Monitoring of parasite Orobanche cumana using Vis-NIR hyperspectral imaging combining with physio-biochemical parameters on host crop Helianthus annuus

文献类型： 外文期刊

第一作者： Li, Juanjuan

作者： Li, Juanjuan;Farooq, Muhammad Ahsan;Huang, Qian;Zhou, Weijun;Pan, Tiantian;Liu, Fei;Xu, Ling;Najeeb, Ullah;Yun, Xiaopeng

作者机构：

关键词： Orobanche cumana; Sunflower; Vis-NIR hyperspectral imaging; Physio-biochemical parameters; Gene expression analysis

期刊名称：PLANT CELL REPORTS （ 影响因子：5.3； 五年影响因子：5.3 ）

ISSN： 0721-7714

年卷期： 2024 年 43 卷 9 期

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收录情况： SCI

摘要： Sunflower broomrape (Orobanche cumana Wallr.) is an obligate weed that attaches to the host roots of sunflower (Helianthus annuus L.) leading to a significant reduction in yield worldwide. The emergence of O. cumana shoots after its underground life-cycle causes irreversible damage to the crop. In this study, a fast visual, non-invasive and precise method for monitoring changes in spectral characteristics using visible and near-infrared (Vis-NIR) hyperspectral imaging (HSI) was developed. By combining the bands sensitive to antioxidant enzymes (SOD, GR), non-antioxidant enzymes (GSH, GSH + GSSG), MDA, ROS (O-2(-), OH-), PAL, and PPO activities obtained from the host leaves, we sought to establish an accurate means of assessing these changes and conducted imaging acquisition using hyperspectral cameras from both infested and non-infested sunflower cultivars, followed by physio-biochemical parameters measurement as well as analyzed the expression of defense related genes. Extreme learning machine (ELM) and convolutional neural network (CNN) models using 3-band images were built to classify infected or non-infected plants in three sunflower cultivars, achieving accuracies of 95.83% and 95.83% for the discrimination of infestation as well as 97.92% and 95.83% of varieties, respectively, indicating the potential of multi-spectral imaging systems for early detection of O. cumana in weed management.

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