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<p>Root system architecture (RSA) is a key determinant of plant growth, resource acquisition, and environmental stress management. Conventional root phenotyping is labor-intensive, destructive, and unsuitable for large-scale germplasm evaluation. However, RhizoVision-based digital phenotyping is well-suited for initial screening of germplasm in breeding programs. In this study, available tomato accessions were examined using the RhizoVision imaging platform. Root images (n = 154) were captured with a Basler machine-vision camera and analyzed in RhizoVision Explorer to measure 22 root architectural traits. Phenotypic variation was assessed using descriptive statistics, principal component analysis (PCA), correlation analysis, hierarchical clustering, and regression analysis. Significant variation in RSA was observed in root length, branching pattern, root volume, diameter, and biomass-related traits. Strong positive correlations among total root length, surface area, perimeter, and root volume suggest coordinated development of root architectural components, whereas biomass traits showed weaker relationships with RSA traits. PCA explained 66% of the phenotypic variation, with the first two principal components distinguishing accessions primarily by root system size, complexity, and thickness. Hierarchical clustering grouped accessions into distinct clusters, further highlighting variation in root architecture. Finally, regression analysis showed a modest positive association between conventional and digital root length measurements (R<sup>2</sup> = 0.5337; r = 0.73), indicating practical agreement between the two approaches. Various accessions displayed considerable variability in standard seedling features, e.g., accession 38082 exhibited the maximum root length, though accession 38074 had the minimum root length. The maximum root diameter was found in accessions 36054 and 37987. Overall, RhizoVision-based phenotyping is a rapid, standardized approach for RSA characterization that can efficiently select varieties for breeding programs.</p>

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Phenotypic variability and multivariate analyses of root system architecture in tomato (Solanum lycopersicum) genotypes

  • 期刊论文

  • 发表日期：

    2026年7月4日

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  • Asim Shahzad,
  • Qurat-ul-ain,
  • Younas Sohail,
  • Dhekra Ben Amara,
  • Aafia Iqbal,
  • Iqra Qayyum

摘要

Root system architecture (RSA) is a key determinant of plant growth, resource acquisition, and environmental stress management. Conventional root phenotyping is labor-intensive, destructive, and unsuitable for large-scale germplasm evaluation. However, RhizoVision-based digital phenotyping is well-suited for initial screening of germplasm in breeding programs. In this study, available tomato accessions were examined using the RhizoVision imaging platform. Root images (n = 154) were captured with a Basler machine-vision camera and analyzed in RhizoVision Explorer to measure 22 root architectural traits. Phenotypic variation was assessed using descriptive statistics, principal component analysis (PCA), correlation analysis, hierarchical clustering, and regression analysis. Significant variation in RSA was observed in root length, branching pattern, root volume, diameter, and biomass-related traits. Strong positive correlations among total root length, surface area, perimeter, and root volume suggest coordinated development of root architectural components, whereas biomass traits showed weaker relationships with RSA traits. PCA explained 66% of the phenotypic variation, with the first two principal components distinguishing accessions primarily by root system size, complexity, and thickness. Hierarchical clustering grouped accessions into distinct clusters, further highlighting variation in root architecture. Finally, regression analysis showed a modest positive association between conventional and digital root length measurements (R2 = 0.5337; r = 0.73), indicating practical agreement between the two approaches. Various accessions displayed considerable variability in standard seedling features, e.g., accession 38082 exhibited the maximum root length, though accession 38074 had the minimum root length. The maximum root diameter was found in accessions 36054 and 37987. Overall, RhizoVision-based phenotyping is a rapid, standardized approach for RSA characterization that can efficiently select varieties for breeding programs.