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ARS Home » Southeast Area » New Orleans, Louisiana » Southern Regional Research Center » Commodity Utilization Research » Research » Publications at this Location » Publication #350591
Title: Rapid data analytics to relate sugarcane aphid [(Melanaphis sacchari (Zehntner)] population and damage on sorghum (Sorghum bicolor (L.) Moench)

Author
item Uchimiya, Sophie
item Knoll, Joseph - Joe

Submitted to: Scientific Reports
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/29/2018
Publication Date: 1/23/2019
Citation: Uchimiya, M., Knoll, J.E. 2019. Rapid data analytics to relate sugarcane aphid [(Melanaphis sacchari (Zehntner)] population and damage on sorghum (Sorghum bicolor (L.) Moench). Scientific Reports. 9:370. https://doi.org/10.1038/s41598-018-36815-0.
DOI: https://doi.org/10.1038/s41598-018-36815-0

Interpretive Summary: Sugarcane aphid pest has caused billions of dollars worth damage to the entire sorghum growing region of the United States in the past several years. Pest density and damage assessment is often highly subjective, and reliable statistical methods are in demand to accurately assess the impact, and to provide solution. This study developed new methods to interpret and extract useful information from field observation of pest damage. Developed methods can be widely applied to different pests and agricultural commodities, enabling steps to timely management of pest problems.

Technical Abstract: 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.