Non-destructive evaluation of bacteria-infected watermelon seeds using visible/near-infrared hyperspectral imaging.
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.


CONCLUSIONS
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.
Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, South Korea.
Hoonsoo
H
Lee
Environmental Microbiology and Food Safety Laboratory, Agricultural Research Service, US Department of Agriculture, Powder Mill Rd, Bldg 303, BARC-East, Beltsville, MD 20705, USA.
Moon S
MS
Kim
Department of Horticultural Biotechnology and Institute of Life Science and Resources, Kyung Hee University, Yongin 441-701, South Korea.
Yu-Rim
YR
Song
Department of Horticultural Biotechnology and Institute of Life Science and Resources, Kyung Hee University, Yongin 441-701, South Korea.
Chang-Sik
CS
Oh
Department of Applied Biology, College of Agriculture and Life Sciences, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, South Korea.
Hyoun-Sub
HS
Lim
Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, South Korea.
Wang-Hee
WH
Lee
Department of Horticultural Bioscience, Pusan National University, Miryang 627-706, South Korea.
Jum-Soon
JS
Kang
Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, South Korea.
Byoung-Kwan
http://orcid.org/0000-0002-8397-9853
BK
Cho
D001419:Bacteria / Q000254:growth & development*; D029773:Citrullus / Q000382:microbiology*; D005516:Food Microbiology / Q000379:methods*; D006801:Humans; D012639:Seeds / Q000382:microbiology*; D019265:Spectroscopy, Near-Infrared / Q000379:methods*
Acidovorax avenae subsp. Citrulli; Vis/NIR hyperspectral imaging; least square support vector machine (LS-SVM); partial least square discriminant analysis (PLS-DA); watermelon seeds