Identification for potato plant abiotic stress through thermal-RGB imaging based on deep learning

DongHwi Kwak; Hoonsoo Lee

doi:10.1117/12.3013642

7 June 2024 Identification for potato plant abiotic stress through thermal-RGB imaging based on deep learning

DongHwi Kwak, Hoonsoo Lee

Author Affiliations +

Proceedings Volume PC13060, Sensing for Agriculture and Food Quality and Safety XVI; PC1306008 (2024) https://doi.org/10.1117/12.3013642
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

Potatoes, often referred to as "earth apples," are globally cultivated crops known for their high vitamin C content, containing three times more vitamin C than apples, along with rich potassium and carbohydrates. While potatoes thrive in cold and harsh environments, they are susceptible to heat stress. Alarmingly, the International Potato Center predicts that ongoing global warming could lead to a significant decline of up to 68% in potato production by 2060. The primary goal of this research is to predict the Crop Water Stress Index (CWSI) in both the temperature gradient and conventional greenhouses and to classify stress conditions with transfer learning

Conference Presentation

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DongHwi Kwak and Hoonsoo Lee "Identification for potato plant abiotic stress through thermal-RGB imaging based on deep learning", Proc. SPIE PC13060, Sensing for Agriculture and Food Quality and Safety XVI, PC1306008 (7 June 2024); https://doi.org/10.1117/12.3013642

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