Author(s)

Xiuhua Liang, Guangming Deng, Bin Yan^*

College of Science, Guilin University of Technology, Guilin, China.

Utilizing principal component analysis (PCA) and cluster analysis, the standardization, dimension-reduction and de-correlation of multiple evaluation index system for fruit and vegetable nutrition are performed to assign principal component factor based on cluster analysis of loading matrix and combining with actual meaning and evaluation direction of index categories. To evaluate the richness of its nutrition according to the score of nutrition of fruit and vegetable, finally equivalent replacement suggestions are given in different seasons of vegetables & fruits according to the result of clustering. Studies show that principal component cluster method can not only carry on the reasonable classification of multivariate data effectively, but also make reasonable evaluation on the sample object, and provide powerful basis for evaluation of fruits and vegetables’ nutrition.

Principal Component Analysis, Cluster Analysis, Multivariate, Classification

Liang, X. , Deng, G. and Yan, B. (2015) Fruit and Vegetable Nutrition Value Assessment and Replacement Based on the Principal Component Analysis and Cluster Analysis. Applied Mathematics, 6, 1620-1629. doi: 10.4236/am.2015.69144.