Prediction of root biomass in cassava based on ground penetrating radar phenomics

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dc.creatorAgbona, A.
dc.creatorTeare, B.
dc.creatorRuíz Guzman, H.
dc.creatorDobreva, I.D.
dc.creatorEverett, M.E.
dc.creatorAdams,T.
dc.creatorMontesinos López, Osval A.
dc.creatorKulakow, Peter A.
dc.creatorHays, D.B.
dc.date2021-12-03
dc.date2022-06-17T10:11:43Z
dc.date2022-06-17T10:11:43Z
dc.date.accessioned2026-06-27T15:59:01Z
dc.descriptionCassava as a world food security crop still suffers from an inadequate means to measure early storage root bulking (ESRB), a trait that describes early maturity and a key characteristic of improved cassava varieties. The objective of this study is to evaluate the capability of ground penetrating radar (GPR) for non-destructive assessment of cassava root biomass. GPR was evaluated for this purpose in a field trial conducted in Ibadan, Nigeria. Different methods of processing the GPR radargram were tested, which included time slicing the radargram below the antenna surface in order to reduce ground clutter; to remove coherent sub-horizontal reflected energy; and having the diffracted energy tail collapsed into representative point of origin. GPR features were then extracted using Discrete Fourier Transformation (DFT), and Bayesian Ridge Regression (BRR) models were developed considering one, two and three-way interactions. Prediction accuracies based on Pearson correlation coefficient (r) and coefficient of determination (R2) were estimated by the linear regression of the predicted and observed root biomass. A simple model without interaction produced the best prediction accuracy of r = 0.64 and R2 = 0.41. Our results demonstrate that root biomass can be predicted using GPR and it is expected that the technology will be adopted by cassava breeding programs for selecting early stage root bulking during the crop growth season as a novel method to dramatically increase crop yield
dc.formatapplication/pdf
dc.identifierhttps://hdl.handle.net/10568/119869
dc.identifier.urihttp://hdl.handle.net/123456789/119213
dc.languageen
dc.publisherMDPI
dc.rightsOpen Access
dc.sourceAgbona, A., Teare, B., Ruiz-Guzman, H., Dobreva, I.D., Everett, M.E., Adams, T., ... & Hays, D.B. (2021). Prediction of Root Biomass in Cassava Based on Ground Penetrating Radar Phenomics. In Remote Sensing, 13(23): 4908, 1-18.
dc.subjectradar
dc.subjectcassava
dc.subjectbranching
dc.subjectspectrum
dc.subjectroots
dc.subjectbiomass
dc.titlePrediction of root biomass in cassava based on ground penetrating radar phenomics
dc.typeJournal Article

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Instituto Internacional de Agricultura Tropical (IITA)