Shrestha Kumar, Thapa Kantilata, Kaler Esha, Taniguchi Misaki, Sattler Scott E, Schnable James C, Louis Joe
Department of Entomology University of Nebraska-Lincoln Lincoln Nebraska USA.
Agricen Science Pilot Point Texas USA.
Plant Direct. 2025 Jul 8;9(7):e70092. doi: 10.1002/pld3.70092. eCollection 2025 Jul.
Current efforts to detect and evaluate crop resistance to insect pests are limited by traditional phenotyping methods, which are time-consuming and highly variable. Sugarcane aphid (SCA; ) is a major pest of sorghum in North America that has emerged over the last decade and negatively impacts plant growth and development. The spectral reflectance data in visible, near infrared and shortwave infrared range (VIS-NIR-SWIR; 400-2500 nm) have been used to measure plant traits related to stress responses, nutrient dynamics, and physiological status. We examined the potential of spectral features (VIS-NIR-SWIR) to improve the current phenotyping methods in monitoring sorghum resistance mechanisms to SCA. We used eight sorghum lines that displayed varied levels of resistance to SCA and collected data from control and aphid-infested plants. Spectral feature data were collected using a leaf spectrometer, while plant physiological and chlorophyll fluorescence parameters were measured with LICOR and MultispeQ devices. The random forest classifier model differentiated the control and aphid-infested plants with a high accuracy of 87.4% with important spectral features in the VIS-NIR spectral range, particularly from 508 to 573 nm and 715 to 728 nm. The spectral indices exhibit significant difference in Greenness Index and Plant Senescence Reflectance Index in aphid-infested susceptible lines (BTx623, SC1345) compared with control plants. In addition, plant physiological parameters, such as stomatal conductance and chlorophyll fluorescence, showed significantly higher value for aphid-infested resistant line (Tx2783) compared with susceptible line (BTx623) in both treatments. Further, a partial least square regression model demonstrated medium predictive capability for plant physiological parameters related to fluorescence. In summary, spectral features at VIS-NIR range demonstrated promising results in differentiating aphid-infested sorghum plants. This is a proof-of-concept study on potential of spectral sensing to develop an effective monitoring and phenotyping plant resistance to aphids.
目前用于检测和评估作物对害虫抗性的方法受到传统表型分析方法的限制，这些方法既耗时又具有高度变异性。甘蔗蚜（SCA）是北美高粱的主要害虫，在过去十年中出现，对植物生长和发育产生负面影响。可见、近红外和短波红外范围（VIS-NIR-SWIR；400-2500nm）的光谱反射率数据已被用于测量与胁迫反应、养分动态和生理状态相关的植物性状。我们研究了光谱特征（VIS-NIR-SWIR）在改进当前表型分析方法以监测高粱对SCA抗性机制方面的潜力。我们使用了八个对SCA表现出不同抗性水平的高粱品系，并从对照植株和蚜虫侵染植株中收集数据。使用叶片光谱仪收集光谱特征数据，同时使用LICOR和MultispeQ设备测量植物生理和叶绿素荧光参数。随机森林分类器模型以87.4%的高精度区分了对照植株和蚜虫侵染植株，重要光谱特征在VIS-NIR光谱范围内，特别是在508至573nm和715至728nm之间。与对照植株相比，受蚜虫侵染的感虫品系（BTx623、SC1345）的光谱指数在绿度指数和植物衰老反射率指数上表现出显著差异。此外，在两种处理中，与感虫品系（BTx623）相比，受蚜虫侵染的抗性品系（Tx2783）的植物生理参数，如气孔导度和叶绿素荧光，显示出显著更高的值。此外，偏最小二乘回归模型对与荧光相关的植物生理参数显示出中等预测能力。总之，VIS-NIR范围内的光谱特征在区分受蚜虫侵染的高粱植株方面显示出有前景的结果。这是一项关于光谱传感开发有效监测和表型分析植物对蚜虫抗性潜力的概念验证研究。
