摘要
为快速估测并直观显示植物叶绿素含量的冠层分布,以苗期的簸箕柳作为研究对象,构建了一套多视角表型信息采集平台,通过目标检测算法YOLO v5检测识别出植物分枝区域并提取不同色彩空间下的主枝部分分层色彩因子,对比多种模型回归方法,将多组色彩因子组合与手持式叶绿素含量测定仪测得的SPAD进行反演建模,得到拟合度最高的色彩因子组合回归模型;将该模型应用于整株苗木图像来表征SPAD的冠层分布,实现叶绿素含量在整株植物分布上的可视化。结果表明:通过对比多种回归算法下不同色彩因子组合模型与SPAD指数的相关性,发现在RGB空间下由色彩因子R、G、B、G/R、G/B构建的对数项岭回归算法拟合模型效果最佳,其拟合度最高(R^(2)为0.73),且误差最小(RMSE为2.16)。本文通过采集多视角图像,基于YOLO v5目标检测模型识别出植物主枝冠层区域,得到叶绿素含量冠层分布的最佳估测模型并进行可视化,可实现植物苗期生长的监测与植物长势的快速评判,为氮胁迫早期诊断和氮肥科学施加提供技术指导。
Chlorophyll content plays an important role in plant photosynthesis,and is indicative of the growth and health of plants.There has been strong interest to measure chlorophyll content quickly and nondestructively,and visualize its spatial distribution in plants.A custom-made imaging platform was used to acquire multi-view RGB images of the seedlings of Salix suchowensis Cheng,a close sister species of poplar.An experiment in growth chamber was conducted involving 32 seedlings.These seedlings was subjected to four levels of nitrogen rates.A series of image processing algorithms was developed,which allowed us to detect the main branch of the plants(using YOLO v5),extract color indices from the main branch to estimate SPAD values(using ridge regression),and obtain the best color factor combination regression model by comparing various model regression methods.The results showed that the best performing regression model to estimate SPAD values employed six color indices derived from the RGB images as predictor variables,with R^(2) of 0.73 and RMSE of 2.16.Finally,the spatial distribution of chlorophyll content of the whole seedling was developed and visualized.In conclusion,the rapid and non-destructive approach to estimate chlorophyll content of poplar seedlings using high-throughput,multi-view RGB imaging was investigated.The imaging platform,the algorithms for plant image analysis and color indices extraction,as well as the models to estimate SPAD readings,provided technical feasibilities to continually assess growth and health related parameters for tree seedlings,and could guide the early diagnosis of nitrogen stress in plants and suitable application of nitrogen fertilizers.
作者
张慧春
张萌
边黎明
葛玉峰
李小平
ZHANG Huichun;ZHANG Meng;BIAN Liming;GE Yufeng;LI Xiaoping(College of Mechanical and Electronic Engineering,Nanjing Forestry University,Nanjing 210037,China;Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources,Nanjing Forestry University,Nanjing 210037,China;College of Forestry,Nanjing Forestry University,Nanjing 210037,China;Biological Systems Engineering Department,University of Nebraska-Lincoln,Lincoln 68583,USA)
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2022年第4期313-321,共9页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家自然科学基金项目(32171790)
江苏省现代农机装备与技术示范推广项目(NJ202018)
江苏省六大人才高峰项目(NY058)
江苏省青蓝工程项目(苏教201842)
江苏省333工程项目(苏人20186)
江苏省重点研发计划现代农业项目(BE2021307)。
关键词
簸箕柳
叶绿素含量
估测拟合模型
表型信息
多视角图像
可视化
Salix suchowensis Cheng
chlorophyll content
estimation fitting model
phenotypic information
multi-view images
visualization
