摘要
【目的】探究一种简便、快捷、低成本的植物叶片表型参数获取方法。【方法】以香瓜茄(Solanum muricatum)为例,采用扫描仪获取离体叶片数字图像,用Image J软件对其表型参数进行测量,并把结果与使用Digimizer软件测量得到的结果进行比较,以此验证方法的可靠性,同时分析了图像质量(图像格式与分辨率)对软件测量结果的影响。【结果】两种软件对香瓜茄叶面积、叶周长、叶长和叶宽测量结果的标准均方根误差(NRMSE)分别为0.471%、1.103%、0.391%和1.662%,相关系数均大于0.97。图像质量会对Image J软件的测量结果有一定影响,对灰度格式或低分辨率图像的影响要小于彩色格式或高分辨率图像,但两种因素叠加会加剧这种影响。【结论】经改进后的扫描仪结合Image J软件测量植物叶片表型参数的方法,具有低成本、半自动、快速、精确、批量等优点,可以为植物叶片表型参数的测量提供一定参考。
【Objective】To seek for a simple,rapid and low-cost method of obtaining the phenotypic parameters of plant leaves.【Methods】Taking Solanum muricatum as an example,digital images of detached leaves were taken by scanner,and Image J software was used to measure phenotypic parameters.The results were compared to those obtained using the Digimizer software to verify the reliability of the method.Additionally the impact of image quality(image format and resolution)on software measurement results was also analyzed.【Results】In measuring the leaf area,leaf circumference,leaf length,and leaf width of Solanum muricatum,the standard root mean square errors(NRMSE)of the two software were 0.471%,1.103%,0.391%and 1.662%,respectively.The correlation coefficients were higher than 0.97.The measuring outcomes of the Image J software were somewhat impacted by the image quality.The impact on grayscale format or low resolution images was smaller than that on color format or high resolution images,but the superposition of the two factors will aggravate the impact.【Conclusion】The improved method by using scanner combined with Image J software to measure phenotypic parameters of plant leaves has the advantages of low cost,semi-automatic,quick and accurate as well as batch processing,which provided references for the measurement of phenotypic parameters of plant leaves.
作者
杨文源
俞玉
张世媛
张娟
玛伊努尔·图尔荪
杨涛
徐丽萍
YANG Wenyuan;YU Yu;ZHANG Shiyuan;ZHANG Juan;Maynur Tursun;YANG Tao;XU Liping(College of Biology and Geographical Sciences,Yili Normal University,Yining 835000,China;School of Information Engineering,Lanzhou City University,Lanzhou 730000,China;Institute of Resources and Ecology,Yili Normal University,Yining 835000,China)
出处
《北方农业学报》
2022年第6期128-134,共7页
Journal of Northern Agriculture
基金
2021年度国家级大学生创新创业训练计划项目(202110764002)。