Table 1_Crop simulation-based assessment of yield gaps and water productivity for improving blackgram (Vigna mungo L.) production across diverse ecologies of India.docx

Blackgram (Vigna mungo L.), a nutritionally and ecologically important pulse crop in India, remains constrained by climatic stress, moisture limitations, and suboptimal agronomic management. To identify pathways for sustainable intensification, the APSIM model was employed to simulate potential yield (Yp), quantify yield gaps, and assess water productivity across twenty major blackgram-growing districts of India during 2003-2023. Simulations integrated long-term weather data, soil profiles, region-specific management practices, and cultivar-specific genetic coefficients, while water productivity was evaluated using physical (PWP), irrigation (IWP), and economic (EWP) indices. Observed yields (280–1040 kg ha-1) were consistently lower than simulated potential yields (840–1176 kg ha-1), revealing yield gaps ranging from 5 to 67%, with an average gap of about 515 kg ha-1. Central Zone districts exhibited the widest gaps, whereas rice-fallow systems in the South Zone showed relatively higher productivity and economic water returns. Model performance was robust, with high accuracy during calibration and validation (R2 and NSE ≈ 0.97-0.99; RMSE ≤20%; NMSE<0.05). District-level carbon budgeting revealed blackgram to be a consistent net carbon sink, with carbon efficiency ranging from 7.05-9.69 and a mean CSI of 7.21. Principal Component Analysis identified nutrient-water coupling (N, P, and irrigation), soil organic carbon, and yield components as dominant drivers of yield variability, while correlation-density matrix analysis highlighted strong interdependence among reproductive traits and trade-offs with crop geometry. Bridging yield and water productivity gaps through climate-resilient varieties, optimized crop geometry, precision irrigation, and targeted policy support can substantially enhance blackgram productivity and resource-use efficiency.