Hosna Fayazi; Ebrahim Zeinali; Afshin Soltani; Benyamin Torabi
Abstract
Global climate change is among the most important agricultural and food security challenges. This study tries to investigate the effect of climate change on potential yield and water productivity of forage maize (Zea mays L.) in Iran. Two scenarios of RCP4.5 and RCP8.5 are used to predict the future ...
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Global climate change is among the most important agricultural and food security challenges. This study tries to investigate the effect of climate change on potential yield and water productivity of forage maize (Zea mays L.) in Iran. Two scenarios of RCP4.5 and RCP8.5 are used to predict the future climate (2050s) and climate data of 2001-2015 have been used as the base period. Potential yield is estimated using SSM-iCrop2 model according to the GYGA protocol and the climate changes for both scenarios are applied in the model. The results show that the climate change will not have a considerable effect on forage maize yield compared to the current conditions (85.6 ton ha-1) and will only lead to an increase of 0.9% and 1.6% in on both scenarios, respectively. This may be attributed to maize being a C4 plant and thus non-effectiveness of CO2 increase on its growth. Also, the temperature will remain in optimum range for maize in most of the main regions for forage maize cultivation areas in Iran. Water productivity in both scenarios will increase by 0.4% and 1.6%, compared to current conditions (10.4 kg m-3), respectively, which may be due to increased CO2 concentration and more closure of stomata. Also, improved water productivity in forage maize may be attributed to increase yield potential due to the fact that no considerable changes are observed in terms of the required water, evapotranspiration and irrigation times.
raheleh arabameri; afshin soltani; Ebrahim Zeinali; benyanen torabi
Abstract
Yield gap analysis is a quantitative estimate of possible increase of the capacity to provide food for a specified area. It is an important component for designing strategies to supply food on a scale of regional, national, and global level. In this regard a study has been conducted to determine the ...
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Yield gap analysis is a quantitative estimate of possible increase of the capacity to provide food for a specified area. It is an important component for designing strategies to supply food on a scale of regional, national, and global level. In this regard a study has been conducted to determine the extent and function of chickpea and lentil crop vacancy distribution at Gorgan University of Agricultural Sciences and Natural Resources during 2016-2018. Using SSM-iCrop2 model, the study simulates potential yield in chickpea and lentil producing regions in Iran. For this purpose, it employs the protocol of Atlas Gap Project, called GYGA protocol, to identify climatic zones and identify important meteorological stations, located in chickpea and lentil production areas in the country. After identifying the important stations, the performance potential for the station range is simulated and then the regional results are generalized to the whole country, based on the GYGA protocol. For dryland chickpeas in the country, the values of actual and potential yield as well as yield gap have been 0.43, 1.04, and 0.61 tons per hectare, respectively. In case of rainfed lentils in the country, the values of actual yield and potential along with yield gap have been 0.43, 1.10, and 0.67 tons per hectare, respectively. The present study can be used for better management in low-yield and high-yield areas of the country for these two products.
Fatemeh salmani; afshin soltani; Ebrahim Zeinali; Hossein Shahkoomahali
Abstract
In order to simulate transplantation, the parameters related to cotton seedling growth are firstly measured in a factorial experiment in a randomized complete block design at Gorgan University of agricultural sciences and natural resources within 2018. The parameters are then utilized in SSM-iCrop2 Model. ...
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In order to simulate transplantation, the parameters related to cotton seedling growth are firstly measured in a factorial experiment in a randomized complete block design at Gorgan University of agricultural sciences and natural resources within 2018. The parameters are then utilized in SSM-iCrop2 Model. In the simulation section, four seedling size based on the leaf area (namely 17, 22, 27, and 37 cm-2 per plant) are evaluated in 4 planting dates (15 June, 1 July, 15 July, and 30 July). Results show that in early planting date, seedling transplantation rushes the process of crop maturation for 43 to 49 days. However, this has had no significant effect on yield values (from 453 to 461 g/m2) and net water requirement (312 to 316 mm). The usual sowing date causes the crop to mature between 27 and 38 days (earlier vacant land), whereas seed sowing at this planting date impairs the subsequent crop cultivation. At this planting date, as in early planting, transplanting has no strong effect on the yield (from 444 to 452 g/m2) and water requirement (299 to 308 mm). In a late planting date, seedling transplanting with four seedling sizes between 1 and 5 days results in premature seed germination, even though seed cultivation impairs subsequent planting. At this planting date, transplanting has a noticeable effect on the yield (361 to 441 g/m2), but the amount of pure irrigation (271 to 300 mm) remains unaffected by transplanting.
Benjamin Torabi; Najebullah Ebrahimi; Afshin Soltani; Ebrahim Zeinali
Abstract
The present study was conducted to parameterize the SSM_iCrop model and evaluate the prediction of growth and development of faba bean in Gorgan climate condition. This study was carried out on faba bean cv."Barkat" as split-plot in randomized complete block design with four replications at Gorgan University ...
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The present study was conducted to parameterize the SSM_iCrop model and evaluate the prediction of growth and development of faba bean in Gorgan climate condition. This study was carried out on faba bean cv."Barkat" as split-plot in randomized complete block design with four replications at Gorgan University of Agricultural Sciences and Natural Resources in 2015-2016. The experimental factors consisted of planting date (27 November, 25 December and 31 January) and plant density (5, 15, 25 and 35 plants/m2). The parameters of phonological stages, leaf expansion and senescence, production and distribution of dry matter and water balance were estimated using the present data experiment and other data. The results of model evaluation showed that, it can well predict, days to flowering (RMSE = 3.8 and CV =4.1), days to maturity (RMSE = 11.9 and CV= 8.1), node number on main stem (RMSE = 1.7 and CV = 10.0), leaf area index (RMSE =0.8 CV =28.8), biological yield (RMSE = 158.5 and CV =21.6) and seed yield (RMSE = 118.6 and CV = 24.7). Therefore, the SSM_iCrop model can be used to evaluate the agronomic management and analyze the growth and yield of faba bean in Gorgan conditions.
Reyhane Rabbani; Farshid Ghaderi-Far; Ebrahim Zeinali; afshin soltani
Abstract
In order to investigate the effect of row spacing on yield and growth of cotton cultivars uncer two conditions of fertilizer application and non-fertilization, a study was conducted in Gorgan as a split-factorial experiment based on randomized complete blocks design with three replicates in 2017. Experimental ...
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In order to investigate the effect of row spacing on yield and growth of cotton cultivars uncer two conditions of fertilizer application and non-fertilization, a study was conducted in Gorgan as a split-factorial experiment based on randomized complete blocks design with three replicates in 2017. Experimental factors included three cotton cultivars (Sajedi, Kashmar and Golestan), row spacing at two levels (20 and 80 cm) and nitrogen, phosphorus and potassium fertilizers application at 350, 300 and 225 kg ha-1 and control treatment (No fertilizer), respectively. According to the results of analysis of variance, the effect of cultivar on number of reproductive branches and bolls as well as the height of first boll from ground was significant, whereas row spacing significantly affected number of vegetative branches and bolls, the height of first boll from ground, boll weight and lint yield. In all three cultivars studied, decrease in row spacing led to decreased plant height and increased leaf area index, dry matter and lint yield. Fertilization led to significant increase in plant height, leaf area index, number of reproductive branches and bolls, boll weight and yield. Among interactions, only the interaction of cultivar× row spacing on number of reproductive branches and interaction of row spacing× fertilizer on boll number, boll weight and lint yield were significant. Therefore, there is a significant interaction between row spacing and nutrient consumption in terms of growth characteristics and yield of cotton cultivars, and decreased row spacing in cotton can significantly increase lint yield.