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<p>Potato is a vital global food crop, providing essential nutrients like carbohydrates, proteins,&#xa0;vitamins, and minerals. This study aimed to identify nutritionally superior potato genotypes using advanced statistical techniques such as Pearson’s correlation analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA), factor analysis and multi-trait genotype ideotype−distance index (MGIDI). The combined analysis of variance revealed significant genotypic variation for traits including pH, moisture content, dry matter, total soluble solids and ascorbic acid, indicating strong potential for genetic improvement. Sensory evaluations identified genotypes P-57 and P-58 as top performers in attributes like taste and texture. Instrumental colour profiling uncovered significant diversity in skin and flesh colour among genotypes, enhancing their market appeal. Pearson’s correlation analysis showed strong associations between carbohydrate content and other biochemical traits, emphasizing its importance in tuber quality. Cluster analysis grouped genotypes with similar biochemical profiles into distinct clusters, providing insight into genetic relationships and facilitating targeted breeding strategies. The PCA analysis revealed that the first 11 components explained 80% of the total variance, with colour-related traits, mineral content and acidity being the primary contributors to the observed biochemical diversity. The factor analysis identified underlying factors explaining 78% of the variance, with successful selection gains observed for traits titratable acidity, fat, dry matter, fibre and ascorbic acid, while negative selection gains were noted for carbohydrates, iron, zinc and protein content. The MGIDI analysis identified genotypes P-53, P-42, P-54, P-57, P-67 and P-9 as superior genotypes for breeding programs focused on improving nutritional quality and consumer preferences. These findings underscore the value of integrating biochemical, sensory and statistical analysis for selecting nutritional rich potato genotypes to address nutritional security.</p>

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Biochemical Characterization, Sensory Evaluation, Instrumental Colour Profiling and Selection of Nutritional-Rich Genotypes through Hierarchical Cluster Analysis, Multivariate Analysis and Multi-trait Genotype Ideotype−Distance Index in Potato (Solanum tuberosum L.)

  • 期刊论文

  • 发表日期：

    2025年3月12日

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  • K. Hanume Gowda,
  • H. Amarananjundeswara,
  • B. Fakrudin,
  • K. R. Vasudeva,
  • B. Doddabasappa,
  • Jyoti Kattegoudar

摘要

Potato is a vital global food crop, providing essential nutrients like carbohydrates, proteins, vitamins, and minerals. This study aimed to identify nutritionally superior potato genotypes using advanced statistical techniques such as Pearson’s correlation analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA), factor analysis and multi-trait genotype ideotype−distance index (MGIDI). The combined analysis of variance revealed significant genotypic variation for traits including pH, moisture content, dry matter, total soluble solids and ascorbic acid, indicating strong potential for genetic improvement. Sensory evaluations identified genotypes P-57 and P-58 as top performers in attributes like taste and texture. Instrumental colour profiling uncovered significant diversity in skin and flesh colour among genotypes, enhancing their market appeal. Pearson’s correlation analysis showed strong associations between carbohydrate content and other biochemical traits, emphasizing its importance in tuber quality. Cluster analysis grouped genotypes with similar biochemical profiles into distinct clusters, providing insight into genetic relationships and facilitating targeted breeding strategies. The PCA analysis revealed that the first 11 components explained 80% of the total variance, with colour-related traits, mineral content and acidity being the primary contributors to the observed biochemical diversity. The factor analysis identified underlying factors explaining 78% of the variance, with successful selection gains observed for traits titratable acidity, fat, dry matter, fibre and ascorbic acid, while negative selection gains were noted for carbohydrates, iron, zinc and protein content. The MGIDI analysis identified genotypes P-53, P-42, P-54, P-57, P-67 and P-9 as superior genotypes for breeding programs focused on improving nutritional quality and consumer preferences. These findings underscore the value of integrating biochemical, sensory and statistical analysis for selecting nutritional rich potato genotypes to address nutritional security.