Kuang Lixue, Wang Zhiqiang, Cheng Yang, Li Haifei, Li Jing, Shen Youming, Zhang Jianyi, Xu Guofeng
Research Institute of Pomology Chinese Academy of Agricultural Sciences, Xingcheng, Liaoning Province 125100, PR China.
Food Chem X. 2024 Jul 14;23:101643. doi: 10.1016/j.fochx.2024.101643. eCollection 2024 Oct 30.
Apple quality is closely related to its cultivar and origin. However, the apple quality characteristics of different cultivars and origins are unclear. The hypothesis that some quality indicators can effectively distinguish the cultivar and origin of apples. The result indicated that the discriminant accuracy of the models was above 90%, and the multilayer perceptron neural network (MLP-NN) model was superior to the linear discriminant analysis (LDA) model. The identification accuracy of cultivars was higher than origins. The main reason was that the single fruit weight, vitamin C, total soluble solid, soluble sugar, sweetness value, sorbitol, glucose, fructose, sucrose, malic acid, quinic acid and citric acid of 'Fuji' apples were significantly higher than 'Gala' apples. This study provides a foundation for the quality evaluation and further geographical traceability studies of apples. Further studies related to the regulatory mechanism of environmental conditions on apple quality characteristics should be explored for theoretical confirmation.
苹果品质与其品种和产地密切相关。然而,不同品种和产地苹果的品质特征尚不清楚。存在一些质量指标可以有效区分苹果品种和产地的假设。结果表明,模型的判别准确率在90%以上,多层感知器神经网络(MLP-NN)模型优于线性判别分析(LDA)模型。品种的识别准确率高于产地。主要原因是‘富士’苹果的单果重、维生素C、总可溶性固形物、可溶性糖、甜度值、山梨醇、葡萄糖、果糖、蔗糖、苹果酸、奎尼酸和柠檬酸显著高于‘嘎啦’苹果。本研究为苹果的品质评价和进一步的地理溯源研究提供了基础。应探索与环境条件对苹果品质特征调控机制相关的进一步研究以进行理论验证。