{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T21:36:37Z","timestamp":1773437797607,"version":"3.50.1"},"reference-count":74,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T00:00:00Z","timestamp":1733443200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Key Program of Inner Mongolia","award":["2021ZD0002"],"award-info":[{"award-number":["2021ZD0002"]}]},{"name":"Science and Technology Key Program of Inner Mongolia","award":["CARS-07-B-5"],"award-info":[{"award-number":["CARS-07-B-5"]}]},{"name":"Science and Technology Key Program of Inner Mongolia","award":["CARS-07-A-6"],"award-info":[{"award-number":["CARS-07-A-6"]}]},{"name":"China Agriculture Research System","award":["2021ZD0002"],"award-info":[{"award-number":["2021ZD0002"]}]},{"name":"China Agriculture Research System","award":["CARS-07-B-5"],"award-info":[{"award-number":["CARS-07-B-5"]}]},{"name":"China Agriculture Research System","award":["CARS-07-A-6"],"award-info":[{"award-number":["CARS-07-A-6"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate crop yield prediction is crucial for optimizing cultivation practices and informing breeding decisions. Integrating UAV-acquired multispectral datasets with advanced machine learning methodologies has markedly refined the accuracy of crop yield forecasting. This study aimed to construct a robust and versatile yield prediction model for multi-genotyped oat varieties by investigating 14 modeling scenarios that combine multispectral data from four key growth stages. An ensemble learning framework, StackReg, was constructed by stacking four base algorithms\u2014ridge regression (RR), support vector machines (SVM), Cubist, and extreme gradient boosting (XGBoost)\u2014to predict oat yield. The results show that, for single growth stages, base models achieved R2 values within the interval of 0.02 to 0.60 and RMSEs ranging from 391.50 to 620.49 kg\/ha. By comparison, the StackReg improved performance, with R2 values extending from 0.25 to 0.61 and RMSEs narrowing to 385.33 and 542.02 kg\/ha. In dual-stage and multi-stage settings, the StackReg consistently surpassed the base models, reaching R2 values of up to 0.65 and RMSE values as low as 371.77 kg\/ha. These findings underscored the potential of combining UAV-derived multispectral imagery with ensemble learning for high-throughput phenotyping and yield forecasting, advancing precision agriculture in oat cultivation.<\/jats:p>","DOI":"10.3390\/rs16234575","type":"journal-article","created":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T03:44:47Z","timestamp":1733456687000},"page":"4575","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Ensemble Learning for Oat Yield Prediction Using Multi-Growth Stage UAV Images"],"prefix":"10.3390","volume":"16","author":[{"given":"Pengpeng","family":"Zhang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Maize Bio-Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China"},{"name":"Key Laboratory of Farming System, Ministry of Agriculture and Rural Affairs of China, China Agricultural University, Beijing 100193, China"},{"name":"Department of Geography, Simon Fraser University, Burnaby, BC V5A 1S6, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6259-1841","authenticated-orcid":false,"given":"Bing","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Geography, Simon Fraser University, Burnaby, BC V5A 1S6, Canada"}]},{"given":"Jiali","family":"Shang","sequence":"additional","affiliation":[{"name":"Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada"}]},{"given":"Xingyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Zhangjiakou Academy of Agricultural Sciences, Zhangjiakou 075000, China"}]},{"given":"Zhenwei","family":"Hou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Maize Bio-Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China"},{"name":"Key Laboratory of Farming System, Ministry of Agriculture and Rural Affairs of China, China Agricultural University, Beijing 100193, China"}]},{"given":"Shujian","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA"}]},{"given":"Yadong","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Maize Bio-Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China"},{"name":"Key Laboratory of Farming System, Ministry of Agriculture and Rural Affairs of China, China Agricultural University, Beijing 100193, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2008-143X","authenticated-orcid":false,"given":"Huadong","family":"Zang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Maize Bio-Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China"},{"name":"Key Laboratory of Farming System, Ministry of Agriculture and Rural Affairs of China, China Agricultural University, Beijing 100193, China"}]},{"given":"Junyong","family":"Ge","sequence":"additional","affiliation":[{"name":"Zhangjiakou Academy of Agricultural Sciences, Zhangjiakou 075000, China"},{"name":"Department of Plant, Food and Environmental Sciences, Agricultural Campus, Dalhousie University, P.O. Box 550, Truro, NS B2N 5E3, Canada"}]},{"given":"Zhaohai","family":"Zeng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Maize Bio-Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China"},{"name":"Key Laboratory of Farming System, Ministry of Agriculture and Rural Affairs of China, China Agricultural University, Beijing 100193, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1007\/s00394-008-0698-7","article-title":"Oat: Unique among the cereals","volume":"47","author":"Butt","year":"2008","journal-title":"Eur. J. Nutr."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Rispail, N., Montilla-Basc\u00f3n, G., S\u00e1nchez-Mart\u00edn, J., Flores, F., Howarth, C., Langdon, T., Rubiales, D., and Prats, E. (2018). 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