Evidence map›Paper›PMID 40374769›Full record

ArticleScientific reports2025

Nutritional profiling of horse gram through NIRS-based multi-trait prediction modelling.

Manju Kumari, Siddhant Ranjan Padhi, Mamta Arya, Rashmi Yadav, M Latha, Anjula Pandey, Rakesh Singh, Chellapilla Bhardwaj, Atul Kumar, Jai Chand Rana and 3 more

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Manju Kumari *ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
Siddhant Ranjan Padhi *ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
Mamta AryaICAR-National Bureau of Plant Genetic Resources - RS, Bhowali, Uttarakhand, India.
Rashmi YadavICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India.
M LathaICAR-National Bureau of Plant Genetic Resources - RS, Thrissur, Kerala, India.
Anjula PandeyICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India.
Rakesh SinghICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India.
Chellapilla BhardwajICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
Atul KumarICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
Jai Chand RanaAlliance of Bioversity International and CIAT, Region - Asia, India Office, New Delhi, India.
Kailash Chandra BhattICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India. Kailash.Bhatt@icar.gov.in.
Rakesh BhardwajICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India. Rakesh.bhardwaj1@icar.gov.in.
Amritbir RiarDepartment of International Cooperation Research Institute of Organic Agriculture, FiBL, Frick, Switzerland. amritbir.riar@fibl.org.

Funding

Direktion für Entwicklung und Zusammenarbeit CROPS4HDUnited Nations Environment Programme Global Environment Facility (GEF)
6 · The paper itself

Abstract

Horse gram (Macrotyloma uniflorum (Lam.) Verd.) is an underutilised legume from the Indian subcontinent. Being a nutritious legume, it plays an important role in human nutrition in developing countries like India. Conventional assessment of nutritional traits, are labour and time intensive for screening of huge germplasm, hence alternative and rapid technique for conventional method for the determination of nutritional components of horse gram flour is needed. NIRS can be used for this purpose as it gives rapid and precise results for most of the plant products. In this study, a highly diverse collection of 139 horse gram accessions was utilized to generate reference data. Prediction models were developed for protein, starch, TSS, phenols, and phytic acid using MPLS regression method with spectral preprocessing using SNV-DT to remove scatter effects and baseline noise. Models were optimized for derivatives, gap selection, and smoothening and evaluated using different statistics including RSQ, bias and RPD. The RSQ and RPD for the best fit models obtained were protein (0.701; 1.85), starch (0.987; 4.03), TSS (0.800; 4.06), phenols (0.778; 2.15) and phytic acid (0.730; 1.88) indicating developed models are good for screening large number of germplasm collections and market samples. Statistical analyses, including paired t-tests, correlation, and reliability assessments, validated the strength of these models. This study represents the first report introducing a rapid, multi-trait evaluation approach for horse gram germplasm, highlighting its high predictive accuracy for pre-breeding applications. High throughput germplasm screening can be done through these developed models to identify trait-specific germplasm, which can be recommended to develop healthy products and thus can also be recommended for production in the farmer field simultaneously.

Indexed as

FabaceaeNutritive ValueIndiaPhenolsPhytic AcidSpectroscopy, Near-InfraredStarchPhenolsPhytic AcidStarchChemometricsDiversityMPLS regressionNutritionRPDRSQ

Identifiers

PMID40374769
PMCPMC12081650

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