Enhancing anthracnose detection in mango at early stages using hyperspectral imaging and machine learning
Author:
Publisher
Elsevier BV
Subject
Horticulture,Agronomy and Crop Science,Food Science
Reference40 articles.
1. Recent advances on postharvest technologies of mango fruit: a review;Bambalele;Int. J. Fruit. Sci.,2021
2. Diversity of Colletotrichum species causing anthracnose disease from mango cv. Nam Dork Mai See Tong based on ISSR-PCR;Bincader;Indian J. Agric. Res.,2022
3. Spectral analysis for the early detection of anthracnose in fruit of sugar mango (Mangifera indica);Cabrera Ardila;Comput. Electron. Agric.,2020
4. The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation;Chicco;BMC Genom.,2020
5. Assessing mango anthracnose using a new three‐dimensional image‐analysis technique to quantify lesions on fruit;Corkidi;Plant Pathol.,2006
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