A Study on the Infrageneric Classification of <i>Hordeum</i> Using Multiple Methods: Based on Morphological Data
The genus <i>Hordeum</i> (barley) represents an essential group within the Poaceae family, comprising diverse species with significant ecological and economic importance. This study aims to improve the infrageneric classification of <i>Hordeum</i> by integrating multiple anal...
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2024-12-01
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| Series: | Agronomy |
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| author | Nayoung Ro Pilmo Sung Mesfin Haile Hyemyeong Yoon Dong-Su Yu Ho-Cheol Ko Gyu-Taek Cho Hee-Jong Woo Nam-Jin Chung |
| author_facet | Nayoung Ro Pilmo Sung Mesfin Haile Hyemyeong Yoon Dong-Su Yu Ho-Cheol Ko Gyu-Taek Cho Hee-Jong Woo Nam-Jin Chung |
| author_sort | Nayoung Ro |
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| description | The genus <i>Hordeum</i> (barley) represents an essential group within the Poaceae family, comprising diverse species with significant ecological and economic importance. This study aims to improve the infrageneric classification of <i>Hordeum</i> by integrating multiple analytical approaches based on morphological data. A comprehensive dataset of key morphological traits was compiled from a wide range of <i>Hordeum</i> accessions, including representatives from all major taxonomic groups within the genus. Understanding and classifying the evolutionary traits of barley species, particularly in terms of environmental adaptation, pest resistance, and productivity improvement, is essential. DNA-based classification methods allow precise molecular-level analysis but are resource-intensive, especially when large-scale processing is required. This study addresses these limitations by employing an integrative approach combining hierarchical clustering, Principal Component Analysis–Linear Discriminant Analysis (PCA-LDA), and Random Forest (RF) to analyze the compiled morphological datasets. Morphological clustering via hierarchical analysis revealed clear taxonomic distinctions, achieving 86.0% accuracy at the subgenus level and 83.1% at the section level. PCA-LDA further refined classification by identifying key traits such as seed width, area, and 100-seed weight as primary contributors, achieving perfect accuracy for the <i>Hordeum</i> section and high accuracy for species like <i>Hordeum vulgare</i> and <i>Hordeum spontaneum</i>. RF analysis enhanced classification performance, achieving 100% accuracy at the section level and high accuracy for species with sufficient data. This approach offers a new framework for classifying diverse barley species and contributes significantly to data-driven decision-making in breeding and conservation efforts, supporting a deeper understanding of barley’s adaptive evolution in response to environmental changes. |
| format | Article |
| id | doaj-art-8785fc1242834d90805933576d83cac4 |
| institution | Kabale University |
| issn | 2073-4395 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj-art-8785fc1242834d90805933576d83cac42025-01-24T13:16:32ZengMDPI AGAgronomy2073-43952024-12-011516010.3390/agronomy15010060A Study on the Infrageneric Classification of <i>Hordeum</i> Using Multiple Methods: Based on Morphological DataNayoung Ro0Pilmo Sung1Mesfin Haile2Hyemyeong Yoon3Dong-Su Yu4Ho-Cheol Ko5Gyu-Taek Cho6Hee-Jong Woo7Nam-Jin Chung8National Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of KoreaNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of KoreaNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of KoreaNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of KoreaNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of KoreaNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of KoreaNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of KoreaNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of KoreaDepartment of Crop Science and Biotechnology, Chonbuk National University, Jeonju 54896, Republic of KoreaThe genus <i>Hordeum</i> (barley) represents an essential group within the Poaceae family, comprising diverse species with significant ecological and economic importance. This study aims to improve the infrageneric classification of <i>Hordeum</i> by integrating multiple analytical approaches based on morphological data. A comprehensive dataset of key morphological traits was compiled from a wide range of <i>Hordeum</i> accessions, including representatives from all major taxonomic groups within the genus. Understanding and classifying the evolutionary traits of barley species, particularly in terms of environmental adaptation, pest resistance, and productivity improvement, is essential. DNA-based classification methods allow precise molecular-level analysis but are resource-intensive, especially when large-scale processing is required. This study addresses these limitations by employing an integrative approach combining hierarchical clustering, Principal Component Analysis–Linear Discriminant Analysis (PCA-LDA), and Random Forest (RF) to analyze the compiled morphological datasets. Morphological clustering via hierarchical analysis revealed clear taxonomic distinctions, achieving 86.0% accuracy at the subgenus level and 83.1% at the section level. PCA-LDA further refined classification by identifying key traits such as seed width, area, and 100-seed weight as primary contributors, achieving perfect accuracy for the <i>Hordeum</i> section and high accuracy for species like <i>Hordeum vulgare</i> and <i>Hordeum spontaneum</i>. RF analysis enhanced classification performance, achieving 100% accuracy at the section level and high accuracy for species with sufficient data. This approach offers a new framework for classifying diverse barley species and contributes significantly to data-driven decision-making in breeding and conservation efforts, supporting a deeper understanding of barley’s adaptive evolution in response to environmental changes.https://www.mdpi.com/2073-4395/15/1/60barleyidentification keysquantitative traitsRFPCA-LDAphylogenetic study |
| spellingShingle | Nayoung Ro Pilmo Sung Mesfin Haile Hyemyeong Yoon Dong-Su Yu Ho-Cheol Ko Gyu-Taek Cho Hee-Jong Woo Nam-Jin Chung A Study on the Infrageneric Classification of <i>Hordeum</i> Using Multiple Methods: Based on Morphological Data Agronomy barley identification keys quantitative traits RF PCA-LDA phylogenetic study |
| title | A Study on the Infrageneric Classification of <i>Hordeum</i> Using Multiple Methods: Based on Morphological Data |
| title_full | A Study on the Infrageneric Classification of <i>Hordeum</i> Using Multiple Methods: Based on Morphological Data |
| title_fullStr | A Study on the Infrageneric Classification of <i>Hordeum</i> Using Multiple Methods: Based on Morphological Data |
| title_full_unstemmed | A Study on the Infrageneric Classification of <i>Hordeum</i> Using Multiple Methods: Based on Morphological Data |
| title_short | A Study on the Infrageneric Classification of <i>Hordeum</i> Using Multiple Methods: Based on Morphological Data |
| title_sort | study on the infrageneric classification of i hordeum i using multiple methods based on morphological data |
| topic | barley identification keys quantitative traits RF PCA-LDA phylogenetic study |
| url | https://www.mdpi.com/2073-4395/15/1/60 |
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