Developing an NIRS prediction model for oil, protein, amino acids and fatty acids in amaranth and buckwheat

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cg.authorship.typesCGIAR and developing country institute
cg.contributor.affiliationIndian Council of Agricultural Research
cg.contributor.affiliationBioversity International
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/10.3390/agriculture13020469
cg.isijournalISI Journal
cg.issn2077-0472
cg.issue2
cg.journalAgriculture
cg.number469
cg.reviewStatusPeer Review
cg.subject.alliancebiovciatBIODIVERSITY
cg.subject.alliancebiovciatFOOD SECURITY
cg.subject.alliancebiovciatNUTRITION
cg.subject.sdgSDG 2 - Zero hunger
cg.volume13
dc.contributor.authorShruti,
dc.contributor.authorShukla, Alka
dc.contributor.authorRahman, Saman Saim
dc.contributor.authorSuneja, Poonam
dc.contributor.authorYadav, Rashmi
dc.contributor.authorHussain, Zakir
dc.contributor.authorSingh, Rakesh
dc.contributor.authorYadav, Shiv Kumar
dc.contributor.authorRana, Jai Chand
dc.contributor.authorYadav, Sangita
dc.contributor.authorBhardwaj, Rakesh
dc.date.accessioned2024-01-24T10:52:36Zen
dc.date.available2024-01-24T10:52:36Zen
dc.identifier.urihttps://hdl.handle.net/10568/138385
dc.titleDeveloping an NIRS prediction model for oil, protein, amino acids and fatty acids in amaranth and buckwheaten
dcterms.abstractAmaranth and buckwheat are two pseudo-cereals preferred for their high nutritional value, are gluten free and carry religious importance as fasting food. Germplasm resources are the reservoir of diversity for different traits, including nutritional characteristics. These resources must be evaluated to utilize their potential in crop improvement programs. However, conventional methods are labor-, cost- and time-intensive and prone to handling errors when applied to large samples. NIRS-based machine learning to predict different nutritional traits is applied in different food crops for multiple traits. NIRS prediction models are developed in this study using the mPLS regression technique for oil, protein, fatty acids and essential amino acid estimation in amaranth and buckwheat. Good RSQ external (power of determination) values were obtained for the above traits ranging from 0.72 to 0.929. Ratio performance deviation (RPD) value for most of the traits ranged between 2 and 3, except for valine (1.88) and methionine (3.55), indicating good prediction capabilities in the developed model. These prediction models were utilized in screening the germplasm of amaranth and buckwheat; the results obtained were in good agreement and confirmed the applicability of developed models. It will enable the identification of a trait-specific germplasm as a potential gene source and aid in crop improvement programs.en
dcterms.accessRightsOpen Access
dcterms.available2023-02-16
dcterms.bibliographicCitationShruti; Shukla, A.; Rahman, S.S.; Suneja, P.; Yadav, R.; Hussain, Z.; Singh, R.; Yadav, S.K.; Rana, J.C.; Yadav, S.; Bhardwaj, R. (2023) Developing an NIRS prediction model for oil, protein, amino acids and fatty acids in amaranth and buckwheat. Agriculture 13(2): 469. ISSN: 2077-0472en
dcterms.issued2023-02-16
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherMDPI
dcterms.subjectgermplasmen
dcterms.subjectnutritionen
dcterms.subjectmodellingen
dcterms.subjectcrop improvementen
dcterms.subjectfatty acidsen
dcterms.subjectoil cropsen
dcterms.typeJournal Article

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