Pheno-morphological, agronomic and genetic diversity in a common bean core collection from Calabria (Italy)

Common bean ( Phaseolus vulgaris L.) is the main grain legume for human consumption worldwide. Many old locally adapted varieties are available and cultivated in several countries of the Mediterranean basin, and frequently they are at risk of extinction. This study assessed the bioagronomic and genetic diversity of 44 common bean populations (15 dwarf and 29 climbing) cultivated in Calabria (Southern Italy). Ten quantitative and ten qualitative traits were analysed according to International Board for Plant Genetic Board (IBPGR) descriptors. In addition, eight (8) Simple Sequence Repeat (SSRs) were used to examine genetic polymorphism, differentiation and population structure. The morphological seed characterization revealed significant variability in colors and shapes, with a predominant white seed color. The phenological traits, flowering time (DASF) and pod development time (DASP), showed significant correlations with main stem length (STL) (r = 0.61** and 0.53**, respectively). Grain yield (GY) was highly correlated with the number of pods per plant (PP) (r = 0.84***). Among the yield components, the number of seeds per area was the most important for yield determinism; the regression analysis was highly significant with a R 2 = 0.85. Principal component analysis (PCA) on bioagronomic data revealed that the first four components explained more than 80 % of total variation. Genetic distance analysis using SSR markers Nei’s genetic distances and the Unweighted Pair Group Method with Arithmetic mean (UPGMA) algorithm identified three main clusters. The relationships between morpho-agronomic and molecular traits based on Euclidean and genetic distances appeared limited (Mantel’s test). Genetic analyses provided a better understanding of the genetic structure of bean landraces, suggesting a history of genetic admixture between the identified groups. The study highlighted the importance of Calabria as an area of high genetic diversity for the common bean. The bioagronomic and genetic characterisation of local accessions provided useful information for the conservation and the utilisation of these genetic resources in breeding programmes. Further studies are needed to explore the influence of environmental factors on agronomic traits. • Bioagronomic and genetic traits of 44 common bean landraces from Calabria, Italy were evaluated. • Seed morphotypes descriptor based on shape and coat color (IBPGR, descriptor list) were able to define different groups. • Principal Component Analysis (PCA) of bioagronomic data allowed us to distinguish bean accessions. • The number of seeds per area resulted the most important yield components. • Genetic analysis (SSR) was able to distinguish three clusters and different genetic structures in the bean core collection.

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Publication Details

Journal
Italian Journal of Agronomy
Published
2025-03-26
DOI
https://doi.org/10.1016/j.ijagro.2025.100038
Citations
2
Primary Topic
Plant pathogens and resistance mechanisms
Type
article
Field-Weighted Citation Impact
3.50
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article

Pheno-morphological, agronomic and genetic diversity in a common bean core collection from Calabria (Italy)

Maurizio Romeo, Monica Bacchi, Giovanni Preiti, Antonio Mauceri
2 citations
Italian Journal of Agronomy
Plant pathogens and resistance mechanisms
3.50
article

Pheno-morphological, agronomic and genetic diversity in a common bean core collection from Calabria (Italy)

Maurizio Romeo, Monica Bacchi, Giovanni Preiti, Antonio Mauceri
article en
2 citations

Abstract

Common bean ( Phaseolus vulgaris L.) is the main grain legume for human consumption worldwide. Many old locally adapted varieties are available and cultivated in several countries of the Mediterranean basin, and frequently they are at risk of extinction. This study assessed the bioagronomic and genetic diversity of 44 common bean populations (15 dwarf and 29 climbing) cultivated in Calabria (Southern Italy). Ten quantitative and ten qualitative traits were analysed according to International Board for Plant Genetic Board (IBPGR) descriptors. In addition, eight (8) Simple Sequence Repeat (SSRs) were used to examine genetic polymorphism, differentiation and population structure. The morphological seed characterization revealed significant variability in colors and shapes, with a predominant white seed color. The phenological traits, flowering time (DASF) and pod development time (DASP), showed significant correlations with main stem length (STL) (r = 0.61** and 0.53**, respectively). Grain yield (GY) was highly correlated with the number of pods per plant (PP) (r = 0.84***). Among the yield components, the number of seeds per area was the most important for yield determinism; the regression analysis was highly significant with a R 2 = 0.85. Principal component analysis (PCA) on bioagronomic data revealed that the first four components explained more than 80 % of total variation. Genetic distance analysis using SSR markers Nei’s genetic distances and the Unweighted Pair Group Method with Arithmetic mean (UPGMA) algorithm identified three main clusters. The relationships between morpho-agronomic and molecular traits based on Euclidean and genetic distances appeared limited (Mantel’s test). Genetic analyses provided a better understanding of the genetic structure of bean landraces, suggesting a history of genetic admixture between the identified groups. The study highlighted the importance of Calabria as an area of high genetic diversity for the common bean. The bioagronomic and genetic characterisation of local accessions provided useful information for the conservation and the utilisation of these genetic resources in breeding programmes. Further studies are needed to explore the influence of environmental factors on agronomic traits. • Bioagronomic and genetic traits of 44 common bean landraces from Calabria, Italy were evaluated. • Seed morphotypes descriptor based on shape and coat color (IBPGR, descriptor list) were able to define different groups. • Principal Component Analysis (PCA) of bioagronomic data allowed us to distinguish bean accessions. • The number of seeds per area resulted the most important yield components. • Genetic analysis (SSR) was able to distinguish three clusters and different genetic structures in the bean core collection.

Italian Journal of AgronomyVol. 20(2)
University of Reggio Calabria (IT)
Zero hunger
Openalex Percentile: Top 9%
Plant pathogens and resistance mechanisms
3.50
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