{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T17:13:16Z","timestamp":1784221996781,"version":"3.55.0"},"reference-count":26,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2017,12,1]],"date-time":"2017-12-01T00:00:00Z","timestamp":1512086400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The uniformity of wheat seed emergence is an important characteristic used to evaluate cultivars, cultivation mode and field management. Currently, researchers typically investigated the uniformity of seed emergence by manual measurement, a time-consuming and laborious process. This study employed field RGB images from unmanned aerial vehicles (UAVs) to obtain information related to the uniformity of wheat seed emergence and missing seedlings. The calculation of the length of areas with missing seedlings in both drill and broadcast sowing can be achieved by using an area localization algorithm, which facilitated the comprehensive evaluation of uniformity of seed emergence. Through a comparison between UAV images and the results of manual surveys used to gather data on the uniformity of seed emergence, the root-mean-square error (RMSE) was 0.44 for broadcast sowing and 0.64 for drill sowing. The RMSEs of the numbers of missing seedling regions for broadcast and drill sowing were 1.39 and 3.99, respectively. The RMSEs of the lengths of the missing seedling regions were 12.39 cm for drill sowing and 0.20 cm2 for broadcast sowing. The UAV image-based method provided a new and greatly improved method for efficiently measuring the uniformity of wheat seed emergence. The proposed method could provide a guideline for the intelligent evaluation of the uniformity of wheat seed emergence.<\/jats:p>","DOI":"10.3390\/rs9121241","type":"journal-article","created":{"date-parts":[[2017,12,1]],"date-time":"2017-12-01T12:30:16Z","timestamp":1512131416000},"page":"1241","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["Evaluation of Seed Emergence Uniformity of Mechanically Sown Wheat with UAV RGB Imagery"],"prefix":"10.3390","volume":"9","author":[{"given":"Tao","family":"Liu","sequence":"first","affiliation":[{"name":"Jiangsu Key Laboratory of Crop Genetics and Physiology\/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Li","sequence":"additional","affiliation":[{"name":"Jiangsu Key Laboratory of Crop Genetics and Physiology\/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6769-214X","authenticated-orcid":false,"given":"Xiuliang","family":"Jin","sequence":"additional","affiliation":[{"name":"INRA-EMMAH, UMT-CAPTE, 84914 Avignon, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinfeng","family":"Ding","sequence":"additional","affiliation":[{"name":"Jiangsu Key Laboratory of Crop Genetics and Physiology\/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinkai","family":"Zhu","sequence":"additional","affiliation":[{"name":"Jiangsu Key Laboratory of Crop Genetics and Physiology\/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengming","family":"Sun","sequence":"additional","affiliation":[{"name":"Jiangsu Key Laboratory of Crop Genetics and Physiology\/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenshan","family":"Guo","sequence":"additional","affiliation":[{"name":"Jiangsu Key Laboratory of Crop Genetics and Physiology\/Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,12,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.isprsjprs.2017.02.001","article-title":"Winter wheat yield estimation based on multi-source medium resolution optical and radar imaging data and the AquaCrop model using the particle swarm optimization algorithm","volume":"126","author":"Jin","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_2","first-page":"149","article-title":"Effects of different seeding manner on the seedling emergence, over-winter and yield of wheat under maize stalk full returned to the field","volume":"26","author":"Jia","year":"2010","journal-title":"Chin. Agric. Sci. Bull."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"582","DOI":"10.2134\/agronj1998.00021962009000050002x","article-title":"Winter wheat seedling emergence from deep sowing depths","volume":"90","author":"Schillinger","year":"1998","journal-title":"AGRON J."},{"key":"ref_4","first-page":"761","article-title":"Modeling the emergence of winter wheat in response to soil temperature, water potential, and planting depth","volume":"57","author":"Huggins","year":"2014","journal-title":"Trans. ASABE"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"137","DOI":"10.2134\/agronj1976.00021962006800010038x","article-title":"A model to predict winter wheat emergence as affected by soil temperature, water potential, and depth of planting","volume":"68","author":"Lindstrom","year":"1976","journal-title":"Agron. J."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1016\/j.compag.2015.09.001","article-title":"Field-based crop phenotyping: Multispectral aerial imaging for evaluation of winter wheat emergence and spring stand","volume":"118","author":"Sankaran","year":"2015","journal-title":"Comput. Electron. Agric."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.biosystemseng.2015.12.003","article-title":"Detection of tomatoes using spectral-spatial methods in remotely sensed RGB images captured by UAV","volume":"146","author":"Senthilnath","year":"2016","journal-title":"Biosyst. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.biosystemseng.2015.01.008","article-title":"Multi-temporal imaging using an unmanned aerial vehicle for monitoring a sunflower crop","volume":"132","author":"Vega","year":"2015","journal-title":"Biosyst. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1007\/s11119-012-9257-6","article-title":"A flexible unmanned aerial vehicle for precision agriculture","volume":"13","author":"Primicerio","year":"2012","journal-title":"Precis. Agric."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.biosystemseng.2016.04.010","article-title":"Field phenotyping system for the assessment of potato late blight resistance using RGB imagery from an unmanned aerial vehicle","volume":"148","author":"Sugiura","year":"2016","journal-title":"Biosyst. Eng."},{"key":"ref_11","first-page":"109","article-title":"Rapid crops classification based on UAV low-altitude remote sensing","volume":"29","author":"Tian","year":"2013","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1007\/s11119-016-9468-3","article-title":"Assessing the potential of images from unmanned aerial vehicles (UAV) to support herbicide patch spraying in maize","volume":"18","author":"Castaldi","year":"2016","journal-title":"Precis. Agric."},{"key":"ref_13","first-page":"207","article-title":"Area extraction of maize lodging based on remote sensing by small unmanned aerial vehicle","volume":"30","author":"Li","year":"2014","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.rse.2017.06.007","article-title":"Estimates of plant density of wheat crops at emergence from very low altitude UAV imagery","volume":"198","author":"Jin","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.biosystemseng.2013.02.002","article-title":"Estimation of leaf area index in onion (Allium cepa L.) using an unmanned aerial vehicle","volume":"115","author":"Ortega","year":"2013","journal-title":"Biosyst. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2164","DOI":"10.3390\/rs5052164","article-title":"Visualizing and quantifying vineyard canopy LAI using an unmanned aerial vehicle (UAV) collected high density structure from motion point cloud","volume":"5","author":"Mathews","year":"2013","journal-title":"Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/j.compag.2008.03.009","article-title":"Verification of color vegetation indices for automated crop imaging applications","volume":"63","author":"Meyer","year":"2008","journal-title":"Comput. Electron. Agric."},{"key":"ref_18","first-page":"819","article-title":"Study of measurement method of population uniformity of wheat based on digital image","volume":"28","author":"Shan","year":"2008","journal-title":"J. Triticeae Crops"},{"key":"ref_19","first-page":"551","article-title":"Effects of drip irrigation circuit design and lateral line lengths: I\u2014On pressure and friction loss","volume":"3","author":"Tayel","year":"2012","journal-title":"Agric. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"211","DOI":"10.2134\/agronj1985.00021962007700020009x","article-title":"Row Spacing and Seeding Rate Effects on Yield and Yield Components of Soft Red Winter Wheat","volume":"77","author":"Joseph","year":"1985","journal-title":"Agron. J."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Zamanallah, M., Vergara, O., Araus, J.L., Tarekegne, A., Magorokosho, C., Zarcotejada, P.J., Hornero, A., Alb\u00e0, A.H., Das, B., and Craufurd, P. (2015). Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize. Plant Methods, 11.","DOI":"10.1186\/s13007-015-0078-2"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1016\/j.rse.2014.06.006","article-title":"Green area index from an unmanned aerial system over wheat and rapeseed crops","volume":"152","author":"Verger","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_23","first-page":"79","article-title":"Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley","volume":"39","author":"Bendig","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"4213","DOI":"10.3390\/rs70404213","article-title":"High-Resolution Airborne UAV Imagery to Assess Olive Tree Crown Parameters Using 3D Photo Reconstruction: Application in Breeding Trials","volume":"7","author":"Rosa","year":"2015","journal-title":"Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1007\/s11119-005-2324-5","article-title":"Evaluation of Digital Photography from Model Aircraft for Remote Sensing of Crop Biomass and Nitrogen Status","volume":"6","author":"Hunt","year":"2005","journal-title":"Precis. Agric."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.agrformet.2012.12.013","article-title":"Estimating leaf carotenoid content in vineyards using high resolution hyperspectral imagery acquired from an unmanned aerial vehicle (UAV)","volume":"171\u2013172","author":"Zarcotejada","year":"2013","journal-title":"Agric. For. Meteorol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/12\/1241\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:52:12Z","timestamp":1760208732000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/12\/1241"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,12,1]]},"references-count":26,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2017,12]]}},"alternative-id":["rs9121241"],"URL":"https:\/\/doi.org\/10.3390\/rs9121241","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,12,1]]}}}