Abstract
In this paper, the kinds and contents of amino acids in Cordyceps sinensis from different habitats of Tibet components using principal component analysis and cluster analysis, the principal component cluster analysis to evaluate the nutritional value of different localities, and provide scientific basis for the further research and development and utilization of Cordyceps resources in Tibet area. The principal component analysis method is a method of using the central idea of dimensionality reduction, the analysis method of multi indicators into a multivariate data several comprehensive index of a few statistics. The principal component analysis method can guarantee the minimizing loss of original data information, with less comprehensive variables instead of multiple variables of the original. Cluster analysis can be used to classify samples of multiple variables by using comprehensive information, the classification results are intuitive, clustering dendrogram clearly show the results of numerical classification, clustering analysis results than the traditional classification method is more detailed, comprehensive, reasonable.
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Zhao, X. et al. (2019). Application of Principal Component Cluster Analysis in the Quality of Cordyceps Sinensis. In: Li, D. (eds) Computer and Computing Technologies in Agriculture X. CCTA 2016. IFIP Advances in Information and Communication Technology, vol 509. Springer, Cham. https://doi.org/10.1007/978-3-030-06155-5_27
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DOI: https://doi.org/10.1007/978-3-030-06155-5_27
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