Analysis Of Chlorophyll “A” And “B” In Randomly Selected Varieties Of Sugarcane Leaves Using Multivariate Analysis Of Variance.

Abstract

Abstract: Multivariate data needed to make rigorous probability statements about the effect of factors and their interaction in experiments. Multivariate statistical methods provide a useful test for analysis of rigorous data sets, because many variables integrated in one analysis. Chlorophyll "a" and "b" are indeed essential for the growth and development of sugarcane stalk. This paper presents multivariate analysis of variance of the chlorophyll content of the randomly selected varieties of sugarcane leaves. The data set obtained from a study conducted at National Cereal Research Institute (NCRI,) Badeggi in Niger State, Nigeria. The results show that there are statistical significant differences in both the seasons and the varieties of the sugarcane leaves in the chlorophyll contents.