{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T00:25:24Z","timestamp":1771547124068,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2019,1,11]],"date-time":"2019-01-11T00:00:00Z","timestamp":1547164800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003627","name":"Rural Development Administration","doi-asserted-by":"publisher","award":["PJ01311303"],"award-info":[{"award-number":["PJ01311303"]}],"id":[{"id":"10.13039\/501100003627","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Viability is an important quality factor influencing seed germination and crop yield. Current seed-viability testing methods rely on conventional manual inspections, which use destructive, labor-intensive and time-consuming measurements. The aim of this study is to distinguish between viable and nonviable soybean seeds, using a near-infrared (NIR) hyperspectral imaging (HSI) technique in a rapid and nondestructive manner. The data extracted from the NIR\u2013HSI of viable and nonviable soybean seeds were analyzed using a partial least-squares discrimination analysis (PLS-DA) technique for classifying the viable and nonviable soybean seeds. Variable importance in projection (VIP) was used as a waveband selection method to develop a multispectral imaging model. Initially, the spectral profile of each pixel in the soybean seed images was subjected to PLS-DA analysis, which yielded a reasonable classification accuracy; however, the pixel-based classification method was not successful for high accuracy detection for nonviable seeds. Another viability detection method was then investigated: a kernel image threshold method with an optimum-detection-rate strategy. The kernel-based classification of seeds showed over 95% accuracy even when using only seven optimal wavebands selected through VIP. The results show that the proposed multispectral NIR imaging method is an effective and accurate nondestructive technique for the discrimination of soybean seed viability.<\/jats:p>","DOI":"10.3390\/s19020271","type":"journal-article","created":{"date-parts":[[2019,1,11]],"date-time":"2019-01-11T11:36:42Z","timestamp":1547206602000},"page":"271","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":60,"title":["Rapid Measurement of Soybean Seed Viability Using Kernel-Based Multispectral Image Analysis"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1044-349X","authenticated-orcid":false,"given":"Insuck","family":"Baek","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA"},{"name":"USDA-ARS Environmental Microbial and Food Safety Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Beltsville, MD 20705, USA"}]},{"given":"Dewi","family":"Kusumaningrum","sequence":"additional","affiliation":[{"name":"Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Korea"}]},{"given":"Lalit Mohan","family":"Kandpal","sequence":"additional","affiliation":[{"name":"Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Korea"}]},{"given":"Santosh","family":"Lohumi","sequence":"additional","affiliation":[{"name":"Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Korea"}]},{"given":"Changyeun","family":"Mo","sequence":"additional","affiliation":[{"name":"National Institute of Agricultural Sciences, Rural Development Administration, 310 Nonsaengmyeong-ro, Wansan-gu, Jeonju-si, Jeollabuk-do 54875, Korea"}]},{"given":"Moon S.","family":"Kim","sequence":"additional","affiliation":[{"name":"USDA-ARS Environmental Microbial and Food Safety Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, 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 34134, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,11]]},"reference":[{"key":"ref_1","unstructured":"Miller-Garvin, J., and Naeve, S.L. (2017). United States Soybean Quality\u2014Annual Report."},{"key":"ref_2","unstructured":"(2018, May 09). FAOSTAT. Available online: http:\/\/www.fao.org\/faostat\/en\/#data\/QC."},{"key":"ref_3","unstructured":"Brown-Lima, C., Cooney, M., and Cleary, D. (2010). An Overview of the Brazil-China Soybean Trade and Its Strategic Implications for Conservation."},{"key":"ref_4","first-page":"301","article-title":"Rapid and Nondestructive Discrimination of Fusarium Asiaticum and Fusarium Graminearum in Hulled Barley (Hordeum vulgare L.) Using Near-Infrared Spectroscopy","volume":"42","author":"Lim","year":"2017","journal-title":"J. Biosyst. Eng."},{"key":"ref_5","unstructured":"(2009). Seed Vigor Testing Handbook, AOSA."},{"key":"ref_6","first-page":"227","article-title":"Machine Vision Technique for Rapid Measurement of Soybean Seed Vigor","volume":"42","author":"Lee","year":"2017","journal-title":"J. Biosyst. Eng."},{"key":"ref_7","first-page":"293","article-title":"Hyperspectral Imaging and Partial Least Square Discriminant Analysis for Geographical Origin Discrimination of White Rice","volume":"42","author":"Mo","year":"2017","journal-title":"J. Biosyst. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.biosystemseng.2015.04.007","article-title":"Classification of contaminants from wheat using near-infrared hyperspectral imaging","volume":"135","author":"Ravikanth","year":"2015","journal-title":"Biosyst. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1081\/JFP-120022981","article-title":"Classification of fungal-damaged soybean seeds using near-infrared spectroscopy","volume":"7","author":"Wang","year":"2004","journal-title":"Int. J. Food Prop."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11694-010-9104-2","article-title":"Identification of wheat classes at different moisture levels using near-infrared hyperspectral images of bulk samples","volume":"5","author":"Mahesh","year":"2011","journal-title":"Sens. Instrum. Food Qual. Saf."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.compag.2016.01.029","article-title":"Classification of maize seeds of different years based on hyperspectral imaging and model updating","volume":"122","author":"Huang","year":"2016","journal-title":"Comput. Electron. Agric."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.foodchem.2016.04.044","article-title":"Classification of maize kernels using NIR hyperspectral imaging","volume":"209","author":"Williams","year":"2016","journal-title":"Food Chem."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.infrared.2015.12.008","article-title":"High speed measurement of corn seed viability using hyperspectral imaging","volume":"75","author":"Ambrose","year":"2016","journal-title":"Infrared Phys. Technol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1016\/j.snb.2016.02.015","article-title":"Near-infrared hyperspectral imaging system coupled with multivariate methods to predict viability and vigor in muskmelon seeds","volume":"229","author":"Kandpal","year":"2016","journal-title":"Sens. Actuators B Chem."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Weyer, L., and Workman, J. (2007). Practical Guide to Interpretive Near-Infrared Spectroscopy, CRC Press.","DOI":"10.1201\/9781420018318"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.1016\/j.trac.2009.07.007","article-title":"Review of the most common pre-processing techniques for near-infrared spectra","volume":"28","author":"Rinnan","year":"2009","journal-title":"TrAC Trends Anal. Chem."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"728","DOI":"10.1002\/cem.1360","article-title":"Variable selection in regression-a tutorial","volume":"24","author":"Andersen","year":"2010","journal-title":"J. Chemom."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1590\/0103-9016-2015-0007","article-title":"Seed vigor testing: An overview of the past, present and future perspective","volume":"72","year":"2015","journal-title":"Sci. Agric."},{"key":"ref_19","first-page":"279","article-title":"Membrane deterioration and other biochemical-changes, associated with accelerated aging of maize seeds","volume":"19","author":"Basavarajappa","year":"1991","journal-title":"Seed Sci. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"126","DOI":"10.15835\/nsb336075","article-title":"Effects of Accelerated Aging on Soybean Seed Germination Indexes at Laboratory Conditions","volume":"3","author":"Rastegar","year":"2011","journal-title":"Not. Sci. Biol."},{"key":"ref_21","first-page":"5","article-title":"Application of infrared spectra technique based on LS-support vector machines to the non-destructive measurement of fat content in milk powder","volume":"3","author":"Wu","year":"2008","journal-title":"J. Infrared Millim. Waves"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1016\/j.foodchem.2010.10.106","article-title":"Nondestructive determination of herbicide-resistant genetically modified soybean seeds using near-infrared reflectance spectroscopy","volume":"126","author":"Lee","year":"2011","journal-title":"Food Chem."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.talanta.2012.10.044","article-title":"Classification of oat and groat kernels using NIR hyperspectral imaging","volume":"103","author":"Serranti","year":"2013","journal-title":"Talanta"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1016\/j.jcs.2014.07.009","article-title":"An optimization strategy for waveband selection in FT-NIR quantitative analysis of corn protein","volume":"60","author":"Chen","year":"2014","journal-title":"J. Cereal Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2427","DOI":"10.1007\/s12161-015-0122-x","article-title":"Selection of Informative Spectral Wavelength for Evaluating and Visualising Enterobacteriaceae Contamination of Salmon Flesh","volume":"8","author":"He","year":"2015","journal-title":"Food Anal. Methods"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.chemolab.2017.12.003","article-title":"Identifying animal species in NIR hyperspectral images of processed animal proteins (PAPs): Comparison of multivariate techniques","volume":"172","author":"Riccioli","year":"2018","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.compag.2014.05.012","article-title":"Classification models of bruise and cultivar detection on the basis of hyperspectral imaging data","volume":"106","author":"Siedliska","year":"2014","journal-title":"Comput. Electron. Agric."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1023\/A:1022916615477","article-title":"Discrimination of viable and empty seeds of Pinus patula Schiede & Deppe with near-infrared spectroscopy","volume":"25","author":"Tigabu","year":"2003","journal-title":"New For."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2543","DOI":"10.1271\/bbb.66.2543","article-title":"New Estimation Method for Fatty Acid Composition in Oil Using Near Infrared Spectroscopy","volume":"66","author":"Sato","year":"2002","journal-title":"Biosci. Biotechnol. Biochem."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2283","DOI":"10.1007\/s00216-011-5291-x","article-title":"Characterisation of non-viable whole barley, wheat and sorghum grains using near-infrared hyperspectral data and chemometrics","volume":"401","author":"McGoverin","year":"2011","journal-title":"Anal. Bioanal. Chem."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Jha, S.N. (2010). Nondestructive Evaluation of Food Quality, Springer.","DOI":"10.1007\/978-3-642-15796-7"},{"key":"ref_32","unstructured":"Jerry Workman, J. (2000). The Handbook of Organic Compounds, Three-Volume Set, Elsevier. [1st ed.]."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1943","DOI":"10.13031\/2013.11410","article-title":"Classification of damaged soybean seeds using near-infrared spectroscopy","volume":"45","author":"Wang","year":"2002","journal-title":"Trans. ASAE"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"726","DOI":"10.1104\/pp.63.4.726","article-title":"Absence of Lipid Oxidation during Accelerated Aging of Soybean Seeds","volume":"63","author":"Priestley","year":"1979","journal-title":"Plant Physiol."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/2\/271\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:25:14Z","timestamp":1760185514000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/2\/271"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,11]]},"references-count":34,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2019,1]]}},"alternative-id":["s19020271"],"URL":"https:\/\/doi.org\/10.3390\/s19020271","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,1,11]]}}}