Plant architecture, defined as the three-dimensional structure and spatial arrangement of plant organs, is a key agronomic trait that strongly influences crop yield. However, the architectural complexity of cotton plants and subjective biases in manual visual assessments have caused inconsistencies in classifying plant architectures across cotton varieties, hindering precise classification. Currently, there is no systematic or standardized framework available for the quantitative classification of cotton plant architecture using digitized phenotypic measurements. In this study, we established an innovative framework for precise digitized 3D classification of cotton plant architecture, enabling quantitative analysis via a specialized integrated 3D phenotypic platform for imaging, modeling, and analysis. This platform rapidly reconstructs high-precision 3D models of individual cotton plants, from which we extracted quantitative, length, and ratio traits related to plant architecture. Among these traits, plant height (PH) and fruit branch horizontal distance (FBHD) were used to calculate the plant architecture decided angle (PADA), and a set of classification criteria was developed to categorize cotton plant architecture into nine distinct types: cylindrical, gyro, inverted triangular funnel, bullet, tower, shuttle, triangular funnel, inverted tower, and sandglass. Subsequently, we analyzed the relationship between architectural traits and cotton yield: total number of cotton bolls (TCB), bolls to branches ratio (BBR), bolls to bolling branches ratio (BBBR), and fruit branch length (FBL) exhibited highly significant correlations with yield ( P < 0.001). Finally, based on the established classification framework, we investigated architectural parameters of cotton varieties across three major cotton-growing regions in China (Northwest Inland, Yangtze River Basin, Yellow River Basin). The findings showed that FBL, fruit branch angle (FBA), and PH of varieties in the Northwest Inland were consistently lower than those in the other two regions. This study represents the first accurate, quantitative classification of cotton plant architecture. It provides an innovative view for investigating plant architectural characteristics, yield correlations, and their underlying molecular regulatory mechanisms in cotton.
Xu et al. (Fri,) studied this question.