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Relationships between climatic factors and flower and boll production in Egyptian cotton (Gossypium barbadense)
Journal of Arid Environments (2002) 52: 499–516 doi:10.1006/jare.2002.1012, available online at http://www.idealibrary.com on
Relationships between climatic factors and flower and boll production in Egyptian cotton (Gossypium barbadense)
Z. M. Sawan%*, L. I. Hannaw, Gh. A. Gad El Karimz & W. L McCuistion} %
Cotton Research Institute, Agricultural Research Center, Ministry of Agriculture & Land Reclamation, 9 Gamaa Street, 12619 Giza Egypt wCentral Laboratory for Design and Statistical Analysis Research, Agricultural Research Center, Ministry of Agriculture & Land Reclamation, 9 Gamaa Street, 12619 Giza Egypt z Agricultural Genetic Engineering Research Institute, Agricultural Research Center, Ministry of Agriculture & Land Reclamation, 9 Gamau Street, 12619 Giza, Egypt }National Agricultural Research Project (Received 6 March 2001, accepted 27 February 2002) Fruiting of cotton plant is determined and influenced by cultivar, climatic conditions, management practices and pests. An understanding of the flowering and boll retention patterns of cotton cultivars can contribute to more efficient and economical crop management. The objective of this investigation was to study the effect of various climatic factors on flower and boll production of Egyptian cotton. This could be used in formulating advanced predictions of the effect of certain climatic conditions on the production of Egyptian cotton. Two uniform field trials, using cotton Gossypium barbadense cv. Giza 75 were carried out in 1992 and 1993 at the Agricultural Research Station, Agricultural Research Center, Ministry of Agriculture, Giza, Egypt, to investigate the relationships between climatic factors, flower and boll production. Climatic factors included maximum and minimum air temperatures along with their difference, evaporation, surface soil temperature (grass temperature or green cover temperature) at 0600 and 1800 h1C1, sunshine duration, maximum and minimum humidity and wind speed. The effects of climatic factors on flower and boll production were quantified in the absence of water and nutritional deficits and damage effects of insects. Results obtained indicate that evaporation, sunshine duration, humidity, surface soil temperature at 1800 h, and maximum air temperature, were the important climatic factors that significantly affect flower and boll production of Egyptian cotton. Consequently, applying appropriate specific cultural practices that minimize the deleterious effect of these factors will lead to an improvement in cotton yield. # 2002 Elsevier Science Ltd. *Corresponding author. Fax: +202 7613 183. E-mail: [email protected] 0140-1963/02/040499 + 18 $35.00/0
# 2002 Elsevier Science Ltd.
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Keywords: boll retention; cotton flower; evaporation; humidity; sunshine duration; temperature
Introduction Cotton yield is determined by boll weight and the number of bolls produced per plant, which is influenced by flowering rate and boll retention. Therefore, it is important to study the effect of climatic factors and their correlation with flowers and bolls produced per plant, to determine the most important effects of these factors on increasing or decreasing cotton production and their magnitudes. In fact, information on the impact of climatic factors on cotton production is not sufficiently available in the required form. Thus, an understanding of these impacts may help physiologists to determine the control mechanism of flowering in plants. Temperature is a primary climatic factor affecting cotton growth. Burke et al. (1988) has defined the optimum temperature range for biochemical and metabolic activities of plants (a temperature range that permits normal enzyme functions in plants) as the thermal kinetic window (TKW). Plant temperatures above or below the TKW result in stress, that limits growth and yield. The TKW for cotton growth is 23?5–321C, with an optimum temperature of 281C. Biomass production is directly related to the amount of time that foliage temperatures are within the TKW. Productivity of cotton, therefore, is influenced strongly by the relationship between plant TKW and the temperatures the crop experiences during the growing season. Fisher (1975) found that high temperatures can cause male sterility in cotton (upland cotton) flowers, and increase boll shedding late in the fruiting season. Cool temperatures are a major limitation on cotton productivity (Gipson, 1986; Ramey, 1986; Winter & Koniger, 1991). Gipson & Joham (1968) reported that cool temperatures (o201C) at night hinder boll (Gossypium hirsutum) development. Bhatt (1977) found that over 14 h of daylength and high day temperatures, singly or in combination, delayed flowering of the upland cotton J34. Reddy et al. (1992) found that the number of bolls (upland cotton) produced, bolls retained, and per cent retention were progressively reduced as the time per day that the canopy temperature was 401C increased. Three weeks exposure to 401C for 2 or 12 h day1 resulted in 64% or 0% bolls retained on the plant, respectively. El-Zik (1980) stated that many factors, such as length of the growing season, climate (including solar radiation, temperature, light, wind, rainfall, and dew), variety, availability of nutrients and soil moisture, pests and cultural practices affect cotton growth. The balance between vegetative and reproductive development can be influenced by soil fertility, soil moisture, cloudy weather, spacing and perhaps other factors such as temperature and humidity (Guinn, 1982). In Texas, Guo et al. (1994) found that plant growth and yield of the cotton cv. DPL50 (upland cotton), were less in a humid area than in an arid area with low humidity. Under arid conditions, high vapour pressure deficit resulted in high transpiration rates, low leaf water potential and lower leaf temperatures. Reddy et al. (1995a), in growth chamber experiments found that Pima cotton cv. S-6 produced less total biomass at 35?5 than at 26?91C and no bolls were produced at 401C. Miller et al. (1996) ran multiple regressions between rainfall, temperature and yield data gathered from 1968–92 and found that in most cases less than 50% of the yield variation for non-irrigated cotton can be explained by a combination of weather factors. The other 50% of yield variation is subject to management. Because the climatic factors are largely uncontrolled, the variables that influence flower and boll production must be quantitatively evaluated if we want to explain
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adequately the effects of any climatic variable on cotton flower and boll production. So it is important to determine the most important climatic factors on increasing or decreasing cotton production and its magnitude. The knowledge of the impact of climatic factors on cotton production is not generally available, or at least not available in the required form. So understanding of the impact may help the physiologist to determine possible control of flowering mechanism in cotton plant. The objective of this investigation was to study the effect of various climatic factors on the overall flower and boll production in Egyptian cotton. This could pave the way for formulating advanced predictions as to the effect of certain climatic conditions on production of Egyptian cotton. It would be useful to minimize the deleterious effects of the factors through utilizing proper cultural practices which would limit and control their negative effects, and this will lead to an improvement in cotton yield. We tested the hypothesis that an understanding of the relationships between climatic factors, flowering and boll-retention patterns of the cotton plant may allow a direct external intervention that can help cotton growth and production.
Materials and methods Two uniform field trials were conducted in 1992 and 1993 at the Agricultural Research Station, Agricultural Research Center, Ministry of Agriculture, Giza (301N, 311280 E), Egypt, on the cotton cultivar ‘Giza 75’ (Gossypium barbadense L.). The soil type was clay loam with an alluvial substratum. The following tabulation shows the mechanical and chemical analysis of the soil.
Mechanical analysis Clay (%) Silt (%) Fine sand (%) Coarse sand (%) Texture Chemical analysis Organic matter (%) Calcium carbonate (%) pH (1:2?5) Available nitrogen (mg kg soil1) Available phosphorus (mg kg soil1) Available potassium (mg kg soil1)
Season 1
Season 2
45 27 19 4 Clay loam
39 27 27 2 Clay loam
2 3 8?0 34 14 300
2 3 8?1 57 19 310
Consumptive use of water by surface irrigation during the growing season, was about 6000 m3 h1. The criterion used for watering the crop depending on soil water status is irrigating when soil water content reached nearly 35% of field capacity (0– 60 cm). The normal cotton cultivation techniques in Egypt were followed (AbdelSalam, 1999). Each trial plot contained 13–15 rows to facilitate proper surface irrigation. Rows were 60 cm apart and 4 m long. Seeds were sown on 15 and 23 March in 1992 and 1993, respectively, in hills 20 cm apart on one side of the row and were thinned to 2 plants hill1 6 weeks after planting, providing plant density of 166,000 plants ha1. Phosphorus fertilizer was applied at the rate of 54 kg P2O5 ha1
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as calcium superphosphate, with land preparation. Potassium fertilizer was applied at the rate of 57 kg K2O/ha1 in the form of potassium sulphate before the first irrigation (as a concentrated band close to the seed row). Nitrogen fertilizer was applied (in the form of pinches beside each hill) at the rate of 144 kg N ha1 as ammonium nitrate with lime (calcium ammonium nitrate) in two equal amounts, i.e. after thinning and before the second irrigation and the next amount was before the third irrigation. These amounts were determined based on the use of soil test guidelines. Soon after thinning, 261 and 358 plants were randomly selected out of 9 and 11 middle rows of a plot with 13 and 15 rows in the first and second seasons, respectively. Pest control management was carried out on an-as-needed basis, according to local practices at the experimental station. The flowers of selected plants were tagged for establishing flowering, fruit-setting or shedding. The flowering season commenced on the opening date of the first flower and, thereafter, the opened flowers on all plants were tagged daily until the end of flowering (31 August) to give opened bolls (50 days old) at the end of picking (20 October). Each flower was tagged according to its opening date on the selected plants. In order to calculate fruit parameters, the following were counted from the data collected (used as dependent variables): (i) daily number of tagged flowers in each day in all selected plants; (ii) number of retained bolls, obtained from the total of each daily tagged flowers in all selected plants at harvest (Figs 1 and 2). In 1992, the flowering period was from 17 June to 31 August (after this date the flowers would not produce mature bolls). The field was irrigated on 15 March (at planting), 8 April (first irrigation), 29 April, 17 May, 31 May, 14 June, 1 July, 16 July and 12 August. In 1993, the flowering period was from 21 June to 31 August. The field was irrigated on 23 March (planting date), 20 April (first irrigation), 8 May, 22 May, 1 June, 18 June, 3 July, 20 July, 7 August and 28 August. As a rule, observations were recorded when the number of flowers on a given day was at least 5 flowers found for a population of 100 plants and this continued for at
Average number of flowers and bolls per plant
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Figure 1. Daily number of flowers and bolls during the first season (sampling size = 261 plants).
Average number of flowers and bolls per plant
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Figure 2. Daily number of flowers and bolls during the second season (sampling size = 358 plants).
least 5 consecutive days. This rule omitted 8 observations in the first season and 10 observations in the second season. So the number of observations (n) was 68 (23 June–29 August) and 62 (29 June–29 August) for the two seasons, respectively. The climatic factors used (independent variables) considered were daily data of maximum air temperature 1C [X1], minimum air temperature 1C [X2], maximum– minimum temperature 1C (temperature magnitude) [X3], evaporation expressed as Piche evap. mm day1 [X4], surface soil temperature 1C (grass temperature or green cover temperature) at 0600 [X5] and 1800 h [X6] sunshine duration h day1 [X7], maximum humidity % [X8] and minimum humidity % [X9] and wind speed m s1 [X10], (in the second season only). The maximum and minimum air temperatures were measured using mercury and alcohol thermometers which were freely exposed in the louvered screens with their bulbs at a height of 160 cms above the ground. Evaporation measurements were taken once daily at 0600 h giving the evaporation readings for the previous 24 h. The evaporation readings were measured by a Piche tube which was freely exposed in sloping double-roofed louvred screens. The evaporation disc has an effective area of 10?1 cm2 having a white colour, and placed at a height of 150 cm, above the ground. Surface soil temperatures were taken regularly in the dry and grass-covered fields at 0600 and 1800 h for the 0?0 cm depth. The surface grass thermometers were used. The actual duration of bright sunshine of the day is the daily calculated periods between sunrise and sunset. The duration of bright sunshine was measured by the Campbell–Stokes sunshine recorders which were suitably exposed. The relative humidity (%) was derived from the dry- and wet-bulb thermometer readings using Jellink’s Psychrometer Tables. No corrections for wind speed or atmospheric pressure were applied. The elements used in preparing the climatological data of surface wind were the routine observations of the surface wind taken at the principal synoptic hours 0600, 1200 and 1800 h. The instrument used is cup-anemometer; its head was freely exposed and erected at 2 m height above the ground. The daily mean surface wind speed was the arithmetic mean of the surface wind speed observations at the three principal synoptic hours. All the climatic factors were measured according to the methodological directions adopted by the World Meteorology Organization (WMO). The source of the climatic data was the Agricultural Meteorological Station of the Agricultural Research Station, Agricultural Research Center, Giza, Egypt. No rainfall occurred during the two growing seasons.
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Table 1. Range and mean values of the independent variables (climatic factors) recorded during the production stage
First season Climatic factors Max temp (1C) Min temp (1C) Max–min temp (1C) Evapor (mm/day1) 0600 h temp (1C) 1800 h temp (1C) Sunshine (h day1) Max hum (%) Min hum (%) Wind speed (m s1)
(X1) (X2) (X3) (X4) (X5) (X6) (X7) (X8) (X9) (X10)
Second season
Overall data (two seasons)
Range
Mean
Range
Mean
Range
Mean
31?0–44?0 18?6–24?5 9?4–20?9 7?6–16?4 14?0–21?5 19?6–32?3 10?3–12?9 62–96 11–45 ND
34?3 21?9 12?4 10?2 17?9 24?2 11?7 85?4 30?8 ND
30?6–38?8 18?4–23?9 8?5–17?6 4?1–9?8 13?3–22?4 20?6–27?4 9?7–13?0 51–84 23–52 2?2–7?8
34?1 21?8 12?2 5?9 18?1 24?1 11?9 73?2 39?8 4?6
30?6–44?0 18?4–24?5 8?5–20?9 4?1–16?4 13?3–22?4 19?6–32?3 9?7–13?0 51–96 11–52 ND
34?2 21?8 12?3 8?2 18?0 24?2 11?8 79?6 35?1 ND
ND not determined.
The range and mean values of the climatological factors (independent variables) recorded during the production stage for the two seasons and overall data are listed in Table 1. Daily number of flowers and number of bolls per plant which survived to maturity (dependent variables) during the production stage in the two seasons are graphically illustrated in Figs 1 and 2. Statistical analysis Simple correlations between the initial group of independent variables (climatic factors; X ’s) and the corresponding dependent variables (Y ’s), were computed for each season and the data of the two seasons combined. The a-level for significance was pr0?05. The independent variables attaining the determined level of significance ( pr0?05), which are expected to be the important variables affecting the dependent variables, were selected and combined with the dependent variables sin multiple regression analysis using a stepwise technique to obtain a convenient predictive equation. Multiple correlation coefficients (r ’s) and coefficients of determination (r2’s) were calculated to measure the success of regression equations in explaining the variation in the dependent variables. Correlation and regression analyses were computed according to Draper & Smith (1966), by means of the computer programs SAS (1985) package.
Results Correlation estimates Results of simple correlation coefficients between the initial group of independent variables and each of flower and boll production in the first, and second seasons and the combined data of the two seasons are shown in Table 2. The simple correlation values indicate clearly that evaporation seems to be the most important climatic factor as it showed the highest correlation value. Also, this factor had a significant negative relationship with flower and boll production.
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Table 2. Simple correlation values for the relationships between the independent variables and the studied dependent variable Independent variables (climatic factors)
Dependent variable First season
Max temp (1C) Min temp (1C) Max–min temp (1C) Evapor (mm/day1) 0600 h temp (1C) 1800 h temp (1C) Sunshine (h/day1) Max hum (%) Min hum (%) Wind speed (m s1)
(X1) (X2) (X3) (X4) (X5) (X6) (X7) (X8) (X9) (X10)
Second season
Combined data
Flower
Boll
Flower
Boll
Flower
Boll
0?07 0?06 0?03 0?56** 0?01 0?20 0?25* 0?40** 0?14 ND
0?03 0?07 0?01 0?53** 0?06 0?16 0?14 0?37** 0?10 ND
0?42** 0?00 0?36** 0?61** 0?14 0?37** 0?37** 0?01 0?45** 0?06
0?42** 0?02 0?37** 0?59** 0?13 0?36** 0?36** 0?01 0?46** 0?04
0?27** 0?03 0?25** 0?40** 0?09 0?27** 0?31** 0?04 0?33** ND
0?26** 0?02 0?24** 0?48** 0?09 0?25** 0?25** 0?06 0?39** ND
ND not determined. *po0?05; **po0?01
Sunshine duration showed a significant negative relation with fruit production except for boll production in the first season, which was not significant. Maximum air temperature, temperature magnitude, and surface soil temperature at 1800 h, were also negatively correlated with flower and boll production in the second season and the combined data of the two seasons. Minimum humidity in the second season, the combined data of the two seasons, and maximum humidity in the first season were positively and highly correlated with flower and boll production. Minimum air temperature and surface soil temperature at 0600 h showed low and insignificant correlation to flower and boll production. Multiple linear regression equation By means of the multiple linear regression analyses, fitting predictive equations (having good fit) were computed for flower and boll production per plant using selected significant factors from the nine climatic variables studied in this investigation. Wind speed evaluated during the second season had no influence on the dependent variables. The equations obtained for each of the two dependent variables, i.e. number of flowers (Y1) and bolls per plant (Y2) in each season and for the combined data from the two seasons are as follows: First season (n = 68) Y1 = 21?6911?968 X40?241 X7 + 0?216 X8, r = 0?608** and r2 = 0?3697, while r2 for all studied variables was 0?4022 (Table 3). Y2 = 15?434 1?633 X4 + 0?159 X8, r = 0?589** and r2 = 0?3469 and r2 for all studied variables was 0?3843 (Table 3). Second season (n = 62) Y1 = 77?436 0?163 X1 – 2?861 X4 1?178 X7 + 0?269 X9, r = 0?644**, r2 = 0?4147 Y2 = 66?281 0?227X1 3?315X4 2?897X7 + 0?196X9, r = 0?629**, r2 = 0?3956. In addition, r2 for all studied variables was 0?4503 and 0?4287 for Y1 and Y2 equations, respectively (Table 3).
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Table 3. Selected factors and their relative contribution to variations of flower and boll production
Selected factors
Flower production *RC (%)
Boll production *RC (%)
First Second Combined First Second Combined season season data season season data Max temp (1C) Evapor (mm day1) 1800 h temp (1C) Sunshine (h day1) Max hum (%) Min hum (%) wr2% for selected factors r2% for factors studied r2% for factors deleted
(X1) F 5?92 (X4) 19?08 23?45 F F (X6) (X7) 9?43 7?77 F (X8) 8?46 F 4?37 (X9) 36?97 41?47 40?22 45?03 3?25 3?56
F 16?06 5?83 8?31 F 7?38 37?58 40?73 3?15
F 5?03 23?04 22?39 F F 11?65 7?88 F F F 4?26 34?69 39?56 38?43 42?87 3?74 3?31
F 22?89 2?52 5?47 F 4?64 35?52 37?90 2?38
*RC% = Relative contribution of each of the selected independent variables to variations of the dependent variable. w 2 r % = Coefficient of determination in percentage form.
Combined data for the two seasons: (n = 130) Y1 = 68?143 0?827 X4 1?190 X6 2?718 X7 + 0?512 X9, r = 0?613**, r2 = 0?3758. Y2 = 52?785 0?997 X4 0?836 X6 1?675 X7 + 0?426 X9, r = 0?569**, r2 = 0?3552, while r2 for all studied variables was 0?4073 for Y1 and 0?3790 for Y2. Three climatic factors, i.e. minimum air temperature, surface soil temperature at 0600 h, and wind speed were not included in the equations since they had very little effect on production of cotton flowers and bolls. Contribution of selected climatic factors to variations in the dependent variable Relative contributions (RC%) for each of the selected climatic factors to variation in flower and boll production are measured and summarized in Table 3. Results in this table indicate that evaporation was the most important climatic factor affecting flower and boll production in Egyptian cotton. Sunshine duration is the second climatic factor of importance affecting production of flowers and bolls. Humidity and temperature at 1800 h were contributing factors but less than evaporation and sunshine duration day1. Maximum temperature made a contribution but less than the other affecting factors. Discussion Correlation estimates The negative relationship between evaporation with flower and boll production, means that high evaporation rate reduces significantly cotton flower and boll production. This may be due to greater plant water deficits when evaporation increases.
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Also, the negative relation between each of maximum temperature, temperature magnitude, soil surface temperature at 1800 h, or sunshine duration, with flower and boll production revealed that the increase in the values of these factors had a detrimental effect upon Egyptian cotton fruit production. On the other hand, there was a positive correlation between each of maximum or minimum humidity with flower and boll production. Results obtained from the production stage of each season individually, and the combined data of the two seasons, indicated that relationships of some climatic variables with the dependent variables varied markedly from one season to another. This may be due to the differences between climatic factors in the two seasons as illustrated by the ranges and means shown in Table 1. For example, maximum temperature, minimum humidity and surface soil temperature at 1800 h did not show significant relations in the first season, while that trend differed in the second season. The effect of maximum humidity varied markedly from the first season to the second. While it was significantly correlated with the dependent variables in the first season, the inverse pattern was true in the second season. This diverse effect may be due to the differences in the mean values of this factor in the two seasons; where as it was, on average, about 86% in the first season, it was about 72% on average in the second season, as shown in Table 1. Boll retention ratio [(The number of retained bolls obtained from the total number of each daily tagged flowers in all selected plants at harvest/total number of daily tagged flowers of all selected plants) 100] curve for each of the two seasons was made (Figs 3 and 4). Also, relationships between boll retention ratio curves and the studied climatic factors were presented in Figs 5–15, to indicate the effect of meteorological events on fruit retention. Furthermore, these curves describe why the shapes and patterns associated with the flower and boll curves for 1992 and 1993 were different. It seems reasonable that the climatic data that were collected in these two experiments (1992 and 1993) could provide adequate information for describing how these two seasons differed and how the crop responded accordingly. These results indicate that evaporation was the most effective and consistent climatic factor affecting boll production. As the sign of the relationship was negative, this means that an increase in evaporation would cause a significant reduction in boll number. Thus, applying specific treatments such as an additional irrigation, and use of plant growth regulators, which would decrease the deleterious effect of evaporation
Boll retention ratio (%)
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Figure 3. Boll retention ratio during flowering period of the first season.
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Boll retention ratio (%)
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Figure 4. Boll retention ratio during flowering period of the second season.
after boll formation and hence contribute to an increase in cotton boll production and retention, and the result is an increase in cotton yield. In this connection, Moseley et al. (1994) stated that methanol has been reported to increase water-use efficiency, growth and development of C3 plants in arid conditions, under intense sunlight. In field trials cotton cv. DPL-50 (G. hirsutum) was sprayed with a nutrient solution (1?33 lb N + 0?27 lb Fe + 0?27 lb Zn acre1) or 30% methanol solution at a rate of 20 gal acre1, or sprayed with both the nutrient solution and methanol under two soil moisture regimes (irrigated and dry land). The foliar spray treatments were applied 6 times during the growing season beginning at first bloom. They found that irrigation (a total of 4?5 in applied in July) increased lint yield across foliar spray treatments by 18%. Zhao & Oosterhuis (1997) found that in a growth chamber when cotton
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Figure 5. Relation between boll retention ratio and air temperature during flowering period of the first season.
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Days after begining of flowering Figure 6. Relation between boll retention ratio and air temperature during flowering period of the second season.
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(G. hirsutum cv. Stoneville 506) plants were treated with the plant growth regulator PGR-IV (gibberellic acid, IBA and a proprietary fermentation broth) under waterdeficit stress they had significantly high dryer weights of roots and floral buds than the untreated water-stressed plants. They concluded that PGR-IV can partially alleviate the detrimental effects of water stress on photosynthesis and DM accumulation and improve the growth and nutrient absorption of growth chamber-grown cotton plants. Meek et al. (1999) in a field experiment in Arkansas, found that application of 3 or
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Figure 7. Relation between boll retention ratio and evaporation (Piche) during flowering period of the first season.
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Figure 8. Relation between boll retention ratio and evaporation (Piche) during flowering period of the second season.
6 kg glycine betaine (PGR) ha1, to cotton plants has the potential to increase yield in cotton exposed to mild water stress. Multiple linear regression equation The sign of the partial regression coefficient for an independent variable (climatic factor) indicates its effect on the production value of the dependent variable (flowers
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Figure 9. Relation between boll retention ratio and surface soil temperature of the first season.
CLIMATIC FACTORS AND FLOWER AND BOLL PRODUCTION
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Figure 10. Relation between boll retention ratio and surface soil temperature of the second season.
or bolls). The positive value of the partial regression coefficient is interpreted as meaning that the higher the rate of the variable, the higher is the expected value of the production variable, and the inverse is also true. This means that high rates of humidity and/or low values of evaporation will increase fruit production. Contribution of selected climatic factors to variations in the dependent variable Evaporation showed the highest contribution to variation in both flower and boll production. This finding can, however, be explained in the light of results found by Boll retention ratio (%) Sunshine duration (h d–1)
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Figure 11. Relation between boll retention ratio and sunshine duration in the first season.
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Boll retention ratio (%)–1 Sunshine duration (h d )
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Figure 12. Relation between boll retention ratio and sunshine duration in the second season.
Ward & Bunce (1986) in sunflower (Helianthus annuus). They stated that decreases of humidity at both leaf surfaces, reduced photosynthetic rate of the whole leaf for plants grown under a moderate temperature and medium light level. Kaur & Singh (1992) found in cotton that flower number was decreased by water stress, particularly when applied at flowering. Seed cotton yield was about halved by water stress applied at flowering, slightly decreased by stress at boll formation, and not significantly affected
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Figure 13. Relation between boll retention ratio and humidity during flowering period in the first season.
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Figure 14. Relation between boll retention ratio and humidity during flowering period in the second season.
by stress in the vegetative stage (6–7 weeks after sowing). Orgaz et al. (1992) in field experiments at Cordoba, SW Spain, grew cotton cultivars Acala SJ-C1, GC-510, Coker-310 and Jean cultivar at evapo-transpiration (ET) levels ranging from 40 to 100% of maximum ET (ETmax) which were generated with sprinkler line irrigation. The water production function of Jean cultivar was linear; seed yield was 5?30 t ha1 at ETmax (820 mm). In contrast, the production function of the three other cultivars was linear up to 85% of ETmax, but levelled off as ET approached ETmax (830 mm) Boll retention ratio (%)
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because a fraction of the set bolls did not open by harvest at high ET levels. These authors concluded that it is possible to define an optimum ET deficit for cotton based on cultivar earliness, growing-season length, and availability of irrigation water. The negative relationship between sunshine duration and cotton production may be due to the fact that the species of Gossypium spp. used is known to be a short-day plant (Hearn & Constable, 1984). So, an increase of sunshine duration than needed for cotton plant growth will decrease flower and boll production. Bhatt (1977) found that, exposure to day light over 14 h and high day temperature, individually or in combination, delayed flowering of the upland cotton J 34. However, several workers referred to the effect of climatic factors on cotton flower and boll production and in turn yield. Mergeai & Demol (1991) in phytotron trials in Belgium found that cotton yield was favoured by intermediate relative humidity (60%) and temperatures of 24–281C. Long photoperiods (16 h) and low night temperature (121C) increased vegetative growth and cotton yields, but under short photoperiods (12 h) yields were better with a higher night temperature (161C). Reddy et al. (1991) found that the number of fruiting sites per plant increased linearly as temperature increased to 30/221C (day/night temperature regimes), but declined by over 50% at 35/271C. Plants grown at 40/321C did not produce reproductive structures during the entire 64 days after emergence (DAE) period. Optimum temperature for reproductive growth in Pima cotton in terms of number of fruiting branches, length and nodes per branch was 30/221C, and this was also the optimum temperature for flower bud and boll production and retention. Vegetative growth increases at temperatures above 30/221C, these increasing main stem height and leaf area at nodes initiated higher on the main stem. More flower buds and bolls were aborted at 35/271C than at the optimum, or lower temperature. Plants grown at 40/321C remained vegetative during the 64 DAE period. These results emphasize the need for heat-tolerant cultivars in today’s cotton production environments. Heattolerant cultivars will be even more essential in the future, as global warming increases. Hodges et al. (1993) found that cotton (G. hirsutum) fruit retention decreased rapidly as the time of exposure to 401C increased. Warner & Burke (1993) indicated that the cool-night inhibition of cotton (G. hirsutum) growth is correlated with biochemical limitation on starch mobilization in source leaves, which results in a secondary inhibition of photosynthesis, even under optimal temperature during the day. Wang & Whisler (1994) reported that data of weather observations near the geographic centre of the Mississippi River Delta, have been converted into GOSSYM (a cotton crop simulation model) format. They indicated that in each year (1965– 1992), from 1 April through 31 December, each week’s daily average, maximum, and minimum temperature, solar radiation, rainfall, and wind run were calculated. The averages of each week for the entire 28-year period were also calculated, as were the deviations from average for each specific week in each year. They found that climatic factors resulting in maximum cotton yield at Mississippi were: maximum temperature was 1% (below the average); minimum temperature was 0–5% (above the average); solar radiation was 10% (below the average); wind speed was 10% or +25% (below or above the average) and rainfall was +1 in (above the average). Reddy et al. (1995b) observed that when cotton cv. DPL-50 plants grown in growth chambers were exposed for 70 days to natural light levels with average temperature of 17?81C, 18?71C, 22?71C, 26?61C or 30?61C, number of squares and bolls produced were increased with increased temperature up to 30?61C. Zhen Jin Zhong (1995) found that the most important factors decreasing cotton yield in Huangchuan County, Henan, were low temperatures in spring, high temperatures and pressure during summer and the sudden fall in temperature at the beginning of autumn. Measures to increase yield included the use of the more suitable high-oil cotton cultivars, which mature early, and choosing sowing dates and spacing which would maximize the utilization of light and temperature. Reddy et al.
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(1996) observed that when cotton cv. DPL-51 (upland cotton) was grown in controlled environments with natural solar radiation, flower and fruit retention was very low at an ambient temperature from 31?31C to 331C plus 5 or 71C. It was concluded that cotton will be severely damaged by temperatures above those presently observed during midsummer in the cotton belt in U.S.A. Also, they concluded that the grower could minimize boll abscission where high temperature and low humidity occur by growing heat-tolerant cultivars, proper management of planting date, adequate fertilization, optimum plant density, and applying suitable irrigation regime which would avoid drought stress. Oosterhuis (1997) studied the reasons for low and variable cotton yields in Arkansas, with unusually high insect pressures and the development of the boll load during an exceptionally hot and dry August. Solutions to the problems are suggested, which are selection of tolerant cultivars, effective and timely insect and weed control, adequate irrigation regime, use of proper cropmonitoring techniques and application of plant growth regulators.
Conclusion Results obtained from this study indicate that evaporation, sunshine duration, humidity, surface soil temperature at 1800 h, and maximum temperature, were the most significant climatic factors affecting flower and boll production of Egyptian cotton. Nevertheless, it could be stated that during the production stage, an accurate weather forecast for the next 5–7 days would provide an opportunity to avoid any adverse effects of climatic factors on cotton production. It would be useful to minimize the deleterious effects of those factors through utilizing proper cultural practices which would limit and control their negative effects, and this will lead to an improvement in cotton yield.
References Abdel-Salam, M.E. (1999). The Egyptian Cotton, pp 109–159. Giza, Egypt: ElKalema Press. 488 pp. Bhatt, J.G. (1977). Growth and flowering of cotton (Gossypium hirsutum L.) as affected by daylength and temperature. Journal of Agricultural Science, 89: 583–588. Burke, J.J., Mahan, J.R. & Hatfield, J.L. (1988). Crop specific thermal kinetic windows in relation to wheat and cotton biomass production. Agronomic Journal, 80: 553–556. Draper, N.R. & Smith, H. (1966). Applied Regression Analysis. New York: John Wiley and Sons, Inc. 407 pp. El-Zik, K.M. (1980). The cotton plant F its growth and development. Western Cotton Production Conference Summary Proceedings, pp. 18–21, Fresno, CA. Fisher, W.D. (1975). Heat induced sterility in Upland cotton. Proceedings of the 27th Cotton Improvement Conference 85. Gipson, J.R. (1986). Temperature effects on growth, development and fiber properties In: Mauney, J.R. & Stewart, J.M. (Eds), Cotton Physiology, pp. 47–56. Memphis, TN: Cotton Foundation. Gipson, L.R. & Joham, H.E. (1968). Influence of night temperature on growth and development of cotton (Gossypium hirsutum L.): I. Fruiting and boll development. Agronomy Journal, 60: 292–295. Guinn, G. (1982). Causes of square and boll shedding in cotton. USDA Technical Bulletin 1672. Guo, Y., Landivar, J.A., Hanggeler, J.C. & Moore, J. (1994). Response of cotton leaf water potential and transpiration to vapor pressure deficit and salinity under arid and humid climate conditions. In: Proceedings Beltwide Cotton Conferences, pp. 1301–1308, January 5-8, San Diego, CA, U.S.A. Memphis, U.S.A. National Cotton Council. 1751 pp.
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Hearn, A.B. & Constable, G.A. (1984). Cotton. In: Goldsworth, P.R. & Fisher, N.M. (Eds). The Physiology of Tropical Food Crops, Chapter 14, p. 495 NY: John Wiley & Sons Ltd. 664 pp. Hodges, H.F., Reddy, K.R., McKinion, J.M. & Reddy, V.R. (1993). Temperature effects on cotton. Bulletin of Mississippi Agricutltural Forestry Experimental Station, 990: 15. Kaur, R. & Singh, O.S. (1992). Response of growth stages of cotton varieties to moisture stress. Indian Journal of Plant Physiology, 35: 182–185. Meek, C.R., Oosterhuis, D.M. & Steger, A.T. (1999). Drought tolerance and foliar sprays of glycine betaine. In: Proceedings Beltwide Cotton Conferences, pp. 559–561. January 3–7, Orlando, FL, U.S.A. Memphis, U.S.A.: National Cotton Council. 1423 pp. Mergeai, G. & Demol, J. (1991). Contribution to the study of the effect of various meteorological factors on production and quality of cotton (Gossypium hirsutum L.) fibers. Bulletin des Recherches Agronomiqued de Gembloux, 26: 113–124. Miller, J.K., Krieg, D.R. & Paterson, R.E. (1996). Relationship between dryland cotton yields and weather parameters on the Southern Hig Plains. In: Proceedings Beltwide Cotton Conferences, pp. 1165–1166, January 9–12, Nashville, TN, U.S.A. Memphis, U.S.A.: National Cotton Council. 1684 pp. Moseley, D., Landivar, J.A. & Locke, D. 1994. Evaluation of the effect of methanol on cotton growth and yield under dry-land and irrigated conditions. In Proceedings Beltwide Cotton Conferences, pp. 1293–1294. January 5–8, San Diego, CA, U.S.A. Memphis, U.S.A.: National Cotton Council. 1751 pp. Oosterhuis, D.M. (1997). Effect of temperature extremes on cotton yields in Arkansas. In: Oosterhuis, D.M. & Stewart, J.M. (Eds) Proceedings of the Cotton Research Meeting, No. 183, pp. 94–98, Monticello, AR, U.S.A., February 13, Special Report–Agricultural Experiment Station, Division of Agriculture, University of Arkansas. Orgaz, F., Mateos, L. & Fereres, E. (1992). Season length and cultivar determine the optimum evapotranspiration deficit in cotton. Agronomy Journal, 84: 700–706. Ramey, H.H. (1986). Stress influence on fiber development. In: Mauney, J.R. and Stewart, J.M. (Ed.), Cotton Physiology, Memphis, TN: Cotton Foundation. pp. 351–360. Reddy, K.R., Hodges, H.F. & McKinion, J.M. (1995a). Carbon dioxide and temperature effects on pima cotton growth. Agriculture Ecosystems and Environment, 54: 17–29. Reddy, K.R., Hodges, H.F. & McKinion, J.M., 1996. Can cotton crops be sustained in future climates? In Proceedings Beltwide Cotton Conferences, pp. 1189–1196, January 9–12, Nashville, TN, U.S.A.: Memphis, U.S.A.: National Cotton Council. 1684 pp. Reddy, K.R., Hodges, H.F. & Reddy, V.R. (1992). Temperature effects on cotton fruit retention. Agronomy Journal, 84: 26–30. Reddy, K.R., McKinion, J.M., Wall, G.W., Bhattacharya, N.C., Hodges, H.F. & Bhattacharya, S. (1991). Effect of temperature on Pima growth and development. In Proceeding Beltwide Cotton Conferences, pp. 841, January 9–12, San Antonio, TX, U.S.A.: Memphis, U.S.A.: National Cotton Council. 1031 pp. Reddy, V.R., Reddy, K.R. & Acock, B. (1995b). Carbon dioxide and temperature interactions on stem extension, node initiation, and fruiting in cotton. Agriculture Ecosystems and Environment, 55: 17–28. SAS Institute Inc. (1985). SAS Users Guide: Statistics (5th Edn). Cary, NC: SAS Inst, Inc. 956 pp. Wang, X. & Whisler, F.D. (1994). Analyses of the effects of weather factors on predicted cotton growth and yield. Bulletin Mississippi Agricultural Forestry Experimental Station, 1014: 51. Ward, D.A. & Bunce, J.A. (1986). Responses of net photosynthesis and conductance to independent changes in the humidity environments of the upper and lower surfaces of leaves of sunflower and soybean. Journal of Experimental Botany, 37: 1842–1853. Warner, D.A. & Burke, J.J. (1993). Cool night temperature alter leaf starch and photosystem II Chlorophyll fluorescence in cotton. Agronomy Journal 85: 836–840. Winter, K. & Koniger, M. (1991). Dry matter production and photosynthetic capacity in Gossypium hirsutum L. under conditions of slightly sub-optimal leaf temperatures and high levels of irradiance. Oecologia, 87: 190–197. Zhao Du Li & Oosterhuis, D. (1997). Physiological response of growth chamber-grown cotton plants to the plant growth regulator PGR-IV under water-deficit stress. Environmental and Experimental Botany, 38: 7–14. Zhen Jin Zhong (1995). The causes of low cotton production in Huanghchuan County and measures to increase production. Henan Nongye Kexue, 2: 5–6.
Relationships between climatic factors and flower and boll production in Egyptian cotton (Gossypium barbadense)
Z. M. Sawan%*, L. I. Hannaw, Gh. A. Gad El Karimz & W. L McCuistion} %
Cotton Research Institute, Agricultural Research Center, Ministry of Agriculture & Land Reclamation, 9 Gamaa Street, 12619 Giza Egypt wCentral Laboratory for Design and Statistical Analysis Research, Agricultural Research Center, Ministry of Agriculture & Land Reclamation, 9 Gamaa Street, 12619 Giza Egypt z Agricultural Genetic Engineering Research Institute, Agricultural Research Center, Ministry of Agriculture & Land Reclamation, 9 Gamau Street, 12619 Giza, Egypt }National Agricultural Research Project (Received 6 March 2001, accepted 27 February 2002) Fruiting of cotton plant is determined and influenced by cultivar, climatic conditions, management practices and pests. An understanding of the flowering and boll retention patterns of cotton cultivars can contribute to more efficient and economical crop management. The objective of this investigation was to study the effect of various climatic factors on flower and boll production of Egyptian cotton. This could be used in formulating advanced predictions of the effect of certain climatic conditions on the production of Egyptian cotton. Two uniform field trials, using cotton Gossypium barbadense cv. Giza 75 were carried out in 1992 and 1993 at the Agricultural Research Station, Agricultural Research Center, Ministry of Agriculture, Giza, Egypt, to investigate the relationships between climatic factors, flower and boll production. Climatic factors included maximum and minimum air temperatures along with their difference, evaporation, surface soil temperature (grass temperature or green cover temperature) at 0600 and 1800 h1C1, sunshine duration, maximum and minimum humidity and wind speed. The effects of climatic factors on flower and boll production were quantified in the absence of water and nutritional deficits and damage effects of insects. Results obtained indicate that evaporation, sunshine duration, humidity, surface soil temperature at 1800 h, and maximum air temperature, were the important climatic factors that significantly affect flower and boll production of Egyptian cotton. Consequently, applying appropriate specific cultural practices that minimize the deleterious effect of these factors will lead to an improvement in cotton yield. # 2002 Elsevier Science Ltd. *Corresponding author. Fax: +202 7613 183. E-mail: [email protected] 0140-1963/02/040499 + 18 $35.00/0
# 2002 Elsevier Science Ltd.
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Keywords: boll retention; cotton flower; evaporation; humidity; sunshine duration; temperature
Introduction Cotton yield is determined by boll weight and the number of bolls produced per plant, which is influenced by flowering rate and boll retention. Therefore, it is important to study the effect of climatic factors and their correlation with flowers and bolls produced per plant, to determine the most important effects of these factors on increasing or decreasing cotton production and their magnitudes. In fact, information on the impact of climatic factors on cotton production is not sufficiently available in the required form. Thus, an understanding of these impacts may help physiologists to determine the control mechanism of flowering in plants. Temperature is a primary climatic factor affecting cotton growth. Burke et al. (1988) has defined the optimum temperature range for biochemical and metabolic activities of plants (a temperature range that permits normal enzyme functions in plants) as the thermal kinetic window (TKW). Plant temperatures above or below the TKW result in stress, that limits growth and yield. The TKW for cotton growth is 23?5–321C, with an optimum temperature of 281C. Biomass production is directly related to the amount of time that foliage temperatures are within the TKW. Productivity of cotton, therefore, is influenced strongly by the relationship between plant TKW and the temperatures the crop experiences during the growing season. Fisher (1975) found that high temperatures can cause male sterility in cotton (upland cotton) flowers, and increase boll shedding late in the fruiting season. Cool temperatures are a major limitation on cotton productivity (Gipson, 1986; Ramey, 1986; Winter & Koniger, 1991). Gipson & Joham (1968) reported that cool temperatures (o201C) at night hinder boll (Gossypium hirsutum) development. Bhatt (1977) found that over 14 h of daylength and high day temperatures, singly or in combination, delayed flowering of the upland cotton J34. Reddy et al. (1992) found that the number of bolls (upland cotton) produced, bolls retained, and per cent retention were progressively reduced as the time per day that the canopy temperature was 401C increased. Three weeks exposure to 401C for 2 or 12 h day1 resulted in 64% or 0% bolls retained on the plant, respectively. El-Zik (1980) stated that many factors, such as length of the growing season, climate (including solar radiation, temperature, light, wind, rainfall, and dew), variety, availability of nutrients and soil moisture, pests and cultural practices affect cotton growth. The balance between vegetative and reproductive development can be influenced by soil fertility, soil moisture, cloudy weather, spacing and perhaps other factors such as temperature and humidity (Guinn, 1982). In Texas, Guo et al. (1994) found that plant growth and yield of the cotton cv. DPL50 (upland cotton), were less in a humid area than in an arid area with low humidity. Under arid conditions, high vapour pressure deficit resulted in high transpiration rates, low leaf water potential and lower leaf temperatures. Reddy et al. (1995a), in growth chamber experiments found that Pima cotton cv. S-6 produced less total biomass at 35?5 than at 26?91C and no bolls were produced at 401C. Miller et al. (1996) ran multiple regressions between rainfall, temperature and yield data gathered from 1968–92 and found that in most cases less than 50% of the yield variation for non-irrigated cotton can be explained by a combination of weather factors. The other 50% of yield variation is subject to management. Because the climatic factors are largely uncontrolled, the variables that influence flower and boll production must be quantitatively evaluated if we want to explain
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adequately the effects of any climatic variable on cotton flower and boll production. So it is important to determine the most important climatic factors on increasing or decreasing cotton production and its magnitude. The knowledge of the impact of climatic factors on cotton production is not generally available, or at least not available in the required form. So understanding of the impact may help the physiologist to determine possible control of flowering mechanism in cotton plant. The objective of this investigation was to study the effect of various climatic factors on the overall flower and boll production in Egyptian cotton. This could pave the way for formulating advanced predictions as to the effect of certain climatic conditions on production of Egyptian cotton. It would be useful to minimize the deleterious effects of the factors through utilizing proper cultural practices which would limit and control their negative effects, and this will lead to an improvement in cotton yield. We tested the hypothesis that an understanding of the relationships between climatic factors, flowering and boll-retention patterns of the cotton plant may allow a direct external intervention that can help cotton growth and production.
Materials and methods Two uniform field trials were conducted in 1992 and 1993 at the Agricultural Research Station, Agricultural Research Center, Ministry of Agriculture, Giza (301N, 311280 E), Egypt, on the cotton cultivar ‘Giza 75’ (Gossypium barbadense L.). The soil type was clay loam with an alluvial substratum. The following tabulation shows the mechanical and chemical analysis of the soil.
Mechanical analysis Clay (%) Silt (%) Fine sand (%) Coarse sand (%) Texture Chemical analysis Organic matter (%) Calcium carbonate (%) pH (1:2?5) Available nitrogen (mg kg soil1) Available phosphorus (mg kg soil1) Available potassium (mg kg soil1)
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Season 2
45 27 19 4 Clay loam
39 27 27 2 Clay loam
2 3 8?0 34 14 300
2 3 8?1 57 19 310
Consumptive use of water by surface irrigation during the growing season, was about 6000 m3 h1. The criterion used for watering the crop depending on soil water status is irrigating when soil water content reached nearly 35% of field capacity (0– 60 cm). The normal cotton cultivation techniques in Egypt were followed (AbdelSalam, 1999). Each trial plot contained 13–15 rows to facilitate proper surface irrigation. Rows were 60 cm apart and 4 m long. Seeds were sown on 15 and 23 March in 1992 and 1993, respectively, in hills 20 cm apart on one side of the row and were thinned to 2 plants hill1 6 weeks after planting, providing plant density of 166,000 plants ha1. Phosphorus fertilizer was applied at the rate of 54 kg P2O5 ha1
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as calcium superphosphate, with land preparation. Potassium fertilizer was applied at the rate of 57 kg K2O/ha1 in the form of potassium sulphate before the first irrigation (as a concentrated band close to the seed row). Nitrogen fertilizer was applied (in the form of pinches beside each hill) at the rate of 144 kg N ha1 as ammonium nitrate with lime (calcium ammonium nitrate) in two equal amounts, i.e. after thinning and before the second irrigation and the next amount was before the third irrigation. These amounts were determined based on the use of soil test guidelines. Soon after thinning, 261 and 358 plants were randomly selected out of 9 and 11 middle rows of a plot with 13 and 15 rows in the first and second seasons, respectively. Pest control management was carried out on an-as-needed basis, according to local practices at the experimental station. The flowers of selected plants were tagged for establishing flowering, fruit-setting or shedding. The flowering season commenced on the opening date of the first flower and, thereafter, the opened flowers on all plants were tagged daily until the end of flowering (31 August) to give opened bolls (50 days old) at the end of picking (20 October). Each flower was tagged according to its opening date on the selected plants. In order to calculate fruit parameters, the following were counted from the data collected (used as dependent variables): (i) daily number of tagged flowers in each day in all selected plants; (ii) number of retained bolls, obtained from the total of each daily tagged flowers in all selected plants at harvest (Figs 1 and 2). In 1992, the flowering period was from 17 June to 31 August (after this date the flowers would not produce mature bolls). The field was irrigated on 15 March (at planting), 8 April (first irrigation), 29 April, 17 May, 31 May, 14 June, 1 July, 16 July and 12 August. In 1993, the flowering period was from 21 June to 31 August. The field was irrigated on 23 March (planting date), 20 April (first irrigation), 8 May, 22 May, 1 June, 18 June, 3 July, 20 July, 7 August and 28 August. As a rule, observations were recorded when the number of flowers on a given day was at least 5 flowers found for a population of 100 plants and this continued for at
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Figure 1. Daily number of flowers and bolls during the first season (sampling size = 261 plants).
Average number of flowers and bolls per plant
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Figure 2. Daily number of flowers and bolls during the second season (sampling size = 358 plants).
least 5 consecutive days. This rule omitted 8 observations in the first season and 10 observations in the second season. So the number of observations (n) was 68 (23 June–29 August) and 62 (29 June–29 August) for the two seasons, respectively. The climatic factors used (independent variables) considered were daily data of maximum air temperature 1C [X1], minimum air temperature 1C [X2], maximum– minimum temperature 1C (temperature magnitude) [X3], evaporation expressed as Piche evap. mm day1 [X4], surface soil temperature 1C (grass temperature or green cover temperature) at 0600 [X5] and 1800 h [X6] sunshine duration h day1 [X7], maximum humidity % [X8] and minimum humidity % [X9] and wind speed m s1 [X10], (in the second season only). The maximum and minimum air temperatures were measured using mercury and alcohol thermometers which were freely exposed in the louvered screens with their bulbs at a height of 160 cms above the ground. Evaporation measurements were taken once daily at 0600 h giving the evaporation readings for the previous 24 h. The evaporation readings were measured by a Piche tube which was freely exposed in sloping double-roofed louvred screens. The evaporation disc has an effective area of 10?1 cm2 having a white colour, and placed at a height of 150 cm, above the ground. Surface soil temperatures were taken regularly in the dry and grass-covered fields at 0600 and 1800 h for the 0?0 cm depth. The surface grass thermometers were used. The actual duration of bright sunshine of the day is the daily calculated periods between sunrise and sunset. The duration of bright sunshine was measured by the Campbell–Stokes sunshine recorders which were suitably exposed. The relative humidity (%) was derived from the dry- and wet-bulb thermometer readings using Jellink’s Psychrometer Tables. No corrections for wind speed or atmospheric pressure were applied. The elements used in preparing the climatological data of surface wind were the routine observations of the surface wind taken at the principal synoptic hours 0600, 1200 and 1800 h. The instrument used is cup-anemometer; its head was freely exposed and erected at 2 m height above the ground. The daily mean surface wind speed was the arithmetic mean of the surface wind speed observations at the three principal synoptic hours. All the climatic factors were measured according to the methodological directions adopted by the World Meteorology Organization (WMO). The source of the climatic data was the Agricultural Meteorological Station of the Agricultural Research Station, Agricultural Research Center, Giza, Egypt. No rainfall occurred during the two growing seasons.
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Table 1. Range and mean values of the independent variables (climatic factors) recorded during the production stage
First season Climatic factors Max temp (1C) Min temp (1C) Max–min temp (1C) Evapor (mm/day1) 0600 h temp (1C) 1800 h temp (1C) Sunshine (h day1) Max hum (%) Min hum (%) Wind speed (m s1)
(X1) (X2) (X3) (X4) (X5) (X6) (X7) (X8) (X9) (X10)
Second season
Overall data (two seasons)
Range
Mean
Range
Mean
Range
Mean
31?0–44?0 18?6–24?5 9?4–20?9 7?6–16?4 14?0–21?5 19?6–32?3 10?3–12?9 62–96 11–45 ND
34?3 21?9 12?4 10?2 17?9 24?2 11?7 85?4 30?8 ND
30?6–38?8 18?4–23?9 8?5–17?6 4?1–9?8 13?3–22?4 20?6–27?4 9?7–13?0 51–84 23–52 2?2–7?8
34?1 21?8 12?2 5?9 18?1 24?1 11?9 73?2 39?8 4?6
30?6–44?0 18?4–24?5 8?5–20?9 4?1–16?4 13?3–22?4 19?6–32?3 9?7–13?0 51–96 11–52 ND
34?2 21?8 12?3 8?2 18?0 24?2 11?8 79?6 35?1 ND
ND not determined.
The range and mean values of the climatological factors (independent variables) recorded during the production stage for the two seasons and overall data are listed in Table 1. Daily number of flowers and number of bolls per plant which survived to maturity (dependent variables) during the production stage in the two seasons are graphically illustrated in Figs 1 and 2. Statistical analysis Simple correlations between the initial group of independent variables (climatic factors; X ’s) and the corresponding dependent variables (Y ’s), were computed for each season and the data of the two seasons combined. The a-level for significance was pr0?05. The independent variables attaining the determined level of significance ( pr0?05), which are expected to be the important variables affecting the dependent variables, were selected and combined with the dependent variables sin multiple regression analysis using a stepwise technique to obtain a convenient predictive equation. Multiple correlation coefficients (r ’s) and coefficients of determination (r2’s) were calculated to measure the success of regression equations in explaining the variation in the dependent variables. Correlation and regression analyses were computed according to Draper & Smith (1966), by means of the computer programs SAS (1985) package.
Results Correlation estimates Results of simple correlation coefficients between the initial group of independent variables and each of flower and boll production in the first, and second seasons and the combined data of the two seasons are shown in Table 2. The simple correlation values indicate clearly that evaporation seems to be the most important climatic factor as it showed the highest correlation value. Also, this factor had a significant negative relationship with flower and boll production.
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Table 2. Simple correlation values for the relationships between the independent variables and the studied dependent variable Independent variables (climatic factors)
Dependent variable First season
Max temp (1C) Min temp (1C) Max–min temp (1C) Evapor (mm/day1) 0600 h temp (1C) 1800 h temp (1C) Sunshine (h/day1) Max hum (%) Min hum (%) Wind speed (m s1)
(X1) (X2) (X3) (X4) (X5) (X6) (X7) (X8) (X9) (X10)
Second season
Combined data
Flower
Boll
Flower
Boll
Flower
Boll
0?07 0?06 0?03 0?56** 0?01 0?20 0?25* 0?40** 0?14 ND
0?03 0?07 0?01 0?53** 0?06 0?16 0?14 0?37** 0?10 ND
0?42** 0?00 0?36** 0?61** 0?14 0?37** 0?37** 0?01 0?45** 0?06
0?42** 0?02 0?37** 0?59** 0?13 0?36** 0?36** 0?01 0?46** 0?04
0?27** 0?03 0?25** 0?40** 0?09 0?27** 0?31** 0?04 0?33** ND
0?26** 0?02 0?24** 0?48** 0?09 0?25** 0?25** 0?06 0?39** ND
ND not determined. *po0?05; **po0?01
Sunshine duration showed a significant negative relation with fruit production except for boll production in the first season, which was not significant. Maximum air temperature, temperature magnitude, and surface soil temperature at 1800 h, were also negatively correlated with flower and boll production in the second season and the combined data of the two seasons. Minimum humidity in the second season, the combined data of the two seasons, and maximum humidity in the first season were positively and highly correlated with flower and boll production. Minimum air temperature and surface soil temperature at 0600 h showed low and insignificant correlation to flower and boll production. Multiple linear regression equation By means of the multiple linear regression analyses, fitting predictive equations (having good fit) were computed for flower and boll production per plant using selected significant factors from the nine climatic variables studied in this investigation. Wind speed evaluated during the second season had no influence on the dependent variables. The equations obtained for each of the two dependent variables, i.e. number of flowers (Y1) and bolls per plant (Y2) in each season and for the combined data from the two seasons are as follows: First season (n = 68) Y1 = 21?6911?968 X40?241 X7 + 0?216 X8, r = 0?608** and r2 = 0?3697, while r2 for all studied variables was 0?4022 (Table 3). Y2 = 15?434 1?633 X4 + 0?159 X8, r = 0?589** and r2 = 0?3469 and r2 for all studied variables was 0?3843 (Table 3). Second season (n = 62) Y1 = 77?436 0?163 X1 – 2?861 X4 1?178 X7 + 0?269 X9, r = 0?644**, r2 = 0?4147 Y2 = 66?281 0?227X1 3?315X4 2?897X7 + 0?196X9, r = 0?629**, r2 = 0?3956. In addition, r2 for all studied variables was 0?4503 and 0?4287 for Y1 and Y2 equations, respectively (Table 3).
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Table 3. Selected factors and their relative contribution to variations of flower and boll production
Selected factors
Flower production *RC (%)
Boll production *RC (%)
First Second Combined First Second Combined season season data season season data Max temp (1C) Evapor (mm day1) 1800 h temp (1C) Sunshine (h day1) Max hum (%) Min hum (%) wr2% for selected factors r2% for factors studied r2% for factors deleted
(X1) F 5?92 (X4) 19?08 23?45 F F (X6) (X7) 9?43 7?77 F (X8) 8?46 F 4?37 (X9) 36?97 41?47 40?22 45?03 3?25 3?56
F 16?06 5?83 8?31 F 7?38 37?58 40?73 3?15
F 5?03 23?04 22?39 F F 11?65 7?88 F F F 4?26 34?69 39?56 38?43 42?87 3?74 3?31
F 22?89 2?52 5?47 F 4?64 35?52 37?90 2?38
*RC% = Relative contribution of each of the selected independent variables to variations of the dependent variable. w 2 r % = Coefficient of determination in percentage form.
Combined data for the two seasons: (n = 130) Y1 = 68?143 0?827 X4 1?190 X6 2?718 X7 + 0?512 X9, r = 0?613**, r2 = 0?3758. Y2 = 52?785 0?997 X4 0?836 X6 1?675 X7 + 0?426 X9, r = 0?569**, r2 = 0?3552, while r2 for all studied variables was 0?4073 for Y1 and 0?3790 for Y2. Three climatic factors, i.e. minimum air temperature, surface soil temperature at 0600 h, and wind speed were not included in the equations since they had very little effect on production of cotton flowers and bolls. Contribution of selected climatic factors to variations in the dependent variable Relative contributions (RC%) for each of the selected climatic factors to variation in flower and boll production are measured and summarized in Table 3. Results in this table indicate that evaporation was the most important climatic factor affecting flower and boll production in Egyptian cotton. Sunshine duration is the second climatic factor of importance affecting production of flowers and bolls. Humidity and temperature at 1800 h were contributing factors but less than evaporation and sunshine duration day1. Maximum temperature made a contribution but less than the other affecting factors. Discussion Correlation estimates The negative relationship between evaporation with flower and boll production, means that high evaporation rate reduces significantly cotton flower and boll production. This may be due to greater plant water deficits when evaporation increases.
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Also, the negative relation between each of maximum temperature, temperature magnitude, soil surface temperature at 1800 h, or sunshine duration, with flower and boll production revealed that the increase in the values of these factors had a detrimental effect upon Egyptian cotton fruit production. On the other hand, there was a positive correlation between each of maximum or minimum humidity with flower and boll production. Results obtained from the production stage of each season individually, and the combined data of the two seasons, indicated that relationships of some climatic variables with the dependent variables varied markedly from one season to another. This may be due to the differences between climatic factors in the two seasons as illustrated by the ranges and means shown in Table 1. For example, maximum temperature, minimum humidity and surface soil temperature at 1800 h did not show significant relations in the first season, while that trend differed in the second season. The effect of maximum humidity varied markedly from the first season to the second. While it was significantly correlated with the dependent variables in the first season, the inverse pattern was true in the second season. This diverse effect may be due to the differences in the mean values of this factor in the two seasons; where as it was, on average, about 86% in the first season, it was about 72% on average in the second season, as shown in Table 1. Boll retention ratio [(The number of retained bolls obtained from the total number of each daily tagged flowers in all selected plants at harvest/total number of daily tagged flowers of all selected plants) 100] curve for each of the two seasons was made (Figs 3 and 4). Also, relationships between boll retention ratio curves and the studied climatic factors were presented in Figs 5–15, to indicate the effect of meteorological events on fruit retention. Furthermore, these curves describe why the shapes and patterns associated with the flower and boll curves for 1992 and 1993 were different. It seems reasonable that the climatic data that were collected in these two experiments (1992 and 1993) could provide adequate information for describing how these two seasons differed and how the crop responded accordingly. These results indicate that evaporation was the most effective and consistent climatic factor affecting boll production. As the sign of the relationship was negative, this means that an increase in evaporation would cause a significant reduction in boll number. Thus, applying specific treatments such as an additional irrigation, and use of plant growth regulators, which would decrease the deleterious effect of evaporation
Boll retention ratio (%)
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8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 Days after begining of flowering
Figure 3. Boll retention ratio during flowering period of the first season.
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Boll retention ratio (%)
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8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 Days after begining of flowering
Figure 4. Boll retention ratio during flowering period of the second season.
after boll formation and hence contribute to an increase in cotton boll production and retention, and the result is an increase in cotton yield. In this connection, Moseley et al. (1994) stated that methanol has been reported to increase water-use efficiency, growth and development of C3 plants in arid conditions, under intense sunlight. In field trials cotton cv. DPL-50 (G. hirsutum) was sprayed with a nutrient solution (1?33 lb N + 0?27 lb Fe + 0?27 lb Zn acre1) or 30% methanol solution at a rate of 20 gal acre1, or sprayed with both the nutrient solution and methanol under two soil moisture regimes (irrigated and dry land). The foliar spray treatments were applied 6 times during the growing season beginning at first bloom. They found that irrigation (a total of 4?5 in applied in July) increased lint yield across foliar spray treatments by 18%. Zhao & Oosterhuis (1997) found that in a growth chamber when cotton
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Days after begining of flowering
Figure 5. Relation between boll retention ratio and air temperature during flowering period of the first season.
CLIMATIC FACTORS AND FLOWER AND BOLL PRODUCTION
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Days after begining of flowering Figure 6. Relation between boll retention ratio and air temperature during flowering period of the second season.
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(G. hirsutum cv. Stoneville 506) plants were treated with the plant growth regulator PGR-IV (gibberellic acid, IBA and a proprietary fermentation broth) under waterdeficit stress they had significantly high dryer weights of roots and floral buds than the untreated water-stressed plants. They concluded that PGR-IV can partially alleviate the detrimental effects of water stress on photosynthesis and DM accumulation and improve the growth and nutrient absorption of growth chamber-grown cotton plants. Meek et al. (1999) in a field experiment in Arkansas, found that application of 3 or
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Figure 7. Relation between boll retention ratio and evaporation (Piche) during flowering period of the first season.
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Figure 8. Relation between boll retention ratio and evaporation (Piche) during flowering period of the second season.
6 kg glycine betaine (PGR) ha1, to cotton plants has the potential to increase yield in cotton exposed to mild water stress. Multiple linear regression equation The sign of the partial regression coefficient for an independent variable (climatic factor) indicates its effect on the production value of the dependent variable (flowers
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Figure 9. Relation between boll retention ratio and surface soil temperature of the first season.
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Figure 10. Relation between boll retention ratio and surface soil temperature of the second season.
or bolls). The positive value of the partial regression coefficient is interpreted as meaning that the higher the rate of the variable, the higher is the expected value of the production variable, and the inverse is also true. This means that high rates of humidity and/or low values of evaporation will increase fruit production. Contribution of selected climatic factors to variations in the dependent variable Evaporation showed the highest contribution to variation in both flower and boll production. This finding can, however, be explained in the light of results found by Boll retention ratio (%) Sunshine duration (h d–1)
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12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 Days after begining of flowering
Figure 11. Relation between boll retention ratio and sunshine duration in the first season.
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Boll retention ratio (%)–1 Sunshine duration (h d )
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Figure 12. Relation between boll retention ratio and sunshine duration in the second season.
Ward & Bunce (1986) in sunflower (Helianthus annuus). They stated that decreases of humidity at both leaf surfaces, reduced photosynthetic rate of the whole leaf for plants grown under a moderate temperature and medium light level. Kaur & Singh (1992) found in cotton that flower number was decreased by water stress, particularly when applied at flowering. Seed cotton yield was about halved by water stress applied at flowering, slightly decreased by stress at boll formation, and not significantly affected
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Figure 13. Relation between boll retention ratio and humidity during flowering period in the first season.
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Figure 14. Relation between boll retention ratio and humidity during flowering period in the second season.
by stress in the vegetative stage (6–7 weeks after sowing). Orgaz et al. (1992) in field experiments at Cordoba, SW Spain, grew cotton cultivars Acala SJ-C1, GC-510, Coker-310 and Jean cultivar at evapo-transpiration (ET) levels ranging from 40 to 100% of maximum ET (ETmax) which were generated with sprinkler line irrigation. The water production function of Jean cultivar was linear; seed yield was 5?30 t ha1 at ETmax (820 mm). In contrast, the production function of the three other cultivars was linear up to 85% of ETmax, but levelled off as ET approached ETmax (830 mm) Boll retention ratio (%)
Wind speed (ms–1) 15
100 90
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30 20
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10 0
0 0
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12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 Days after begining of flowering Figure 15. Relation between boll retention ratio and wind speed flowering period in the second season only.
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because a fraction of the set bolls did not open by harvest at high ET levels. These authors concluded that it is possible to define an optimum ET deficit for cotton based on cultivar earliness, growing-season length, and availability of irrigation water. The negative relationship between sunshine duration and cotton production may be due to the fact that the species of Gossypium spp. used is known to be a short-day plant (Hearn & Constable, 1984). So, an increase of sunshine duration than needed for cotton plant growth will decrease flower and boll production. Bhatt (1977) found that, exposure to day light over 14 h and high day temperature, individually or in combination, delayed flowering of the upland cotton J 34. However, several workers referred to the effect of climatic factors on cotton flower and boll production and in turn yield. Mergeai & Demol (1991) in phytotron trials in Belgium found that cotton yield was favoured by intermediate relative humidity (60%) and temperatures of 24–281C. Long photoperiods (16 h) and low night temperature (121C) increased vegetative growth and cotton yields, but under short photoperiods (12 h) yields were better with a higher night temperature (161C). Reddy et al. (1991) found that the number of fruiting sites per plant increased linearly as temperature increased to 30/221C (day/night temperature regimes), but declined by over 50% at 35/271C. Plants grown at 40/321C did not produce reproductive structures during the entire 64 days after emergence (DAE) period. Optimum temperature for reproductive growth in Pima cotton in terms of number of fruiting branches, length and nodes per branch was 30/221C, and this was also the optimum temperature for flower bud and boll production and retention. Vegetative growth increases at temperatures above 30/221C, these increasing main stem height and leaf area at nodes initiated higher on the main stem. More flower buds and bolls were aborted at 35/271C than at the optimum, or lower temperature. Plants grown at 40/321C remained vegetative during the 64 DAE period. These results emphasize the need for heat-tolerant cultivars in today’s cotton production environments. Heattolerant cultivars will be even more essential in the future, as global warming increases. Hodges et al. (1993) found that cotton (G. hirsutum) fruit retention decreased rapidly as the time of exposure to 401C increased. Warner & Burke (1993) indicated that the cool-night inhibition of cotton (G. hirsutum) growth is correlated with biochemical limitation on starch mobilization in source leaves, which results in a secondary inhibition of photosynthesis, even under optimal temperature during the day. Wang & Whisler (1994) reported that data of weather observations near the geographic centre of the Mississippi River Delta, have been converted into GOSSYM (a cotton crop simulation model) format. They indicated that in each year (1965– 1992), from 1 April through 31 December, each week’s daily average, maximum, and minimum temperature, solar radiation, rainfall, and wind run were calculated. The averages of each week for the entire 28-year period were also calculated, as were the deviations from average for each specific week in each year. They found that climatic factors resulting in maximum cotton yield at Mississippi were: maximum temperature was 1% (below the average); minimum temperature was 0–5% (above the average); solar radiation was 10% (below the average); wind speed was 10% or +25% (below or above the average) and rainfall was +1 in (above the average). Reddy et al. (1995b) observed that when cotton cv. DPL-50 plants grown in growth chambers were exposed for 70 days to natural light levels with average temperature of 17?81C, 18?71C, 22?71C, 26?61C or 30?61C, number of squares and bolls produced were increased with increased temperature up to 30?61C. Zhen Jin Zhong (1995) found that the most important factors decreasing cotton yield in Huangchuan County, Henan, were low temperatures in spring, high temperatures and pressure during summer and the sudden fall in temperature at the beginning of autumn. Measures to increase yield included the use of the more suitable high-oil cotton cultivars, which mature early, and choosing sowing dates and spacing which would maximize the utilization of light and temperature. Reddy et al.
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(1996) observed that when cotton cv. DPL-51 (upland cotton) was grown in controlled environments with natural solar radiation, flower and fruit retention was very low at an ambient temperature from 31?31C to 331C plus 5 or 71C. It was concluded that cotton will be severely damaged by temperatures above those presently observed during midsummer in the cotton belt in U.S.A. Also, they concluded that the grower could minimize boll abscission where high temperature and low humidity occur by growing heat-tolerant cultivars, proper management of planting date, adequate fertilization, optimum plant density, and applying suitable irrigation regime which would avoid drought stress. Oosterhuis (1997) studied the reasons for low and variable cotton yields in Arkansas, with unusually high insect pressures and the development of the boll load during an exceptionally hot and dry August. Solutions to the problems are suggested, which are selection of tolerant cultivars, effective and timely insect and weed control, adequate irrigation regime, use of proper cropmonitoring techniques and application of plant growth regulators.
Conclusion Results obtained from this study indicate that evaporation, sunshine duration, humidity, surface soil temperature at 1800 h, and maximum temperature, were the most significant climatic factors affecting flower and boll production of Egyptian cotton. Nevertheless, it could be stated that during the production stage, an accurate weather forecast for the next 5–7 days would provide an opportunity to avoid any adverse effects of climatic factors on cotton production. It would be useful to minimize the deleterious effects of those factors through utilizing proper cultural practices which would limit and control their negative effects, and this will lead to an improvement in cotton yield.
References Abdel-Salam, M.E. (1999). The Egyptian Cotton, pp 109–159. Giza, Egypt: ElKalema Press. 488 pp. Bhatt, J.G. (1977). Growth and flowering of cotton (Gossypium hirsutum L.) as affected by daylength and temperature. Journal of Agricultural Science, 89: 583–588. Burke, J.J., Mahan, J.R. & Hatfield, J.L. (1988). Crop specific thermal kinetic windows in relation to wheat and cotton biomass production. Agronomic Journal, 80: 553–556. Draper, N.R. & Smith, H. (1966). Applied Regression Analysis. New York: John Wiley and Sons, Inc. 407 pp. El-Zik, K.M. (1980). The cotton plant F its growth and development. Western Cotton Production Conference Summary Proceedings, pp. 18–21, Fresno, CA. Fisher, W.D. (1975). Heat induced sterility in Upland cotton. Proceedings of the 27th Cotton Improvement Conference 85. Gipson, J.R. (1986). Temperature effects on growth, development and fiber properties In: Mauney, J.R. & Stewart, J.M. (Eds), Cotton Physiology, pp. 47–56. Memphis, TN: Cotton Foundation. Gipson, L.R. & Joham, H.E. (1968). Influence of night temperature on growth and development of cotton (Gossypium hirsutum L.): I. Fruiting and boll development. Agronomy Journal, 60: 292–295. Guinn, G. (1982). Causes of square and boll shedding in cotton. USDA Technical Bulletin 1672. Guo, Y., Landivar, J.A., Hanggeler, J.C. & Moore, J. (1994). Response of cotton leaf water potential and transpiration to vapor pressure deficit and salinity under arid and humid climate conditions. In: Proceedings Beltwide Cotton Conferences, pp. 1301–1308, January 5-8, San Diego, CA, U.S.A. Memphis, U.S.A. National Cotton Council. 1751 pp.
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Hearn, A.B. & Constable, G.A. (1984). Cotton. In: Goldsworth, P.R. & Fisher, N.M. (Eds). The Physiology of Tropical Food Crops, Chapter 14, p. 495 NY: John Wiley & Sons Ltd. 664 pp. Hodges, H.F., Reddy, K.R., McKinion, J.M. & Reddy, V.R. (1993). Temperature effects on cotton. Bulletin of Mississippi Agricutltural Forestry Experimental Station, 990: 15. Kaur, R. & Singh, O.S. (1992). Response of growth stages of cotton varieties to moisture stress. Indian Journal of Plant Physiology, 35: 182–185. Meek, C.R., Oosterhuis, D.M. & Steger, A.T. (1999). Drought tolerance and foliar sprays of glycine betaine. In: Proceedings Beltwide Cotton Conferences, pp. 559–561. January 3–7, Orlando, FL, U.S.A. Memphis, U.S.A.: National Cotton Council. 1423 pp. Mergeai, G. & Demol, J. (1991). Contribution to the study of the effect of various meteorological factors on production and quality of cotton (Gossypium hirsutum L.) fibers. Bulletin des Recherches Agronomiqued de Gembloux, 26: 113–124. Miller, J.K., Krieg, D.R. & Paterson, R.E. (1996). Relationship between dryland cotton yields and weather parameters on the Southern Hig Plains. In: Proceedings Beltwide Cotton Conferences, pp. 1165–1166, January 9–12, Nashville, TN, U.S.A. Memphis, U.S.A.: National Cotton Council. 1684 pp. Moseley, D., Landivar, J.A. & Locke, D. 1994. Evaluation of the effect of methanol on cotton growth and yield under dry-land and irrigated conditions. In Proceedings Beltwide Cotton Conferences, pp. 1293–1294. January 5–8, San Diego, CA, U.S.A. Memphis, U.S.A.: National Cotton Council. 1751 pp. Oosterhuis, D.M. (1997). Effect of temperature extremes on cotton yields in Arkansas. In: Oosterhuis, D.M. & Stewart, J.M. (Eds) Proceedings of the Cotton Research Meeting, No. 183, pp. 94–98, Monticello, AR, U.S.A., February 13, Special Report–Agricultural Experiment Station, Division of Agriculture, University of Arkansas. Orgaz, F., Mateos, L. & Fereres, E. (1992). Season length and cultivar determine the optimum evapotranspiration deficit in cotton. Agronomy Journal, 84: 700–706. Ramey, H.H. (1986). Stress influence on fiber development. In: Mauney, J.R. and Stewart, J.M. (Ed.), Cotton Physiology, Memphis, TN: Cotton Foundation. pp. 351–360. Reddy, K.R., Hodges, H.F. & McKinion, J.M. (1995a). Carbon dioxide and temperature effects on pima cotton growth. Agriculture Ecosystems and Environment, 54: 17–29. Reddy, K.R., Hodges, H.F. & McKinion, J.M., 1996. Can cotton crops be sustained in future climates? In Proceedings Beltwide Cotton Conferences, pp. 1189–1196, January 9–12, Nashville, TN, U.S.A.: Memphis, U.S.A.: National Cotton Council. 1684 pp. Reddy, K.R., Hodges, H.F. & Reddy, V.R. (1992). Temperature effects on cotton fruit retention. Agronomy Journal, 84: 26–30. Reddy, K.R., McKinion, J.M., Wall, G.W., Bhattacharya, N.C., Hodges, H.F. & Bhattacharya, S. (1991). Effect of temperature on Pima growth and development. In Proceeding Beltwide Cotton Conferences, pp. 841, January 9–12, San Antonio, TX, U.S.A.: Memphis, U.S.A.: National Cotton Council. 1031 pp. Reddy, V.R., Reddy, K.R. & Acock, B. (1995b). Carbon dioxide and temperature interactions on stem extension, node initiation, and fruiting in cotton. Agriculture Ecosystems and Environment, 55: 17–28. SAS Institute Inc. (1985). SAS Users Guide: Statistics (5th Edn). Cary, NC: SAS Inst, Inc. 956 pp. Wang, X. & Whisler, F.D. (1994). Analyses of the effects of weather factors on predicted cotton growth and yield. Bulletin Mississippi Agricultural Forestry Experimental Station, 1014: 51. Ward, D.A. & Bunce, J.A. (1986). Responses of net photosynthesis and conductance to independent changes in the humidity environments of the upper and lower surfaces of leaves of sunflower and soybean. Journal of Experimental Botany, 37: 1842–1853. Warner, D.A. & Burke, J.J. (1993). Cool night temperature alter leaf starch and photosystem II Chlorophyll fluorescence in cotton. Agronomy Journal 85: 836–840. Winter, K. & Koniger, M. (1991). Dry matter production and photosynthetic capacity in Gossypium hirsutum L. under conditions of slightly sub-optimal leaf temperatures and high levels of irradiance. Oecologia, 87: 190–197. Zhao Du Li & Oosterhuis, D. (1997). Physiological response of growth chamber-grown cotton plants to the plant growth regulator PGR-IV under water-deficit stress. Environmental and Experimental Botany, 38: 7–14. Zhen Jin Zhong (1995). The causes of low cotton production in Huanghchuan County and measures to increase production. Henan Nongye Kexue, 2: 5–6.