Hyperspectral reflectance imaging for nondestructive evaluation of root rot in Korean ginseng (Panax ginseng Meyer)

Frontiers in Plant Science

Plant Science

Eunsoo Park¹  Mohammad Akbar Faqeerzada¹  Byoung-Kwan Cho²  Moon S. Kim³  Insuck Baek³  Yun-Soo Kim⁴ 

[1] Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, Daejeon, Republic of Korea;Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, Daejeon, Republic of Korea;Department of Smart Agricultural System, College of Agricultural and Life Science, Chungnam National University, Daejeon, Republic of Korea;Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, United States;R&D Headquarters, Korea Ginseng Corporation, Yuseong, Daejeon, Republic of Korea;

关键词: near-infrared hyperspectral imaging;    non-destructive measurement;    spectral analysis;    plant phenomics;    ginseng;    root rot;   

DOI  :  10.3389/fpls.2023.1109060

 received in 2022-11-27, accepted in 2023-01-18,  发布年份 2023

来源: Frontiers

【 摘 要 】

Root rot of Panax ginseng caused by Cylindrocarpon destructans, a soil-borne fungus is typically diagnosed by frequently checking the ginseng plants or by evaluating soil pathogens in a farm, which is a time- and cost-intensive process. Because this disease causes huge economic losses to ginseng farmers, it is important to develop reliable and non-destructive techniques for early disease detection. In this study, we developed a non-destructive method for the early detection of root rot. For this, we used crop phenotyping and analyzed biochemical information collected using the HSI technique. Soil infected with root rot was divided into sterilized and infected groups and seeded with 1-year-old ginseng plants. HSI data were collected four times during weeks 7–10 after sowing. The spectral data were analyzed and the main wavelengths were extracted using partial least squares discriminant analysis. The average model accuracy was 84% in the visible/near-infrared region (29 main wavelengths) and 95% in the short-wave infrared (19 main wavelengths). These results indicated that root rot caused a decrease in nutrient absorption, leading to a decline in photosynthetic activity and the levels of carotenoids, starch, and sucrose. Wavelengths related to phenolic compounds can also be utilized for the early prediction of root rot. The technique presented in this study can be used for the early and timely detection of root rot in ginseng in a non-destructive manner.

【 授权许可】

Unknown   
Copyright © 2023 Park, Kim, Faqeerzada, Kim, Baek and Cho