Plant phenotyping is the primary task of any plant breeding program, and accurate measurement of plant traits is essential to select genotypes with better quality, high yield, and climate resilience. The majority of currently used phenotyping techniques are destructive and time-consuming. Recently, the development of various sensors and imaging platforms for rapid and efficient quantitative measurement of plant traits has become the mainstream approach in plant phenotyping studies. Here, we reviewed the trends of image-based high-throughput phenotyping methods applied to horticultural crops. High-throughput phenotyping is carried out using various types of imaging platforms developed for indoor or field conditions. We highlighted the applications of different imaging platforms in the horticulture sector with their advantages and limitations. Furthermore, the principles and applications of commonly used imaging techniques, visible light (RGB) imaging, thermal imaging, chlorophyll fluorescence, hyperspectral imaging, and tomographic imaging for high-throughput plant phenotyping, are discussed. High-throughput phenotyping has been widely used for phenotyping various horticultural traits, which can be morphological, physiological, biochemical, yield, biotic, and abiotic stress responses. Moreover, the ability of high-throughput phenotyping with the help of various optical sensors will lead to the discovery of new phenotypic traits which need to be explored in the future. We summarized the applications of image analysis for the quantitative evaluation of various traits with several examples of horticultural crops in the literature. Finally, we summarized the current trend of high-throughput phenotyping in horticultural crops and highlighted future perspectives.

Background/Objectives: Senna tora and Senna obtusifolia are closely related herbaceous plant species with highly similar morphology that serve as important sources of herbal medicine. These two species have long been subject to taxonomic ambiguity. In this study, we aimed to clarify their phylogenetic relationship using chloroplast genome sequences and 45S nuclear ribosomal DNA (nrDNA) sequences. Methods: We assembled and analyzed complete chloroplast genomes and 45S nrDNA sequences of three Senna accessions (K276760, IT104602, and K276758) and used these datasets for phylogenetic analysis together with those of previously reported Senna species. We then performed comparative analyses to identify informative polymorphisms between S. tora and S. obtusifolia. Results: The chloroplast genomes of K276760 and IT104602 were identical in length (162,218 bp), whereas the K276758 genome was slightly larger (162,347 bp). All three chloroplast genomes exhibited quadripartite structure typical of angiosperm chloroplast genomes and contained 112 unique genes. The 45S nrDNA sequences of all three accessions were 5852 bp long and consisted of 18S rRNA, ITS1, 5.8S rRNA, ITS2, and 26S rRNA. Phylogenetic analysis based on both chloroplast genome and 45S nrDNA sequences resolved S. tora and S. obtusifolia into separate, well-supported clades. K276760 and IT104602 were assigned to the S. obtusifolia clade, whereas K276758 showed greater affinity towards S. tora. We identified single-nucleotide polymorphisms (SNPs) and insertion/deletion (InDel) polymorphisms, and developed three candidate InDel markers to distinguish S. tora from S. obtusifolia. Conclusions: The congruent chloroplast genome and 45S nrDNA phylogenies provide strong molecular evidence for species-level differences between S. tora and S. obtusifolia. The sequence datasets and candidate InDel markers developed in this study will be useful for species identification and future taxonomic and evolutionary studies within Senna.