A STUDY ON IMPACT OF CLIMATE CHANGE ON WHEAT CROP YIELD AND DEVELOPMENT OF STATISTICAL MODELS FOR PRE- HARVEST FORECAST OF CROP - YIELD IN AYODHYA DISTRICT OF EASTERN U.P
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Date
2021-03-10
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ANDUAT, Kumarganj, Ayodhya
Abstract
The present investigation entitled “A Study on impact of climate change on Wheat crop yield and development of statistical models for pre- harvest forecast of crop - yield in Ayodhya district of eastern U.P” consists of five chapters including summary and conclusion. The purpose of the study is to develop statistical models for studying the relationship between weather variables and crop yield and to develop different forecast models based on discriminant function and principal component analysis.
Time series data on wheat crop yield and weekly data from 44th SMW of previous year to 11th SMW of the following year on seven weather variables viz., minimum temperature, maximum temperature, relative humidity at 7 hour, relative humidity at 14 hour, wind velocity rainfall and rainy days covering the period from 1990-1991 to 2016-2017 have been utilized to study the relationship wheat crop yield and weather variables and development of pre-harvest forecast model. In all, eight models have been developed to study the relationship between crop yield and weather variables. The model-V has been found to be the best for studying the relationship between crop yield and weather variables.
Statistical methodology using multiple regression, discriminant functions and principal component analysis for developing pre-harvest forecast model has been described. In all, 13 models (one based on regression, seven from discriminant function and six from principal component) have been developed for pre-harvest forecast model. The model-A is based on weather indices, D2 to D6 based on discriminant function and P1 to P2 based on principal component analysis have been developed. On the basis of Adjust R2, RMSE and PSE, the best three models for both technique obtained by the application of discriminant function and principal component analysis of weekly weather data are D2, D3 & D6 and P1, P2 & P3 respectively. These models can be used to get the reliable forecast of wheat one and half months before the harvest.
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