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Temperature effect on yield of winter and spring irrigated crops
Agricultural and Forest Meteorology 279 (2019) 107664
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Temperature effect on yield of winter and spring irrigated crops a,⁎
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Hedayatollah Karimzadeh Soureshjani , Ayoub Ghorbani Dehkordi , Mahmoud Bahador a b c
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Department of Agronomy and Plant Breeding, Ferdowsi University of Mashhad, Iran Department of Horticulture, Gorgan University of Agricultural Science and Natural Resources, Iran Department of Agronomy, Shahrekord University, Iran
ARTICLE INFO
ABSTRACT
Keywords: Agrometeorology Chi-square Crop yield Weather condition
Extreme weather conditions, such as low and high air temperature changes during the growing season, play a significant role in irrigated crop yield. In this study an iterative chi-square statistical method was used to determine the relationship between air temperature and yield of dominant winter and spring irrigated crops in Shahrekord, Iran. Long term daily weather (1991–2016) and annual crop yield (wheat, barley, potato, alfalfa) data were analyzed and the relationships between low and high crop yield years with maximum and minimum air temperatures was evaluated. Our results indicated that higher temperature during tillering, dormancy breaking and stem elongation (fewer number of days with Tmax ≤ 5 °C and greater number of days with Tmax > 20 °C) and colder temperature in short time before dormancy breaking led to wheat yield loss. Cold weather during germination, seedling growth and tillering (greater number of days with Tmax ≤ 0 °C and excess nights with Tmin ≤ −20 °C) as well as cold temperature during breaking dormancy and kernel dough development (fewer days with Tmax > 25 °C) caused to reduce the barely grain yield. Warmer nights during potato flowering, development of fruit and mid-stage of tuber formation (excess days with Tmin > 10 °C) and cooler days during potato senescence (greater number of days with Tmax ≤ 20 °C) reduced potato tuber yield. Cool weather during emergence of first flower buds and first flowering stages (greater number of days with Tmax ≤ 20 °C) led to forage yield loss of alfalfa. Determination of critical periods when these crops are most sensitive to air temperature extremes provides important information for modifying management practices, such as adjusting planting date in order to reduction the negative effects of temperature extremes on crop yield. This information will also be useful for predicting crop yields in different years.
1. Introduction Annual crop yields depend on several factors which among the most important factors, crop yields is highly sensitive to weather (Frieler et al., 2017; Zhao et al., 2017). Climate explaining 30–50% of global crop yield variability (Rezaei et al., 2018; Zampieri et al., 2017). Temperature and precipitation have been recognized as the major climate factors governing crop growth regionally and globally (Deryng et al., 2011; Lobell et al., 2011; Ray et al., 2015). On the other hand, in irrigated crops which crops water requirement is provided by irrigation, the effect of temperature is most important climate factor in crops production. Extreme weather conditions, such as low and high air temperature changes during the growing season of each crop, play a significant role in crop yield. Any change in air temperature especially during critical developmental stages of crops such as flowering may effect growth processes and cause in huge yield changes (Bannayan et al., 2010). The crops response to high and low temperature
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particularly when it coincides with sensitive stages is very different (Challinor et al., 2005). The impacts of weather variation (temperature and precipitation) differed among the crops and depended upon the crop growth stage when the change occurred (Lobell et al., 2007). Understanding of the association between weather and crop yield can help to evaluate possible potential of yield enhancement and describe the climatic changes effects on agricultural production (Bannayan and Sanjani, 2011). Accurate information on the weather condition impacts on yield and especially quantitative analysis of these impacts are not available for most crops in many areas (McKeown et al., 2005). About 90% of Iran extends over arid and semi-arid areas (Karimzadeh Soureshjani et al., 2019) and has a variable climate (Bannayan et al., 2011). Crop yield in Iran varies from year to year, mainly due to very variable weather conditions hence it will be more affected by climate change. Climate change is likely to effect the number, magnitude and frequency of some extreme weather events (Mirza, 2003). One of the key effects of climate change on agriculture in
Corresponding author. E-mail address: [email protected] (H. Karimzadeh Soureshjani).
https://doi.org/10.1016/j.agrformet.2019.107664 Received 6 March 2019; Received in revised form 16 July 2019; Accepted 17 July 2019 0168-1923/ © 2019 Elsevier B.V. All rights reserved.
Agricultural and Forest Meteorology 279 (2019) 107664
H. Karimzadeh Soureshjani, et al.
arid and semi-arid regions includes decrease in crop yields and agricultural productivity with subsequent threats to the food security of dry-land countries (Amiri and Eslamian, 2010). Several studies have investigated the impacts of climate variation on crop yields in Iran. Bannayan and Sanjani (2011) examined the association between temperature and irrigated wheat yield in Khorasan province. Their results of chi-square analysis for wheat yield indicated that the critical time in which extreme temperature led to yield loss differed among regions. In Bojnourd, in late April to early May, and excess days (good or poor yield years have more days meeting a cardinal value than normal years) with maximum temperature higher than 30 °C, wheat yield decreased while in Birjand, cooler maximum temperature (≤10 °C) and excess days with minimum temperature particularly lower than −5 °C in midDecember were associated with low yielding year of wheat. They reported that relationship between various crop yield and weather conditions varied in different study location. Studding the association between saffron yield and climate variables in Khorasan province revealed that yield decrease of saffron in Khorasan province was linked to changes in climatic factors especially temperature and precipitation during the past ten years (Hosseini et al., 2008). They reported that 31–66 percent of yield variation can be explained by these climate variables. It was also concluded that precipitation compared with monthly temperature had less impact on saffron yield. In this study an “iterative chi-square” statistical method was used to determine the relationship between air temperature and yield of dominant winter and spring irrigated crops in Shahrekord, Iran. The iterative X2 method was first developed to found correlation between daily weather records and annual crop yields (Caprio, 1966). This method was adopted to determine the relationship of daily weather occurrences with apple yield in British Columbia (Caprio and Quamme, 1999), horticultural crops in Ontario (McKeown et al., 2005) and canola in Saskatchewan, Canada (Kutcher et al., 2010). Using the iterative X2 statistical method to elucidation of crop weather association can help to determine cause and effect relations (Caprio and Quamme, 2006). The objective of this investigation was to study the effect of temperature on yields of winter and spring crops grown under irrigated conditions in Shahrekord, Iran. Also using iterative X2 approach, the timing of climate events in relation to yield variations of all crops, were studied.
2.2. Iterative chi-square Iterative X2 was initially introduced by Caprio (1966), and has been applied to analysis of apple (Caprio and Quamme, 1999), grape (Caprio and Quamme, 2002), horticultural crops (Caprio and Quamme, 2006), variety of vegetable crops (Warland et al., 2006), canola (Kutcher et al., 2010) and wheat (Bannayan and Sanjani, 2011). The method firstly requires separation of annual crop yield data into quartiles and then defines three yield categories (good, normal and poor). Poor and good yield years are defined as the bottom and top quartiles based on a 5-year running average of yields. The normal years are then the remaining 50% of recorded years. Annual and 5 year running average of each crop yield were shown in Fig. 2. Iterative X2 test compares the number of days that meet a threshold condition with in a moving 3-week period (i.e. week 1–3, week 2–4 and so on) in good or poor yield years compared to normal years. In the other words in this study temperature were grouped into intervals of 5 °C. The number of days meeting the threshold for years in each yield category (in each temperature group) is expected to be proportionally distributed; otherwise, the returned X2 value departs from 0. In the other words, the day number in each temperature group (in each yield category) is expected to match with theoretical (expected) days. The deference between actual and theoretical day number in each temperature group was evaluated by X2 method for each yield category. A X2 value of 7 was taken as the critical value for significant impact of temperature (p < 0.01, df = 1) (Caprio, 1966; Kutcher et al., 2010). The test isolates the time of year at which the significant difference occurs, the strength of the difference (through the magnitude of X2), the threshold value below (or above) which the most significant difference occurs, and further defines a negative X2 for a deficit of days meeting the threshold condition and a positive X2 for an excess days meeting the threshold condition (Kutcher et al., 2010). In the other words, if the number of days at a specific temperature group during poor or good yield years exceed the theoretical days, the X2 will be positive. The number of days less than the theoretical number of days in each temperature group will also cause the X2 sign to be negative. The two value were generated for total number of days accumulating in temperature variable and for poor and good yield years in both high to low and low to high scans (Caprio, 1966). In the test, a X2 value is generated for each week of the growing season and for a range of threshold temperature values. At the maximum X2 point in a given scan, the temperature is referred to as the “cardinal” value which has been called “threshold” value (Kutcher et al., 2010). The growing season of winter crops (wheat and barley), potato and alfalfa were defined from November to June, June to October and May to October respectively. For more information about X2 analyses see Caprio (1966); Caprio and Quamme (2002); McKeown et al. (2005); Kutcher et al. (2010) and Bannayan and Sanjani (2011). Matlab™ programming language was used to coding X2 analysis.
2. Methodology 2.1. Crops and weather data In this study, we examined temperature effect on winter and spring crops in Shahrekord, Iran (Fig. 1). The average annual of Tmin, Tmax and Tmean of Shahrekord were 2.6 ± 1.1 °C (data ± standard deviation), 20.3 ± 0.9 °C and 11.5 ± 0.7 °C respectively. Shahrekord experiences cold winter and warm summer period. Annual total precipitation also was 333 ± 94 mm. The studied crops include wheat (Triticum aestivum L.), barley (Hordeum vulgar L.), potato (Solanum tuberosum L.) and alfalfa (Medicago sativa L.). Total area under cultivation of these crops were 8000 ha yr−1, 2300 ha yr−1, 1000 ha yr−1 and 4000 ha yr−1 for wheat, barley, potato and alfalfa respectively. Historical crop yields (1991–2016) of four different crops were obtained from the Agricultural Jihad Organization of Chaharmahal and Bakhtiari province. In this study the water requirement of crops has been provided by irrigation and the need for fertilizer is also provided annually, hence the crops yield was not dependent to precipitation and fertilizers (Table 1) hence the effect of minimum and maximum temperature on crops yield was studied in present study. Daily weather data include minimum temperatures (°C), maximum temperatures (°C) and precipitation (mm) from 1991 to 2016 were obtained from meteorological station of Shahrekord airport.
3. Results and discussion Chi-square value shows the temperature level at which the most significant difference is seen between good or poor yield years and the normal years. In this study both low-high and high-low scans were used. 3.1. Wheat Wheat poor-yield years had fewer number of days with Tmax ≤ 5 °C in the late-November and early-December, greater number of days with Tmax ≤ 5 °C in the late- February and early-March (Fig. 3d) and greater number of days with Tmax > 20 °C from early March to mid-April (Fig. 3c). Also, poor-yield years had fewer number of days with Tmax ≤ 15 °C in March and fewer number of days with Tmax ≤ 20 °C in the first half of April (Fig. 3d). On the contrary good-yield years had 2
Agricultural and Forest Meteorology 279 (2019) 107664
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Fig. 1. Location of the study area at the west of Iran.
temperature damage to winter wheat has been observed in all stages of growth from seedlings through to maturity (Fuller et al., 2007). Cold stress during vegetative growth decreases seedling survival as well as causing leaf damage resulting in the scorched appearance of leaves (Fuller et al., 2007; Shroyer et al., 1995) thus the radiation interception will be reduced. The cold temperature also limits root growth of wheat, since the development of root systems is primarily controlled by soil temperature (Kristensen et al., 2011). Warmer days during early March to mid-April (Tmax > 20 °C) coincides with dormancy breaking and stem elongation of winter wheat. Comparison of poor and normal yield years suggests that during this period, wheat requires cooler temperature (Tmax < 20 °C), and the high temperature in this period is a limiting factor for wheat grain yield. Fewer number of warmer days in early-January and the first half of March (Tmin > −5) coincides with wheat dormancy. Less cold nights during this period in good-yield years resulting in lower cold stress injury in winter wheat plants. Fuller et al. (2007) showed a seedling survival gradient of winter wheat, with seedling survival starting to reduction at −5 °C for non-acclimated plants and between −6 °C and −8 °C for acclimated winter wheat seedlings. Also, cool days in first half of March (Tmax > 15 °C) in good-yield years that coincides with dormancy breaking is more favorable for this stage in winter wheat. While warmer days in this period (Tmax > 20 °C) are one of the limiting factors that reduce wheat yield in poor-yield years.
Table 1 Correlation coefficient of precipitation and fertilizers with studied crops yield. Crops
P
N
P2O5
K2O
Wheat Barley Potato Alfalfa
0.09ns 0.19ns −0.10ns 0.11ns
0.001ns 0.10ns −0.10ns −0.31ns
0.18ns −0.05ns −0.01ns 0.38ns
−0.19ns 0.12ns −0.10ns −0.16ns
P: total growing season precipitation. ns: non-significant difference.
fewer number of days with Tmin ≤ −5 °C in early-November and earlyDecember, fewer number of days with Tmin ≤ −10 °C in the February (Fig. 3d), fewer number of days with Tmax > 15 °C in early-January and the first half of March (Fig. 3c) and fewer number of days with Tmin ≤ 10 °C in the first half of March (Fig. 3d). Also, good-yield year had excess days with Tmax > 15 °C in the first half of March (Fig. 3c). Wheat tillering takes place in late-November and December in Shahrekord. Warmer temperature during this period (fewer number of days with Tmax ≤ 5 °C) in poor-yield years causes the tiller number reduce rather than normal-yield years and ultimately produce weaker plants. On the contrary fewer day numbers with Tmin ≤ −5 °C and Tmax > 15 °C (lower cold injury) during wheat germination, seedling growth and tillering stages in good-yield years significantly correlated with higher grain yield of wheat. In fact, during these stages in goodyield years the temperature is cool, but cold stress injury is minimal. Other researchers also reported that low temperatures can increase tillering in winter wheat (Assuero and Tognetti, 2010). High tiller number causes early season ground cover, this trait contributes to the competition with weeds and minimizing water loss due to soil evaporation (Borràs-Gelonch et al., 2010; Dreccer et al., 2012). Colder days in the late-February and early-March (Tmax ≤ 5 °C) coincides with short time before dormancy breaking of winter wheat. The lower daily maximum temperature during this period may damage wheat plant and causes cold stress in poor-yield years. Cold
3.2. Barley There was a significant association between temperature and barley yield. Poor-yield years of barley had greater number of days with Tmax ≤ 0 °C in mid-November to mid-December (Fig. 4d), fewer number of days with Tmax > 15 °C in mid-November to mid-December (Fig. 4c), excess days with Tmin ≤ −20 °C in mid to late December (Fig. 4b), greater number of days with Tmax ≤ 5 °C in early-March and also greater number of days with Tmax ≤ 25 °C in early-June (Fig. 4d). Good-yield years of barley had more number of days with 3
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Fig. 2. Annual and 5 year running average of yield of wheat, barley, potato and alfalfa. (Horizontal line: average crop yield during studied period).
Tmax ≤ 10 °C in mid-November to mid-December (Fig. 4d), greater number of days with Tmax > 15 °C in early-January (Fig. 4c), greater number of days with Tmax ≤ 20 °C in late-April (Fig. 4d) and greater number of days with Tmin > 10 °C in early-June (Fig. 4a). Also goodyield years had fewer number of days with Tmin ≤ −5 °C in the first half of November, fewer number of days with Tmin ≤ −15 °C in lateDecember and early-January (Fig. 4b), fewer number of days with Tmin > 15 °C in mid-November to mid-December (Fig. 4c), fewer number of days with Tmin ≤ -10 °C in late-January to mid-February
(Fig. 4b) and fewer number of days with Tmax > 20 °C, Tmax > 25 °C and Tmax > 30 °C in mid-April, early-May and early-June respectively (Fig. 4c). November, December and early-January coincides with pre-dormancy growth of barley includes germination, seedling growth and tillering. During this period lower temperature in poor-yield years (greater number of days with Tmax ≤ 0 °C and excess nights with Tmin ≤ −20 °C) causing frost damage to these growth stages, resulting in lower number of fertile spike production per unit area. Prášil et al. Fig. 3. The iterative X2 analysis for wheat (a: high to low scan of daily minimum temperature (Tmin), b: low to high scan of daily minimum temperature (Tmin), c: high to low scan of daily maximum temperature (Tmax), d: low to high scan of daily maximum temperature (Tmax)). ×2 values = 7 (indicated by the dotted lines) is the critical values for significance (P ≥ 0.01, df = 1). Cardinal values (the temperature value at the maximum X2) is indicated on the graph.
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Fig. 4. The iterative X2 analysis for barley (a: high to low scan of daily minimum temperature (Tmin), b: low to high scan of daily minimum temperature (Tmin), c: high to low scan of daily maximum temperature (Tmax), d: low to high scan of daily maximum temperature (Tmax)). ×2 values = 7 (indicated by the dotted lines) is the critical values for significance (P ≥ 0.01, df = 1). Cardinal values (the temperature value at the maximum X2) is indicated on the graph.
(2007) evaluated the effect of low temperature on 39 barley cultivars and breeding lines in the Czech Republic. They observed that barley has a Tlmin50 (at which 50% of samples are killed) of −17.3 to −12.9 °C across 20 cultivars. On the contrary in good-yield years, this period is warmer and hence the temperature is more suitable for early growth and tillering. Also cold temperature during the first half of March (Tmax ≤ 5 °C) coincides with breaking dormancy of winter barley in poor-yield years. Cold weather during this period causes the barley plants to suffer cold stress. Barley plant stem elongation occurs in late-April that this time confidence with greater number of days with Tmax ≤ 20 °C in goodyield years. These observations indicate that the regrowth of barley after the winter dormancy has an optimum Tmax range of 5 ˜ 15 °C, and the temperatures outside this range is a limiting factor in the grain yield of winter barley. Winter barley booting, heading and anthesis occurs in May and this period coincides with fewer number of days with Tmax > 25 °C in goodyield years. In fact, during this period, there was no heat stress in goodyield years and weather condition were suitable for reproductive growth of barley. Reproductive stages are strongly affected by high temperatures in most plants, which eventually affect fertilization and post-fertilization processes leading to decreased crop yield (Wahid et al., 2007). It has been shown that high temperature during grain filling can decrease barley grain yield by reducing grain weight (Passarella et al., 2005). The kernel dough development of winter barley occurs in early-June that coincides with cooler temperature in poor-yield years (Tmax ≤ 25 °C) and warmer temperature in good-yield years (Tmax < 30 °C). These results show that the suitable Tmax for barley kernel dough development is between 25 and 30 °C.
Tmax ≤ 25 °C and Tmax ≤ 20 °C in late-September and mid-October respectively (Fig. 5d). Good-yield years of potato had fewer number of days with Tmin > 15 °C in July (Fig. 5a), greater number of days with Tmin ≤ 10 °C in early-July (Fig. 5b), excess days with Tmax ≤ 30 °C in early-July and greater number of days with Tmax ≤ 20 °C in early-October (Fig. 5c). Late-July to late-August coincides with potato flowering, development of fruit and mid-stage of tuber formation in Shahrekord. During this period there were warmer nights in poor-yield years. Inflorescence emergence and commence of tuber formation occur in July and this time coincides with cool weather that are not hot in good-yield years, hence these stages occur under optimal temperature conditions in goodyield years. Hancock et al. (2014) exposed tuberizing potato plants to elevated temperatures (30/20 °C, day/night). They report that the plants grown at elevated temperature had lower tuber yield. They observed these plants exhibited a reduction in biomass allocation to tubers and increase biomass allocation to leaves, hence tuber fresh weight, dry weight, dry matter and harvest index were reduced under elevated temperature condition. Potato senescence occurs in late-September to mid-October and this time coincides with cooler days (Tmax ≤ 25 °C and Tmax ≤ 20 °C) in poor-yield years. Good-yield years also had greater number of days with Tmax ≤ 20 °C in early-October but the number of days in this temperature range were very lower in good-yield years (10 days versus 30 days). In fact, in addition to the temperature range, the duration of exposure to the temperature range is also very important and it is very effective in determining the potato tuber yield. 3.4. Alfalfa Alfalfa yield was significantly correlated with temperature. Pooryield years of alfalfa had fewer number of days with Tmax > 25 °C in mid-September and fewer number of days with Tmax > 30 °C in earlyOctober (Fig. 6c), also greater number of days with Tmax ≤ 20 °C from early-September to early-October and greater number of days with Tmax ≤ 15 °C in mid-October (Fig. 6d). While good-yield years of alfalfa had fewer number of days with Tmin > 5 °C in June, fewer number of
3.3. Potato A significant association between potato yield and temperature was observed. Potato poor-yield years had fewer day numbers with Tmin ≤ 10 °C from late-July to late-August (Fig. 5b), excess days with Tmin > 10 °C in early-August (Fig. 5a) and greater number of days with 5
Agricultural and Forest Meteorology 279 (2019) 107664
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Fig. 5. The iterative X2 analysis for potato (a: high to low scan of daily minimum temperature (Tmin), b: low to high scan of daily minimum temperature (Tmin), c: high to low scan of daily maximum temperature (Tmax), d: low to high scan of daily maximum temperature (Tmax)). ×2 values = 7 (indicated by the dotted lines) is the critical values for significance (P ≥ 0.01, df = 1). Cardinal values (the temperature value at the maximum X2) is indicated on the graph.
days with Tmin > 10 °C in early-July (Fig. 6a), fewer number of days with Tmax > 30 °C in late-September (Fig. 6c), greater number of days with Tmax ≤ 20 °C in early-June (Fig. 6d) and excess days with Tmin ≤ 5 °C in early-July (Fig. 6b). Alfalfa forage harvests occur three times annually in Shahrekord which includes first week of July, second week of August and first week of October. Early-September and early-October coincide with emergence of first flower buds and first flowering stages respectively in third harvest. During these two periods the weather are less warm (fewer
number of days with Tmax > 25 °C and greater number of days with Tmax ≤ 20 °C) in poor-yield years and it looks like the weather is not warm enough for these stages (reproductive growth). Previous studies also have shown that the alfalfa optimum temperature is 25–29/ 15–18 °C (day/night) (Aranjuelo et al., 2006, 2007) and cooler temperature reduces alfalfa forage yield. The first flower buds to first flowering stages at first forage harvest occur in June and this time coincides with cooler but not frigid nights and cool days in good-yield years. Comparison of the suitable Fig. 6. The iterative X2 analysis for alfalfa (a: high to low scan of daily minimum temperature (Tmin), b: low to high scan of daily minimum temperature (Tmin), c: high to low scan of daily maximum temperature (Tmax), d: low to high scan of daily maximum temperature (Tmax)). ×2 values = 7 (indicated by the dotted lines) is the critical values for significance (P ≥ 0.01, df = 1). Cardinal values (the temperature value at the maximum X2) is indicated on the graph.
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temperature of the flowering stage in the first and third harvest reveal that the optimum temperature of this stage at the first and third harvest is not the same. In the first harvest the growth period duration is longer than third harvest (9 weeks versus 6 weeks). Because the growth period is shorter in third harvest, the optimum temperature is higher than the first one. Only in this condition (higher optimum temperature in third harvest), the thermal time requirement of the plant will be provided in a shorter period of time. Other researchers also reported that the response of alfalfa to the temperature in different harvest is not the same. For example Aranjuelo et al. (2006) evaluated the response of alfalfa to temperature and observed that different alfalfa forage harvests did not the same response to temperature. They reported plants dry matter production, no differences were detected between treatment treatments (25/15 °C day/night versus 29/19 °C day/night). While the forage yield at second harvest was significantly higher in elevated temperature treatment.
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4. Conclusions The results of this study indicated that there was association between crop yields and air temperature. Also, the results showed that the time and duration of the extreme temperatures in determining the yield of the investigated crops is very decisive. Warmer temperature during tillering, colder days in short time dormancy breaking and warmer days during dormancy breaking and stem elongation led to yield loss of wheat. Lower temperature during germination, seedling growth and tillering, cold temperature during breaking dormancy and cooler temperature during kernel dough development caused to reduce the grain yield of winter barley. Warmer nights during potato flowering, development of fruit and mid-stage of tuber formation and cooler days during potato senescence reduced potato tuber yield. Cool weather during emergence of first flower buds and first flowering stages led to forage yield loss of alfalfa. Determination of critical periods when these crops are most sensitive to air temperature extremes provides important information for modifying management practices, such as adjusting planting date in order to reduction the negative effects of temperature extremes on crop yield. This information will also be useful for predicting crop yields in different years. References Amiri, M., Eslamian, S., 2010. Investigation of climate change in Iran. J. Environ. Sci. Technol. 3 (4), 208–216. Aranjuelo, I., Irigoyen, J.J., Perez, P., Martinez-Carrasco, R., Sanchez-Diaz, M., 2006. Response of nodulated alfalfa to water supply, temperature and elevated CO2: productivity and water relations. Environ. Exp. Bot. 55 (1–2), 130–141. Aranjuelo, I., Irigoyen, J.J., Sánchez-Díaz, M., 2007. Effect of elevated temperature and water availability on CO2 exchange and nitrogen fixation of nodulated alfalfa plants. Environ. Exp. Bot. 59 (2), 99–108. Assuero, S.G., Tognetti, J.A., 2010. Tillering regulation by endogenous and environmental factors and its agricultural management. Am. J. Plant Sci. Biotechnol. 4 (1), 35–48. Bannayan, M., Lotfabadi, S.S., Sanjani, S., Mohamadian, A., Aghaalikhani, M., 2011. Effects of precipitation and temperature on crop production variability in northeast Iran. Int. J. Biometeorol. 55 (3), 387–401. Bannayan, M., Sanjani, S., 2011. Weather conditions associated with irrigated crops in an arid and semi arid environment. Agric. For. Meteorol. 151 (12), 1589–1598. Bannayan, M., Sanjani, S., Alizadeh, A., Lotfabadi, S.S., Mohamadian, A., 2010.
7
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Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Temperature effect on yield of winter and spring irrigated crops a,⁎
b
c
Hedayatollah Karimzadeh Soureshjani , Ayoub Ghorbani Dehkordi , Mahmoud Bahador a b c
T
Department of Agronomy and Plant Breeding, Ferdowsi University of Mashhad, Iran Department of Horticulture, Gorgan University of Agricultural Science and Natural Resources, Iran Department of Agronomy, Shahrekord University, Iran
ARTICLE INFO
ABSTRACT
Keywords: Agrometeorology Chi-square Crop yield Weather condition
Extreme weather conditions, such as low and high air temperature changes during the growing season, play a significant role in irrigated crop yield. In this study an iterative chi-square statistical method was used to determine the relationship between air temperature and yield of dominant winter and spring irrigated crops in Shahrekord, Iran. Long term daily weather (1991–2016) and annual crop yield (wheat, barley, potato, alfalfa) data were analyzed and the relationships between low and high crop yield years with maximum and minimum air temperatures was evaluated. Our results indicated that higher temperature during tillering, dormancy breaking and stem elongation (fewer number of days with Tmax ≤ 5 °C and greater number of days with Tmax > 20 °C) and colder temperature in short time before dormancy breaking led to wheat yield loss. Cold weather during germination, seedling growth and tillering (greater number of days with Tmax ≤ 0 °C and excess nights with Tmin ≤ −20 °C) as well as cold temperature during breaking dormancy and kernel dough development (fewer days with Tmax > 25 °C) caused to reduce the barely grain yield. Warmer nights during potato flowering, development of fruit and mid-stage of tuber formation (excess days with Tmin > 10 °C) and cooler days during potato senescence (greater number of days with Tmax ≤ 20 °C) reduced potato tuber yield. Cool weather during emergence of first flower buds and first flowering stages (greater number of days with Tmax ≤ 20 °C) led to forage yield loss of alfalfa. Determination of critical periods when these crops are most sensitive to air temperature extremes provides important information for modifying management practices, such as adjusting planting date in order to reduction the negative effects of temperature extremes on crop yield. This information will also be useful for predicting crop yields in different years.
1. Introduction Annual crop yields depend on several factors which among the most important factors, crop yields is highly sensitive to weather (Frieler et al., 2017; Zhao et al., 2017). Climate explaining 30–50% of global crop yield variability (Rezaei et al., 2018; Zampieri et al., 2017). Temperature and precipitation have been recognized as the major climate factors governing crop growth regionally and globally (Deryng et al., 2011; Lobell et al., 2011; Ray et al., 2015). On the other hand, in irrigated crops which crops water requirement is provided by irrigation, the effect of temperature is most important climate factor in crops production. Extreme weather conditions, such as low and high air temperature changes during the growing season of each crop, play a significant role in crop yield. Any change in air temperature especially during critical developmental stages of crops such as flowering may effect growth processes and cause in huge yield changes (Bannayan et al., 2010). The crops response to high and low temperature
⁎
particularly when it coincides with sensitive stages is very different (Challinor et al., 2005). The impacts of weather variation (temperature and precipitation) differed among the crops and depended upon the crop growth stage when the change occurred (Lobell et al., 2007). Understanding of the association between weather and crop yield can help to evaluate possible potential of yield enhancement and describe the climatic changes effects on agricultural production (Bannayan and Sanjani, 2011). Accurate information on the weather condition impacts on yield and especially quantitative analysis of these impacts are not available for most crops in many areas (McKeown et al., 2005). About 90% of Iran extends over arid and semi-arid areas (Karimzadeh Soureshjani et al., 2019) and has a variable climate (Bannayan et al., 2011). Crop yield in Iran varies from year to year, mainly due to very variable weather conditions hence it will be more affected by climate change. Climate change is likely to effect the number, magnitude and frequency of some extreme weather events (Mirza, 2003). One of the key effects of climate change on agriculture in
Corresponding author. E-mail address: [email protected] (H. Karimzadeh Soureshjani).
https://doi.org/10.1016/j.agrformet.2019.107664 Received 6 March 2019; Received in revised form 16 July 2019; Accepted 17 July 2019 0168-1923/ © 2019 Elsevier B.V. All rights reserved.
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arid and semi-arid regions includes decrease in crop yields and agricultural productivity with subsequent threats to the food security of dry-land countries (Amiri and Eslamian, 2010). Several studies have investigated the impacts of climate variation on crop yields in Iran. Bannayan and Sanjani (2011) examined the association between temperature and irrigated wheat yield in Khorasan province. Their results of chi-square analysis for wheat yield indicated that the critical time in which extreme temperature led to yield loss differed among regions. In Bojnourd, in late April to early May, and excess days (good or poor yield years have more days meeting a cardinal value than normal years) with maximum temperature higher than 30 °C, wheat yield decreased while in Birjand, cooler maximum temperature (≤10 °C) and excess days with minimum temperature particularly lower than −5 °C in midDecember were associated with low yielding year of wheat. They reported that relationship between various crop yield and weather conditions varied in different study location. Studding the association between saffron yield and climate variables in Khorasan province revealed that yield decrease of saffron in Khorasan province was linked to changes in climatic factors especially temperature and precipitation during the past ten years (Hosseini et al., 2008). They reported that 31–66 percent of yield variation can be explained by these climate variables. It was also concluded that precipitation compared with monthly temperature had less impact on saffron yield. In this study an “iterative chi-square” statistical method was used to determine the relationship between air temperature and yield of dominant winter and spring irrigated crops in Shahrekord, Iran. The iterative X2 method was first developed to found correlation between daily weather records and annual crop yields (Caprio, 1966). This method was adopted to determine the relationship of daily weather occurrences with apple yield in British Columbia (Caprio and Quamme, 1999), horticultural crops in Ontario (McKeown et al., 2005) and canola in Saskatchewan, Canada (Kutcher et al., 2010). Using the iterative X2 statistical method to elucidation of crop weather association can help to determine cause and effect relations (Caprio and Quamme, 2006). The objective of this investigation was to study the effect of temperature on yields of winter and spring crops grown under irrigated conditions in Shahrekord, Iran. Also using iterative X2 approach, the timing of climate events in relation to yield variations of all crops, were studied.
2.2. Iterative chi-square Iterative X2 was initially introduced by Caprio (1966), and has been applied to analysis of apple (Caprio and Quamme, 1999), grape (Caprio and Quamme, 2002), horticultural crops (Caprio and Quamme, 2006), variety of vegetable crops (Warland et al., 2006), canola (Kutcher et al., 2010) and wheat (Bannayan and Sanjani, 2011). The method firstly requires separation of annual crop yield data into quartiles and then defines three yield categories (good, normal and poor). Poor and good yield years are defined as the bottom and top quartiles based on a 5-year running average of yields. The normal years are then the remaining 50% of recorded years. Annual and 5 year running average of each crop yield were shown in Fig. 2. Iterative X2 test compares the number of days that meet a threshold condition with in a moving 3-week period (i.e. week 1–3, week 2–4 and so on) in good or poor yield years compared to normal years. In the other words in this study temperature were grouped into intervals of 5 °C. The number of days meeting the threshold for years in each yield category (in each temperature group) is expected to be proportionally distributed; otherwise, the returned X2 value departs from 0. In the other words, the day number in each temperature group (in each yield category) is expected to match with theoretical (expected) days. The deference between actual and theoretical day number in each temperature group was evaluated by X2 method for each yield category. A X2 value of 7 was taken as the critical value for significant impact of temperature (p < 0.01, df = 1) (Caprio, 1966; Kutcher et al., 2010). The test isolates the time of year at which the significant difference occurs, the strength of the difference (through the magnitude of X2), the threshold value below (or above) which the most significant difference occurs, and further defines a negative X2 for a deficit of days meeting the threshold condition and a positive X2 for an excess days meeting the threshold condition (Kutcher et al., 2010). In the other words, if the number of days at a specific temperature group during poor or good yield years exceed the theoretical days, the X2 will be positive. The number of days less than the theoretical number of days in each temperature group will also cause the X2 sign to be negative. The two value were generated for total number of days accumulating in temperature variable and for poor and good yield years in both high to low and low to high scans (Caprio, 1966). In the test, a X2 value is generated for each week of the growing season and for a range of threshold temperature values. At the maximum X2 point in a given scan, the temperature is referred to as the “cardinal” value which has been called “threshold” value (Kutcher et al., 2010). The growing season of winter crops (wheat and barley), potato and alfalfa were defined from November to June, June to October and May to October respectively. For more information about X2 analyses see Caprio (1966); Caprio and Quamme (2002); McKeown et al. (2005); Kutcher et al. (2010) and Bannayan and Sanjani (2011). Matlab™ programming language was used to coding X2 analysis.
2. Methodology 2.1. Crops and weather data In this study, we examined temperature effect on winter and spring crops in Shahrekord, Iran (Fig. 1). The average annual of Tmin, Tmax and Tmean of Shahrekord were 2.6 ± 1.1 °C (data ± standard deviation), 20.3 ± 0.9 °C and 11.5 ± 0.7 °C respectively. Shahrekord experiences cold winter and warm summer period. Annual total precipitation also was 333 ± 94 mm. The studied crops include wheat (Triticum aestivum L.), barley (Hordeum vulgar L.), potato (Solanum tuberosum L.) and alfalfa (Medicago sativa L.). Total area under cultivation of these crops were 8000 ha yr−1, 2300 ha yr−1, 1000 ha yr−1 and 4000 ha yr−1 for wheat, barley, potato and alfalfa respectively. Historical crop yields (1991–2016) of four different crops were obtained from the Agricultural Jihad Organization of Chaharmahal and Bakhtiari province. In this study the water requirement of crops has been provided by irrigation and the need for fertilizer is also provided annually, hence the crops yield was not dependent to precipitation and fertilizers (Table 1) hence the effect of minimum and maximum temperature on crops yield was studied in present study. Daily weather data include minimum temperatures (°C), maximum temperatures (°C) and precipitation (mm) from 1991 to 2016 were obtained from meteorological station of Shahrekord airport.
3. Results and discussion Chi-square value shows the temperature level at which the most significant difference is seen between good or poor yield years and the normal years. In this study both low-high and high-low scans were used. 3.1. Wheat Wheat poor-yield years had fewer number of days with Tmax ≤ 5 °C in the late-November and early-December, greater number of days with Tmax ≤ 5 °C in the late- February and early-March (Fig. 3d) and greater number of days with Tmax > 20 °C from early March to mid-April (Fig. 3c). Also, poor-yield years had fewer number of days with Tmax ≤ 15 °C in March and fewer number of days with Tmax ≤ 20 °C in the first half of April (Fig. 3d). On the contrary good-yield years had 2
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Fig. 1. Location of the study area at the west of Iran.
temperature damage to winter wheat has been observed in all stages of growth from seedlings through to maturity (Fuller et al., 2007). Cold stress during vegetative growth decreases seedling survival as well as causing leaf damage resulting in the scorched appearance of leaves (Fuller et al., 2007; Shroyer et al., 1995) thus the radiation interception will be reduced. The cold temperature also limits root growth of wheat, since the development of root systems is primarily controlled by soil temperature (Kristensen et al., 2011). Warmer days during early March to mid-April (Tmax > 20 °C) coincides with dormancy breaking and stem elongation of winter wheat. Comparison of poor and normal yield years suggests that during this period, wheat requires cooler temperature (Tmax < 20 °C), and the high temperature in this period is a limiting factor for wheat grain yield. Fewer number of warmer days in early-January and the first half of March (Tmin > −5) coincides with wheat dormancy. Less cold nights during this period in good-yield years resulting in lower cold stress injury in winter wheat plants. Fuller et al. (2007) showed a seedling survival gradient of winter wheat, with seedling survival starting to reduction at −5 °C for non-acclimated plants and between −6 °C and −8 °C for acclimated winter wheat seedlings. Also, cool days in first half of March (Tmax > 15 °C) in good-yield years that coincides with dormancy breaking is more favorable for this stage in winter wheat. While warmer days in this period (Tmax > 20 °C) are one of the limiting factors that reduce wheat yield in poor-yield years.
Table 1 Correlation coefficient of precipitation and fertilizers with studied crops yield. Crops
P
N
P2O5
K2O
Wheat Barley Potato Alfalfa
0.09ns 0.19ns −0.10ns 0.11ns
0.001ns 0.10ns −0.10ns −0.31ns
0.18ns −0.05ns −0.01ns 0.38ns
−0.19ns 0.12ns −0.10ns −0.16ns
P: total growing season precipitation. ns: non-significant difference.
fewer number of days with Tmin ≤ −5 °C in early-November and earlyDecember, fewer number of days with Tmin ≤ −10 °C in the February (Fig. 3d), fewer number of days with Tmax > 15 °C in early-January and the first half of March (Fig. 3c) and fewer number of days with Tmin ≤ 10 °C in the first half of March (Fig. 3d). Also, good-yield year had excess days with Tmax > 15 °C in the first half of March (Fig. 3c). Wheat tillering takes place in late-November and December in Shahrekord. Warmer temperature during this period (fewer number of days with Tmax ≤ 5 °C) in poor-yield years causes the tiller number reduce rather than normal-yield years and ultimately produce weaker plants. On the contrary fewer day numbers with Tmin ≤ −5 °C and Tmax > 15 °C (lower cold injury) during wheat germination, seedling growth and tillering stages in good-yield years significantly correlated with higher grain yield of wheat. In fact, during these stages in goodyield years the temperature is cool, but cold stress injury is minimal. Other researchers also reported that low temperatures can increase tillering in winter wheat (Assuero and Tognetti, 2010). High tiller number causes early season ground cover, this trait contributes to the competition with weeds and minimizing water loss due to soil evaporation (Borràs-Gelonch et al., 2010; Dreccer et al., 2012). Colder days in the late-February and early-March (Tmax ≤ 5 °C) coincides with short time before dormancy breaking of winter wheat. The lower daily maximum temperature during this period may damage wheat plant and causes cold stress in poor-yield years. Cold
3.2. Barley There was a significant association between temperature and barley yield. Poor-yield years of barley had greater number of days with Tmax ≤ 0 °C in mid-November to mid-December (Fig. 4d), fewer number of days with Tmax > 15 °C in mid-November to mid-December (Fig. 4c), excess days with Tmin ≤ −20 °C in mid to late December (Fig. 4b), greater number of days with Tmax ≤ 5 °C in early-March and also greater number of days with Tmax ≤ 25 °C in early-June (Fig. 4d). Good-yield years of barley had more number of days with 3
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Fig. 2. Annual and 5 year running average of yield of wheat, barley, potato and alfalfa. (Horizontal line: average crop yield during studied period).
Tmax ≤ 10 °C in mid-November to mid-December (Fig. 4d), greater number of days with Tmax > 15 °C in early-January (Fig. 4c), greater number of days with Tmax ≤ 20 °C in late-April (Fig. 4d) and greater number of days with Tmin > 10 °C in early-June (Fig. 4a). Also goodyield years had fewer number of days with Tmin ≤ −5 °C in the first half of November, fewer number of days with Tmin ≤ −15 °C in lateDecember and early-January (Fig. 4b), fewer number of days with Tmin > 15 °C in mid-November to mid-December (Fig. 4c), fewer number of days with Tmin ≤ -10 °C in late-January to mid-February
(Fig. 4b) and fewer number of days with Tmax > 20 °C, Tmax > 25 °C and Tmax > 30 °C in mid-April, early-May and early-June respectively (Fig. 4c). November, December and early-January coincides with pre-dormancy growth of barley includes germination, seedling growth and tillering. During this period lower temperature in poor-yield years (greater number of days with Tmax ≤ 0 °C and excess nights with Tmin ≤ −20 °C) causing frost damage to these growth stages, resulting in lower number of fertile spike production per unit area. Prášil et al. Fig. 3. The iterative X2 analysis for wheat (a: high to low scan of daily minimum temperature (Tmin), b: low to high scan of daily minimum temperature (Tmin), c: high to low scan of daily maximum temperature (Tmax), d: low to high scan of daily maximum temperature (Tmax)). ×2 values = 7 (indicated by the dotted lines) is the critical values for significance (P ≥ 0.01, df = 1). Cardinal values (the temperature value at the maximum X2) is indicated on the graph.
4
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Fig. 4. The iterative X2 analysis for barley (a: high to low scan of daily minimum temperature (Tmin), b: low to high scan of daily minimum temperature (Tmin), c: high to low scan of daily maximum temperature (Tmax), d: low to high scan of daily maximum temperature (Tmax)). ×2 values = 7 (indicated by the dotted lines) is the critical values for significance (P ≥ 0.01, df = 1). Cardinal values (the temperature value at the maximum X2) is indicated on the graph.
(2007) evaluated the effect of low temperature on 39 barley cultivars and breeding lines in the Czech Republic. They observed that barley has a Tlmin50 (at which 50% of samples are killed) of −17.3 to −12.9 °C across 20 cultivars. On the contrary in good-yield years, this period is warmer and hence the temperature is more suitable for early growth and tillering. Also cold temperature during the first half of March (Tmax ≤ 5 °C) coincides with breaking dormancy of winter barley in poor-yield years. Cold weather during this period causes the barley plants to suffer cold stress. Barley plant stem elongation occurs in late-April that this time confidence with greater number of days with Tmax ≤ 20 °C in goodyield years. These observations indicate that the regrowth of barley after the winter dormancy has an optimum Tmax range of 5 ˜ 15 °C, and the temperatures outside this range is a limiting factor in the grain yield of winter barley. Winter barley booting, heading and anthesis occurs in May and this period coincides with fewer number of days with Tmax > 25 °C in goodyield years. In fact, during this period, there was no heat stress in goodyield years and weather condition were suitable for reproductive growth of barley. Reproductive stages are strongly affected by high temperatures in most plants, which eventually affect fertilization and post-fertilization processes leading to decreased crop yield (Wahid et al., 2007). It has been shown that high temperature during grain filling can decrease barley grain yield by reducing grain weight (Passarella et al., 2005). The kernel dough development of winter barley occurs in early-June that coincides with cooler temperature in poor-yield years (Tmax ≤ 25 °C) and warmer temperature in good-yield years (Tmax < 30 °C). These results show that the suitable Tmax for barley kernel dough development is between 25 and 30 °C.
Tmax ≤ 25 °C and Tmax ≤ 20 °C in late-September and mid-October respectively (Fig. 5d). Good-yield years of potato had fewer number of days with Tmin > 15 °C in July (Fig. 5a), greater number of days with Tmin ≤ 10 °C in early-July (Fig. 5b), excess days with Tmax ≤ 30 °C in early-July and greater number of days with Tmax ≤ 20 °C in early-October (Fig. 5c). Late-July to late-August coincides with potato flowering, development of fruit and mid-stage of tuber formation in Shahrekord. During this period there were warmer nights in poor-yield years. Inflorescence emergence and commence of tuber formation occur in July and this time coincides with cool weather that are not hot in good-yield years, hence these stages occur under optimal temperature conditions in goodyield years. Hancock et al. (2014) exposed tuberizing potato plants to elevated temperatures (30/20 °C, day/night). They report that the plants grown at elevated temperature had lower tuber yield. They observed these plants exhibited a reduction in biomass allocation to tubers and increase biomass allocation to leaves, hence tuber fresh weight, dry weight, dry matter and harvest index were reduced under elevated temperature condition. Potato senescence occurs in late-September to mid-October and this time coincides with cooler days (Tmax ≤ 25 °C and Tmax ≤ 20 °C) in poor-yield years. Good-yield years also had greater number of days with Tmax ≤ 20 °C in early-October but the number of days in this temperature range were very lower in good-yield years (10 days versus 30 days). In fact, in addition to the temperature range, the duration of exposure to the temperature range is also very important and it is very effective in determining the potato tuber yield. 3.4. Alfalfa Alfalfa yield was significantly correlated with temperature. Pooryield years of alfalfa had fewer number of days with Tmax > 25 °C in mid-September and fewer number of days with Tmax > 30 °C in earlyOctober (Fig. 6c), also greater number of days with Tmax ≤ 20 °C from early-September to early-October and greater number of days with Tmax ≤ 15 °C in mid-October (Fig. 6d). While good-yield years of alfalfa had fewer number of days with Tmin > 5 °C in June, fewer number of
3.3. Potato A significant association between potato yield and temperature was observed. Potato poor-yield years had fewer day numbers with Tmin ≤ 10 °C from late-July to late-August (Fig. 5b), excess days with Tmin > 10 °C in early-August (Fig. 5a) and greater number of days with 5
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Fig. 5. The iterative X2 analysis for potato (a: high to low scan of daily minimum temperature (Tmin), b: low to high scan of daily minimum temperature (Tmin), c: high to low scan of daily maximum temperature (Tmax), d: low to high scan of daily maximum temperature (Tmax)). ×2 values = 7 (indicated by the dotted lines) is the critical values for significance (P ≥ 0.01, df = 1). Cardinal values (the temperature value at the maximum X2) is indicated on the graph.
days with Tmin > 10 °C in early-July (Fig. 6a), fewer number of days with Tmax > 30 °C in late-September (Fig. 6c), greater number of days with Tmax ≤ 20 °C in early-June (Fig. 6d) and excess days with Tmin ≤ 5 °C in early-July (Fig. 6b). Alfalfa forage harvests occur three times annually in Shahrekord which includes first week of July, second week of August and first week of October. Early-September and early-October coincide with emergence of first flower buds and first flowering stages respectively in third harvest. During these two periods the weather are less warm (fewer
number of days with Tmax > 25 °C and greater number of days with Tmax ≤ 20 °C) in poor-yield years and it looks like the weather is not warm enough for these stages (reproductive growth). Previous studies also have shown that the alfalfa optimum temperature is 25–29/ 15–18 °C (day/night) (Aranjuelo et al., 2006, 2007) and cooler temperature reduces alfalfa forage yield. The first flower buds to first flowering stages at first forage harvest occur in June and this time coincides with cooler but not frigid nights and cool days in good-yield years. Comparison of the suitable Fig. 6. The iterative X2 analysis for alfalfa (a: high to low scan of daily minimum temperature (Tmin), b: low to high scan of daily minimum temperature (Tmin), c: high to low scan of daily maximum temperature (Tmax), d: low to high scan of daily maximum temperature (Tmax)). ×2 values = 7 (indicated by the dotted lines) is the critical values for significance (P ≥ 0.01, df = 1). Cardinal values (the temperature value at the maximum X2) is indicated on the graph.
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temperature of the flowering stage in the first and third harvest reveal that the optimum temperature of this stage at the first and third harvest is not the same. In the first harvest the growth period duration is longer than third harvest (9 weeks versus 6 weeks). Because the growth period is shorter in third harvest, the optimum temperature is higher than the first one. Only in this condition (higher optimum temperature in third harvest), the thermal time requirement of the plant will be provided in a shorter period of time. Other researchers also reported that the response of alfalfa to the temperature in different harvest is not the same. For example Aranjuelo et al. (2006) evaluated the response of alfalfa to temperature and observed that different alfalfa forage harvests did not the same response to temperature. They reported plants dry matter production, no differences were detected between treatment treatments (25/15 °C day/night versus 29/19 °C day/night). While the forage yield at second harvest was significantly higher in elevated temperature treatment.
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4. Conclusions The results of this study indicated that there was association between crop yields and air temperature. Also, the results showed that the time and duration of the extreme temperatures in determining the yield of the investigated crops is very decisive. Warmer temperature during tillering, colder days in short time dormancy breaking and warmer days during dormancy breaking and stem elongation led to yield loss of wheat. Lower temperature during germination, seedling growth and tillering, cold temperature during breaking dormancy and cooler temperature during kernel dough development caused to reduce the grain yield of winter barley. Warmer nights during potato flowering, development of fruit and mid-stage of tuber formation and cooler days during potato senescence reduced potato tuber yield. Cool weather during emergence of first flower buds and first flowering stages led to forage yield loss of alfalfa. Determination of critical periods when these crops are most sensitive to air temperature extremes provides important information for modifying management practices, such as adjusting planting date in order to reduction the negative effects of temperature extremes on crop yield. This information will also be useful for predicting crop yields in different years. References Amiri, M., Eslamian, S., 2010. Investigation of climate change in Iran. J. Environ. Sci. Technol. 3 (4), 208–216. Aranjuelo, I., Irigoyen, J.J., Perez, P., Martinez-Carrasco, R., Sanchez-Diaz, M., 2006. Response of nodulated alfalfa to water supply, temperature and elevated CO2: productivity and water relations. Environ. Exp. Bot. 55 (1–2), 130–141. Aranjuelo, I., Irigoyen, J.J., Sánchez-Díaz, M., 2007. Effect of elevated temperature and water availability on CO2 exchange and nitrogen fixation of nodulated alfalfa plants. Environ. Exp. Bot. 59 (2), 99–108. Assuero, S.G., Tognetti, J.A., 2010. Tillering regulation by endogenous and environmental factors and its agricultural management. Am. J. Plant Sci. Biotechnol. 4 (1), 35–48. Bannayan, M., Lotfabadi, S.S., Sanjani, S., Mohamadian, A., Aghaalikhani, M., 2011. Effects of precipitation and temperature on crop production variability in northeast Iran. Int. J. Biometeorol. 55 (3), 387–401. Bannayan, M., Sanjani, S., 2011. Weather conditions associated with irrigated crops in an arid and semi arid environment. Agric. For. Meteorol. 151 (12), 1589–1598. Bannayan, M., Sanjani, S., Alizadeh, A., Lotfabadi, S.S., Mohamadian, A., 2010.
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