R. Jeyajothi S. Pazhanivelan M. Saravana kumar N. Vinothini A. Indhushree S. Ramadass S. Marimuthu


Crop modelling can make it easier for researchers to comprehend and describe experimental results and pinpoint yield disparities. In this competition, the impact of pigeonpea growth and yield under various fertigation levels was examined using the
Decision Support Systems for Agrotechnology Transfer 4.6 (DSSAT) and CROPGRO pigeonpea models. Under drip fertigated levels, the cultivars received various nutrient doses. The pigeonpea model developed by DSSAT-CROPGRO successfully
simulated measured pigeonpea grain yield. The field trials took place in Coimbatore at the millet breeding facility of the Tamil Nadu Agricultural University. The study ran the GLUE coefficient estimator to estimate the cultivar coefficients until it had a good match between the predicted and observed seed yield. The accuracy of the model was measured by calculating its R-squared, RMSE, NRMSE, and Agreement percentage. According to model simulation and field measurements, drip fertigation at 125% RDF via WSF + Azophosmet and foliar spray of 1% PPFM resulted in the highest seed output of 1875 kg ha-1(V1F5) over both years. The increase in seed yield with drip fertigation at 125% RDF via WSF + Azophosmet and foliar spray of 1% PPFM (V1F5) was 8.0 - 11.0% when compared to drip fertigation at 100% RDF via WSF + Azophosmet and foliar spray of 1% PPFM (V1F4)12.9 - 16.1 % compared to drip fertigation at 100% RDF through WSF; and 68.0 - 74.3 % compared to conventional fertilizer. It was indicated that the DSSAT v.4.6 can be a helpful tool for determining and forecasting pigeonpea growth yield if it is appropriately calibrated. Simulation models substantially facilitated maximizing crop growth and generating management advice.





CROPGRO pigeon pea model, Drip fertigation , DSSAT, Genetic co-efficients

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Research Articles

How to Cite

Evaluation of DSSAT CROPGRO model on growth and yield of pigeonpea cultivars under different fertigation levels. (2023). Journal of Applied and Natural Science, 15(3), 1071-1079. https://doi.org/10.31018/jans.v15i3.4740