Thumbnail Image

Theses

Browse

20231
Reset filters
Subject: Statistics × Author: Chetna × End date: 2023 × Start date: 2020 × Type: Thesis ×
Reset filters

Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    ThesisItemOpen Access
    A study on impact of climate change and statistical models for pre-harvest forecast of wheat-yield in Haryana
    (CCSHAU, Hisar, 2023-05) Chetna; Monika Devi
    This study aimed to improve the predictability of wheat yield in four districts of Haryana state using advanced statistical techniques. The best models for predicting weather variables were identified, and analyzed the impact of weather variables on crop yield during different growth stages. It was found that weather variables had varying effects on crop yield during different growth stages and across different districts. The observed positive effects of temperature on crop yield during the reproductive stages could be attributed to increased photosynthesis and growth rate of the crop, while the negative effects of temperature during the germination, milking, and harvesting stages could be due to increased plant stress and water loss. The study also found that the negative effects of rainfall on crop yield during certain growth stages could be attributed to waterlogging and soil compaction, while the positive effects of rainfall during certain growth stages could be due to increased soil moisture availability. The study developed models with high R2 values and low error values for predicting wheat yield in all four districts. Pre-harvest forecast models were developed to predict wheat yield before harvest in selected districts of Haryana, using discriminant function analysis and weekly meteorological variables. The models achieved high accuracy in correctly classifying the grouped cases in all districts, with varying effects of predictor variables and autocorrelation. The evaluation of various models for yield forecasting in different districts of Haryana State has yielded impressive results. Principal Component Analysis (PCA) was also utilized to investigate the impact of weather variables on the weather indices in various districts of Haryana State. The models showed a good fit with observed data and high accuracy in predicting yield, with different levels of complexity and performance depending on the district and the model used.