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Contribution of climatic variables in predicting rice yield
Agricultural Meteorology, 15(1975) 71--86 @)Elsevier Scientific Publishing Company, Amsterdam -- Printed in The Netherlands
CONTRIBUTION OF CLIMATIC VARIABLES IN PREDICTING RICE YIELD
A. K. SAMSUL HUDA I , B. P. GHILDYAL 1 , V. S. TOMAR 1 and R. C. JAIN 2
1Department of Soil Science; 2 Department of Mathematics and Statistics, G. B. Pant University of Agriculture and Technology, Pantnagar, Nainital (India) (Received January 10, 1975; accepted January 23, 1975) ABSTRACT Huda, A. K. S., Ghildyal, B. P., Tomar, V. S. and Jain, R. C., 1975. Contribution of climatic variables in predicting rice yield. Agric. Meteorol., 15: 71--86. An attempt was made to understand how the intensity and distribution pattern of weather parameters at different stages of growth affect the rice yield. The second-degree multiple-regression equation can profitably be employed in quantifying the relationship between rice yield and weather variables. The results show that the crop reacts differently to climatic parameters during different stages of development. The resultant response is manifested in the final yield. Above average weekly total rainfall is beneficial during the nursery period. The vegetative phase coincides with the heavy-rain period on account of the onset of the monsoon and therefore any increase in weekly total rainfall more than the average has the adverse effect. The ripening phase is the most susceptible to excess rainfall. Above average maximum and minimum daily temperature have beneficial effect during the nursery period. A change of +I°C of maximum daily temperature from the average value has slight effect during the later part of the nursery, the early active vegetative stage and the later part of the ripening period. The lag vegetative to early reproductive phase is most susceptible to maximum daily temperature. The later part of the nursery period and the early active vegetative phase are slightly affected by a change of -+1°C minimum daily temperature from the average. A change of -+1% of maximum and minimum daily relative humidity from the average during the nursery period slightly affects the yield. The reproductive and ripening phases are susceptible to a change of +1% maximum and minimum daily relative humidity and also to a change of +I°C minimum daily temperature from their corresponding averages. INTRODUCTION
Climate affects crop growth through soil and plant processes. Soil properties such as thermal and water regimes, nutrient and aeration status are influenced by climatic conditions. These effects are manifested through crop stand, n u mb er of tillers, r o o t length, leaf area, num b er of ear heads, etc., which ultimately determine crop yield. The climatic variables may also create conditions favourable or unfavourable for the development of diseases and pests. The complex interactions among climatic parameters themselves and with soil and plant make difficult an accurate analysis of the relationships involved.
72 Several attempts have been made to utilize the correlation and regression methods to study the effect of climatic parameters on crop yield (Fisher, 1924; Stacy et al., 1957; Ram Dayal, 1965; Runge, 1968). Correlation studies, however, have n o t been fruitful as might be hoped. First reason is the essential requirement of reliable meteorological and related crop yeild data for a series of a sufficient n u m b e r of years. Though the reliable meteorological data are available for quite a long period for a n u m b e r of stations, the related cropyield figures are n o t available. If available for a district or locality, the data are n o t reliable. The crop yield varies from year to year depending not only on climatic factors but also on the plant t y p e used, soil conditions and management inputs. Soil physical and chemical conditions may vary from place to place resulting variation in crop yield. The variation in soil conditions and management inputs causes a variation ~n crop yield from year to year and place to place. The objectives of crop--weather relationship studies thus may n o t be achieved in absence of reliable yield data. At the University Farm, Pantnagar, accurate yield data, soil information and corresponding meteorological data are available for more than a decade. Since this is a commercial seed production farm, the management inputs are not limiting to crop yield. High yielding varieties, r e c o m m e n d e d doses of manures and fertilizers, proper plant protection measures and ot her soil and water management and cultural practices are undertaken regularly. The second essential requirement for such studies is to know h o w t h e changes in climatic conditions during a specific growth period or during different growth stages of the crop or during the whole growing season affect the yield. The crop reacts differently to climatic parameters during different stages of development. These responses are usually manifested in the final yield of the crop. Therefore, not only the reliable meteorological data for the whole crop-growing season are needed but it is also essential to know their distribution at each growth stage. Analysis of this data may help in understanding the crop--weather relationship. Such an analysis based on weekly weather data enables one to determine the seasonal variations and the effect of weather factors more accurately than from yearly or cropping season or m o n t h l y weather data. In this paper attempts have been made to understand how the intensity and distribution of different climatic variables at different stages of growth affect the rice yield. MATERIALS AND METHODS Pantnagar is situated approximately 283.89 m above sea level. It is at a latitude of 29°N and a longitude of 79.3°E. This region known as Tarai (meaning wet) has a dry season from early O ct ober to mid June and a wet season from mid June to early October. The soils of the Tarai are mainly silty and loamy, have good moisture storage capacity and are highly productive. Th ey are classified as Mollisols.
73
Rice yield Rice yield data are given in Table I. The yields are the average of the whole Pantnagar rice farm covering approximately 1,000 ha. Though the data of twelve years may not be sufficient for statistical analysis, it was assumed that it can explain some of the variability in rice yield due to weather conditions.
TABLEI Rice yield data Year
Yield (quintals/ha)
1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972
11.05 20.55 19.20 21.17 21.10 30.25 16.95 27.92 28.42 30.37 31.87 38.15
Rice growing season As shown in Fig.l, the rice growing season covers an approximate period of 168 days from May 21 to November 4. For analysis purpose this period was divided into 24 7-day periods. The whole rice growth season can broadly be grouped into following three phases. (1) Establishment phase. This includes the period from sowing to emergence, nursery growth and transplanting. During this period the puddling and o th er land preparation operations are completed. For all these practices including puddling and transplanting considerable a m o u n t of water is required. This period comprises of early five weeks of growing season covering May 21 to June 24. On the basis of climatic parameters this is termed as p r e m o n s o o n period. This pre-monsoon period is characterised by the occasional prem o ns o o n showers, h o t days, rising minimum daily temperature, and rising m a x i m u m and minimum daily relative humidity.
74 (2) Growth phase. This phase includes the active, the lag vegetative and the reproductive growth periods. The critical stages of this phase appear to be maximum tillering, ear-initiation and flowering. This phase lasts from June 25 to September 30 and is termed climatologically as monsoon period. This monsoon period is characterised by heavy showers due to onset of the monsoon, moderately high maximum daily temperature, warm nights and high maximum and minimum daily relative humidity.
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Fig.1. Growth stages of the rice crop.
(3) Maturity phase. This phase includes the ripening stage of the crop covering the period from October 1 to November 4. Climatologically this is called as post-monsoon period. This period is characterised by scanty rain due to withdrawal of the monsoon, low maximum daily temperature and decrease in minimum daily temperature and minimum daily relative humidity. These phases may be sub-divided into seven physiological stages, viz. sowing and emergence from May 21--27, nursery growth from May 28 to June 17, transplanting from June 18--24, active vegetative stage comprising of transplanting to maximum tillering period from June 25 to August 5, lag vegetative stage from August 6 to September 2, reproductive phase from September 3-30, and ripening stage from October 1 to November 4.
Statistical analysis Exact mathematical relations for crop yield, rainfall, maximum and minimum daily temperature, maximum and minimum daily relative humidity are not known. However, based on previous work (Stacy et al., 1957; Ram Dayal, 1965; Runge, 1968) it was assumed that a second degree multiple regression equation would be sufficiently flexible to express the relation. The assumptions used in this study were similar to those used by Runge (1968). The second-degree multiple regression equation between crop yield and
75 each climatic variable as developed by Fisher (1924), modified by Hendricks and Scholl (1943) and as adopted by Stacy et al. (1957) and Runge (1968) is:
Z : Ao + a, L (to Y) + a2 ~ (tliy) + a3 ~ (t~ y) + D T i=1
i=1
i=1
where Z = crop yield (q/ha); A o , a~, a2, a3 and D (- constants); y = any climatic variable within any given 7-day period; t~ = the number of each of the 7-day periods (it is 1 for the period from May 21--27 and 24 for the period from Oct. 29 to Nov. 4); n = 24 7-day periods in a given season of the year; T = year number (beginning with one in 1961 and ending with twelve in 1972) which was included to correct for the long term upward or downward trend in yield. Since the data on relative humidity were in percentages and were not normally distributed, the data were, therefore, transformed into arc-sine root proportion and then subjected to analysis. RESULTS AND DISCUSSION
To elucidate the effect of climate on rice yield, the distribution of climatic variables during the rice growing season is discussed first and then its effect on rice yield.
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60C
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Fig.2. T o t a l r a i n f a l l f o r d i f f e r e n t y e a r s .
76
Distribution o f clima tic variables Rainfall. The total rainfall for d i f f e r e n t years indicates t h a t t h o u g h the average rainfall for Pantnagar is 1,500 ram, the total a m o u n t o f rainfall m a y f l u c t u a t e f r o m 790 m m to 2,100 m m f r o m y e a r to year (Fig.2). The first good showers o f rain are received in the third week o f May. The average w e e k l y total rainfall distribution for each 7-day period during the rice growing season shows an increasing t r e n d in the rainfall f r o m May 21 to July I (Fig.3). During this period the rainfall received varied f r o m 8.7 m m 140~ 130i
8
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~ 30i
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3 JUNE
JULY
AUG
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17 SEPT
24
1
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15 22 29 OCT
Fig.3. Average total rainfall and evaporation for each S-day period, May 21 -- November 4. to 61.0 m m . It may, h o w e v e r , be as high as 211 m m ( J u n e 18--24, 1962). July to August 26 is the peak m o n s o o n period. During this period the rainfall m a y vary f r o m 67 m m to 135 m m and it m a y be as high as 107 m m ( O c t o b e r
1--7, 1968). From Fig.3 it is apparent that the period ranging from the last week of June to the third week of September is of low water deficit, because evapotranspiration losses are low and rainfall is high. This period appears to be highly conducive for good vegetative growth; M a x i m u m and m i n i m u m daily temperature. The average m a x i m u m daily t e m p e r a t u r e during the rice growing season varied f r o m 30 ° t o 40°C, and the m i n i m u m f r o m 13 ° t o 25 ° C. The distribution o f average m a x i m u m and minim u m daily t e m p e r a t u r e s for each 7-day period during the rice growing season shows a decreasing m a x i m u m t e m p e r a t u r e and rising m i n i m u m t e m p e r a t u r e
77 during the period from May 21 to June 24 (Fig.4). The average maximum temperature may vary from 36 ° to 40°C but it may be as high as 43°C (May 21--27, 1969) and the minimum may vary from 21 ° to 25°C.
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Fig.4. Average m a x i m u m a n d m i n i m u m daily t e m p e r a t u r e for each 7-day period, May 21 - - N o v e m b e r 4.
The period covering June 25 to September 30 is characterized by stable maximum and minimum temperatures. During this period the maximum temperature varied.between 32 ° and 34°C and it may be 29°C (August 27--September 2, 1962) while the minimum temperature varied between 24 ° and 25°C. During the period of October 1 to November 4, the maximum temperature may vary a little while the minimum temperature decreased rapidly. Maximum and minimum daily relative humidity. The average maximum daily relative humidity during the rice growing season varied from 57 to 92%, and the minimum from 26 to 75%. The distribution of average maximum and minimum daily relative humidity for each 7-day period during the rice growing season shows that both values register rapid increase from May 21 to June 24 (Fig.5). During this period the maximum relative humidity may increase from 57 to 78% and the minimum relative humidity from 26 to 53%. The maximum and minimum relative humidity are stabilized during the period of June 25 to August 26, i.e., during the peak monsoon period. During this period the maximum relative humidity varied from 80 to 92% and minimum relative humidity from 60 to 75%. During the period of August 27 to November 4 there was a slight decrease
78 in maximum relative humidity but the minimum relative humidity decreased sharply. During this period the maximum relative humidity decreased from 90 to 84% while minimum relative humidity decreased from 55 to 43%.
E f f e c t o f climatic variables on rice yield The weekly total rainfall, weekly average maximum and minimum daily temperatures, and maximum and minimum daily relative humidity of 24 weeks of the rice growing season and the rice yield for 12 years, i.e. from 1961 to 1972, were analysed. The multiple regression equations were obtained for different climatic parameters. g6[_
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Fig.5. Average maximum and minimum daily relative humidity for each S-day period, May 21 -- November 4.
E f f e c t o f rainfall distribution. The multiple regression equation obtained for rainfall was: 24
24
Z = 19.405499 + 0.00332357 ~ t°yl - 0.0007246248 ~ t]yl i=1
i=1
24
+ 0.0000019906 ~ t~y~ + 1.799578 T i= 1
The coefficient of determination (R 2 ) obtained was 0.7952 which was found to be significant at 2.5% level.
79 During the establishment phase, the average weekly total rainfall varied from 8.7 to 40.5 mm. Therefore, if the total a m o u n t of rainfall received in each week during this period excepting the fifth week was 1 m m more than the average, the beneficial effect of rainfall on rice yield was observed. This was 260 g/ha during the first week covering May 21--27 (Fig.6). This effect decreased in the following weeks and was 188 gm, 117 gm and 46 gm per hectare during the second, third and fourth week, respectively, During the fifth week, however, the increase in weekly total rainfall by 1 mm m ore than the average reduced the yield. On the contrary, the reverse was true if the weekly total rainfall was 1 mm less than the average i.e., adverse effect of decreasing rainfall was observed. +O3
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Fig.6. Effect of I mm of rainfall above average weekly total rainfall on rice yield for each 7-day period, May 21 -- November 4. During the growth phase, the average weekly total rainfall varied from 35.0 to 134.6 mm. The heavy rainfall received in each week during this period is more than sufficient to meet the growth requirements of the crop. Further increase in weekly total rainfall may be of no use, but the excess water may adversely affect the crop. Therefore, the reduction in yield was observed during this period if the weekly total rainfall was 1 mm m ore than the average. The reduction in yield was 95 g/ha during the sixth week and 165 g/ha during the 7th week. The same was 441 g/ha during the 11th week (maximum tillering stage), 710 g/ha during the 15th week (ear-initiation
80
stage), and 972 g/ha during the ] 9 t h week. On the contrary the reverse was true, i.e., beneficial effect was observed if the weekly total rainfall was 1 mm less than the average. During the maturity phase, the average weekly total rainfall varied from 17.4 to 0.0 mm. The ripening phase requires clear sunny days and increased sunshine hours. Heavy showers during this period may cause a great damage to the crop. It may also delay the harvesting operation. Therefore, if the weekly total rainfall during this phase was 1 mm more than the average, the adverse effect on yield was observed. This was of the order of 1.04 kg/ha during the 20th week, 1.10 kg/ha during the 21st week and 1.29 kg/ha during the 24th week. On the contrary, the reverse was true if the weekly total rainfall was 1 mm less than the average. E f f e c t o f m a x i m u m daily temperature. The multiple regression equation obtained for maximum daily temperature was: 24
24
Z = 95.46937 + 0.2068969 ~ t°y2 - 0.06046426 ~ t])'2 i=1
i
i
24
+ 0 . 0 0 2 1 4 4 8 9 3 ~ t~y2 + 2.021593 T i=1
The coefficient of determination (R 2 ) obtained was 0.7855 and it was found to be significant at 2.5% level. During the establishment phase, the average m axi m um daily temperature decreased from 39.5 ° to 36.4 ° C. Because of this decreasing temperature trend the beneficial effect of temperature was observed in the first three weeks and the adverse effect in the last two weeks (Fig.7). The beneficial
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Fig.7. E f f e c t o f 1~C above the average m a x i m u m daily t e m p e r a t u r e o n rice yield for each 7-day period, May 21 - - N o v e m b e r 4.
81 effect was of the order of 14.8 kg/ha during the first week while the adverse effect was 4.180 kg/ha during the 5th week, if the maximum daily temperature was l°C more than the average. The reverse was true if maximum daily temperature was I°C less than the average. The higher temperature helped in better establishment of the crop. During the growth phase, the average maximum daily temperature varied between 32 ° and 34°C. Since the optimal temperature for tillering is 32 ~ -34°C (Kondo and Okamura, 1936), further increase in maximum daily temperature during this phase by 1°C more than the average had an adverse effect on yield. This was as high as 20.0 kg/ha during the maximum tillering stage, 21.8 kg/ha during the ear-initiation stage and 16.8 kg/ha during the flowering stage. The beneficial effect was obtained if the maximum daily temperature was I°C less than the average. During the maturity phase, the average maximum daily temperature decreased from 32 ° to 29°C. If the maximum daily temperature was 1°C more than the average, the adverse effect on yield reduction was observed. This was 14.4 kg/ha during the 20th week and only 0.879 kg/ha during the 24th week. Effect of minimum daily temperature. The multiple regression equation obtained for minimum daily temperature was: 24
24
Z = 76.41432 + 0.1267232 ~ tiy3 o - 0.02699649 ~ t~y3 z=l
i=1
24
+ 0 . 0 0 0 3 9 7 5 8 5 4 ~ t~y3 +1.747374T i=1
The coefficient of determination (R 2 ) obtained was 0.8023 and it was found to be significant at 2.5% level. During the establishment phase, the average minimum daily temperature varied from 21.1 ° to 24.7°C. If the minimum daily temperature during this period was 1°C more than the average, the beneficial effect on yield was observed (Fig.8). This was 10.012 kg/ha during the first week and decreased to 0.168 kg/ha during the 5th week. During the growth phase, the average minimum daily temperature varied from 24 ° to 21.9°C. If there was an increase in minimum daily temperature during this phase by 1°C more than the average, the adverse effect on yield was observed. It appears (Vamadevan, 1974) that higher minimum temperature at vegetative stage is found to have a significant negative role in determining yield even for the high yielding dwarf indicas. The results showed that the adverse effect due to increase in the minimum daily temperature was 12.2 kg/ha during the maximum tillering stage, 18.9 kg/ha during the ear-initiation stage and 24.3 kg/ha during the flowering stage. During the maturity phase, the average minimum daily temperature
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Fig.8. Effect of I°C above the average minimum daily temperature on rice yield for each 7-day period, May 21 -- November 4. decreased f r o m 19.6 ° to 12.8°C. If the m i n i m u m daily t e m p e r a t u r e during this phase was I ° C m o r e than the average, the r e d u c t i o n in yield was observed. This was up t o 29.22 k g / h a during the 2 4 t h week. Effect o f maximum daily relative humidity. The multiple regression e q u a t i o n o b t a i n e d for m a x i m u m daily relative h u m i d i t y was: 24
Z = 64.171637 + 0.01483521 ~
24
t~y4 - 0 . 0 0 6 4 5 0 2 0 5 ~ t~y4
i=l
i=1
24
+ 0.0001709098 ~
t~y4 + 1 . 8 5 5 8 9 7 T
i=l
The c o e f f i c i e n t o f d e t e r m i n a t i o n (R 2 ) o b t a i n e d was 0 . 7 8 3 3 and it was f o u n d to be significant at 2.5% level. During the e s t a b l i s h m e n t phase, the average m a x i m u m daily relative h u m i d i t y varied f r o m 57 to 78%. During the first t w o weeks, if the m a x i m u m daily relative h u m i d i t y was 1% m o r e than the average, a slight beneficial e f f e c t on yield was observed (Fig.9). But the increase in m a x i m u m daily relative h u m i d i t y b y 1% t h a n the average r e d u c e d the yield during the rest o f the weeks o f this period. During the growth phase, the average m a x i m u m daily relative h u m i d i t y varied f r o m 84 to 92%. If there was an increase in m a x i m u m daily relative h u m i d i t y during this phase b y i per cent than the average, the r e d u c t i o n in
83
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Fig.9. Effect of 1% of relative humidity above the average maximum daily relative humidity o n r i c e y i e l d f o r e a c h 7 - d a y p e r i o d , M a y 21 -- November 4.
yield was observed. This was 3.5 kg/ha during the maximum tillering stage and 4.4 kg/ha during the ear-initiation stage and 4.6 kg/ha during the flowering stage. During the maturity phase, the average maximum daily relative humidity varied from 84 to 87%. Therefore, with the increase in maximum daily relative humidity during the period by 1% more than the average, the adverse effect on yield was observed. This was of the order of 4.6 kg/ha during the 20th week, and 4.2 kg/ha during the 24th week. Similarly, the reverse effect is observed on rice yield at a decrease of 1% below average maximum daily relative humidity. Effect o f m i n i m u m daily relative humidity. The multiple regression equation obtained for minimum daily relative humidity was: 24
Z =- 14.788064 + 0.002536192 ~
24
t°ys - 0 . 0 0 1 3 3 8 1 0 5 ~ t]ys
i=1
i=1
24
+ 0 . 0 0 0 0 2 1 4 0 6 4 2 t~ys + 1 . 7 6 5 0 4 5 T i=1 The coefficient of determination (R 2 ) obtained was 0 . 7 5 4 6 and it was found to be significant at 5% level.
84 During the establishment phase, the average minimum daily relative humidity increased from 26 to 53%. The increase in minimum daily relative humidity had slight beneficial effect during the first week and adverse effect during the rest of this period (Fig.10). Like temperature, increased humidity, during the early stages of the establishment phase helped in increasing the growth and establishment of the crop.
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Fig. 10. E f f e c t o f 1% o f relative h u m i d i t y above the average m i n i m u m daily relative humi-
dity on rice yield for each 7-day period, May 21 - - N o v e m b e r 4.
During the growth phase, the average minimum daily relative humidity varied from 55 to 75%. If there was an increase in minimum daily relative humidity during this phase by 1% more than the average, an adverse effect on yield was observed. This was only 0.96 kg/ha during the maximum tillering stage, 1.3 kg/ha during the ear-initiation stage and 1.5 kg/ha during the flowering stage. High humidity in tropics, particularly during the rainy season is likely to affect the plant growth by reducing the transpirational cooling of the plant. The lowering of the yield with the increase in maximum and minimum daily relative humidity may be related to this effect. This hypothesis is further supported by the fact that low humidity is one of the important agrometeorological environmental factors for maximum rice production (DeDatta and Zarate, 1970). During the maturity phase, the average minimum daily relative humidity decreased from 54 to 43%. If the minimum daily relative humidity during this phase was 1% more than the average, an adverse effect on yield was observed. This was of the order of 1.57 kg/ha during the 24th week.
85
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PREDCTED
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i
Fig.11. Aetual and predicted yield for different years, using the regression equation for rainfall effects on rice yield. On the c o n t r a r y , if t h e m i n i m u m daily relative h u m i d i t y during m a t u r i t y phase was 1% less t h a n the average the reverse e f f e c t on yield was o b s e r v e d . T h e increase in yield with low relative h u m i d i t y c o n f i r m s the earlier observ a t i o n (Ghildyal and Jana, 1967) t h a t a low relative h u m i d i t y a r o u n d 43% during t h e grain f o r m a t i o n stage, and a t e m p e r a t u r e o f 12°--13°C are considered to be c o n d u c i v e to increased rice yield. This s t u d y shows a close r e l a t i o n s h i p b e t w e e n the m o n s o o n rice c r o p and w e e k l y climatic variables. A s e c o n d - d e g r e e m u l t i p l e regression e q u a t i o n can p r o f i t a b l y be e m p l o y e d in q u a n t i f y i n g these relationships. If the d i s t r i b u t i o n of climatic p a r a m e t e r s is k n o w n , the yield t r e n d can be p r e d i c t e d f o r d i f f e r e n t years. By using the regression e q u a t i o n o b t a i n e d for effects of rainfall on rice yield, the p r e d i c t e d and actual rice yield for d i f f e r e n t years f r o m 1961 to 1 9 7 2 are s h o w n in F i g . l l .
REFERENCES Best, R., 1962. Production factors in the tropics. Neth. J. Agri., 10: 347--353. De-Datta, S. K. and Zarate, P. M., 1970. Biometeorological problems in developing countries. Biometeorology, 4: 71--89. Fisher, R. A., 1924. The influence of rainfall on the yield of wheat at Rothamsted. R. Soc. (Lond.). Phil. Trans., Ser. B, 213: 89--142. Ghildyal, B. P. and Jana, R. K., 1967. Agrometeorological environment affecting rice yield. Agron. J., 59: 286--287.
86 Hendricks, W. A. and Scholl, J. C., 1943. Techniques in measuring joint relationship. The joint effects of temperature and precipitation on crop yield. N. Carolina Agric. Exp. Sta. Tech. Bull., 74. Kondo, M. and Okamura, T., 1936. Relation of water, temperature and growth in rice, II. NogaKukenkyu, 17: 37--64. Ram Dayal, 1965. Impact of rainfall on crop yield and average. 1. J.A.E., 20: 48--55. Runge, E. C. A., 1968. Effects of rainfall and temperature interactions during the growing season on crop yield. Agron. J., 60: 503--507. Stacy, S. V., Steamson, O., Jones, L. S. and Foreman, J., 1957. Joint effects of maximum temperatures and rainfall on crop yields. Agron. J., 49: 26--28. Tanaka, A., Kawano, K. and Yamaguchi, J., 1966. Photosynthesis, respiration and plant types of the tropical rice plant. Int. Rice Res. Inst., Los Banos, Laguna, Philippines, Tech. Bull., 7: 46. Vamadevan, V. K., 1974. Studies on water use and soil--water--plant climate relationships in rice. Paper presented at the International Rice Research Conference, April 22--25, 1974.
CONTRIBUTION OF CLIMATIC VARIABLES IN PREDICTING RICE YIELD
A. K. SAMSUL HUDA I , B. P. GHILDYAL 1 , V. S. TOMAR 1 and R. C. JAIN 2
1Department of Soil Science; 2 Department of Mathematics and Statistics, G. B. Pant University of Agriculture and Technology, Pantnagar, Nainital (India) (Received January 10, 1975; accepted January 23, 1975) ABSTRACT Huda, A. K. S., Ghildyal, B. P., Tomar, V. S. and Jain, R. C., 1975. Contribution of climatic variables in predicting rice yield. Agric. Meteorol., 15: 71--86. An attempt was made to understand how the intensity and distribution pattern of weather parameters at different stages of growth affect the rice yield. The second-degree multiple-regression equation can profitably be employed in quantifying the relationship between rice yield and weather variables. The results show that the crop reacts differently to climatic parameters during different stages of development. The resultant response is manifested in the final yield. Above average weekly total rainfall is beneficial during the nursery period. The vegetative phase coincides with the heavy-rain period on account of the onset of the monsoon and therefore any increase in weekly total rainfall more than the average has the adverse effect. The ripening phase is the most susceptible to excess rainfall. Above average maximum and minimum daily temperature have beneficial effect during the nursery period. A change of +I°C of maximum daily temperature from the average value has slight effect during the later part of the nursery, the early active vegetative stage and the later part of the ripening period. The lag vegetative to early reproductive phase is most susceptible to maximum daily temperature. The later part of the nursery period and the early active vegetative phase are slightly affected by a change of -+1°C minimum daily temperature from the average. A change of -+1% of maximum and minimum daily relative humidity from the average during the nursery period slightly affects the yield. The reproductive and ripening phases are susceptible to a change of +1% maximum and minimum daily relative humidity and also to a change of +I°C minimum daily temperature from their corresponding averages. INTRODUCTION
Climate affects crop growth through soil and plant processes. Soil properties such as thermal and water regimes, nutrient and aeration status are influenced by climatic conditions. These effects are manifested through crop stand, n u mb er of tillers, r o o t length, leaf area, num b er of ear heads, etc., which ultimately determine crop yield. The climatic variables may also create conditions favourable or unfavourable for the development of diseases and pests. The complex interactions among climatic parameters themselves and with soil and plant make difficult an accurate analysis of the relationships involved.
72 Several attempts have been made to utilize the correlation and regression methods to study the effect of climatic parameters on crop yield (Fisher, 1924; Stacy et al., 1957; Ram Dayal, 1965; Runge, 1968). Correlation studies, however, have n o t been fruitful as might be hoped. First reason is the essential requirement of reliable meteorological and related crop yeild data for a series of a sufficient n u m b e r of years. Though the reliable meteorological data are available for quite a long period for a n u m b e r of stations, the related cropyield figures are n o t available. If available for a district or locality, the data are n o t reliable. The crop yield varies from year to year depending not only on climatic factors but also on the plant t y p e used, soil conditions and management inputs. Soil physical and chemical conditions may vary from place to place resulting variation in crop yield. The variation in soil conditions and management inputs causes a variation ~n crop yield from year to year and place to place. The objectives of crop--weather relationship studies thus may n o t be achieved in absence of reliable yield data. At the University Farm, Pantnagar, accurate yield data, soil information and corresponding meteorological data are available for more than a decade. Since this is a commercial seed production farm, the management inputs are not limiting to crop yield. High yielding varieties, r e c o m m e n d e d doses of manures and fertilizers, proper plant protection measures and ot her soil and water management and cultural practices are undertaken regularly. The second essential requirement for such studies is to know h o w t h e changes in climatic conditions during a specific growth period or during different growth stages of the crop or during the whole growing season affect the yield. The crop reacts differently to climatic parameters during different stages of development. These responses are usually manifested in the final yield of the crop. Therefore, not only the reliable meteorological data for the whole crop-growing season are needed but it is also essential to know their distribution at each growth stage. Analysis of this data may help in understanding the crop--weather relationship. Such an analysis based on weekly weather data enables one to determine the seasonal variations and the effect of weather factors more accurately than from yearly or cropping season or m o n t h l y weather data. In this paper attempts have been made to understand how the intensity and distribution of different climatic variables at different stages of growth affect the rice yield. MATERIALS AND METHODS Pantnagar is situated approximately 283.89 m above sea level. It is at a latitude of 29°N and a longitude of 79.3°E. This region known as Tarai (meaning wet) has a dry season from early O ct ober to mid June and a wet season from mid June to early October. The soils of the Tarai are mainly silty and loamy, have good moisture storage capacity and are highly productive. Th ey are classified as Mollisols.
73
Rice yield Rice yield data are given in Table I. The yields are the average of the whole Pantnagar rice farm covering approximately 1,000 ha. Though the data of twelve years may not be sufficient for statistical analysis, it was assumed that it can explain some of the variability in rice yield due to weather conditions.
TABLEI Rice yield data Year
Yield (quintals/ha)
1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972
11.05 20.55 19.20 21.17 21.10 30.25 16.95 27.92 28.42 30.37 31.87 38.15
Rice growing season As shown in Fig.l, the rice growing season covers an approximate period of 168 days from May 21 to November 4. For analysis purpose this period was divided into 24 7-day periods. The whole rice growth season can broadly be grouped into following three phases. (1) Establishment phase. This includes the period from sowing to emergence, nursery growth and transplanting. During this period the puddling and o th er land preparation operations are completed. For all these practices including puddling and transplanting considerable a m o u n t of water is required. This period comprises of early five weeks of growing season covering May 21 to June 24. On the basis of climatic parameters this is termed as p r e m o n s o o n period. This pre-monsoon period is characterised by the occasional prem o ns o o n showers, h o t days, rising minimum daily temperature, and rising m a x i m u m and minimum daily relative humidity.
74 (2) Growth phase. This phase includes the active, the lag vegetative and the reproductive growth periods. The critical stages of this phase appear to be maximum tillering, ear-initiation and flowering. This phase lasts from June 25 to September 30 and is termed climatologically as monsoon period. This monsoon period is characterised by heavy showers due to onset of the monsoon, moderately high maximum daily temperature, warm nights and high maximum and minimum daily relative humidity.
©
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101112
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o
(WEEKS) 13
14
15
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18
19
20
21
22
23
24
13 2 0 2 7 3 10 17 2 4 1 8 15 22 2 9 AUG ~ ~ S E P T ~ ~ , O C T --~ VEGETATIVE~REPRODUCTIVE ~ -RIPENING
Fig.1. Growth stages of the rice crop.
(3) Maturity phase. This phase includes the ripening stage of the crop covering the period from October 1 to November 4. Climatologically this is called as post-monsoon period. This period is characterised by scanty rain due to withdrawal of the monsoon, low maximum daily temperature and decrease in minimum daily temperature and minimum daily relative humidity. These phases may be sub-divided into seven physiological stages, viz. sowing and emergence from May 21--27, nursery growth from May 28 to June 17, transplanting from June 18--24, active vegetative stage comprising of transplanting to maximum tillering period from June 25 to August 5, lag vegetative stage from August 6 to September 2, reproductive phase from September 3-30, and ripening stage from October 1 to November 4.
Statistical analysis Exact mathematical relations for crop yield, rainfall, maximum and minimum daily temperature, maximum and minimum daily relative humidity are not known. However, based on previous work (Stacy et al., 1957; Ram Dayal, 1965; Runge, 1968) it was assumed that a second degree multiple regression equation would be sufficiently flexible to express the relation. The assumptions used in this study were similar to those used by Runge (1968). The second-degree multiple regression equation between crop yield and
75 each climatic variable as developed by Fisher (1924), modified by Hendricks and Scholl (1943) and as adopted by Stacy et al. (1957) and Runge (1968) is:
Z : Ao + a, L (to Y) + a2 ~ (tliy) + a3 ~ (t~ y) + D T i=1
i=1
i=1
where Z = crop yield (q/ha); A o , a~, a2, a3 and D (- constants); y = any climatic variable within any given 7-day period; t~ = the number of each of the 7-day periods (it is 1 for the period from May 21--27 and 24 for the period from Oct. 29 to Nov. 4); n = 24 7-day periods in a given season of the year; T = year number (beginning with one in 1961 and ending with twelve in 1972) which was included to correct for the long term upward or downward trend in yield. Since the data on relative humidity were in percentages and were not normally distributed, the data were, therefore, transformed into arc-sine root proportion and then subjected to analysis. RESULTS AND DISCUSSION
To elucidate the effect of climate on rice yield, the distribution of climatic variables during the rice growing season is discussed first and then its effect on rice yield.
2200
1800
E 140C E z
!ooc z
60C
2ooh
Fig.2. T o t a l r a i n f a l l f o r d i f f e r e n t y e a r s .
76
Distribution o f clima tic variables Rainfall. The total rainfall for d i f f e r e n t years indicates t h a t t h o u g h the average rainfall for Pantnagar is 1,500 ram, the total a m o u n t o f rainfall m a y f l u c t u a t e f r o m 790 m m to 2,100 m m f r o m y e a r to year (Fig.2). The first good showers o f rain are received in the third week o f May. The average w e e k l y total rainfall distribution for each 7-day period during the rice growing season shows an increasing t r e n d in the rainfall f r o m May 21 to July I (Fig.3). During this period the rainfall received varied f r o m 8.7 m m 140~ 130i
8
II
l~oL
Q 90-
~ 30i
2 X1AY
3 JUNE
JULY
AUG
I
17 SEPT
24
1
8
15 22 29 OCT
Fig.3. Average total rainfall and evaporation for each S-day period, May 21 -- November 4. to 61.0 m m . It may, h o w e v e r , be as high as 211 m m ( J u n e 18--24, 1962). July to August 26 is the peak m o n s o o n period. During this period the rainfall m a y vary f r o m 67 m m to 135 m m and it m a y be as high as 107 m m ( O c t o b e r
1--7, 1968). From Fig.3 it is apparent that the period ranging from the last week of June to the third week of September is of low water deficit, because evapotranspiration losses are low and rainfall is high. This period appears to be highly conducive for good vegetative growth; M a x i m u m and m i n i m u m daily temperature. The average m a x i m u m daily t e m p e r a t u r e during the rice growing season varied f r o m 30 ° t o 40°C, and the m i n i m u m f r o m 13 ° t o 25 ° C. The distribution o f average m a x i m u m and minim u m daily t e m p e r a t u r e s for each 7-day period during the rice growing season shows a decreasing m a x i m u m t e m p e r a t u r e and rising m i n i m u m t e m p e r a t u r e
77 during the period from May 21 to June 24 (Fig.4). The average maximum temperature may vary from 36 ° to 40°C but it may be as high as 43°C (May 21--27, 1969) and the minimum may vary from 21 ° to 25°C.
r.
~, M A X I M U M
DAILY
TEMPERATURE
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TEMPERATURE
MINIMUM
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16
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-JULY
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Fig.4. Average m a x i m u m a n d m i n i m u m daily t e m p e r a t u r e for each 7-day period, May 21 - - N o v e m b e r 4.
The period covering June 25 to September 30 is characterized by stable maximum and minimum temperatures. During this period the maximum temperature varied.between 32 ° and 34°C and it may be 29°C (August 27--September 2, 1962) while the minimum temperature varied between 24 ° and 25°C. During the period of October 1 to November 4, the maximum temperature may vary a little while the minimum temperature decreased rapidly. Maximum and minimum daily relative humidity. The average maximum daily relative humidity during the rice growing season varied from 57 to 92%, and the minimum from 26 to 75%. The distribution of average maximum and minimum daily relative humidity for each 7-day period during the rice growing season shows that both values register rapid increase from May 21 to June 24 (Fig.5). During this period the maximum relative humidity may increase from 57 to 78% and the minimum relative humidity from 26 to 53%. The maximum and minimum relative humidity are stabilized during the period of June 25 to August 26, i.e., during the peak monsoon period. During this period the maximum relative humidity varied from 80 to 92% and minimum relative humidity from 60 to 75%. During the period of August 27 to November 4 there was a slight decrease
78 in maximum relative humidity but the minimum relative humidity decreased sharply. During this period the maximum relative humidity decreased from 90 to 84% while minimum relative humidity decreased from 55 to 43%.
E f f e c t o f climatic variables on rice yield The weekly total rainfall, weekly average maximum and minimum daily temperatures, and maximum and minimum daily relative humidity of 24 weeks of the rice growing season and the rice yield for 12 years, i.e. from 1961 to 1972, were analysed. The multiple regression equations were obtained for different climatic parameters. g6[_
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Fig.5. Average maximum and minimum daily relative humidity for each S-day period, May 21 -- November 4.
E f f e c t o f rainfall distribution. The multiple regression equation obtained for rainfall was: 24
24
Z = 19.405499 + 0.00332357 ~ t°yl - 0.0007246248 ~ t]yl i=1
i=1
24
+ 0.0000019906 ~ t~y~ + 1.799578 T i= 1
The coefficient of determination (R 2 ) obtained was 0.7952 which was found to be significant at 2.5% level.
79 During the establishment phase, the average weekly total rainfall varied from 8.7 to 40.5 mm. Therefore, if the total a m o u n t of rainfall received in each week during this period excepting the fifth week was 1 m m more than the average, the beneficial effect of rainfall on rice yield was observed. This was 260 g/ha during the first week covering May 21--27 (Fig.6). This effect decreased in the following weeks and was 188 gm, 117 gm and 46 gm per hectare during the second, third and fourth week, respectively, During the fifth week, however, the increase in weekly total rainfall by 1 mm m ore than the average reduced the yield. On the contrary, the reverse was true if the weekly total rainfall was 1 mm less than the average i.e., adverse effect of decreasing rainfall was observed. +O3
~O1
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~jUNE
. . 2. . g 8 25 \--
16
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Fig.6. Effect of I mm of rainfall above average weekly total rainfall on rice yield for each 7-day period, May 21 -- November 4. During the growth phase, the average weekly total rainfall varied from 35.0 to 134.6 mm. The heavy rainfall received in each week during this period is more than sufficient to meet the growth requirements of the crop. Further increase in weekly total rainfall may be of no use, but the excess water may adversely affect the crop. Therefore, the reduction in yield was observed during this period if the weekly total rainfall was 1 mm m ore than the average. The reduction in yield was 95 g/ha during the sixth week and 165 g/ha during the 7th week. The same was 441 g/ha during the 11th week (maximum tillering stage), 710 g/ha during the 15th week (ear-initiation
80
stage), and 972 g/ha during the ] 9 t h week. On the contrary the reverse was true, i.e., beneficial effect was observed if the weekly total rainfall was 1 mm less than the average. During the maturity phase, the average weekly total rainfall varied from 17.4 to 0.0 mm. The ripening phase requires clear sunny days and increased sunshine hours. Heavy showers during this period may cause a great damage to the crop. It may also delay the harvesting operation. Therefore, if the weekly total rainfall during this phase was 1 mm more than the average, the adverse effect on yield was observed. This was of the order of 1.04 kg/ha during the 20th week, 1.10 kg/ha during the 21st week and 1.29 kg/ha during the 24th week. On the contrary, the reverse was true if the weekly total rainfall was 1 mm less than the average. E f f e c t o f m a x i m u m daily temperature. The multiple regression equation obtained for maximum daily temperature was: 24
24
Z = 95.46937 + 0.2068969 ~ t°y2 - 0.06046426 ~ t])'2 i=1
i
i
24
+ 0 . 0 0 2 1 4 4 8 9 3 ~ t~y2 + 2.021593 T i=1
The coefficient of determination (R 2 ) obtained was 0.7855 and it was found to be significant at 2.5% level. During the establishment phase, the average m axi m um daily temperature decreased from 39.5 ° to 36.4 ° C. Because of this decreasing temperature trend the beneficial effect of temperature was observed in the first three weeks and the adverse effect in the last two weeks (Fig.7). The beneficial
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Fig.7. E f f e c t o f 1~C above the average m a x i m u m daily t e m p e r a t u r e o n rice yield for each 7-day period, May 21 - - N o v e m b e r 4.
81 effect was of the order of 14.8 kg/ha during the first week while the adverse effect was 4.180 kg/ha during the 5th week, if the maximum daily temperature was l°C more than the average. The reverse was true if maximum daily temperature was I°C less than the average. The higher temperature helped in better establishment of the crop. During the growth phase, the average maximum daily temperature varied between 32 ° and 34°C. Since the optimal temperature for tillering is 32 ~ -34°C (Kondo and Okamura, 1936), further increase in maximum daily temperature during this phase by 1°C more than the average had an adverse effect on yield. This was as high as 20.0 kg/ha during the maximum tillering stage, 21.8 kg/ha during the ear-initiation stage and 16.8 kg/ha during the flowering stage. The beneficial effect was obtained if the maximum daily temperature was I°C less than the average. During the maturity phase, the average maximum daily temperature decreased from 32 ° to 29°C. If the maximum daily temperature was 1°C more than the average, the adverse effect on yield reduction was observed. This was 14.4 kg/ha during the 20th week and only 0.879 kg/ha during the 24th week. Effect of minimum daily temperature. The multiple regression equation obtained for minimum daily temperature was: 24
24
Z = 76.41432 + 0.1267232 ~ tiy3 o - 0.02699649 ~ t~y3 z=l
i=1
24
+ 0 . 0 0 0 3 9 7 5 8 5 4 ~ t~y3 +1.747374T i=1
The coefficient of determination (R 2 ) obtained was 0.8023 and it was found to be significant at 2.5% level. During the establishment phase, the average minimum daily temperature varied from 21.1 ° to 24.7°C. If the minimum daily temperature during this period was 1°C more than the average, the beneficial effect on yield was observed (Fig.8). This was 10.012 kg/ha during the first week and decreased to 0.168 kg/ha during the 5th week. During the growth phase, the average minimum daily temperature varied from 24 ° to 21.9°C. If there was an increase in minimum daily temperature during this phase by 1°C more than the average, the adverse effect on yield was observed. It appears (Vamadevan, 1974) that higher minimum temperature at vegetative stage is found to have a significant negative role in determining yield even for the high yielding dwarf indicas. The results showed that the adverse effect due to increase in the minimum daily temperature was 12.2 kg/ha during the maximum tillering stage, 18.9 kg/ha during the ear-initiation stage and 24.3 kg/ha during the flowering stage. During the maturity phase, the average minimum daily temperature
82 +12
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17
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Fig.8. Effect of I°C above the average minimum daily temperature on rice yield for each 7-day period, May 21 -- November 4. decreased f r o m 19.6 ° to 12.8°C. If the m i n i m u m daily t e m p e r a t u r e during this phase was I ° C m o r e than the average, the r e d u c t i o n in yield was observed. This was up t o 29.22 k g / h a during the 2 4 t h week. Effect o f maximum daily relative humidity. The multiple regression e q u a t i o n o b t a i n e d for m a x i m u m daily relative h u m i d i t y was: 24
Z = 64.171637 + 0.01483521 ~
24
t~y4 - 0 . 0 0 6 4 5 0 2 0 5 ~ t~y4
i=l
i=1
24
+ 0.0001709098 ~
t~y4 + 1 . 8 5 5 8 9 7 T
i=l
The c o e f f i c i e n t o f d e t e r m i n a t i o n (R 2 ) o b t a i n e d was 0 . 7 8 3 3 and it was f o u n d to be significant at 2.5% level. During the e s t a b l i s h m e n t phase, the average m a x i m u m daily relative h u m i d i t y varied f r o m 57 to 78%. During the first t w o weeks, if the m a x i m u m daily relative h u m i d i t y was 1% m o r e than the average, a slight beneficial e f f e c t on yield was observed (Fig.9). But the increase in m a x i m u m daily relative h u m i d i t y b y 1% t h a n the average r e d u c e d the yield during the rest o f the weeks o f this period. During the growth phase, the average m a x i m u m daily relative h u m i d i t y varied f r o m 84 to 92%. If there was an increase in m a x i m u m daily relative h u m i d i t y during this phase b y i per cent than the average, the r e d u c t i o n in
83
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9
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16 JULY
213
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7
.
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10 ~SEPT
.17 .
.
24
.1 . ~
8
15 OCT
22
~
29
oOB
v o 16 d
w _U24 _z :2 U ~4o 44
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a
48
Fig.9. Effect of 1% of relative humidity above the average maximum daily relative humidity o n r i c e y i e l d f o r e a c h 7 - d a y p e r i o d , M a y 21 -- November 4.
yield was observed. This was 3.5 kg/ha during the maximum tillering stage and 4.4 kg/ha during the ear-initiation stage and 4.6 kg/ha during the flowering stage. During the maturity phase, the average maximum daily relative humidity varied from 84 to 87%. Therefore, with the increase in maximum daily relative humidity during the period by 1% more than the average, the adverse effect on yield was observed. This was of the order of 4.6 kg/ha during the 20th week, and 4.2 kg/ha during the 24th week. Similarly, the reverse effect is observed on rice yield at a decrease of 1% below average maximum daily relative humidity. Effect o f m i n i m u m daily relative humidity. The multiple regression equation obtained for minimum daily relative humidity was: 24
Z =- 14.788064 + 0.002536192 ~
24
t°ys - 0 . 0 0 1 3 3 8 1 0 5 ~ t]ys
i=1
i=1
24
+ 0 . 0 0 0 0 2 1 4 0 6 4 2 t~ys + 1 . 7 6 5 0 4 5 T i=1 The coefficient of determination (R 2 ) obtained was 0 . 7 5 4 6 and it was found to be significant at 5% level.
84 During the establishment phase, the average minimum daily relative humidity increased from 26 to 53%. The increase in minimum daily relative humidity had slight beneficial effect during the first week and adverse effect during the rest of this period (Fig.10). Like temperature, increased humidity, during the early stages of the establishment phase helped in increasing the growth and establishment of the crop.
+04 +02~
~ ~2~
z
18L
Fig. 10. E f f e c t o f 1% o f relative h u m i d i t y above the average m i n i m u m daily relative humi-
dity on rice yield for each 7-day period, May 21 - - N o v e m b e r 4.
During the growth phase, the average minimum daily relative humidity varied from 55 to 75%. If there was an increase in minimum daily relative humidity during this phase by 1% more than the average, an adverse effect on yield was observed. This was only 0.96 kg/ha during the maximum tillering stage, 1.3 kg/ha during the ear-initiation stage and 1.5 kg/ha during the flowering stage. High humidity in tropics, particularly during the rainy season is likely to affect the plant growth by reducing the transpirational cooling of the plant. The lowering of the yield with the increase in maximum and minimum daily relative humidity may be related to this effect. This hypothesis is further supported by the fact that low humidity is one of the important agrometeorological environmental factors for maximum rice production (DeDatta and Zarate, 1970). During the maturity phase, the average minimum daily relative humidity decreased from 54 to 43%. If the minimum daily relative humidity during this phase was 1% more than the average, an adverse effect on yield was observed. This was of the order of 1.57 kg/ha during the 24th week.
85
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¢, ACTUAL YIELD
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~ .....
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° V
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PREDCTED
YIELD
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Fig.11. Aetual and predicted yield for different years, using the regression equation for rainfall effects on rice yield. On the c o n t r a r y , if t h e m i n i m u m daily relative h u m i d i t y during m a t u r i t y phase was 1% less t h a n the average the reverse e f f e c t on yield was o b s e r v e d . T h e increase in yield with low relative h u m i d i t y c o n f i r m s the earlier observ a t i o n (Ghildyal and Jana, 1967) t h a t a low relative h u m i d i t y a r o u n d 43% during t h e grain f o r m a t i o n stage, and a t e m p e r a t u r e o f 12°--13°C are considered to be c o n d u c i v e to increased rice yield. This s t u d y shows a close r e l a t i o n s h i p b e t w e e n the m o n s o o n rice c r o p and w e e k l y climatic variables. A s e c o n d - d e g r e e m u l t i p l e regression e q u a t i o n can p r o f i t a b l y be e m p l o y e d in q u a n t i f y i n g these relationships. If the d i s t r i b u t i o n of climatic p a r a m e t e r s is k n o w n , the yield t r e n d can be p r e d i c t e d f o r d i f f e r e n t years. By using the regression e q u a t i o n o b t a i n e d for effects of rainfall on rice yield, the p r e d i c t e d and actual rice yield for d i f f e r e n t years f r o m 1961 to 1 9 7 2 are s h o w n in F i g . l l .
REFERENCES Best, R., 1962. Production factors in the tropics. Neth. J. Agri., 10: 347--353. De-Datta, S. K. and Zarate, P. M., 1970. Biometeorological problems in developing countries. Biometeorology, 4: 71--89. Fisher, R. A., 1924. The influence of rainfall on the yield of wheat at Rothamsted. R. Soc. (Lond.). Phil. Trans., Ser. B, 213: 89--142. Ghildyal, B. P. and Jana, R. K., 1967. Agrometeorological environment affecting rice yield. Agron. J., 59: 286--287.
86 Hendricks, W. A. and Scholl, J. C., 1943. Techniques in measuring joint relationship. The joint effects of temperature and precipitation on crop yield. N. Carolina Agric. Exp. Sta. Tech. Bull., 74. Kondo, M. and Okamura, T., 1936. Relation of water, temperature and growth in rice, II. NogaKukenkyu, 17: 37--64. Ram Dayal, 1965. Impact of rainfall on crop yield and average. 1. J.A.E., 20: 48--55. Runge, E. C. A., 1968. Effects of rainfall and temperature interactions during the growing season on crop yield. Agron. J., 60: 503--507. Stacy, S. V., Steamson, O., Jones, L. S. and Foreman, J., 1957. Joint effects of maximum temperatures and rainfall on crop yields. Agron. J., 49: 26--28. Tanaka, A., Kawano, K. and Yamaguchi, J., 1966. Photosynthesis, respiration and plant types of the tropical rice plant. Int. Rice Res. Inst., Los Banos, Laguna, Philippines, Tech. Bull., 7: 46. Vamadevan, V. K., 1974. Studies on water use and soil--water--plant climate relationships in rice. Paper presented at the International Rice Research Conference, April 22--25, 1974.