{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T13:54:39Z","timestamp":1778594079725,"version":"3.51.4"},"reference-count":23,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2014,10,10]],"date-time":"2014-10-10T00:00:00Z","timestamp":1412899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The objective of this study was to evaluate the use of hyperspectral near-infrared (NIR) reflectance imaging techniques for detecting cuticle cracks on tomatoes. A hyperspectral NIR reflectance imaging system that analyzed the spectral region of  1000\u20131700 nm was used to obtain hyperspectral reflectance images of 224 tomatoes:  112 with and 112 without cracks along the stem-scar region. The hyperspectral images were subjected to partial least square discriminant analysis (PLS-DA) to classify and detect cracks on the tomatoes. Two morphological features, roundness (R) and minimum-maximum distance (D), were calculated from the PLS-DA images to quantify the shape of the stem scar. Linear discriminant analysis (LDA) and a support vector machine (SVM) were then used to classify R and D. The results revealed 94.6% and 96.4% accuracy for classifications made using LDA and SVM, respectively, for tomatoes with and without crack defects. These data suggest that the hyperspectral near-infrared reflectance imaging system, in addition to traditional NIR spectroscopy-based methods, could potentially be used to detect crack defects on tomatoes and perform quality assessments.<\/jats:p>","DOI":"10.3390\/s141018837","type":"journal-article","created":{"date-parts":[[2014,10,10]],"date-time":"2014-10-10T10:24:07Z","timestamp":1412936647000},"page":"18837-18850","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Detection of Cracks on Tomatoes Using a Hyperspectral  Near-Infrared Reflectance Imaging System"],"prefix":"10.3390","volume":"14","author":[{"given":"Hoonsoo","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, Korea"},{"name":"Environmental Microbiology and Food Safety Laboratory, Agricultural Research Service,  U.S. Department of Agriculture, Powder Mill Rd. Bldg. 303, BARC-East, Beltsville,  MD 20705, USA"}]},{"given":"Moon","family":"Kim","sequence":"additional","affiliation":[{"name":"Environmental Microbiology and Food Safety Laboratory, Agricultural Research Service,  U.S. Department of Agriculture, Powder Mill Rd. Bldg. 303, BARC-East, Beltsville,  MD 20705, USA"}]},{"given":"Danhee","family":"Jeong","sequence":"additional","affiliation":[{"name":"Environmental Microbiology and Food Safety Laboratory, Agricultural Research Service,  U.S. Department of Agriculture, Powder Mill Rd. Bldg. 303, BARC-East, Beltsville,  MD 20705, USA"},{"name":"Department of Food and Nutrition, Hanyang University, Seoul 133-791, Korea"}]},{"given":"Stephen","family":"Delwiche","sequence":"additional","affiliation":[{"name":"Fruit Quality Laboratory, USDA-ARS, Beltsville, MD 20705, USA"}]},{"given":"Kuanglin","family":"Chao","sequence":"additional","affiliation":[{"name":"Environmental Microbiology and Food Safety Laboratory, Agricultural Research Service,  U.S. Department of Agriculture, Powder Mill Rd. Bldg. 303, BARC-East, Beltsville,  MD 20705, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8397-9853","authenticated-orcid":false,"given":"Byoung-Kwan","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2014,10,10]]},"reference":[{"key":"ref_1","unstructured":"FAOSTAT Food and Agriculture Organiztion of the United Nations Statistics Division. Available online: http:\/\/faostat3.fao.org\/faostat-gateway\/go\/to\/home\/E."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"4113","DOI":"10.1021\/jf9801973","article-title":"Antioxidant activity and total phenolics in selected fruits, vegetables, and grain products","volume":"46","author":"Mazza","year":"1998","journal-title":"J. Agric. Food Chem."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1089\/fpd.2008.0232","article-title":"Salmonellosis outbreaks in the United States due to fresh produce: Sources and potential intervention measures","volume":"6","author":"Hanning","year":"2009","journal-title":"Foodborne Pathog. Dis."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4760","DOI":"10.1128\/AEM.67.10.4760-4764.2001","article-title":"Survival of Salmonellae on and in tomato plants from the time of inoculation at flowering and early stages of fruit development through fruit ripening","volume":"67","author":"Guo","year":"2001","journal-title":"Appl. Environ. Microb."},{"key":"ref_5","unstructured":"CDC (2007). Multistate Outbreaks of Salmonella Infections Associated with Raw Tomatoes Eaten in Restaurants\u2014United States, 2005\u20132006, CDC."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1128\/am.11.1.7-10.1963","article-title":"Distribution of Bacteria within Tissue of Healthy Tomatoes","volume":"11","author":"Samish","year":"1963","journal-title":"Appl. Microbiol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"48","DOI":"10.5307\/JBE.2013.38.1.048","article-title":"Applications of discrete wavelet analysis for predicting internal quality of cherry tomatoes using visible\/near-infrared spectroscopy","volume":"38","author":"Kim","year":"2013","journal-title":"J. Biosyst. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2505","DOI":"10.1021\/ac048651r","article-title":"Nondestructive determination of solids and carotenoids in tomato products by near-infrared spectroscopy and multivariate calibration","volume":"77","author":"Pedro","year":"2005","journal-title":"Anal. Chem."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.jfoodeng.2009.02.023","article-title":"Classification of tomatoes with different genotypes by visible and short-wave near-infrared spectroscopy with least-squares support vector machines and other chemometrics","volume":"94","author":"Xie","year":"2009","journal-title":"J. Food Eng."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"199","DOI":"10.5307\/JBE.2013.38.3.199","article-title":"Detection algorithm for cracks on the surface of tomatoes using multispectral visible\/near-infrared reflectance imagery","volume":"38","author":"Jeong","year":"2013","journal-title":"J. Biosyst. Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.lwt.2007.02.022","article-title":"Early detection of apple bruises on different background colors using hyperspectral imaging","volume":"41","author":"ElMasry","year":"2008","journal-title":"Lwt Food Sci. Technol."},{"key":"ref_12","first-page":"2027","article-title":"Multispectral detection of fecal contamination on apples based on hyperspectral imagery. Part I. Application of visible and near-infrared reflectance imaging","volume":"45","author":"Kim","year":"2002","journal-title":"Trans. Am. Soc. Agric. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/S0168-1699(00)00146-0","article-title":"Use of genetic artificial neural networks and spectral imaging for defect detection on cherries","volume":"29","author":"Guyer","year":"2000","journal-title":"Comput. Electron. Agric."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.compag.2006.04.001","article-title":"Near-infrared hyperspectral. reflectance imaging for detection of bruises on pickling cucumbers","volume":"53","author":"Ariana","year":"2006","journal-title":"Comput. Electron. Agric."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1007\/BF02707141","article-title":"Robust nonlinear PLS based on neural networks and application to composition estimator for high-purity distillation columns","volume":"17","author":"Liu","year":"2000","journal-title":"Korean J. Chem. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"8128","DOI":"10.1021\/jf0512297","article-title":"Rapid detection of kernel rots and mycotoxins in maize by near-infrared reflectance spectroscopy","volume":"53","author":"Berardo","year":"2005","journal-title":"J. Agric. Food Chem."},{"key":"ref_17","unstructured":"Mercier, G., and Lennon, M. (2003, January 21\u201325). Support Vector Machines for Hyperspectral Image Classification with Spectral-based Kernels. Toulouse, France."},{"key":"ref_18","unstructured":"Scholkopft, B., and Mullert, K.-R. (1999, January 23\u201325). Fisher discriminant analysis with kernels. Madison, WI, USA."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1016\/j.jpba.2007.03.023","article-title":"A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies","volume":"44","author":"Roggo","year":"2007","journal-title":"J. Pharm. Biomed. Anal."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"8097","DOI":"10.1021\/jf301247w","article-title":"Protein and Oil Composition Predictions of Single Soybeans by Transmission Raman Spectroscopy","volume":"60","author":"Schulmerich","year":"2012","journal-title":"J. Agric. Food Chem."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Lee, H., Kim, M.S., Jeong, D., Chao, K., Cho, B.-K., and Delwiche, S.R. (2011). Hyperspectral near-infrared reflectance imaging for detection of defect tomatoes. Proc. SPIE, 8027.","DOI":"10.1117\/12.888098"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1111\/j.1399-3054.2012.01647.x","article-title":"Tomato fruit continues growing while ripening, affecting cuticle properties and cracking","volume":"146","author":"Parra","year":"2012","journal-title":"Physiol. Plant."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.aca.2010.03.048","article-title":"Variables selection methods in near-infrared spectroscopy","volume":"667","author":"Zou","year":"2010","journal-title":"Anal. Chim. Acta"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/14\/10\/18837\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:16:46Z","timestamp":1760217406000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/14\/10\/18837"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,10,10]]},"references-count":23,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2014,10]]}},"alternative-id":["s141018837"],"URL":"https:\/\/doi.org\/10.3390\/s141018837","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,10,10]]}}}