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Non-destructive evaluation of bacteria-infected watermelon seeds using visible/near-infrared hyperspectral imaging.
J Sci Food Agric. 2017 Mar; 97(4):1084-1092.JS

Abstract

BACKGROUND

There is a need to minimize economic damage by sorting infected seeds from healthy seeds before seeding. However, current methods of detecting infected seeds, such as seedling grow-out, enzyme-linked immunosorbent assays, the polymerase chain reaction (PCR) and the real-time PCR have a critical drawbacks in that they are time-consuming, labor-intensive and destructive procedures. The present study aimed to evaluate the potential of visible/near-infrared (Vis/NIR) hyperspectral imaging system for detecting bacteria-infected watermelon seeds.

RESULTS

A hyperspectral Vis/NIR reflectance imaging system (spectral region of 400-1000 nm) was constructed to obtain hyperspectral reflectance images for 336 bacteria-infected watermelon seeds, which were then subjected to partial least square discriminant analysis (PLS-DA) and a least-squares support vector machine (LS-SVM) to classify bacteria-infected watermelon seeds from healthy watermelon seeds. The developed system detected bacteria-infected watermelon seeds with an accuracy > 90% (PLS-DA: 91.7%, LS-SVM: 90.5%), suggesting that the Vis/NIR hyperspectral imaging system is effective for quarantining bacteria-infected watermelon seeds.

CONCLUSION

The results of the present study show that it is possible to use the Vis/NIR hyperspectral imaging system for detecting bacteria-infected watermelon seeds. © 2016 Society of Chemical Industry.

Authors+Show Affiliations

Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, South Korea.Environmental Microbiology and Food Safety Laboratory, Agricultural Research Service, US Department of Agriculture, Powder Mill Rd, Bldg 303, BARC-East, Beltsville, MD 20705, USA.Department of Horticultural Biotechnology and Institute of Life Science and Resources, Kyung Hee University, Yongin 441-701, South Korea.Department of Horticultural Biotechnology and Institute of Life Science and Resources, Kyung Hee University, Yongin 441-701, South Korea.Department of Applied Biology, College of Agriculture and Life Sciences, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, South Korea.Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, South Korea.Department of Horticultural Bioscience, Pusan National University, Miryang 627-706, South Korea.Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, South Korea.

Pub Type(s)

Evaluation Study
Journal Article

Language

eng

PubMed ID

27264863

Citation

Lee, Hoonsoo, et al. "Non-destructive Evaluation of Bacteria-infected Watermelon Seeds Using Visible/near-infrared Hyperspectral Imaging." Journal of the Science of Food and Agriculture, vol. 97, no. 4, 2017, pp. 1084-1092.
Lee H, Kim MS, Song YR, et al. Non-destructive evaluation of bacteria-infected watermelon seeds using visible/near-infrared hyperspectral imaging. J Sci Food Agric. 2017;97(4):1084-1092.
Lee, H., Kim, M. S., Song, Y. R., Oh, C. S., Lim, H. S., Lee, W. H., Kang, J. S., & Cho, B. K. (2017). Non-destructive evaluation of bacteria-infected watermelon seeds using visible/near-infrared hyperspectral imaging. Journal of the Science of Food and Agriculture, 97(4), 1084-1092. https://doi.org/10.1002/jsfa.7832
Lee H, et al. Non-destructive Evaluation of Bacteria-infected Watermelon Seeds Using Visible/near-infrared Hyperspectral Imaging. J Sci Food Agric. 2017;97(4):1084-1092. PubMed PMID: 27264863.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Non-destructive evaluation of bacteria-infected watermelon seeds using visible/near-infrared hyperspectral imaging. AU - Lee,Hoonsoo, AU - Kim,Moon S, AU - Song,Yu-Rim, AU - Oh,Chang-Sik, AU - Lim,Hyoun-Sub, AU - Lee,Wang-Hee, AU - Kang,Jum-Soon, AU - Cho,Byoung-Kwan, Y1 - 2016/06/30/ PY - 2016/02/18/received PY - 2016/05/14/revised PY - 2016/05/28/accepted PY - 2016/6/7/pubmed PY - 2017/7/1/medline PY - 2016/6/7/entrez KW - Acidovorax avenae subsp. Citrulli KW - Vis/NIR hyperspectral imaging KW - least square support vector machine (LS-SVM) KW - partial least square discriminant analysis (PLS-DA) KW - watermelon seeds SP - 1084 EP - 1092 JF - Journal of the science of food and agriculture JO - J Sci Food Agric VL - 97 IS - 4 N2 - BACKGROUND: There is a need to minimize economic damage by sorting infected seeds from healthy seeds before seeding. However, current methods of detecting infected seeds, such as seedling grow-out, enzyme-linked immunosorbent assays, the polymerase chain reaction (PCR) and the real-time PCR have a critical drawbacks in that they are time-consuming, labor-intensive and destructive procedures. The present study aimed to evaluate the potential of visible/near-infrared (Vis/NIR) hyperspectral imaging system for detecting bacteria-infected watermelon seeds. RESULTS: A hyperspectral Vis/NIR reflectance imaging system (spectral region of 400-1000 nm) was constructed to obtain hyperspectral reflectance images for 336 bacteria-infected watermelon seeds, which were then subjected to partial least square discriminant analysis (PLS-DA) and a least-squares support vector machine (LS-SVM) to classify bacteria-infected watermelon seeds from healthy watermelon seeds. The developed system detected bacteria-infected watermelon seeds with an accuracy > 90% (PLS-DA: 91.7%, LS-SVM: 90.5%), suggesting that the Vis/NIR hyperspectral imaging system is effective for quarantining bacteria-infected watermelon seeds. CONCLUSION: The results of the present study show that it is possible to use the Vis/NIR hyperspectral imaging system for detecting bacteria-infected watermelon seeds. © 2016 Society of Chemical Industry. SN - 1097-0010 UR - https://www.unboundmedicine.com/medline/citation/27264863/Non_destructive_evaluation_of_bacteria_infected_watermelon_seeds_using_visible/near_infrared_hyperspectral_imaging_ L2 - https://doi.org/10.1002/jsfa.7832 DB - PRIME DP - Unbound Medicine ER -