Krishna Priya, S.R (2024) Yield Forecast of Sugarcane Using Two Different Techniques in Discriminant Function Analysis. Yield Forecast of Sugarcane Using Two Different Techniques in Discriminant Function Analysis, 97: 00064. pp. 1-8.

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Abstract

The present study aims to develop yield forecast models for the
Sugarcane crop of the Coimbatore district in Tamilnadu using two different
techniques namely Variables and Months in Discriminant function
analysis. For this, the Sugarcane yield data for 57 years along with the
monthly data on seven weather variables have been taken. For applying
discriminant analysis, the yield data of sugarcane has been divided into two
categories namely two groups and three groups. The discriminant scores
from the two and three-group discriminant functions were employed as
independent variables in the development of yield forecast models. The
yield forecast models for both strategies were created utilizing scores and
trend values as independent variables. The first 52 years of yield data
(1960-2012) were used to create the model, and the last five years of data
(2012-2016) were used for validation. The comparison has been made
between two and three groups for both techniques. The results indicate the
technique using the variable-wise method gives better results based on
goodness of fit. Among the two categories in the variable-wise method,
three groups performed better.

Item Type: Article
Divisions: PSG College of Arts and Science > Department of Statistics
Depositing User: Dr. B Sivakumar
Date Deposited: 13 Dec 2025 05:26
Last Modified: 13 Dec 2025 05:26
URI: https://ir.psgcas.ac.in/id/eprint/2595

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