Multivariate Characterization and Nutritional Profiling of Advanced Soybean (Glycine max (L.) Merr.) Breeding Lines Using Atomic Absorption Spectroscopy
P. S. Raja
Department of Molecular Biology and Genetic Engineering, Collage of Basic Science & Humanities, G.B. Pant University of Agriculture and Technology Pantnagar, India.
Raju Ratan Yadav
Department of Molecular Biology and Genetic Engineering, Collage of Basic Science & Humanities, G.B. Pant University of Agriculture and Technology Pantnagar, India.
M. K. Karnwal
Department of Genetics and Plant Breeding, G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India.
Pankaj Kumar Yadav
Department of Soil Science, Irrigation Research Station, Madhepura, Bihar Agricultural University, Sabour, Bihar, India.
Brij Raj Singh *
Department of Molecular Biology and Genetic Engineering, Collage of Basic Science & Humanities, G.B. Pant University of Agriculture and Technology Pantnagar, India.
*Author to whom correspondence should be addressed.
Abstract
Soybean (Glycine max (L.) Merr.) is a leguminous crop known for its high nutritional potential and its capacity to address prevalent nutrient deficiencies through breeding and biofortification strategies. The current study assessed the mineral composition of 97 advanced soybean breeding lines using atomic absorption spectroscopy (AAS) to measure two macronutrients - calcium (Ca) and magnesium (Mg) - and four micronutrients - iron (Fe), zinc (Zn), copper (Cu) and manganese (Mn). The observations were subjected to correlation analysis, principal component analysis (PCA) and hierarchical clustering, and a nutritional index was calculated. Considerable differences were observed in mineral distribution profiles among the genotypes and among the minerals. Calcium showed the highest variability, while magnesium displayed more consistent accumulation. A weak to moderate positive relationship was detected among several micronutrients, especially Fe–Zn, Fe–Cu and Fe–Mn, suggesting potential for simultaneous enhancement of multiple nutritional traits in the breeding programmes. PCA and hierarchical clustering categorised the genotypes into distinct groups based on their mineral composition, confirming noticeable diversity within the breeding material. PS 26 had high calcium content, PS 1505 showed high iron content, PS 1733 had high magnesium content and NRC 142 had high copper content according to these observations. The nutritional index highlighted PS 1670, PS 1521, PS 1734, EC 69729 and NRC 142 as outstanding genotypes with balanced and above-average levels of overall mineral composition as indicated by the nutritional index. These results demonstrate informative genetic diversity in seed mineral content and identify promising donor lines for soybean biofortification and nutrient enhancement. The study offers essential insights for the development of mineral-rich soybean cultivars aimed at promoting sustainable agriculture and improving human nutrition.
Keywords: Glycine max, mineral profiling, micronutrient, macronutrient, atomic absorption spectroscopy, biofortification, principal component analysis, hierarchical clustering, nutritional index, genetic diversity