Alfalfa yield prediction by some vegetative indices and environmental variables in Southern Khorasan:Case study of Sarayan

This study was conducted to predict alfalfa forage yield based on some climatic, soil and vegetative indices (PVI) derived from Sentinel-2 sensor in Sarayan (Southern Khorasan) of Iran in July 2018. Alfalfa yield data were collected from 52 points (10 of those experimental points) in two consecutive harvests to predict alfalfa performance, a stepwise multivariate linear regression was used. Results showed that the alfalfa performance map, in both consecutive harvests, with the mean of rainfall, PVI index and soil class was significant at 1% probability level. Validation showed that R2, RMSE and GMER were 0.82, 0.88 and 0.91, respectively, indicating the high compliance of the estimated performance model with the actual yield of alfalfa. Also, the results of chi-square test (P = 0.99) showed non-significant difference between actual values and estimated hay yield during two harvests. Therefore, due to the high reliability of terrestrial observations and climatic data in the region, these variables can be used to provide proper utilization pattern for forage plants.