Identification and Cluster Analysis of Sweet Corn Based on Grain Textural Properties
Journal of Plant Sciences
Volume 8, Issue 5, October 2020, Pages: 177-184
Received: Sep. 22, 2020;
Accepted: Oct. 9, 2020;
Published: Oct. 16, 2020
Views 156 Downloads 57
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
Follow on us
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.
Sweet Corn, Textural Properties, Principal Component Analysis, Cluster Analysis
To cite this article
Identification and Cluster Analysis of Sweet Corn Based on Grain Textural Properties, Journal of Plant Sciences.
Vol. 8, No. 5,
2020, pp. 177-184.
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.
James M, Robertson D, Myers A. Characterization of the maize gene sugary1, a determinant of starch composition in kernels. Plant Cell. 1995; 7: 417–429.
Feng Z, Liu J, Fu F, Li W. Molecular mechanism of sweet and waxy in maize. Intl J Plant Breed Genet. 2008; 2: 93–100.
Khanduri A, Prasanna B, Hossain F, Lakhera P. Genetic analysis and association studies of yield components and kernel sugar concentration in sweet corn. Indian J Genet. 2010; 70: 257–263.
Khanduri A, Hossain F, Lakhera P, Prasanna B. Effect of harvest time on kernel sugar concentration in sweet corn. Indian J Genet. 2011; 71: 231–234.
Tracy W, Shuler S, Dodson-Swenson H. Sweet corn [M]// The physiology of vegetable crops. 2020.
FAOSTAT. 2014. http://faostat.fao.org.
Liang Q, Yin Y. The cultivation technology of sweet corn. Yun Nan Agriculture. 2002; 000 (003): 9–11. (in Chinese).
Ni Y. Study on the development of sweet corn industrialization in Huizhou. Zhongkai University of Agriculture and Engineering. 2018. (in Chinese).
Liu P, Wang C, Wang F, et al. Changes of quality components in waxy corn kernels after pollination. Scientia Agricultural Sinica. 2007; 40 (8): 1817–1821. (in Chinese).
Lin F, Jiang Z, Liao S. Texture analyzer and its application in food quality evaluation. Life Sciences and Scientific Instruments. 2009; (5): 61–63. (in Chinese).
Kuang F, Liu Q, Cao Q, Feng Y. Application of texture analyzer in food industries. Food Science and Technology. 2020; (03): 112–115. (in Chinese).
Bourne M. Food texture and viscosity. New York: Academic Press, 2002: 254–262.
Zhan X, Zheng T, Tao J. Study on application of texture analyzer in quality evaluation of Rice. Journal of Food Science. 2007; 28 (9): 62–65. (in Chinese).
Chang s, Li D, Lan Y, Ozkan N. Study on creep properties of japonica cooked rice and its relationship with rice chemical compositions and sensory evaluation. International Journal of Food Engineering. 2009; 5 (3): 1–16.
Chauvin M, Ross C, Pitts M, Kupferman E, Swanson B. Relationship between instrumental and sensory determination of apple and pear texture. Journal of Food Quality. 2010; 33 (2): 181–198.
Karamizadeh S, Abdullah S, Manaf A, Zamani M, Hooman A. An overview of principal component analysis. Journal of Signal and Information Processing. 2013; 4 (3B): 173–175.
Zhang Y, Liu J, Zhou X, et al. Study on the correlation between instrument evaluation and sensory evaluation of rice palatabilit. Journal of grain processing. 2015; 040 (003): 26–30. (in Chinese).
Hu Y. Application Situation of Texture Analyzer in the Study of Food. Food Research and Development. 2013; 000 (011): 101–104. (in Chinese).
Farcuh M, Copes B, Le-Navenec G, et al. Texture diversity in melon (Cucumis melo L.): Sensory and physical assessments. Postharvest Biology and Technology. 2020; 159: 111024.
Flores D, Giovanni M, Kirk L, et al. Capturing and explaining sensory differences among organically grown vegetable-soybean varieties grown in Northern California: Capturing and explaining sensory difference. Journal of Food Science, 2019; 84 (3): 613–622.
Sun H. Study on rheological properties evaluation system of instant corn. Jilin Agricultural University. 2011. (in Chinese).
Lu B, Dong H, Xu L, et al. Relationship between water content and physical properties and quality of sweet corn at different harvesting periods. Acta Agriculturae Boreali-sinica. 2019; 34 (S1): 69–77. (in Chinese).
Lu D, Wang X, Yan B, et al. Genotypic difference and principal component analysis for grain textural properties of fresh waxy Maize. Journal of Food Science. 2013; (21): 16–19. (in Chinese).
Zhao F, Jing L, Yan B, et al. Genotypic difference in textural properties of sweet corn grain. Jiangsu Journal of Agricultural Science. 2013; 29 (1): 14–19.