Indian Society of Genetics & Plant Breeding

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MULTIPLE REGRESSION EQUATION AND SELECTION FOR GRAIN AND FODDER YIELD IN SORGHUM VULGARE

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With a view to formulate an index to aid breeding for high yield in forage sorghum,
multiple regression analysis was carried out to estimate the contributions made by
eight common independent component characters. The studies in the four
environments, showed· the characters: green fodder yield/plant, digestible dry
matter/plant and crude protein yield/plant contributed substantially to the
determination of dry matter yield/plant. Dry matter yield/plant, leaf/stem ratio and
panicle weight/plant were found to be most important characters in the determination
of green fodder yield/plant. Dry matter yield/plant exerted highest degree of influence
to the determination of digestible dry matter/plant. Seed yield/plant influenced
significantly to the determination of panicle weight/plant and vice versa was also
true.
The multiple correlation coefficients R in each case showed a high degree of goodness
of fit as indicated by as high as 72% to 99% of the variability for various dependent
characters in each of the fitted regression equations. The genetic upgrading of forage
productivity in combination with grain in sorghum requires the judicious combining
of the forage yield and forage quality components with seed yield compQnents as
indicated by multiple regression equations.
 

Keywords: Sorghum vulgare, forage sorghum, multiple correlation, standard partial regression coefficient

Info

Year: 1998
Volume: 58
Issue: 4
Article DOI: NA
Print ISSN: 0019-5200
Online ISSN: 0975-6906

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