{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T12:53:25Z","timestamp":1791896005026,"version":"4.3.4"},"reference-count":51,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T00:00:00Z","timestamp":1791849600000},"content-version":"vor","delay-in-days":42,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100004242","name":"Princess Nourah Bint Abdulrahman University","doi-asserted-by":"publisher","award":["PNURSP2026R20"],"award-info":[{"award-number":["PNURSP2026R20"]}],"id":[{"id":"10.13039\/501100004242","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Physiologia Plantarum"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Accurate quantification of early wheat growth is essential for improving productivity, resource\u2010use efficiency, and stress adaptation; however, conventional phenotyping approaches remain labor\u2010intensive and difficult to scale for breeding programs. This study evaluated the potential of UAV\u2010based multispectral phenotyping to rapidly and non\u2010destructively estimate early vegetation vigor across diverse wheat genotypes and identify vegetation indices most strongly associated with canopy development. A panel of 221 historical wheat genotypes was evaluated under irrigated field conditions at NIGAB\u2010NARC, Islamabad, Pakistan. Multispectral imagery was acquired at 47 and 61\u2009days after sowing using a MicaSense Altum\u2010PT sensor mounted on a DJI MATRICE 200 RTK V2 platform, producing ultra\u2010high\u2010resolution imagery (1.12\u20131.50\u2009cm GSD). Eighteen vegetation indices (VIs) were extracted and validated against Canopeo\u2010derived ground cover measurements. Significant variation was observed for all indices, while principal component analysis showed that the first two components explained 92% of the total variation, primarily driven by greenness\u2010 and biomass\u2010related traits. Most VIs exhibited strong positive correlations with ground cover, with nine indices showing correlation coefficients greater than 0.85. Among these, GNDVI, CIRE, and RENDVI consistently provided the highest predictive accuracy across both developmental stages, achieving\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    values of 0.86\u20130.91 with RMSE and MAE values below 0.055 and 0.045, respectively. These findings demonstrate that UAV\u2010based multispectral phenotyping provides a rapid, precise, and scalable framework for early\u2010stage wheat monitoring and offers strong potential for integration into high\u2010throughput breeding and precision agriculture programs.\n                  <\/jats:p>","DOI":"10.1111\/ppl.71145","type":"journal-article","created":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T12:29:22Z","timestamp":1791894562000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["<scp>UAV<\/scp>\n                    \u2010Based High\u2010Throughput Phenotyping for Early Canopy Vigor Quantification in Wheat"],"prefix":"10.1111","volume":"178","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-3557-9593","authenticated-orcid":false,"given":"Fara","family":"Muqaddas","sequence":"first","affiliation":[{"name":"National Institute for Genomics and Advanced Biotechnology (NIGAB)  Islamabad Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2544-0773","authenticated-orcid":false,"given":"Muhammad Asad","family":"Ullah","sequence":"additional","affiliation":[{"name":"National Institute for Genomics and Advanced Biotechnology (NIGAB)  Islamabad Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5076-0396","authenticated-orcid":false,"given":"Latifa","family":"AlHusnain","sequence":"additional","affiliation":[{"name":"Department of Biology, College of Science Princess Nourah bint Abdulrahman University  Riyadh Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muneera D.F.","family":"AlKahtani","sequence":"additional","affiliation":[{"name":"Department of Biology, College of Science Princess Nourah bint Abdulrahman University  Riyadh Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2697-4957","authenticated-orcid":false,"given":"Muhammad Kashif","family":"Naeem","sequence":"additional","affiliation":[{"name":"National Institute for Genomics and Advanced Biotechnology (NIGAB)  Islamabad Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8329-9762","authenticated-orcid":false,"given":"Muhammad","family":"Uzair","sequence":"additional","affiliation":[{"name":"National Institute for Genomics and Advanced Biotechnology (NIGAB)  Islamabad Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2902-9858","authenticated-orcid":false,"given":"Sajad","family":"Ali","sequence":"additional","affiliation":[{"name":"Department of Biological Sciences, College of Science King Faisal University  Al\u2010Ahsa Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2626-1694","authenticated-orcid":false,"given":"Muhammad","family":"Hamza","sequence":"additional","affiliation":[{"name":"National Institute for Genomics and Advanced Biotechnology (NIGAB)  Islamabad Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4522-3972","authenticated-orcid":false,"given":"Muhammad","family":"Aqeel","sequence":"additional","affiliation":[{"name":"National Institute for Genomics and Advanced Biotechnology (NIGAB)  Islamabad Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2992-1765","authenticated-orcid":false,"given":"Kotb A.","family":"Attia","sequence":"additional","affiliation":[{"name":"Center of Excellence in Biotechnology Research, King Saud University  Riyadh Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9097-4359","authenticated-orcid":false,"given":"Sajid","family":"Fiaz","sequence":"additional","affiliation":[{"name":"Institute of Molecular Biology and Biotechnology, The University of Lahore  Lahore Pakistan"},{"name":"Life Sciences Research Center, Western Caspian University  Baku Azerbaijan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0603-2209","authenticated-orcid":false,"given":"Seung Hwan","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Biotechnology Chonnam National University, Chonnam  Yeosu South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad Ramzan","family":"Khan","sequence":"additional","affiliation":[{"name":"National Institute for Genomics and Advanced Biotechnology (NIGAB)  Islamabad Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,10,13]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"crossref","first-page":"1709","DOI":"10.3390\/agronomy13071709","article-title":"Enhancing Essential Grains Yield for Sustainable Food Security and Bio\u2010Safe Agriculture Through Latest Innovative Approaches","volume":"13","author":"Albahri G.","year":"2023","journal-title":"Agronomy"},{"key":"e_1_2_11_3_1","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1007\/s13562-024-00949-2","article-title":"High Throughput Phenomics in Elucidating Drought Stress Responses in Rice (\n                     Oryza sativa\n                   L.)","volume":"34","author":"Anand S.,. L.","year":"2025","journal-title":"Journal of Plant Biochemistry and Biotechnology"},{"key":"e_1_2_11_4_1","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1071\/FP13126","article-title":"Development and Evaluation of a Field\u2010Based High\u2010Throughput Phenotyping Platform","volume":"41","author":"Andrade\u2010Sanchez P.","year":"2013","journal-title":"Functional Plant Biology"},{"key":"e_1_2_11_5_1","doi-asserted-by":"crossref","first-page":"324","DOI":"10.9734\/ijecc\/2023\/v13i81957","article-title":"Remote Sensing as a Management and Monitoring Tool for Agriculture: Potential Applications","volume":"13","author":"Ashraf A.","year":"2023","journal-title":"International Journal of Environment and Climate Change"},{"key":"e_1_2_11_6_1","doi-asserted-by":"crossref","first-page":"10395","DOI":"10.3390\/rs61110395","article-title":"Estimating Biomass of Barley Using Crop Surface Models (CSMs) Derived From UAV\u2010Based RGB Imaging","volume":"6","author":"Bendig J.","year":"2014","journal-title":"Remote Sensing"},{"key":"e_1_2_11_7_1","doi-asserted-by":"crossref","first-page":"169","DOI":"10.3390\/drones6070169","article-title":"Estimation of Maize Foliar Temperature and Stomatal Conductance as Indicators of Water Stress Based on Optical and Thermal Imagery Acquired Using an Unmanned Aerial Vehicle (UAV) Platform","volume":"6","author":"Brewer K.","year":"2022","journal-title":"Drones"},{"key":"e_1_2_11_8_1","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.jag.2012.10.008","article-title":"Remote Estimation of Crop and Grass Chlorophyll and Nitrogen Content Using Red\u2010Edge Bands on Sentinel\u20102 and\u20103","volume":"23","author":"Clevers J. G.","year":"2013","journal-title":"International Journal of Applied Earth Observation and Geoinformation"},{"key":"e_1_2_11_9_1","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1201\/9780429431180-3","volume-title":"Biophysical and Biochemical Characterization and Plant Species Studies","author":"Cohen Y.","year":"2018"},{"key":"e_1_2_11_10_1","doi-asserted-by":"crossref","first-page":"100318","DOI":"10.1016\/j.rsase.2020.100318","article-title":"UAV\u2010Multispectral and Vegetation Indices in Soybean Grain Yield Prediction Based on In\u00a0Situ Observation","volume":"18","author":"Da Silva E. E.","year":"2020","journal-title":"Remote Sensing Applications: Society and Environment"},{"key":"e_1_2_11_11_1","doi-asserted-by":"crossref","first-page":"147","DOI":"10.3390\/rs13010147","article-title":"Applying RGB\u2010and Thermal\u2010Based Vegetation Indices From UAVs for High\u2010Throughput Field Phenotyping of Drought Tolerance in Forage Grasses","volume":"13","author":"De Swaef T.","year":"2021","journal-title":"Remote Sensing"},{"key":"e_1_2_11_12_1","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1007\/978-3-030-90673-3_4","volume-title":"Wheat Improvement: Food Security in a Changing Climate","author":"Erenstein O.","year":"2022"},{"key":"e_1_2_11_13_1","doi-asserted-by":"crossref","first-page":"3914","DOI":"10.3390\/rs17233914","article-title":"Probing Early and Long\u2010Term Drought Responses in Kauri Using Canopy Hyperspectral Imaging","volume":"17","author":"Felix M. J. 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A.","year":"2002","journal-title":"Remote Sensing of Environment"},{"key":"e_1_2_11_18_1","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.rse.2014.01.004","article-title":"Relationships Between Gross Primary Production, Green LAI, and Canopy Chlorophyll Content in Maize: Implications for Remote Sensing of Primary Production","volume":"144","author":"Gitelson A. A.","year":"2014","journal-title":"Remote Sensing of Environment"},{"key":"e_1_2_11_19_1","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.rse.2003.12.013","article-title":"Hyperspectral Vegetation Indices and Novel Algorithms for Predicting Green LAI of Crop Canopies: Modeling and Validation in the Context of Precision Agriculture","volume":"90","author":"Haboudane D.","year":"2004","journal-title":"Remote Sensing of Environment"},{"key":"e_1_2_11_20_1","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.plantsci.2018.10.022","article-title":"A Rapid Monitoring of NDVI Across the Wheat Growth Cycle for Grain Yield Prediction Using a Multi\u2010Spectral UAV Platform","volume":"282","author":"Hassan M. A.","year":"2019","journal-title":"Plant Science"},{"key":"e_1_2_11_21_1","unstructured":"Khan M. R. M. A.Ullah M. K.Naeem andF.Muqaddas.2026. \u201cUAV\u2010Based Multispectral Imaging Dataset for Quantifying Early Canopy Growth in Wheat.\u201dZenodo. Published August 13.https:\/\/doi.org\/10.5281\/zenodo.21921337."},{"key":"e_1_2_11_22_1","doi-asserted-by":"crossref","first-page":"5264","DOI":"10.1093\/jxb\/erac242","article-title":"High\u2010Throughput UAV\u2010Based Phenotyping Provides Insights Into the Dynamic Process and Genetic Basis of Rapeseed Waterlogging Response in the Field","volume":"73","author":"Li J.","year":"2022","journal-title":"Journal of Experimental Botany"},{"key":"e_1_2_11_23_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2024.3500000","article-title":"Multi\u2010Source Remote Sensing Data\u2010Driven Estimation of Rice Grain Starch Accumulation: Leveraging Matter Accumulation and Translocation Characteristics","author":"Li W.","year":"2024","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"e_1_2_11_24_1","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1071\/FP09121","article-title":"Partitioning of Assimilates to Deeper Roots Is Associated With Cooler Canopies and Increased Yield Under Drought in Wheat","volume":"37","author":"Lopes M. 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