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利用荧光、热成像和 NDVI 成像的特征检测生菜中的生物胁迫。

The Use of Features from Fluorescence, Thermography, and NDVI Imaging to Detect Biotic Stress in Lettuce.

机构信息

Leibniz-Institute of Vegetable and Ornamental Crops Großbeeren and Erfurt, Theodor-Echtermeyer-Weg 1, 14979, Großbeeren, Germany.

出版信息

Plant Dis. 2018 Jun;102(6):1101-1107. doi: 10.1094/PDIS-10-17-1536-RE. Epub 2018 Apr 9.

Abstract

Fluorescence, normalized difference vegetation index, and thermal imaging are three frequently used nondestructive methods to detect biotic stress in plants. Due, in part, to the inconsistent results reported in the literature and the lack of measurements on the whole-plant scale, we tested the suitability of a wide variety of variables obtained using these three imaging methods to classify young plants into biotically stressed and nonstressed plants. To this end, we applied the model plant-pathogen system lettuce-Rhizoctonia solani. The relevant data from each image and plant (healthy and diseased) was extracted semiautomatically using sophisticated image processing algorithms. This method enabled us to identify the most appropriate variables via discriminant function and logistic regression analysis: photosystem II maximum quantum yield (F/F) and fluorescence decline ratio can be used to classify variables with an error ≤0.052. Lettuce seedlings with an F/F ratio > 0.73 were consistently healthy. In some cases, it was possible to detect infection prior to the appearance of symptoms. Possibilities to transfer the method to horticultural practice are discussed.

摘要

荧光、归一化差异植被指数和热成像是三种常用于检测植物生物胁迫的非破坏性方法。部分由于文献中报道的结果不一致以及缺乏全植物尺度的测量,我们测试了使用这三种成像方法获得的各种变量来对生物胁迫和非胁迫的幼株进行分类的适宜性。为此,我们应用了模式植物-病原菌系统生菜-腐霉。使用复杂的图像处理算法,从每个图像和植物(健康和患病)中提取相关数据。该方法使我们能够通过判别函数和逻辑回归分析识别最合适的变量:光合系统 II 最大量子产量(F/F)和荧光下降比可用于以 ≤0.052 的错误率对变量进行分类。F/F 比 > 0.73 的生菜幼苗始终保持健康。在某些情况下,甚至有可能在出现症状之前检测到感染。讨论了将该方法转移到园艺实践中的可能性。

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