Author:
Wang Kunhua,Ren Wenxin,Jia Xiaoran,Xing Ying,Wang Youte,Wang Jun,Xu Huaide
Funder
Northwest A&F University
Shaanxi Provincial Science and Technology Department
Reference43 articles.
1. Detection of mulberry ripeness stages using deep learning models;Ashtiani;IEEE Access,2021
2. Relationship between fruit density and quality parameters, levels of sugars, organic acids, bioactive compounds and volatiles of two nectarine cultivars, at harvest and after ripening;Aubert;Food Chem.,2019
3. Evaluation of image processing technique as an expert system in mulberry fruit grading based on ripeness level using artificial neural networks (ANNs) and support vector machine (SVM;Azarmdel;Postharvest Biol. Technol.,2020
4. Ripeness indexes and physicochemical changes of papaya (Carica papaya L. cv. Maradol) during ripening on-tree;Barragán-Iglesias;Sci. Hortic.,2018
5. Color, flavor, texture, and nutritional quality of fresh-cut fruits and vegetables: desirable levels, instrumental and sensory measurement, and the effects of processing;Barrett;Crit. Rev. Food Sci. Nutr.,2010
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