Analysis of Anthocyanin Components Based on Computer Image Recognition and Chromatography

Abstract

Anthocyanin is the main color-forming substance of mango peel, and bagging is an important technical measure to regulate the formation of fruit apparent color. In this paper, using 'Renong1' and 'Ono' as materials, combined with computer image recognition and liquid chromatography technology, the differences and accumulation characteristics of anthocyanins in the peel before and after bagging were compared. Using computer image recognition technology, the skin color of different mango varieties before and after bagging can be quickly screened and identified. Ten indicators such as second-order moment and third-order moment are used for feature extraction, and then the principal component analysis of the indicators is carried out through MATLAB, and the results are obtained. The results showed that five major anthocyanins could be identified in the peels of two different mango cultivars before and after bagging. For the two mango varieties, the accumulation patterns of anthocyanins after bagging were exactly opposite. Bagging of the light-dependent variety ‘Renong1’ inhibited the accumulation of anthocyanins in the peel, while ‘Ono’ accumulated anthocyanins after bagging, showing pigmentation independent of light. This indicates that the bagging technique can be used to breed new red mango varieties with more easily colored skins. This study provides a theoretical basis for the cultivation of new mango varieties, color metabolism and regulation research, and has important application value. At the same time, combined with computer image recognition technology, it provides a fast and efficient detection method for the preliminary screening of plant anthocyanin components.