Calibration and Validation of CERES-Wheat Model for Wheat Varieties under Raipur District of Chhattisgarh

Abstract


 The current study "Calibration and validation of CERES-Wheat model for wheat varieties under Raipur district of Chhattisgarh" was carried out in the Department of Agrometerology, IGKV, Raipur, for which a field experiment was done at the college of Agriculture's farm field Raipur at latitude of 21.25’ N, longitudes 81.62’E and altitude 289.5 m above mean sea level. Along with 3 wheat variety (Kanchan, HD2967 and CG1013) and three growing environment D1 (26th Nov), D2 (06th Dec) and D3 (16th Dec). This paper aimed to Genetic co-efficient of three wheat varieties determined and calibration & validation the DSSAT model. Result of study revealed that closer estimation of Validation shows days to anthesis, days to maturity and grain yields % of error and Root mean square erro (RMSE) observed values were 2.8%, 2.8%, 4.2% of error and 1.41%,1.41%, 2.12% RMSE in D1, D2, D3 for Kanchan variety and HD2967 were observed 1.4%, 4.1%, 5.6% of error and 0.71%, 2.12%, 2.83% of RMSE respectively. CG1013 observed in 1.4%, 4.2%, 7.0% of error and 0.71%, 2.12%, 3.54% RMSE respectively. Days to maturity observed in 2.7%, 6.5%, 8.6% of error and 2.12%, 4.93%, 6.36% RMSE in D1, D2, D3 for Kanchan variety and HD2967 were observed 2.7%, 1.8%, 7.4% of error and 2.12%, 1.41%, 5.66% RMSE respectively. CG1013 observed values were 0.9%, 4.7%, 7.7% and RMSE observed were 0.71%, 3.54%, 5.66% respectively. Grain yield observed were 3.9%, 1.1%, 0.6% of error and 81.32%, 21.92%, 11.31% RMSE in D1, D2, D3 for Kanchan variety and HD2967 were observed 2.7%, -2.1, 0.8% and 47.38%, 31.82%, 12.02% of RMSE respectively. CG1013 observed in 0.8%, 4.1%, 0.5% and 17.68%, 84.85%, 9.90% RMSE respectively. The model has been successfully calibrated and validated for wheat growing in Raipur, Chhattisgarh environment and can now it can be taken for further applications in natural resources management and climate change impact studies. The model performance was evaluated using % of error and RMSE and it was observed that DASST CERES model was able to predict the growth parameters like days to anthsis, day to maturity and grain yield with reasonably good accuracy (error% less than 10).

Yield Prediction in Maize ( ) using Weather Parameters Zea Mays under Subtropical and Intermediate Regions of North-Western Himalayas

“…Weather indices: The best agro meteorological indices to incorporate in the agro meteorological yield forecast model at F and F stage in maize crop was Tmax (Z11), T min (Z21), 2 3Tmax X Tmin (Z121), Tmin XRF (Z230),RF X RH II (Z350). In Udhampur district, the best agro meteorological indices at F 2 (pre flowering stage) and F (pre harvesting stage) were 3 Tmax (Z11), RH II(Z51), Tmax X Tmin (Z121), Tmax X RH II (Z141), RFXRH I(Z 341) and RF XRH II(Z351).Similar, results were also reported byPatel et al (2018). The validation of results of statistical model during 2020 kharif and results reported that the percent deviation in maize yield at F stage was 2.57 percent and 9.15percent in Jammu and 2 Udhampur district whereas at F stage the percent deviation 3 in maize yield in Jammu and Udhampur district were -3.00…”