Correlation-Based Analysis of Weighted and Unweighted Weather Indices for Pear Yield in Kashmir

Abstract

Pear is an important temperate fruit crop in the Kashmir Valley, where climatic variability poses serious challenges to horticultural productivity. This study investigated the relationship between pear yield and weekly weather variables, maximum and minimum temperature, rainfall, sunshine hours, and relative humidity over a 39 year period (1985–2023). Using meteorological data from the Indian Meteorological Department (IMD) and yield records from the Directorate of Economics and Statistics, a correlation analysis based on both unweighted and weighted weather indices was conducted using Pearson’s method. The findings revealed that weighted weather indices exhibited stronger correlations with pear yield than unweighted indices, highlighting their superior predictive efficiency. Among the main weather variables, rainfall (Z31) and relative humidity (Z51) emerged as the most influential, while interaction-based weighted indices such as Z231 and Z351 showed particularly high correlations (r > 0.60). Visual tools such as correlation heatmaps and bar plots further confirmed the strength and direction of these associations. These findings offers valuable insights for developing climate-resilient orchard management strategies and contributes to improving yield prediction tools in horticultural crops