{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T06:04:06Z","timestamp":1789365846941,"version":"build-2803163510"},"reference-count":54,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T00:00:00Z","timestamp":1789344000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Plant Sci."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Accurate extraction of maize seedling phenotypes is essential for early growth assessment, yet field-grown seedlings exhibit complex backgrounds, non-rigid leaf deformation, self-occlusion, and adhered leaves that challenge three-dimensional point-cloud analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Here, we developed a workflow integrating PMSPA-Net, an enhanced PointNet++ model, with geometric region decomposition for semantic and organ-level segmentation of field-grown maize seedlings. Multi-view RGB images of 65 complete plants were reconstructed with OpenMVS, and all data were partitioned at the whole-plant level before point-block sampling. Fifteen plants were retained as a fixed independent test set, while the remaining samples were used for training and validation across three predefined random seeds.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Under a common protocol, PMSPA-Net outperformed PointNet, PointNet++, DGCNN, and RandLA-Net, achieving an mIoU of 0.8286 \u00b1 0.0149, a macro-F1 of 0.8981 \u00b1 0.0238, and a balanced accuracy of 0.9561 \u00b1 0.0223. A four-configuration ablation study showed complementary gains from the multi-scale spatial pyramid attention module and IOA-based hyperparameter optimization. Geometric region decomposition also achieved more accurate and complete adhered-leaf separation than DBSCAN in three annotated cases. Point-cloud-derived leaf length and width agreed well with manual measurements.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>This workflow demonstrates the feasibility of integrated semantic and organ-level phenotyping under the evaluated field conditions; validation across additional sites, developmental stages, and acquisition conditions is required before broader generalization.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpls.2026.1920542","type":"journal-article","created":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T05:38:56Z","timestamp":1789364336000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["PMSPA-Net framework with geometric region decomposition for high-precision phenotyping of field-grown maize seedlings"],"prefix":"10.3389","volume":"17","author":[{"given":"Jing","family":"Zhou","sequence":"first","affiliation":[{"name":"College of Information and Technology, Jilin Agricultural University","place":["Changchun, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenlong","family":"Zou","sequence":"additional","affiliation":[{"name":"College of Information and Technology, Jilin Agricultural University","place":["Changchun, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yushan","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Information and Technology, Jilin Agricultural University","place":["Changchun, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Helong","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Information and Technology, Jilin Agricultural University","place":["Changchun, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingren","family":"Cui","sequence":"additional","affiliation":[{"name":"College of Information and Technology, Jilin Agricultural University","place":["Changchun, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianyu","family":"Lu","sequence":"additional","affiliation":[{"name":"Faculty of Agronomy, Jilin Agricultural University","place":["Changchun, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lixin","family":"Hou","sequence":"additional","affiliation":[{"name":"College of Information and Technology, Jilin Agricultural University","place":["Changchun, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yijia","family":"Tang","sequence":"additional","affiliation":[{"name":"College of Information and Technology, Jilin Agricultural University","place":["Changchun, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yudi","family":"Gao","sequence":"additional","affiliation":[{"name":"College of Information and Technology, Jilin Agricultural University","place":["Changchun, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Information and Technology, Jilin Agricultural University","place":["Changchun, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuntao","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Information and Electrical Engineering, China Agricultural University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Zhang","sequence":"additional","affiliation":[{"name":"Faculty of Agronomy, Jilin Agricultural University","place":["Changchun, China"]},{"name":"Department of Biology, University of British Columbia, Okanagan","place":["Kelowna, BC, Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,14]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2024.109033","article-title":"Unlocking plant secrets: A systematic review of 3D imaging in plant phenotyping techniques","volume":"222","author":"Akhtar","year":"2024","journal-title":"Comput. 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