RESEARCH INTERESTS
Paul Armstrong is a scientist working on the development of sensors and instrumentation for non-destructive measurement of grain attributes and the monitoring of stored grain. Research includes development of rapid single-kernel near-infrared spectroscopic instrumentation to measure chemical composition and attributes of corn and soybeans (protein, lysine, tryptophan, oil, mold damage, etc), and development in situ moisture and quality monitoring systems for stored grain.
|
RECENT PUBLICATIONS
| • Identification and candidate gene evaluation of a large fast neutron-induced deletion associated with a high-oil phenotype in soybean seeds - (Peer Reviewed Journal) |
| Serson, W., Gishini, M., Stupar, R., Stec, A., Armstrong, P.R., Hildebrand, D. 2024. Identification and candidate gene evaluation of a large fast neutron-induced deletion associated with a high-oil phenotype in soybean seeds. Journal of Theoretical and Applied Genetics. 15(7). Article 892. https://doi.org/10.3390/genes15070892. |
| • Developing a multi-spectral NIR LED-based instrument for detection of pesticide residues containing chlorpyrifos-methyl in rough, brown and milled rice - (Peer Reviewed Journal) |
| Rodriguez, F.S., Armstrong, P.R., Maghirang, E.B., Yaptenco, K.F., Scully, E.D., Arthur, F.H., Brabec, D.L., Adviento-Borbe, A.A., Suministrado, D.C. 2024. Developing a multi-spectral NIR LED-based instrument for detection of pesticide residues containing chlorpyrifos-methyl in rough, brown and milled rice. Sensors. 24(13). Article 4055. https://doi.org/10.3390/s24134055. |
| • Rapid single flax (Linum usitatissimum) seed phenotyping of oil and other quality traits using single kernel near infrared spectroscopy - (Peer Reviewed Journal) |
| Gokhan, H., Armstrong, P.R., Mendoza, T.P. 2024. Rapid single flax (Linum usitatissimum) seed phenotyping of oil and other quality traits using single kernel near infrared spectroscopy. Journal of the American Oil Chemists' Society. https://doi.org/10.1002/aocs.12875. |
| • Real-time stored product insect detection and identification using deep learning: System integration and extensibility to mobile platforms - (Peer Reviewed Journal) |
| Badgujar, C., Armstrong, P.R., Gerken, A.R., Pordesimo, L.O., Campbell, J.F. 2023. Real-time stored product insect detection and identification using deep learning: System integration and extensibility to mobile platforms. Journal of Stored Products Research. 104. Article 102196. https://doi.org/10.1016/j.jspr.2023.102196. |
| • [RA] NIR spectral imaging for animal feed quality and safety - (Peer Reviewed Journal) |
| Dantes-Mendoza, P., Hurburgh, C.R., Maier, D.M., Armstrong, P.R. 2024. [RA] NIR spectral imaging for animal feed quality and safety. Applied Engineering in Agriculture. 39(6): 553-564. https://doi.org/10.13031/aea.15051. |
| • Identifying common stored product insects using automated deep learning methods - (Peer Reviewed Journal) |
| Badgujar, C., Armstrong, P.R., Gerken, A.R., Pordesimo, L.O., Campbell, J.F. 2023. Identifying common stored product insects using automated deep learning methods. Journal of Stored Products Research. 103. Article 102166. https://doi.org/10.1016/j.jspr.2023.102166. |
| • Assessment of oil quantification methods for high oil seeds - (Peer Reviewed Journal) |
| Al-Bakri, A., Al-Amery, M., Su, K., Anderson, H., Geneve, R., Crocker, M., Teets, N., Armstrong, P.R., Kachroo, P., Hildebrand, D. 2023. Assessment of oil quantification methods for high oil seeds. Analytical Chemistry. 50. Article 102715. https://doi.org/10.1016/j.bcab.2023.102715. |
| • Application of machine learning for insect monitoring in grain facilities - (Peer Reviewed Journal) |
| Mendoza, Q.A., Pordesimo, L.O., Nielsen, M.L., Armstrong, P.R., Campbell, J.F. 2023. Application of machine learning for insect monitoring in grain facilities. Artificial Intelligence. 4:348-360. https://doi.org/10.3390/ai4010017. |
| • Crop seed phenomics: Enabling nondestructive phenotyping approaches for characterization of functional and quality traits - (Peer Reviewed Journal) |
| Hacisalihoglu, G., Armstrong, P.R. 2023. Crop seed phenomics: Enabling nondestructive phenotyping approaches for characterization of functional and quality traits. Plants. 12(5):1177. https://doi.org/10.3390/plants12051177. |
| • Prediction of sorghum oil and kernel weight using near-infrared hyperspectral imaging - (Peer Reviewed Journal) |
| Mendoza, P.D., Armstrong, P.R., Peiris, K.H., Siliveru, K., Bean, S.R., Pordesimo, L.O. 2023. Prediction of sorghum oil and kernel weight using near-infrared hyperspectral imaging. Cereal Chemistry. 100(3):775-783. https://doi.org/10.1002/cche.10656. |
|
