From Phenotype to Phenomics: Multidimensional Classification of Plant Traits

Abstract:

Phenotypic traits represent the observable outcomes of interactions between plant genetic architecture and environmental conditions and form the foundation for understanding plant growth, adaptation, and productivity. With the rapid advancement of high-throughput phenotyping and phenomics platforms, trait evaluation has evolved from isolated measurements toward integrative, data-driven frameworks capable of capturing structural, physiological, and functional plant responses across spatial and temporal scales. However, the expanding diversity of measurable traits and analytical approaches has created a need for a coherent conceptual framework that organizes phenotypic traits in a biologically meaningful and experimentally practical manner. This review addresses this gap by synthesizing existing knowledge and presenting a comprehensive classification of plant phenotypic traits based on measurement strategy, including direct and surrogate traits, as well as biological organization, developmental stage, functional relevance, environmental responsiveness, and genetic control. Particular emphasis is placed on the growing role of surrogate image-derived traits as scalable proxies for complex physiological processes, enabling rapid, non-destructive phenotyping across large populations. By integrating traditional trait concepts with modern imaging technologies, sensor systems, and data analytics, the review highlights how multidimensional trait classification strengthens genotype-phenotype interpretation, improves experimental design, and accelerates precision breeding efforts. Ultimately, this synthesis provides a unified perspective linking phenomics technologies with plant biology, offering a conceptual and methodological foundation for advancing crop improvement and developing climate-resilient agricultural systems.