Bowman Christian S, Traband Ryan, Wang Xuesong, Knowles Sara P, Lo Sassoum, Jia Zhenyu, Vorsa Nicholi, Herniter Ira A
Department of Botany and Plant Sciences University of California Riverside, 2142 Batchelor Hall Riverside California 92521 USA.
Department of Plant Biology Rutgers University 59 Dudley Road New Brunswick New Jersey 08901 USA.
Appl Plant Sci. 2023 Mar 21;11(2):e11513. doi: 10.1002/aps3.11513. eCollection 2023 Mar-Apr.
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.
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.
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.
在使用数字图像分析软件时，从数字图像中测量叶片形态参数可能既耗时又有局限性。多叶样本提取系统（MuLES）是一种新工具，它能够以最少的用户输入或前提条件（如编码知识或图像修改）实现高通量叶片形状分析。
MuLES利用对比像素颜色值来区分叶片对象及其背景区域，无需其他软件方法通常所需的基于颜色阈值的方法或颜色校正卡。该软件测量的叶片形态参数，尤其是叶长宽比，能够以高通量方式区分同一物种的大量不同种质。
MuLES提供了一种从数字图像中快速测量大型植物群体叶片形态参数的简单方法，并证明了叶长宽比区分密切相关植物类型的能力。
