UAV-based NDVI estimation of sugarbeet yield and quality under varied nitrogen and water rates

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dc.contributor.authorWalsh, Olga S.en
dc.contributor.authorNambi, Evaen
dc.contributor.authorShafian, Sanazen
dc.contributor.authorJayawardena, Dileepa M. M.en
dc.contributor.authorAnsah, Emmanuella Owusuen
dc.contributor.authorLamichhane, Ritikaen
dc.contributor.authorMcClintick-Chess, Jordan R. R.en
dc.date.accessioned2023-03-22T19:00:38Zen
dc.date.available2023-03-22T19:00:38Zen
dc.date.issued2023-03en
dc.description.abstractThe accuracy of the traditional soil and plant-based techniques for assessing sugarbeet demand for nitrogen (N) and yield prediction is generally low. Refining N and irrigation water management is a key to maximizing return for sugarbeet (Beta vulgaris L.) growers from agronomic, economic, and environmental perspective. The use of Normalized Difference Vegetative Index (NDVI) in combination with the unmanned aerial vehicle (UAV)-based data collection for in-season estimation of sugarbeet root yield and sugar concentration has potential for precision N management. Sugarbeet field trials were conducted in Idaho in 2019 and 2020 to assess (1) effects of water and N fertilizer rates on yield and estimated recoverable sugar (ERS) and (2) feasibility of predicting root yield and ERS using UAV NDVI. At the lowest N rate, application of water at 100% level resulted in greater yield, compared to 50%, in both years. At higher N rates, 50% level produced higher yields. At each N level, application of water at 100% level resulted in lower ERS, compared to 50%. The UAV NDVI was strongly correlated with root yield and ERS. The relationship between UAV NDVI and root yield and ERS was stronger in July (60 days after planting) compared to June (40 days after planting). Estimating the yield and ERS potential in late June/early July and topdressing the crop before the end of July may help to improve N use efficiency while optimizing sugarbeet production.en
dc.description.notesSnake River Sugarbeet Research and Seed Allianceen
dc.description.sponsorshipSnake River Sugarbeet Research and Seed Allianceen
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1002/agg2.20337en
dc.identifier.eissn2639-6696en
dc.identifier.issue1en
dc.identifier.othere20337en
dc.identifier.urihttp://hdl.handle.net/10919/114147en
dc.identifier.volume6en
dc.language.isoenen
dc.publisherWileyen
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectBeta-vulgaris l.en
dc.subjectDrip irrigationen
dc.subjectroot yielden
dc.subjectsoilen
dc.subjectfertilizeren
dc.subjectperformanceen
dc.subjectpredictionen
dc.subjectmanagementen
dc.subjectbiomassen
dc.subjectpotatoen
dc.titleUAV-based NDVI estimation of sugarbeet yield and quality under varied nitrogen and water ratesen
dc.title.serialAgrosystems Geosciences & Environmenten
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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