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Unmanned aerial vehicle (UAV) remote sensing technology is a promising approach for monitoring crop biomass. However, the determination of winter wheat AGB based on canopy reflectance is affected by spectral saturation effects. Thus, constructing a generic model for accurately estimating winter wheat AGB using UAV data is significant. In this study, a three-dimensional conceptual model (3DCM) for estimating winter wheat AGB was constructed using plant height (PH) and fractional vegetation cover (FVC). Compared with both the traditional vegetation index model and the traditional multi-feature combination model, the 3DCM yielded the best accuracy for the jointing stage (based on RGB data: coefficient of determination (R2) = 0.82, normalized root mean square error (nRMSE) = 0.2; based on multispectral (MS) data: R2 = 0.84, nRMSE = 0.16), but the accuracy decreased significantly when the spike organ appeared. Therefore, the spike number (SN) was added to create a new three-dimensional conceptual model (n3DCM). Under different growth stages and UAV platforms, the n3DCM (RGB: R2 = 0.73\u20130.85, nRMSE = 0.17\u20130.23; MS: R2 = 0.77\u20130.84, nRMSE = 0.17\u20130.23) remarkably outperformed the traditional multi-feature combination model (RGB: R2 = 0.67\u20130.88, nRMSE = 0.15\u20130.25; MS: R2 = 0.60\u20130.77, nRMSE = 0.19\u20130.26) for the estimation accuracy of the AGB. This study suggests that the n3DCM has great potential in resolving spectral errors and monitoring growth parameters, which could be extended to other crops and regions for AGB estimation and field-based high-throughput phenotyping.<\/jats:p>","DOI":"10.3390\/rs15133332","type":"journal-article","created":{"date-parts":[[2023,6,30]],"date-time":"2023-06-30T01:02:41Z","timestamp":1688086961000},"page":"3332","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["A Three-Dimensional Conceptual Model for Estimating the Above-Ground Biomass of Winter Wheat Using Digital and Multispectral Unmanned Aerial Vehicle Images at Various Growth Stages"],"prefix":"10.3390","volume":"15","author":[{"given":"Yongji","family":"Zhu","sequence":"first","affiliation":[{"name":"College of Resources and Environment, Anhui Science and Technology University, Chuzhou 233100, China"}]},{"given":"Jikai","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, Anhui Science and Technology University, Chuzhou 233100, China"}]},{"given":"Xinyu","family":"Tao","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, Anhui Science and Technology University, Chuzhou 233100, China"}]},{"given":"Xiangxiang","family":"Su","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, Anhui Science and Technology University, Chuzhou 233100, China"}]},{"given":"Wenyang","family":"Li","sequence":"additional","affiliation":[{"name":"College of Agriculture, Anhui Science and Technology University, Chuzhou 233100, China"}]},{"given":"Hainie","family":"Zha","sequence":"additional","affiliation":[{"name":"School of Computer and Information, Anqing Normal University, Anqing 246133, China"},{"name":"Anhui Yigang Information Technology Co., Ltd., Anqing 246003, China"}]},{"given":"Wenge","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, Anhui Science and Technology University, Chuzhou 233100, China"},{"name":"Rice Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230001, China"}]},{"given":"Xinwei","family":"Li","sequence":"additional","affiliation":[{"name":"College of Resources and Environment, Anhui Science and Technology University, Chuzhou 233100, China"},{"name":"Agricultural Waste Fertilizer Utilization and Cultivated Land Quality Improvement Engineering Research Center, Chuzhou 233100, China"},{"name":"Anhui Engineering Research Center of Smart Crop Planting and Processing Technology, Chuzhou 233100, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2022.02.016","article-title":"The effects of Landsat image acquisition date on winter wheat classification in the North China Plain","volume":"187","author":"Fan","year":"2022","journal-title":"ISPRS-J. 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