{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T15:14:52Z","timestamp":1785942892844,"version":"3.56.0"},"reference-count":56,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T00:00:00Z","timestamp":1785196800000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDB1580101"],"award-info":[{"award-number":["XDB1580101"]}]},{"name":"Research Fund of the State Key Laboratory of Plant Trait Design","award":["PDTD001"],"award-info":[{"award-number":["PDTD001"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["RENCAI2025041"],"award-info":[{"award-number":["RENCAI2025041"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000268","name":"Biotechnology and Biological Sciences Research Council","doi-asserted-by":"publisher","award":["BB\/Y513969\/1"],"award-info":[{"award-number":["BB\/Y513969\/1"]}],"id":[{"id":"10.13039\/501100000268","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000268","name":"Biotechnology and Biological Sciences Research Council","doi-asserted-by":"publisher","award":["BB\/Y514081\/1"],"award-info":[{"award-number":["BB\/Y514081\/1"]}],"id":[{"id":"10.13039\/501100000268","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Seedling establishment represents a critical phase in early crop growth and development, directly influencing biomass accumulation and yield potential. To characterise early growth dynamics under field conditions, both growth rate and uniformity of emergence need to be assessed continuously; however, manual quantification of these dynamic traits in large-scale trials remains impractical. Here, we present LeafTip-RN, an open-source and deep learning (DL)-powered pipeline for dynamically measuring the early establishment of wheat (Triticum aestivum) in the field. To enable flexible and scalable data collection, ultra-low-altitude drone phenotyping was employed, followed by the development of an optimised DL model to automate the extraction of leaf-tip-related features from complex backgrounds. In order to address sparsity of data arising from the use of only eight phenotyping time-points, we integrated an image-to-video generative AI (GenAI) module into the pipeline to interpolate keyframes between early and late seedling stages (i.e. 18\u201340\u2005days after sowing, DAS), resulting in a training library comprising 353 019 labelled leaf tips. Using the pipeline, we successfully quantified multiple agronomically important traits related to establishment (e.g. plot-level leaf tips and seedling spatial uniformity) and then derived growth curves for 51 wheat varieties across two growing seasons (2024\u20132026). After validating these LeafTip-RN-derived traits, we further computed varietal relative growth rates and uniformity indices, based on which the varieties were classified into high-, medium-, and low-performance groups, and this revealed discrepancies between the LeafTip-RN-derived classification (18\u201340\u2005DAS) and a manual assessment at 40\u2005DAS when dynamic early performance was considered. Finally, to facilitate its broad adoption by the plant research community, we developed an openly accessible graphical user interface for non-expert users to visualise and analyse rapid seedling developmental changes. Taken together, our study provides a scalable GenAI-powered solution for evaluating seedling establishment in wheat that offers valuable tools for breeders and researchers to identify varieties with enhanced early growth vigour and emergence dynamics, and that are extensible to other cereal crops.<\/jats:p>","DOI":"10.1093\/jxb\/erag321","type":"journal-article","created":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T08:33:57Z","timestamp":1784709237000},"source":"Crossref","is-referenced-by-count":0,"title":["LeafTip-RN: generative AI-powered temporal interpolation for continuous phenotypic analysis of seedling establishment traits in wheat"],"prefix":"10.1093","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-7332-9915","authenticated-orcid":false,"given":"Jinlong","family":"Huang","sequence":"first","affiliation":[{"name":"College of Engineering, College of Smart Agriculture (College of Artificial Intelligence), Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University , Nanjing 210095 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3941-576X","authenticated-orcid":false,"given":"Jie","family":"Dai","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Plant Trait Design, CAS Center for Excellence in Molecular Plant Sciences (CEMPS), Shanghai Institute of Plant Physiology and Ecology (SIPPE), Chinese Academy of Sciences (CAS) , Shanghai 200032 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8191-1070","authenticated-orcid":false,"given":"Zhenjie","family":"Wen","sequence":"additional","affiliation":[{"name":"College of Engineering, College of Smart Agriculture (College of Artificial Intelligence), Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University , Nanjing 210095 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3896-2341","authenticated-orcid":false,"given":"Yumeng","family":"Wan","sequence":"additional","affiliation":[{"name":"College of Engineering, College of Smart Agriculture (College of Artificial Intelligence), Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University , Nanjing 210095 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8934-6879","authenticated-orcid":false,"given":"Suyan","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Engineering, College of Smart Agriculture (College of Artificial Intelligence), Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University , Nanjing 210095 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3218-4473","authenticated-orcid":false,"given":"Shuchen","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Engineering, College of Smart Agriculture (College of Artificial Intelligence), Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University , Nanjing 210095 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0048-7440","authenticated-orcid":false,"given":"Lei","family":"Ju","sequence":"additional","affiliation":[{"name":"National Institute of Agricultural Botany (NIAB), Crop Science Centre (CSC) , Cambridge CB3 0LE ,","place":["UK"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5727-0656","authenticated-orcid":false,"given":"Xiaomin","family":"Song","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Plant Trait Design, CAS Center for Excellence in Molecular Plant Sciences (CEMPS), Shanghai Institute of Plant Physiology and Ecology (SIPPE), Chinese Academy of Sciences (CAS) , Shanghai 200032 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5330-4495","authenticated-orcid":false,"given":"Songtao","family":"Ban","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Plant Trait Design, CAS Center for Excellence in Molecular Plant Sciences (CEMPS), Shanghai Institute of Plant Physiology and Ecology (SIPPE), Chinese Academy of Sciences (CAS) , Shanghai 200032 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5752-5524","authenticated-orcid":false,"given":"Ji","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Engineering, College of Smart Agriculture (College of Artificial Intelligence), Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University , Nanjing 210095 ,","place":["China"]},{"name":"State Key Laboratory of Plant Trait Design, CAS Center for Excellence in Molecular Plant Sciences (CEMPS), Shanghai Institute of Plant Physiology and Ecology (SIPPE), Chinese Academy of Sciences (CAS) , Shanghai 200032 ,","place":["China"]},{"name":"University of the Chinese Academy of Sciences , Beijing 100049 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,7,28]]},"reference":[{"key":"2026080510363528200_erag321-B1","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1111\/nph.19575","article-title":"Deciphering temporal growth patterns in maize: integrative modeling of phenotype dynamics and underlying genomic variations","volume":"242","author":"Adak","year":"2024","journal-title":"New 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