{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T12:03:53Z","timestamp":1790337833519,"version":"4.1.0"},"reference-count":0,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T00:00:00Z","timestamp":1790294400000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Quantitative studies of plant growth and environmental responses increasingly rely on time-series imaging, yet automated segmentation remains challenging due to continuous growth, large non-rigid morphological change, and frequent self-occlusion. Traditional image-processing pipelines and task-specific deep learning models often require extensive annotated datasets and retraining, limiting portability across species, developmental stages, and imaging conditions.<\/jats:p>\n                  <jats:p>Here we present SAP (Segment Any Plant), a plant-focused framework that leverages the pretrained Segment Anything Model 2 (SAM2) to enable few-shot, training-free segmentation of plant time-series imagery. SAP integrates interactive prompting, automated temporal mask propagation, and centerline extraction within a web-based interface, allowing users to move from raw images to quantitative descriptors of organ shape, growth, and dynamics without programming expertise.<\/jats:p>\n                  <jats:p>Across multiple systems, including Arabidopsis thaliana rosette development, root growth, sunflower gravitropism, and confocal root microscopy, SAP achieves high segmentation accuracy on macroscopic organs (mean IoU 0.89\u20130.93) and pixel-level centerline precision from single-frame prompting, with lower but promising accuracy at the cellular scale (confocal, mean IoU 0.75) that we report as a proof of concept. By reducing the need for task-specific retraining, SAP provides a transferable framework for reproducible time-series phenotyping across diverse experimental contexts.<\/jats:p>","DOI":"10.1093\/jxb\/erag467","type":"journal-article","created":{"date-parts":[[2026,9,20]],"date-time":"2026-09-20T11:22:22Z","timestamp":1789903342000},"source":"Crossref","is-referenced-by-count":0,"title":["Segment Any Plant (SAP): Foundation-Model Segmentation for Plant Time-Series Phenotyping"],"prefix":"10.1093","author":[{"given":"Alex","family":"Abbey","sequence":"first","affiliation":[{"name":"The Center for Physics and Chemistry of Living Systems, Tel-Aviv University , Tel Aviv 6997801 ,","place":["Israel"]},{"name":"Department of Condensed Matter, School of Physics and Astronomy, Tel Aviv University , Tel Aviv 69978 ,","place":["Israel"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4752-0372","authenticated-orcid":false,"given":"Yasmine","family":"Meroz","sequence":"additional","affiliation":[{"name":"School of Plant Sciences and Food Security, Tel Aviv University , Tel Aviv 6997801 ,","place":["Israel"]},{"name":"The Center for Physics and Chemistry of Living Systems, Tel-Aviv University , Tel Aviv 6997801 ,","place":["Israel"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,9,25]]},"container-title":["Journal of Experimental Botany"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/jxb\/advance-article-pdf\/doi\/10.1093\/jxb\/erag467\/71395102\/erag467.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jxb\/advance-article-pdf\/doi\/10.1093\/jxb\/erag467\/71395102\/erag467.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T11:47:20Z","timestamp":1790336840000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jxb\/advance-article\/doi\/10.1093\/jxb\/erag467\/8835663"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,25]]},"references-count":0,"URL":"https:\/\/doi.org\/10.1093\/jxb\/erag467","relation":{},"ISSN":["0022-0957","1460-2431"],"issn-type":[{"value":"0022-0957","type":"print"},{"value":"1460-2431","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,25]]},"article-number":"erag467"}}