Soil Mapping Using Electromagnetic Induction to Assess the Suitability of Land for Growing Leptospermum nitens in Western Australia

Abstract

Leptospermum sp. with dihydroxyacetone in their nectar are a source of high-value medicinal honey production and can provide income from agriculturally marginal lands. The current study was from two newly planted Leptospermum nitens sites, one with duplex soil and the other in deep sandy soil, in the low rainfall areas of the south-west of Western Australia, with the aim of identifying key soil parameters influencing the plantation’s survival and growth. Electromagnetic induction (EMI) at different depths was used to investigate the possible impact of soil variability on the Leptospermum nitens plantations. Two EMI surveys were conducted at each site, at different times of the year, to account for soil moisture variability (relatively dry and wet conditions). A least-square inversion algorithm was used to determine true electrical conductivities at three different soil depths (0–0.5, 0.5–0.8, and 0.8–1.6 m) to produce quasi-3D maps of soil inverted electrical conductivity. Corresponding soil samples from each depth were used for the physico-chemical analysis of soil parameters and to develop laboratory-based electrical resistivity to soil volumetric moisture calibrations with R2 values between 0.95 and 0.99. Shrub survival and growth (canopy diameter) were estimated using unmanned aerial vehicle (UAV) images and machine learning. Comparing EMI soil mapping with UAV imagery results showed significantly greater shrub survival and growth (p < 0.001) in areas with higher ECa ranges of 12–24 mS m−1 at the variable textured site and 6–9 mS m−1 at the uniformly sandy site. Overall, the variable textured site, with an 82% survival rate, had a significantly higher shrub count and larger plants than the uniformly sandy site, with a 75% survival rate. A principal component analysis (PCA) identified inverted EC to be strongly correlated with soil moisture > pH > soil texture. Such soil mapping may be a robust and effective method for risk assessment of new shrub plantations.