Volume 8, Issue 5, October 2020, Page: 177-184
Identification and Cluster Analysis of Sweet Corn Based on Grain Textural Properties
Xiangnan Li, Institute of Maize and Featured Upland Crops, Zhejiang Academy of Agricultural Sciences, Dongyang, P. R. China
Guihua Lv, Institute of Maize and Featured Upland Crops, Zhejiang Academy of Agricultural Sciences, Dongyang, P. R. China
Jianjian Che, Institute of Maize and Featured Upland Crops, Zhejiang Academy of Agricultural Sciences, Dongyang, P. R. China
Zhenxing Wu, Institute of Maize and Featured Upland Crops, Zhejiang Academy of Agricultural Sciences, Dongyang, P. R. China
Guojin Guo, Institute of Maize and Featured Upland Crops, Zhejiang Academy of Agricultural Sciences, Dongyang, P. R. China
Received: Sep. 22, 2020;       Accepted: Oct. 9, 2020;       Published: Oct. 16, 2020
DOI: 10.11648/j.jps.20200805.20      View  11      Downloads  6
Abstract
The edible qualities are crucial factors for quality of Fresh-eating sweet Corn. However, the research of the edible quality at the milking stage remains largely ambiguous in sweet corn. To identify phenotypes and classify genotypes via principal component analysis and cluster analysis, the textural properties of the grain of 51 sweet corn varieties in regional tests were measured by texture analyzer. The results showed that there was high genetic variation and diversity in the grain textural properties (hardness, springiness, cohesiveness, adhesiveness, chewiness, resilience, gumminess) between the 51 sweet corn varieties. Among the variation in these textural properties, the variation in adhesiveness was the greatest, and the variation in cohesiveness was the smallest; the variation ranges were 1.145~18.190 and 0.126~0.253, respectively. There were very significantly positive relationships between hardness, cohesiveness, chewiness and gumminess; the correlation coefficients were greater than 0.783. However, no significant correlation between resilience and the other traits was observed. According to principal component analysis (PCA), the above seven textural characteristics were governed by three independent principal components. The per cent contributions of the variance of the three independent principal components were 54.656%, 15.814% and 14.737%. Hardness, springiness and resilience were the dominant factors affecting the textural properties of the sweet corn grain. According to systematic cluster analysis, the 51 sweet corn varieties could be classified into 2 groups based on their hardness values, and group 1 could be further classified into 3 subgroups based on the values of springiness and resilience. These results indicated that significant genetic differences exist in the textural properties of sweet corn grain and provided useful information for improving the edible quality of sweet corn.
Keywords
Sweet Corn, Textural Properties, Principal Component Analysis, Cluster Analysis
To cite this article
Xiangnan Li, Guihua Lv, Jianjian Che, Zhenxing Wu, Guojin Guo, Identification and Cluster Analysis of Sweet Corn Based on Grain Textural Properties, Journal of Plant Sciences. Vol. 8, No. 5, 2020, pp. 177-184. doi: 10.11648/j.jps.20200805.20
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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