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Plant Science Today (PST)

Research Articles

Early Access

Calibration of genetic coefficients for blackgram using DSSAT-CROPGRO model

DOI
https://doi.org/10.14719/pst.10421
Submitted
3 July 2025
Published
11-12-2025

Abstract

Blackgram is an important pulse crop in India, but abiotic stresses and poor management often limit its productivity. This study, for the first time, optimized genetic coefficients for 12 blackgram genotypes, providing a valuable resource for accurate simulation and crop modelling applications. Crop simulation models such as Decision Support System for Agrotechnology Transfer (DSSAT-CROPGRO) are valuable tools for evaluating varietal responses under diverse environmental conditions. However, accurate simulation requires genotype-specific genetic coefficients, which are largely unavailable for blackgram, limiting the effective application of such models. To address this gap, we calibrated and validated the CROPGRO-Drybean model under rainfed conditions during the Kharif season (2022-23) at the Main Agricultural Research Station (MARS), University of Agricultural Sciences (UAS), Dharwad. Genetic coefficients were optimized for 12 blackgram genotypes (DBG-5, DBG-19, DBG-31, DBG-33, DBG-34, DBG-93, DBG-16, DBG-96, DBG-90, DBG-95, DBG-61 and DU-1) using 3 replicated datasets from two sowing dates (May 30 and June 27) for calibration and the remaining two other sowing dates (June 13 and July 18) for validation. Results showed that simulated values closely matched with observed data, with deviations within ± 10 %. Phenological deviations ranged from 0 % to + 2.4 % for anthesis and - 1.3 % to + 1.3 % for maturity, while grain yield deviations ranged from - 3.1 % to + 5.8 %. Model performance was further supported by low root mean squared error (RMSE) values (0 - 1.41 days for phenology, 16.97 - 127.28 kg ha-1 for yield) and consistently high index of agreement (d = 0.889 – 1.0).

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