Although monitoring insect pest populations in the fields is essential in crop management, it is still a laborious and sometimes ineffective process. Imprecise decision-making in an integrated pest management program may lead to ineffective control in infested areas or the excessive use of insecticides. In addition, high infestation levels may diminish the photosynthetic activity of soybean, reducing their development and yield. Therefore, we proposed that levels of infested soybean areas could be identified and classified in a field using hyperspectral proximal sensing. Thus, the goals of this study were to investigate and discriminate the reflectance characteristics of soybean non-infested and infested with Bemisia tabaci using hyperspectral sensing data. Therefore, cages were placed over soybean plants in a commercial field and artificial whitefly infestations were created. Later, samples of infested and non-infested soybean leaves were collected and transported to the laboratory to obtain the hyperspectral curves. The results allowed us to discriminate the different levels of infestation and to separate healthy from whitefly infested soybean leaves based on their reflectance. In conclusion, these results show that hyperspectral sensing can potentially be used to monitor whitefly populations in soybean fields.

中文翻译：

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通过近距离感测监测大豆中的烟粉虱（Gennadius）（半翅目：无翅目）

尽管监视田间害虫的数量对作物管理至关重要，但这仍然是一个费力且有时无效的过程。有害生物综合治理计划中决策不准确可能会导致受感染地区的控制不力或过度使用杀虫剂。此外，高水平的侵染可能会降低大豆的光合作用活性，从而降低大豆的发育和产量。因此，我们建议可以使用高光谱近端感测技术在田间识别和分类侵染大豆的面积。因此，本研究的目的是调查和区分未感染和已感染烟粉虱的大豆的反射特性使用高光谱感应数据。因此，在商业领域中，将笼子放置在大豆植物上，并产生了人工粉虱侵扰。随后，收集受侵染和未侵染的大豆叶片样品，并将其运送到实验室以获得高光谱曲线。结果使我们能够区分出不同程度的侵染，并根据它们的反射率将健康的与粉虱侵染的大豆叶片分开。总之，这些结果表明，高光谱感测可以潜在地用于监测大豆田中的粉虱种群。