Hongmin Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Hongmin Liu has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Gailing Zhang
College of Agronomy, Xinyang Agriculture and Forestry University, Xinyang 464000, China
1 shared publication - Hongzhong Shi
College of Agronomy, Xinyang Agriculture and Forestry University, Xinyang 464000, China
1 shared publication - Pengliang Pan
College of Agronomy, Xinyang Agriculture and Forestry University, Xinyang 464000, China
1 shared publication - Ruifei Wang
College of Agronomy, Xinyang Agriculture and Forestry University, Xinyang 464000, China
1 shared publication - Shibao Guo
College of Agronomy, Xinyang Agriculture and Forestry University, Xinyang 464000, China
1 shared publication - Zhou Zhou
College of Agronomy, Xinyang Agriculture and Forestry University, Xinyang 464000, China
1 shared publication
Latest Publications
- Open Access
To Explore the Utility of Leaf Morphological, Color, and Chlorophyll Traits in Assessing Inter-Cultivar Variations Among Six Tea Plant Cultivars
Reliable traits are needed for identification of tea (Camellia sinensis) cultivars, yet the stability of leaf morphology and color across leaf positions remains unclear. This study evaluated inter-cultivar variation and positional stability in leaf morphological, RGB color, and SPAD traits in six predominant cultivars. One-year-old shoots were sampled in a completely randomized design, and five fully expanded leaves below the apical bud were analyzed. SPAD values were measured with a chlorophyll meter, and scanned images were used to extract contour and RGB traits. Data were analyzed using ANOVA, correlation analysis, PCA, and discriminant analysis. Leaf morphology differed among cultivars and leaf positions, with significant cultivar-by-position interactions; however, the width-to-length ratio differed among cultivars but remained stable across positions in these cultivars. SPAD values increased with leaf position and were strongly associated with RGB components, being negatively correlated with R and G and positively correlated with B. Morphological traits explained 52.988% of total variance in PCA and yielded 64.6% overall classification accuracy, with LaoHan showing the highest accuracy (83.3%). Misclassification was concentrated among genetically similar cultivars. These findings suggest that stable leaf shape proportions and SPAD–RGB relationships provide useful descriptors, whereas genetic relatedness limits morphology-based cultivar identification under the present conditions.
Open AccessTo Explore the Utility of Leaf Morphological, Color, and Chlorophyll Traits in Assessing Inter-Cultivar Variations Among Six Tea Plant Cultivars
Reliable traits are needed for identification of tea (Camellia sinensis) cultivars, yet the stability of leaf morphology and color across leaf positions remains unclear. This study evaluated inter-cultivar variation and positional stability in leaf morphological, RGB color, and SPAD traits in six predominant cultivars. One-year-old shoots were sampled in a completely randomized design, and five fully expanded leaves below the apical bud were analyzed. SPAD values were measured with a chlorophyll meter, and scanned images were used to extract contour and RGB traits. Data were analyzed using ANOVA, correlation analysis, PCA, and discriminant analysis. Leaf morphology differed among cultivars and leaf positions, with significant cultivar-by-position interactions; however, the width-to-length ratio differed among cultivars but remained stable across positions in these cultivars. SPAD values increased with leaf position and were strongly associated with RGB components, being negatively correlated with R and G and positively correlated with B. Morphological traits explained 52.988% of total variance in PCA and yielded 64.6% overall classification accuracy, with LaoHan showing the highest accuracy (83.3%). Misclassification was concentrated among genetically similar cultivars. These findings suggest that stable leaf shape proportions and SPAD–RGB relationships provide useful descriptors, whereas genetic relatedness limits morphology-based cultivar identification under the present conditions.