草地学报 ›› 2025, Vol. 33 ›› Issue (4): 1201-1210.DOI: 10.11733/j.issn.1007-0435.2025.04.020

• 研究论文 • 上一篇    

基于RGB成像技术估算盐胁迫下紫花苜蓿幼苗生长性能

雷俊锋1,2, 王沛1,2, 陈有军1,2, 周青平1,2, 汪辉1,2   

  1. 1. 四川若尔盖高寒湿地生态系统国家野外科学观测研究站, 四川 成都 610041;
    2. 西南民族大学草地资源学院, 四川 成都 610041
  • 收稿日期:2024-07-29 修回日期:2024-10-05 发布日期:2025-04-28
  • 通讯作者: 汪辉,E-mail:zzbjwh@163.com
  • 作者简介:雷俊锋(1997-),男,汉族,四川成都人,硕士研究生,主要从事草地生态学研究,E-mail:996618231@qq.com
  • 基金资助:
    四川省自然科学基金项目(2024NSFSC0311);西南民族大学“双一流”项目(CX2023015)资助

Estimating Alfalfa Seedling Growth Characteristics under Salt Stress Based on RGB Imaging Technology

LEI Jun-feng1,2, WANG Pei1,2, CHEN You-jun1,2, ZHOU Qing-ping1,2, WANG Hui1,2   

  1. 1. Sichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, Chengdu, Sichuan Province 610041, China;
    2. Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, Sichuan Province 610041, China
  • Received:2024-07-29 Revised:2024-10-05 Published:2025-04-28

摘要: 为实现无损、高效、准确估算紫花苜蓿(Medicago sativa L.)幼苗生长性能指标,本研究基于LemnaTec Scananlyzer植物表型分析系统拍摄盐胁迫下29个紫花苜蓿品种幼苗顶视、正视和侧视RGB图像,分析筛选可估算幼苗生物量、叶绿素含量(Soil and plant analyzer development,SPAD)、叶面积和株高等生长性能指标的图像表型参数。结果表明:侧视图投影面积与紫花苜蓿幼苗叶干重、茎干重和总干重均具有显著的正相关关系;基于顶视、正视和侧视投影面积计算得到的5个参数中,VIAPVIntegrated Analysis Platform)对幼苗总干重具有较好的预测效果,模型为y=0.0054x+0.0305(R2=0.84)。侧视图投影面积和侧视图最小外接圆直径可分别用于建立紫花苜蓿幼苗叶面积和株高的估算模型(R2分别为0.71和0.84)。主成分分析表明,无盐胁迫、低盐胁迫(75 mmol·L-1)和高盐胁迫浓度(150和225 mmol·L-1)处理的幼苗图像表型参数明显在不同象限。顶视、正视和侧视3个角度投影面积和侧视图最小外接圆直径均在4个盐胁迫浓度梯度之间呈现显著性差异,能够估算紫花苜蓿幼苗生长性能,进而评价其耐盐胁迫能力。

关键词: 无损估算, 紫花苜蓿, RGB成像, 盐胁迫, 投影面积

Abstract: In order to estimate alfalfa seedling growth parameters by a non-inductive, high-efficiency and accurate method, RGB images of 29 alfalfa cultivars seedlings under salt stress were taken from the top, side and front view using the LemnaTec Scananlyzer. Phenotypic parameters acquired from RGB images were analyzed, including biomass, SPAD value (Soil and plant analyzer development), leaf area and plant height. Results showed that the object area from the side view images had the significantly positive correlation with the leaf dry weight, the stem dry weight and the total dry weight. Five indices were calculated using the object area from the top, side and front view images and VIAPVIntegrated Analysis Platform) could predict total dry weight better with the model of y=0.0054x+0.0305 (R2=0.84). The object area and the min enclosing circle diameter from the side view images could respectively estimate the leaf area and the plant height with the R2 of 0.71 and 0.84. According to the principal component analysis, phenotypic parameters of seedlings could be obviously separated in different quadrant for the treatments of no salt level, low salt level (75 mmol·L-1) and high salt level (150 and 225 mmol·L-1). The significant difference was found in the object area from three view images and the min enclosing circle diameter from the side view images among four salt stress levels. Thus, these phenotypic parameters could be used to estimate the growth characteristics and the salt tolerance of alfalfa seedlings.

Key words: Non-inductive estimation, Alfalfa, RGB imaging technology, Salt stress, Object area

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