Ryan C. Traband

This study utilized the Fourier-based method to analyze the morphology of over 4000 leaves from more than 190 accessions selected from the Givaudan Citrus Variety Collection at the University of California Riverside, one of the world’s most diverse collections of citrus and closely related genera. Our analysis revealed significant variations in leaf morphology among the major citrus species groups, and hybrid varieties produced through breeding exhibited intermediate leaf morphology compared to their parental citrus species. We found a positive correlation between leaf area in native citrus species and temperature in lower tropical latitudes, while negative/positive associations between aspect ratio and temperature/rainfall were also observed, respectively. These results suggest that citrus leaves may have evolved into larger but thinner leaves to increase their photosynthetic capacity per unit area while maintaining water balance by reducing water loss through transpiration. Our analysis also indicates that the existing biodiversity observed in citrus species can be attributed to their migrations across the foothills of the Himalayas, southward to the islands of Indonesia, and northward to the islands of Japan. Our study supports the hypothesis that citrus species have adapted to warm areas lacking extreme daily and nightly temperatures, where a large number of species of origin are found. Overall, this study presents a promising approach to investigate the morphological variation in citrus leaves, which could potentially aid in the selection and breeding of citrus cultivars with superior physiological traits and deepen our understanding of citrus diversity.

Premise: The measurement of leaf morphometric parameters from digital images can be time‐consuming or restrictive when using digital image analysis softwares. The Multiple Leaf Sample Extraction System (MuLES) is a new tool that enables high‐throughput leaf shape analysis with minimal user input or prerequisites, such as coding knowledge or image modification.Methods and Results: MuLES uses contrasting pixel color values to distinguish between leaf objects and their background area, eliminating the need for color threshold–based methods or color correction cards typically required in other software methods. The leaf morphometric parameters measured by this software, especially leaf aspect ratio, were able to distinguish between large populations of different accessions for the same species in a high‐throughput manner.Conclusions: MuLES provides a simple method for the rapid measurement of leaf morphometric parameters in large plant populations from digital images and demonstrates the ability of leaf aspect ratio to distinguish between closely related plant types.