author(s)
AA Bhandare, DD Khedkar, SK Ghodke, NJ Danawale, MS Mane and VS Patil

abstract
The analysis of experiment entitled “Evaluation of Aqua Crop model for potato crop” carried out using resulted data of field experiment for rabi season in 2020-21, 2021-22 and 2022-23 (Chavan, 2023 and Golande, 2024) [2, 7] at the Demonstration-cum-Research Farm of the Interfaculty Department of Irrigation Water Management, Mahatma Phule Krishi Vidyapeeth, Rahuri. This study aimed to calibrate and validate the FAO Aqua Crop model for potato crop using a factorial randomized block design with nine treatments and four replications. The Aqua Crop model was calibrated using data from 2020-21 and 2021-22, focusing on canopy cover, biomass, and yield, and validated with 2022-23 data. Calibration of AquaCrop model was done using three parameters i.e canopy cover, biomass and tuber yield. The calibration of the model for the rabi season of 2020-21 revealed a good fit for canopy cover (CC) with a coefficient of determination R2 = 0.92, Root mean square error = 0.96, index of agreement = 0.96, and Mean Absolute error = 0.05, good prediction for biomass (R2 =0 .90, RMSE = 0.25, d(IA) = 0.90, MAE = 0.01) and good prediction for yield (R2 =0 .88, RMSE = 0.19, d(IA) = 0.99, MAE = 0.01). The calibration of the model for the rabi season of 2021-22 revealed a good fit for canopy cover (CC) with a coefficient of determination R2 = 0.93, Root mean square error = 0.95, index of agreement = 0.96, and Mean Absolute error = 0.05, good prediction for biomass (R2 =0.89, RMSE = 0.21, d(IA) = 0.89, MAE = 0.01) and good prediction for yield (R2 =0 .84, RMSE = 0.25,d(IA) = 0.86, MAE = 0.01). The validation of the Model for rabi season of 2022-23 revealed a good fit for Biomass (R2 = 0.89, (RMSE) = 0.21, d (IA) = 0.92, MAE = 0.01) good prediction for yield (R2 =0 .81, RMSE = 0.24, d(IA) = 0.88, MAE = 0.01).The model slightly overestimated biomass and yield due to climatic influences but remained within acceptable limits. Aqua Crop model is considered a useful tool in predicting Canopy cover, biomass and yield.