Common bean (Phaseolus vulgaris L.) is the world's most important legume crop and a vital staple food for millions of people in Latin America and Africa. Given the increasing trend in bean consumption and its importance for nutrition and food security in these regions, there is an urgent need to enhance common bean seeds' nutritional value through breeding. This requires rapidly assessing large and diverse germplasm collections to uncover key nutritional traits in the available genetic diversity. To address this challenge, Near-Infrared Spectroscopy (NIRS) offers a large-scale, cost-effective and non-destructive approach for accurately predicting nutrient content in intact common bean seeds. This study describes the development of predictive models based on NIRS to predict nitrogen (N), iron (Fe) and zinc (Zn) content, using whole common bean seeds from a germplasm core collection held at the International Center for Tropical Agriculture. Spectra were captured for 1754 accessions (wild and domesticated), and reference values for N, Fe, and Zn content were measured with conventional destructive methods in a panel of 401 accessions. Prediction models of N content achieved a concordance correlation coefficient (CCC) of 0.84, while for Fe and Zn, CCC was 0.4. NIRS quantification detected higher N content in wild accessions than in domesticated accessions. These results demonstrate that NIRS can effectively estimate the N content of common bean seeds in a non-destructive manner, while providing valuable nutritional information to enhance access to large genebank collections for bean breeding.
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