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

cg.authorship.typesCGIAR and developing country instituteen
cg.contributor.affiliationTexas A&M Universityen
cg.contributor.affiliationOhio State Universityen
cg.contributor.affiliationUniversidad de Colimaen
cg.contributor.affiliationInternational Institute of Tropical Agricultureen
cg.contributor.crpRoots, Tubers and Bananas
cg.contributor.donorNational Science Foundation-Basic Research to Enable Agricultural Developmenten
cg.coverage.countryNigeria
cg.coverage.iso3166-alpha2NG
cg.coverage.regionAfrica
cg.coverage.regionWestern Africa
cg.creator.identifierPeter Kulakow: 0000-0002-7574-2645en
cg.identifier.doihttps://doi.org/10.3390/rs13234908en
cg.identifier.iitathemeBIOTECH & PLANT BREEDINGen
cg.isijournalISI Journalen
cg.issn2072-4292en
cg.issue23: 4908en
cg.journalRemote Sensingen
cg.reviewStatusPeer Reviewen
cg.subject.iitaBIOSCIENCEen
cg.subject.iitaCASSAVAen
cg.subject.iitaFOOD SECURITYen
cg.subject.impactAreaNutrition, health and food security
cg.volume13en
dc.contributor.authorAgbona, A.en
dc.contributor.authorTeare, B.en
dc.contributor.authorRuíz Guzman, H.en
dc.contributor.authorDobreva, I.D.en
dc.contributor.authorEverett, M.E.en
dc.contributor.authorAdams,T.en
dc.contributor.authorMontesinos López, Osval A.en
dc.contributor.authorKulakow, Peter A.en
dc.contributor.authorHays, D.B.en
dc.date.accessioned2022-06-17T10:11:43Zen
dc.date.available2022-06-17T10:11:43Zen
dc.identifier.urihttps://hdl.handle.net/10568/119869
dc.titlePrediction of root biomass in cassava based on ground penetrating radar phenomicsen
dcterms.abstractCassava 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 yielden
dcterms.accessRightsOpen Access
dcterms.audienceScientistsen
dcterms.available2021-12-03en
dcterms.bibliographicCitationAgbona, 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.en
dcterms.extent1-18en
dcterms.issued2021-12-03en
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherMDPIen
dcterms.subjectradaren
dcterms.subjectcassavaen
dcterms.subjectbranchingen
dcterms.subjectspectrumen
dcterms.subjectrootsen
dcterms.subjectbiomassen
dcterms.typeJournal Article

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