Agricultural Meteorology
M. Abdollahi Fuzi; B. Bakhtiari; K. Qaderi
Abstract
IntroductionSpring frost is considered an important threat to agricultural products in high and middle latitudes. The damage caused by Late Spring Frosts (LSFs) significantly impacts vulnerable plant organs. This event has caused more economic losses to agriculture than any other climatic hazard in Asia, ...
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IntroductionSpring frost is considered an important threat to agricultural products in high and middle latitudes. The damage caused by Late Spring Frosts (LSFs) significantly impacts vulnerable plant organs. This event has caused more economic losses to agriculture than any other climatic hazard in Asia, North America, and Europe. Also, these phenomena have contributed to low crop yields in Iran. The latest statistics released by the Food and Agriculture Organization of the United Nations (FAO) show that Iran is one of the largest producers of agricultural products and the world’s second-biggest producer of pistachios. Kerman province is one of the significant areas of pistachio production. This province has a large share of the pistachio word area plantation. Spring frost damage to pistachio crops has led to low yields in recent years. A key aspect of studying frost is the ability to accurately estimate its occurrence. In this study, artificial neural network methods have been used to estimate late spring frost in the pistachio crop of Kerman city. Materials and MethodsIn this study, the efficiency of this method was investigated in the estimation of minimum temperature. For this purpose, the daily data of the synoptic station of Kerman city were obtained from Iran Meteorological Organization from 2000 to 2020. Meteorological data including mean, maximum, and minimum temperatures, relative humidity, wind speed, saturated vapor pressure, and sunshine hours were used. Five different combinations of these variables was considered as input variables in artificial neural network method for minimum temperatures modeling. After entering data into network and modeling with each combination, RMSE and R2 values were calculated. Finally, the combination of 8 variables including average and maximum temperature, the minimum temperature the previous day and two days prior, relative humidity, wind speed, saturated vapor pressure, and sunny hours were selected as the most suitable combination of variables. Subsequently, a simulation of minimum temperature values was conducted using 10% of the data. The performance of the methods was evaluated using statistical indices of coefficient of determination (R2), mean square of error (RMSE), Mean Bias Error (MBE), and Coefficient of Nash–Sutcliffe (NSE). Results and DiscussionThe accuracy of an analytical method is the degree of agreement between the test results generated by the method and the true value. Upon examining the models, the M1 model was identified as the best due to its lowest RMSE and higher R². ANN model results were evaluated using various performance measure indicators. The simulated outcome of the model indicated a strong association with actual data, where the correlation coefficient was above 0.95, and the MBE index was zero. Also, the RMSE value was positive and close to zero, and the NSE value was above 0.75. Therefore artificial neural network method had high accuracy. In this study, mean annual minimum temperature was estimated using artificial neural network models (from March 10 to May 20). Comparison between the observed and calculated data showed that these data were in good agreement. Also, the results showed that temperature fluctuations were high between March 10 and March 31. From 2011 to 2017, an almost uniform temperature trend has been observed between March 10 and March 31. However, the years 2000, 2006, and 2020 showed a noticeable decrease in temperature. From 2018 to 2020, this trend of temperature reduction continued. In April, the temperature values were between 7 and 10 degrees Celsius. The years 2001, 2005, 2006, 2009, 2016, and 2019 had a noticeable decrease in temperature. In May, the mean minimum temperature was between 10 and 14 degrees Celsius. Therefore, the probability of frost occurrence in early-flowering cultivars was higher in late March than in April and May. The years 2000, 2004, 2005, 2012, 2015, 2019 and 2020 had the highest number of frost days in the last two decades. ConclusionThe results showed that the artificial neural network method had a high performance in estimating the minimum temperature. The values of the statistical indicators were R2=0.963, RMSE=0.027oC, MBE= 0 and NSE=0.966 respectively. In addition, the ANN method performed well in estimating the number of critical frost days for pistachio crops. The results showed that, although reducing the amount of input data in models decreases their output precision, data-driven methods can still be useful tools for minimum temperature estimation.
babak motesharezadeh; somayeh rezaezadeh; majid fekri
Abstract
Introduction: Boron is one of the seven essential microelements for the natural growth of plants. The toxicity of this element occurs in arid and semi-arid regions, which is because of its high level in soils and the irrigation water of mentioned regions. The aim of this study was to evaluate the effect ...
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Introduction: Boron is one of the seven essential microelements for the natural growth of plants. The toxicity of this element occurs in arid and semi-arid regions, which is because of its high level in soils and the irrigation water of mentioned regions. The aim of this study was to evaluate the effect of nitrogen application on boron toxicity tolerance in pistachio, Badami-Zarand variety. The effects of three nitrogen levels (0, 250, and 350 mg/kg of soil) on the reduction of toxicity due to the three levels of boron (0, 15, and 30 mg/kg of soil) were examined in Badami-Zarandi variety of pistachio under greenhouse conditions. After 7 months from sowing the seeds, pistachio seedlings were harvested and desired traits were measured. The results showed that by increasing boron application level, boron concentration in the shoot and root of seedlings increased whereas their dry weight decreased. Using of nitrogen reduced the negative effects of boron on the dry weight and led to increase dry weight and decrease boron concentration in the shoot and root of pistachio, Badami variety. Nitrogen application at the levels of 250 and 350 mg N per kg of soil reduced boron uptake in shoots by reinforcing plant vegetative system and increasing chlorophyll content by 13.5% and 30.2%, respectively and finally led to diluted boron concentration in the plant (dilution effect) and reduced the effects of boron toxicity. Hence, optimized nitrogen application is suggested as one of the management methods in controlling Boron toxicity under these conditions.
Materials and Methods: A factorial experiment based on randomized complete block design with four replications was carried out. Soil sampling was done in 0-30 cm depth in a zeekzack way from a pistachio garden that located in mahmoodiye area in Rafsanjan. The soil sample was air-dried and passed through a 2mm sieve. The soil chemical and physical properties were measured. In this study, badami-zarand cultivar seed was used because it is one of the most important pistachio cultivars. The seeds were soaked in water for 24 hours and disinfected by benomyl fungicide. When the seeds germinated, they were planted in the pots containing 4.5 kg soil and without drainage, so nutrients balance was kept during growing period. After 7 months, the seedlings were harvested and B was measured.
Results and Discussion: The results showed that increasing the boron levels from 0 to 30 mg kg-1 led to decrease shoot dry weight from 3.72 to 2.45 gram and root DM from 2.28 to 1.50 gram. Increasing 30 mg kg-1 boron led to 2.8 times increase of shoot boron concentration. The averages of shoot boron concentration in the levels of 15 and 30 mg kg-1 boron were 87.6 and 122 mg kg-1DM, respectively. The boron toxicity level in Badami-Zarand cultivar is 8.9 mg kg-1 DM (Sepaskhahet al, 1994), so these levels were the cause of boron toxicity and boron toxicity symptoms were seen as leaf burn, often at the margins and the tips of older leaves.
The results showed that increasing nitrogen levels led to decrease shoot boron concentration and increase their weight. The results also showed a significant negative correlation between the nitrogen levels and boron uptake. Boron uptake in the shoots of seedlings about 13.5 and 30.2 percent decreased when nitrogen levels increased. Shoot dry weight decreased when boron application increased, but it increased when nitrogen was used (Koohkan and Maftoun, 2009).
Conclusion: The reduction of dry weight and increasing boron concentration occurred when increased boron application. The Maximum of boron uptake was seen by leaves, and boron toxicity symptoms were appeared as leaf burn especially at the tips and margins of older leaves. Since, boron is immobile in pistachio; it is absorbed by mass flow, so the accumulation of boron at older leaves is persuaded. Nitrogen reduced the bad effects of boron on dry weight and the bad effects of increasing boron concentration by the synthesis of chlorophyll, so it was more useful in shoot than root. Boron uptake was also reduced by nitrogen application. This effect of nitrogen is probably concerned to the increase of dry weight more than boron concentration (Dilution effect). On the other hand, nitrogen caused to increase leaf index and increase the number of seedling leaves. The injured leaves due to boron toxicity were restored, because of high leaf chlorophyll. It is suggested that this study will be done under field conditions for fertilizer application recommendations and to be used for creation of tolerant cultivars of pistachio.
N. Sedaghati; S.J. Hosseinifard; A. Mohammadi Mohammadabadi
Abstract
Unsustainable harvesting of agricultural water resources in the province of Kerman, has caused an annual average of one-meter drop in ground water levels. Surface irrigation methods in pistachio trees have low efficiency because of inherent characteristics and its incorrect application, as well as low ...
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Unsustainable harvesting of agricultural water resources in the province of Kerman, has caused an annual average of one-meter drop in ground water levels. Surface irrigation methods in pistachio trees have low efficiency because of inherent characteristics and its incorrect application, as well as low access to water resource in pistachio regions. Therefore under the current critical condition, basic development of pressurized irrigation systems is an effective step to raise water use efficiency in the pistachio orchards. In this research, two irrigation systems including conventional surface drip irrigation and subsurface drip irrigation (SDI) with two drip line depths (30cm and 50cm) with three levels of water irrigation in each treatment, including 40%, 60% and 80% of irrigation requirement of pistachio in surface irrigation system (2932, 4398 and 5864 m3/ha.year respectively) for four years, was studied. Growth and yield factors, water use efficiency (WUE) and water and salinity distribution in root zone were measured. The results indicated that 30cm installation depth was the best treatment. Between irrigation systems, amounts of 60% and 80% irrigation requirement don't have significant difference, but 40% irrigation requirement treatment, affected negatively on most of evaluated factors significantly. Therefore with regard to all evaluated factors in this research, subsurface drip irrigation with buried drip line at 30cm and 60% of irrigation requirement of pistachio in surface irrigation system, with water use efficiency of 0.290kg/m3 and 25% water saving in comparison with surface drip irrigation system, was the best treatment and recommended.
