A comparison of spectral preprocessing methods and their effects on nutritional traits in cowpea germplasm

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cg.authorship.typesCGIAR and developing country institute
cg.contributor.affiliationIndian Council of Agricultural Research
cg.contributor.affiliationBioversity International
cg.contributor.donorCGIAR Trust Fund
cg.contributor.initiativeSustainable Healthy Diets
cg.coverage.countryIndia
cg.coverage.iso3166-alpha2IN
cg.coverage.regionAsia
cg.coverage.regionSouthern Asia
cg.creator.identifierJai Chand  Rana: 0009-0004-4603-5732
cg.identifier.doihttps://doi.org/10.1002/leg3.229
cg.isijournalISI Journal
cg.issn2639-6181
cg.issue2
cg.journalLegume Science
cg.numbere2977
cg.reviewStatusPeer Review
cg.subject.actionAreaSystems Transformation
cg.subject.alliancebiovciatAGRICULTURE
cg.subject.impactAreaNutrition, health and food security
cg.subject.sdgSDG 2 - Zero hunger
cg.volume6
dc.contributor.authorPadhi, Siddhant Ranjan
dc.contributor.authorJohn, Racheal
dc.contributor.authorTripathi, Kuldeep
dc.contributor.authorWankhede, Dhammaprakash Pandhari
dc.contributor.authorJoshi, Tanay
dc.contributor.authorRana, Jai Chand
dc.contributor.authorRiar, Amritbir
dc.contributor.authorBhardwaj, Rakesh
dc.date.accessioned2024-10-11T07:58:01Zen
dc.date.available2024-10-11T07:58:01Zen
dc.identifier.urihttps://hdl.handle.net/10568/155311
dc.titleA comparison of spectral preprocessing methods and their effects on nutritional traits in cowpea germplasmen
dcterms.abstractABSTRACT Cowpea ( Vigna unguiculata L. (Walp)) is a multipurpose legume, which has good nutritional properties. Nutritional parameters assessed conventionally can be labour intensive, costly and time taking for germplasm screening. Near‐infrared reflectance spectroscopy (NIRS) is a rapid and nondestructive method, which can facilitate high‐throughput germplasm screening. In our study, estimation of amylose and sugars has been done using NIRS. Two preprocessing methods, that is, SNV‐DT (standard normal variate with detrending) and MSC (multiplicative scatter correction), were performed for optimization of the original spectra. Subsequently, MPLS (modified partial least square) regression method was employed to construct the prediction models. In amylose, the best RSQ external (coefficient of determination) (0.962) was found in SNV‐DT with mathematical treatment 3,8,8,2. The same result was shown in sugar where the best RSQ external (0.914) was found in SNV‐DT with mathematical treatment 3,4,4,1. Overall, in the case of amylose and sugars, SNV‐DT was found to be a good preprocessing treatment than MSC. Paired t ‐test values in all the treatments for both the preprocessing methods were > 0.05 indicating their reliability. High RSQ external values for both the traits imply the applicability of the prediction models. Thus, these models can facilitate high‐throughput germplasm screening in different national and international crop improvement programmes focusing on quality traits.en
dcterms.accessRightsOpen Access
dcterms.available2024-04-11
dcterms.bibliographicCitationPadhi, S.R.; John, R.; Tripathi, K.; Wankhede, D.P.; Joshi, T.; Rana, J.C.; Riar, A.; Bhardwaj, R. (2024) A comparison of spectral preprocessing methods and their effects on nutritional traits in cowpea germplasm. Legume Science 6(2): e229. ISSN: 2639-6181en
dcterms.issued2024-06
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherWiley
dcterms.subjectgermplasmen
dcterms.subjectscreeningen
dcterms.subjectlegumesen
dcterms.subjectnutritive valueen
dcterms.subjectvigna unguiculataen
dcterms.subjectcowpea, spectralen
dcterms.typeJournal Article

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