Show Author Affiliation

Olufelo, J.O.

Department of Crop Production, University of Agriculture and Environmental Sciences Umuagwo, Owerri, Imo- State, Nigeria.

*Corresponding Author: jolufelo@yahoo.com

ABSTRACT

Digital imaging is a fast and reliable method for cultivar identification and discrimination. Computer seed digital imaging was utilized in this study to evaluate the differences in seed metric traits in ten genotypes of mung bean as affected by the seed production environment. A hundred seeds in each of the mung bean genotypes were subjected to digital imaging analysis using the ‘WinSEEDLE™’ software to differentiate the seed metric characters. For every replication, a hundred seeds were placed on the lighting hood in such a way that the embryo axis of the seed faces the image analysis system and the longitudinal axis runs parallel to the surface of the scanner. Seeds were automatically analyzed by the scanner and the image of the seed was recorded by the ‘WinSEEDLE™’. The procedure of hundred seeds placement on seed digital image was repeated three times for each genotype. The parameters observed were seed area, straight length, curve length, straight width, curve width, width length, and seed perimeter. Scan data collected from ‘WinSEEDLE™’ were subjected to analysis of variance and principal component analysis. The result revealed that the Mung bean genotypes evaluated were highly variable in all the seed metric traits evaluated. The study recommended that attention should be given to genotypes and seed production environments in the seed production of Mung bean. Genotypes Tvr-73, Tvr-27, Tvr-98, and Tvr-78 have been identified with consistent and high seed morphometric characteristic performance for most of the attributes examined, hence, can be important criteria in selecting superior seed physical traits and could be used as parental material, in the development of high seed yielding varieties.

Keywords: Genotypes, seed imaging, seed metric, seed quality, seed scanner, Mung bean

Cite this article as:


Olufelo, J.O., 2022. Effect of Environment on Morphometric Characteristics of Mung bean (vigna radiata (L.) Genotypes through Seed Digital Imaging Analysis. Nigerian Journal of Environmental Sciences and Technology, 6(2), pp. 362-369. https://doi.org/10.36263/nijest.2022.02.0384

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