USDA-ARS Southern Regional Research Center, 1100 Robert E. Lee Boulevard, New Orleans, LA, 70124, USA.
USDA-ARS Crop Genetics and Breeding Research Unit, 115 Coastal Way, Tifton, GA, 31793, USA.
Sci Rep. 2019 Jan 23;9(1):370. doi: 10.1038/s41598-018-36815-0.
Sugarcane aphid [(Melanaphis sacchari (Zehntner)] emerged in the United States in 2013 as a new pest infesting sorghum (Sorghum bicolor (L.) Moench). Aphid population and plant damage are assessed by field scouting with mean comparison tests or repeated regression analysis. Because of inherently large replication errors from the field and interactions between treatments, new data analytics are needed to rapidly visualize the pest emergence trend and its impact on plant damage. This study utilized variable importance in the projection (VIP) and regression vector statistics of partial least squares (PLS) modeling to deduce directional relationships between aphid population and leaf damage from biweekly field monitoring (independent variable) and chemical composition (dependent variable) of 24 sweet sorghum cultivars. Regardless of environment, aphid population increase preceded the maximum damage rating. Greater damage rating at earlier growth stage in 2015 than 2016 led to an overall higher damage rating in 2015 than 2016. This trend in damage coincided with higher concentrations of trans-aconitic acid and polyphenolic secondary products in stem juice in 2016 than 2015, at the expense of primary sugar production. Developed rapid data analytics could be extended to link phenotypes to perturbation parameters (e.g., cultivar and growth stage), enabling integrated pest management.
甘蔗绵蚜[(Melanaphis sacchari (Zehntner)]于 2013 年在美国出现,成为一种新的甘蔗害虫。通过田间巡查进行蚜虫种群和植物损害评估,采用均值比较检验或重复回归分析。由于田间固有的大复制误差以及处理之间的相互作用,需要新的数据分析方法来快速可视化害虫出现趋势及其对植物损害的影响。本研究利用投影变量重要性(VIP)和偏最小二乘(PLS)模型的回归向量统计,从双周田间监测(自变量)和 24 个甜高粱品种的叶片损伤(因变量)的化学成分中推导出蚜虫种群和叶片损伤之间的定向关系。无论环境如何,蚜虫种群的增加都先于最大损害等级。2015 年比 2016 年更早的生长阶段更大的损害等级导致 2015 年的总体损害等级高于 2016 年。这种损害趋势与 2016 年比 2015 年茎汁中转-乌头酸和多酚类次生产物浓度更高有关,这会影响到主要糖的产生。开发的快速数据分析方法可以扩展到将表型与干扰参数(如品种和生长阶段)联系起来,从而实现综合虫害管理。