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Visible and near-infrared spectroscopy for detection of powdery mildew in Cucurbita pepo L. leaves
Journal of Applied Remote Sensing ( IF 1.4 ) Pub Date : 2020-12-02 , DOI: 10.1117/1.jrs.14.044515
Claudia Angelica Rivera-Romero 1 , Elvia Ruth Palacios-Hernández 2 , Monica Trejo-Durán 3 , Maria del Carmen Rodríguez-Liñán 4 , Roberto Olivera-Reyna 5 , Jorge Alberto Morales-Saldaña 6
Affiliation  

Abstract. Cucurbits plants are very susceptible to fungal diseases as powdery mildew (PM) infection. Currently, the PM early detection in the field is the cutting-edge research. The objectives of our study were to assess visible and near-infrared spectroscopy of normal and infected leaves for early detection of PM in Cucurbita pepo L. plants. Samples for spectral analysis were taken three days a week (Monday, Wednesday, and Friday) after the first true leaves appeared. The reflectance spectra of leaves were collected using an HR4000CG-UV-NIR spectrometer (Ocean Optics) with a fiber optics probe. Vegetative indices were used for discrimination between infected and healthy plants. The calculated vegetation indices (green normalized difference vegetation index, triangular greenness index, single-band reflectance index, simple ratio indices, and anthocyanins reflectance index) showed the highest sensitivity to differentiate healthy, infected plants at a symptomless stage, first symptoms, and diseased plants. The best prediction on early detection in sampling days were structure-independent pigment index and red-edge reflection point with an R of 0.211 and 0.1893, respectively. Our study shows the efficacy of the identification based on reflectance spectra for an early distinction of PM disease and could be used in cucurbits plants with similar characteristics on leaves.

中文翻译:

用可见光和近红外光谱检测西葫芦叶中的白粉病

摘要。葫芦科植物非常容易受到真菌病害,如白粉病 (PM) 感染。目前,该领域的PM早期检测是前沿研究。我们研究的目的是评估正常和受感染叶片的可见光和近红外光谱,以便早期检测 Cucurbita pepo L. 植物中的 PM。在第一片真叶出现后,每周三天(周一、周三和周五)采集用于光谱分析的样本。使用带有光纤探头的 HR4000CG-UV-NIR 光谱仪(Ocean Optics)收集叶子的反射光谱。营养指数用于区分受感染植物和健康植物。计算的植被指数(绿色归一化差异植被指数、三角绿度指数、单波段反射指数、简单比率指数、和花青素反射指数)显示出区分健康、受感染植物在无症状阶段、初期症状和患病植物方面的最高敏感性。采样日早期检测的最佳预测是与结构无关的色素指数和红边反射点,R 分别为 0.211 和 0.1893。我们的研究显示了基于反射光谱的识别对 PM 疾病早期区分的有效性,并可用于具有相似叶子特征的葫芦科植物。分别。我们的研究显示了基于反射光谱的识别对 PM 疾病早期区分的有效性,并可用于具有相似叶子特征的葫芦科植物。分别。我们的研究显示了基于反射光谱的识别对 PM 疾病早期区分的有效性,并可用于具有相似叶子特征的葫芦科植物。
更新日期:2020-12-02
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