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This is to certify that the

thesis entitled

Factors Influencing Primary Bud
Development Among Different Vitis Cultivars

presented by
Kendra A. Anderson

has been accepted towards fulfillment
of the requirements for

Master of Science degree in Horticulture

 

gram 51Wt

Major professor

Date April 29, 1983

0.7639 MS U is an Affirmative Action/Equal Opportunity Institution

 

 

 

MSU RETURNING MATERIAL?
Place in book drop to
LJBRARJES remove this checkout from
J-IIKIIHIL your record. FINE§ will

 

 

 

be charged if book is
returned after the date
stamped below.

J
‘l

 

——__.__ *1 m* ———
”M t._ -

FACTORS INFLUENCING PRIMARY BUD DEVELOPMENT
AMONG DIFFERENT VITIS CULTIVARS

By

Kendra A. Anderson

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF SCIENCE
Department of Horticulture

1983

mi —</53y

ABSTRACT

FACTORS INFLUENCING PRIMARY BUD DEVELOPMENT
AMONG DIFFERENT VITIS CULTIVARS

By

Kendra A. Anderson

Spring bud development of seven grape cultivars was observed
for three years in several vineyards. The cultivars were compared and
ranked according to-rate and earliness of growth.

An attempt to use weather data as a predictor of development
was made. Several heat unit formulae were statistically tested but
only the number of days over threshold temperatures of 50°F.and
45°F and time were found to be good predictors of bud burst.

Fall pruned and spring pruned 'Concord' vines showed little
difference in bud development. Only when the canes were left long
(more than 15 nodes) was growth retardation of 2-3 days observed.

Horizontal canes developed more rapidly than vertical canes.

ACKNOWLEDGMENTS

I would like to express my appreciation to the members of my
committee, Ceel Van DenBrink and Dr. Amy Iezzoni. A special thanks
is extended to my major professor, Dr. G. Stan Howell, for encourage-
ment and assistance.

I wish to thank my colleagues, friends, and family for their
support. The whole viticultural research team was a pleasure to work
with, especially Tim Mansfield and Jim Wolpert who assisted me in

data collection and analysis many times.

ii

TABLE OF CONTENTS

Page
LIST OF TABLES . . . . . . . . . . . . . . . . vi
LIST OF FIGURES . . . . . . . . . . . . . . . iv
INTRODUCTION . . . . . . . . . . . . . . . . 1
LITERATURE REVIEW . 2
Plant Structure and Function 3
Role of Dormancy 6
Phenology Models 8
MATERIALS AND METHODS . . . . . . . . . . . . . 13
Direct Comparisons and Ranking . . . . . . . . 13
Predictive Models . . . . . . . . . . . . . 16
Histograms . . . . . . . . . . . . . . 20
Cultural Factors and their Effect on Concord
Development . . . . . . . . . . . . . . 21
RESULTS . . . . . . . . . . . . . . . . . . 22
DISCUSSION . . . . . . . . . . . . . . . . . 30

 

Table

10.
11.
12.

13.

14.

LIST OF TABLES

Cultivars, vineyards, and years used in this study .
Origin of weather data used

Percentage of buds in each of the developmental cate-
gories at Tabor Hill Vineyard in spring of 1980 .

Percentage of buds in each of the developmental cate-
gories at HRC Vineyard in spring of 1980

Percentage of buds in each of the developmental cate-
gories at Sodus Vineyard in spring of 1980

Percentage of buds in each of the developmental cate-
gories of Sodus Vineyard in the spring of 1979

Table of H.D. Days for each cultivar, vineyard, and
heat unit formula at the date when each has 50% of
buds at burst . . . . . . . . .
Ranked onsets of growth in 1980

Ranked rate of bursting in 1980

Onset of growth in 1979 .

Classification of growth onset and rate in 1978 at SHRS .

Comparison of percentage of buds per developmental
category on the same dates, same year, and cultivar
at different vineyards, 'Baco Noir' and 'Seyval'

Comparison of weather conditions in 1980 and 1981, for
the cultivars at the Sodus HRS for the last observa-
tion date in April and an observation date in early
May . . . . . . . . . . . .

Effect of time of pruning and cane length on winter
kill of 'Concord' grape buds, percent dead primaries

iv

Page
14
19

35

36

37

39

41

42

43

44
45

46

47

48

 

Table Page

15. Effect of spatial orientation of canes on phenological

devevelopment of 'Concord' grape buds . . . . . . 49
16. Percent primary buds at dormant or scale crack stages . 50
17. All pair-wise comparisons using Tukey's H.S.D. test for

unbalanced replication . . . . . . . . . . . 51
18. Coefficients of variation for all cultivars . . . . 52

 

 

 

 

 

Figure

10.

LIST OF FIGURES

Calculations of heat units using four methods for
an example day . . . . . . .

A—P. Percentage of buds at burst are shown versus
dates of observation. The cultivar and year are shown
for each figure . . . . . .

Coefficient of variation for daily max-base versus
base temperature. The lowest C.V. gives the best
base temperature to use for a given cultivar .

Coefficient of variation for daily mean-base versus
base temperaures. The lowest C.V. gives the best
base temperature to sue for a given cultivar .

Coefficient of variation for number of days over the
base. The lowest C.V. gives the best base tempera-
ture to sue for a given cultivar . .

Coefficient of variation for Lindsay and Newman heat
units. The lowest C.V. gives the best base tempera-
ture to use for a given cultivar .

Using 'Baco Noir' as an example, the different models
are compared using the C.V. at the 45° threshold.
The lowest C.V. gives an indication of the best model
to use for the cultivar and threshold .

Using 'Aurore' as an example, the different models are
compared using the C.V. at the 45° threshold. The
lowest C.V. gives an indication of the best model to
use for the cultivar and threshold

Using 'De Chaunac‘ as an example, the different models
are compared using the C.V. at the 45° threshold. The
lowest C.V. gives an indication of the best model to
use for the cultivar and threshold

Percentage of buds in each developmental category at
Table Hill vineyard in the spring of 1980 . .

vi

Page

17

53

62

62

64

64

66

66

68

7O

 

Figure

11.

The percentage of buds in each developmental category
at Tabor Hill vineyard in the spring of 1980

vii

Page

72

INTRODUCTION

Michigan ranks fourth in the United States in grape and grape
products production (59). In 1981, Michigan growers harvested 53
thousand tons of grapes which sold for $14.4 million (27). The value
of the grape crop has been modestly increasing through the years due
to inflation and a shift toward growing the more valuable wine grapes.
Although the acreage devoted to grape production is shrinking, the
value of Michigan's crop is increasing. With such a valuable crop,
growers are increasingly interested in frost protection systems to
reduce damage from late spring frosts. To economically operate pro-
tection systems, the cold hardiness of developing grape buds must be
known and development must be able to be predicted based on easily
measurable environmental factors.

This research was undertaken to compare spring development
of the standard cultivar, 'Concord' with recently introduced grape
cultivars, to test the accuracy of several heat unit models used to
predict primary bud development, and to evaluate cultural practices

and how they affect bud development in 'Concord'.

 

REVIEW OF LITERATURE

The prediction of spring bud development in the grapevine
would be an asset to the growers in Michigan. This state has become
notorious for having late spring freezes after long periods of mild
weather. The warm days initiate bud expansion and a late spring
freeze can devastate the crop for that season by damaging the buds.
The premise for this research lies in the different hardiness levels
of the bud development stages. When buds are dormant, they are far
more resistant to cold injury than after they begin to open in the
spring. The more advanced the developing bud, the more sensitive it
is to freezing temperatures (33). For example, buds at "full swell"
were reported to withstand -4.5°C while dormant buds can withstand
much lower temperatures (31).

As many new grape cultivars become commercially important, it
is desirable to quantify the differences between them. This has been
done in other crops such as apples (5). An accurate estimate of
apple bloom can also assist with spray planning, thinning programs,
work crews, and blossom festivals.

In addition to helping plan spring work, there is an indication
that the harvest time is based to a large degree on the date of bloom
in apples (5). Therefore, the timing of early spring development of
the flowers and small fruits was found to be more effective in deter-

mining harvest time than weather occurring in the middle of summer (20).

2

 

 

 

There is evidence that a similar pattern of growth exists in grape-
vines as well. The first 100 days of the growing season after
April 1 seem to be the most important for determining harvest time
(55).

For Michigan, the ideal grape cultivar would be one that
begins development rather late in the spring, (when there is less
chance of a spring freeze) and develops rapidly. Breeders of new
grape cultivars may be able to select seedlings having these character-
istics (31). A better understanding of the interactions between
spring temperatures and bud growth and development would be a boon

to both growers and students of phenology.

Plant Structure and Function

 

Woody species in the temperate zone must respond to seasonal
changes irI their~ environment. They have adapted by becoming dormant
in the winter. Woody species must have a mechanism to survive the
cold and still flower and fruit in the summer season. The plants we
usually think of as commercially important fruit producers, all flower
in the spring and have the summer to mature their fruits. Unlike the
tree fruits, woody vines, such as grapes, have a growth habit result-
ing from a strong apical dominance. Because of the nature of their
growth pattern, the apical buds on [itis canes begin growing first,
and development continues proximally from the distal end of the cane
(6,7).

The roots may have an input to spring bud development by

mechanical action. Roots do not undergo a dormancy like the upper

part of the plant (51). They continue to grow until they get too cold
and resume growth when the ground thaws. The first stages of bud
development are probably the result of water coming into the bud and
making it swell. Roots themselves cannot initiate development if the
tops of the plants are still unprepared; they must work together with
the crown and trunk and buds.

The crown and trunk are exposed to the elements and appear to
enter a rest period (51). They must receive a minimum amount of
chilling before they are capable of serving the buds. Esau observed
the plugging of the phloem tubes as the plants went into winter (26).

Even with these and other changes, the primary emphasis is
on the buds as the "seat of rest" (51). The buds grow after the
crown and trunk are active again. It is common to prune dormant grape-
vines on a warm day and see the spring flush of sap dripping from the
fresh cuts. The vine is active at this stage, yet the buds appear
dormant.

If the buds are the seat of rest and growth, it is appropriate
to review their morphology. In the grapevine the buds are mixed, that
is, they contain both flower and shoot primordia (59). At the node,
there is usually a compound bud, having both a primary and secondary
bud along with a less well developed tertiary (54). Stergios and
Howell studied the various degrees of cold hardiness in these three
bud types (54), and noted that the primary was the most fruitful and
least hardy, while the secondary and tertiary buds were less fruitful
‘and more hardy. The hardiness levels can differ by as much as 10°C

between the primary and secondary buds.

 

 

 

The primary bud develops first and represses the development
of the secondary and tertiary companion buds. When buds open in the
spring, the shoot which will arise from it is mostly differentiated.
The apex of the flower clusters may, however, be a disorganized mass
of meristematic cells (59). The shoot begins organization in the bud
the summer before it will emerge. The first initiation of clusters
begins in early June in California (59). The meristem becomes bilobed
as a cluster is differentiated. One lobe becomes the cluster and the
other continues as the growing point (59). This is the fundamental
process resulting in the zig-zag or sympodial growth form of grape
canes.

Flower differentiation in the grape is regular. The first
thing to be organized is the calyx tissue, then the corolla, then
stamens, and finally, the pistil. yjtj§_flowers have two carpels,
from which four ovules arise. The ovary is epigynous and flower parts
are in fives (32).

As buds begin to develop, the apical dominance of the plant
dictates that the distal buds open first. Buds along a cane operate
in pairs, on the same side of a cane. Pairs develop together, open—
ing at the same time (8). As the buds develop, they pass through
distinct stages named by Baggiolini (13). The first stage is the
dormant stage (D). The second stage, called scale crack (SC), is
characterized by the parting of the bud scale and emergence of the
leaf rolled inside. The next two stages are swell one and well two
(31, $2). Swell one has a globular bud of a doeskin color. Swell

two is tinged with pink and is 1.5—2.0 times longer than it is wide.

 

The burst stage (B) is defined as the dehiscence of the bud, exposing

the first flat leaf.

Role of Dormancy

 

In order not to use confusing or ill-defined terms in the
paper, I will use terms as defined by Samish (51). Dormancy is the
"temporary suspension of visible growth . . . without regard to its
cause." There are two reasons why a plant may be dormant. The first
may be extremely harsh external environmental factors, such as drought,
high or low temperatures, etc. This type of dormancy caused by
external factors is called quiescence.

The second kind of dormancy is caused by internal factors.
Even in mild weather, for example, unchilled grape buds will not grow
until their chilling requirement has been satisfied. This is called
the resting state. The term rest specifically excludes dormany caused
by internal factors (within plant), but external to the bud. This
type of dormancy has been called correlated inhibition. An example
would be the dormancy imposed upon a basal bud by active apical buds.

The entrance of woody plants into rest is preceded by quies-
cence as the result of environmental factors like short days of
autumn or freezing temperatures. From quiescence, the buds move
into preliminary rest. In this state, buds will not grow if returned
to a favorable environment, but can be easily forced by cold, heat,
wounding, anesthetics, etc.

As time goes on, the buds enter mid-rest. It is very diffi-
cult to force buds in this state to grow. Even if they can be

prompted into some response, it is often minimal or abnormal.

 

The buds later move into a state called after rest, which has
the same characteristics as preliminary rest. Usually, this is
followed by another quiescent period. The last quiescent period is
often called induced or imposed dormancy. These stages of dormancy
have been described in many woody species (14,36,61,43,12,37).

In most woody species, rest must be broken by a chilling
period. The chilling requirement is defined as a period of cold with
or without interruption, necessary for the resumption of normal
growth. The length of time needed to break dormancy varies with the
species of plant and variety.

In the grape, a new shoot emerges from a bud, and that shoot
expands to eventually create buds of its own in the leaf axiles. The
newly created buds are rarely seen to grow until they have passed
through a winter. Under artificial conditions where the growing
points and lateral shoots were removed within six weeks of bud break,
they can be forced into growth (1). This is a good example of corre—
lative inhibition.

In most cases, however, the canes continue to grow until the
weather becomes too cold. The buds then enter quiescence, preliminary
rest, mid-rest, and after rest. Many workers have tried to pinpoint
the number of hours needed to satisfy the chilling requirement of
grapes. This is the same as trying to find where after restends and
induced dormancy begins. The answers vary due to variety differences,
different ways of evaluating the buds and even factors such as whether

or not the vines have been pruned.

 

The number of chilling units required by Vitis labrusca

 

'Concord' have been reported as follows: 830 chill units (C.U. =
1 hour exposure at 6°C) in Utah (57), over 1400 hours in a growth
chamber (39), 2,070 hours below 32°F or 3,580 hours below 45°F in
Cornell, New York (34). Other varieties of grape such as Thompson
Seedless (56), Carignane (15), or various y, vinifera have been studied
with much variation observed. In species other than grape, there is
just as much disagreement. Several varieties of peaches are discussed
by Richardson, et al. (48) and Maxwell, et al. (40). Eggert studied
the chilling requirement for twelve apple varieties and eleven species
of fruit (24).

Once the chilling requirement of various fruit varieties and
species is defined and known, important decisions can be made (48).
One can determine if there will be enough low temperature during
winter to sufficiently chill certain fruits in a given geographical
area. (This is often a problem in the southermost ranges of temperate
fruit.) One can also decide when to begin accumulating growing degree
days used in predicting bud development and fruit harvest (16,52,11,
19,49,6). One can also determine when plants are in need of artificial
cooling from sprinklers to delay bloom by determining when plants begin

to lose their cold hardiness.

Phenology Models

 

Many factors affect the spring development of buds in the
grapevine. Presumably, the factor with the most impact is air tem-

perature (28,47,52). Other workers stress the importance of

 

 

photoperiod, stating that it is the interaction of temperature and
photoperiod that cause buds to open (18,21). In guercus, it has been
shown that bud opening is dependent upon the history of irratiation
they have received, that is, buds differentiated in the shade open
before those that differentiated in the sun.

The importance of soil moisture and photoperiod in bud develop-
ment has been disputed (28,53). Generally speaking, as long as ade-
quate moisture and warmth are given, the buds will develop. Changes
from year to year in the timing of bud opening cannot be accounted
for by photoperiod and soil moisture (38,53).

Some workers have adopted the holistic approach, naming a
great many environmental and genetic factors that govern bud develop-
ment in woody species. The factors most often studies are air tem-
perture, soil moisture, light, and humidity (17,52). The author
would also add genetically controlled enzyme systems (45) which would
create differences among cultivars and species, chilling history (57),
and nutrient status (38).

Since air temperature apparently has the greatest effect on
bud development, most predictive models are temperature related (5,10,
11,9,14,19,23,20,25,30,38,44,49,50,53,55,58). They all involve the
summation of degrees of temperature and time, giving a dosage of heat
and time with response recorded as bud development (30).

The most accurate of the models use an hourly (or continuous)
temperature reading and a growth threshold or base temperature. Time

spent below the base is considered ineffective for plant growth. The

 

 

10

area under the curve but above the base is the dose the plant receives
(38,19,10,5,11,49). In all the models, growth is approximated as
linear as temperature increases because growth constants are unavail—
able for most woody species (25).

Other methods of accumulating temperatures use daily maximums
instead of hourly readings, arguing that this method introduces little
additional variation (14,53,44).

Successful models for a variety of crops were reviewed by
Anstey (5). Included are the following formulae:

1. Summation (daily maximum minus base).

2. Summation (daily mean minus base).

3. Mean monthly temperature minus base x number
of days.

4. Photothermal units (same as 1 and 2 but tem-
peratures are effective only when the sum is up).

5. Summation (minimum/base) x (maximum—base).

6. Efficiency degree days using Van't Hoff and
Arrhenius rule.

The most successful formula for apple, pear, cherry, peach,
and apricot was proved to be the first, using summation of daily
maximum temperatures above the base. The most ineffective system
proved to be efficiency degree days.

In deciding which model is most appropriate for a crop, the
most important criterion to measure is the amount of variability of
the number of degree days required to get a standard response. The
two ways variability has been measured are the standard deviation from

the mean for the degree-hour sums for the different years, and the

 

11

coefficient of variation (S.D. as percent of mean) (38,14,44,10,5,9,
11,49). The standard deviation of the temperature is considered
important. This is done for ten-day periods beginning at the date of
burst and progressing backwards to February 1. (For example, Febru-
ary 1 through June 10 equals 130 days worth of temperature accumula-
tion.) The formula with the least amount of variation was selected
as the model for the crop (38).

When several years worth of data are available, the date when
temperatures should begin to be accumulated can also be found (38).
Summations are made using various starting dates and the date giving
the least variation is used.

The use of the coefficient of variation to determine the date
after which temperature should begin to be accumulated has been
debated (9,38). The criticism of the use of this statistic has been
based on the dependence of it on the mean values. An advancement in
starting date increases the mean and thus reduces the C.V. 'When the
C.V. is plotted on a graph versus the number of days heat units are
summed, the relative rate of change can be observed. The C.V. is the
proper statistic to use and is preferred to the 5.0. when judging the
amount of variability in days (9).

The third way to decide when temperatures should begin to be
accumulated is based on the physiological state of the plant (36,52,
11,49,63). The argument is made that the plant cannot begin to
respond to warming spring temperaures until the chilling requirement
has been satisfied. The use of chronological landmarks are not appro-

priate since the chilling requirement can be satisfied early or late

 

12

in the winter. As much as a two-month difference in emergence after
rest in peach has been observed in Utah (49). It appears that the
best way to determine the date to begin heat unit accumulation is
based on the physiological state of dormancy the plant has reached.

The growth thresholds of many woody plant species have been
determined graphically using both 5.0. and the C.V. methods similar
to those just described. The 3.0. or the C.V. is plotted versus the
various threshold temperatures used to calculate heat unit summations.
A graphical interpretation gives the base temperature with the least
variability (38).

An experimental approach to determining the base temperature
used low temperatures in growth chambers (5). The advantage of this
approach is the direct evaluation of the plant's physiological status.

The field observations and their interpretations that follow
use some of the techniques presented here to compare models of growth,

varieties, and threshold temperatures.

 

 

MATERIALS AND METHODS

This study consisted of four parts. The first involved careful
observation of bud development of different cultivars, in different
vineyards for three years. Ranking by cultivar, vineyard, and year
showed a direct comparison of bud development.

The second portion of the study used statistical methods to
attempt to predict certain stages of bud development based on growing
degree days. The F max test by Bartlet was used to ascertain whether
or not grape bud development was related to accumulations of heat
units of several types.

The third section was devoted to histograms showing percentages
of buds in developmental categories and how the percentages changed
as time progressed. In addition, a fourth study of cultural manipu-

lations and how they effect bud development was done.

Direct Comparisons and Ranking.

 

The cultivars studies were ‘Aurore', 'Baco Noir', 'Concord',
'De Chaunac', 'Seyval', and 'Vidal'. The vines evaluated were planted
to an 8'I spacing within the row and 10' between rows and were at
least eight years old, in good health, and pruned to a balanced prun-
ing formula appropriate to the cultivar. 'Concord' and 'Baco Noir'

were pruned to a 30 + 10 formula and all others were pruned to 10 + 10.

13

 

14

All canes used for evaluation were 8 nodes in length, coming from a
bilateral cordon on the top wire at a height of 1.8 meters.

The exception to this is 'Baco Noir' at the Tabor Hill vine-
yard which was trained to a Geneva double curtain trellis at a height
of 1.8 meters.

A list of the cultivars, their corresponding vineyards, and

years evaluated is shown in Table 1.

TABLE 1.--The seven grape varieties studied are shown versus the five
vineyard locations used. Not all varieties were grown at
all locations. The years that spring data was taken are
shown in the body of the table for a variety and location.

 

 

 

 

 

Locations
Varieties
MSUHRC SHRC Warner Lawton Tabor Hill
Aurore 1978,'79,'80 1980
BaCO NOir 19789.799'80 1980
Concord 1978,'8O l978,'79,'80 1980

 

0e Chaunac 1980 1978,'79,'80

 

 

 

Seyval 1978.'79.'80 1980
Vidal 1978,'79 1980
Vignoles 1980 1980

 

 

 

 

 

 

The bulk of observations were done at Sodus Horticultural
Research Station of Michigan State University (SHRS), in Sodus,
Michigan. Data were also taken at the Horticulture Research Center

of Michigan State UniversityV(HRC), located in East Lansing, Michigan.

 

 

15

In Lawton, Michigan, both the Warner vineyard and the vineyard of the
William Cronenwett family (designated the Lawton vineyard) were studied.
The Tabor Hill winery is located in Buchanan, Michigan.

Bud devel0pment was recorded as frequency data similar to the
system used by Baggiolini (13), Weeks (57), and Johnson (33). The
categories are abbreviated by a notation as follows:

0 --Dormant, showing no growth or swell.
SC~-Scale crack, showing a break of the bud scales and a
slight visible shoot.
Sl--Swell 1, earlier swell stage, globular.
,82--Swell 2, later swell stage with much more elongation
than 51, length 1.5 times longer than wide.
B —-Burst, stage when Unafirst leaf comes away from the

surface of the bud.

The total number of buds observed is given in the tables
reporting the data for 1980 observations. In 1979 100 buds were
selected at the outset of the observations and the number observed
decreased due to bud loss during the experiment. Percentages of
remaining buds were given in the 1979 data.

At the same vineyard, in the same year, the cultivars being
grown together were compared directly. From the developmental data,
ranking of cultivars by onset and growth rate was done. Onset was
defined in two ways. Since the easiest stage of development to identify
in the field is B, and there is therefore, less chance of error,
the onset of burst was given importance in comparing growth. Growth
really begins far earlier than the eye can detect it, so in addition

to onset of burst, the first bud observed in the swell one category

was used to help compare onset of growth in the cultivars.

 

16

The second facet of growth examined was the rate of burst.
This was determined by the slope of the line on a graph showing per-
centage of buds recorded at burst versus time in days. The slopes
were used in conjunction with the onset data to develop a simple rank-
ing of cultivar growth for each vineyard and year.

The variation introduced by the different vineyards and years
was compared directly in tables showing the frequency data collected.
For vineyard comparison, Sodus and Tabor Hill vineyards were compared
directly using 'Baco Noir' and 'Seyval' data because the two vineyards
had those cultivars in common.

Weather conditions in 1980 and 1981 were compared directly
using data at SHRS by comparing 'Aurore', 'Baco Noir', 'Chelois',

'De Chaunac', 'Vignoles', and 'Seyval'.

Predictive Models

 

Using the same development data from the previous observations,
an attempt was made to predict stages of development based on tempera-
ture and time-related models. Four models based on temperature were
used. The Lindsey and Newman model (38) attempted to estimate the
amount of time spent above a threshold of growth. For example, with
a maximum of 90°F, a minimum of 45°F, and a threshold (or base tem-
perature) of 50°F, the Lindsey and Newman model was the area of the
triangle over the threshold to give the number of heat units per day.
The triangle's base is 24 hours long, its height is the daily maximum
minus the daily minimum. The area of the triangle gives the heat

units (38). The other models used were daily maximum minus the base,

 

17

daily mean minus the base and number of days over the base. These
models are compared for an example day in Figure 1.

For an example day, with a maximum of 90°F and a minimum of
45°F, the different models deliver a wide variety of heat unit figures,

ranging from 426 units to 1 unit.

 

+ 90° maximum Example Day with
+ 50° threshold (base) ”lfiififlfi : Zg°E
Growth threshold = 50°F

+ 45° minimum

 

(also known as

+ 24 hrs. + base temperature)

Diagram used for Lindsey
and Newman units only.

MODELS
. , 1 90-50 _
1. Lindsey and Newman. (2(90-50) x (24 90_45 - 426

40 units

2. Daily maximum-base = (90-50)
3. Daily mean-base (90:45 - 50 = 17.5 units

4. Number of days over base 90° > 50° = 1 unit

 

Figure 1. Calculations of heat units using four methods for an
example day.

In this study, the threshold temperatures examined were 45°,
50°, and 55°F. Since the item of interest was the variance of the
cultivars in days, the models were equated by dividing the number of
heat-time units it took for a variety to reach 50% B by the average
daily accumulation of units. This gave a basis for comparison among

the models and thresholds. Since the object of this study was to

 

 

18

determine the value of modeling based on temperature, the additional
model of number of calendrical days from March 1 to 50% of burst was
included for comparison. The thermograph was placed at Tabor Hill,

HRC, and SHRS vineyards in 1980 only.

Weather data were taken with a thermograph having a seven-day
clock mechanism and a chart recording pen. A maximum-minimum thermome-
ter was used to assure precision and was checked at weekly intervals.
In a few cases, missing temperature data due to mechanical or human
error required that the weather data were estimated from the nearest
weather station of the National Oceanic and Atmospheric Administration,
the United States Department of Commerce, National Weather Service
station's maximum-minimum readings. Table 2 shows the place of origin
of the weather data used for the various locations and years.

The cultivars of grapes used were 'Aurore', 'Baco Noir',
'Concord', 'De Chaunac', 'Seyval', and 'Vidal'. The cultivar consti-
tuted the experimental treatment with the different vineyards and
years making up the replications. The frequency data collected from
all the vines within a vineyard were used to determine the one item
of interest: the date on which one-half of that vineyard's buds, of
a.cultivar3 were at burst. Different numbers of buds were used to
determine that data, and these are reported on Table 7.

Using the weather data available for each vineyard and year,
the number of daily heat units was claculated and summed from March 1
until the date of 50% burst. The heat unit sums are shown for loca-

tion and date on Table 7. The variance within the cultivars was

 

 

19

TABLE 2.--Origin of weather data used to compare models.

 

Year and Dates Location Origin of Data

 

1978 Sodus, MI. U.S. Dept. of Commerce, N.O.A.A.
Weather Station, at SHRS

 

1978 3/1-3/31 Lansing, MI. N.O.A. Weather Association,
Lansing, MI.

 

 

 

 

1978 4/1-6/1 Lansing, MI. U.S.D.C. Weather Bureau at M.S.U.
Hort. Farm

1979 3/1-3/31 Sodus, MI. N.O.A.W.A., Eau Claire Station

1979 4/1-6/1 Sodus, MI. U.S.0.C W.B. at SHRS

1980 3/1—6/1 Sodus, MI. U.S.D.C.W.B. at SHRS and student's
thermograph

 

1980 3/1-5/23 Buchanan, MI. Student's thermograph at Tabor Hill
Vineyard

 

1980 5/24-6/1 Buchanan, MI. N.O.A.W.A., Eau Claire Station

 

1980 3/1-6/1 East Lansing, U.S.D C W.B. at East Lansing, MI.,
Mi. M.S.U. Hort. Farm

 

calculated and recorded on Table 7 also. The variances were statisti—
cally tested using the F maximum test.

The means of the cultivars for each model were statistically
tested using the Tukey test or honestly significant difference test
(HSD) modified for unbalanced replication.

In order to aid the selection of appropriate thresholds of
growth, the coefficient of variation was plottedversus the three
thresholds considered. Then, using only the one threshold selected,
the models for heat unit accumulation were compared with each other

and with time.

.5“

 

20

One of the important questions asked in this thesis concerns
the use of heat units to predict bud development. For the same number
of heat units, and the same cv, is the development on that date the
same for all vineyards and years? The comparisons that could be made
were rather limited due to the fact that three observations of a culti-
var at a particular heat unit accumulation point were considered mini-
mum. Nevertheless, 'Vidal' was used first as an example variety because
it appeared to respond to the most stable way, with the lowest variance
of all the cultivars. Based on the outcome of the analysis of vari-
ance and the direct comparisons with 'Vidal', no other cultivars were

used.

Histograms

 

A series of histograms of the stages of bud development at dates
in the spring show the bud population distribution. Two cultivars,
'Vidal'euui'Baco Noir', were used. These histograms make it easy to
visualize when frost protection measures would be the most cost
effective.

Cultural Factors and Their Effect
on 'Concord' DevETopment

 

 

The time of pruning, cane length, and orientation were investi-
gated to ascertain their effects on bud development. Five treatments
were given 'Concord' canes at the Lawton, Michigan, vineyard in 1979-
1980 fall through spring. The treatments were fall pruned to 8 node
canes, fall pruned but left at 20 or more nodes, spring pruned to 8

node canes, Spring pruned to the long canes (20+), and unpruned until

 

 

 

 

21

May 15, 1980. Developmental data were taken at 2-3 day intervals on
nodes 1-8 throughout the 1980 spring using the 0, SC, $1, $2, and B
categories. Chi square analysis was done on the different treatments
to test for significance at p = .05.

As an example of an analysis of variance using this data, the
Tabor Hill, 1980, observations and Sodus, 1980, observations were used.
The analysis of variance on May 13, 1980, compared 'Baco Noir',
'Vidal', and 'Seyval' at the same site and date. To change the cate—
gorical data into numerical for the analysis of variance, each devel-
opmental category was assigned a number from dormant being one through
burst being ranked a five. The different cultivars observed at a
vineyard were considered the treatment. The replications were the

number of bud observations taken per cultivar.

 

 

 

 

RESULTS

Grape cultivars studied in the vineyards and years listed in
Table 1 all had similar patterns of growth. Grapevines have a great
tendency for apical dominance and this was very evident when taking
bud development data. The canes, all pruned to 8-node length,
developed proximally from the apical bud. The first set of tables
(3through 6) give the percentage of buds in each category for each
cultivar on each data observed.

Table 3 shows 'Baco Noir', 'Vidal', and 'Seyval' in direct
comparison at the same vineyeard and year. The number of missing
buds slowly increased in most of these studies due to mechanical injury
and insect damage. These data are particularly interesting because
'Vidal' and 'Baco Noir' are grown at the same site and clear differences
can be seen in their development. 'Baco Noir' was so early that
observations had to be started April 24, 1980, when more than 12% of
'Baco Noir' buds were in stage 82. 'Vidal' was first observed a week
later and 53.4% of its buds were still in D. 'Seyval' was midway
between the two. Nine observation trips to Sodus were required in the
six—week period of study.

At the HRC, 'Vignoles' and 'De Chaunac' could be compared in
the spring of 1980, as shown in Table 4. 'De Chaunac' appeared to be

a faster developer than 'Vignoles'. On May 8, 1980, only 46.2% of the

22

23

'Vignoles' had reached S2 or B; but 97.9% of the 'De Chaunac' buds
had reached 52 or beyond.

Table 5 shows how 'Aurore', 'Baco Noir', 'Concord', 'De
Chaunac', 'Vignoles', and 'Seyval' developed as time progressed at
the SHRS in 1980. 'Baco Noir' again was the earliest to begin growth.
On May 5, 1980, ‘Baco Noir' had 25.8% of its buds at burst, and only
'Concord' (with 4.6%) had any at that stage at all. Among 'Vignoles',
'Seyval', 'Aurore', and 'De Chaunac', it is difficult to say whether
any were faster than the others. The first buds at B or beyond were
noted for all of them on May 9, 1980, (although 'De Chaunac' had
rougly 10% more at B than 'Aurore' and 'Seyval' and 13.6% more than
'Vignoles'). Comparing the four cultivars at early stages and lumping
0 and SC together, we see 'Seyval' way ahead with 20.2% beyond 0 and
SC versus 'De Chaunac' with 5.7% beyond and 'Aurore' and 'Vignoles'
with 0%.

Table 6 shows another comparison among 'De Chaunac', 'Seyval',
and 'Aurore' in 1979 at SHRS. 'De Chaunac' was the first of the three
to show bursting with 0.7% on May 8, 1979. In this case, 'Seyval'
was not ahead of 'De Chaunac' in the early stages of D and SC. On
the first day of observation, April 26, 1979, 'De Chaunac' had 44.9%
beyond 0 and SC while 'Seyval' only had 12.7% and 'Aurore' had 0%.

Using the percentages available in Tables 3 through 6,

Table 7 was created to summarize the growth onset data for the spring
of 1980, within vineyard comparisons are shown first. The onset of
growth was somewhat hard to define, so both the date of the onset of

bursting and the date of the first observable growth (SI) were

 

 

\ - W

24

compared. At Tabor Hill, in 1980, 'Baco Noir' was the fastest
followed by 'Seyval' and 'Vidal', respectively.

At SHRS, seven cultivars were directly compared and ranked
from fastest to slowest as follows: 'Baco Noir', 'Concord', 'De
Chaunac', 'Seyval', 'Aurore', 'Vignoles', and 'Chelois'.

Only two cultivars were observed at M.S.U.H.F. in 1980. The
variety 'De Chaunac' started growth before 'Vignoles', just as it
did at Sodus.

At the bottom of Table 8 is a combination of the onset rank-
ings taken from Tabor Hill, Sodus, and M.S.U. vineyards in the spring
of 1980. With the possible exception of lAurore', the ranking is
self-explanatory. 'Aurore' was given the slow to mid onset descriptor
because even though the date of bursting put it into the mid category,
the first 31 observed was late relative to the other cultivars.

The second facet of growth, besides onset, is the over-all
rate. From the growth curves (seen in Figure 2), the slope of the
line drawn through the point of inflection of the sigmoid curve was
used to rank cultivars as shown on Table 9. By using the slope of
the line, numerical comparisons could be made. 'Seyval', at Sodus
in 1980, had a double sigmoid growth curve so both slopes were
reported. One might think cultivars that have an early onset would
develop slowly so the opening flowers would escape late spring
frosts. One might think too that those cultivars with a late onset
might have quick growth rates to compensate for their late start and

assure that they have enough time to mature their fruits and seeds.

 

 

 

 

 

25

These grape cultivars were not, however, naturally selected. Character—
istics that would insure survival cannot be dictated by the environ-
ment. The major theme running through the growth rate data in
Table 9 is that the fast starters are also fast growers; the late
starters are slow growers.

Table 9 shows the results of observations in the 1979 season
in two vineyards (Sodus, Tabor Hill). All cultivars were beginning
to burst within four days of each other.

Table 11 was adapted from Phenological development of differ-

 

ent Vitis cultivars by Anderson, Howell, and Wolpert (2). The rate
of growth is not comparable to rate defined in the previous tables.
Rate in this case is defined by percentage of buds at B or beyond
versus the number of days at 45°F or more. Note that instead of the
trend seen earlier of early starters showing fast growth, this table
shows early starters with slow growth and late starters with fast
growth. This can be explained by the redefinition of the growth rate.
An early onset cultivar has few days over 45° in which to grow in
April. Many of the days over 45° are interspersed with cold days. The
growth of grape buds is not controlled with a simple threshold switch
and so the effect of the days exceeding the threshold was diluted by
intermittent cold days. This may give support to the hypothesis that
plants must remain at a relatively high temperature for a minimum
period of time before growth begins in spring.

The onset of growth data does follow the trend noted in

Tables 8, 9, and 10. 'Baco Noir' was the first to begin growth,

 

 

 

 

 

 

26

'Vidal' was the last, and the rest were not spectacularly early or
late and very similar to each other.

So far the observations discussed have been based on percent-
ages of buds in definite categories. Table 7 brings in another facet
of spring bud development. Temperature has been used to compare
development of 'Aurore', 'Baco Noir', 'Concord', 'De Chaunac',
'Seyval', and 'Vidal'. For 'Seyval', the Lindsay and Newman chart
value with a threshold of 55°F has a significantly larger variance
than number of days over the base (55°). Type I error was less than
25%.

'Vidal' had significantly lower variance (a = .25) under daily
mean minus base (50°) than number of days over base (50° and 55°).
Daily mean minus base also had significantly lowervariance than time,
with an a level of 1% for 'Vidal'. With these exceptions, none of the
heat unit formulae were found to be significantly more accurate than
time alone or any other formula.

Data of this type have many sources of variation so a side-by—
side comparison of vineyards and years was undertaken and the results
are shown in Table 12 and 13. Table 12 shows the percentage of buds
in each developmental category for the same year, dates, and culti-
vars. Using this table, we can see the effect of the two locations
on bud development. All the data taken at Tabor Hill was significantly
different from data taken at Sodus HRS with varying levels of confi-
dence. 'Baco Noir' was not affected as much by location as 'Seyval'.
Nevertheless, this table points out the importance the vineyard site

is in spring bud development.

 

 

 

 

27

Table 13 compares years directly using the same vineyard,
dates of observation, and cultivars. The late April data in 1979
and 1980 is significantly different at the p levels shown on the
table. The early May data are allsignificantly different at the
p = .001 level. This high level of confidence in the differences
between 1980 and 1979 show how dissimilar weather conditions are
between years.

Skipping to Table 17, it will show the statistical basis of
the comparisons of models given in Table 7. The numbers in the cells
of the chart are the means of the cultivar, using a particular model
and threshold, divided by the average daily accumulations. An all
pair—wise comparison, modified for unbalanced replication, shows that
daily mean minus base, number of days over base, and time, all have
some significant differences in them between cultivars. 'Baco Noir'
and 'De Chaunac' had significantly (a = .2) fewer heat units required
to reach 50% burst than 'Vidal'. When heat units were daily mean minus
base and base was 45°F. 'Baco Noir' required significantly (a = .2)
fewer heat units than 'Vidal' to reach 50% burst when heat units were
number of days over base and base was 55°. 'Baco Noir' and 'De
Chaunac' required significantly (a = .2) fewer days to reach 50% B
than 'Vidal'. It is important to note that only mean minus base was
as good as time in picking up differences in treatments, and none of
the heat unit models were better than time alone.

Table 18 shows the coefficient of variation (standard deviation/
mean) of the cultivars and heat unit models. You will recall that

the CV unit is only used for direct comparisons and is not subject

 

 

 

 

28

to statistical tests in this case. The smaller the number, the more
superior the measurement (less variation). Figure 3 shows CV of the
daily max minus base model for all available cultivars and three
base temperatures. For this model, 45° appears to be the threshold
resulting in the least amount of variation. The best temperature to
use with the daily mean minus base model is 45°, as shown in Figure 4.
For number of days over the base temperature, Figure 5, the CV was
lowest at 45° for 'Baco Noir' and 'De Chaunac', 50° was lowest for
'Aurore' and 'Seyval' and 55° was lowest for 'Vidal'.

The CV versus the base gives 50° as the best base result in
Figure 6 as to which base is best when using the Linsey and Newman
model. The CV is plotted for time alone to show how small the statis-
tic is compared to all other models.

This point is brought home in the figure that follows, showing
the various models versus time for the threshold of choice for a cul-
tivar. Figure 7 shows that Time has a lower CV statistic than any
other model for 'Baco Noirl with a 45° base. Similarly, Figures 8 and
show Time to be superior to any other model for 'Aurore' (45° base)
and 'De Chaunac' (45° base), respectively. In summary, it would seen
that none of the models tested would be more desirable than Time alone
in predicting bud development.

The next portion of this study was devoted to cultural manipu-
lations and how they affect buds and spring development. Table 16
shows five treatments as fall-pruned 8 node canes, fall-pruned long

canes, spring pruned 8 node canes, spring pruned long canes and an

k0

 

 

 

29

unpruned control. There was no difference in primary bud mortality
among these treatments as seen in Table 14.

Table 15 shows the results of bud development around the cordon.
The sides of the cordon showed more bud development in the advanced
stages than the lower area of the cordon which was not exposed to
the sun.

Table 16 shows the five treatments on eight dates. In every
case, the 8—node canes were more advanced than the long cane treat-
ments. Fall or spring pruning had little effect in the short canes,
but in the long canes, fall-pruned seemed to have slower development
than the spring or unpruned.

Figures 10 and 11 show the varieties 'Baco Noir' and 'Vidal'
in developmental categories according to dates of observation. Frost
protection systems such as overhead irrigation might be employed if

the majority of buds are in the S2 or B category.

 

 

 

 

DISCUSSION

The first group of Tables, 3 through 6, were used to compare
the cultivars with each other in Tables 8 through 9. In Table 8 the
onset of growth of eight cultivars was ranked. Onset and rate of
growth were recognized as separate aspects of growth. Other workers
have separated onset and rate in tree seedlings (16) because they are
important characteristics to select for in breeding programs. It is
possible to use the ranking of these cultivars as an indication of
their response to spring temperatures. In Michigan, a late onset
grape cultivar would be the best at avoiding spring freeze damage.
'Chelois' and 'Vidal' would be good candidates while 'Baco Noir' and
'Concord' would not be.

Table 9 shows relative rates of growth in 1980. A fast growing
grape would be best for Michigan because of its fairly short growing
season. Several workers have observed that quick growth in the spring
dictates harvest time more than summer temperatures (20,50,49,55).
For our state then, the cultivars would be ranked 'Concord', 'Baco
Noir', 'De Chaunac', 'Seyval', 'Vignoles', 'Aurore', 'Chelois', and
'Vidal'.

Since the cultivars that had early onset of growth also grew
quickly,our ”ideal" grape variety has not yet been observed.

Table 10 shows a ranking of cultivars in 1979. The cultivars
fall into the same pattern as 1980 with the exception of the reversal

3O

 

 

 

 

I

31

of 'Vignoles' and 'Aurore'. The cultivars seem to have consistent
responses during two years and at three sites. The cultivars appear
in a different order in Table 11 because in 1978, the rate of growth
was defined as the slope of the line on a graph showing the percent-
age of buds at burst versus number of days over 45°F. In 1979 and
1980, growth rate was defined as the slope of the line at the point
of inflection of the sigmoid curve shown on a graph of percentage of
buds at burst versus time in days.

Table 7 uses spring temperature to observe the consistency of
various methods of heat unit accumulations and time of bud develop-
ment. The only factor observed in this study was temperature. Tradi-
tionally, only temperature is used in spring bud development models
(5,8,9,10,ll,14,17,19,28,29,38,44,56,46,47,49,52, 53). Based on the
literature, the growth thresholds used were 45°, 50°, and 55°.
(Lindsey and Newman consider 55° as too high for a growth threshold.)
Thresholds of growth in apple (53), and grape (57) are similar.

In the literature, there is much discussion of dormancy and
its role in spring bud development (6,11,12,14,18,36,37,40,43,45,58,6l).
The reason dormancy is so important is that the plant cannot respond
to environmental cues while it is in deep dormancy. It would be non-
sensical to begin accumulating heat units when the plant is physio-
logically unable to respond to them. Therefore, it is important to
begin accumulating whatever heat units your model uses when the plant

1 enters induced dormancy. In this study, weather data were collected
1 March I through burst. No study of the dormancy states was done

1 because the grapes entered induced dormancy far before March I.

(”-1. u

 

 

32

Even after February 1, Michigan had very few days warm enough to
contribute heat units to the accumulated total until March.

With only a few exceptions, the models were not good predic—
tors of bud development. For a model to have any merit, it must be
more accurate than guestimates. There are some problems with using
heat units to measure bud development. One of the most widely recog-
nized problems is that models are based on air temperature and buds
are responding to cane—bud temperatures. Grainger reported bud tem-
perature departures from air temperature that were considerable (29).
Evaporation and radiant energy absorption from the sun were given as
causes. Radiant energy appears to be the most important factor, warm-
ing the canes and buds above air temperatures on windless days (38,15).

Models may also be inadequate because they discount the input
of other factors (38,45,49). Some works feel that heat units cannot
be summed and used in models because how they are perceived is based
on the plant's previous history (9,41). Others feel that air tempera-
ture models would work if proper growth thresholds could be worked
out since they change as the plant develops (17). Factors found to
affect spring bud development include fertility (22), site (8,31),
and pruning (8,31).

From Tables 12 and 13, this study demonstrates the importance
of location and year in affecting bud development. If proper models
using air temperature are attempted in the future, many more years
worth of observations are needed. Ashcroft suggests six as a minimum

(11).

 

33

The last portion of this study was devoted to cultural manipu-
lations and how they effect buds and spring development. There was not
a difference in primary bud mortality based on the five pruning treat—
ments seen on Table 14. On 'Concord', then, leaving canes long or
cutting them short, no matter when it is done, does not cause winter
damage to primary buds.

Table 15 shows some observations which question the impact
of the sun's radiant heat on bud development. If growth proceeds
faster at higher temperatures, the top 120° of a horizontal cordon
should show more growth than the sides. The sides should show more
growth than the shaded lower 120°. The observations, however, show
the sides of a cane to be at the optimum for bud growth and the
upper, then lower 120° in order respectively. A possible explanation
would be that bud development has an optimum temperature which the
side buds more often obtain. The upper buds may exceed the optimum
temperature and the lower buds may be under the optimum temperature.

Table 16 gives a strong indication that long canes left at
pruning time retard bud development. This technique is an important
manipulation the growers in Michigan can use to retard spring bud
development and give themselves several days of weather ”insurance"
protection against late spring frosts.

These data support the current recommendations regarding cul-
tural practices in Michigan vineyards. The more delay in spring
development, the better because there is less chance of injury from

a late spring freeze. The lesser developed buds are hardier and can

 

 

34

better withstand cold temperatures (33). From this data we would
advise fall pruning leaving long canes to retard development, then
coming through the vineyard and shortening them in late May or early
June.

This group of observations on seven grape cultivars can be
helpful in learning the spring development characteristics from
direct comparisons in the field. Time seems to be the best predictor

of all the temperature-time related models tested. We have seen that

 

the population in a field is normally distributed in regard to its
spring development. The last observation from this data is that long
canes retard spring development and if left will provide a hedge

against spring freezes of about two to three days.

35

TABLE 3.--The percentage of buds in each developmental category at
Tabor Hill vineyard in_the spring of 1980. Categories were
designated: dormant (0), scale crack (SC), swell 1 (S1),
swell 2 ($2), burst (B), missing (M), total number of buds
recorded (Total), and number of buds given a 0 through B
rating (T—M).

 

 

 

 

 

Date Cultivar 0 SC 51 $2 B M Total T-M
4-24-80 Baco Noir 3.6 48.1 35.9 12.3 0.0 4.6 808 771
4-28-80 Baco Noir 3.9 10.2 68.4 17.4 0.0 2.7 752 735
5-1-80 Baco Noir 2.1 22.7 55.6 19.5 0.0 6.3 760 712
5-5-80 Baco Noir 4.2 .1 22.9 52.7 12.9 6.7 736 687
5-9-80 Baco Noir 1.9 2.7 7.1 19.3 61.9 3.4 718 693
5-13-80 Baco Noir 0.5 .7 9.4 5.8 83.6 17.2 728 603
5-1-80 Vidal 53.4 46.6 0.0 0.0 0.0 1.1 840 831
5-5-80 Vidal 12.4 81.9 5.7 0 0.0 1.6 832 819
5-9-80 Vidal 36.9 43.8 17.0 .0 0.0 0.6 805 800
5-13-80 Vidal 39.1 27.9 13.2 16.2 2.8 1.5 856 847
5-16-80 Vidal 25.0 32.8 14.5 19.4 8.2 2.9 856 831
5-20-80 Vidal 23.5 22.2 13.4 15.7 25.2 1.3 840 829
5-23-80 Vidal 8.3 11.1 5.9 25.6 49.1 2.0 840 823
6-2-80 Vidal 23.2 2.2 0.7 0.4 73.6 1.3 840 829
4-24-80 Seyval 37.5 57.3 5.2 0.0 0.0 0.6 768 763
4-28-80 Seyval 18.4 70.6 10.9 0.0 0.0 0.9 784 777
5-1-80 Seyval 24.6 71.6 3.8 0.0 0.0 1.0 792 782
5-5-80 Seyval 7.1 36.9 51.6 4.4 0.0 2.6 792 771
5-9-80 Seyval 7.0 19.2 39.2 33.8 0.8 1.8 769 760
5-13-80 Seyval 5.8 10.5 18.9 48.9 15.9 4.4 768 734
5-16-80 Seyval 4.6 7.8 10.1 39.4 37.9 7.1 800 743
5-20-80 Seyval 7.1 2.5 5.4 17.8 67.2 5.8 752 708
5—23-80 Seyval 6.5 .9 2.8 3.3 86.6 5.8 760 716

 

in. i

I II"

 

 

36

Table 4.--The percentage of buds in each developmental category at
the HRC vineyard in the spring of 1980

 

 

 

Date Variety 0 SC $1 82 B M Total T-M
4—29-80 Vignoles 13.9 86.1 0.0 0.0 0.0 1.3 80 79
5—2-80 Vignoles 15.2 84.8 0.0 0.0 0.0 1.3 80 79
5-6-80 Vignoles 6.4 20.5 30.8 42.3 0.0 2 6 80 78
5-8-80 Vignoles 3.8 10.0 40.0 46.2 0.0 0.0 80 80
5-12-80 Vignoles 1.3 3 8 16.4 72 I 6.3 1.3 80 79
5—14—80 Vignoles 1.3 2 6 11 5 50.0 34 6 2.6 80 78
5-19-80 Vignoles 0.0 0 5 3 42.1 52 6 5.0 80 76

 

4-29-80 De Chaunac 16.8 73.4 9.8 o. 0.7 144 143
144 144

0.7 144 143

5-2-80 De Chaunac 0.0 34.7 65.

O

C)

O

O

U‘l

030
O

#OO
0

COD
0
O

5—6—80 De Chaunac 36. 58.

O
\l
O

5-8-80 De Chaunac 1.4 22.7 75.2 2.1 144 141

93.7 1.4 144 142

O
\1
O
OO
O
\1
4:.

5-12-80 0e Chaunac

 

 

37

TABLE 5.--The percentage of buds in each developmental category at
the SHRS in the spring of 1980.

 

 

 

 

Date Variety 0 SC SI S2 B M Total T-M
4-25-80 Baco Noir 4.2 45.4 47.5 2.8 0.0 2.1 144 141
4-28-80 Baco Noir 2.7 36.2 44.3 16.8 0.0 2.0 152 149
5-1-80 Baco Noir 0.7 10.3 50.0 34.9 0.0 3.9 152 146
5-5—80 Baco Noir 0.0 6.8 20.4 46.9 25.8 3.3 152 147
5—9-80 Baco Noir 0.7 0.7 11.9 23.8 62.9 .0 143 I43
5—13-80 Baco Noir 0.0 0.7 7.3 2.2 89.8 9.9 152 137
4—28-80 Vignoles 63.8 36.2 0.0 0.0 0.0 0.0 224 224
5-1—80 Vignoles 60.4 39.6 0.0 0.0 0.0 1.5 200 197
5-5—80 Vignoles 26.1 27.1 43.6 3.2 0.0 2.7 224 218
5-9-80 Vignoles 15.8 15.4 18.1 50.2 0.4 1.3 224 221
5-16-80 Vignoles 3.7 7.0 16.7 44.2 28.4 4.0 224 215
5—20—80 Vignoles 3.5 0.4 6.7 27.2 62.5 6.7 240 224
5-23-80 Vignoles 1.8 0.9 0.9 9.0 69.5 7.1 240 223
4-28—80 Seyval 36.8 42.9 20.2 0.0 0.0 5.0 120 114
5—1-80 Seyval 34.5 16.8 48.7 0.0 0.0 5.8 120 113
5-5—80 Seyval 22.6 6.6 30.2 40.6 0.0 5.3 112 106
5-9-80 Seyval 29.3 1.8 7.3 56.9 4.6 2.7 112 109
5—13—80 Seyval 28.3 0.0 2.6 28.3 40.7 5.8 120 113
5-16—80 Seyval 22.2 0.0 1.8 19.4 56.5 10.0 120 108
5-20—80 Seyval 19.8 0.0 0.9 2.8 73.6 11.7 120 106

 

 

 

 

 

 

 

 

38

TABLE 5.——Continued

Date Variety 0 SC 51 52 B M Total T-M
4—25-80 Aurore 66.5 33.5 0.0 0.0 0.0 2.7 224 218
4-28-80 Aurore 55.9 44.1 0.0 0.0 0.0 1.8 224 220
5-1-80 Aurore 46.9 47.4 5.7 0.0 0.0 4 0 200 192
5—5-80 Aurore 21.9 42.1 28.1 6.1 0.0 1.7 232 228
5—9-80 Aurore 19.9 14.3 20.8 40.7 4.2 0.0 216 216
5-13-80 Aurore 15.1 10.3 3.3 42.4 28.8 5.5 224 212
5-16-80 Aurore 15.1 8.7 4.5 22.8 48.8 5.6 232 219
5-20-80 Aurore 16.6 0.5 2.8 8.5 70.6 9.5 232 211
4-25-80 0e Chaunac 43.1 52.3 4.6 0.0 0.0 1.1 176 174
4-28-80 0e Chaunac 33.3 60.9 5.7 0.0 0.0 1.1 176 174
5-1-80 De Chaunac 22.8 55.0 22.2 0.0 0.0 2 8 176 171
5-5-80 De Chaunac 8.0 26.0 54.0 11.5 0.0 1.1 176 174
5-9-80 De Chaunac 12.4 7 1 13.6 52.7 14.2 N.D. 169 169
5-13-80 De Chaunac 6.8 2 5 5 1 34 9 50.2 8 2 256 235

 

4—25—80 Concord 52.0 46.5 7.3 0.0 0.0 1.7 296 291
4—28—80 Concord 33.4 50.2 16.4 0.0 0.0 1 8 280 275
5-1-80 Concord 32.8 38.1 28.7 0.4 0.0 2.6 272 265
5-5-80 Concord 8.5 14.2 23.1 49.6 4.6 1.5 264 260
5-9-80 Concord 4.5 3.8 9.4 24.1 57.7 2.9 272 265
5—13-80 Concord 1.7 0.9 2.2 8.2 87.0 9.8 256 231

 

 

 

39

TABLE 6.—-The percentage of buds in each developmental category at the
SHRS in the spring of 1979

 

 

 

 

 

Date Variety 0 SC S1 $2 B Total
4-26-79 De Chaunac 28.9 26.1 44.6 0.3 0.0 100
4—29-79 0e Chaunac 31.3 48.4 20.3 0.0 0.0 100
5—1-79 De Chaunac 30.0 37.7 32.2 0.0 0.0 100
5—5—79 De Chaunac 25.7 47.8 26.5 0.0 0.0 100
5—8-79 De Chaunac 14.4 21.4 25.2 38.4 0.7 100
5-10-79 De Chaunac 20.9 7.9 5.1 15.6 50.5 100
5-12-79 De Chaunac 5.6 1.6 3.5 5.2 84.0 100
4-26—79 Seyval 23.8 63.4 12.7 0.0 0.0 100
5-1-79 Seyval 4.2 63.9 31.9 0.0 0.0 100
5-5—79 Seyval 26.4 62.5 11.1 0.0 0.0 100
5—8-79 Seyval 27.4 23.0 21.8 27.8 0.0 100
5-10-79 Seyval 7.6 1.9 7.4 37.3 47.3 100
5-12—79 Seyval 0.0 0.0 3.1 6.0 91.0 100
4—26—79 Aurore 45.8 54.2 0.0 0.0 0.0 100
5-1-79 Aurore 44.6 i 55.4 0.0 0.0 0.0 100
5-5-79 Aurore 26.3 71.5 2.2 0.0 0.0 100
5-8—79 Aurore 4.4 40.0 37.1 19.0 0.0 100
5-10-79 Aurore 5.4 16.2 6.3 32.7 40.7 100
5-12-79 Aurore 1.2 4.3 6.1 9.0 79.4 100

 

 

 

l—i > ‘ ~tq—«r f

 

 

 

 

40

TABLE 6.--Continued

Date Variety 0 SC $1 $2 B Total
4-26—79 Chelois 91.4 9 O 0 O 0.0 0.0 100
5-1-79 Chelois 54.7 45.3 0.0 0.0 0.0 100
5-5—79 Chelois 26.0 74.0 0 0 O 0 0.0 100
5—8-79 Chelois 7.3 44.7 41.1 11.1 0.0 100
5-10-79 Chelois 0.0 13.8 12.5 64.1 9.0 100
4-26-79 Vignoles 66.6 32.4 0.0 0.0 0.0 100
5-1—79 Vignoles 7.0 92.9 0.0 0.0 0.0 100
5—5-79 Vignoles 19.0 74.5 1.5 0.0 0.0 100
5—8—79 Vignoles 1.5 45.7 48.3 15.1 0.0 100

5—10—79 Vignoles 1.6 16.0 15.3 49.9 21.2 100
5-12—79 Vignoles 1.4 7.0 14.3 50.9 21.2 100

 

 

4-26-79 Baco Noir 13.1 38.7 40.5 4.4 0.0 100
5-1-79 Baco Noir 3.9 47.8 44.5 3.8 0.0 100
5—5-79 Baco Noir 1.9 51.0 43.0 1.9 0.0 100
5-8-79 Baco Noir 0.0 14.2 48.9 34.3 2.5 100
4-26-79 Vidal 91.0 0.0 0 0 0.0 0.0 100
5—1-79 Vidal 85.8 14.2 0.0 0.0 0.0 100
5-5-79 Vidal 91.9 8.1 0.0 0.0 0.0 100
5-8—79 Vidal 6.3 66.7 25.1 3.4 0 0 100
5-10-79 Vidal 19.1 25.8 18.7 23.4 12.9 100
5-12-79 Vidal 14.9 11.5 9.0 20.8 44.5 100
5-14—79 Vidal 0.0 21.6 7.7 16.7 51.1 100

 

 

 

zll

 

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mm. H d 4:43 ummu xOE git
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4.44 4.44 4.44 4.44 4.44 4.44 4.44 4.44 4.44 444 4.44 444 4444 44 44444444
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42

Table 8.--Growth onset in 1980 comparing the cultivars 'Baco Noir',
'Concord', 'De Chaunac', 'Seyval', 'Aurore', 'Vignoles',
'Chelois', and 'Vidal'. Frequency data shown in Tables 3,
4, and 5 was used to obtain the date of the first recorded
bursts and the data of the first recorded swell ones.

 

 

 

 

 

 

 

 

 

Comparative . Date of First
Ranking of Cultivar gaéf1°gn21r5t recorded Recorded
Growth Onset Burst
Tabor Hill Vineyard, 1980 i
Faster Baco Noir Before April 24 May 1
I Seyval Before April 24 May 5
Slower Vidal May 5 May 9
SHRS Vineyard, 1980
Faster Baco Noir Before April 25 May 1
i Concord Before April 25 May 3
De Chaunac Before April 25 May 5
Seyval Between April 25 & 28 May 5
Aurore Between April 28 & May 1 May 5
¢ Vignoles Between May 1 & 5 May 9
Slower Chelois Between May 1 & 5 May 11
HRC Vineyard, 1980
Fasier De Chaunac Before April 29 May 3
Slower Vignoles Between May 2 & 6 May 8

 

Combination of All Vineyards Showing Relative Ranking of Onset of Growth

 

Comparative Ranking of

 

 

Growth Onset CU1thar Score
Faster Baco Noir Fast
. Concord Fast
} De Chaunac Mid
Seyval Mid
Aurore Slow-mid
Vignoles Mid
if Chelois Slow
Slower Vidal Slow

 

 

43

Table 9.—-Slope of curve of percent B versus time.
The slopes of the curves at the point of inflection on
Figures 2, A-K were used to quantify the varieties' growth.
Cultivars studied were 'Aurore', 'Baco Noir', 'Chelois',
'Concord', 'De Chaunac', 'Seyval', 'Vidal', and 'Vignoles'.
The steeper the slope the higher the number and the faster
the variety reached burst with regard to time in 1980.

 

Comparative Ranking

 

 

 

 

of Growth Rate Slope Cultivar
SHRS, 1980
Faster 16.7 Concord
9.25 Baco Noir
8.75 De Chaunac
8.75 & 5.3* Seyval
8.5 Vignoles
7.5 Aurore
Slower 6.7 Chelois
HRC, 1980
Faster 11.0 De Chaunac
¢ 9.5 Baco Noir
Slower 9.2 Vignoles

 

Tabor Hill, 1980

 

Faster 16.0 Baco Noir
¢ 7.1 Seyval
Slower 6.8 Vidal

 

Combined 1980 Rates of Development

 

Comparative Ranking

C l '
of Growth Rate U tivar

 

Faster Concord
Baco Noir
De Chaunac
Seyval
Vignoles
Aurore
Chelois

Slower Vidal

 

*Double sigmoid curve with two points of inflection.

44

TABLE 10.--Growth onset in 1979 comparing the cultivars 'Aurore',
'Baco Noir', 'Chelois', 'De Chaunac', 'Seyval', 'Vidal',
and 'Vignoles'. Frequency data shown in Table 6 from
SHRS was used to obtain the date of the first recorded
bursts and the date of the first recorded swell ones.

 

Growth Onset in 1979

 

 

 

Growth Rate Cultivar Onset of Onset of

in 1979 Bursting Growth
N.D.* Baco Noir May 5 , Before April 26
Fast De Chaunac May 8 Before April 26
Fast Seyval May 8 Before April 26
N.D. Vignoles May 7 Between May 1 & 5
Mid Aurore May 8 Between May 1 & 5
N.D. Chelois May 8 Between May 5 & 8
Slow Vidal May 8 Between May 5 & 8

 

*N.D. indicates data were not taken or were unusable.

45

Table 11.--Classification of growth onset and rate in 1978 among
cultivars at the Sodus Horticultural Research Station.

 

 

 

 

Cultivar Onset Rate
Baco Noir Early Slow
De Chaunac Mid Slow
Seyval Mid Slow
Vignoles Mid Fast
Chelois Mid Slow
Aurore Mid Fast
Vidal Late Fast

 

46

 

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47

 

 

 

 

 

 

 

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48

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49

TABLE 15.--Effect of spatial orientation of canes on phenologicai
deveiopment of 'Concord' grape buds.

 

Percent Primary Buds (Nodes 1-8) at Dormant or Scaie Crack Stages of

 

 

 

Development
Date
Cane Orientation 4-25-80 5-1-80 5-5-80
Upper 120° 92.9ab* 62.1ab 16.1ab
Middle 120° 92.5b 60.4b 11.1b
Lower 120° 95.5a 68.5a 18.4a

 

*Within coiumns, means foiiowed by different 1etters signifi-
cantly different at a = .05 by chi-square test.

Prepared by Tim Mansfieid.

 

50

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51

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00 0.00 0.0m 00.00 00.00 00.00 00.0 00.00 00.00 00.00 00.00 00.00 00>00m
000 0.00 0.NN 00.00 00.00 00.00 00.0 00.00 000.00 00.00 00.0N 00.mm 0000000 00
00 0.NN 0.00 00.00 00.00 0m.00 00.00 00.00 00.00 00.00 00.00 00.00 000000
000 0.00 N.NN 0000.00 00.0m 00.00 00.0 00.00 000.00 00.00 00.0N 00.00 0002 0000

0:02 0mm 00m 0mm oOm om? 0mm 00m om? 0mm 00m mom¢

0000 000u000m00 0000 00>0 0000 0 0000 - 0000 00000 0000 - x00 00000 00>0000o

0000: 000000000

 

 

.0000000000000 00000 00000>0

000 00 0000>00 .000000000 000 00000 0000000000 0 00000 .000>0000u 000 00 00000

000 000 00000 000 00 00000 000 00 0000000 000 .00000000000 0000000000 000 00000000
0000 A0mzv 0000000000 00000000000 00000000 0.00000 00000 00000000000 0003-0000 000--.00 00000

 

'
I: I.

 

 

52

.00-00 .00 .00000 .00000 000000>000 00000 0300

 

"0300 000<V
0 .00> .000000um 0000002 000 00000< 000 00 000000000xm 00 0000000< 000 000000 .0000 00000

 

 

 

 

 

 

 

 

000. 000. 000. 000. 000. 000. 000. 000. 000. 000. 000. 000. 0000>
000. 000. 000. N00. 000. 000. 000. 000. 000. ~00. 000. 000. 00>000
000. 000. 000. 000. 000. 000. 000. 000. 000. 000. 000. 000. 0000000 00
000. 000. 000. 000. 000. 000. 000. 000. 000. 000. 000. 000. 00000<
000. 000. 000. 000. 00m. 000. 000. 000. 000. 000. 000. 000. 0002 0000
00oz 000 com 000 000 000 000 000 000 000 000 000

0000 00y0m M00: 0000 00>o 0000 0 0000 - 0002 00000 0000 - x02 00000 00>00000

00000000> 00 000000000000

 

 

.0000>00 000 00 00000 00000000000 00000000000 000 000000 00000000

0 00 00 .0000000000 00 0000000x0 .0000 000 00 000000>00 00000000 000 00 00000

000 00 >0 000 00000 .0.0 00 00.0 0000 00000 0000000 0000 .0000000 00 0.00000000
0000000000 000 00 0000 000 00.0 0000 0000000 00000000> 00 000000000000 .0 00000
00 03000 000000>00000 000 00 0000000000 0000 000 .0000000000 000 0000000 000

.o—nwu. mwcu. cw CBOLm 0L6 mLm>waDU Ucm meUOE _._.w L00. cowpwwLm> “00 mwcmewwuvmoo w..:.!...m._n wgmdfi

 

 

53

Figure 2.A-P. Percentage of buds at burst are shown versus dates
of observation. The cuitivarandyear are shown

for each figure.

Figure

100%-

d

80%.

d

60%<

40%1
J

20%«

 

0% '

FigureZ-B

100%1

1
80%.

60%,

40%.

20%-

 

0%

 

54

Cultivar_§§§;9;§

2—A Year $212

$7 ' I9 '

U1

5/1

Dates in May

Cultivar Vidal

Year 1272

 

i7

Dates in May

 

 

55

FigureZ-C Year 1272 Cultivar De Chaunac

 

100%1'

1

80%.
J

60%«

d

40%-

q

20%.

 

 

 

0%

5/1T3H5' 7 9 11 13 15 17 19

Dates in May

FigureZ-D Year 1272 Cultivar Seyval

100%1

80%.

J
60%.

20%.

20%.

 

o%‘

*v r ——T f 1 I —fi —V—' ‘7 —'

5/1 3 5 7 9 11 13 15 1719
Dates in May

 

 

56

Figure 2-E Year 1272 Cultivar Aurore

100%‘

1

80%1

60%.

J

40%i

20%1

 

0%1 .,0.000r.00-0--
5/1 :3 5 '7 9 11 13 15 17 19

Dates in May

Figure 2-F Year 1280 Cultivar Concord

 

 

 

 

571* 3 5'7 9 '11'1371571‘7' 19

Dates in May

I
«mm. II 11‘: I"

 

57

FigureZLG Year 1980 Cultivar Concord
unpruned
100%

i
80%;

fi

60%1

i
40%i

q

20%.

 

0% 00..---00000-
9 11 13 15
Dates in May

1777 179%

mi
U1
\1

5/1

FigureZ-H Year 1280 Cultivar Aurore
100%"

80%1

.4

600*

d

uo%‘

l

20%

 

 

1

 

0%. 00 1 0 0:#=f;.. .0 . . . 0 01 . 0, . 0 . 0
5/1 3 5 7 9 11 13 15 17 19

Dates in May

 

.5“

‘.
I' II “I

 

58

Figure 2-1 Year 1980 Cultivar Chelois

100%1

80% .

1

607a .

q

40% .

1
20%‘
1

 

 

0%

U 1 f 1 fi U V V V V' V I W I T— i V v V

571 :3 5 '7 9 11 13 15 17 19

Dates in May

Figure 2-J Year 1980 Cultivar De Chaunac

100%‘
80%.

60%1
407A
J
20% 1

 

 

0%... .r.+1'..r .
5/1 3 5 7 9 11 13 15 17 19

Dates in May

 

p.11 I: i'; h

 

 

59

FigureéhK Year 1280 Cultivar Baco noir

 

100%4

T
1

80%
60%7
[+070 4

J

20%}

 

 

 

0721 1..5111T‘jr‘.a,_‘
5/1 3 5 7 9 11 13 15 1719

Dates in May

vv

FigureZ-L ‘ Year 1280 Cultivar Viggoles

100%1
80%1

60%1
1
110% 1

'1
20%,

1
0% . 1 ‘11 r . 1. 1 1 1 1 1
5/1 3 5 7 9 11 13 15 17 19

Dates in May

 

 

 

 

. v
.. .u -n '1': ll»

 

 

 

 

6O

FigureZ-M Year 1280 Cultivar_Seyxal

100%1
80%1

60%1

1.
40%
1
20%1

0% 1 1 1 1 1 1 . 111 1 1 . 1 1 . 1 .
5/1 3 5 7 9 1113 15 17 19

Dates in May

 

 

 

 

Figure 2—N Year 1280 Cultivar Vidal

100%.
80%1
60%1
40%J

20%‘

 

 

A“

V V V V f ‘1 v V V“ 1‘1 ‘7 1— Y

0%4F—4======:1 i 11 1
5/9 11 13 15 17 19 21 23 25 27

Dates in May

. m. u 'i'- 1i";

 

61

Figure 24) Year 1280 Cultivar Baco noir

 

100%5

80%.

60%-

1

40%.

1
20%‘

 

 

 

0%J V ' ' T 1 i 1 a

5/1 3 5 7 Dgtes ié May];3 15 17 19

Figure 24’ Year 1280 Cultivar Seyval

100%5

d

80%4
J
60%-
1
110711
1
20%1
J
0% 1 1 1 . 1 1

5/5 7 9 11 13 15 17 19 21 23

Dates in May

 

 

 

fij r ‘ V fif'v W

u t ,
we: r 1'. “it;

 

Figure 3.

Figure 4.

62

Coefficient of variation for daily max-base versus
base temperature. The lowest C.V. gives the best

base temperature to use for a given cultivar.

Coefficient of variation for daily mean—base versus
base temperatures. The lowest C.V. gives the best

base temperature to use for a given cultivar.

 

63

 

 

 

 

 

Figure 35 Daily Max — base
100%.1
80% y
%CV «
60% .
#00 Aurore .
7 ‘ Baco n01r
' DeChaunac
20% l
0% i7 ‘1 11 #1111921
45 50 55
Figure 4 Daily mean — base
100%].
%cv 80% 1
60% l
Baco noir
4 4 DeChaunac
001
7 Aurore
/Seyval
20% . //
1 ~1~_-_____"'#,1’/’”‘Vidal blanc
0% 1 1 11

 

1....111 I I!”

 

64

Figure 5. Coefficient of variation for number of days over the
base. The lowest C.V. gives the best base temperature

to use for a given

Figure 6. Coefficient of variation for Lindsay and Newman heat
units. The lowest C.V. gives the best base tempera-

ture to use for a given

65

Figure 5 Number of days over base
1007
80
%CV 60
40

Baco noir

20 4_,,.1’rv””dDeChaunac
;;___=:___af:::::::::Aurore
W

 

 

 

 

Seyval
O Vidal
95° 50° 550
Figure 6 Lindsey and Newman units and Time

lOO%*[

80% 1

1

60% 1
I
Baco noir
14,070 1 / Aurore
+ / S eyval
20%1

1 32:3: :7 111 Vidal

0% V" 1
Time 50v SSU

%CV

DeChaunac

 

 

 

Figure 7.

Figure 8.

66

Using 'Baco Noir' as an example, the different models
are compared using the C.V. at the 45° threshold.
The lowest C.V. gives an indication of the best model

to use for the cultivarand threshold.

Using 'Aurore' as an example, the different models are
compared using the C.V. at the 45° threshold. The
lowest C.V. gives an indication of the best model to

use for the cultivar and threshold.

67

Figure 7 Baco noir at 450threshold

100%
l
80%.
%CV
60701
J

‘ I

20%1

 

 

 

 

0%

 

dailycbiy days L&N time
max— mean-over unigs
base base base (50 )

Figure 8 Aurore at 450threshold
100%l

80%.
%CV

60%.

110911

20%1

 

 

J” I I
0% 7 W V VT
daily daily days L&N time

max— mean— over unigs
base base base (50 )

 

 

Figure 9.

68

Using 'De Chaunac' as an example, the different models
are compared using the C.V. at the 45° threshold. The
lowest C.V. gives an indication of the best model to

use for thecultivar and threshold.

 

69

Figure 9 De Chaunac at #5Othreshold
100% 1
80%
60%
40% '

209.:
1711.1 .1
daily daily days L&N time

max— mean- over uni 8
base base base (50 )

 

 

 

 

70

Figure 10. Percentage of buds in each developmental category

at Tabor Hill vineyard in the spring of 1980.

 

Baco Noir on 0-20-80
100%4

80%1

60%<

40%1

20%<

 

 

 

 

 

0% 1 1

Baco Noir on 5—1-80

100%‘
80%4
60%1

110921

”f ‘l

 

 

 

 

0% r v
D SC $1 $2

Baco Noir on 5—9-80
100%]

80%

60%

 

10%

20% ——r——:f_4_

 

 

 

 

0% 1 1 111 1

71

Baco Noir on #-28-80

100%«

80%‘

60%1

4071‘

20%1

1117—“?

0% 1 1
D SC 51 52 B

 

 

 

 

Baco Noir on 5—5-80
100%1

80%1

60%1

2107.1

 

20%1

 

 

 

 

 

e—r‘i

D SC 81 82 B

 

 

0%

Baco Noir on 5-13-80
100%

80% pun—i

 

 

 

 

 

 

 

 

Figure 11.

72

The percentage of buds in each developmental category

at Tabor Hill vineyard in the spring of 1980.

 

73

Vidal on 5-1-80
100%

80%

60%

 

 

40%

20%

 

 

 

0%

 

Vidal on 5—9-80

 

 

 

 

 

 

100%

80%

60%

40%

20%

0%

100%

80%

60%

90%

Vidal on 5—5-80

 

 

 

 

 

 

SI

82

Vidal on 5-13-80

 

 

 

 

51

$2

 

 

74

 

 

 

 

Vidal on 5-16-80 Vidal on 5—20-80
100%1 100%.
80% 80%
60% 60%
110% 40%
20%‘ 20%
0% 1 111_11 111 1 0% 1
D so 51 32 B D so 51

 

 

 

Vidal on 5-23—80 Vidal on 6-2-80
100%] 100%:
80% 80%
60% 60%
40% 40%
20% 20%

0% , 0%. 1

 

 

 

 

 

 

 

 

 

 

 

  

- I . I
m. h III ll“ ‘5. _

 

BIBLIOGRAPHY

75

 

 

 

10.

11.

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