{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T00:21:56Z","timestamp":1779236516019,"version":"3.51.4"},"reference-count":52,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2020,5,12]],"date-time":"2020-05-12T00:00:00Z","timestamp":1589241600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation","award":["31471409"],"award-info":[{"award-number":["31471409"]}]},{"name":"Project of Scientific Operating Expenses, Ministry of Education of China","award":["2017PT19"],"award-info":[{"award-number":["2017PT19"]}]},{"name":"the National Key Research and Development Program","award":["2016YFD0200600-2016YFD0200602"],"award-info":[{"award-number":["2016YFD0200600-2016YFD0200602"]}]},{"name":"the Key Research and Development Project of Shandong Province","award":["2019GNC106091"],"award-info":[{"award-number":["2019GNC106091"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Plant height and leaf area are important morphological properties of leafy vegetable seedlings, and they can be particularly useful for plant growth and health research. The traditional measurement scheme is time-consuming and not suitable for continuously monitoring plant growth and health. Individual vegetable seedling quick segmentation is the prerequisite for high-throughput seedling phenotype data extraction at individual seedling level. This paper proposes an efficient learning- and model-free 3D point cloud data processing pipeline to measure the plant height and leaf area of every single seedling in a plug tray. The 3D point clouds are obtained by a low-cost red\u2013green\u2013blue (RGB)-Depth (RGB-D) camera. Firstly, noise reduction is performed on the original point clouds through the processing of useable-area filter, depth cut-off filter, and neighbor count filter. Secondly, the surface feature histograms-based approach is used to automatically remove the complicated natural background. Then, the Voxel Cloud Connectivity Segmentation (VCCS) and Locally Convex Connected Patches (LCCP) algorithms are employed for individual vegetable seedling partition. Finally, the height and projected leaf area of respective seedlings are calculated based on segmented point clouds and validation is carried out. Critically, we also demonstrate the robustness of our method for different growth conditions and species. The experimental results show that the proposed method could be used to quickly calculate the morphological parameters of each seedling and it is practical to use this approach for high-throughput seedling phenotyping.<\/jats:p>","DOI":"10.3390\/rs12101540","type":"journal-article","created":{"date-parts":[[2020,5,12]],"date-time":"2020-05-12T10:53:55Z","timestamp":1589280835000},"page":"1540","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["An Efficient Processing Approach for Colored Point Cloud-Based High-Throughput Seedling Phenotyping"],"prefix":"10.3390","volume":"12","author":[{"given":"Si","family":"Yang","sequence":"first","affiliation":[{"name":"Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China"},{"name":"College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China"},{"name":"Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lihua","family":"Zheng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China"},{"name":"College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China"},{"name":"Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wanlin","family":"Gao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China"},{"name":"College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bingbing","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China"},{"name":"College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xia","family":"Hao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China"},{"name":"College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaqi","family":"Mi","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China"},{"name":"College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China"},{"name":"Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minjuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China"},{"name":"College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China"},{"name":"College of Information Science and Engineering, Shandong Agriculture and Engineering University, Jinan 251100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1016\/j.tplants.2011.09.005","article-title":"Phenomics\u2013technologies to relieve the phenotyping bottleneck","volume":"16","author":"Furbank","year":"2011","journal-title":"Trends Plant Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.tplants.2013.09.008","article-title":"Field high-throughput phenotyping: The new crop breeding frontier","volume":"19","author":"Araus","year":"2014","journal-title":"Trends Plant Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1016\/j.biosystemseng.2013.02.006","article-title":"Machine vision techniques for the evaluation of seedling quality based 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