Prediction of Root Biomass in Cassava Based on Ground Penetrating Radar Phenomics
Cassava 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 rad...
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MDPI AG
2021-12-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/23/4908 |
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| author | Afolabi Agbona Brody Teare Henry Ruiz-Guzman Iliyana D. Dobreva Mark E. Everett Tyler Adams Osval A. Montesinos-Lopez Peter A. Kulakow Dirk B. Hays |
| author_facet | Afolabi Agbona Brody Teare Henry Ruiz-Guzman Iliyana D. Dobreva Mark E. Everett Tyler Adams Osval A. Montesinos-Lopez Peter A. Kulakow Dirk B. Hays |
| author_sort | Afolabi Agbona |
| collection | DOAJ |
| description | Cassava 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 (R<sup>2</sup>) 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 R<sup>2</sup> = 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. |
| first_indexed | 2024-03-10T04:46:58Z |
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| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T04:46:58Z |
| publishDate | 2021-12-01 |
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| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-f4dbec436fb94f5b9e3857b5329fc3fd2023-11-23T02:58:12ZengMDPI AGRemote Sensing2072-42922021-12-011323490810.3390/rs13234908Prediction of Root Biomass in Cassava Based on Ground Penetrating Radar PhenomicsAfolabi Agbona0Brody Teare1Henry Ruiz-Guzman2Iliyana D. Dobreva3Mark E. Everett4Tyler Adams5Osval A. Montesinos-Lopez6Peter A. Kulakow7Dirk B. Hays8Molecular & Environmental Plant Sciences, Texas A&M University, College Station, TX 77843, USAMolecular & Environmental Plant Sciences, Texas A&M University, College Station, TX 77843, USADepartment of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843, USADepartment of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843, USADepartment of Geology & Geophysics, Texas A&M University, College Station, TX 77843, USAMolecular & Environmental Plant Sciences, Texas A&M University, College Station, TX 77843, USAFacultad de Telemática, Universidad de Colima, Colima 28040, MexicoInternational Institute of Tropical Agriculture, Old Oyo Road, Ibadan 20002, NigeriaMolecular & Environmental Plant Sciences, Texas A&M University, College Station, TX 77843, USACassava 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 (R<sup>2</sup>) 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 R<sup>2</sup> = 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.https://www.mdpi.com/2072-4292/13/23/4908ground penetrating radarcassavabranchingpower spectrumroot biomassradargram |
| spellingShingle | Afolabi Agbona Brody Teare Henry Ruiz-Guzman Iliyana D. Dobreva Mark E. Everett Tyler Adams Osval A. Montesinos-Lopez Peter A. Kulakow Dirk B. Hays Prediction of Root Biomass in Cassava Based on Ground Penetrating Radar Phenomics Remote Sensing ground penetrating radar cassava branching power spectrum root biomass radargram |
| title | Prediction of Root Biomass in Cassava Based on Ground Penetrating Radar Phenomics |
| title_full | Prediction of Root Biomass in Cassava Based on Ground Penetrating Radar Phenomics |
| title_fullStr | Prediction of Root Biomass in Cassava Based on Ground Penetrating Radar Phenomics |
| title_full_unstemmed | Prediction of Root Biomass in Cassava Based on Ground Penetrating Radar Phenomics |
| title_short | Prediction of Root Biomass in Cassava Based on Ground Penetrating Radar Phenomics |
| title_sort | prediction of root biomass in cassava based on ground penetrating radar phenomics |
| topic | ground penetrating radar cassava branching power spectrum root biomass radargram |
| url | https://www.mdpi.com/2072-4292/13/23/4908 |
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