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Influence of day and night temperature on the growth of young tomato plants
Scientia Horticulturae, 38 ( 1989 ) 11-22 Elsevier Science Publishers B.V., Amsterdam - - Printed in The Netherlands
11
I n f l u e n c e of D a y and N i g h t T e m p e r a t u r e on the G r o w t h of Y o u n g T o m a t o Plants* E. HEUVELINK
Agricultural University, Department of Horticulture, P.O. Box 30, 6700 AA Wageningen (The Netherlands) (Accepted for publication 12 July 1988 )
ABSTRACT Heuvelink, E., 1989. Influence of day and night temperature on the growth of young tomato plants. Scientia Hortic., 38:11-22. Young tomato plants were grown at different day and night temperature combinations with an average of 21°C. Some combinations with a different average 24-h temperature were included. Day temperature (Td) varied between 16 and 26 ° C, night temperature ( Tn ) between 12 and 26 ° C, while the daylength was 12 h. Light intensity was about 26 W m - 2photosynthetic active radiation
(PAR). An inversed temperature regime ( T d lower than Tn) reduced plant growth (fresh weight, FW; dry weight, DW) and development (number of leaves, number of trusses). Reduction in development was less than reduction in growth. Growth reduction was caused by a lowering of the leaf area ratio (LAR). The decrease in LAR at an inversed temperature regime was caused mainly by a decrease in specific leaf area (SLA). Net assimilation rate (NAR) was not influenced by the temperature regime. For young widely spaced plants a lower SLA (thicker leaves) results in less light interception and thus in growth reduction. It is possible now to explain the different reactions on temperature regime at the same temperature integral between young plants and closed canopies. In a closed canopy (a producing crop ) differences in leaf area index, brought about by differences in leaf thickness, have hardly any influence on light interception because most light has been already intercepted anyway. This explains why a producing crop, in contrast to young plants, shows hardly any reaction to temperature regime at the same temperature integral. A regression analysis indicated that for FW and DW, plant length, leaf area (A), number of leaves, number of trusses, relative growth rate (RGR), LAR and SLA, Td is more important than
Tn. Keywords: growth analysis; leaf area ratio; specific leaf area; temperature; tomato; young plants. Abbreviations:A = total plant leaf area (cm 2); DW = total dry weight of the plant (g); DW, = total dry weight of the leaves (g); EC = electrical conductivity (mS); FW = total fresh weight of the plant (g); F PR = F probability; probability of obtaining an F statistic at least as large as the present one when all treatment means are equal; LAR = leaf area ratio (A/DW) (cm 2 rag-'); *Publication no. 529, Department of Horticulture, Wageningen, The Netherlands.
0304-4238/89/$03.50
© 1989 Elsevier Science Publishers B.V.
12 L W R = l e a f weight ratio (DW1/DW); N A R = n e t assimilation rate (mg c m - 2 d a y - l ) ; PAR=photosynthetic active radiation (400-700 nm) (W m - 2 ) ; r=correlation coefficient; R 2_- squared multiple correlation coefficient times 100 ( % ); RGR = relative growth rate ( day - 1); S E = s t a n d a r d error; SLA=specific leaf area (A/DW~) (cm2mg-~); t = t i m e ( d a y - l ) ; Td----temperature during light period ( ° C ); Td ----Td-- 21 ( ° C ); Tn -- temperature during dark period (°C); ~'. = T n - 2 1 (°C).
INTRODUCTION
The recent introduction of computer-based control systems for greenhouse climate makes it possible to work with temperature regimes which were either impossible or impracticable with earlier control systems (Cockshull, 1986). Setpoints for temperature can be adjusted continuously in order to obtain the best economic output. This approach is particularly interesting with the introduction of new developments in greenhouse technology like highly effective thermal screens and use of waste and reject heat for greenhouse heating, which require new control strategies (Challa and Brouwer, 1985). For example, traditionally most greenhouse crops are cultivated at a day temperature (Td) somewhat higher than the night temperature (Tn). However, especially when thermal screens are used in winter, it can be profitable to use an inversed temperature regime (Td < Tn; Leatherland, 1986). Adjustment of temperature setpoint for wind speed (lower temperatures at high wind speed and vice versa) led to improvements in fuel economy (Hurd and Graves, 1984). Langhans et al. ( 1981 ) showed for lettuce the efficacy of sliding or averaging night temperatures as a method of energy saving in greenhouses. Td and Tn requirements of the tomato were first investigated by Went (1944), who found that maximal growth (stem elongation) occured when the temperature during the dark period was lower than during the diurnal light period. He introduced the term "thermoperiodicity" for sensitivity to diurnal temperature pattern. It includes all effects of a temperature differential between light and dark periods on responses of the plant. Young plants appear to have this thermoperiodicity in contrast to producing crops (closed canopies). Calvert (1964), Hussey (1965) and Klapwijk and Wubben (1978) reported a reduced growth of young plants at an inversed temperature regime. Hurd and Graves (1984) and De Koning (1986), however, reported that total tomato yield was not influenced by the temperature regime, but mainly by the temperature integral. The same was found for the yield of sweet pepper (Hand and Hannah, 1978) and cucumber (Slack and Hand, 1983 ). The aim of the present research was to find an explanation for the growth reduction of young plants at an inversed temperature regime. This might also provide an explanation for the difference in thermoperiodicity between young plants and closed canopies.
13 MATERIALS AND METHODS
Experimental design. - Tomato seeds (Lycopersicon lycopersicum (L.) Farw. 'Counter') were sown in a greenhouse in seed trays. Ten to 12 days after sowing, seedlings were transplanted in expanded clay grit (Leca) in 11-cm plastic pots, after removing all soil from the roots. In Experiment 1 expanded clay in the diameter range 12-16 mm was used; in Experiments 2 and 3, 6-8 mm. The plots were placed on benches in the greenhouse in a 2-cm water layer, where the seedlings were allowed to acclimate to the new root medium for 3 days. At the start of an experiment plants were placed in growth cabinets (Controlled Environments Ltd., Winnipeg, Manitoba, Canada; length × weight × height = 185 × 77 × 137 cm) in a 2-cm nutrient solution of Nutriflora-T (Windmill Holland BV; contains all major and minor nutrients except Ca; 1.25 g l- 1) and Ca (NO~) 2 (1.50 g l - 1). By adding water and nutrient solution when necessary, EC was kept at approximately 3 mS. pH was 6-7 and in each experiment the nutrient solution was refreshed after 3 weeks. In the growth cabinets relative humidity was maintained at 60-80% and plants were grown at approximately 300/d l-1 COe concentration. Nine treatments, partly in duplicate, were given. Treatments were different combinations of Td and Tn at a daylength of 12 h. Plants were lighted by Philips TLD-hf 50-W fluorescent tubes {colour 84) at a light intensity of 26 W m -2 PAR. Three experiments were conducted in the period November 1986-April 1987 (Table 1). In 6 of the 9 treatments the average 24-h temperature was 21 ° C. In each experiment a treatment consisted of 48 plants. Leaf area (LI-COR Model 3100 Area Meter), leaf, stem and root fresh and dry weight (60°C; forced air oven for at least 5 days ), plant length, number of leaves ( > 5 mm) and number of trusses (below the last leaf > 5 mm) were determined by six weekly destructive measurements on 8 plants t r e a t m e n t - 1. Growth analysis. - A growth analysis was conducted according to the functional approach (Hunt, 1982 ). The best fitting polynome (up to the sixth degree ) for TABLE 1 Treatments and growth period for each experiment Experiment
Treatments (TjTn, ° C )
Sowing date
Transplanted
Start of End of experiment experiment
Growing period (days)
1 2 3
18/24,22/20,26/16,18/18,24/24 As Expt. 1 24/18,20/22,16/26,24/12
24 Oct. 23 Dec. 6Feb.
5 Nov. 6 Jan. 19Feb.
7 Nov. 9 Jan. 23 Feb.
41 41 40
17 Dec. 18 Feb. 3 Apr.
14
the relation between natural logarithms of DW, DWi and A with time was calculated (Nilwik, 1981a). The degree of the polynomials was chosen by using the ordinary “least squares estimate” (Draper and Smith, 1966). With this method polynomials of degree 2 were found to be sufficient for A in all 14 cases (5 treatments in duplicate and 4 single treatments). In the other 28 cases (DW, DW, ) except 6, also polynomials of degree 2 were necessary and sufficient, the exceptional cases being degree 1. This is in agreement with Hurd (1977)) who also found for young plants that curves for the natural logarithms of both leaf expansion and dry-weight gain could be described by a quadratic polynomial relation and who concluded that, taking biological expectation into account, the quadratic relation provides the most satisfactory fit to the data. In the present study, a quadratic relationship was fitted to all the plots of the natural logarithms of A, DW and DW, against time. Thus for DW as a function of time the following relation was assumed: lnDW=a+b*t+c*t’
(c#O)
(I)
According to Equation ( 1) RGR is described by: RGR=b+2*c*t
(cz0)
(2)
In Eqn. (1) parameter a represents the logarithm of the dry weight at t=O, parameter b represents RGR at t=O and parameter c reflects the degree of curvature in progressions of 1nDW. If c equals zero equation (1) is the simple exponential relationship. When b is positive and c is negative, growth is concave to the abcissa (Hunt, 1982). This was always the case in our experiments, and means that an increasing proportion of the plant material stops growing (Hurd, 1977). Because growth rate is size dependent (ontogenetic effect), it is necessary to take this into account. Terry (1968) used DW as an index of ontogenetic state. This approach has also been employed here. Therefore average values for the growth parameters RGR, NAR, LAR, SLA and LWR were compared on the basis of a DW interval instead of a time interval. The DW interval is 20.1-2981 mg (1nDW = 3-8)) because this is about the largest possible interval in these experiments not requiring extrapolation of data. This means that at the beginning of each experiment DW was less than 20 mg and at the end of each experiment all treatments had reached at least a DW of 3000 mg. Instantaneous values were calculated by means of the polynome described in Equation ( 1) and similar polynomes for the plots of the natural logarithms of DW1 and A against time. Average RGR, NAR, LAR, SLA and LWR values were calculated by taking the mean of daily instantaneous values over the DW interval. Results were statistically analysed by analysis of variance. An attempt to give results in simple regression formula was made. With the statistical package GENSTAT the best model was calculated out of 5 independent regressors,
15 i.e. Td, Tn, Td* Tn, T~ a n d T~, b y b a c k w a r d e l i m i n a t i o n , w h i c h is o f t e n a very good variable selection p r o c e d u r e ( M o n t g o m e r y a n d Peck, 1982, pp. 2 7 3 - 2 7 5 ). R e g r e s s o r s were r e m o v e d f r o m t h e m o d e l u n t i l t h e a b s o l u t e value o f t h e t statistic for e a c h p a r a m e t e r was m o r e t h a n 2. F u r t h e r m o r e a linear regressor (e.g. T~) was n o t r e m o v e d f r o m t h e m o d e l if t h e q u a d r a t i c regressor (in this e x a m p l e T~ ) was s i g n i f i c a n t in t h e model. So, in a way, we a d o p t e d t h e v i e w p o i n t t h a t it is t h e o r d e r o f t h e m o d e l t h a t is i m p o r t a n t , n o t t h e individual t e r m s (L.C.A. C o r s t e n , p e r s o n a l c o m m u n i c a t i o n , 1987). RESULTS AND DISCUSSION
Parameters. - F W , D W , p l a n t length, A a n d n u m b e r of leaves were signific a n t l y i n f l u e n c e d b y t h e t e m p e r a t u r e regime ( T a b l e 2), w h e r e a s n u m b e r of t r u s s e s was not. T h e l a t t e r was p r o b a b l y due to t h e small n u m b e r of t r u s s e s anyway. F W was equal at c o n s t a n t t e m p e r a t u r e ( 2 0 / 2 2 °C a n d 2 2 / 2 0 ° C ) a n d u n d e r c o n d i t i o n s w i t h a h i g h e r To ( 2 6 / 1 6 ° C a n d 2 4 / 1 8 ° C ) , b u t t h e s a m e average t e m p e r a t u r e ( T a b l e 2). D W shows identical b e h a v i o u r . F r i e n d a n d H e l s o n (1976) r e p o r t e d t h e s a m e for g r o w t h o f y o u n g t o m a t o plants. G r o w t h u n d e r a n i n v e r s e d t e m p e r a t u r e regime ( 1 8 / 2 4 ° C a n d 1 6 / 2 6 ° C ) was r e d u c e d c o m p a r e d to a c o n s t a n t regime a t t h e s a m e t e m p e r a t u r e integral. T h i s negative effect of i n v e r s e d t e m p e r a t u r e regimes o n g r o w t h o f y o u n g t o m a t o p l a n t s has also b e e n TABLE 2 Effects of temperature regime1 (treatment) on FW, DW, plant length, A, number of leaves ( > 5 mm) and number of trusses at the end of the experiments Treatment (Td/Tn, °C)
Average n temp. (°C)
FW (g)
DW (g)
26/16 24/18 22/20 20/22 18/24 16/26 18/18 24/24 24/12
21 21 21 21 21 21 18 24 18
61a~d 95ab 61~¢d 102~b 48Cd 40Cd 26d 92b 73~b¢
6.5abed 8.9~ 6.2~bcd 9.4ab 4.8bed 3.8ed 2.8d 9.2a 7.2~bcd
F PR
2 1 2 1 2 1 2 2 1
0.004
0.006
Plant length (cm)
A (cm2)
52ab 1190a 50abe 1932cd 34co 1292ac 35bCde 21100 28de 925~b 23de 802~b 18~ 552b 54~ 1867ca 39abed 1421~¢d < 0.001
No. of leaves No. of trusses 16.6~d 17.70 16.2acd 16.9d 15.2abe 14.1~ 13.3b 17.9d 16.0acd
0.001
1Mean separation by Tukey's HSD test (P < 0.05), only when F PR < 0.01. n = No. of replicates; F PR = F probability.
0.002
3.6 4.0 3.2 3.9 3.0 2.9 2.4 3.8 3.7 0.110
16 reported by Calvert (1964), Hussey (1965), Klapwijk and Wubben (1978) and Went (1944). Also Friend and Helson (1976), who investigated growth of 7 crops, concluded that a high Td and lower Tn resulted in greater growth than a low Td and higher Tn for the same daily mean temperature. For A, influence of temperature regime at the same temperature integral was the same as for FW and DW. However, plant length was always reduced when Td decreased at the same temperature integral (Table 2). This was also reported for cucumber and sweet pepper (Klapwijk and Wubben, 1978), soybean (Thomas and Raper, 1978) and tomato (Verkerk, 1955; Calvert, 1964; Morgan and Clarke, 1975; Klapwijk and Wubben, 1978). Plant development (number of leaves, number of trusses) was similar at constant temperature and under conditions with a higher Td at the same integral. At an inversed temperature regime development was slowed. This reduction was much less than the reduction in weight. At 16/26 ° C, compared to 26/16 ° C, DW was reduced by 42 %, whereas the number of leaves was reduced by only 15% (Table 2). When the influences of temperature regime on number of leaves and plant length are compared, differences obtained in plant length were rather a result of differences in internode elongation than in number of nodes produced (Table 2). Thomas and Raper (1978) report the same for soybean. Klapwijk and Wubben (1978), using young tomato, cucumber, sweet pepper and chrysanthemum plants, concluded that an inversed temperature regime (17/23 °C) reduced plant length more than FW. The same was found in the present study when 26/16°C and 16/26°C were compared. For young tomato plants the inversed temperature regime led to a 34% reduction in FW, while length was reduced by 56%. However, for 24/18°C and 18/24°C decrease in FW ( - 4 9 % ) was about the same as decrease in length ( - 4 4 % ). a n a l y s i s . - In order to explain the decrease in growth and development at an inversed temperature regime a growth analysis was conducted (Table 3). RGR can be separated into an assimilatory component (NAR) and a morphological component (LAR). From the given F PR in Table 3 (bottom line ) a preliminary conclusion might be that changes in RGR due to temperature regime are mainly caused by changes in LAR and not by changes in NAR. This is in good agreement with Nilwik (1981b), who reported for sweet pepper that the influence of temperature on RGR was largely mediated through changes in LAR. Also Challa and Brouwer (1985) concluded for young cucumber plants that the influence of different Tn regimes is mainly through LAR. In general, no large temperature effects on NAR are reported (Warren Wilson, 1966; Terry, 1968). This also agrees with Gaastra's (1959) finding that net photosynthesis of tomato leaves at 0.03% CO2 is hardly influenced by the temperature (12.520.5 ° C). As respiration rates are rather small compared to photosynthetic rates at our conditions, they do not contribute much to the measured NAR. HowGrowth
]7 TABLE3 Effects of t e m p e r a t u r e regime ~ on m e a n values of RGR, NAR, LAR, SLA a n d L W R over t h e D W interval 20.1-2981 mg Treatment (Td/Tn, °C)
Average temp.
n
26/16 24/18 22/20 20/22 18/24 16/26 18/18 24/24 24/12
21 21 21 21 21 21 18 24 18
2 1 2 1 2 1 2 2 1
FPR
RGR (day -1) 0.168 ab 0.177 ~ 0.169 ab 0.178 b~ 0.158 ~c 0.146 cd 0.136 d 0.184 e 0.164 abe <0.001
NAR ( m g c m - 2 d a y -1)
LAR (cm2mg -1)
SLA ( c m 2 m g -1)
LWR
0.528 0.542 0.509 0.508 0.541 0.483 0.526 0.517 0.558
0.319 0.326 0.335 0.350 0.296 0.304 0.249 0.356 0.294
0.489 0.492 0.491 0.513 0.426 0.447 0.356 0.524 0.462
0.657 0.663 0.690 0.685 0.697 0.683 0.673 0.686 0.638
0.915
0.122
0.342
0.773
1Mean separation by Tukey's H S D test ( P < 0.05 ), only w h e n F P R < 0.01 ). n = No. of replicates; F P R = F probability.
ever, Friend and Helson (1976) concluded for wheat that the high rate of growth obtained under a temperature regime of high Td was the result of a high rate of net photosynthesis. This conclusion was based on their finding that LAR, SLA and LWR were not influenced by the temperature regime at the same temperature integral and on the positive correlation between respiration rate and night temperature. On the other hand, one can argue that a lower Td will reduce respiration during the day, just as a lower Tn lowered respiration during the night. As a matter of fact, this can be concluded from the results presented by Friend and Helson (1976) themselves. At 30°C mean temperature, C02 uptake during the day minus CO2 release during the night was the same for 25/35°C and 35/25°C. Plant weight and leaf area did not differ, so any ontogenetic effects were unlikely. At a mean temperature of 20 ° C, CO2 uptake during the day minus CO2 release during the night was 20% higher at 15/25 °C than at 25/15°C, whereas DW and A were about 30% lower. According to Friend and Helson (1976) net gain in CO2 and NAR are highly correlated. Thus these authors found LAR, SLA and LWR to be independent of temperature regime at the same temperature integral, but their conclusion that increased growth at higher Td at the same integral is caused by higher NAR is not supported by their own results. LAR can be considered as the result of SLA times LWR. Table 3 (bottom line ) shows that changes in LAR were mainly caused by changes in SLA, and thus by differences in leaf thickness (1/SLA). Also Harssema (1977) concluded that for young tomato plants LWR was insensitive to temperature. In this respect it is also interesting to note that Nilwik (1981b) reported for sweet
18 pepper that L A R was highly correlated with the specific leaf weight ( 1 / S L A ) . H u n t (1982) concluded that of SLA and LWR, the former is in general more sensitive to environmental change. Warren Wilson (1966) reported for rape, maize and sunflower that temperature effects on growth were mainly through L A R (not N A R ) and SLA (not L W R ) . This is exactly what we can conclude for the effect of different temperature regimes at the same temperature integral (Table 3 ). Correlations. - To obtain a general picture of the treatment effects on the different growth parameters pairwise correlation coefficients can be calculated (Eagles, 1967; Wilson and Cooper, 1969; Nilwik, 1981b). For all 9 treatments together, correlation coefficients (Table 4) were positive and significant between R G R and LAR, between R G R and SLA and between L A R and SLA. The negative and significant correlation coefficient between N A R and L W R was unexpected. For the 6 treatments at the same temperature integral (21 ° C ) correlation coefficients (Table 4) were positive and significant between R G R and LAR, and between R G R and SLA. There was a highly positive correlation between L A R and SLA. It is clear that differences in R G R under different temperature regimes (at the same integral) are almost completely related to differences in leaf thickness ( 1 / S L A ) . It is now concluded that growth reduction at an inversed temperature regime in comparison with a traditional or constant temperature regime was due to the development of thicker leaves (SLA was lower ) at an inversed temperature regime. Thicker leaves led to less light interception per unit leaf weight and thus to growth and development reduction. For a producing crop (closed can-
TABLE4 Correlations between growth parameters of young tomato plants. The correlation matrix is given for all treatments (n=9) and for those treatments with an average 24-h temperature of 21°C
(n=6) RGR
NAR
All treatments (n = 9 ) NAR 0.141 LAR 0.901"** - 0.280 SLA 0.933*** - 0.133 LWR - 0.005 - 0.584* Treatments with mean temperature of 21 °C (n = 6) NAR 0.469 LAR 0.810" - 0.131 SLA 0.838* - 0.034 LWR -0.354 -0.273 *P
LAR
SLA
0.966*** 0.261
0.946*** -0.145
0.012
- -
0.455
19
opy) leaf thickness barely influences light interception (all the light is already intercepted) and this explains why young plants, in contrast to producing crops, show a strong thermoperiodicity. The results can be presented in the form of regression formulae (Table 5). These formulae are centered round 21°C. R 2 is quite low for some relationships (Table 5). This means that a lot of variation in the plant parameters is not explained by Td and Tn. Most extreme, this is demonstrated for NAR, which was not influenced by Td and Tn in the present experiments. Table 5 shows that for RGR there is an interaction between Td and Tn. This makes general evaluations of simple effects of day and night temperatures difficult for this parameter. It should be kept in mind that Table 5 shows the results of a regression analysis. This means that extrapolation outside the temperature range used in our experiments is not valid. For example, if we were to calculate plant length for a treatment with Td= 12°C and T n = 12°C, it would be negative. Furthermore, these regression formulae are based on only 9 Td and T~ combinations and not a complete set of temperatures. Therefore, their validity is restricted. Some of the formulae in Table 5 are displayed graphically in Fig. 1. Table 5 and Fig. 1 show that the influence of Td on plant growth and development is larger than the influence of Tn (between 18 and 24°C ), which is in accordance with results obtained by Calvert (1964). Hussey (1965) reported that for 9day-old tomato plants Td was about twice as important as Tn for RGR. Leaf growth rate and stem growth of young tomato plants were, according to Hars-
Regressions. -
TABLE 5 "Best models" selected by a backward elimination procedure. Independent regressors used are T,, T,. Regressors were removed from the model until the absolute value of the t statistic for each parameter was more than 2 Selected model FW (g) DW (g) Plantlength (cm) A (dm 2) Numberofleaves Number of trusses RGR NAR LAR SLA LWR
= = = = --
= = = = = =
63.0 +6.44 Td+3.08 T~ 6.26+0.647Td+0.287T~ 36.3 +4.48 Td+l.37 Tn 15.4 +1.37 Td+0.615Tn-0.246 T~ 16.4 +0.513Td+0.221Tn-0.0442T~ 3.26+0.117Td
0.172+0.00511Td +0.00283Tn +0.000405TdTn-0.00101T~ 0.524 0.315+0.00998Td+0.00694Tn 0.464+0.0167 Td+0.00891T~ 0.680+0.00373Tn
R2
SE
54 62 94 67 88 47
18.9 1.59 3.50 3.37 0.623 0.432
95 0 65 55 36
0.00433 0.00844 0.0245 0.0477 0.0208
20
55
0.55
A
13
jr"
0.50
(.5
8' 0.45
25
15
J.;..S(." I
I
I
16
18
~
0.40 /
~
I 2(. T d (°C)
C
--
0.35
.S
r"
i
i
16
10
20
0.10
6
~" o,~6
~.
0,14
/
0.12
/
/ p
s
I 10
~
2~ T d (°C)
Tn
/
- - - - 21% -- - - l r C
/
I 16
i
22
0.20
0
I".~,
I
I 20
I 22
I 24 T d I'C )
0.10
d I
I
I
I
16
10
29
22
I
24 Td ('PC)
Fig. 1. Plant length (A), SLA (B), DW (C) and RGR (D) for young tomato plants as influenced by Td and T., according to the regression formulae of Table 5.
sema (1977), largely influenced by Td, while the effect of Tn was much smaller. Friend and Helson (1976) concluded for 7 crops that at suboptimal diurnal temperatures Td was more important for DW increases than Tn. From the experiments of T h o m a s and Raper (1978) with soybean it could be concluded, although a significant interaction between Td and Tn occurred, that Td was more important for main stem length than T., even at a day length of 9 h. However, Haroon et al. (1972) found for tobacco that growth of seedlings from first leaf to transplant size was affected to a larger extent by Tn than by Td. This can probably be explained by the day length of only 9 h in their experiment, making in advance T. almost twice as important as Td. ACKNOWLEDGEMENTS
The author wishes to thank Prof. L.C.A. Corsten for his statistical advice. He is much indebted to Miss R.P.M. Buiskool, who did most of the measurements, and to De Ruiter Seeds, Bleiswijk, The Netherlands, for supplying the tomato seeds.
21 REFERENCES
Calvert, A., 1964. The effects of air temperature on growth of young tomato plants in natural light conditions. J. Hortic. Sci., 39:194-211. Challa, H. and Brouwer, P., 1985. Growth of young cucumber plants under different diurnal temperature patterns. Acta Hortic., 174: 211-217. Cockshull, K.E., 1985. Greenhouse climate and crop response. Acta Hortic., 174: 285-292. Draper, N.R. and Smith, H., 1966. Applied Regression Analysis. Wiley, New York, pp. 264-267. Eagles, C.F., 1967. The effect of temperature on vegetative growth in climatic races of Dactylis glomerata in controlled environments. Ann. Bot., 31: 31-39. Friend, D.H.C. and Helson, V.A., 1976. Thermoperiodic effects on the growth and photosynthesis of wheat and other crop plants. Bot. Gaz., 137" 75-84. Gaastra, P., 1959. Photosynthesis of crop plants as influenced by light, carbon dioxide, temperature, and stomatal diffusion resistance. Meded. Landbouw Hogesch. Wageningen, 59: 1-68. Hand, D.W. and Hannah, M.A., 1978. Sweet pepper: application of lower-than-normal temperatures for varying durations within the night periods. Annu. Rep. Glasshouse Crops Res. Inst., Littlehampton, 1977: 53-55. Haroon, M., Long, R.C. and Weybrew, J.A., 1972. Effect of day/night temperature on factors associated with growth .of Nicotiana tabacum L. in controlled environments. Agron. J., 64: 509-515. Harssema, H., 1977. Root temperature and growth of young tomato plants. Meded. Landbouw Hogesch, Wageningen, 77: 1-86. Hunt, R., 1982. Plant Growth Curves. The Functional Approach to Plant Growth Analysis. Edward Arnold, London, 248 pp. Hurd, R.G., 1977. Vegetative plant growth analysis in controlled environments. Ann. Bot., 41: 779-787. Hurd, R.G. and Graves, C.J., 1984. The influence of different temperature patterns having the same integral on the earliness and yield of tomatoes. Acta Hortic., 148: 547-554. Hussey, G., 1965. Growth and development in the young tomato. III The effect of night and day temperatures on vegetative growth. J. Exp. Bot., 16: 373-385. Klapwijk, D. and Wubben, C.F.M., 1978. Effect of various temperatures regimes at a same temperature sum on plant growth. Annual Report 1977, Glasshouse Crops Research and Experiment Station, Naaldwijk, pp. 27-28. De Koning, A.N.M., 1986. Temperature experiments with tomato: Influence of temperature regime on growth, development and production. Groenten en Fruit, 41:30-34 {in Dutch). Langhans, R.W., Wolf, M. and Albright, L.D., 1981. Use of average night temperatures for plant growth for potential energy savings. Acta Hortic., 115: 31-37. Leatherland, M., 1986. Dotting the i's in the Efford regime. Grower Suppl., 105 (4): 83-87. Montgomery, D.C. and Peck, E.A., 1982. Introduction to Linear Regression Analysis. Wiley, New York, 504 pp. Morgan, J.V. and Clarke, E.J., 1975. Influence of temperature, photoperiod and container size on the growth rate and development of tomato plants in growing rooms. Acta Hortic., 51: 77-87. Nilwik, H.J.M., 1981a. Growth analysis of sweet pepper (Capsicum a n n u u m L. ). 1. The influence of irradiance and temperature under glasshouse conditions in winter. Ann. Bot., 48: 129-136. Nilwik, H.J.M., 1981b. Growth analysis of sweet pepper (Capsicum a n n u u m L.). 2. Interacting effects of irradiance, temperature and plant age in controlled conditions. Ann. Bot., 48: 137145. Slack, G. and Hand, D.W., 1983. The effect of day and night temperatures on the growth, development and yield of glasshouse cucumbers. J. Hortic. Sci., 58: 567-573.
22 Terry, N., 1968. Developmental physiology of sugar beet. I. The influence of light and temperature on growth. J. Exp. Bot., 19: 795-811. Thomas, J.F. and Raper, C.D., 1978. Effect of day and night temperatures during floral induction on morphology of soybeans. Agron. J., 70: 893-898. Verkerk, K., 1955. Temperature, light and the tomato. Meded. Landbouw Hogesch. Wageningen, 44: 175-224. Warren Wilson, J., 1966. Effect of temperature on net assimilation rate. Ann. Bot., 30: 753-761. Went, F.W., 1944. Plant growth under controlled conditions. II. Thermoperiodicity in growth and fruiting of the tomato. Am. J. Bot., 31: 135-150. Wilson, D. and Cooper, J.P., 1969. Assimilation rate and growth of Lolium populations in the glasshouse in contrasting light intensities. Ann. Bot., 33: 951-965.
11
I n f l u e n c e of D a y and N i g h t T e m p e r a t u r e on the G r o w t h of Y o u n g T o m a t o Plants* E. HEUVELINK
Agricultural University, Department of Horticulture, P.O. Box 30, 6700 AA Wageningen (The Netherlands) (Accepted for publication 12 July 1988 )
ABSTRACT Heuvelink, E., 1989. Influence of day and night temperature on the growth of young tomato plants. Scientia Hortic., 38:11-22. Young tomato plants were grown at different day and night temperature combinations with an average of 21°C. Some combinations with a different average 24-h temperature were included. Day temperature (Td) varied between 16 and 26 ° C, night temperature ( Tn ) between 12 and 26 ° C, while the daylength was 12 h. Light intensity was about 26 W m - 2photosynthetic active radiation
(PAR). An inversed temperature regime ( T d lower than Tn) reduced plant growth (fresh weight, FW; dry weight, DW) and development (number of leaves, number of trusses). Reduction in development was less than reduction in growth. Growth reduction was caused by a lowering of the leaf area ratio (LAR). The decrease in LAR at an inversed temperature regime was caused mainly by a decrease in specific leaf area (SLA). Net assimilation rate (NAR) was not influenced by the temperature regime. For young widely spaced plants a lower SLA (thicker leaves) results in less light interception and thus in growth reduction. It is possible now to explain the different reactions on temperature regime at the same temperature integral between young plants and closed canopies. In a closed canopy (a producing crop ) differences in leaf area index, brought about by differences in leaf thickness, have hardly any influence on light interception because most light has been already intercepted anyway. This explains why a producing crop, in contrast to young plants, shows hardly any reaction to temperature regime at the same temperature integral. A regression analysis indicated that for FW and DW, plant length, leaf area (A), number of leaves, number of trusses, relative growth rate (RGR), LAR and SLA, Td is more important than
Tn. Keywords: growth analysis; leaf area ratio; specific leaf area; temperature; tomato; young plants. Abbreviations:A = total plant leaf area (cm 2); DW = total dry weight of the plant (g); DW, = total dry weight of the leaves (g); EC = electrical conductivity (mS); FW = total fresh weight of the plant (g); F PR = F probability; probability of obtaining an F statistic at least as large as the present one when all treatment means are equal; LAR = leaf area ratio (A/DW) (cm 2 rag-'); *Publication no. 529, Department of Horticulture, Wageningen, The Netherlands.
0304-4238/89/$03.50
© 1989 Elsevier Science Publishers B.V.
12 L W R = l e a f weight ratio (DW1/DW); N A R = n e t assimilation rate (mg c m - 2 d a y - l ) ; PAR=photosynthetic active radiation (400-700 nm) (W m - 2 ) ; r=correlation coefficient; R 2_- squared multiple correlation coefficient times 100 ( % ); RGR = relative growth rate ( day - 1); S E = s t a n d a r d error; SLA=specific leaf area (A/DW~) (cm2mg-~); t = t i m e ( d a y - l ) ; Td----temperature during light period ( ° C ); Td ----Td-- 21 ( ° C ); Tn -- temperature during dark period (°C); ~'. = T n - 2 1 (°C).
INTRODUCTION
The recent introduction of computer-based control systems for greenhouse climate makes it possible to work with temperature regimes which were either impossible or impracticable with earlier control systems (Cockshull, 1986). Setpoints for temperature can be adjusted continuously in order to obtain the best economic output. This approach is particularly interesting with the introduction of new developments in greenhouse technology like highly effective thermal screens and use of waste and reject heat for greenhouse heating, which require new control strategies (Challa and Brouwer, 1985). For example, traditionally most greenhouse crops are cultivated at a day temperature (Td) somewhat higher than the night temperature (Tn). However, especially when thermal screens are used in winter, it can be profitable to use an inversed temperature regime (Td < Tn; Leatherland, 1986). Adjustment of temperature setpoint for wind speed (lower temperatures at high wind speed and vice versa) led to improvements in fuel economy (Hurd and Graves, 1984). Langhans et al. ( 1981 ) showed for lettuce the efficacy of sliding or averaging night temperatures as a method of energy saving in greenhouses. Td and Tn requirements of the tomato were first investigated by Went (1944), who found that maximal growth (stem elongation) occured when the temperature during the dark period was lower than during the diurnal light period. He introduced the term "thermoperiodicity" for sensitivity to diurnal temperature pattern. It includes all effects of a temperature differential between light and dark periods on responses of the plant. Young plants appear to have this thermoperiodicity in contrast to producing crops (closed canopies). Calvert (1964), Hussey (1965) and Klapwijk and Wubben (1978) reported a reduced growth of young plants at an inversed temperature regime. Hurd and Graves (1984) and De Koning (1986), however, reported that total tomato yield was not influenced by the temperature regime, but mainly by the temperature integral. The same was found for the yield of sweet pepper (Hand and Hannah, 1978) and cucumber (Slack and Hand, 1983 ). The aim of the present research was to find an explanation for the growth reduction of young plants at an inversed temperature regime. This might also provide an explanation for the difference in thermoperiodicity between young plants and closed canopies.
13 MATERIALS AND METHODS
Experimental design. - Tomato seeds (Lycopersicon lycopersicum (L.) Farw. 'Counter') were sown in a greenhouse in seed trays. Ten to 12 days after sowing, seedlings were transplanted in expanded clay grit (Leca) in 11-cm plastic pots, after removing all soil from the roots. In Experiment 1 expanded clay in the diameter range 12-16 mm was used; in Experiments 2 and 3, 6-8 mm. The plots were placed on benches in the greenhouse in a 2-cm water layer, where the seedlings were allowed to acclimate to the new root medium for 3 days. At the start of an experiment plants were placed in growth cabinets (Controlled Environments Ltd., Winnipeg, Manitoba, Canada; length × weight × height = 185 × 77 × 137 cm) in a 2-cm nutrient solution of Nutriflora-T (Windmill Holland BV; contains all major and minor nutrients except Ca; 1.25 g l- 1) and Ca (NO~) 2 (1.50 g l - 1). By adding water and nutrient solution when necessary, EC was kept at approximately 3 mS. pH was 6-7 and in each experiment the nutrient solution was refreshed after 3 weeks. In the growth cabinets relative humidity was maintained at 60-80% and plants were grown at approximately 300/d l-1 COe concentration. Nine treatments, partly in duplicate, were given. Treatments were different combinations of Td and Tn at a daylength of 12 h. Plants were lighted by Philips TLD-hf 50-W fluorescent tubes {colour 84) at a light intensity of 26 W m -2 PAR. Three experiments were conducted in the period November 1986-April 1987 (Table 1). In 6 of the 9 treatments the average 24-h temperature was 21 ° C. In each experiment a treatment consisted of 48 plants. Leaf area (LI-COR Model 3100 Area Meter), leaf, stem and root fresh and dry weight (60°C; forced air oven for at least 5 days ), plant length, number of leaves ( > 5 mm) and number of trusses (below the last leaf > 5 mm) were determined by six weekly destructive measurements on 8 plants t r e a t m e n t - 1. Growth analysis. - A growth analysis was conducted according to the functional approach (Hunt, 1982 ). The best fitting polynome (up to the sixth degree ) for TABLE 1 Treatments and growth period for each experiment Experiment
Treatments (TjTn, ° C )
Sowing date
Transplanted
Start of End of experiment experiment
Growing period (days)
1 2 3
18/24,22/20,26/16,18/18,24/24 As Expt. 1 24/18,20/22,16/26,24/12
24 Oct. 23 Dec. 6Feb.
5 Nov. 6 Jan. 19Feb.
7 Nov. 9 Jan. 23 Feb.
41 41 40
17 Dec. 18 Feb. 3 Apr.
14
the relation between natural logarithms of DW, DWi and A with time was calculated (Nilwik, 1981a). The degree of the polynomials was chosen by using the ordinary “least squares estimate” (Draper and Smith, 1966). With this method polynomials of degree 2 were found to be sufficient for A in all 14 cases (5 treatments in duplicate and 4 single treatments). In the other 28 cases (DW, DW, ) except 6, also polynomials of degree 2 were necessary and sufficient, the exceptional cases being degree 1. This is in agreement with Hurd (1977)) who also found for young plants that curves for the natural logarithms of both leaf expansion and dry-weight gain could be described by a quadratic polynomial relation and who concluded that, taking biological expectation into account, the quadratic relation provides the most satisfactory fit to the data. In the present study, a quadratic relationship was fitted to all the plots of the natural logarithms of A, DW and DW, against time. Thus for DW as a function of time the following relation was assumed: lnDW=a+b*t+c*t’
(c#O)
(I)
According to Equation ( 1) RGR is described by: RGR=b+2*c*t
(cz0)
(2)
In Eqn. (1) parameter a represents the logarithm of the dry weight at t=O, parameter b represents RGR at t=O and parameter c reflects the degree of curvature in progressions of 1nDW. If c equals zero equation (1) is the simple exponential relationship. When b is positive and c is negative, growth is concave to the abcissa (Hunt, 1982). This was always the case in our experiments, and means that an increasing proportion of the plant material stops growing (Hurd, 1977). Because growth rate is size dependent (ontogenetic effect), it is necessary to take this into account. Terry (1968) used DW as an index of ontogenetic state. This approach has also been employed here. Therefore average values for the growth parameters RGR, NAR, LAR, SLA and LWR were compared on the basis of a DW interval instead of a time interval. The DW interval is 20.1-2981 mg (1nDW = 3-8)) because this is about the largest possible interval in these experiments not requiring extrapolation of data. This means that at the beginning of each experiment DW was less than 20 mg and at the end of each experiment all treatments had reached at least a DW of 3000 mg. Instantaneous values were calculated by means of the polynome described in Equation ( 1) and similar polynomes for the plots of the natural logarithms of DW1 and A against time. Average RGR, NAR, LAR, SLA and LWR values were calculated by taking the mean of daily instantaneous values over the DW interval. Results were statistically analysed by analysis of variance. An attempt to give results in simple regression formula was made. With the statistical package GENSTAT the best model was calculated out of 5 independent regressors,
15 i.e. Td, Tn, Td* Tn, T~ a n d T~, b y b a c k w a r d e l i m i n a t i o n , w h i c h is o f t e n a very good variable selection p r o c e d u r e ( M o n t g o m e r y a n d Peck, 1982, pp. 2 7 3 - 2 7 5 ). R e g r e s s o r s were r e m o v e d f r o m t h e m o d e l u n t i l t h e a b s o l u t e value o f t h e t statistic for e a c h p a r a m e t e r was m o r e t h a n 2. F u r t h e r m o r e a linear regressor (e.g. T~) was n o t r e m o v e d f r o m t h e m o d e l if t h e q u a d r a t i c regressor (in this e x a m p l e T~ ) was s i g n i f i c a n t in t h e model. So, in a way, we a d o p t e d t h e v i e w p o i n t t h a t it is t h e o r d e r o f t h e m o d e l t h a t is i m p o r t a n t , n o t t h e individual t e r m s (L.C.A. C o r s t e n , p e r s o n a l c o m m u n i c a t i o n , 1987). RESULTS AND DISCUSSION
Parameters. - F W , D W , p l a n t length, A a n d n u m b e r of leaves were signific a n t l y i n f l u e n c e d b y t h e t e m p e r a t u r e regime ( T a b l e 2), w h e r e a s n u m b e r of t r u s s e s was not. T h e l a t t e r was p r o b a b l y due to t h e small n u m b e r of t r u s s e s anyway. F W was equal at c o n s t a n t t e m p e r a t u r e ( 2 0 / 2 2 °C a n d 2 2 / 2 0 ° C ) a n d u n d e r c o n d i t i o n s w i t h a h i g h e r To ( 2 6 / 1 6 ° C a n d 2 4 / 1 8 ° C ) , b u t t h e s a m e average t e m p e r a t u r e ( T a b l e 2). D W shows identical b e h a v i o u r . F r i e n d a n d H e l s o n (1976) r e p o r t e d t h e s a m e for g r o w t h o f y o u n g t o m a t o plants. G r o w t h u n d e r a n i n v e r s e d t e m p e r a t u r e regime ( 1 8 / 2 4 ° C a n d 1 6 / 2 6 ° C ) was r e d u c e d c o m p a r e d to a c o n s t a n t regime a t t h e s a m e t e m p e r a t u r e integral. T h i s negative effect of i n v e r s e d t e m p e r a t u r e regimes o n g r o w t h o f y o u n g t o m a t o p l a n t s has also b e e n TABLE 2 Effects of temperature regime1 (treatment) on FW, DW, plant length, A, number of leaves ( > 5 mm) and number of trusses at the end of the experiments Treatment (Td/Tn, °C)
Average n temp. (°C)
FW (g)
DW (g)
26/16 24/18 22/20 20/22 18/24 16/26 18/18 24/24 24/12
21 21 21 21 21 21 18 24 18
61a~d 95ab 61~¢d 102~b 48Cd 40Cd 26d 92b 73~b¢
6.5abed 8.9~ 6.2~bcd 9.4ab 4.8bed 3.8ed 2.8d 9.2a 7.2~bcd
F PR
2 1 2 1 2 1 2 2 1
0.004
0.006
Plant length (cm)
A (cm2)
52ab 1190a 50abe 1932cd 34co 1292ac 35bCde 21100 28de 925~b 23de 802~b 18~ 552b 54~ 1867ca 39abed 1421~¢d < 0.001
No. of leaves No. of trusses 16.6~d 17.70 16.2acd 16.9d 15.2abe 14.1~ 13.3b 17.9d 16.0acd
0.001
1Mean separation by Tukey's HSD test (P < 0.05), only when F PR < 0.01. n = No. of replicates; F PR = F probability.
0.002
3.6 4.0 3.2 3.9 3.0 2.9 2.4 3.8 3.7 0.110
16 reported by Calvert (1964), Hussey (1965), Klapwijk and Wubben (1978) and Went (1944). Also Friend and Helson (1976), who investigated growth of 7 crops, concluded that a high Td and lower Tn resulted in greater growth than a low Td and higher Tn for the same daily mean temperature. For A, influence of temperature regime at the same temperature integral was the same as for FW and DW. However, plant length was always reduced when Td decreased at the same temperature integral (Table 2). This was also reported for cucumber and sweet pepper (Klapwijk and Wubben, 1978), soybean (Thomas and Raper, 1978) and tomato (Verkerk, 1955; Calvert, 1964; Morgan and Clarke, 1975; Klapwijk and Wubben, 1978). Plant development (number of leaves, number of trusses) was similar at constant temperature and under conditions with a higher Td at the same integral. At an inversed temperature regime development was slowed. This reduction was much less than the reduction in weight. At 16/26 ° C, compared to 26/16 ° C, DW was reduced by 42 %, whereas the number of leaves was reduced by only 15% (Table 2). When the influences of temperature regime on number of leaves and plant length are compared, differences obtained in plant length were rather a result of differences in internode elongation than in number of nodes produced (Table 2). Thomas and Raper (1978) report the same for soybean. Klapwijk and Wubben (1978), using young tomato, cucumber, sweet pepper and chrysanthemum plants, concluded that an inversed temperature regime (17/23 °C) reduced plant length more than FW. The same was found in the present study when 26/16°C and 16/26°C were compared. For young tomato plants the inversed temperature regime led to a 34% reduction in FW, while length was reduced by 56%. However, for 24/18°C and 18/24°C decrease in FW ( - 4 9 % ) was about the same as decrease in length ( - 4 4 % ). a n a l y s i s . - In order to explain the decrease in growth and development at an inversed temperature regime a growth analysis was conducted (Table 3). RGR can be separated into an assimilatory component (NAR) and a morphological component (LAR). From the given F PR in Table 3 (bottom line ) a preliminary conclusion might be that changes in RGR due to temperature regime are mainly caused by changes in LAR and not by changes in NAR. This is in good agreement with Nilwik (1981b), who reported for sweet pepper that the influence of temperature on RGR was largely mediated through changes in LAR. Also Challa and Brouwer (1985) concluded for young cucumber plants that the influence of different Tn regimes is mainly through LAR. In general, no large temperature effects on NAR are reported (Warren Wilson, 1966; Terry, 1968). This also agrees with Gaastra's (1959) finding that net photosynthesis of tomato leaves at 0.03% CO2 is hardly influenced by the temperature (12.520.5 ° C). As respiration rates are rather small compared to photosynthetic rates at our conditions, they do not contribute much to the measured NAR. HowGrowth
]7 TABLE3 Effects of t e m p e r a t u r e regime ~ on m e a n values of RGR, NAR, LAR, SLA a n d L W R over t h e D W interval 20.1-2981 mg Treatment (Td/Tn, °C)
Average temp.
n
26/16 24/18 22/20 20/22 18/24 16/26 18/18 24/24 24/12
21 21 21 21 21 21 18 24 18
2 1 2 1 2 1 2 2 1
FPR
RGR (day -1) 0.168 ab 0.177 ~ 0.169 ab 0.178 b~ 0.158 ~c 0.146 cd 0.136 d 0.184 e 0.164 abe <0.001
NAR ( m g c m - 2 d a y -1)
LAR (cm2mg -1)
SLA ( c m 2 m g -1)
LWR
0.528 0.542 0.509 0.508 0.541 0.483 0.526 0.517 0.558
0.319 0.326 0.335 0.350 0.296 0.304 0.249 0.356 0.294
0.489 0.492 0.491 0.513 0.426 0.447 0.356 0.524 0.462
0.657 0.663 0.690 0.685 0.697 0.683 0.673 0.686 0.638
0.915
0.122
0.342
0.773
1Mean separation by Tukey's H S D test ( P < 0.05 ), only w h e n F P R < 0.01 ). n = No. of replicates; F P R = F probability.
ever, Friend and Helson (1976) concluded for wheat that the high rate of growth obtained under a temperature regime of high Td was the result of a high rate of net photosynthesis. This conclusion was based on their finding that LAR, SLA and LWR were not influenced by the temperature regime at the same temperature integral and on the positive correlation between respiration rate and night temperature. On the other hand, one can argue that a lower Td will reduce respiration during the day, just as a lower Tn lowered respiration during the night. As a matter of fact, this can be concluded from the results presented by Friend and Helson (1976) themselves. At 30°C mean temperature, C02 uptake during the day minus CO2 release during the night was the same for 25/35°C and 35/25°C. Plant weight and leaf area did not differ, so any ontogenetic effects were unlikely. At a mean temperature of 20 ° C, CO2 uptake during the day minus CO2 release during the night was 20% higher at 15/25 °C than at 25/15°C, whereas DW and A were about 30% lower. According to Friend and Helson (1976) net gain in CO2 and NAR are highly correlated. Thus these authors found LAR, SLA and LWR to be independent of temperature regime at the same temperature integral, but their conclusion that increased growth at higher Td at the same integral is caused by higher NAR is not supported by their own results. LAR can be considered as the result of SLA times LWR. Table 3 (bottom line ) shows that changes in LAR were mainly caused by changes in SLA, and thus by differences in leaf thickness (1/SLA). Also Harssema (1977) concluded that for young tomato plants LWR was insensitive to temperature. In this respect it is also interesting to note that Nilwik (1981b) reported for sweet
18 pepper that L A R was highly correlated with the specific leaf weight ( 1 / S L A ) . H u n t (1982) concluded that of SLA and LWR, the former is in general more sensitive to environmental change. Warren Wilson (1966) reported for rape, maize and sunflower that temperature effects on growth were mainly through L A R (not N A R ) and SLA (not L W R ) . This is exactly what we can conclude for the effect of different temperature regimes at the same temperature integral (Table 3 ). Correlations. - To obtain a general picture of the treatment effects on the different growth parameters pairwise correlation coefficients can be calculated (Eagles, 1967; Wilson and Cooper, 1969; Nilwik, 1981b). For all 9 treatments together, correlation coefficients (Table 4) were positive and significant between R G R and LAR, between R G R and SLA and between L A R and SLA. The negative and significant correlation coefficient between N A R and L W R was unexpected. For the 6 treatments at the same temperature integral (21 ° C ) correlation coefficients (Table 4) were positive and significant between R G R and LAR, and between R G R and SLA. There was a highly positive correlation between L A R and SLA. It is clear that differences in R G R under different temperature regimes (at the same integral) are almost completely related to differences in leaf thickness ( 1 / S L A ) . It is now concluded that growth reduction at an inversed temperature regime in comparison with a traditional or constant temperature regime was due to the development of thicker leaves (SLA was lower ) at an inversed temperature regime. Thicker leaves led to less light interception per unit leaf weight and thus to growth and development reduction. For a producing crop (closed can-
TABLE4 Correlations between growth parameters of young tomato plants. The correlation matrix is given for all treatments (n=9) and for those treatments with an average 24-h temperature of 21°C
(n=6) RGR
NAR
All treatments (n = 9 ) NAR 0.141 LAR 0.901"** - 0.280 SLA 0.933*** - 0.133 LWR - 0.005 - 0.584* Treatments with mean temperature of 21 °C (n = 6) NAR 0.469 LAR 0.810" - 0.131 SLA 0.838* - 0.034 LWR -0.354 -0.273 *P
LAR
SLA
0.966*** 0.261
0.946*** -0.145
0.012
- -
0.455
19
opy) leaf thickness barely influences light interception (all the light is already intercepted) and this explains why young plants, in contrast to producing crops, show a strong thermoperiodicity. The results can be presented in the form of regression formulae (Table 5). These formulae are centered round 21°C. R 2 is quite low for some relationships (Table 5). This means that a lot of variation in the plant parameters is not explained by Td and Tn. Most extreme, this is demonstrated for NAR, which was not influenced by Td and Tn in the present experiments. Table 5 shows that for RGR there is an interaction between Td and Tn. This makes general evaluations of simple effects of day and night temperatures difficult for this parameter. It should be kept in mind that Table 5 shows the results of a regression analysis. This means that extrapolation outside the temperature range used in our experiments is not valid. For example, if we were to calculate plant length for a treatment with Td= 12°C and T n = 12°C, it would be negative. Furthermore, these regression formulae are based on only 9 Td and T~ combinations and not a complete set of temperatures. Therefore, their validity is restricted. Some of the formulae in Table 5 are displayed graphically in Fig. 1. Table 5 and Fig. 1 show that the influence of Td on plant growth and development is larger than the influence of Tn (between 18 and 24°C ), which is in accordance with results obtained by Calvert (1964). Hussey (1965) reported that for 9day-old tomato plants Td was about twice as important as Tn for RGR. Leaf growth rate and stem growth of young tomato plants were, according to Hars-
Regressions. -
TABLE 5 "Best models" selected by a backward elimination procedure. Independent regressors used are T,, T,. Regressors were removed from the model until the absolute value of the t statistic for each parameter was more than 2 Selected model FW (g) DW (g) Plantlength (cm) A (dm 2) Numberofleaves Number of trusses RGR NAR LAR SLA LWR
= = = = --
= = = = = =
63.0 +6.44 Td+3.08 T~ 6.26+0.647Td+0.287T~ 36.3 +4.48 Td+l.37 Tn 15.4 +1.37 Td+0.615Tn-0.246 T~ 16.4 +0.513Td+0.221Tn-0.0442T~ 3.26+0.117Td
0.172+0.00511Td +0.00283Tn +0.000405TdTn-0.00101T~ 0.524 0.315+0.00998Td+0.00694Tn 0.464+0.0167 Td+0.00891T~ 0.680+0.00373Tn
R2
SE
54 62 94 67 88 47
18.9 1.59 3.50 3.37 0.623 0.432
95 0 65 55 36
0.00433 0.00844 0.0245 0.0477 0.0208
20
55
0.55
A
13
jr"
0.50
(.5
8' 0.45
25
15
J.;..S(." I
I
I
16
18
~
0.40 /
~
I 2(. T d (°C)
C
--
0.35
.S
r"
i
i
16
10
20
0.10
6
~" o,~6
~.
0,14
/
0.12
/
/ p
s
I 10
~
2~ T d (°C)
Tn
/
- - - - 21% -- - - l r C
/
I 16
i
22
0.20
0
I".~,
I
I 20
I 22
I 24 T d I'C )
0.10
d I
I
I
I
16
10
29
22
I
24 Td ('PC)
Fig. 1. Plant length (A), SLA (B), DW (C) and RGR (D) for young tomato plants as influenced by Td and T., according to the regression formulae of Table 5.
sema (1977), largely influenced by Td, while the effect of Tn was much smaller. Friend and Helson (1976) concluded for 7 crops that at suboptimal diurnal temperatures Td was more important for DW increases than Tn. From the experiments of T h o m a s and Raper (1978) with soybean it could be concluded, although a significant interaction between Td and Tn occurred, that Td was more important for main stem length than T., even at a day length of 9 h. However, Haroon et al. (1972) found for tobacco that growth of seedlings from first leaf to transplant size was affected to a larger extent by Tn than by Td. This can probably be explained by the day length of only 9 h in their experiment, making in advance T. almost twice as important as Td. ACKNOWLEDGEMENTS
The author wishes to thank Prof. L.C.A. Corsten for his statistical advice. He is much indebted to Miss R.P.M. Buiskool, who did most of the measurements, and to De Ruiter Seeds, Bleiswijk, The Netherlands, for supplying the tomato seeds.
21 REFERENCES
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