considered very high, and anything above 6 would be 

thought to produce severe salt injury symptoms (Warncke & Krauskopf, 1983), however, in the 

present work high EC value composts still produced acceptable transplants.  However, that the 

highest EC compost, Mix+ADE, had the lowest root rating which supports the negative effects 

that EC can have.  Reducing EC by blending high EC composts with lower EC composts, or 

materials such as peat, and having a better idea of a target range for EC when the nutrients are 

coming from compost as opposed to more soluble synthetic forms, could help in the 

development of compost root media. 

One somewhat surprising result of our study was the negative effect of ADE on several 

plant growth indicators.  ADE, particularly effluent with manure or post-consumer food residue 

as a feedstock which is what was used in this study, is known to have high salt concentrations of 

a number of different ions, but Na and Cl in particular can become a problem.  Looking at just 

the Mix+ADE and Mix+BC+ADE treatments, there are elevated levels of Na and Cl in each 

compared to the control Mix.  Sodium as a non-nutritive salt is contributing towards the higher 

EC also found for these treatments as compared to the treatments without ADE.  The Mix+ADE 

consistently had values for all plant metrics lower or equal to the other treatments.  Compared 

specifically to the Mix+BC+ADE the parameters of early emergence, dry and wet weights and 

root rating were all lower (Table 2.4), while the values for nearly all nutrients were not different 

 

85 

between them (Tables 2.3) with the exception of soluble P.  Thomas et al. (2013) found that 

biochar was able to ameliorate the negative effects of sodium chloride sorption of salts.  Manure 

based composts are high in many important nutrients, but also Na which can be a negative as 

possibly seen in this experiment.  Biochar may be able to counteract the addition of Na while still 

maintaining high nutrient levels in the compost for superior plant growth.   

Interveinal chlorosis was observed in five of the 12 replications of transplants from the 

treatment Mix+ADE.  Chlorosis of new leaves in particular may be due to high pH, root issues, 

or imbalances of nutrients (Ding et al., 2006).  Of particular interest are Mg, Mn, and Fe all of 

which are needed for production of chlorophyll.  Manganese and iron were analyzed as parts per 

million of the total nutrients (ash) and no significant differences were observed when comparing 

other treatments to Mix+ADE for these elements, though this does not necessarily rule out the 

possibility of an imbalance of these nutrients.  It is important to note the changes that would have 

happened since the analysis of the compost samples especially in regards to the soluble nutrients 

and possible changes to their relative proportions.  The increase of Na in composts with ADE 

may have thrown off the balance of the other nutrients and made it more difficult for these other 

nutrients to be taken up by the plants; leaf tissue analysis would help assess this but was not 

performed in this study.     

Of note is the small amount of statistical power in the experiment due to the low number 

of replications.  While there are variations in the means between treatments that may at first 

appear to be substantial, when evaluated using Tukey’s HSD there is no significant difference 

between some treatments that were hypothesized.  Greater power through additional replication 

may have identified more differences as significant. 

 

 

86 

FUTURE RESEARCH AND CONCLUSIONS 

Based on knowledge gained from this experiment, future experiments could include 

biochar added at different percentages to assess the relationship of percent change in biochar to 

changes in specific physiochemical characteristics and the different percentages of co-composted 

biochar effects on transplants.  Increasing percentages could determine a target rate beyond 

which the impacts of increased biochar have a negative effect on transplants.  Comparisons could 

also be made of co-composted biochar in media versus fresh biochar as media component for 

growing transplants.  Similarly, testing different rates of ADE added into a composting system 

could help assess whether the negative effects that were observed in the transplants could be 

ameliorated at a lesser rate while still achieving some benefits of nutrient additions from ADE.  

Use of the composts in transplant media could also be adjusted using different percentages mixed 

with another component such as peat, trying to determine a target percentage of root medium. 

Further experimentation could compare performance of different plant species to assess 

the consistency of biochar impacts in root media.  The differential responses of plant variables 

between treatments may be more pronounced in other plant species if tested, such as in results by 

Kaya et al. (2016) in which high salt content resulted in dry matter and chlorophyll reductions 

that were more pronounced in pepper transplants as compared with cucumber.  Cucumbers have 

a much shorter production phase (two to three weeks) as compared with other vegetables such as 

brassicas or solanaceous transplants at four to six weeks, or alliums at 10-12 weeks.  The nutrient 

load of root media and having more slow-release nutrients may have a greater impact when 

production cycle is longer and no supplemental fertilizer is used. 

Future research to build upon the short-term impact on transplants could be a study of 

transplants planted out into the field to assess long-term ramifications of transplant media on 

 

87 

harvestable yield and disease presence/severity.  Elad et al. (2010) have shown that biochar can 

induce systemic resistance in plants, one means by which biochar in media may have long term 

consequences in the field.  In addition, the compost root media could be used for growing plants 

to full maturity in containers and the impact on yield/health in this environment.  Container plant 

culture in protected environments is a subsector of the specialty crop industry that is rapidly 

expanding (Rogers, 2017).  If sowing and growing plants in the compost media to full maturity 

in a controlled environment (no transplanting), the decreased root growth observed initially for 

some treatments may not be an issue as there would not be concern over damage to sensitive 

roots during transplanting.   

Such long-term field-study impacts of use of biochar in transplant media could 

incorporate an economic analysis as to a percentage increase/decrease in yield and profits versus 

the cost of incorporating biochar into media. A multi-year field study could also account for the 

gradual accumulation of biochar in the soil over time and the effect this has on soil properties. 

 

Additional parameters that could be measured in future work include physical 

characteristics such as water holding capacity, total solids, volatile solids, aeration porosity, 

easily available water, water buffering capacity, and total porosity/pore space, CEC, air-filled 

pore space / air-capacity.  Study of the biological changes in compost made with and without 

biochar, as well as adjustment of nutrient levels with ADE, and the relation of these variables 

with transplant performance would further the understanding of the effects of biochar.  If 

analyzed to the species level, a similar statistical analysis using PCA that was used here for 

physiochemical characteristics could be employed to assess differences in the biology of 

different compost as a result of adding BC.    

 

88 

For all plant metric data, the main factors of biochar and ADE were significant.  Based 

upon the data for these transplant metrics, it can be concluded within the confines of this study 

that the inclusion of ADE into the compost media resulted in a decrease in transplant quality, 

while the inclusion of biochar had a positive effect on transplants in these compost-based media.  

Although the values for many of the transplant metrics were higher in the compost based media 

compared to the peat-based media, the opposite was true for root rating, which is of particular 

importance for transplants.  The poor performance of the compost media for this metric indicates 

that all of these composts may need to be blended with other media components to achieve more 

desirable root growth while still maximizing the positive effects on the above ground metrics.  

That the effect of biochar on compost was inconsistent between the thermophilic composts and 

vermicomposts, however, gives pause to any broad statements about biochar at large.  More 

research into biochar / compost systems is needed. 

 
 

 

 

89 

APPENDIX

 

90 

 

Experiment 1 Compost 
Biochar x ADE Interaction 
Mix 
 
Mix + ADE 
 
Main Effect of Biochar 
No Biochar 
Biochar 

 
 

Significance 
(p-values) 

 

0% 
10% 
0% 
10% 

Biochar 
ADE 

Interaction 

 

 

0.39 (0.01) 
0.31 (0.02) 
0.36 (0.01) 
0.32 (0.01) 

0.37 (0.01) 
0.32 (0.01) 

0.007 
0.422 
0.161 

 

 

 
 
 

 
a 
b 
 
 
 

44.1 (2.7) 
53.7 (3.2) 
51.2 (3.6) 
46.3 (1.0) 

70.3 (1.1) 
69.2 (2.0) 
64.9 (2.7) 
67.8 (3.2) 

 

 
 
 

40.8 (0.6) 
40.1 (1.2) 
37.6 (1.6) 
39.4 (1.9) 

 

 
 
 

 
 

 

22 (0.8) 
23 (0.6) 
21 (1.0) 
23 (0.4) 

 

 
21.4 (0.6)  a 
23.2 (0.3)  b 

0.438 
0.959 
0.041 

0.721 
0.210 
0.429 

0.709 
0.214 
0.431 

0.017 
0.238 
0.219 

Table 2.1. Experiment 1 effects of biochar and liquid anaerobic digester effluent (ADE) addition to compost on physical 
characteristics of dry bulk density and moisture as well as organic matter, carbon and C:N. Experiment 2 effects of biochar addition 
to vermicompost on bulk density, moisture, organic matter, carbon and C:N. Mean (+SE, n=3) for all. 
Organic Matter 

Dry Bulk Density 

Moisture 

Carbon 

C:N 

Rate of Biochar 

g/cc 

% 

% 

% 

Experiment 2 Compost 

Rate of Biochar 

Vermicompost 
Vermi + BC 

0% 
10% 

p-value 

 

Bulk Density 
0.47 (0.03) 
0.50 (0.00) 

0.374 

  Moisture (%) 
63.2 (0.4) 
 
64.1 (0.3) 
 
 

0.162 

Organic Matter 

(%) 

64.4 (0.6) 
65.6 (0.5) 

0.174 

Carbon (%) 
37.4 (0.3) 
38.0 (0.3) 

C:N 

11 (0.3)  a 
12 (0.1)  b 

0.200 

0.031 

Means followed by the same letter in the same column are not statistically different (p<0.05) according to Tukey's HSD test 
 
 

 

 

91 

Table 2.2. Experiment 1 effects of biochar and liquid anaerobic digester effluent (ADE) addition to compost on compost pH and EC 
at 5 and 15 months old (mo). Experiment 2 effects of biochar addition to vermicompost on pH and EC. Mean (+/- SE, n=3) for all.  
*EC (15mo) 

EC (SME, 5mo) 

Experiment 1 Compost 
Biochar x ADE Interaction 
Mix 
 
Mix + ADE 
 
Main Effect of ADE 
No ADE 
ADE 

Significance 
(p-values) 

 

 
Rate of Biochar 

pH 
5 mo 

pH 
15 mo 

0% 
10% 
0% 
10% 

 
 
Biochar 
ADE 
Interaction 

 

 

8.6 (0.12) 
8.7 (0.00) 
8.6 (0.03) 
8.3 (0.12) 

 

 

8.3 (0.09) 
8.3 (0.03) 
8.1 (0.03) 
8.2 (0.03) 

8.7 (0.06) 
8.5 (0.08) 

8.3 (0.04) 
8.1 (0.03) 

0.463 
0.057 

0.143 
0.010 

0.098 

0.742 

 
 
 

a 
b 

 

 
 
 

 

 

dS m-1 

4.0 (0.43) 
4.7 (0.36) 
5.9 (0.23) 
5.6 (0.90) 

4.3 (0.3) 
5.7 (0.4) 
0.627 
0.035 

0.282 

 
 
 
 
 
 
 
 

dS m-1 

 

7.0 (0.33) 
8.3 (0.44) 
9.5 (0.61) 
10.2 (0.69) 
 

 

 

a 
b 

 
 
 

7.6 (0.4) 
9.9 (0.4) 
0.016 

<0.001 
0.218 

a 
b 

a 
b 

 
 
 
 
 

Experiment 2 Compost 

Rate of Biochar 

Vermicompost 
Vermi + BC 

P 

0% 
10% 
P 

pH 

6.7 (0.06) 
6.6 (0.09) 

0.561 

EC 

12.0 (0.00) 
10.8 (0.24) 
0.007 

*EC values for 15mo compost were converted from EC values obtained from a 1:2 compost:water dilution using a conversion factor 
of 2.8 * EC (1:2). Conversion factor was calculated from ratio of SME EC to 1:2 EC readings from Warncke and Krauskopf, 1983 
Means followed by the same letter in the same column are not statistically different (p<0.05) according to Tukey's HSD test 
 

 

 

92 

Table 2.3. Experiment 1 effects of biochar addition and anaerobic digester effluent (ADE) on compost soluble nutrients. Experiment 
2 effects of biochar addition to vermicompost on soluble nutrients. Mean (+/- SE, n=3) for all. 

 
Rate of Biochar 

Experiment 1 Compost 
Biochar x ADE Interaction 
Mix 

NO3-N 
ppm 

P 
ppm 

K 
ppm 

Ca 
ppm 

 

 
145 (17) 

 

 
7.3 (1.1)  b  997 (78)  362 (21) 

 

 

 

 

Mg 
ppm 

 

 
95 (7) 

121 (22) 

6.0 (0.2)  b 

1170 
(107) 

413 (24) 

109 (9) 

268 (29) 

7.8 (0.4)  b  1349 (37)  520 (30) 

116 (8) 

Na 
ppm 

 

 

36 (0.3) 

36 (3.5) 

Cl 
ppm 

 
616 (44) 

758 (68) 

123 (5.5) 

854 (23) 

117 (9.3) 
 

932 (123) 
 

 

 

 

0% 

10% 
0% 

10% 

284 (99) 
 

 

 

 
Biochar 
ADE 
Interaction 

113 
(13) 
276 
(46) 
0.561 
0.018 
0.768 

 
Mix + ADE 

 
Main Effect of ADE 

No ADE 

ADE 

Significance 
(p-values) 

 

Vermicompost 

Experiment 2 Compost  Rate of Biochar  NO3-N 
1009  
(4) 
895  
(7) 

Vermi + BC 

10% 

0% 

p-value 

 

<0.001 

 

545 (78)  123 (25) 
 

 

 

a 

1266 
(126) 
 

11.4 (1.1)  a 
 
 
a  1084 
(71) 
b  1308 
(62)  b 
0.603 
0.049 
0.190 

6.7 
(0.6) 
9.6 
(0.9) 
0.132 
0.004 
0.008 

 
 
387 
a   
(18) 
533 
(38)  b   
0.379 
0.040 
0.572 

 

 

0.517 
0.256 
0.874 

36 
(1.6) 
120 
(4.8) 
0.573 
<0.001 
0.852 

a 

b 
 
 
 

a 

b 

687 
(48) 
893 
(58) 
0.185 
0.028 
0.487 

P 

163.8  
(5.1) 
145.5  
(18.4) 
0.394 

 
 

 

 

 
a 

K 
2388  
(28) 
2184  
(48)  b 
0.021 
 

Ca 
567  
(16) 
514  
(7) 
0.037 

  Mg 
227  
a 
(3) 
210  
(6) 
0.038 

b 

 

b 

 

 
  Na (ppm)    Cl (ppm)   
 
a 

 

247 
(4.8) 
223 
(7.0) 
0.052 

 

 

562 
(15) 
521 
(19) 
0.166 

 

 

a 

b 

 
a 

b 

Means followed by the same letter in the same column are not statistically different (p<0.05) according to Tukey's HSD test 

 

93 

Table 2.4. Effects of biochar addition and anaerobic digester effluent (ADE) in compost media on emergence and plant growth 
responses. Mean (+/- SE), n=4. 
 

Shoot Wet 

 

Early Emergence 

Shoot Dry 
Weight 

Weight 

Plant 
Height 
(cm) 

Root Rating  Root Rating :  
Dry Weight 

(1-5) 

(%) 

(g) 

(g) 

92 
(1.2) 
95 
(1.1) 

93 
(1.1) 
93 
(1.2) 

 
a 

b 
 

 

 

 

 

0.22 
(0.01) 
0.26 
(0.01) 

0.25 
(0.01) 
0.23 
(0.01) 

 

 

 

a 

b 
 

a 

b 

2.87 
(0.13) 
3.34 
(0.13) 

3.22 
(0.13) 
2.99 
(0.14) 

a 

b 

 

 

 

 

 

 

12.0 
(0.5) 
13.8 
(0.5) 

13.4 
(0.5) 
12.1 
(0.5) 

 

 

 
a 

b 
 

a 

b 

Leaves 

# 

2.17 
(0.04) 
2.28 
(0.05) 

 
a 

b 
 

 

 

2.21 
(0.04) 
2.24 
(0.05) 

 

 

2.18 
(0.14) 
3.07 
(0.17) 

2.99 
(0.15) 
2.27 
(0.17) 

 

 

 
a 

b 
 

a 

b 

9.95 
(0.45) 
11.53 
(0.40) 

11.80 
(0.39) 
9.68 
(0.41) 

 

a 

b 
 

a 

b 
 
 
 
 

Root Media 
Main Effect of Biochar 

No Biochar 

Biochar 

Main Effect of ADE 

No ADE 

ADE 

 

p-values 
Biochar 
ADE 
Interaction 
Means followed by the same letter in the same column are not statistically different (p<0.05) according to Tukey's HSD test 
 
 

<0.001 
0.019 
0.328 

<0.001 
<0.001 
0.567 

0.043 
0.888 
0.072 

0.007 
0.021 
0.326 

0.041 
0.537 
0.837 

0.001 
0.099 
0.602 

 

 

 

 
 
 
 

 

 
 
 
 

 
 
 
 

 

 
 
 
 

 
 
 
 

 
 
 
 

 

0.005 
<0.001 
0.612 

 

 

94 

Table 2.5. Comparison of compost-media treatments with peat-medium control for mean (+/- SE, n=12) emergence and plant growth 
responses. Asterisks indicate significant differences between treatments and the peat-based control using Dunnett’s test. 

Early Emergence 

Shoot Dry 
Weight 

Shoot Wet 

Weight 

Root Rating  Plant Height  Leaves  Root Rating:  
Dry Weight 

(g) 
0.20 
(.01) 

(g) 
1.75 
(0.06) 

0.24 
(.02) 
0.27 * 
(0.01) 
0.20 
(0.02) 
0.26 
(0.01) 

3.00 ** 
(0.19) 
3.44 *** 
(0.19) 
2.75 * 
(0.19) 
3.25 *** 
(0.19) 

(1-5) 
5.00 
(0.00) 
2.59 *** 
(0.14) 
3.39 *** 
(0.22) 
1.77 *** 
(0.17) 
2.76 *** 
(0.22) 

(cm) 
7.7 
(0.7) 

12.9 ** 
(0.7) 
14.0 *** 
(0.8) 
11.0 * 
(0.5) 
13.2 *** 
(0.7) 

# 
1.63 
(0.03) 
2.15 *** 
(0.05) 
2.27 *** 
(0.06) 
2.19 *** 
(0.06) 
2.29 *** 
(0.07) 

24.98 
(1.46) 

11.14 *** 

(0.50) 

12.45 *** 

(0.54) 
8.76 *** 
(0.57) 

10.61 *** 

(0.48) 

Root Media 

Rate of 
Biochar 

Peat-Based Media 

Mix 

 

Mix + ADE 

0% 

10% 

0% 

(%) 
98 
(1.5) 
93 
(1.5) 
94 
(1.8) 
91 . 
(1.9) 
96 
(1.2) 

10% 

 
Significance levels for Dunnett's Test: '***' 0.001, '**' 0.01, '*' 0.05, '.' 0.1 
 
 

 

95 

1 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 2.1.  Root ratings scale for transplant root assessment ranging from 1 to 5 which were used in the visual assessment of 
transplants.   
 
 
 

5 

2 

3 

4 

 

96 

 

Figure 2.2.  Principal component analysis biplots of the first and second principal components 
for compost physiochemical properties of A) all four thermophilic composts, B) Mix and 
Mix+BC only, C) Mix+AD and Mix+BC+AD only, and D) Vermicomposts.  The percentages of 
the total variance accounted for by each principal component are indicated in parentheses in axis 
titles. 
 

 

 

 

97 

 

 

 

 

 
Figure 2.3. Loading contribution of compost physiochemical characteristics for interpretation of 
PCA values of PC1 and PC2 for A) all four thermophilic composts, B) Mix and Mix+BC only, 
C) Mix+AD and Mix+BC+AD only, and D) Vermicomposts.

 

98 

  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 

Figure 2.4.  A subset of eight plants from one of the replications from each compost treatment A) Mix; B) Mix+BC; C) Mix+ADE; 
and D) Mix+BC+ADE. 

99 

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FEEDSTOCK EFFECT ON COMPOSTING WORMS AND VERMICOMPOST 

NUTRIENTS AND MICROBIAL COMMUNITY FUNCTION

CHAPTER III 

 

 

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ABSTRACT 

A laboratory bioassay was used to determine the effects of five common kitchen 

preparation food residue feedstocks on earthworms and the microbial community, and the 

nutrient quality of the finished vermicompost.  Carrot, melon, pineapple, onion, spent coffee 

grounds (SCG), and a mixture of all five at equal proportions by volume were added to 

earthworm cultures established in compost twice weekly for five weeks at rates estimated to be 

one-half worm body mass per day and compared with a no feed control treatment.  Worm 

populations as indicated by mass did not change over the course of the bioassay and were the 

same in all treatments, indicating no negative effect of any food on the worms.  The microbial 

community was assessed by using Biolog-EcoplatesTM for community-level physiological 

profiles (CLPP).  The SCG vermicompost had equivalent or higher estimated microbial biomass, 

substrate richness and functional diversity relative to other treatments.  The food mixture (which 

included a lower percentage of SCG) had intermediate values between that of SCG and the other 

feedstocks.  Nutrient values for both soluble and total nutrients differed by treatment as well.  

For example, the SCG treatment had lower NO3-N but higher total N (2.4%) compared to the 

food mix (2.1%) as well as all single-feedstock treatments (1.5-1.7%). 

. 

INTRODUCTION 

Vermicompost is organic material that has been processed under protected/managed 

conditions by a dense population (target of 1 lb/ft2) of composting worms, in a time frame 

resulting in a mixture of worm castings and other organic matter (C. A Edwards et al., 2010).  

There are only about six species of worms out of thousands of species that are used 

commercially as composting worms.  The most prevalent worldwide across tropical, subtropical 

 

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and temperature climates is Eisenia fetida, more commonly called the red wriggler or tiger worm 

(James & Guimaraēs, 2010).  Beyond the presence of worms having processed the material, the 

primary distinction between vermicompost and thermophilic or hot compost is the temperature at 

which material is converted to stable humic-rich organic matter.  While the primary microbial 

activity of thermophilic compost is above 130°F, vermicompost microbial activity occurs at 

mesophilic temperatures, generally between 50-80°F (Dominguez & Edwards, 2011).  

Vermicompost frequently sells for a higher price than hot compost if being sold, driven in part 

by limited production and thereby supply as well as conceptions of its superior attributes as 

compared to thermophilic compost, whether accurate or not.  The particle size is often smaller, as 

a result of passing through the worm.  There is an important distinction, however, between 

vermicompost and worm castings which is the material that did specifically pass through the gut 

of a worm, whereas vermicompost is a mixture of castings and other organic matter.  The 

microbial community in vermicomposts has been demonstrated to be markedly different than 

that of thermophilic composts, even if made from the same starting feedstocks (Neher et al., 

2013).   

The amount of food wasted in the US and around the world has been gaining heightened 

attention with recent estimates that as much as 40% of food produced in the US is not consumed 

by people.  The most recent data compiled by the USEPA (from 2017) was that of the 270 

million tons of municipal solid waste generated in the US, 27 million pounds (10%) was 

composted, despite the fact that 60% of the waste was compostable, whereas 139 million tons 

(52%) was disposed of in landfills (US EPA, 2017).  Of what was landfilled, 21.9% is food 

waste, whereas only 2.7% of composted material is food waste.  Long-term nutrient extraction 

from the soil and deposition to landfills instead of resupplying the soil is not sustainable.  Food 

 

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waste is an ideal food for worms to produce vermicompost due to its high moisture content and 

nutrients.  However, there is concern over some of the more common kitchen preparation food 

waste materials regarding possible negative effects on composting worms (Angima et al., 2011; 

Dickerson, n.d.; Sherman, 2017).  Some concerns stem from the pH or the perceived pH of 

material in that it may be too acidic for maintaining a healthy worm population (Harris, n.d.; 

Shaw, 2011).  For the MSU project of vermicomposting dining hall pre-consumer kitchen 

preparation residue there is often a predominance of pineapple skins, melon rinds/insides, onions 

layers and skins, and carrot peels.  Onion is a food source that has been singled out to not feed to 

worms, as well as high acid food which would include pineapple (Angima et al., 2011; 

Dickerson, n.d.; Sherman, 2017).  These are prevalent food residues from MSU making these of 

particular interest in this study.  Other common food residues are melon rinds/insides, and 

carrots/peels. 

Spent coffee grounds (SCG) are also prevalent coming from dining halls and coffee 

shops.  Coffee is an abundant food residue with annual production at approximately six million 

tones worldwide, or 650 kg SCG per 1 ton of green coffee, which has been generally landfilled 

(Mussatto et al., 2011).  This abundant material could be labeled a resource instead of 

environmental pollutant through its valorization but more research has been called for (Stylianou 

et al., 2018).  It has been identified as a preferred feedstock for worms and often as a sole food 

source by some vermicomposters (Shaw, 2011), though the specifics of how this feedstock 

affects worms and finished vermicompost has not been sufficiently evaluated.  This is another 

prevalent food residue coming from MSU campus to the worm composting facility. 

Feedstocks are anticipated to affect the biology of the compost, especially as the nutrients 

and food type (proteins, starches, sugars, etc.) contained therein can inhibit or promote growth of 

 

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certain genera/species (bacterial, fungal, higher organisms) over others.  Abundances and 

diversity of microorganisms at different stages of vermicomposting have been reported as well 

(Chen et al., 2015; Gómez-Brandón et al., 2011, 2012; Gopal et al., 2017; Vivas et al., 2009).  

Still other studies have looked at finished vermicompost for presence of plant-beneficial 

microbes (Gopal et al., 2009; Pathma & Sakthivel, 2013; Raphael & Velmourougane, 2011).  

Knowledge of the microbiology resulting from specific feedstocks could be related to these and 

other studies if attempting to achieve a desired microbial population. 

A vermicomposting laboratory bioassay was developed to determine the effects of the 

five feedstocks on the worms, the microbial community, and the nutrient quality of the compost.  

The feedstocks were single ingredients of melon (rind and seed cavity), carrot (primarily peel), 

pineapple rinds, onion (skin and layers) and SCG, as well as a mix of all together.  Food waste 

feedstocks for vermicomposting are more likely to be mixed instead of single-source; however, 

knowledge of how each might affect the finished vermicompost and earthworms advances 

vermicompost technology.  At MSU specifically, this information could help to guide what is 

vermicomposted on campus if a specific residue was found to be particularly deleterious or 

beneficial to the worms or vermicompost.  We hypothesized that the worms would survive in all 

treatments, but there would be differences between treatments in worm biomass at the 

termination of the vermicomposting process.  Specifically, we hypothesized that the mixture 

would be the food that enhanced growth of the biomass of the worm the most.  Regarding 

microbial community, we hypothesized that there would be differences in the community-level 

physiological profiles (CLPP) between treatments, and the mixture would have the highest level 

of microbial diversity and abundance as determined by Biolog EcoPlatesTM.  Lastly, we 

 

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hypothesized that the worm food sources would affect pH, EC and specific nutrient 

concentrations of the vermicompost produced. 

 

MATERIALS AND METHODS 

Feeding Treatments and Experimental Design 

Eisenia fetida were isolated from earthworm bins at the vermicompost research facility 

and established in recycled cafeteria food service plastic bins of 4” x 20” x 4” depth with two 

liters of a moistened immature compost as bedding (compost feedstocks of softwood shavings, 

hay, straw, and peat).  The compost bedding had been maintained in an indoor laboratory space 

at MSU (70°F), and was not fully decomposed, still having some structure of original materials 

such as stems of grass/straw.   Each bin (0.55ft2 surface area) was established with 150g (0.6 

lb/ft2) composting worms at the start of the experiment.  The feedstock treatments were 1) 

Control (no food added), 2) carrot, peels and whole, 3) melon, rinds and seed cavity, 4) 

pineapple, skins, 5) onion, skins and whole, 6) spent coffee grounds (SCG), and 7) a food 

mixture of 2-6 at equal parts by volume.  Samples of all feedstocks were oven dried to obtain 

moisture content which was approximately 90% for each. 

Buckets were provided to the food preparation kitchen at MSU for the purpose of 

separating the common food preparation residues.  The food was prepared for worm trial by 

grinding with a food processor to a puree, with the exception of the moist SCG that were used 

directly.  The food was primarily the discarded portion (melon rinds, pineapple skins, onion skin, 

carrot peel) though for the carrot and onion there were some whole vegetables that were no 

longer edible.   

 

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Each experimental unit was one worm bin/tray with two liters volume of starting bedding 

material.  There were four replications of each treatment for a total of 28 vermicomposting bins, 

arranged on a vertical/stacked shelving unit (Figure 3.1A).  Replications were assigned positions 

at random, each shelf having one replication, comprising a randomized complete block design 

(RCBD). 

Vermicompost Management and Data Collection 

Worms were fed the equivalent of half of the earthworm body weight per bin, per day, 

distributed by 262g feedings twice weekly.  The food was put on the compost/bedding surface 

and covered with a thin layer of shredded leaves, then moistened with water from a 0.5 L hand 

pump sprayer (Figure 3.1B).  Fresh food was placed on only one half of the bin each week, 

alternating which half received food.  This was in accordance to feeding protocol in use at a 

larger scale at the MSU HTRC mid-scale vermicomposting facility to ensure worms could move 

away from the added food if necessary.  Bins were weighed weekly to guide water applications 

and maintain moisture uniformity as supplemental water was added.  Multiple layers of 

newspaper were also layered on top of the bins (above the surface of the compost) to maintain 

low light and humid conditions.  Feeding lasted a total of five weeks, with four additional weeks 

for the worms to finish composting the freshest material, during which time the vermicompost 

was mixed and watered weekly.  

The earthworms were re-isolated at the termination of the experiment and weighed.   

At the end of the trial a sample of each vermicompost, collected from the thoroughly 

mixed content of each container, was analyzed for chemical and physical properties.  Key 

responses measured from mature compost samples were for nutrients including water soluble 

nutrients using saturated media extract (SME) (pH, EC, ppm nitrate-N, ammonium-N, P, K, Ca, 

 

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Mg, Na, Cl), and total nutrients (% N, P, K, Ca, Mg, S, Na; ppm Zn, Mn, Fe, Cu, B, Al), organic 

matter (%) and moisture (%).  Percent carbon and the carbon to nitrogen ratio were calculated 

from the data and nutrient balance (percent of each nutrient contribution to the electrical 

conductivity) was also calculated using the equation  

[1]  % Element  = ((ppm element) / (EC mg/L * 700)) * 100 (Warncke & Krauskopf, 1983). 

CLPP of the microbial communities was determined using Biolog EcoPlatesTM (Biolog 

Inc., CA, USA) to provide an assessment of the functional diversity and estimation of microbial 

biomass.  The culturable soil microbial population was exposed to 31 distinct carbon sources and 

a water control well within a 96-well plate, each replicated three times.  A procedure based on 

field soils by Garland and Mills (1991) was adapted for use with compost.  Ten grams moist 

compost from each treatment replicate sample (n=3) were shaken in 90 ml of a sterilized saline 

solution (0.85% NaCl, w/v) for 60 min, pre-incubated for 18 h at 23 °C, and then brought to a 

final dilution of 103 before 150 µl aliquots were added to each of the 96 wells (1 plate per 

treatment replicate). Reduction of tetrazolium dye in the wells by the respiration of microbes 

results in color change (clear to purple) indicating use of the carbon source.  Plates were 

incubated at 23°C for 7 days, during which time color development in each well was measured at 

24 hour intervals as absorbance at 590 nm using a microplate reader (Model 680, Bio-Rad 

Laboratories, Hercules, CA).  The overall degree of substrate use was expressed as average well 

color development (AWCD), calculated as the mean difference between carbon source 

absorbances (Ri) and the absorbance reading for the control well (C) within plate replicates 

(Garland and Mills, 1991):  

 [2] AWCD  =      

∑Ri −C 

 

 

31 

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Substrate richness (S) was calculated by the number of carbon substrates that were oxidized 

(from 0 to 31 possible substrates utilized).  The Shannon-Wiener diversity index (H)  and 

evenness (E) were calculated using the following equations (Spellerberg & Fedor, 2003; Zak et 

al., 1994): 

[3] H = ∑ Ri(lnRi) 

[4] E = H/logS 

where Ri is the ratio of the corrected absorbance values of each well to the sum of absorbance 

value of all wells.  The Shannon-Wiener diversity index provides information on the functional 

diversity of the compost microbial community.  Evenness is a measure of the equitability of 

activity across all of the utilized substrates (Zak et al., 1994).  Patterns of substrate use were 

investigated after first dividing the control-corrected absorbances (Ri - C) by AWCD within 

plate replicates to reduce potential bias due to differences in inoculum density among samples 

(Garland, 1997).   

Statistical Analysis 

Chemical, physical, and biological properties of the composts and final weight of the 

worm population were analyzed for treatment significance by analysis of variance (ANOVA).  

Significant differences between means of treatments were determined by pairwise comparison 

using Tukey’s Honestly Significant Difference (HSD) test (P≤0.05).  For the worm population 

data only, a decrease in the no-food Control was anticipated and therefore not included in the 

pairwise comparison that was to assess the foods’ effect on the worms.  Data analyses were 

carried out using R statistical software package, and multcomp package (glht function) for 

pairwise comparisons (R Core Team, 2019).  For all data, normality was determined by 

univariate procedures and Sattherthwaite’s degrees of freedom was employed to account for 

 

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potential nonequal variance in the data.  Where normality assumptions were violated, the data 

were log transformed prior to analysis. 

 

RESULTS 

Worm Growth and Health.  Based on visual assessments at each feeding, there were no 

obvious negative impacts on the worm populations for the duration of the experiment.  

Additionally, worms appeared to readily move into the fresh material shortly after it was applied.  

Final mass of worms for some food treatments differed.  The Carrot, Pineapple and Mix 

treatments mass of worms (range of 139-148g) were different only from the Melon treatment 

(120g) and not from the Onion and SCG (Table 3.1).  The mass decrease observed from the 

original 150 g ranged from 1-21% for food treatments while the worm mass of the Control 

decreased by 64%.  The water equivalent of what the other treatments received in the food 

(feedstocks at 89% moisture) was added to the no-food bins to ensure that it was not moisture 

that was a limiting factor on growth.   

Microbial Community Analysis.  Compared to the Control, differences in substrate 

richness and functional diversity (Shannon-Wiener Diversity Index) were only detected for 

Carrot, SCG and the Mix treatments (Table 3.2).  The SCG had greater functional diversity than 

the Control, Melon, Pineapple and Onion treatments, but was equivalent to the Carrot and Mix.  

Substrate richness ranged from 21.2 (Control) to 27.7 (SCG), and the functional diversity index 

ranged from 2.74 (Control) to 3.08 (SCG).  Substrate evenness, however, did not differ between 

treatments (2.07-2.13).  The estimation of microbial biomass (using AWCD) had a smaller range 

of values from 0.46 (Onion) to 0.70 (SCG); SCG had greater microbial biomass than all 

treatments other than Carrot and the Mix for which it was equivalent. 

 

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Chemical Analysis.  All treatments other than SCG and Mix produced similar results in 

regards to final percent organic matter or percent carbon with values ranging from 48-53.7% 

(Table 3.3).  The SCG treatment, however, had a higher percent organic matter at 73.7% than all 

other treatments, while the Mix (58.3%), with SCG incorporated into the feed at 20% by volume, 

was also higher than all but the Control and Pineapple.  The percentage C, having been 

calculated from the organic matter followed the same trend, with SCG with the highest values at 

42.3%.  The C:N ratio of all treatments were not different from one another, spanning from 16.3 

(Mix) to 20.7 (Control).  Moisture content was marginally significant (p=0.055) where it would 

appear that SCG may have had greater moisture than the other treatments (at p<0.1).  

There were differences in the EC and pH values observed (Table 3.4).  EC values were 

highest for the Melon and Carrot treatments at 13.7 dS/m (though equivalent with Onion).  EC of 

SCG was the lowest by a factor of almost four in comparison with all other treatments at 

2.5dS/m (Table 3.4).  The pH differed by treatment with the Control at the lowest pH of 5.5 and 

Carrot the highest at 9.1 followed by Pineapple (8.2).  The other food treatments had equivalent 

pH, near neutral. 

There were differences observed between treatments for all soluble and total nutrients with the 

exception of NH4-N (Tables 3.4, 3.5).  Of the soluble nutrients, the nutrient values from SCG 

were all lower than or equivalent to the other treatments, of particular note are NO3-N (5ppm), 

and Ca (405ppm).  The Control, in contrast had higher values for a number of soluble nutrients, 

including Mg (279ppm) and NO3-N (988ppm).  Some total nutrient concentration values of note 

are the higher N in SCG (2.4%), higher K in compost from Carrots (2.9%), higher S in compost 

from Onions (0.38%), higher Zn in compost from Melons (104.7ppm), and higher Mn in 

compost from Pineapple (318ppm, although not different from Onions, and then Onions from 

 

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others).  The treatments Carrot and Melon had similar profiles of nutrients, differing from one 

another only for total K (Carrot 2.9% > Melon 2.2%) and Zn (Melon 104.7ppm > Carrot 

75.7ppm) and in soluble Mg (Melon 172ppm > Carrot 80ppm) and Na (Melon 445ppm > Carrot 

235ppm). 

 

DISCUSSION 

The hypothesis that composting earthworms would survive in all treatments is supported 

by the data of the worm biomass at the termination of the experiment, as was the hypothesis that 

there would be differences in earthworm biomass between treatments at the termination of the 

experiment.  The hypothesis that the Mix would enhance the growth of the biomass the most was 

not supported as no treatments increased the biomass of the worms, and the final earthworm 

biomass in the Mix was not different than all food treatments except Melon.  The primary 

difference observed was between the food treatments and the no-food control where it was 

expected that worm biomass would decline, which it did.  Inconsistent with our findings, Liu and 

Price (2011) observed a reduced worm growth/survival in SCG treatments, though this effect 

was decreased with cardboard additions which may have had a similar effect as the compost 

bedding used in our study.   

The data in this experiment are from one point in time after a total period of 56 days, five 

weeks of feeding, and four additional weeks wherein no new food was added but the worms had 

additional time to process material.  At this high density of worms present, along with the stable 

temperature and moisture conditions, it is a reasonable expectation that the majority of the 

feedstock would be processed by the worms (Clive A. Edwards, 2011).  The time frame, 

however, would not have allowed for reproduction of worms and their growth/decline may have 

 

118 

become more apparent with a longer experimental duration.  It is important to note that 

individual worms were not counted.  While the worm population can be inferred by the data 

collected, the reality could be that some worms died while others grew larger.  Also common in 

vermicomposting can be worms leaving a bed system if conditions become unfavorable, and this 

was not observed in any of the treatments.  The relative consistency of final worm mass 

regardless of treatment indicates a stable density of approximately 300g-worms/ft2 in this 

container system, but a longer term study would help to evaluate what the optimal socking 

density would be under these conditions as the worm population would have the chance to 

stabilize over time by reproduction.  

There were differences observed between treatments in their CLPP as hypothesized, with 

the impact of SCG on the microbial community being of particular interest.  In SCG 

vermicompost all parameters measured/calculated were higher or equal to the other treatments.  

Some possible relationships may be with the higher organic matter and nitrogen present.  The 

coffee seeds may contain more complete, complex, or diverse compounds to be digested, which 

enhanced the microbial community resulting in the CLPP seen.  The hypothesis that the Mix 

would have the highest level of microbial functional diversity and abundance was not supported, 

though it was equivalent to the SCG in all of the parameters.  The Mix might be assumed to have 

the most complex assemblage of different compounds as it contains all of the individual foods, 

but if this is true, it did not result in a more diverse microbial community relative to the other 

treatments.   

Changes in the microbial community over time were not measured here, but rather the 

microbial community function assessed at one point in time.  Findings by Gopal et al. (2017) in 

which samples were taken at four different intervals (when worms were introduced to material at 

 

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day 15, 45, 75 and 105 days) displayed significant differences in microbial community structure 

at the different points in time, with the highest abundance of microbes at day 75 of their study, 

which based on when they inoculated their substrate with composting earthworm was 

approximately equal in timing to our analysis of microbial community function.  Whether the 

biological differences seen between vermicomposts with the different substrates would be 

consistent over time would need to be evaluated with a longer duration study in which material is 

assessed multiple times. 

Feedstock treatment did affect the concentrations of all soluble and total nutrients except 

NH4-N.  Differences observed between the SCG feedstocks and the others are the most distinct 

in all the treatments, particularly with regard to N.  SCG had the highest total N at 2.4%, while 

there was nearly an undetectable quantity of soluble NO3-N (Tables 3.3 and 3.4).  The 

differences between soluble N and total N may in part be due to the N being assimilated in the 

bodies of the microbes, which may create a kind of slow-release fertilizer over time as microbes 

cycle and decay, and mineralize more soil organic matter.  The recalcitrant nature of SCG 

(Shofie et al., 2015) may also be contributing to this lack of soluble N for such a short duration 

vermicomposting experiment.   There could also be inhibition of mineralization and nitrification.  

The SCG treatment final volume was approximately 50% larger than the other treatments as the 

material did not appear to be as digested or reduced in volume at the termination of the study.  

Regarding other soluble and total nutrients, SCG was lower or equal to the other treatments for 

all (with the exception of total N).  Our results contradict that of Adi and Noor (2009) that 

addition of SCG enhances the quality of vermicompost in regards to nutrients as opposed to 

kitchen scrap vermicomposting alone.  The only nutrient that was enhanced in their trial as well 

as ours was the total N.   

 

120 

The observation that the Control treatment had the highest values for soluble NO3-N and 

Mg is of interest, as well as having high concentration of P, though this was not higher than the 

Mix, Melon or Onion.  One possible explanation is that the microbial biomass was lower than the 

other treatments, possibly due to no fresh / degradable food added, and not as many nutrients 

were sequestered in the microbial biomass itself.  Soluble P (measured by SME) for peat-based 

media is often related to the pH (lower pH, higher P) and the pH is lowest in the Control, but 

there is not a consistent trend in these results. 

There has been concern circulated over pH of bedding/feedstock material becoming too 

acidic for composting earthworms, such as if using a high acid food like pineapple (pH 3.2-3.7, 

Bridges & Mattice, 1939).  Out of all of the feedstocks tested, however, the pineapple feedstock 

treatment had the second highest pH of the finished vermicompost.  That the final pH values 

were so high contradicts the findings of Garg et al., (2012) in which the acidity of their finished 

vermicompost was more acidic than the starting feedstocks.  The decomposition of the material 

is attributed to the decrease in pH as humic acids and other ions are formed.  

Future research:  While the results of this experiment indicated that there was no 

negative effect on the worm population, the short duration of the experiment did not allow 

sufficient time to assess any potential effects on reproduction.  A longer study in which 

reproduction is assessed by looking at cocoons and actual worm numbers for population instead 

of mass as an indication of density would further elucidate the effects of specific feedstocks.   

The experimental design of the feedstock vermicomposting bioassay can be used for 

testing other parameters of a vermicomposting system such as temperature, the limits of EC 

where worm health drops off (as measured either by mass as it was herein, or by number of 

worms), pH, addition of various minerals, or use of different feedstocks.  Additional feedstocks 

 

121 

have a conception of being negative or positive, as taught by extension publications, in 

workshops and online with frequency such as citrus (negative) or banana peels (positive), but 

they have not been evaluated specifically (Dickerson, n.d.; Sherman, 2017).  The compost 

bedding was not sufficient to sustain the worm population, and so establishing a different 

baseline against which to test other feedstocks would be warranted.  A limitation with this 

bioassay, however, was the amount of time required to isolate worms for the bins and 

improvements in the method could be made.   

Further analysis of microbial communities may be benefited from more refined 

techniques to determine genus/species composition.  Beyond production and testing of 

vermicompost, future work may involve experiments to evaluate how these microbial 

communities affect plant growth and the long-term impact on the rhizosphere when 

vermicompost is incorporated into soils or used for transplant production.  

 

122 

 

 

APPENDIX 

123 

Table 3.1. Microbiology of composts determined by Biolog Ecoplates for species richness, 
Shannon-Wiener Diversity Index, substrate evenness, and AWCD by vermicompost feedstock 
treatment. 

Feedstock 

NoFood 
Carrot 
Melon 
Pineapple 
Onion 
Coffee 
Mix 

P 

Species Richness  Shannon-Wiener 
Diversity Index 
a 
2.74 (.04) 
21.2 (.9) 
25.8 (.6) 
2.98 (.03) 
bcd 
abc 
2.89 (.07) 
24.6 (1.4) 
ab 
2.82 (.04) 
22.4 (.6) 
23.4 (.5) 
2.86 (.03) 
ab 
d 
3.08 (.03) 
27.7 (.5) 
27.4 (.6) 
3.03 (.03) 
cd 

a 
bc 
abc 
ab 
ab 
c 
c 

<0.001 

<0.001 

Substrate Evenness 

AWCD 

2.07 (.01) 
2.11 (.01) 
2.09 (.02) 
2.09 (.02) 
2.09 (.02) 
2.13 (.01) 
2.11 (.01) 

0.132 

0.47 (.04) 
a 
0.56 (.03)  ab 
a 
0.49 (.05) 
a 
0.53 (.03) 
0.46 (.02) 
a 
0.70 (.05) 
b 
0.60 (.03)  ab 

<0.001 

* means followed by the same letter in the same column are not statistically different (p<0.05) 
according to Tukey’s HSD test 
 
 
 

 

124 

C 
% 

31 (0) 
28 (1.5) 
29.7 (0.3) 
31.3 (0.3) 
30.3 (0.7) 
42.3 (0.3) 
34 (0.6) 

 
 
 
 
 
 
 

Table 3.2. Compost properties of organic matter (%), carbon (%), carbon to nitrogen ratio, and moisture by compost treatment after 5 
weeks of feeding and 4 weeks of incubation. 

Compost 

C:N 

 

Moisture 

% 

OM 
% 
53.7 (0.3) 
48 (2.5) 
51 (0.6) 
53.7 (0.7) 
52.7 (0.9) 
73.7 (0.7) 
58.3 (1.2) 

ab 
a 
a 
ab 
a 
c 
b 

ab* 
a 
a 
ab 
a 
c 
b 

NoFood 
Carrot 
Melon 
Pineapple 
Onion 
Coffee 
Mix 

61.3 (3.3) 
63.7 (1.3) 
64.3 (0.9) 
66.3 (2.7) 
63.3 (1.8) 
71 (0.6) 
62.7 (1.2) 
0.055 
* means followed by the same letter in the same column are not statistically different (p<0.05) according to Tukey’s HSD test 
 
 
 
 
 
 
 

20.7 (1.2) 
16.7 (0.9) 
18 (1.2) 
19.3 (0.9) 
18 (1.2) 
17.7 (0.7) 
16.3 (1.2) 
0.121 

 

P 

<0.001 

<0.001 

 
 
 
 
 
 
 

 

125 

Table 3.3. The pH, EC and water soluble nutrient values from the saturated media extract for vermicompost treatments after 5 weeks 
of feeding and 4 weeks of incubation. 

Control 

a 

Carrot 

Melon 

e 

bc 

d 

ab 

Compost 

Pineapple 

Cl 
ppm 

NO3-N 
ppm 

pH 
dS m-1 
 
(0.1)  a*  10.3  
5.5  
(0.5)  bc 
9.1  
(0.3)  d  13.7  
(1.2)  d 
(0.1)  b  13.7  
7.3  
(0.7)  d 
8.2  
7.9  
(0.2)  b 
(0.1) 
6.8  
(0.3)  b  11.5  
(0.6)  cd 
7.1  
2.5  
a 
(0.2) 
(0) 
7.3  
9.4  
(0.1)  b 
(0.2)  bc 
<0.001 
<0.001 

NH4-N 
P 
K 
Ca 
Mg 
Na 
ppm 
ppm 
ppm 
ppm 
ppm 
ppm 
(0.9)  a  146  
4.7  
1305  
(52)  bc  279  
1080  
100  
403  
(2)  a 
(6) 
(78) 
(14) 
(18) 
3.7  
(0.7)  a  58  
3569  
1490  
80  
235  
(24)  b  997  
(355)  d 
(9) 
(3) 
(98) 
(116) 
(104)  d  172  
(163)  cd  1620  
(5)  bcd  2856  
3.7  
(0.7)  a  92  
445  
(27)  c  1146  
(30)  bc 
(33) 
(0.3)  a  35  
820  
2060  
2.3  
b  102  
56  
788  
ab 
(44)  bc 
(2)  a 
(73) 
(18) 
(10) 
(0) 
c  195  
3.7  
(0.9)  a  132  
2304  
(36)  bc  1110  
481  
90  
ab 
(6)  a 
(20) 
(30) 
(22) 
(23) 
a  59  
7  
727  
405  
84  
65  
232  
(3)  a 
(13) 
(10) 
(9) 
(2) 
(9) 
(56) 
6  
(1.2)  a  89  
(16)  bcd  2286  
(36)  bc  1050  
(30)  bc  141  
(11)  abc  175  
(8)  b  843  
(161)  bc 
<0.001 
<0.001 
<0.001 
<0.001 
<0.001 
0.098 
 
* means followed by the same lower-case letter in the same column are not statistically different (p<0.05) according to Tukey’s HSD 
test 
 
 

988  
(51) 
694  
(104) 
769  
(25) 
302  
(49) 
827  
(128) 
5  
(2) 
572  
(53) 
<0.001 

b 

d 

a 

a 

c 

c 

cd 

ab 

c 

b 

b 

a 

Onion 

Coffee 

d 

a 

c 

a 

d 

a 

Mix 

P 

bcd 

cd 

EC 

 

a 

ab 

 

126 

Table 3.4. Total nutrient analysis of vermicomposts after 5 weeks of feeding and 4 weeks of incubation. 

Compost 

N 
% 

NoFood 

1.5  
(0.1) 

a
* 

Carrot 

Melon 

Pineappl
e 

Onion 

Coffee 

Mix 

a
b 

a
b 

a
b 

1.7  
(0.02
) 
1.7  
(0.12
) 
1.6  
(0.07
) 
1.7  
(0.09
) 
2.4  
(0.09
) 
2.1  
(0.19
) 
<0.001 

a
b 

b
c 

c 

P 
% 
0.15  
(0.019

) 

0.36  
(0.013

) 

a 

c 

0.36  
(0.01)  c 
0.21  
(0.015

a 

) 

0.36  
(0.009

) 

0.15  
(0.003

) 

b
c 

a 

0.29  
(0.024

b 

b 

c 

b
c 

c 

a 

d 

Ca 
% 
1.8  
(0.17
) 
2.1  
(0.14
) 
2.4  
(0.06
) 
2.3  
(0.12
) 
2.4  
(0.05
) 
1.3  
(0.06
) 
2.1  
(0.11
) 

K 
% 
0.8  
(0.13
) 
2.9  
(0.13
) 
2.2  
(0.06
) 
1.8  
(0.14
) 
1.6  
(0.05
) 
0.9  
(0.01
) 
1.8  
(0.15
) 
<0.001  <0.001 

b
c 

b
c 

b 

a 

b
c 

c 

b
c 

a 

Mg 
% 
0.48  
(0.03
) 

ab 

0.53  
(0.04
) 

0.63  
(0.02
) 

0.61  
(0.01
) 

0.55  
(0.02
) 

0.45  
(0.04
) 

ab
c 

c 

bc 

ab
c 

a 

S 
% 
0.15  
(0.023

) 

0.22  
(0.006

) 

0.28  
(0.006

) 

0.21  
(0.017

) 

0.38  
(0.012

) 

0.19  
(0.003

) 

Zn 
ppm 

a 

64  
(8)  b 

Mn 
ppm 
181.3  
(12.2
) 

ab 

ab
c 

75.7  
(1.8) 

c 

104.
7  
(0.9) 

b
c 

210.3  
(10.2
) 
d  219  
(4) 

ab
c 

ab
c 

ab
c 

76  
(4.9) 

b
c 

318  
(23.4
) 

d  93.7  
(2.7) 

c
d 

257.7  
(27.4
) 
(1.2)  a  150  
(5) 

ab  41.7  

d 

cd 

a 

Cu 
ppm 
20.7  
(0.9
) 

a 

27.7  
(2.8
) 
30  
(1.2
) 

25.7  
(2.7
) 

21.7  
(0.3
) 

27.7  
(0.9
) 

a
b 

b 

a
b 

a 

a
b 

B 
ppm 
21.7  
(3.7
) 

a 

Fe 
ppm 
5122  
(570.3

) 

a
b 

Al 
ppm 
2500  
(120.4

) 

a
b 

40.3  
(2.4
) 

37.3  
(1.9
) 

36.3  
(4.7
) 
36  
(1.2
) 

17.3  
(0.3
) 

b 

b 

b 

5476  
(792.8

) 

5162  
(372.3

) 

5002  
(331.1

) 

b  4961  
(95.1) 

b  2845  

(344)  b 

a
b 

a
b 

a
b 

2632  
(66.8)  b 
2493  
(165.4

a
b 

) 

2423  
(74.1) 

a
b 

a  2766  

(62.6)  a  1549  
(82.7)  a 
2626  
5607  
(831.4
(319.2

b 

b 

) 
0.011 

P 

) 
<0.001 

) 
0.029 
* means followed by the same letter in the same column are not statistically different (p<0.05) according to Tukey’s HSD 
 
 

) 
<0.001 

 

ab
c 

0.54  
(0.03
) 
0.006 

0.26  
(0.024

bc  72.3  

(4.3)  b  236.3  
(6.4)  bc 
<0.001  <0.001 

b 

30.3  
(2.7
) 

32.3  
(0.9
) 
0.002  <0.001 

a
b 

 

127 

 
Figure 3.1.  A) Laboratory set-up for vermicomposting feeding trial with the seven treatments, one replication per shelf and a total of 
four replications and B) Close-up of feeding of pineapple on one half of worm bin (back) and covered with ground leaves before being 
wet by misting (front). 
 

 

 

 

128 

REFERENCES

 

129 

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representative foods*. American Journal of Digestive Diseases, 6(7), 440–449.  

 
Chen, Y., Zhang, Y., Zhang, Q., Xu, L., Li, R., Luo, X., Zhang, X., & Tong, J. (2015). 
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(2017). Changes in structure and function of bacterial communities during coconut leaf 
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Gopal, M., Gupta, A., Sunil, E., & Thomas, G. V. (2009). Amplification of Plant Beneficial 

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132 

AERATED COMPOST TEA FOR DISEASE SUPPRESSION IN HIGH TUNNEL 

TOMATO AND FIELD GROWN WINTER SQUASH 

CHAPTER IV 

 

 

133 

ABSTRACT 

Compost tea (CT) is a watery extract of compost; CTs have been tested for a variety of host 

plant/pathogen systems for disease suppression.  Disease pressure can decrease yields and 

pesticide options are limited for organic growers.  The effectiveness of aerated (48hr) CT (1:5 

v:v compost:water) from three composts [leaf/grass/coffee (LGC) and dairy manure (DMC) 

thermophilic composts and vermicompost (VC)] were evaluated in five separate experiments: 

two with tomatoes and tomato leaf mold (Fulvia fulva), varieties ‘Celebrity’ and ‘Big Beef’; and 

three with winter squash and powdery mildew (Podosphaera xanthii), varieties ‘Waltham 

Butternut,’ ‘Delicata,’ and ‘Blue Ballet Hubbard’ in field trials in 2016.   Treatments included 

the three undiluted CTs, a spreader-sticker (NuFilm P), VC with the spreader-sticker, and a no-

spray control.  Experimental treatments provided some degree of disease suppression relative to 

the control early in the crop production cycle for both varieties of tomato, and butternut squash, 

but not for hubbard or delicata.  CTs made from the three composts differed in their efficacy, 

with treatment VC+NuFilm P providing the most consistent early reductions in the incidence and 

overall severity of disease in tomatoes, for example.  For the host/pathogen combinations in 

which there had been early disease suppression, this effect disappeared over the course of the 

season, and no differences in final disease suppression or crop yield between treatments were 

detected.   Foliar spray of CT as part of an integrated pest management system may contribute to 

early season disease suppression of F. fulva on tomatoes and P. xanthii on butternut squash, but 

efficacy declines later in the season as the disease progresses. 

 

 

 

 

134 

INTRODUCTION 

The general definition of compost tea (CT) is a watery fermented extract of compost, 

aimed at obtaining soluble nutrients and multiplying beneficial microbes from the compost in an 

aqueous solution that can be applied to plants or soil (Martin, 2014; Scheuerell & Mahaffee, 

2002).  There are many factors that could influence the effectiveness of compost teas which 

include the quality of the compost, water source and ratio with compost, added nutrients, 

aeration, fermentation time, temperature, pH, dilution, application equipment, application timing, 

adjuvants, and application rates (Edwards et al., 2011; Ingham, 2000; Litterick et al., 2004; 

Neher et al., 2013; Scheuerell, 2002).  The brewing process of compost teas influences the 

resultant characteristics of the extract, the primary distinction being whether a CT is aerated or 

non-aerated (W. Brinton et al., 2004) with certain advantages attributed to both methods.  There 

are guidelines from the National Organics Standards Board (NOP, 2011) to address concerns for 

safety (regarding possible transmission of human pathogens primarily), but more research and 

guidelines have been called for by the scientific community and farmers (De Corato, 2020; 

Kelley et al., 2004; Scheuerell, 2002; personal communication).  

Soluble nutrients from compost are transferred into the CT as well as biological 

organisms, making quality and maturity of compost used for CT one of the most important 

factors for efficacy and mode of action.  Microbial life in CT include bacteria, fungi, 

actinomycetes, protozoa such as ciliates, flagellates and amoebas, and nematodes (Ingham, 

2000).  The ratio of compost to water and dilution prior to application is also a major determinant 

of quantity of nutrients and biology being applied with CT application (Islam et al., 2016).  CT 

may be applied as a soil drench a foliar spray, the latter is a means of inoculating the 

phyllosphere with beneficial microorganisms (Ingham, 2000).  The suppressive abilities of 

 

135 

composts or CTs have been diminished by heat treatment, indicating the importance of the 

biology for disease management (Elad & Shtienberg, 1994; Koné et al., 2010; Malandraki et al., 

2008; Siddiqui et al., 2009).  Metabolites and secondary compounds such as plant growth 

hormones and regulators, and free enzymes produced by microorganisms may be driving 

efficacy instead of the biology itself (Edwards et al., 2011; Larbi et al., 2006).   

Efficacy of a CT against a disease system starts with the compost used to make the CT 

(Elad & Shtienberg, 1994; Koné et al., 2010).  The effect of feedstocks and production method 

influence the finished compost product in terms of biological, physical and chemical properties 

(Neher et al., 2013).  The two primary means of composting are thermophilic (hot) composting 

and mesophilic vermicomposting with worms, most often Eisenia fetida.  The biological 

differences between these methods has been quantified in various studies, with vermicompost 

generally having higher levels of both bacteria and fungi (Dominguez & Edwards, 2011).  This is 

in part due to the interaction of the gut fauna within the worm itself interacting with the compost 

product.  Whether CT is made from composts that have manure feedstocks or vegetative matter 

only have been shown to affect efficacy as well for certain host/patho systems (Elad & 

Shtienberg, 1994).  Feedstock effects on biological, chemical, and physical characteristics of 

compost and thereby CT may impact efficacy. 

A primary desired benefit of CT is the ability of teas to suppress plant diseases.  The 

biology present in composts/CT lends the suppressive ability (Edwards et al., 2011; Marín et al., 

2013).  Various studies have shown suppression of a range of fungal and bacterial plant 

pathogens in different agricultural systems, though with inconsistent efficacy (Hadar, 2011; 

Litterick et al., 2004; Martin et al., 2012; Scheuerell, 2002; Scheuerell & Mahaffee, 2006).  

Mechanisms of disease suppression include competition for nutrients, antibiosis, secreting 

 

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secondary metabolites that are toxic to pathogens, parasitizing pathogens, or activating plant 

defense responses (Agrios, 2005; W. F. Brinton, 1995; On et al., 2015; Scheuerell, 2002; Segarra 

et al., 2009).  Mode of action may be different for different host/disease systems.  A study by On 

et al. (2015) demonstrated a synergistic effect of specific bacteria found in composts for disease 

reduction, adding further support to idea that a consortium of biology may be more effective than 

specific biocontrol agents on their own.  However, while a CT may be effective against one 

disease, it may not be for another, and therefore broad generalities are difficult to make.  Many 

research studies present extreme disease pressure and artificial conditions that would not mirror 

the natural field environment so the complicated interactions in the field may also produce 

different results.  Compost tea as a preventative or protective measure is more likely to provide 

protection as opposed to reactive efforts to reduce populations already above economic impact 

threshold (Scheuerell & Mahaffee, 2002).   

When CT is applied as a foliar spray, a spreader-sticker (surfactant) may be used 

(Mahaffee & Scheuerell, 2006).  Spreader-stickers help a spray solution cover evenly and 

effectively over the surface of leaves, thus helping the CT to adhere to the surface and making it 

more likely to be effective (Rajkovic & Markovic, 2012).  Such adjuvants have been shown to 

have some degree of disease suppression applied alone (Bruggen et al., 2016).  There have been 

studies that employed a spreader-sticker (McGrath, 2009), and others that have not (Segarra et 

al., 2009).  There is a paucity of research as to the degree to which a spreader-sticker may aid in 

the suppressive ability of a CT and more work is needed in this area (Martin, 2014).  NuFilm P 

(Miller Chemical and Fertilizer, LLC) is a spreader-sticker approved for use in organic systems 

that could provide increased efficacy of CT treatments but needs to be evaluated. 

 

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Tomatoes are one of the most important agricultural fruits and vegetables grown and 

consumed around the world (Blancard, 2012; Wang et al., 2009).  While there are many diseases 

that affect tomatoes, one of the most prominent in greenhouse/high tunnel grown tomatoes is 

Fulvia fulva (syn. Mycovellosiella fulva) is commonly referred to as tomato leaf mold (Blancard, 

2012).  F. fulva is a parasitic fungus that attacks the leaves, appearing early as light green to pale 

yellow spots and progressing to brown necrotic lesions (Figure 4.1).  Its damage can be 

considerable and cause significant yield losses.  Primary means of management are cultural 

measures such as cultivar selection for resistant varieties, proper ventilation, removal of old 

and/or infected leaves, and fungicide application though no fungicides that are approved for 

organic systems are labeled for use against F. fulva (Bardin & Gullino, 2020; Blancard, 2012; 

Caldwell et al., 2013). 

Powdery mildew (PM) is an obligate biotroph, a common fungal pathogen of many plants 

and particularly the genus Cucurbitaceae including winter squash (Hacquard, 2014).  PM can 

give a white fuzzy appearance to leaves in early stages and results in complete leaf necrosis as 

the disease progresses (Grubinger, 2005; Pérez-García et al., 2009, Figure 4.1).  PM contributes 

to decreases in harvestable yield, immature fruits, and premature death of plants (Caldwell et al., 

2013; Rur et al., 2018).  Podosphaera xanthii is one species of fungus that is commonly referred 

to as powdery mildew and is a significant disease affecting winter squash varieties (Barickman et 

al., 2017; Pérez-García et al., 2009).  Varietal selection of those breed for resistance to PM has 

been a primary means of control, as well as removal of infected tissue, and commercially 

available fungicides that have varying degrees of efficacy (Caldwell et al., 2013).  Development 

of fungicide resistance has been demonstrated to be a particular problem with P. xanthii around 

the world (Pérez-García et al., 2009; Rur et al., 2018). 

 

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CT may be more important for biological/ecological agricultural systems, especially 

those that are organically certified, which have limited options for managing diseases (Bruggen 

et al., 2016; Zaker, 2016).  Additionally, crops such as tomatoes that have a scalar harvest over 

time often would have time-to-harvest intervals making options even more limited (Bellini et al., 

2020).  A result of some studies has been that disease management provided by CT or other 

biofungicides would not be commercially acceptable if there were other means of controlling 

disease, but also that use of CT may be best used in an integrated pest management system 

instead of being relied upon as a sole method of disease control (Barickman et al., 2017; Evans 

& Percy, 2014; Marín et al., 2013; Martin, 2014).  Additionally, resistance to many fungicides 

traditionally used for these diseases has become an issue, as well as concerns for both 

environmental and human health, making development and better understanding of biofungicides 

even more pressing (De Corato, 2020; Mahaffee & Scheuerell, 2006; Pérez-García et al., 2009; 

Rur et al., 2018; Zaker, 2016).  Determination of CT treatments as biofungicides that would 

maximize efficacy could increase adoption of its use and the options available to organic 

growers. 

The objective of this study was the evaluation of aerated compost teas, made with three 

composts that varied by starting feedstocks and composting method, for their effects on two 

host-disease systems: tomato leaf mold on tomatoes, and powdery mildew on winter squash.  An 

additional objective was the assessment of the use of a sticker-spreader and if such use enhances 

the suppressive abilities of compost tea by looking at its effects both on its own and in 

conjunction with the vermicompost CT treatment.  We hypothesized that all compost tea 

treatments would have significant reduction in disease as compared with the no-spray control but 

the extent of disease reduction would vary.  We also hypothesized that the spreader-sticker 

 

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would have some degree of efficacy on its own, but the synergistic effect of the vermicompost 

tea and the spreader-sticker would be greater than either treatment on their own.  Yield data from 

compost tea treatments was hypothesized to be greater than in the control and correlate with 

degree of reduction of disease.  We further hypothesized that these effects would be consistent 

across different genera, and species/varieties within genera.  While results are limited to these 

specific host/disease systems, assessing composts that have such contrasting characteristics on 

multiple host/disease systems may help us understand whether one type of compost may be more 

effective than another for disease suppression more broadly when used to make CT. 

 

MATERIALS AND METHODS 

Five separate experiments were conducted at Michigan State University (MSU) Student 

Organic Farm (SOF) at the Horticulture Teaching and Research Center (HTRC) in Holt, MI 

(42°40” N, 84°28” W) in the summer of 2016.  Each experiment evaluated the effects of 

compost tea treatments on a different crop or cultivar.  These included two varieties of tomatoes, 

and three varieties of winter squash.  Working within the existing planting schedule and plan for 

a working farm, the number of rows and plants were limited so both size and number of 

replications were made within these constraints. 

Compost Tea Treatments and Experimental Design 

Compost: For all 5 experiments, three types of compost tea were used with two factors 

being considered: method of composting and compost feedstocks.  The two composting methods 

employed were themophilic (hot) composting, and worm or vermicomposting.  A thermophilic 

compost was made with the feedstocks municipal fall-collected leaves, fresh cut grass from 

organic certified land, and spent coffee grounds at approximate volume ratio of 2:2:1.  An 

 

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approximately ten cubic yard turned windrow was managed over the course of two months, then 

stored in wooden crates (approximately 1yd3) in an unheated high tunnel for approximately 1 

year prior to use in the trial.   The second thermophilic compost had a primary feedstock of dairy 

manure, and is a commercially available compost called Dairy Doo® produced in managed 

windrows by Morgan’s Composting, Inc. (Sears, MI).  The final compost was vermicompost 

made with the feedstocks of municipal fall-collected leaves and pre-consumer kitchen 

preparation food scraps.  These feedstocks were first pre- hot composted for two weeks and then 

surface applied to a wedge windrow vermicomposting system in a high tunnel that allowed 

approximately six months for the earthworms (sp. Eisenia fetida) to process the material.   

Total nutrient analysis by ashing of each compost included N, P, K, Ca, Mg, S, and Na 

(%) and ppm Zn, Mn, Fe, Cu, B, and Al.  Saturated media extract (SME) analysis included pH, 

electrical conductivity (EC), nitrate-N, ammonium-N, P, K, Ca, Mg, Na, and Cl (ppm).    

Compost tea preparation:  Compost teas were brewed with forced aeration for 48 hours 

prior to application, using a built brewing system of 15-gallon plastic totes with PVC piping with 

holes drilled into it arrange along the bottom attached to a 1750gal/hr air pump providing forced 

air.  The ratio of compost to water was 1:5 v/v for all CT applied; ten gallons were brewed at a 

time with 2 gallons of compost contained in a 5-gallon capacity paint strainer bag.  Three CTs 

were made with identical methods, the variable being the type of compost used.  At the end of 48 

hours the sleeve of compost was removed and spraying of CT began within 1 hour after aerated 

brewing finished. 

Quality control parameters of oxygen concentration and temperature were monitored for 

each batch of CT made from each compost.  Oxygen content remained consistent in each batch, 

averaging just over 100ppm O2 throughout the duration of brewing (measured using ExStik®II 

 

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dissolved oxygen meter by Extech).  Brewing was in a laboratory setting with ambient 

temperatures of approximately 21°C, and temperature of CT averaged just below 20°C.   

Treatments and application:  Each of the 5 separate field experiments were arranged in a 

randomized complete block design with 3 replications of six treatments: CT made from the 

leaf/grass/coffee compost (LGC), CT made from dairy manure based Dairy Doo® compost 

(DMC), CT made from the vermicompost (VC), VC with NuFilm P spreader-sticker added just 

prior to application (VC+Nu), NuFilm P alone added to water (NuFilm), and a no-spray control 

(Control).  The unsprayed control treatment was included to compare actual practices used by 

farmers in the field, and in particular the farm management plan at the SOF for these crops.  

While brewing method (aerated versus non-aerated) effect on efficacy of teas is another 

important distinction, aerated only was selected, as number of treatments was limited by the size 

of the plot available. Additionally, aerated methods have been gaining in popularity, and allow 

for a faster turn-around time when CT is needed, allowing farmers to take weather forecast into 

account when deciding when to brew CT. 

Undiluted CTs were filtered through three layers of cheese cloth to remove any 

remaining debris when put into Chapin pump backpack sprayer.  CT was sprayed onto foliage 

using backpack sprayer with handheld boom, allowing for full coverage by wetting leaves on all 

surfaces to the point of runoff (approximately 50gal/acre when plants were full grown).    Sprays 

were applied on a weekly basis for a total duration of 13 weeks from June (6/8) to September in 

2016.  Weather was monitored to ensure that leaves were not wet prior to application and would 

have sufficient time to dry before any rain event. 

 

 

 

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Tomato Leaf Mold (Fulvia fulva) Trials 

In the two tomato experiments, we evaluated the effects of CT on high tunnel grown 

tomato (Solanum lycopersicum) cvs. ‘Big Beef’ and ‘Celebrity.’  For each experiment, 

treatments were applied to experimental units of two plants, with three replications of the six 

spray treatments with one plant buffer between each.  Plant spacing was 24” within row, one row 

per 30” bed.  Plants were top trellised and suckers removed as the plants grew to allow for good 

air flow, and plants watered with drip irrigation.   

Winter Squash Powdery Mildew (Podosphaera xanthii) Trials 

In three separate experiments, we evaluated the effects of CT on three different varieties 

of winter squash.  Cucurbitaceae moschata ‘Waltham Butternut,’ and C. pepo ‘Delicata’ 

experiments were planted in 150’ beds and four plants (2 plants per bed spanning 2 beds, 

approximately 144ft2) comprising an experimental unit with a block of four plants between for a 

buffer.  C. maxima ‘Blue Ballet Hubbard” squash plants were arranged in one bed of 150’ with 

three plants (approximately 108ft2) per experimental unit with one additional plant between for a 

buffer.  Buffers were in place to eliminate the factor of spraying overlap, and account for the 

vining nature of winter squash growing into one another.  There were three replications of each 

of the six spray treatments for a total of 18 experimental units per species.  For all winter squash, 

spacing was 24” within row, and 6’ between rows, with irrigation provided by drip tape.  The 

field was cultivated prior to placing 4-week-old squash transplants, and weeded again at three 

weeks after transplanting.  Late season weed pressure was very high. 

Data collection 

For both tomato and winter squash, plants were monitored weekly for disease.  Disease 

incidence and severity of tomato leaf mold was assessed twice for tomatoes, once shortly after 

 

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disease had appeared (7 August, 2 months after spray trial began), and once when disease had 

spread significantly (12 September) based on visual observation and before any final harvest of 

fruits.  Winter squash varieties were visually rated for powdery mildew, for both incidence and 

severity, twice for ‘Delicata’ (8/5 and 9/9) but only once for ‘Butternut’ and ‘Hubbard’ (on 8/6) 

due to high weed pressure eventually ending their trial early and final attempt at rating having 

insufficient leaves to assess.   

Disease incidence is the percentage leaves with disease, calculated from the number of 

leaves with disease out of a total of 30 leaves per experimental unit.  Disease severity is the 

percentage of leaf area that is symptomatic on diseased leaves only.  Percentages of disease 

severity on individual leaves were averaged for all leaves assessed that had disease incidence per 

experimental unit and this average was used for the severity measure.  Overall severity is a 

measure of the total leaf area infected (%) for the whole plant and is calculated using the 

equation  

[1] 

(Incidence * Severity)/100.  

For tomatoes harvest data were also collected, for both total number of fruit and total 

weight throughout the multiple harvests during the growing season, data collected from mid June 

to late September approximately every 4 days.  Winter squash harvest data was not possible at 

this farm. 

Statistical Analysis 

Data analyses were carried out using R statistical software package, and additional 

packages for R including lme4 for the linear mixed model and multcomp for Tukey’s HSD 

pairwise comparisons (R Core Team, 2019).  Unless otherwise noted, statistical significance is 

determined at a<0.05.  Data were analyzed for normality and heterogeneity of variance prior to 

 

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analysis of variance.  Where normality assumptions were violated, the data were log transformed 

prior to analysis and Sattherthwaite’s degrees of freedom was employed to account for potential 

nonequal variance in the data.   

One-way ANOVA with random effect to account for the blocking effect of the RCBD 

design was performed for each species/variety, as well as mean separation (p<0.05 unless 

otherwise noted).  Mean separation by Tukey’s Highly Significant Difference (HSD) test was 

performed for pairwise comparisons (p<0.05 unless otherwise noted).  This means of statistical 

analysis was done for the individual varieties and their respective diseases, for disease incidence, 

severity, and overall severity, as well as for the harvest data collected for the tomato varieties.   

To address the hypothesis that the efficacy of VC was affected by the use of the spreader-sticker 

NuFilm P, we conducted a separate two-way ANOVA on the subset of four treatments 

representing all four combinations of VC and NuFilm P.  

  

RESULTS 

Tomato Disease and Yield 

For ‘Big Beef’ disease ratings from the early assessment there was a treatment effect on 

overall severity (F=10.052, p=0.001), incidence (F=9.192, p=0.002) and severity of infection on 

infected leaves only (F=4.5, p=0.021; Table 4.1, Figure 4.2).  The  overall severity of F. fulva as 

a measure of the percent leaf area infected on the entire plant ranged between 8.0% (Control) and 

1.2% (VC+Nu).  All treatments were lower than the Control, and additional VC+Nu was also 

lower than LGC and DMC.  The percent of leaves infected (disease incidence) ranged between 

90.0% (Control) and 40.0% (VC+Nu); VC, NuFilm and VC+Nu were all lower than the Control, 

as well as some additional treatment differences.  Severity of infection on infected leaves ranged 

 

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between 8.8% (Control) and 3.0% (VC+Nu) with no differences between experimental 

treatments, but all were lower than the Control. 

For ‘Celebrity’ there was a treatment effect on overall severity (F=8.546, p=0.002), 

incidence (F=8.351, p=0.002) and severity of infection on infected leaves only (F=5.288, 

p=0.012; Table 4.1).  The overall severity ranged between 10.9% (LGC) and 2.6% (VC+Nu).  

VC+Nu treatment was different from all but DMC, and DMC was different from the Control and 

LGC treatments.  The percent of leaves infected (disease incidence) ranged between 94.4% (VC) 

and 52.2% (VC+Nu), with the only differences observed being between VC+Nu and all other 

treatments.  Severity of infection on infected leaves ranged between 12.2% (LGC) and 4.6 

(VC+Nu) with VC+Nu being different from the Control, LGC and VC, and DMC different from 

LGC. 

Suppressiveness of CT sprays diminished over the season in both varieties (data not 

shown).  Data taken later in the season (on 12 September) when disease pressure was 

significantly higher yielded no differences between any treatments for overall severity (F=6.637, 

p=0.677 and F=0.585, p=0.712 for ‘Big Beef’ and ‘Celebrity’, respectively).  The range of the 

percent leaf area infected at this time was between 26-45% for ‘Celebrity’ and 34-46% for ‘Big 

Beef’ (data not shown).  Similarly, neither incidence or severity were different by treatment.   

In the evaluation of the subset of data to specifically assess the interactive effects of VC 

CT and the spreader-sticker NuFilm P, the two-factor ANOVA performed on the data from the 

first disease rating for overall severity demonstrated significance of the main effects of both VC 

and NuFilm, as well as their interaction for both varieties of tomato (Table 4.4).  For ‘Big Beef’ 

a decrease in overall disease severity with the application of NuFilm was only observed in the 

absence of the VC CT (Figure 4.3A), whereas when VC CT was already being applied, NuFilm 

 

146 

did not appear to increase its efficacy.  The interaction for ‘Celebrity’ was marginally significant 

(p=0.062, Figure 4.3B), and displayed a different trend with NuFilm decreasing overall severity 

on its own and in concert with VC CT, but even more effectively when combined with VC CT 

than when on its own.   

Yield differences between treatments were not observed for total number of fruit 

harvested, total weight harvested over the season, or fruit weight (grams per tomato) for either 

variety (Table 4.2).  ‘Big Beef’ mean harvestable weight per plant ranged from 6.9-11.8 pounds 

per plant, while ‘Celebrity’ harvest weights ranged from 14.4-17.7 pounds per plant.  The total 

number of tomatoes by variety was greater for ‘Celebrity’ with 35-42 tomatoes per plant whereas 

‘Big Beef’ yielded 15-24 tomatoes per plant.  In this trial, yield was not affected by spray 

treatment and not affected by disease severity.   

Winter Squash Disease 

Winter squash varieties were visually rated for powdery mildew, for both incidence and 

severity on 5 August (Table 4.3, Figure 4.4).  Level of infection was higher for ‘Delicata’ (4.2-

12.5% overall leaf area infected) followed by ‘Hubbard’ (0.8-2.5%) and then ‘Butternut’ (0.8-

1.8%).  Delicata and Hubbard squash displayed no differences in overall disease severity, 

incidence, or severity of infected leaves by treatment (Table 4.3, Figure 4.4 for overall severity).   

For the ‘Waltham Butternut’ squash trial there was a treatment effect on overall severity 

(F=4.297, p=0.024), marginal effect on severity of infection on infected leaves only (F=2.609, 

p=0.092) while no differences were observed between treatments for incidence (F=2.363, 

p=0.116; Table 4.3).  The overall severity ranged between 1.8% (Control) and 0.8% (both 

VC+Nu and LGC), with all treatments besides NuFilm being different from the Control, and no 

differences between spray treatments.  Disease incidence ranged between 69.3% (Control) and 

 

147 

50.7% (VC+Nu), and despite a lack of significance observed in the linear model, Tukey’s HSD 

comparison resulted in separation between VC+Nu and the Control, with all others being not 

different statistically.  Severity of infection on infected leaves ranged between 2.6% (Control) 

and 1.5 (VC+Nu and LGC) with VC+Nu and LGC being marginally different from the Control. 

Excessively weedy conditions complicated the experiment, ending the spray trial of 

‘Hubbard’ and ‘Butternut’ earlier than anticipated, and while a final disease rating was attempted 

the plants were so compromised by the weeds any data were discarded.  Downy mildew 

(Pseudoperonospora cubensis) was also present on the ‘Butternut’ making it difficult to assess 

powdery mildew only.  Delicata squash, however, were rated a second time on 9 September, 

when disease pressure had increased by between 284% (Control) and 785% (VC+Nu), which had 

originally displayed the least signs of disease (data not shown).  The spread of the overall 

severity data for the final rating of ‘Delicata’ was from 36% for the LGC and VC CT treatments 

to 48% leaf area infected for the Control with no differences between treatments as was the case 

for the rating of disease earlier in the season for Delicata (F=1.164, p=0.390; data not shown).   

There were very few fruits for harvest of ‘Blue Ballet Hubbard’ and due to unexpected 

circumstances, no harvest data were collected for ‘Butternut’ or ‘Delicata.’    

The two-factor ANOVA used to evaluate the interaction of VC CT and NuFilm P for the 

Butternut squash overall severity of infection early in the season indicated the significance of VC 

CT (p=0.012), which decreased overall severity independent of NuFilm (Table 4.4).  NuFilm 

was marginally significant (p=0.087), also decreasing overall severity with its use independent of 

VC CT.  The combination of VC CT and NuFilm did not impact efficacy (p=0.669, Figure 

4.3C).   

 

 

148 

DISCUSSION 

The primary hypothesis that all compost tea treatments would have significant reduction 

in disease as compared with the no-spray control was supported in some of the experiments but 

not others.  The Control in all experiments was the same or higher than all of the experimental 

treatments for the metrics of overall severity which is of the most interest, incidence and severity 

of disease on infected leaves.  Of the experiments where differences were observed, for ‘Big 

Beef’ tomatoes and ‘Butternut’ squash all CT sprays were different from the Control, while for 

‘Celebrity’ tomatoes the LGC CT was not different but the other CTs were.  There appeared to 

be a lack of any efficacy in reduction for ‘Delicata’ and ‘Hubbard.’  Within compost tea 

literature, there are many examples of disease reduction but also many where there was no effect 

which is consistent with our results (Martin, 2014). 

That the extent of the disease reduction would vary was again supported by some of the 

experiments but not all.  For the tomatoes, there was variation between spray treatments.  Of 

particular interest is the difference in efficacy of the LGC and the VC CT sprays where in the 

‘Celebrity’ tomatoes these were not different than the Control, while they did reduce disease 

severity for ‘Big Beef’ tomatoes.  For all the winter squash trials, there were no differences 

between the experimental sprays, and only for ‘Butternut’ was there even a difference between 

spray treatments and the Control.   

The hypothesis that the spreader-sticker would have some degree of efficacy on its own 

when compared against the Control was supported in both tomato experiments.  This was seen 

from the full set of data and pairwise comparisons, and was even more apparent in the subset of 

data examining the main effects of VC and NuFilm P.  This is in contrast to the three winter 

squash experiments in which NuFilm P had no effect on any of the varieties; however, for 

 

149 

‘Butternut’ squash when analyzed in the two-way ANOVA the results were marginally 

significant (p=0.087, Table 4.4).   

 

The results of increased efficacy in VC+Nu (for ‘Celebrity’ tomatoes) and of efficacy of 

NuFilm P on its own further substantiates findings by Rajkovic and Markovic (2012) in which 

they used NuFilm P in conjunction with biofungicide AQ10 for powdery mildew on oak trees, as 

well as NuFilm P on its own demonstrating efficacy for disease reduction.  Rur et al. (2018) 

evaluated spreader-sticker Yuccah for effects with and without a biocontrol agent also 

demonstrating greatest efficacy in PM control by use of a spreader-sticker.  This is, however, in 

contrast to findings by Yohalem et al. (1996) in which the spreader-sticker Latron had no effect 

on CT efficacy for apple scab.  In our trial whether there was any additive effect of VC CT and 

NuFilm was dependent on species/variety.  For ‘Celebrity’ tomatoes VC+Nu overall severity 

was lower than for either treatment on its own.  This did not hold true for ‘Big Beef’ tomatoes or 

butternut squash, however, where the treatments were not different from one another.  This 

should be reviewed further, and testing spreader-stickers with other CTs to determine if there is 

in fact likely to be an additive effect or not, and if this would be dependent on type of CT, or 

plant/pathogen system. 

What differences there were between treatments did not appear to have a lasting effect.  

There was also no impact on yield of tomato in either variety by treatment.  This refuted the 

hypothesis that compost tea treatments would result in increases in yield.  This is contrary to 

other findings in which irrespective of disease presence it was found that yield could be 

increased by foliar feeding of nutrients found in CT sprays (Haggag & Saber, 2007; Martin, 

2014).  In a study of effect of foliar application of Ca and Mg on tomatoes, Ilyas et al. (2016) 

suggests their addition can increase growth and yield of tomatoes.  Increases of disease severity 

 

150 

are generally inversely proportional with yield in many plant/disease systems (Gaunt, 1995), but 

at least the early reduction in disease did not correlate with increases in yield in these 

experiments, and for the yield data there was nearly significant differences of some treatments, 

but for decreases in yield which is the opposite of what would have been expected. 

 

In looking at the results of the five different experiments together and comparing 

significance by treatments, the hypothesis that effects of CTs would be consistent across 

different genera, and species/varieties within genera is not supported.  While some of the CT 

sprays were effective for tomatoes, this was largely not the case for winter squash.  Within 

tomatoes, the effect of the LGC and VC CTs in particular were inconsistent, while the DMC CT 

and VC with NuFilm were consistent in their reduction of overall severity.  Within winter 

squash, efficacy was only observed for ‘Butternut,’ thereby undercutting the assertion that these 

CT sprays are effective against P. xanthii. 

For the two different tomato experiments the varieties responded differently to some 

treatments.  The plant morphology of the two different tomato varieties may have had an impact 

on the efficacy of the CT and spreader-sticker sprays.  For the ‘Celebrity’ tomatoes (a semi-

determinant variety), the plants were dense/compact with foliage.  This was in contrast to the 

‘Big Beef’ (an indeterminant variety) for which the top trellising kept plants very vertical, 

growing tall with less foliage lower in the plant.  This likely allowed increased airflow which is 

helpful for suppression of F. fulva and other fungal diseases (Blancard, 2012).  Free standing 

water can increase the presence of the disease, and with more dense foliage in the ‘Celebrity’ 

tomatoes foliage is likely to have stayed wet longer and this could be part of the reason for the 

greater overall disease levels in this variety for all treatments.  This would give greater weight to 

the decrease in disease observed for DMC and VC+Nu treatments despite this complicating 

 

151 

factor.  To assess this more directly, data on the average length of time the foliage remained wet 

in both varieties could be taken in future experiments. 

The common name powdery mildew is used for a variety of different fungal species that 

produce similar morphological features and responses to host plants.  The lack of efficacy of CT 

against powdery mildew has been demonstrated in other host/patho systems such as Koné et al. 

(2010) or Kelley et al. (2004), whereas other studies have found significant control of the disease 

(Marín et al., 2013; Naidu et al., 2012; Segarra et al., 2009) though some of this work has been 

done on other fungal species responsible for PM.  It can be difficult to compare across studies, 

even if the specific host/pathogen system is the same due to the differences in CT used for 

treatments. 

Documentation of efficacy of CTs to reduce disease presence/severity caused by foliar 

pathogens has been less successful in field trials as compared to trials in more controlled 

environments.  Martin (2014) reviewed 42 field trials for different host/pathogen systems finding 

that 57% of CT treatments had less disease compared with the control, whereas 89% of the 47 in 

vitro, greenhouse and/or container experiments reviewed resulted in CT treatments with decrease 

in disease.  This was attributed at least in part to the diverse interactions of biotic and abiotic 

factors that are generally not present in a more controlled setting.  In these experiments the high 

degree of variability may contribute towards the lack of statistical significance between 

treatments.  The low number of replications (n=3) per treatment contributed to this, and future 

experimentation should aim to increase replication where possible.  Replication of the 

experiments in subsequent seasons as well would add to the knowledge of how reliable these 

results might be.  

 

152 

Regarding differences between the plant/pathogen systems in this study it is important to 

note the role of leaf wetness.  While the presence of water on the leaf surface will aid in the 

transmission of and the infection by F. fulva, the opposite is true of P. xanthii.  Based on the 

biology of the pathogens, suppression results observed in tomato are very likely real treatment 

effects, while for squash, it is possible that effects are just due to application of water. 

The primary decision for the control treatment to be “no spray” as opposed to a water 

spray was what the default method that would be employed on a farm, in which they would be 

unlikely to ever spray just water on foliage.  This choice was especially important in the high 

tunnel environment in which rainfall is excluded and the practice on this farm was for drip 

irrigation in which the leaves were never wet unless by the intentional spraying for this study.  

Also only having a negative control with the no spray treatment, inferences as to how CT would 

have compared to a positive control of a conventional fungicide known to treat these diseases 

cannot be made under these conditions.   

 

FUTURE RESEARCH AND CONCLUSIONS 

Biological data for the constituent bacteria and fungi in each of the respective compost 

teas if collected could be related to the relative efficacy.  Collection of such data by MiSeq 

analysis was originally intended for this study but was not possible.  If in the future specific 

organisms could be isolated against the diseases of interest it could even be possible to establish 

a new specific biological control organism that could be targeted in compost and CT to increase 

efficacy.  There are multiple biocontrol organisms that have already been identified for efficacy 

against F. fulva and P. xanthii (Gao et al., 2016; Lee et al., 2011; Zhang et al., 2018) that may be 

present in some composts, and species specific data from multiple types of composts would 

 

153 

elucidate whether there is a factor of feedstock or production measures on presence of these 

specific organisms in compost or CT. 

Based on this study, CT sprays from the vermicompost and dairy-manure based compost 

used in this study can provide some disease management benefits of F. fulva tomatoes and 

butternut squash.  Similar to prior published research, certain compost teas were disease 

suppressive while others were not.  Later in the season differences between treatment efficacy 

declined in all experiments, indicating that while CT may be effective at delaying the onset and 

early spread of disease the efficacy diminished over time in the present study.  CT could be 

incorporated into a spray regimen for disease management but appears unable to suppress 

disease effectively on its own over the course of the growing season. 

Farmers have expressed their desire for more information on the topic of compost teas, 

looking for more concrete recommendations consistent with chemical pest management 

strategies.  More research into CTs with methods that are reproducible by farmers may increase 

the adoption of the use of CTs if found to be effective against specific host/pathogen systems 

such as F. fulvia demonstrated here.  More research of compost teas is needed to better 

understand the mechanisms of disease reduction and how to reliably produce CT that will 

decrease disease severity.   

 
 

 

 

154 

APPENDIX 

 

155 

Table 4.1. Overall severity, incidence, and severity for ‘Big Beef’ and 'Celebrity’ tomatoes 
infestation by F. fulvia. Data taken on 7 August 2016, two months after weekly spraying 
commenced when plants showed moderate signs of disease. 
 

Severity 

 

Tomato Variety 

CT Treatment 

Incidence 
(% Leaves 
Infected) 

Overall Severity 
(Total % Leaf 
Area Infected) 
8.0 (1.4) 
c 
b 
3.9 (1.5) 
b 
3.1 (0.2) 
2.3 (0.8) 
ab 
a 
1.2 (0.2) 
2.1 (0.3) 
ab 
0.001 
9.6 (3.6) 
10.9 (3.1) 
3.9 (1.0) 
9.4 (3.3) 
2.6 (1.3) 
5.4 (1.4) 
0.002 

90.0 (6.9) 
75.6 (6.2) 
66.7 (5.1) 
51.1 (8.7) 
40.0 (6.7) 
52.2 (7.3) 
0.002 
92.2 (4.8) 
c 
88.9 (1.1) 
c 
74.4 (8.0) 
ab 
94.4 (2.9) 
bc 
a 
52.2 (7.3) 
bc  76.7 (10.2) 
0.002 

(% Infection on 
Infected Leaves) 
8.8 (1.0) 
5.0 (1.8) 
4.6 (0.4) 
4.2 (0.9) 
3.0 (0.5) 
4.0 (0.3) 

b 
a 
a 
a 
a 
a 

0.021 
10.2 (3.4) 
12.2 (3.4) 
5.2 (1.1) 
9.8 (3.2) 
4.6 (1.6) 
6.8 (1.0) 

0.012 

bc 
c 
ab 
bc 
a 
abc 

d 
cd 
bcd 
ab 
a 
abc 

b 
b 
b 
b 
a 
b 

Control 
LGC 
DMC 
VC 
VC+Nu 
NuFilm 
 

Control 
LGC 
DMC 
VC 
VC+Nu 
NuFilm 
 

'Big Beef' 

P 

'Celebrity' 

P 

* means followed by the same letter in the same column are not statistically different according 
to Tukey’s HSD test at p<0.05. 
  
 

 

 

156 

Table 4.2. Harvest data for 'Big Beef' and 'Celebrity' tomatoes by number of tomatoes 
harvested, total weight harvested, and grams (g) per tomato over the course of the season per 
plant. 

Tomato Variety  CT Treatment 

Control 
LGC 
DMC 
VC 
VC+Nu 
NuFilm 
 

Control 
LGC 
DMC 
VC 
VC+Nu 
NuFilm 
 

 

'Big Beef' 

P 

'Celebrity' 

P 

 

 

Number tomatoes  

per plant 
20.3 (4.0) 
23.7 (2.8) 
23.5 (2.0) 
18.3 (0.6) 
22.0 (1.9) 
15.5 (0.3) 

0.177 

42.3 (3.6) 
37.0 (3.3) 
37.7 (1.4) 
32.3 (2.2) 
41.7 (2.2) 
34.8 (5.8) 

0.079 

Pounds tomatoes 

per plant 
11.8 (3.7) 
11.5 (1.3) 
11.7 (1.7) 
9.4 (1.1) 
11.6 (0.9) 
6.9 (0.9) 
0.411 

17.7 (0.7) 
16.0 (0.7) 
15.3 (0.7) 
13.8 (0.7) 
17.4 (0.6) 
14.4 (2.2) 

0.060 

Grams per tomato 

0.55 (0.08) 
0.49 (0.02) 
0.49 (0.03) 
0.51 (0.05) 
0.53 (0.01) 
0.44 (0.05) 

0.651 

0.42 (0.02) 
0.44 (0.04) 
0.41 (0.01) 
0.43 (0.01) 
0.42 (0.03) 
0.41 (0.01) 

0.925 

157 

Table 4.3. Overall severity, incidence, and severity for 'Waltham Butternut,' 'Delicata,' and 'Blue 
Ballet Hubbard' squash infestation by P. xanthii. Data taken on 5 August 2016, two months after 
weekly spraying commenced when plants showed moderate signs of disease. 
 

Incidence 

Severity 

Overall Severity 
(Total % Leaf Area 

Infected) 

(% Infection on 
Infected Leaves) 

 

Squash 
Variety  CT Treatment 

Control 
LGC 
DMC 
VC 
VC+Nu 
NuFilm 
 

Control 
LGC 
DMC 
VC 
VC+Nu 
NuFilm 
 

Control 
LGC 
DMC 
VC 
VC+Nu 
NuFilm 
 

'Waltham 
Butternut' 

P 

'Delicata' 

P 

'Blue 
Ballet 
Hubbard' 

P 

1.8 (0.5) 
0.8 (0.2) 
0.9 (0.1) 
0.9 (0.2) 
0.8 (0.2) 
1.2 (0.2) 

b 
a 
a 
a 
a 
ab 

0.024 

12.5 (2.9) 
7.3 (2.3) 
6.2 (2.5) 
8.7 (1.9) 
4.2 (0.6) 
8.6 (0.3) 
0.161 
2.5 (0.7) 
2.7 (1.4) 
0.8 (0.2) 
1.8 (0.6) 
1.8 (1.1) 
0.3 (0.1) 
0.265 

(% Leaves Infected) 
69.3 (9.3) 
b 
ab 
53.3 (10.4) 
ab 
53.3 (6.7) 
56.0 (4.6) 
ab 
a 
50.7 (10.4) 
54.7 (9.3) 
ab 
0.116 

67.8 (7.8) 
56.7 (3.8) 
57.8 (13.7) 
62.2 (4.0) 
51.1 (2.9) 
63.3 (3.8) 

0.647 

49.3 (9.3) 
37.3 (8.7) 
50.7 (4.8) 
42.7 (6.7) 
44.0 (6.1) 
36.0 (4.6) 

0.494 

2.6 (0.4) 
1.5 (0.1) 
1.8 (0.2) 
1.7 (0.4) 
1.5 (0.1) 
2.2 (0.2) 
0.092 

18.3 (3.7) 
12.5 (3.1) 
10.0 (3.4) 
14.1 (3.3) 
8.2 (0.8) 
13.7 (0.9) 

0.211 
5.6 (2.4) 
6.1 (3.1) 
1.5 (0.3) 
4.2 (1.6) 
3.6 (1.9) 
0.9 (0.3) 
0.353 

* means followed by the same letter in the same column are not statistically different (p<0.05) 
according to Tukey’s HSD test 
  
 

 

 

158 

Table 4.4. Significance (p-value) of the main effects of vermicompost 
compost tea (VC CT), the spreader-sticker NuFilm P, and their interaction on 
overall severity of Fulvia fulva on tomatoes and Podosphaera xanthii on 
butternut squash. 

 
 

VC CT 
NuFilm 
VC+NuFilm 
 

Tomatoes 

Winter Squash 

Big Beef 

Celebrity 

Disease 

F. fulva 

<.001 
<.001 
0.034 
 

0.046 
0.002 
0.062 

Butternut 
P. xanthii 

0.012 
0.087 
0.669 

 

159 

A) 

B) 

C) 

 
Figure 4.1.  A) Tomato leaf mold on ‘Celebrity’ tomatoes, B) Close up of tomato leaf infected, 
and C) Powdery mildew symptoms on ‘Blue Ballet Hubbard’ squash.  
 

 

  

 

 

 

160 

c 

b 

b 

ab 

ab 

a 

c 

c 

bc 

 

bc 

ab 

a 

 

 
 
 
Figure 4.2.  Overall severity (incidence*severity) as % leaf area infected by F. fulvia for tomato 
varieties A) ‘Big Beef’ and B) ‘Celebrity’ by compost tea treatment.  Columns labeled with the 
same letter are not significantly different than one another (p<0.05).  LGC = CT from 
leaf/grass/coffee thermophilic compost; DMC = CT from dairy manure based themophilic 
compost; VC = CT from vermicompost (no manure); VC+Nu = VC with NuFilm P added; 
NuFilm = NuFilm P only.  
 

 

 

161 

b 

b 

ab 

b 

 

 

a 

b 

a 

a 

A
S 
B 

 

 
Figure 4.3.  Overall severity (% leaf area infected) for the treatments Control (- VC, - NuFilm), 
VC, NuFilm and VC+Nu of F. fulvia on tomato varieties A) ‘Big Beef’ B) ‘Celebrity’ and of P. 
xanthii on C) ‘Waltham Butternut’ squash from disease ratings taken on 5 and 7 August in the 
early stages of disease.  Letters indicate differences by treatment according to Tukey’s HSD test 
(p<0.05), capital letters in C) are for main effects of VC only, as there was no interaction. 

 

162 

a 

b 

b 

b 

b 

ab 

 

  

 

 
Figure 4.4.  Overall severity (incidence*severity) as % leaf area infected by P. xanthii for three 
winter squash species/varieties A) (Cucurbitaceae moschata) ‘Waltham Butternut’, B) C. pepo 
‘Delicata‘, and C) C. maxima ‘Blue Ballet Hubbard’ by compost tea treatment.  Columns labeled 
with the same letter are not significantly different than one another (p<0.05).  LGC = CT from 
leaf/grass/coffee thermophilic compost; DMC = CT from dairy manure based themophilic 
compost; VC = CT from vermicompost (no manure); VC+Nu = VC with NuFilm P added; 
NuFilm = NuFilm P only.

 

163 

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164 

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