文章基本信息

标题：Fruit quality prediction based on soil mineral element content in peach orchard
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作者：Hailong Sun ; Xiao Huang ; Tao Chen 等
期刊名称：Food Science & Nutrition
电子版ISSN：2048-7177
出版年度：2022
卷号：10
期号：6
页码：1756-1767
DOI：10.1002/fsn3.2794
语种：English
出版社：John Wiley & Sons, Ltd.
摘要：Abstract Mineral nutrition of orchard soil is critical for the growth of fruit trees and improvement of fruit quality. In the present study, the effects of soil mineral nutrients on peach fruit quality were studied by using artificial neural network model. The results showed that the four established ANN models had the highest prediction accuracy (R2 = .9735, .9607, .9036, and .9440, respectively). The results of prediction model sensitivity analysis showed that available B, Ca, N, and K in the soil had the greatest influence on the single fruit weight, available Fe, K, B, and Ca in the soil had the greatest effect on fruit soluble solid content, available Ca, N, B, and K in the soil had the greatest influence on the fruit titratable acid content, and available Ca, Fe, N, and Mn in the soil had the greatest effect on fruit edible rate. The response surface methodology analysis determined the optimal range of these mineral elements, which is critical for guiding precision fertilization in peach orchards and improving peach fruit quality.