THE PREDICTION 6F FLQWERING DATE
OF PETUNEA HYBREDA HORT.,
CV. WHéTE CASCADE

Thesis for the Degree of M. S.
MICHIGAN. STATE UNWERSITY
STANLEY J. KAYS
1 96 9

ABSTRACT

THE PREDICTION OF FLOWERING DATE OF
PETUNIA HYBRIDA HORT.,
CV. WHITE CASCADE

 

BY

Stanley J. Kays

Accurate prediction of the flowering date in

Petunia hybrida Hort. would facilitate the scheduling and

 

growing of this plant by commercial growers. With petunia,
many environmental factors exert considerable influence on
the date of flowering. Correlation of several environmen-
tal factors to provide a prediction equation for first and
fifty percent flower was undertaken.

Experiments were conducted with White Cascade be-
tween February and June of 1968 to determine the relative
effect of growing temperature, date of planting and level
of supplemental mineral nutrition on flowering and their
value as factors in a working prediction equation.

Results indicated that flowering date for Petunia
hybrida Hort., cv. White Cascade can be accurately predicted
utilizing these factors under the given environmental and

cultural conditions. Prediction equations for first and

Stanley J. Kays

50% flower were derived:

28.55 + 7.08T + 13.41t + 4.00F (l)

D

29.04 + 7.75T + 13.42t + 5.67F (2)

D50

In the equation, D represents the number of days from seed—

ing to first flower (D = days to 50% flower), T = the

50
growing temperature, t = the time of planting and F = the
level of supplemental mineral nutrients applied. The
treatment levels are coded as either the number 1 or 2.

The merits and demerits of the equations are discussed

along with the relative effects of each factor.

 

THE PREDICTION OF FLOWERING DATE OF

PETUNIA HYBRIDA HORT.,

 

CV. WHITE CASCADE

BY

Stanley J. Kays

A THESIS

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

MASTER OF SCIENCE

Department of Horticulture

1969

 

ACKNOWLEDGMENTS

Appreciation is expressed to Drs. W. H. Carlson,
Charles Cress, A. A. De Hertogh and A. L. Kenworthy for
their advice and guidance during the course of this
investigation.

Acknowledgment is made to Dr. Louis Aung for his
constructive criticism and suggestions in preparation of

the manuscript.

ii

TABLE OF CONTENTS

ACKNOWLEDGMENTS O O O O I I O C O O O O O O O O 0

LIST OF TABLES C O O O O O O O O O I O O O O O 0

LIST OF FIGURES O O O O O O O O O O O O O O O O 0

INTRODUCTION 0 O O O O I O O O O O O O O O O O 0

LITERATURE REVIEW 0 O O O O O O O O O O O O O I O

I.

II.

III.

IV.
METHODS
I.

II.
III.

IV.
V.

RESULTS

I.

II.

Light and Flowering . . . . . . . . . . .
(A) Some General Aspects of Light and
Flowering . . . . . . . . . . . . .
(B) Light and Flowering of Petunia . . .
Temperature and Flowering . . . . . . . .
(A) Some General Aspects of Temperature
and Flowering . . . . . . . . . . . .
(B) Temperature and Flowering of Petunia
Nutrition and Flowering . . . . . . . . .
(A) Some General Aspects of Nutrition and
Flowering . . . . . . . . . . . . . .
(B) Nutrition and Flowering of Petunia .
Prediction of Plant Response . . . . . .

AND MATERIALS 0 O O 0 O O O O O C O I I 0

Test Plant . . . . . . . . .
Seedling Growth . . . . . . .

Treatments . . . . . . . . . . . . . .
(A) Date of Planting . . . .
(B) Temperature . . . . . . . . . . . . .
(C) Soil Fertility . . . . . . . . . . .
Flowering Data . . . . . . . . . .
Statistical Design and Analysis . . . . .

Effect of Environmental Treatments on
Date of First Flower . . . . . . . . . .
Effect of Environmental Treatments on
Date of 50% Flower . . . . . . . . . . .

iii

Page

ii

vi

12

12
12
l3
l3
18
18
l9
19

20

20

29

DISCUSSION

SUMMARY

LITERATURE CITED

APPENDIX

iv

Page

42
46
47

51

._ .. $1

“1‘ '.‘u.‘ \ .‘f a Drum-1"

Table

LIST OF TABLES

Analysis of variance for first flower of
Petunia hybrida Hort., cv. White Cascade,
Split - Sp 1t plOt deSign o o o c o o I o I

Analysis of variance for overall regression
(first flower of Petunia hybrida Hort., cv.
White Cascade), regression coefficients,

multiple correlation coefficient and stand-
ard error of estimate . . . . . . . . . . .

 

Prediction equation for first flower of
Petunia hybrida Hort., cv. White Cascade
and residuaIs (difference between the pre-
dicted and actual number of days to first
flower) . . . . .‘. . . . . . . . . . . . .

 

Residuals for means, first and 50% flower
of Petunia hybrida Hort., cv. White
cascade O O O O O O O O O O O I I O O O O O

 

Analysis of variance table for 50% flower
of Petunia hybrida Hort., cv. White
Cascade. Split - split plot design . . . .

 

Analysis of variance for overall regression
(50% flower of Petunia hybrida Hort., cv.

White Cascade), regression coefficient and
standard error of estimate . . . . . . . .

 

Prediction equation for first flower of
Petunia hybrida Hort., cv. White Cascade
and residualSITdifference between the pre-
dicted and actual number of days to 50%
flower) . . . . . . . . . . . . . . . . . .

 

Page

24

26

27

28

36

37

39

—‘ M17 77—15?!

Figure

l.

2.

6.

LIST OF FIGURES

Page

Increase in daylength from January 1 to
may 30 O O O O O O O O O O O O O O O O O O I 14

Cumulative (weekly) solar radiation totals

in langleys are graphed in relation to date,

between the first week of February and last

week of June, 1968 . . . . . . . . . . . . . 16

The relationship of temperature and date of

planting to two levels of supplemental min-

eral nutrients to the number of days to first

flower . . . . . . . . . . . . . . . . . . . 21

The relationship of temperature and date of
planting at two levels of supplemental mineral
nutrients to the number of days to 50%

flower . . . . .1. . . . . . . . . . . . . . 30

Graphic illustration of the three factor in-
teraction between temperature, date of

planting and level of supplemental mineral

nutrients . . . . . . . . . . . . . . . . . . 33

A graph of the combination of temperature,

date of planting and level of supplemental

mineral nutrients required for selected days

to 50% flower . . . . . . . . . . . . . . . . 40

vi

 

INTRODUCTION

Hudson (21) once stated, "the condition of a plant
at any time is the summation of the effects of all the
environmental conditions it has experienced up to that
time." Although this over simplifies the situation, it
suggests that with a greater understanding and control of
the environmental factors, the more closely one can manip-
ulate and control the plant.

The prediction of plant response in relation to
various environmental factors has been investigated by many
workers. One of the early methods was to establish a cor—
relation between temperature and date of harvest. Many of
these approaches analyzed only what was considered the
major factor affecting the variability in date of flowering
or harvest. With bedding plants such as petunia, it is
known that a number of environmental factors exert consid—
erable influence on the plant's growth and subsequent
flowering (34). Petunia growers use a wide range of envi-
ronmental combinations for controlled production of plants
according to a predetermined schedule.

Since many of the presently used methods of pre-
dicting the time of flowering correlate only those envi-

ronmental factors contributing the greatest influence on
1

this response (eg. temperature), the wide range in other

factors utilized by the grower often renders them inad-

equate. Because of this, there is need for the correlation

of several environmental factors into an equation to aid

in predicting the time of flowering of petunia. An attempt

to utilize this relationship for bedding plants presents a n
complex of problems in that many factors relate both

directly or indirectly to flowering.

This study is primarily concerned with determining
the effect of date of planting, temperature and mineral
nutrients on the flowering of petunias. The specific ques-
tion which has been raised is; can sufficient variability

in flowering response be accounted for by these parameters?

REVIEW OF LITERATURE

I. Light and Flowering

 

(A). Some General Aspects of Light and Flowering:
Energy derived from sunlight ultimately supplies all the
energy for biological processes. Of the total light which
strikes the earth's surface, only a small portion, 5 to 6%,
is utilized in photosynthesis (l). The quality, duration
and intensity of light can influence the behavior of plants
in many ways: for instance, the red / far red interaction
in seed germination (30).

The term photoperiodism was first used by Garner
and Allard (14). It implies the ability of the plant to
respond to the duration of the light period. This response
has been the subject of extensive investigation since the
work in 1920. Information relating to flowering has been
both extensive and complex. As a result, a number of
generalizations have been formulated from basic facts on
flowering (40). Two of these relate to long day plants
and may be expressed as:

(1). Long day plants flower in response to day
lengths with light hours exceeding a certain minimum crit- .

ical value. At the same time, it should be noted that the

response to dark periods of less than a maximum value
appears to be more critical than the response to the light
period (45).

(ii). A combination of responses is commonly ob-
served within a single plant. Many plants are day neutral

in one particular temperature range and highly sensitive to

"T 5"” ifii

photOperiod within another range (45).
The discovery (18) of the effect of intermittent

light during the dark period led to the study of critical

It“ 1-.._____,__.__-,_. - -

day length requirement. The critical day length concept
for long day plants asserts a minimum required duration of
the light period (on a 24 hour time cycle) for flowering
to take place. Bonner and Liverman (7) suggested that
length of the light period rather than shortness of the
dark period determines the critical day length for long
day plants. At present, it is generally accepted that the
dark period when of a magnitude less than a maximum critical
value appears to be the governing factor (40). With many
long day plants (e.g. dill), a longer photoperiod, up to
the critical value, results in earlier flowering (33).
Near this critical length, very small changes in day length
have had relatively great effects on the flowering response
(24).

While it has been established that the total light
intensity is only of secondary importance (14), there are

several pertinent factors that merit review. Plants are

very sensitive to low light intensities especially at the
end of their photOperiod. The extreme daytime fluctuations
in light intensity, due to clouds, for the most part do not
affect the photoperiodic response of the plant (49). On
the other hand, clouds may, during twilight, exert consid-
erable influence on the measurement of day length (15, 45).
Craig (12), in his study, concluded that cummulative solar
energy, rather than the number of days from transplant to
flowering was the major factor influencing the flowering of

Pelargonium hortum class.

 

(B). Light and Flowering of Petunia: It was reported in
1930 that long days hastened flowering of petunia (3).
Early work on the photoperiodic requirements of this plant
suggested that night temperature could affect this response
to the point of preventing flowering. It was concluded
that petunia was day-length sensitive only between 63 and
76° F and under this regime it was a long day plant (36).
This was generally accepted due perhaps in part to the fact
that many plants were classed as day neutral at one tem-
perature and day length sensitive at another (25).

Contrary to earlier reports or opinions, van der
Vean and Meijer (48) found petunia to be a non-obligate
long day plant. Under short day conditions and low tem-
perature, flowering was materially delayed but eventually

occurred. These effects were substantiated by Piringer

and Cathey (34). Their experiments with Petunia hybrida
Hort. showed the direct influence of photOperiod on growth
and flowering. Using both early and late varieties, the
plants were exposed to either an 8 or 16 hour photoperiod.
In each case, earlier flowering occurred with the longer
photOperiod. Many workers have since derived similar con-

clusions which lend additional support (4, 5, 28, 47).

II. Temperature and Flowering

(A). Some General Aspects of Temperature and Flowering:
Sachs (39) in 1860 was one of the earlier workers to note
and record the ability of temperature to alter the earliness
of flowering in plants. The specific effect of temperature
on flower initiation was studied with Xanthium (18). The
results indicated that the temperature, during the dark
period, greatly influenced initiation of flower buds.
Conversely, varying the temperature during the photOperiod
exerted little effect on the initiation of floral primo-
ridia. Later research (27) showed that high and low tem-
peratures could modify both light and dark processes in
photoperiodism. The degree of variation depended upon the
temperature, plant species, Specific cycle, as well as the
portion of light or dark chosen.

Temperature interacting with photoperiod causing a
shift in phase and amplitude of the photoperiod has been

shown in a number of plants (8, 9, l6, 17, 32). With

1&1. ‘0 “1....-

“1‘24

Hyoscyamus, a 3 hour cold treatment during the dark period
resulted in a significant delay in flowering (41). This

is also seen with Rudbeckia bicolor Nutt. The plant will

 

flower at relatively high temperatures under photoperiods
too short to permit flowering under cool conditions. How-
ever, Rudbeckia speciosa Wenderoth, remains a long day
plant under either high or low temperature (31). Searle
(42) suggested that low temperatures may substitute in part

for darkness and high temperatures for light.

(B). Temperature and Flowering of Petunia: Roberts and

 

Struckmeyer (36, 37) showed the effect of the interaction
of temperature and photoperiod on the flowering of many
plants. With Petunia hybrida Hort., they concluded that it
was a temperature dependent long day plant. Later work
(34), however failed to support this view. The flowering
response, chronologically, may be shifted by temperature
but the photoperiodic requirement is not completely elim-
inated. The plant will flower under low temperatures and
short day conditions with an appreciable delay in flowering.
Piringer and Cathey (34) demonstrated the effect of tem-
perature on the flowering of petunia. Flowering was ear-
liest at 80° F and slightly later at 70° F while at 60° and
50° F there was a significant delay. These results have
been supported by research of a number of other workers

(4' 8, 28' 43).

 

III. Nutrition and Flowering

 

(A). Some General Aspects of Nutrition and Flowering:

 

There are numerous theories and opinions concerning the

role of inorganic nutrition in the flowering of plants (6).
Leopold (25) suggested that the rate of flower development
was affected by inorganic nutrients; but that they had
relatively little effect on floral initiation. This view
has been supported by other workers (25), however, excep-
tions have been recorded. In tests with Sinapis alb§_Linn.,
nitrogen nutrition was found to be directly related to
floral initiation (13). In this instance the photoperiodic
reaction of the plant was not principally altered but date
of flowering was appreciably modified. Very low levels of
available nitrogen favored flower initiation. Calcium and
phosphorous were also noted to exert an influence on flower-
ing behavior (19). It was suggested that the effects of
nitrogen on flowering were due to the production of "build-
ing materials" necessary for flower formation (13, 19).

A number of authors have reported that low nitrogen
levels delayed the initiation and development of flower
buds (6, 51). While prevention or restriction of vegetative
growth may induce earlier anthesis in a number of plants
(eg. cotton, grape) there are a number of cases where
flower promoting treatments also may stimulate vegetative
growth, especially for those long day plants that generally

bolt before flowering (26). An instance where promotion of

growth induced earlier flowering has been seen with gibber-

 

ellin A3 treatment of Lactuca sativa Linn. and Petunia

hybrida Hort. (50). With Phleum pratense Linn., flowering

 

was delayed by a low level of nutrition, especially in the
instance of plants induced to flower soon after germination.

With Lycopersicon esculentum Mill., Wittwer and
Teubner (51) found that high nitrogen levels (440 ppm)
favored both earlier and increased flower formation. This
was contrary to the earlier generally accepted idea that
reproductive development in plants was favored by a high
carbon to nitrogen ratio (40).

In general, the results show that low levels of
available nitrogen may promote, while in other cases it
may delay flowering in plants. The response will be spe-
cies dependent. The strong promotive effects were almost
without exception associated with long day plants while
inhibition or delayed flowering was exhibited most by short

day plants (19, 21).

(B). Nutrition and Flowering of Petunia: As is charac-
teristic of most long day plants, flowering of Petunia
hybrida Hort. is delayed by low levels of nutrition. A
number of workers (4, 5, 44, 47) have reported data which
supports this conclusion. An adequate nutritional level
results in earlier anthesis without unfavorable morpholog-

ical effects (4). When comparing the effect of frequency

10

of fertilizer application, it was noted that earlier flow-
ering occurred on those plants which had received the more
frequent application even though the total amount of fer-

tilizer applied was in all cases equal (44).

IV. Prediction of Plant Response

 

The prediction of plant response in relation to
environmental factors has been studied by a number of
workers (10, 11). Many different methods have been uti-
lized in attempts to accurately characterize the plant and
its response. One of the early methods was to establish a
correlation between temperature and date of harvest. The
length of temperature exposure was quantitatively repre-
sented in "heat units" or "degree days" (10). This pro-
cedure which was used extensively by de Candolle in 1854,
has been useful in helping to predict flowering and harvest
dates of both vegetable and fruit crOps (2). This correla-
tion, however presupposes a linear relationship between
average temperature and growth and/or flowering. It is the
general consensus that this relationship definitely does
not exist. Over a narrow range of temperatures such a
relationship may hold by approximation, and thus in rel-
atively uniform climates the heat summary expresses the
growing conditions over an entire growing season for certain

plants. With many plants, such as some of the Solanaceae

11

family where night temperatures predominately control many
plant responses, heat sums, as used currently, appear to
be of little value (40).

Since the advent of the digital computer, the mul-
tiple regression analysis has become more practical. This
allows for the simultaneous analysis of a number of var—
iables affecting a specific parameter. It has been used to
determine a number of different relationships. Carlson
(11) used plant and soil analysis data in multiple regres-
sion equations to predict the yield of roses. This, under
the Specified environmental and cultural conditions utilized,
provided a relatively accurate method for the predetermining
of yield (in this case the number of flowers produced).
Hodgson (20), with this technique, investigated the seasonal
changes in light radiation and temperature on the vegeta-

tive growth of Helianthus annus Linn. and Vicia faba Linn.

 

The results demonstrated the positive dependency of net
assimilation rate and relative growth rate on light and
temperature. Equations to predict the net assimilation

rate and relative growth rate were developed.

METHODS AND MATERIALS

I. Test Plant: Petunia hybrida Hort., cv. White Cascade

 

was selected as the test plant because of uniform growth
and flowering characteristics. Seed for these tests was

supplied by Geo. J. Ball, Inc. of West Chicago, Illinois.

II. Seedling Growth: Seeds were germinated in a 12 x 4

 

x 5 ft. polyethylene film plastic intermittent mist chamber,
located in a greenhouse. The ambient air temperature was
maintained constant at 65° F during the first 16 days fol-
lowing seeding. Bottom heat was supplied by means of
General Electric heating cables imbedded in a 3 in. layer

of perlite. The flats were held in the chamber at 70° F

for the duration of the seedling growth period. Intermit-
tent overhead mist was utilized to maintain optimum humidity
conditions. Natural phot0period and intensity was augmented
by 16 hours of light from two 40 watt cool white fluorescent
lamps placed 60 cm. above the seedlings. The interval of
supplemental illumination began at daylight in order to
coincide with the natural light source. This provided from
three to six hours of additional illumination to the natural

day length depending on the time of the year.

12

13

The germination medium consisted of steam sterilized
sandy loam soil, "Turface" and peat moss (1:1:1). Seeds
were planted in 1/4 in. trenches in flats of moist medium
and were not covered. The seeded flats were covered with
panes of greenhouse glass and remained in place until after
germination. The 16 day old seedlings at the two leaf

stage, were then transplanted into 12 x 12 x 5 cm. undivided

‘i Iw-Lfifl--_H_

thin plastic containers holding approximately 600 ml. of

the soil mix. Nine plants were grown per container. After

E Ill—13' ‘ ‘3' ’.' .o‘

transplanting, the plants were moved from the mist chamber

to greenhouse benches.

III. Treatments

 

(A). Date of Planting: Commercial petunia growers plant

 

seed and produce seedlings throughout an extended time
period (22). A preliminary test was established in an
effort to study the combined effects of a number of eco-
logical factors (eg. longer natural photoperiod, higher
daily solar radiation peaks and totals, a gradual increase
in day temperature, etc. (See Figures 1 and 2) associated
with differing planting dates.

Seed of the cultivar White Cascade were planted on
February 1, 1968 and March 26, 1968. Seedling production
methods were the same for both planting dates and were
identical with those previously described. It should be

noted that although the seedlings were started under a 16

14

.U .o .soumcflnmmz .muoum>ummno Hm>mz

mmumum popes: .moflmmo omcmEH« Havausmz an pmpa>onm

mumo .umzoam unmoumm om pcm umuflm um mm Ham3

mm pmuocmp ma mump msflucmHm some um numsmaump one
.om was CD a wannamn Scum sumsmammp aw mmmmuosfl m£B||.H musmflm

ON

----—--—----1

>(t 2;

33:0 wagon-p0 won—«9:0 page. :0 pafiappop

022.2(t pal:

bun:
gas 5

7:20:

to:

 

  

.Z<..

86

§

531.0le IN" 5'00“ “I (IISNIIS OI. lSIlNflfl

095

SM—

099
«:9

H19N 31 AVG

l6

.manmaam>m
uoc meB mmmH .mmz How mmcflpmwu coflumwpmm
A.cmmflsowz .msflmsmq pmmm um smmusm Hospmmg
.m .9 may some memos .mmma .mcsn mo x663

ummH msp pom mumsunmm mo Moms umuflm mag cmmzu

Ion .mpmp on coflumawu ca pmcmmum mum mmmHmst

ca mamuou soapmflpmu Hmaom Amaxmmzv m>apmasESUIl.m musmflm

 

A—
i

 

M
”noun 0: mm /1v101 mm: '9"

NOILVIOVII llV'IOS

DATA MISSING

MARCH APRIL MAY JUNE

WEEKS 'l-4 / MONTH

12341234123412341234
FEB.

18

hour photOperiod at both seeding dates, the natural photo-
period did increase along with a corresponding increase in
solar radiation. Figure 1 shows the natural photOperiod at

seeding and at 50% flower for both time treatments.

(B). Temperature: Thermostatically controlled night
temperatures of 60° and 70° F were evaluated with respect
to their effect on flowering date. Day temperatures were
maintained as closely as possible to corresponding night
temperatures. The temperature range selected for these
tests was based upon recommended growing temperatures for
petunia (34) and are those used by a majority of Michigan
flower growers (22). The temperature treatments were ini-

tiated immediately following transplanting.

(C). Soil Fertility: The test plants were watered twice
weekly with a 20-20-20 fertilizer solution at one of two
rates.

(1) One pound of 20-20-20 per 100 gallons of water

(240 ppm each of N03, P and K20).

2055 '
(2) Three pounds of 20-20-20 per 100 gallons of

water (720 ppm each of N03, P 05, and K20).

2
The first application was made seven days following trans-
planting and continued bi-weekly to-the termination of the
experiment. The containers were watered sufficiently to

provide for some leaching thus preventing a salt build-up

in the medium.

19

IV. Flowering Data: The number of days to anthesis was
used as a specific growth stage index. Two phases in the
development of the plant were recorded.

(A). The date of first plant in each unit of nine plants
to come into flower.

(B). The date when at least 50% of the plants per unit
were in flower.
This information was converted to number of days from seed-

ing until initial and 50% flowering and analyzed as such.

V. Statistical Design and Analysis: The experimental
design was a split-split plot with splits for temperature
and time. Variance was analyzed utilizing STAT Series
program 14 of the Michigan State University Computer Lab-
oratory (Analysis of Variance With Equal Frequency in Each
Cell). In the statistical analysis, since the main concern
was to determine if the factors accounted for sufficient
variance to allow their use in prediction of flowering
date, a multiple regression program was utilized. The
least squares of variables program STAT Series (no. 8) of
Michigan State University Computer Laboratory was selected.
This provided among other statistics, the degree of varia-
tion accounted for by each variable and the total variation
for all of the variables collectively. Using the regression
coefficients for the variables, prediction equations for

first and 50% flowering were derived.

RESULTS

I. Effect of Environmental Treatments on Date of First
Flower

At first flower, only the main effects were found
to be significant. Graphically, the response of the main

effects in days to first flower is illustrated in Figure 3.

Temperature

 

Plants grown at 70° F flowered an average of 7 days
earlier than similar plants grown at 60° F (Table 4). The
temperature treatments did not interact appreciably in this
test with either date of planting or level of supplemental
mineral nutrients applied. Because of this, the same re-
sponse in days to first flower was realized for the tem-
perature effect at varying levels of the other environmental

factors.

Planting Date

 

Plants from the later of the two planting dates
(March 26) flowered an average of 13.5 days faster than
those planted at the earlier time (February 1), Table 4.
It may be noted that considerable change in the environment
occurred between and during the two growing times. The

natural daylength (as recorded by the U. S. Weather Bureau

20

21

.Hm3on umuflm on whom mo HmQEsc map on musmwuusc
Hmnmsflfi HabcmamHQQSm mo mam>ma ozu pm mcflpsmam
mo mump paw manpmummfiwp mo masmcoflpmawn maell.m musmflm

VIMPIIAWII

VIMPIIA‘I’UII

HIGH LEVEL

OF SUPPLEMENTAL NUYIIINTS

  

 

‘ DA‘I’I OI PLANTING 2

LOW LEVEL

70

DATE Of PLAN‘I’INO

23

for East Lansing, Michigan) at the first planting was 9
hours and 58 minutes (Figure 1); whereas at the second
planting the photoperiod was 12 hours and 26 minutes. By
the time the plants in the first planting had reached first
flower, the photoperiod had increased to 13 hours and 11

minutes. With the second planting at the same morpholog-

In“

ical stage of development, the photoperiod was 14 hours

and 49 minutes.

- $-\LE.‘!'LZ 2 ’

Likewise, during the same time period, the level of
solar radiation also increased (Figure 2). The general A
trend of increase was much more random.

The date of planting did not interact significantly

in this test with the other factors under study.

Supplemental Nutrient Level

 

With the higher level of supplemental fertilizer
(3# of 20-20-20 per 100 gallons of water), the number of
days from planting to flower was reduced by 4 over the

lower level (1# of 20-20-20 per 100 gallons of water).

Statistical Results

Only main effects were found to be significant in
this study (Table 1). Consequently, the lack of significant
interaction allowed the utilization of only linear terms in
the multiple regression equation for characterization of
the response of the plants to the environmental factors

studied. Treatment means were used in the multiple

24

wins.
. ~ I

_
w 1
1.1: sh! .n . at .....1F» IMKu u... uni)“; . ,

 

 

 

 

 

 

Anamoflmflcmflm mHamHm ..c
anm.mmHm pH Hmpoe
nomm.m mmmm.mOH om AUV Houum
mmm.o mmmm.H mmmm.m mmmm.m H .Dumm x mEHB
.x .mEmB
0mm.o Nmmm.o mmmm.H mmmm.H H .pumm .x mEHB
ooo.H oooo.o oooo.o oooo.o H .unmm .x .mEmB
«emooo.o nmmv.mm oooo.mmH oooo.mmH H .uumm
anH.m hmoH.Hm OH Amv Hounm
OHh.o GGVH.0 oom>.o oomh.o H mEHB .x .mEmB
eemooo.o HmmH.Nme mmmo.omHm mmmo.omHm H mEHB
mmwm.mH mmmm.vm OH Adv Hounm
eemoo.o mmmv.mv mmmo.moo mmmo.mom H .mEmB
mum.o mvvm.o
mosmoHMHcmHm OHDmHDmum mumsvm mmumswm Socomnm mOGMHum>
mumEonummd m saw: no 55m mo mmmumma mo mousom
.smHmwp DOHQ DHHmm I pHHQm .mpmommo manz
.>o .pnom_mmmmmwm MHssumm mo Hw3on umHHm How mHQmu mosMHHm> mo,mHmmHmsdll.H mHQMB

25

regression program (Table 2). The least squares equation
obtained for the prediction of first flower was:

D = 28.55 + 7.08T + 13.41t + 4.00F (1)
In the equation, D represents the number of days from seed-
ing to first flower, T = the growing temperature, t = the

time of planting and F = the level of supplemental mineral

F11“
nutrients applied. Since two levels of each environmental g
factor were studied, the treatment levels are coded as ;
either the number 1 or 2, i.e. the values for T, t and F E
ranged from 1 to 2. Using this equation, predicted values E..

for the days to first flower were calculated and compared
with the observed values (Table 3).

The multiple regression coefficients for this equa—
tion accounted for 99.65 percent of the variability in days
to flower for the treatment means. The standard error of
estimate for the equation was 2.29. The residuals for the
means (the difference between the predicted and actual) are
illustrated in Table 4. Although adequate data were not
available to critically test the accuracy of the equation,
it was tested against the individual measurements in this
experiment (Table 3). Only two of the predicted flowering
dates resulted in a residual (the difference between the
predicted and the observed) that fell outside of one

standard deviation from the mean.

26

.
a
A. L
f!!! Ihuuuu .“ I... 3 31.13.51

 

 

 

 

 

 

mvmm.m u m I mumEHpmm mo uouum pumpcmum
momm.o H mm I psmHonmmou soHDMHmnuou mHmHuHsz
oo.v Hv.MH mo.n mm.mm mustonmmoo
muHHHDHmm wEHB MHSDMHOQEDB unapmsou
mucmHUHmmmoo sonmmHmmm
AnamoHMHcmHm sHemHm .ev

mbhm. om nonum + HMSpHmmm
«emoo.o Hmmm.mmH mHmo.va mmmH.mmv m conmmHmmm
nmmm.mmv n Hmuoe

OUCMOHMHsmHm UHumHumum mumswm moundvm Eowmmum mosMHHm>

mumEonummm m saw: no Edm mo mmmnmma mo mousom

 

GOHmmmummm HHmum>o How mOCMHHm> mo mHmmHmsd

 

 

.mumEHumm Mo Houuw pumpsmum paw ucmHonmmoo soHpmHmuuoo
mHmauHsfi .musmHOHmmmoo GOHmmmHmmH .Ampmommu muHsz .>o ..puom MUHHQNS
MHssumm mo Hmonm umHHmv QOHmmmHmmu HHmnm>o Mom mOGMHum> mo mHmmHmchI.N mHnma

27

Table 3.--Prediction equation for first flower of Petunia
hybrida Hort., cv. White Cascade and re81duals
(difference between the predicted and actual
number of days to first flower).

 

D = 28.55 + 7.08T + 13.41t + 4.00F (1)

Temperature (High) ‘ =
(Low) =

Time (Second Planting) .=‘
(First Planting =

Fertility (High) =
(Low) =

Residuals Per Unit of Nine Plants

1 tit“) .741 ‘-
In
I

 

 

T t F Actual Pred. Residual T t F Actual Pred. Residual
2 2 2 76.00 77.54 +1.54 1 2 2 66.00 64.13 -l.87
2 2 2 82.00 77.54 -4.46 l 2 2 62.00 64.13 +2.13
2 2 2 77.00 77.54 +0.54 1 2 2 62.00 64.13 +2.13
2 2 2 81.00 77.54 -3.46 1 2 2 66.00 64.13 -l.87
2 2 2 77.00 77.54 +0.54 1 2 2 65.00 64.13 -0.87
2 2 2 75.00 77.54 +2.54 1 2 2 61.00 64.13 +3.13
2 2 l 75.00 73.54 —l.46 1 2 l 60.00 60.13 +0.13
2 2 l 74.00 73.54 -0.46 1 2 l 61.00 60.13 -0.87
2 2 l 71.00 73.54 +2.54 1 2 l 62.00 60.13 -l.87
2 2 1 71.00 73.54 +2.54 1 2 1 61.00 60.13 -0.87
2 2 l 75.00 73.54 -l.46 l 2 l 60.00 60.13 +0.13
2 2 1 71.00 73.54 +2.54 1 2 l 61.00 60.13 -0.87
2 l 2 69.00 70.46 +1.46 1 l 2 54.00 57.05 +3.05
2 l 2 69.00 70.46 +1.46 1 l 2 58.00 57.05 -0.95
2 l 2 73.00 70.46 -2.54 l 1 2 65.00 57.05 -7.95
2 l 2 69.00 70.46 +1.46 1 l 2 59.00 57.05 -l.95
2 l 2 70.00 70.46 +0.46 1 l 2 53.00 57.05~ +4.05
2 l 2 72.00 70.46 -l.54 l l 2 54.00 57.05 +3.05
2 l l 66.00 66.46 +0.46 1 l l 52.00 53.04 +1.04
2 l 1 67.00 66.46 -0.54 l l l 55.00 53.04 -l.96
2 l l 66.00 66.46 +0.46 1 l 1 52.00 53.04 +1.04
2 l l 67.00 66.46 -0.54 l l 1 54.00 53.04 -0.96
2-1 1 67.00 66.46 -0.54 l 1 l 51.00 53.04 +2.04
2 l l 68.00 66.46 -l.54 1 l l 52.00 53.04 +1.04

 

28

. ‘ 1

i I? ’flvg bl u

 

 

 

 

omNH.N omON.NN OQNN.NN N N N N
mNON.HI mnmo.n> oomN.mN H N N N
mth.HI mNNN.mm oomm.nm N N H o
ooem.o OONm.mm oomH.Hm H N H m
mth.HI mth.HN ooom.mN N H N N
ooem.o comN.Nm oomm.mo H H N N
oomn.o oovm.Hm oomm.mm N H H N
mNNH.o mNNN.mm oooo.mm H H H H
NHBOHH ezmommm NamHm
oome.o ooem.>n oooo.NN N N N N
mNON.oI msmm.ma oomN.NN H N N N
mhme.ou mNNH.Nm oonm.mm N N H o
omon.o omNH.om oomN.om H N H m
mNNH.oI mnmw.on oomm.on N H N N
omnm.o omme.mo oomm.mw H H N m
omNH.o omeo.Nm OONH.Nm N H H N
mNNN.oI mNNo.Nm oonm.Nm H H H H
mHMUpHmmm w UmumEHpmm mus> w Hmsuom .unmm mEHB .mEmB .mno

 

mmBOHm EmmHh

 

 

 

.mpmommu mpH£3

.>0 ..uHom MUHHQNn MHGSHmm mo HOBOHM wom paw pmHHm .mcmmfi Hem mHmspHmmmII.v mHQme

29

II. Effect of Environmental Treatments on Date of 50%
Flower

 

The response recorded at 50% flower for the envi-
ronmental parameters was very similar to that obtained at
first flower. The index level of 50% flowering was con-
sidered to be attained when at least one half of the plants
in a unit of nine had reached anthesis. The number of days
from seeding to this stage was recorded. The data are

graphically illustrated (Figure 4).

Temperature

 

Petunia plants that were grown at 70° F reached
the 50% level of flowering an average of 7.8 days sooner
than similar plants grown at 60° F. No two-factor inter-
actions were significant, however, the three factor inter-
action was judged highly significant. This latter inter-

action will be discussed in a separate section.

Date of Planting

 

As at first flower, petunias planted at the later
date (March 26) flowered in a shorter period than those
planted the first day of February (Table 4). The March
planting reached flowering an average of 13.4 days earlier
than the earlier planting. There was also a considerable
change in the environment in which the plants were grown
following first flower. The photOperiod (Figure 1) in-
creased from 9 hours and 58 minutes on February 1, to 13

hours and 26 minutes (50% flowering). The photoperiod of

 

30

.Hmonm wom 0p hump mo Hmnfisc gnu 0H mpcmHupsc
HmumcHE prcmeHQQSm mo mHmbmH oBu um mchGMHm
mo mump paw musumummfimu mo mHanOHumHmu mQBII.v musmHm

HIGH LEVEL

OF SUPPLIMIN'I’AL NUTIIINYS

  

DAYS YO FLOWER

  

‘IIMPIIAIIIII

DA‘I’I Of PLAN‘I’INO

LOW LEVE L

V
II

on: to non:
70

.L

I

TIMPII AWII

” - —-—- ---

DAY! OF PLAN‘I'INO

32

the later planting date (March 26) approached the critical
day length for petunia when the 50% level of flowering was
attained. The light period in this case increased from 12
hours and 26 minutes at seeding to 14 hours and 58 minutes

at 50% flower (Figure 1).

Supplemental Mineral Nutrient Level

 

With the higher application of supplemental mineral

nutrients, the petunia plants reached the 50% level of

flowering an average of 5.7 days earlier than the low level.

The concentrations here were 3 pounds and 1 pound of 20-20—

20 fertilizer per 100 gallons of water, respectively.

Interaction

 

As noted, there was a significant three factor
interaction between temperature, supplemental nutrient
level and date of planting. Graphs of this interaction
are presented in Figure 5. The magnitude of the interac-
tion is exemplified by the failure of the two graphs to be
alike. One may note that the interaction, although highly
significant, is a matter of the degree of response and not
difference in kind. It is possible to examine this from
several aspects. For example, the delay in 50% flower at
the low nutrient level compared to the high level at the
early planting is (a) and (b) for the high and low tem-
perature respectively (intervals (a) and (b) in Figure 5).

The same intervals for the late planting date are (c) and

s.“'mflnu_fl

‘ 37' '. 1. 77743- "—LN"'..- .7

 

33

.mucmHupsc HmnmSHE HmucmEmHmmzm mo Hw>mH
paw mcHHGMHm mo mpmp .musvmummamp smonmn soHu
IomumucH Houomm mmusp 0:» mo COHumuumsHHH UHSQMHUII.m musmHm

34

PLANTING DATE 1

LOW

b

LEVEL OF SUPPLEMENTAL
MINERAL NUTRIENTS

O
O

NUMIER OF DAYS FROM
SEED TO 50% FLOWER

H

O

O‘
O

 

HIGH LOW
TEMPERATURE

PLANTING DATE 2

90

5 .I
g I; 80
g 2

‘
9 mm 0! suncmmu:
3§ 70 mm... m...“
I

In
3 :I

 

HIGH LOW
TEMPERATURE

35

(d) for the high and low temperatures (intervals (c) and
(d) in Figure 5). The significant three factor interaction

indicates that the lack of joint equality of intervals (a)

and (b) with (c) and (d) is not likely to be a chance event.

The main effects were found to be statistically
significant in this study (Table 5). Significance was also
noted for the interaction of all three environmental fac-
tors. The presence of a significant interaction would
normally require the use of cross-product terms in the
multiple regression equation to characterize the response
with the highest degree of accuracy. However, the over-
powering size of the main effects resulted in a relatively
minor improvement when cross-product terms were added to
the equation (2). For this reason the simpler model with
only linear terms was chosen for prediction. The treatment
means were used in the regression program. From the anal-
ysis of variance, the variability in days to 50% flower
accounted for by the regression model with linear terms
was found to be highly significant (Table 6). The regres-
sion coefficients this determined give rise to the follow-
ing prediction equation for predicting the number of days
from seeding to 50% flower.

D50 = 29.04 + 7.75T + 13.42t + 5.67F (2)
In the equation, D represents the number of days from seed—
ing to 50% flower, T = the growing temperature, t = the

time of planting and F = the level of supplemental

‘r-‘fi—‘flc—i

36

. . . v .
1 nilil .14“)... \uwz‘ififl-

 

AuamonHamHm NHsmHm .

«V

 

 

hmHm.mHmm 5v Hmpoa

oomm.v oooo.bm om HOV Houum

Nemoo.o memo.HH oooo.mv oooo.mv H .unmm x

.mEmB x mEHB

Hmm.o Hmm~.H mmmm.m mmmm.m H .unmm x .mfime

Nemooo.o vmmm.mm mmmm.mmm mmmm.mmm H .uumm

mmmo.v mmmm.ow OH Amy Houum

mHH.o ooom.N NmNo.OH NmNo.OH H msHs x .msma

Nemooo.o mnmm.mmm mmmo.omHm mmmo.omHm H mEHB

mmmm.HH hmmm.>m OH HHV Houum

«emoo.o mmmv.mm oom>.o~h oomn.omn H .9809
mocMOHMHsmHm UHHmHHMHm m mumswm smmz mmumswm mo 85m Eocemum GUQMHHM>
mumEHXOHQQH mo mmmummo mo moudom

 

 

 

psmHme uon uHHmquHHmm

.mpmommo muH£3

.>o ..unom mpHHnmn MHcdumm mo szon wom How mHQMD QOHDMHH6> mo mHmHHmcdll.m mHnma

37

r5412. 1.. I. 1. H .r

 

 

 

 

 

 

 

ommo.m n m I mmeHumm mo HOHHm pumpcmum
emnm.o u Nm I pamHonmmoo cOHumHmHHoo mHmHuHsz
hm.m m¢.mH mh.h vo.mm mucmHOHmmmou
wuHHHuumm QEHB mmusumuwmame pamumcou
mpcmHOHmmmou aonmmHmmm
HucNOHHHamHm HHsmHm «.1
ommh. om Hounm + HmspHmmm
«emoo.o mvnm.omm Hmvv.HmH mhvm.qvm m COHmmmHmmm
Hmmh.mmm n Hmuoa
mOGMOHMHcmHm UHDmHumum mumsvm mmnmswm EOUmmHm mUGMHHm>
mumEonummd m cums mo 85m mo mmmummo mo moHsom

 

COHmmmummm HHmum>o How mUGMHHm> mo mHthmam

 

 

.mumEHumm mo Houum pnmcsmum paw ucmHOHmmmoo

soHHMHmHHoo mHmHuHSE .musmHonmmoo sonmmHmmH .Ampmommo muHSB .>o ..puom
mpHHQNS MHssumm mo HmBOHm womv GOHmmmummH HHmum>o MOM mosmHHm> m0 mHmemcHII.m MHQMB

38

mineral nutrients applied. Since there were two levels of
each factor studied, the levels were coded as either the
number 1 or 2. These values were then substituted into the
equation for the appropriate treatment combination to
obtain the predictions in Table 7. Graphically, the pre-
dicted values are illustrated in Figure 6.

The multiple regression coefficients for this equa-
tion accounted for 97.94 percent of the variability. The
residuals for the means (the difference between the actual

and the predicted) are quite low in magnitude (Table 4).

F“? ' ' u- IITIT‘TTL'L': r(_.uMIn_-—u1 ‘

The standard error of estimate for the equation was 2.09.
As with the equation for first flower,-the equation for
50% flower was tested against individual measurements in
the experiment (Table 7). The residuals indicate that the
equation on the whole fairly accurately estimates the re-

quired number of days from seeding to 50% flower.

 

39

Table 7.--Prediction equation for first flower of Petunia
h brida Hort., cv. White Cascade and resiauaIs
(difference between the predicted and actual
number of days to 50% flowering).

 

 

 

D50 = 29.04 + 7.75T + 13.42t + 5.67F (2)
Temperature (High) =1
(Low) =2
Time (Second Planting) =1
(First Planting) =2
Fertility (High) =1
(Low) =2
Residuals Per Unit of Nine Plants
T t F Actual Pred. Residual T t F Actual Pred. Residual
2 2 2 85.00 82.70 -2.30 l 2 2 69.00 69.29 +0.29
2 2 2 83.00 82.70 -0.30 1 2 2 69.00 69.29 +0.29
2 2 2 87.00 82.70 -4.30 1 2 2 67.00 69.29 +2.29
2 2 2 86.00 82.70 -3.30 1 2 2 66.00 69.29 +3.29
2 2 2 85.00 82.70 -2.30 1 2 2 68.00 69.29 +1.29
2 2 2 83.00 82.70 -0.30 1 2 2 68.00 69.29 +1.29
2 2 l 78.00 77.03 -l.97 1 2 l 63.00 63.62 +0.62
2 2 1 78.00 77.03 -l.97 l 2 l 63.00 63.62 +0.62
2 2 1 73.00 77.03 +4.03 1 2 l 63.00 63.62 +0.62
2 2 1 75.00 77.03 +2.03 1 2 l 67.00 63.62 -3.38
2 2 l 76.00 77.03 +1.03 1 2 1 66.00 63.62 -2.38
2 2 1 75.00 77.03 +2.03 1 2 l 63.00 63.62 +0.62
2 l 2 73.00 74.96 +1.96 1 l 2 58.00 61.54 +2.54
2 l 2 73.00 74.96 +1.96 1 l 2 67.00 61.54 -5.46
2 l 2 75.00 74.96 -0.04 l l 2 69.00 61.54 -7.46
2 l 2 73.00 74.96 +1.96 1 l 2 62.00 61.54 -0.46
2 l 2 74.00 74.96 +0.96 1 l 2 58.00 61.54 +2.54
2 l 2 73.00 74.96 +1.96 1 1 2 60.00 61.54 +1.54
2 1 l 70.00 69.29 -0.71 1 1 l 57.00 55.87 -l.03
2 1'1 69.00 69.29 +0.29 1 l 1 57.00 55.87 -l.03
2 l l 71.00 69.29 -l.7l 1 l 1 57.00 55.87 -l.03
2 l l 69.00 69.29 +0.29 1 l l 57.00 55.87 -l.03
2 l l 69.00 69.29 +0.29 1 l l 54.00 55.87 +1.94
2 l l 71.00 69.29 -1.71 l l l 54.00 55.87 +1.94

 

355‘”.—

lrm‘“. w’w—‘fi- A. a :gr.
I

4O

.Hmonm

mom on mmmp pmuomHmm mom UmHHdme mucmHHusc

HMHmcHE HapcmEmHmmdm mo Hm>mH paw mcHusmHm mo
mump .muspmummamu mo sOHDmsHQEOO may mo ammum ¢Il.o musmHm

41

NUMBER or DAYS FROM
seen 1'0 50% ANTHESIS

I21 221

2"

 

I12 212

DISCUSSION

The response trends for the environmental factors
tested support the conclusions reached by earlier workers
in this area (3, 30, 35). The results indicated a definite
relationship between the test factors concerning the amounts
of the total variability accounted for by each. Therefore,
within the test ranges for these factors, quantitative com-
parisons can be made. Because of the nature of the statis-
tical design used, this presupposes a linear relationship
between the parameters established for each environmental
factor. Interpolation is valid if this condition is fac—
tual. The general quantitative trends are accurate esti-
mates of variation accounted for by the particular chosen
increment of each environmental factor. Extrapolation of
these relationships outside the test conditions would prob-
ably lead to error.

From the regression coefficients, it is noted that
the date of planting contributed the highest degree in
variation in days to first and fifty percent flower. The
variation between the first and second date amounted to
13.5 days for first flower and 13.4 days for fifty percent

flowering. Although the conclusion that planting date per

42

_-f"?I;

I raffle-m ar'flxlm “pt ‘4
:' I

43

se contributes the greatest effect on the flowering re—
Sponse seems logical, it is, however, not substantiated.
More correctly, the increment allocated for planting date
(the degree of difference between the two dates) accounted
for more of the variation in this test than either the
range for temperature or supplemental mineral nutrient

level.

: .' t .3’- an «In «than '

The increment of ten degrees (Fahrenheit) resulted
in a difference of 7 days to the first flower and 7.8 days

for fifty percent flowering. As the temperature is in-

 

In?

creased up to a maximum (28), fewer days are required to
obtain the flowering response. Although the linearity of
this increase has not been substantiated, the general trend
is valid.

The range in levels of supplemental mineral nu-
trients supplied to the plants accounted for the lowest
degree of variation in flowering response of the factors
tested. Both levels chosen were within a relatively 0p-
timal range for petunia, consequently if these levels were
extended to more critical levels (e.g. nearing deficiency
and/or excess) a higher variation would undoubtedly be
realized. It would not be advisable to extrapolate linearly
outside the experimental factor space. The variation due
to level of supplemental mineral nutrients was 4 days at

first flower and 5.4 days at fifty percent flower.

 

44

The high degree of correlation between these envi-
ronmental factors and flowering (first and 50%) is no doubt
partially due to several reasons.

One of the factors leading to the relatively high
degree of accuracy of the regression equations has been
the somewhat compound parameter, date of planting. Al-
though with temperature and supplemental nutrients it was :
possible to construct a fairly critical test of their ef-
fects, date of planting undoubtedly entails many individual

factors working collectively. It has been noted that con-

1. FIG “cu-u— v.

siderable change in day length as well as daily solar
radiation totals occurred during the experiment. Partic-
ularly notable is the extreme random variation in the solar
radiation. Because of the potential seasonal variability,
it was felt that this parameter (planting date) shOUld be
broken down into more precise components and tested with a
higher degree of precision.

The use of mean values in the regression program
also eliminated some degree of the inherent variation that
would have otherwise been acquired. Had mean values not
been utilized, the percent correlation would have been
lower. In this study, it is felt that little would be
gained with this procedure.

The non-universality of the present equation also
merits mention. While under identical environmental and

cultural conditions at Michigan State University in

45

following years, the equations will probably yield reason-
able estimates of the number of days to first flower and
fifty percent flowering, few commercial growers have similar
conditions. In fact, as previously stated, there is a
diverse array of growing conditions used in the Southern
part of Michigan alone. Because of this, factors such as
structural cover, altitude, latitude, carbon dioxide

level, etcetera, must be analyzed before an accurate work-

ing equation can be produced.

—‘H—. r7, ~—
E" -I‘-.’ A I; ‘r I '2. n.2,:

SUMMARY

(1) Flowering date can be predicted for Petunia hybrida
Hort., cv. White Cascade using growing temperature, date of fi‘”‘
planting and level of supplemental mineral nutrition under I
given environmental and cultural conditions.

(2) Further analysis should be made of these environ-

 

mental parameters, expanding the present ranges. Specific
attention should be given to planting date. A more complete
breakdown and analysis of contributing factors is suggested.
(3) Coefficients for other environmental factors and
varieties should be formulated to increase the universality

of the equations.

46

LITERATURE CITED

 

10.

11.

LITERATURE CITED

Anderson, M. C. 1964. Light relations of terrestrial
plant communities and their measurement. Biol.

Rev. 39:425. 3""

Anstey, T. H. 1966. Prediction of full bloom date J
from air temperature date. Amer. Soc. Hort. Sci. ?
88:57. ’

Author, J. M., J. D. Guthrie and J. M. Newell. 1930.
Some effects of artificial climates on the growth

and chemical composition of plants. Amer. J. Bot. 5
17:416.

 

 

Ball, G. V. (ed). 1965. Bedding plants - how to grow
'em. Grower Talks. Nov. Issue.

. 1966.. How to grow bedding plants. Grower
TaIEs. Jan. Issue.

Blake, J. and G. P. Harris. 1960. Effects of nitrogen

nutrition on flowering in carnation. Ann. Bot.
24(94):247.

Bonner, J. and J. L. Liverman. 1953. Hormonal control
of flower initiation. p. 283 in W. E. Loomis (ed.),
Growth and Differentiatipn in Plants. Iowa State
University Press. Ames, Iowa.

Bunning, E. 1960. Cold Spring Harbor Symp. Quant.
Biol. 25:249-56.

. 1964. The Physiological Clock. Academic
Press, No Yo'

Candolle, A. de. 1855. Geographic Botanique Raisonnee.
p. 606. Masson, Paris, France.

Carlson, W. H. 1966. Yield predictions of "Better
Times" roses (Rosa h brida) based on plant and soil
analysis. Ph.D. Thes1s, Pennsylvania State Univer-
sity.

47

 

12.

13.

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

48

Craig, R. and D. E. Walker. 1963. The flowering of
Pelargonium hortorum Bailey seedlings as affected
by cumulative solar energy. Amer. Soc. Hort. Sci.
83:772.

 

Doorenbos, J. and S. J. Wellensiek. 1959. Photo-
periodic control of flower induction. Ann. Rev.
Plant Physiol. 10:147.

Garner, W. W. and H. A. Allard. 1920. Effect of the
relative length of day and night and other factors
of the environment on growth and reproduction in
plants. J. Agri. Res. 18(11):553.

Greuach, V. A. 1942. The length of the photoperiodic-
ally effective twilight period. Ohio J. Sci. 42:71.

Hammer, K. 1960. Cold Spring Harbor Symp. Quant.
Biol. 25:269.

-" '- mfaz': 1 My: 9 m
I “‘1
u . _ r I

. 1963. Environmental controlpfplant growth.
p. 215. L. T. Evans (ed.).' Academic Press, New
York.

, and J. Bonner. 1938. Photoperiodism in
relation to hormones as factors in floral initiation
and development. Bot. Gaz. 100:388.

Hinnawy, E. I. 1956. Mededel. Landbouwhogeschool
Wageningen. 56:1.

Hodgson, G. L. 1967. Physiological and ecological
studies in the analysis of plant environment. XIII.
A comparison of the effects of seasonal variations
in light energy and temperature on the growth of
Helianthus annuus and Vicia faba in the vegetative
phase. Ann. Bot. 31(122):291.

 

Hudson, J. P. (ed.). 1957. Control of the Plant
Environment. p. 240. Butterworths Scientific
Publications, London.

 

Kays, S. J. and W. H. Carlson. 1967. Unpublished
data. Department of Horticulture, Michigan State
University.

Kraus, E. J. and Krayhill. 1918. Vegetation and
reproduction with special reference to the tomato.
Oregon Agri. Expt. Sta. Bull. No. 149. As cited in
E. J. Kraus. 1925. Soil nutrients in relation to
vegetation and reproduction. Amer. J. Bot. 12:510.

 

24.

25.

26.

27.

28.

29.

30.

31.

32.

33.

34.

35.

36.

37.

49

Lang, A. and G. Melechers. 1943. Die photoperiodischi
reakton von Hyoscyamus niger. Planta 33:653.

 

Leopold, A. C. 1951. Photoperiod in plants. Quart.
Biol. Rev. 26:247.

. (ed.). 1964. Plant Growth and Development.
p. 266. McGraw-Hill. New York. '

Long, E. M. 1939. PhotOperiodic induction as influenced
by environmental factors. Bot. Gaz. 101:168.

Mastalerz, J. W. 1963. Controlling growth of petunias.
Penn. Fl. Gr. Bull. 145:4.

McCree, K. J. and J. H. Thoughton. 1966. Prediction
of growth rate at different light levels from meas-
ured photosynthesis and respiration rates. Plant
Physiol. 41:559.

Mhor, H. 1964. The control of plant growth and devel-
opment by light. Biol. Rev. 30:87.

Murneek, A. C. 1940. Length of day and temperature
effects in Rudbeckia. Bot. Gaz. 102:269.

Nanda, K. K. and K._C. Hamner. 1959. Planta 53:45.

Naylor, A. W. 1941. Effects of some environmental
factors on photOperiodic induction of beet and
dill. Bot. Gaz. 102:557.

Piringer, A. A. and H. M. Cathey. 1960. Effect of
photoperiod, kind of supplemental light and tem-
perature on the growth and flowering of petunia
plants. Amer. Soc. Hort. Sci. 76:649.

Rafter, M. E. and W. L. Ruble. 1967. Stepwise deletion
of variables from a least square equation.~ STAT
Series Description No. 8. Michigan State University
Computer Laboratory (mimeo).

Roberts, R. H. and B. E. Struckmeyer. 1938. The ef-
fects of temperature and other environmental factors
upon the photoperiodic responses of some of the
higher plants. J. Agri. Res. 56:633.

. 1939. Further studies of the effects of.
temperature and other environmental factors upon
the photoperiodic responses of plants. J. Agri.
Res. 59:699. ‘

T lie—5.7573?“ «J'rngmzfl
I

 

 

38.

39.

40.

41.

42.

43.

44.

45.

46.

47.

48.

49.

50.

51.

50

Ruble, W. L., D. F. Kiel and M. E. Rafter. 1968.
Analysis of variance with equal frequency in each
cell. STAT Series Description No. 14. Michigan
State University Computer Laboratory (mimeo).

Sachs, J. 1860. Physiologische untersuchungen iiber
die abhangigkeit der keimung von der temperatur.
Jahrb., Wiss. Bot. 1:49.

Salisburg, F. B.- 1961. PhotOperiodism and the flow-
ering process. Ann. Rev. Plant Physiol. 12:293.

Schwemmle, B. 1960. Cold Spring Harbor Symp. Quant.
Biol. 25:239.

Searle, N. E. 1965. Physiology of flowering. Ann.
Rev. Plant Physiol., 16:97. (L. Machlis and W. R.
Briggs, eds.7 Ann. Rev., Inc., Palo Alto, Calif-
ornia.

Seeley, J. G. 1955. Petunias for sale 8 weeks after
potting. Penn. Fl. Gr. Bull. 51:1.

. 1965. As cited in Grower Talks, J. G. Ball

(ed.). Nov. Issue.

Spector, W. S. (ed.). 1956. Handbook of Biological
Data. p. 584. W. B. Saunders Co., Philadelphia,
Pa.

 

Takimoto, A. and K. Ikeda. 1959. Studies on-the light

controlling flower initiation of Pharbitis nil, V.
On the light following the inductive dark period.
Bot. Mag. (Tokyo) 73:90.

 

Tayama, H. K. and D. C. Kiplinger. 1966. Tips on
growing bedding plants. Flor. Rev. Dec. 12.

van der Veen, R. and G. Meijer (eds.).- 1959. Light

and Plant Growth. p. 162. MacMillan Co., New York.

Withrow, R. B. (ed.).. 1949. Photoperiodism and Related

Phenomena in Plants and Animals. p. 439. Amer.
Assoc. Advance. Sci}, Washington, D. C.

Wittwer, S. H. and M. J. Bukovac. 1957. Gibberellins:

new chemicals for crop production. Mich. State
Agri. Expt. Sta. Quart. Bull. 39:469.

, and F. G. Teubner. 1957. The effect of tem-
perature and nitrogen nutrition on flower formation

in the tomato. Amer. J. Bot. 44:125.

.1 J-‘Zfi' j
‘II

 

.. _._~1.__

 

APPENDIX

 

51

Appendix Table l.--Number of days from planting to first
and 50% flower for each observation.

 

 

 

 

 

 

 

 

Treatment Number of Days to Number of Days to
First 50% First 50%
T t F Flower Flower Treatment Flower Flower
l 1 1 '52 57 2 l 1 66 70
55 57 67 69
52 57 66 71
54 57 67 69
51 54 67 69
52 54 68 71
l l 2 54 58 2 1 2 69 73
58 67 69 73
65 69 73 75
59 62 69 73
53 58 70 74
54 60 72 73
l 2 l 60 63 2 2 l 75 78
61 63 74 78
62 63 71 73
61 67 71 75
6O 66 75 76
61 63 71 75
1 2 2 66 69 2 2 2 76 85
62 69 82 83
62 67 77 87
66 66 81 86
65 68 77 85

61 68 75 83

 

 

 

N STATE 1v LIBRRRIES

”‘IIIIIIIIIIIIIIIIIIII III IIIIIII

 

312931052842