Response of CERES sorghum model for different agroclimatic conditions

Varshneya, M. C.; SABALE, None R.N.; BOTE, None N. L.; SALUNKE, S.S.; MORE, D. B.; THANEDAR, P.V.

doi:10.54386/jam.v6i1.706

Cited by 3 publications

(3 citation statements)

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“…However, there is a tendency for sorghum crop yield to increment with rainfall while declining with an increase in temperature. This study agrees with the study carried out by [23], which also documented that sorghum crop yield is inversely proportional to the change in temperature, while grain yield is directly proportional to the change in rainfall. The adjusted R-squared statistic of multiple regression revealed that the overall effect of month-based rainfall and temperature conditions during the growing period was 76.9% (Table 8), which indicated that five variables explained 76.9% of the variation in sorghum grain yield.…”

Section: Analysis Of Sorghum Grain Yield Response To Climate Variabilitysupporting

confidence: 92%

“…Here, the results of sorghum grain yield variability evaluated by inter-seasonal climate variability separately showed that changes in sorghum grain yield variability were influenced 15.6% differently with a correlation value of (+0.39) and 11.5% differently with a correlation value of (+0.34) due to September and August rainfall variability, respectively, whereas there was a 14.8% difference with a correlation value of (−0.39) and a 13.4% difference with a correlation value of (−0.37) due to the June minimum and May maximum temperature variability, respectively (Table 7). Similarly, this study agrees with the study carried out by [23], which also documented that sorghum crop yield has a negative relationship with temperature, while grain yield has a positive relationship with monthly rainfall.…”

Section: Correlation and Regression Of Sorghum Versus Its Growing Per...supporting

confidence: 92%

“…Mainly, unpredictable rainfall has a detrimental effect on crop production [22]. Similarly, the report stated by [23] also reported that sorghum phenology is inversely proportional to an increase in temperature, while grain yield is directly proportional to an increase in rainfall. More importantly, recurrent droughts frequently impact grain yield [24].…”

Section: Introductionmentioning

confidence: 93%

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Impacts of Climate Variability and Change on Sorghum Crop Yield in the Babile District of Eastern Ethiopia

Tolosa

Dadi²,

Mirkena

et al. 2023

Climate

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The impacts of various climatic conditions, such as temperature and rainfall variabilities, are very critical and sensitive to rain-fed crop production, particularly over the water stress arid and semi-arid regions of Ethiopia. This study was designed to evaluate the potential impact of climate variability and change on sorghum grain yield in the Babile district of eastern Ethiopia. The study was conducted based on observed and model-based simulated projected rainfall and temperature obtained from the Ethiopian Meteorological Institute and General Circulation Models (GCM) used by the Intergovernmental Panel on Climate Change (IPCC) of the Fifth Assessment Report CMIP5) and Agricultural Model Inter-comparison and Improvement Project (AgMIP). Three GCM models, namely GFDLESM2M, CanESM2, and HadGEM2-ES under RCP4.5, were considered to generate future climate projections for the near-term 21st century. Various univariate and multivariate statistical techniques were employed to compute and identify whether the impacts of climate variability and change on rain-fed sorghum crop performance were reasonably viable over the districts where grain yield is highly stable and productive under normal climate conditions. Our findings revealed that more stable and better rainfall performance from May to September, the season when sorghum crops are normally planted in the Babile district, was positively correlated, while the maximum and minimum temperatures of the season were negatively correlated with sorghum grain yield. A significant association has been detected between sorghum grain yield and its growing period rainfall, number of rainy days, and maximum and minimum temperature with multi-regression analysis. Thus, the variability of rainfall in August, June temperature, and the number of rainy days in September significantly impacted sorghum crop productivity. As a result, the multi-regression model adjusted R-squared indicated that 77% variance in annual sorghum yield performance was explained by rainfall and temperature conditions that prevailed during the crop growing period. During the past period, there was a significant increase in sorghum yields, which are projected to decline during the near term of the 21st century in the future. This revealed that declining and disturbed rainfall performance and increases in temperature are likely to reduce overall sorghum grain yield in the Babile district. We recommend that there is a need to enhance awareness for smallholder farmers on the adverse impact of climate variability and change on sorghum grain yield. In view of this, the farmers need to be geared toward employing climate-smart agriculture as a possible adaptation measure to reduce the negative impacts of climate variability and change on rain-fed crop production practices in the Babile district and other arid and semi-arid parts of eastern Ethiopia.

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Section: Analysis Of Sorghum Grain Yield Response To Climate Variabilitysupporting

confidence: 92%

Section: Correlation and Regression Of Sorghum Versus Its Growing Per...supporting

confidence: 92%

Section: Introductionmentioning

confidence: 93%

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Impacts of Climate Variability and Change on Sorghum Crop Yield in the Babile District of Eastern Ethiopia

Tolosa

Dadi²,

Mirkena

et al. 2023

Climate

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Simulated impacts of rise in temperature on kharif sorghum genotypes in Northern Transitional Zone of Karnataka, India

Sannagoudar

Patil

Kumar

et al. 2020

CEREAL RESEARCH COMMUNICATIONS

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Weather-Based Neural Network, Stepwise Linear and Sparse Regression Approach for Rabi Sorghum Yield Forecasting of Karnataka, India

et al. 2020

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Sorghum is an important dual-purpose crop of India grown for food and fodder. Prevailing weather conditions during the crop growth period determine the yield of sorghum. Hence, the crop yield forecasting models based on weather parameters will be an appropriate option for policymakers and researchers to develop sustainable cropping strategies. In the present study, six multivariate weather-based models viz., least absolute shrinkage and selection operator (LASSO), elastic net (ENET), principal component analysis (PCA) in combination with stepwise multiple linear regression (SMLR), artificial neural network (ANN) alone and in combination with PCA and ridge regression model are examined by fixing 90% of the data for calibration and remaining dataset for validation to forecast rabi sorghum yield for different districts of Karnataka. The R2 and root mean square error (RMSE) during calibration ranged between 0.42 to 0.98 and 30.48 to 304.17 kg ha−1, respectively, without actual evapotranspiration (AET) whereas, these evaluation parameters varied from 0.38 to 0.99 and 19.84 to 308.79 kg ha−1, respectively with AET inclusion. During validation, the RMSE and nRMSE (normalized root mean square error) varied between 88.99 to 1265.03 kg ha−1 and 4.49 to 96.84%, respectively without AET and including AET as one of the weather variable RMSE and nRMSE were 63.48 to 1172.01 kg ha−1 and 4.16 to 92.56%, respectively. The performance of six multivariate models revealed that LASSO was the best model followed by ENET compared to PCA_SMLR, ANN, PCA_ANN and ridge regression models because of reduced overfitting through penalisation of regression coefficient. Thus, it can be concluded that LASSO and ENET weather-based models can be effectively utilized for the district level forecast of sorghum yield.

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Response of CERES sorghum model for different agroclimatic conditions

Cited by 3 publications

References 0 publications

Impacts of Climate Variability and Change on Sorghum Crop Yield in the Babile District of Eastern Ethiopia

Impacts of Climate Variability and Change on Sorghum Crop Yield in the Babile District of Eastern Ethiopia

Simulated impacts of rise in temperature on kharif sorghum genotypes in Northern Transitional Zone of Karnataka, India

Weather-Based Neural Network, Stepwise Linear and Sparse Regression Approach for Rabi Sorghum Yield Forecasting of Karnataka, India

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