Park Eunsoo, Kim Yun-Soo, Faqeerzada Mohammad Akbar, Kim Moon S, Baek Insuck, Cho Byoung-Kwan
Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, Daejeon, Republic of Korea.
R&D Headquarters, Korea Ginseng Corporation, Yuseong, Daejeon, Republic of Korea.
Front Plant Sci. 2023 Feb 1;14:1109060. doi: 10.3389/fpls.2023.1109060. eCollection 2023.
Root rot of caused by , 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.
由一种土壤传播的真菌引起的人参根腐病，通常通过频繁检查人参植株或评估农场中的土壤病原体来诊断，这是一个耗时且成本高昂的过程。由于这种病害给人参种植户造成了巨大的经济损失，因此开发可靠且无损的早期病害检测技术非常重要。在本研究中，我们开发了一种用于早期检测根腐病的无损方法。为此，我们利用作物表型分析，并分析了使用高光谱成像（HSI）技术收集的生化信息。将感染根腐病的土壤分为灭菌组和感染组，并播种一年生人参植株。在播种后第7至10周期间收集了4次HSI数据。对光谱数据进行分析，并使用偏最小二乘判别分析提取主要波长。在可见/近红外区域（29个主要波长）平均模型准确率为84%，在短波红外区域（19个主要波长）为95%。这些结果表明，根腐病导致养分吸收减少，进而导致光合活性以及类胡萝卜素、淀粉和蔗糖水平下降。与酚类化合物相关的波长也可用于根腐病的早期预测。本研究中提出的技术可用于以无损方式早期及时检测人参根腐病。
