Grey relational analysis and fuzzy synthetic discrimination of antioxidant components in peach fruit

Abstract

Free phenolic compounds and total phenolic content were quantified using four stages of four blood-flesh and four non-blood-flesh peach fruits. Data were used to assess the oxidation resistance using grey relational analysis and fuzzy synthetic discrimination methods. Data from equal-weight and weighted evaluations calculated using both grey relational analysis and fuzzy synthetic discrimination were very similar. The weighted relational grade and weighted evaluation value of the overall resistance to fruit oxidation were ordered according to the weight coefficient method, which demonstrated that there were discrepancies in the ranking of oxidation resistance of the tested varieties between early and late fruit developmental stages. During fruit development, the blood-flesh varieties showed a relatively high overall resistance to oxidation, with the highest observed in Beijingyixianhong. The results suggest that both grey relational analysis and fuzzy synthetic discrimination have high applicability in assessing the resistance to oxidation of peach varieties.

A combination of FDM, EWM, and GRA to measure performance in higher vocational college: An empirical case from China

“…Multi criteria problems can be effectively handled using GRA [ 49 ], and it assists ranking considering all quantitative criteria [ 50 ]. As it gradually matured, GRA has been widely applied as MCDM method to solve problems in many fields, such as international trade [ 51 ], project management [ 52 ], financial performance assessment [ 53 ], healthcare service [ 54 ], electricity power generation [ 55 ], quality of fruit [ 56 ], efficiency of public hospitals [ 57 ], etc.…”