VGG-MFO-orange for sweetness prediction of Linhai mandarin oranges.

ABSTRACT: Mandarin orange is a popular fruit in China and known worldwide for its unique flavor and nutritional benefits. As consumer demand for fruit quality increases, the fine assessment and grading of fruit sweetness-especially through non-destructive testing techniques-are becoming increasingly important in agriculture and commerce. In this paper, a new Attention for Orange (AO) attention mechanism and Multiscale Feature Optimization (MFO) feature extraction module are designed and combined with VGG13 convolutional neural network (CNN), innovatively proposed VGG-MFO-Orange CNN model for accurately classifying mandarin oranges with different sweetness. First, a sample of Linhai mandarin oranges was collected, and a sweetness triple classification dataset with 5022 images was formed, utilizing im

SUBMITTER: Fang C 

PROVIDER: S-EPMC11973220 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature