ArticleFood chemistry: X2024
High-throughput seed quality analysis in faba bean: leveraging Near-InfraRed spectroscopy (NIRS) data and statistical methods.
Article in Food chemistry: X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Research on Detection Model of Penicillin Potency Content based on Near-infrared Spectroscopy Technology.Current computer-aided drug design · 2026Article
- NIRS chemometrics for rapid nutritional profiling of vegetable pea (Pisum sativum L.) germplasm.Scientific reports · 2025Article
- Quinolizidine Alkaloid Composition of White Lupin Landraces and Breeding Lines, and Near-Infrared Spectroscopy-Based Discrimination of Low-Alkaloid Material.Plants (Basel, Switzerland) · 2025Article
- Comprehensive Assessment of Biochemical Traits in Diverse Faba Bean (Food science & nutrition · 2025Article
- A panomics-driven framework for the improvement of major food legume crops: advances, challenges, and future prospects.Horticulture research · 2025Article
- Nutritional profiling of horse gram through NIRS-based multi-trait prediction modelling.Scientific reports · 2025Article
- GWAS Identifies SNP Markers and Candidate Genes for Off-Flavours and Protein Content in Faba Bean (Plants (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Near-infrared spectroscopy (NIRS) provides a high-throughput phenotyping technique to assist breeding for improved faba bean seed quality. We combined chemical analysis of protein, oil content (and composition) with NIRS through chemometrics, employing Partial Least Squares (PLS), Elastic Net (EN), Memory-based Learning (MBL), and Bayes B (BB) as prediction models. Protein was the most reliably predicted trait (R
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Registered trials
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