Using the AquaCrop model to simulate sesame performance in response to superabsorbent polymer and humic acid application under limited irrigation conditions

Mahallati, Mehdi Nassiri; Jahan, Mohsen

doi:10.1007/s00484-020-02001-z

Cited by 6 publications

(3 citation statements)

References 39 publications

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“…The AquaCrop model showed a fair performance in simulating the canopy cover evolution and biomass accumulation. The length of developmental stages determined by the model which is based on the FAO 56 stages, showed a slight difference with four calibrated stages for sesame [38]. The standard error of the means (SEM) for simulated canopy cover at the time of reaching the maximum canopy growth coefficient, flowering and the maximum canopy cover was more than the SEM at the time of canopy senescence.…”

Section: Plos Climatementioning

confidence: 93%

“…Crop management data including planting date, plant density, fertilizer management, irrigation, date of occurrence of phenological stages and duration of each stage, and harvest date, were obtained from 10 field experiments conducted at the research farm of Ferdowsi University of Mashhad, in addition to two experiments conducted by the authors in 2015 and 2016 during sesame growing season (May to October). The full description of the weather data, experimental design, planting and management, sampling, measurement and calculations were provided by Nassiri-Mahallati & Jahan [38].…”

Section: Field Experimentsmentioning

confidence: 99%

“…This is because plant parameters have different values under different conditions and their values depend on farm management factors as well (Table 3). The AquaCrop required parameters for the study area conditions have already been tuned, calibrated and validated [38]. In addition to the data measured at field experiments in the present study, data from 10 experiments on sesame between 2010 and 2018, all of which were conducted at the research farm of Ferdowsi University of Mashhad (as the same site of the present study), were used for tuning of crop parameters to local conditions.…”

Section: Tuning Of Crop Model Parameters To Local Conditionsmentioning

confidence: 99%

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Modeling the response of sesame (Sesamum indicum L.) growth and development to climate change under deficit irrigation in a semi-arid region

Jahan

Mahallati

2022

PLOS Clim

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The future climate outlook was based on a combination of CCMs based on three Representative Concentration Pathway (RCP) scenarios including RCP 2.6, RCP 4.5 and RCP 8.5 for the future period of 2021–2051. The results showed an increase of the average Tmax in June, July and August (averaged by 1.8°C compared to the observed period) and a decrease in rainfall in May to September (averaged by 30.76 mm compared to the observed period under all three scenarios. Estimation of phenological stages of sesame under different scenarios showed that with increasing Tmax in April and May, the beginning of flowering, grain filling and physiological maturity was accelerated, also with increasing temperature from June to August the duration of the phenological stages was decreased. The effect of deficit irrigation (DI, supplying of 50% plant water requirement) on sesame phenological stages was not significantly different from full irrigation (FI). Simulation of canopy cover evolution (CC) and dry matter accumulation using the AquaCrop model revealed that the length of the late-season and the mid-season stages, have the greatest liability to be changed under the future climate change. Under the studied scenarios, the beginning of sesame growing season will accelerate from 9 to 11 days, which makes possible delayed sowing of sesame. The average of biomass (B) produced under three scenarios in DI and FI conditions were 17920 and 17241 kg ha-1, and the average of grain yield (GY) was 2905 and 3429 kg ha-1, respectively, which shows an increase by 31.5% and 28.7% of B, 18.4% and 39.5% of GY, compared to the observations (year 2016). The results revealed that under the future climate (except for RCP8 scenario), DI strategy can be used without reducing the GY of sesame due to the very little reduction (1.2%) in GY under DI compared to FI.

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Section: Plos Climatementioning

confidence: 93%

Section: Field Experimentsmentioning

confidence: 99%

Section: Tuning Of Crop Model Parameters To Local Conditionsmentioning

confidence: 99%

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Modeling the response of sesame (Sesamum indicum L.) growth and development to climate change under deficit irrigation in a semi-arid region

Jahan

Mahallati

2022

PLOS Clim

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Identification of climatic and management factors influencing wheat’s yield variability using AgMERRA dataset and DSSAT model across a temperate region

Farhadi,

Bannayan,

Fallah

et al. 2024

Discov Life

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One of the main challenges of today’s agriculture to ensure food security is developing strategies to deal with potential negative impacts of adaptation to climate variability. This study was conducted to determine climatic and management factors influencing wheat yield variability throughout a temperate region in Northeastern Iran in the period of 1980–2010. The growth stages and yield of wheat crop were simulated via DSSAT model, using AgMERRA gridded weather dataset. Also, the effect of climatic variables on yield was identified using Panel Data Regression (PDA). According to the results, 63% of the changes in irrigated wheat yield are explained by climatic factors (temperature and precipitation) and 37% by management factors. PDA revealed that among the climatic variables, the number of days with temperatures above 30 °C during the growing season, mean temperature, as well as amount and frequency of precipitation have a significant effect on irrigated wheat yield (p ≤ 0.05). The management practices, including provision of inputs such as chemical fertilizers, modified seeds, tillage machinery and equipment, information transfer and the penetration of knowledge in the field, would increase yields by 5 kg on average per year in study region. In general, employing effective management methods, in particular selecting the appropriate planting date that could result in better adaptation of the phenological stages of wheat to climatic conditions, thus improving the wheat yield. The results of this research suggest that use of valid AgMERRA meteorological dataset as input for DSSAT crop model could produce reliable simulations which in turn could be employed by food policy and decision makers, farmers, and managers in a temperate region.

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Nutritional Management Improved Sesame Performance and Soil Properties: a Function-Based Study on Sesame as Affected by Deficit Irrigation, Water Superabsorbent, and Salicylic Acid

Jahan

Javadi

Hesami

et al. 2021

J Soil Sci Plant Nutr

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To assess and investigate the effects of application of superabsorbent polymer (SAP) and salicylic acid (SA) on performance of drought-affected sesame (Sesamum indicum L.), soil characteristics, and water productivity of irrigation (WPi). A randomized complete block design with split-strip plot arrangement and three replications in two successive cropping years was arranged. Two levels of irrigation consisting of supplying 50% and 100% of the sesame water requirement (deficit irrigation, DI and full irrigation, FI, respectively) were allocated to the main plots, and application of SAP (80 kg ha −1 ) was allocated to the subplots. Foliar application of SA (1 mM) and control was allocated to the strip plots. The results showed that the highest seed yield (SY) was obtained from DI, along with SAP and SA application. Under drought stress (DI), separate and simultaneous applications of SAP and SA increased WPi by 42% (SAP), 36% (SA), and 43% (SAP + SA), respectively, compared with control. The highest WPi was achieved through DI plus SAP application, which was 60% more than combination treatment of FI plus no-application of SAP. The results of principal component analysis (PCA) indicated that SY, seed weight per plant (SW), crop growth rate (CGR), and WPi were the effective variables of the first principal component (PC) and explained 67% of the total variance of the data. The nutritional management was effective in reducing drought stresses; moreover, the highest SY and biological yield (BY), CGR, the total amount of soil nitrogen (Soil N), and WPi were obtained in the simultaneous application of SAP and SA.

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Using the AquaCrop model to simulate sesame performance in response to superabsorbent polymer and humic acid application under limited irrigation conditions

Cited by 6 publications

References 39 publications

Modeling the response of sesame (Sesamum indicum L.) growth and development to climate change under deficit irrigation in a semi-arid region

Modeling the response of sesame (Sesamum indicum L.) growth and development to climate change under deficit irrigation in a semi-arid region

Identification of climatic and management factors influencing wheat’s yield variability using AgMERRA dataset and DSSAT model across a temperate region

Nutritional Management Improved Sesame Performance and Soil Properties: a Function-Based Study on Sesame as Affected by Deficit Irrigation, Water Superabsorbent, and Salicylic Acid

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