Thresholding and continuous wavelet transform (CWT) analysis of Ground Penetrating Radar (GPR) data for estimation of potato biomass

Potato (Solanum tuberosum) is widely recognized as the leading vegetable crop in the United States, with millions of tons produced annually. Despite many advancements in cultivars, crop production still suffers from meager progress in the assessment of early maturity. One potential solution to this problem is Ground-Penetrating Radar (GPR), a near-surface geophysical tool that has recently been applied to agriculture for assessment of root systems by detecting dielectric variations in sub-surface and soil layers by means of electromagnetic waves emitted into the ground. This study seeks to assess GPR’s capability to serve as a non-destructive proximal-sensing technique for quantifying potato tuber biomass by estimating the size of potatoes by measuring changes in the reflected GPR signal. Two methods, thresholding analysis and continuous wavelet transform (CWT), were employed in this study to extract features from GPR responses to predict tuber biomass. The dataset was collected in a controlled sandbox system. Thresholding analysis on the interpolated amplitude values yielded significant results, being able to predict tuber biomass with an accuracy of r = 0.82 and R2 = 0.64 based upon Multiple Linear regression. CWT was somewhat less successful, yet still significant, with a prediction accuracy of r = 0.6 and R2 = 0.32. These results indicate that GPR technology is suitable as a decision-support tool for potato breeders seeking to monitor tuber growth.