Charcoal rot is one of the most destructive fungal diseases of soybean, caused by the pathogen called Macrophomina phaseolina . This disease thrives in warm and dry conditions, affecting the yield of soybean and other important agronomic crops. Existing methods used to screen the disease suffer from several drawbacks including, manual rating, low accuracy, high operating time, and high system complexity. To circumvent these drawbacks, we developed a laser biospeckle based sensor to characterize the charcoal rot in soybean crop. Applicability of the proposed sensor was tested to analyze three major aspects of plant disease management, viz. characterization of disease progression, early identification of disease symptoms, and analysis of genetic resistance of the given cultivar towards the disease. The experiments were conducted during Kharif season for two consecutive years (2019 and 2020) on two cultivars of soybean, namely, JS 90–41 and AMS-MB-5-18. The proposed sensor as well as standard rating protocol (i.e. measuring the length of necrosis) were used to analyze the extent of disease. To characterize the disease progression and the genetic resistance of different cultivars against M. phaseolina , two new metrics, charcoal rot severity index and disease susceptibility index were introduced. Biospeckle activity was found to be strongly correlated with the lesion length of infected plant stems ( $\text {r} = {+}0.96$ , $\text {p} < .01$ , two-tailed (for JS 90-41) and ( $\text {r} = {+}0.95$ , $\text {p} < .01$ , two-tailed (for AMS-MB-5-18) for the year 2019; and $\text {r} = {+}0.97$ , $\text {p} < .01$ , two-tailed (for JS 90-41) and $\text {r} = {+}0.93$ , $\text {p} < .01$ , two-tailed (for AMS-MB-5-18) for the year 2020). Experimental results clearly indicate that the proposed sensor can be used as an efficient tool to detect the disease in its early stages of pathogen development. This study provides insights into development and implementation of disease control measures for increasing soybean crop production.

中文翻译：

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基于生物斑点的传感器，用于表征大豆（甘氨酸最大（L.）Merr。）作物中的木炭腐烂（Macrophomina Phaseolina（Tassi）Goid）病

木炭腐烂是大豆中最具破坏性的真菌病之一，由病原体引起 巨噬性菜豆 。该病在温暖和干燥的条件下繁盛，影响大豆和其他重要农艺作物的产量。用于筛查疾病的现有方法具有多个缺点，包括手动评级，低准确性，高操作时间和高系统复杂性。为了克服这些缺点，我们开发了基于激光生物散斑的传感器来表征大豆作物中的木炭腐烂。测试了拟议传感器的适用性，以分析植物病害管理的三个主要方面，即。疾病进展的特征，疾病症状的早期识别以及给定品种对疾病的遗传抗性分析。实验是在哈里夫两个大豆品种，即JS 90–41和AMS-MB-5-18，连续两年（2019年和2020年）。所提出的传感器以及标准的评估方案（即测量坏死的长度）用于分析疾病的程度。表征疾病进展和不同品种对玉米的遗传抗性菜豆 引入了两个新指标，即木炭腐烂严重程度指数和疾病易感性指数。发现生物斑点活性与受感染植物茎的病灶长度密切相关（ $ \ text {r} = {+} 0.96 $ ， $ \ text {p} <.01 $ ，两尾（针对JS 90-41）和（ $ \ text {r} = {+} 0.95 $ ， $ \ text {p} <.01 $ ，两尾（适用于AMS-MB-5-18），适用于2019年; 和 $ \ text {r} = {+} 0.97 $ ， $ \ text {p} <.01 $ ，两尾（针对JS 90-41）和 $ \ text {r} = {+} 0.93 $ ， $ \ text {p} <.01 $ ，两尾（适用于AMS-MB-5-18），适用于2020年）。实验结果清楚地表明，所提出的传感器可以用作在病原体发展的早期阶段检测疾病的有效工具。该研究为提高大豆作物产量的疾病控制措施的开发和实施提供了见识。