Prediction of Root Biomass in Cassava Based on Ground Penetrating Radar Phenomics

Abstract

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 (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.

Estimation of starch content in cassava based on coefficient of reflection measurement

“…Furthermore, the starch measurement device is expected to deliver a major impact in cassava HTP studies. Coupling the nondestructive starch estimation method in this report with nondestructive ground-penetrating radar (GPR), currently being tested to monitor biomass of root crops such as cassava during the crop growing season (Agbona et al, 2021) will be a game-changer in terms of predicting dry-root yield at scale.…”

Geophysical methods reveal the soil architecture and subsurface stratigraphic heterogeneities across land-lake interfaces along Lake Erie

“…SM is known to cause signal attenuation in GPR data (e.g. Huisman et al 2003;Klotzsche et al 2018;Agbona et al 2021). This signal attenuation due to water saturation is expected to be more pronounced in wetlands with high water residence time and could also lead to temporal variations in GPR measurement due to seasonal variation in SM in such wetlands.…”

Climate change challenges, plant science solutions

“…Earlier stage, nondestructive evaluation of physiological drought responses and root bulking is needed. Remote sensing of photosynthetic performance using drones with hyperspectral imaging ( Verma et al, 1993 ; Banerjee et al, 2020 ) and root yield using ground penetrating radar is now possible ( Agbona et al, 2021 ). High-throughput phenotyping plus genomic prediction and GWAS-based discovery are powerful tools for climate-resilience breeding ( Juliana et al, 2019 ; Jha et al, 2020 ).…”