EFFECT OF DIFFERENT BIOCHEMICAL TRAITS ON SEED COTTON YIELD: AN APPLICATION OF LIU LINEAR
REGRESSION
M. Qasim1,4, M. Amin2 and M. K. S. Sarwar3
1Department of Statistics
and Computer Science, University of Veterinary and Animal Sciences, Lahore, Pakistan.
4Department of
Economics, Finance and Statistics, Jönköping University, Jönköping, Sweden.
2Department of Statistics,
University of Sargodha, Pakistan.
3National Institute
for Biotechnology & Genetic Engineering, Faisalabad, Pakistan.
3Cotton research station,
Ayub agricultural research institute, Faisalabad, Pakistan.
Corresponding Author’s Email: muhammad.qasim@uvas.edu.pk;
qasim.stat@gmail.com
ABSTRACT
This article aimed
to study the associations among the biochemical traits and their effects on seed
cotton yield using the regression analysis and to assess the alternative approach
for reducing the impact of multicollinearity problem in estimating the regression
coefficients. The field experiment was conducted where five explanatory variables
(chlorophyll ‘a’, chlorophyll ‘b’, total chlorophyll, total soluble
protein and total soluble sugar) and one dependent variable seed cotton yield were measured.
The correlation matrix of showed that biochemical traits were
significantly correlated. The multicollinearity problem among the biochemical traits
was determined by condition index and correlation matrix. Using the least square
regression analysis, the effects of biochemical traits on seed cotton yield were
not satisfactory since least square regression model has high value of MSE (3352475), AIC (366.7) and
inconsistent estimates of traits. The Liu regression analysis was efficient (MSE
= 57212 and AIC = 363.8) and reliable in reducing the adverse
effects of multicollinearity. The Liu regression results indicated that total
chlorophyll and total soluble protein were contributed a significant (p-value <
0.05) role in seed cotton yield. In contrast, ordinary least square regression analysis
was showed insignificant (p-value > 0.05) effect of total chlorophyll on seed
cotton yield.
Key words: Seed Cotton Yield,
Biochemical Traits; Multicollinearity; Least Squares Regression Analysis; Liu Linear
Regression.
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