Applicability of medium range weather forecasts for yield prediction of wheat (Triticum aestivum) using CERES-wheat model in south-western Punjab - SINGH, TIRATH; PAL, R K; KINGRA, P K; KAUR, RAMANJIT; SANYAM; DHIR, ABHISHEK (The Indian Journal of Agricultural Sciences, 2025)
The study was carried out during the winter (rabi) season of 2021–22 at Punjab Agricultural University, Regional Research Station, Bathinda, Punjab to evaluate the predictability of wheat (Triticum aestivum L.) production using forecast scenarios that were gathered from the India Meteorological Department (IMD). CERES-wheat model was used to estimate crop phenology and wheat yield. The experiment was laid out in a split-plot design (SPD) with three replications. The main plot treatments included five sowing dates, viz. October 25, November 4, November 14, November 24 and December 4 with four sub-plot treatments of variety which were HD 3086, PBW 725, HD 2967 and PBW 658. The model’s output with R2/RMSE for emergence, anthesis and maturity by using actual and forecasted data having 0.38/3.37 and 0.48/2.63, 0.56/4.28 and 0.70/8.48 and 0.71/8.30 and 0.49/2.63, respectively. Moreover, the wheat yield with R2/RMSE values of 0.85/148.31 kg/ha for the actual data and 0.86/140.50 kg/ha for the simulated data showed good agreement between simulated and observed data. Model validation showed that simulated emergence, anthesis and maturity were deviated over observed by 1–3 days, 1–8 days, and 1–20 days, respectively, whereas anthesis, maturity and yield were overestimated. Additionally, the simulated wheat yield differed from the observed yield by 0.5–12%. Phenology and yield were found to have greater RMSE values, wider deviations between simulated and actual values and less connection with delayed sowing. For the wheat growing season (2013–21), rainfall, Tmax and Tmin weather forecast were employed, which were to assess the likelihood of wheat production at various sowing periods. The medium-range weather forecast and the actual weather data closely matched each other for wheat phenology and yield. The annual fluctuation in observed wheat yields as well as treatment-wise variations was more or less effectively reflected by the daily medium-range weather forecast data. The findings of the study are extremely valuable for directing decisions in the study area, figuring out the best time to sow wheat crop, choosing appropriate wheat varieties based on predicted conditions, scheduling irrigation at critical growth stages and applying fertiliser optimally to increase crop productivity and resource efficiency.