Pre harvest forecast models of rice yield based on weather variables for Eastern agro-climatic zone of Haryana using Discriminant function analysis
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Date
2019
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CCSHAU
Abstract
The present investigation entitled “Pre harvest forecast models of rice yield based on weather variables for Eastern agro-climatic zone of Haryana using Discriminant function analysis” 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 analysis.
Time series data on rice yield and weekly data from 22nd Standard Meteorological Week (SMW) to 41th SMW of on five weather variables viz., minimum temperature, maximum temperature, relative humidity, wind velocity and sun shine hour covering the period from 1996-1997 to 2016-2017 have been utilized for development of pre-harvest forecast model and the remaining two-year 2016-17 and 2017-18 yield data was used to validate the models. Statistical methodology using multiple regression and discriminant functions for developing pre-harvest forecast models has been described. The Model-1 is based on weather indices and rests are based on discriminant functions. The model 9 is proposed one. These models can be used to get the reliable forecast of rice yield about one and half months prior to the harvest.
In all, nine models have been developed to study the relationship between crop yield and weather variables. The model-3(R2 =85.8%, Adjust R2=83.1%, PED =1.15 & 1.04 for 2016-17 & 2017-18 respectively) has been found to be the best for studying the relationship between crop yield and weather variables. Model 6 & Model 9 also exposes chances for better forecast. Therefore, these models also can be recommended for pre-harvest forecast of the rice yield in practice.
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