Comprehensive Evaluation of Phenotypic Traits in Vegetable Faba Bean ( <i>Vicia faba</i> L.) Germplasms Based on Multivariate Statistical Methods

Faba bean is a significant crop, valued by consumers for its tender quality, sweet waxy taste, and distinctive flavor. However, the current morphological identification and comprehensive evaluation of faba beans primarily revolve around the characteristics of dry mature seeds. In this study, we selected 121 vegetable faba bean germplasms as our experimental material and precisely measured 25 agricultural and quality‐related indicators. Our results revealed that the coefficient of variation for the 25 indicators ranged from 4.34% to 40.48%, with fresh pod weight being the most significant indicator displaying the highest coefficient of variation, suggesting potential for breeding to increase yield. The diversity index spanned from 1.64 to 2.11, indicating the presence of a rich diversity and good dispersion within the germplasms. Correlation analysis among the 25 indicators highlighted strong associations among phenotypic traits. Notably, fresh pod weight exhibited a significant positive correlation with fresh pod length and fresh pod width, while fresh 100‐grain weight was significantly positively correlated with fresh grain length and fresh grain width. Conversely, fresh grain hardness displayed a significant negative correlation with fresh pod and grain morphological traits. The correlations among traits can guide the selection of germplasms with desired combinations of traits to develop new varieties with improved quality. Principal component analysis grouped the 25 indicators into six principal components, cumulatively accounting for 86.769% of the total variance. Methodologically, our study introduces innovations including the use of image recognition and deep learning for accurate trait determination, reducing human error. The results provide a foundational and theoretical framework for the comprehensive evaluation and selection of vegetable faba bean germplasms for assessing food quality and consumer preferences.

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Publication Details

Journal
Journal of Food Quality
Published
2025-01-01
DOI
https://doi.org/10.1155/jfq/1621073
Primary Topic
Genetic and Environmental Crop Studies
Type
article
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article

Comprehensive Evaluation of Phenotypic Traits in Vegetable Faba Bean ( Vicia faba L.) Germplasms Based on Multivariate Statistical Methods

Tingfu Liu, Ruifang Ma, Yangmin Zhong, Linlin Wang et al.
Journal of Food Quality
Genetic and Environmental Crop Studies
article

Comprehensive Evaluation of Phenotypic Traits in Vegetable Faba Bean ( Vicia faba L.) Germplasms Based on Multivariate Statistical Methods

Tingfu Liu, Ruifang Ma, Yangmin Zhong, Linlin Wang, H.C. Li
article en

Abstract

Faba bean is a significant crop, valued by consumers for its tender quality, sweet waxy taste, and distinctive flavor. However, the current morphological identification and comprehensive evaluation of faba beans primarily revolve around the characteristics of dry mature seeds. In this study, we selected 121 vegetable faba bean germplasms as our experimental material and precisely measured 25 agricultural and quality‐related indicators. Our results revealed that the coefficient of variation for the 25 indicators ranged from 4.34% to 40.48%, with fresh pod weight being the most significant indicator displaying the highest coefficient of variation, suggesting potential for breeding to increase yield. The diversity index spanned from 1.64 to 2.11, indicating the presence of a rich diversity and good dispersion within the germplasms. Correlation analysis among the 25 indicators highlighted strong associations among phenotypic traits. Notably, fresh pod weight exhibited a significant positive correlation with fresh pod length and fresh pod width, while fresh 100‐grain weight was significantly positively correlated with fresh grain length and fresh grain width. Conversely, fresh grain hardness displayed a significant negative correlation with fresh pod and grain morphological traits. The correlations among traits can guide the selection of germplasms with desired combinations of traits to develop new varieties with improved quality. Principal component analysis grouped the 25 indicators into six principal components, cumulatively accounting for 86.769% of the total variance. Methodologically, our study introduces innovations including the use of image recognition and deep learning for accurate trait determination, reducing human error. The results provide a foundational and theoretical framework for the comprehensive evaluation and selection of vegetable faba bean germplasms for assessing food quality and consumer preferences.

Journal of Food QualityVol. 2025(1)
Lishui Academy of Agricultural Sciences (CN), Lishui Vocational and Technical College (CN), Lishui Academy of Forestry (CN)
Openalex Percentile: Top 92%
Genetic and Environmental Crop Studies
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