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Abstract: The common bean (Phaseolus vulgaris L.) is a major food legume and an important plant genetic resource for sustainable agriculture. Effective use of this diversity requires integrated evaluation of phenotypic variation and agronomic performance, with preliminary assessments of line performance across seasons. In this study, phenotypic diversity was evaluated in a subsample of the INCREASE R-core collection, a large and well-defined core set of common-bean SSD lines derived from heterogeneous germplasm lines. A total of 507 lines were characterized using 57 agro-morphological traits. Multivariate analyses revealed wide phenotypic diversity structured mainly by growth habit, phenology, and yield-related traits, with clear differentiation among lines. Mixed-data clustering identified cluster 4 as the main phenotypic group associated with higher seed- and yield-related performance and composed predominantly of indeterminate climbing landraces. Multi-trait selection indices generally ranked lines from this group highest, while early, small-seeded types tended to show lower overall performance. Evaluation of a selected subset of 19 lines across two growing seasons revealed marked year-to-year variation in yield performance, indicating contrasting responses among otherwise high-performing lines. The multi-trait genotype–ideotype distance index further distinguished lines with balanced performance across traits and years. Overall, this study shows that large-scale phenotypic characterization combined with multi-trait evaluation can provide a useful exploratory basis for identifying breeding-relevant ideotypes and promising lines for further validation for common-bean improvement.
Keywords: common bean, phenotypic diversity, germplasm evaluation, multivariate analysis, selection index, year-to-year variation, yield stability
Published in DiRROS: 20.04.2026; Views: 463; Downloads: 225
Full text (8,66 MB)

Keywords: descriptive sensory analysis, dry-cured ham, multivariate statistical analysis, volatile compounds
Published in DiRROS: 02.10.2025; Views: 761; Downloads: 317
Full text (1,76 MB)

Abstract: Introduction: The global burden of diabetes mellitus is escalating, and more efficient investigative strategies are needed for a deeper understanding of underlying pathophysiological mechanisms. The crucial role of skeletal muscle in carbohydrate and lipid metabolism makes it one of the most susceptible tissues to diabetes-related metabolic disorders. In tissue studies, conventional histochemical methods have several technical limitations and have been shown to inadequately characterise the biomolecular phenotype of skeletal muscle to provide a holistic view of the pathologically altered proportions of macromolecular constituents. Materials and methods: In this pilot study, we examined the composition of five different human skeletal muscles from male donors diagnosed with type 2 diabetes and non-diabetic controls. We analysed the lipid, glycogen, and collagen content in the muscles in a traditional manner with histochemical assays using different staining techniques. This served as a reference for comparison with the unconventional analysis of tissue composition using Fourier-transform infrared spectroscopy as an alternative methodological approach. Results: A thorough chemometric post-processing of the infrared spectra using a multi-stage spectral decomposition allowed the simultaneous identification of various compositional details from a vibrational spectrum measured in a single experiment. We obtained multifaceted information about the proportions of the different macromolecular constituents of skeletal muscle, which even allowed us to distinguish protein constituents with different structural properties. The most important methodological steps for a comprehensive insight into muscle composition have thus been set and parameters identified that can be used for the comparison between healthy and diabetic muscles. Conclusion: We have established a methodological framework based on vibrational spectroscopy for the detailed macromolecular analysis of human skeletal muscle that can effectively complement or may even serve as an alternative to histochemical assays. As this is a pilot study with relatively small sample sets, we remain cautious at this stage in drawing definitive conclusions about diabetes-related changes in skeletal muscle composition. However, the main focus and contribution of our work has been to provide an alternative, simple and efficient approach for this purpose. We are confident that we have achieved this goal and have brought our methodology to a level from which it can be successfully transferred to a large-scale study that allows the effects of diabetes on skeletal muscle composition and the interrelationships between the macromolecular tissue alterations due to diabetes to be investigated.
Keywords: diabetes mellitus, skeletal muscle, metabolism, macromulecular composition, infrared spectroscopy, multivariate analysis, histochemical assays
Published in DiRROS: 11.01.2024; Views: 2200; Downloads: 1005
Full text (1,71 MB)
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