Characterization and multivariate analysis of engineering properties of red sunflower seed weevil-infested achenes

Authors: JAMMEH, PA - North Dakota State University; Prasifka, Jarrad; Hulke, Brent; BERTI, MARISOL - North Dakota State University; SUN, XIN - North Dakota State University; MONONO, EWUMBUA - North Dakota State University

Submitted to: Journal of Agriculture and Food Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/3/2026
Publication Date: 2/3/2026
Citation: Jammeh, P.T., Prasifka, J.R., Hulke, B.S., Berti, M., Sun, X., Monono, E. 2026. Characterization and multivariate analysis of engineering properties of red sunflower seed weevil-infested achenes. Journal of Agriculture and Food Research. 26. Article 102749. https://doi.org/10.1016/j.jafr.2026.102749.
DOI: https://doi.org/10.1016/j.jafr.2026.102749

Interpretive Summary: Red sunflower seed weevil is a persistent and increasing problem for farmers in South Dakota. This weevil has developed resistance to high use rates of common insecticides. Researchers are working to develop new methods of control of the insect, but there is a need to find a fast and inexpensive ways to estimate damage in samples of seeds. To search for an efficient way to estimate damage, we measured common metrics for grain quality. A combination of measures of structural integrity of the seeds and aerodynamic behavior in a wind tunnel could separate infested and non-infested seeds. The combined measures development could help detect changes in weevil populations and evaluate success of new management strategies, supporting better insect management for farmers.

Technical Abstract: The structural integrity of sunflower seeds is severely affected by red sunflower seed weevil (RSSW, Smicronyx fulvus) infestation, which reduces seed quality and marketability across major production regions in North America. Six sunflower seed varieties representing low (0–10%), moderate (27–36%), and high (70%) infestation levels were evaluated for changes in structural and aerodynamic traits. Eighteen engineering properties including geometric, gravimetric, mechanical, and aerodynamic traits were measured, and principal component analysis (PCA) was applied to identify key patterns of trait variation and diagnostic indicators of infestation. Infestation led to significant reductions in key traits including geometric mean diameter, true density, rupture force, and terminal velocity (p'<'0.001). Rupture force declined from 45.7'N in low-infested RH-16 to 30.8'N in highly infested WRRF-7, while true density peaked in moderately infested 404 before declining. Terminal velocity declined from 4.86'm·s'¹ to 3.55'm·s'¹ across the same varieties. Correlation analysis revealed strong interdependencies among traits. For instance, geometric diameter was highly correlated with seed width (r'='0.99), supporting the use of multivariate modeling. PCA revealed that the first three components accounted for 88.9% of the total variance, distinguishing trait clusters linked to structural integrity and aerodynamic behavior. Clustering analyses (hierarchical and k-means) further separated seed varieties by infestation level, with WRRF-7 (70% infestation) forming a distinct group characterized by high deformability and altered airflow traits. These results confirm that RSSW infestation induces quantifiable and systematic changes in seed traits. The multivariate trait-based approach demonstrated here offers a simple, non-destructive method for characterizing infestation severity and supports the development of sensor-based sorting strategies for postharvest quality assurance in RSSW-affected regions.