3D optical surface profiler for quantifying leaf surface roughness

Biological efficiency of pesticide droplets is affected by leaf surface fine structures; however, few reliable methods exist to physically measure and quantify surface roughness. A 3D optical surface profiler was evaluated for its effectiveness as a novel and reliable method to measure and quantify leaf surface roughness in terms of areal roughness parameters. Evaluations included its accuracy for measuring 3D roughness parameters relating mean roughness length, Sa, skewness, Ssk, and kurtosis, Sku. Their values were compared with the wettability of seven leaf types ranging from easy-to-wet to very difficult-to-wet. Measurement accuracy was validated by a qualitative visual analysis comparing 3D surface renderings of measured leaf surfaces generated by the profiler and micrographs taken with a scanning electron microscope (SEM). The accuracy was also validated by measuring and comparing the micrometer and sub-micrometer scaled roughness on leaf types with hierarchical (multi-scale) structuring and smooth surfaces. Both the renderings and the SEM showed visual agreement in surface variations from waxes and trichomes. The measured roughness lengths for the multi-scale and smooth surfaces were on the same order of magnitude for micrometer scale roughness, approximately 1×100 μm, but different orders of magnitude for sub-micrometer scale roughness, approximately 1×10−1 μm and 1×10−3 μm, respectively. Comparisons for Ssk and Sku to wettability were inconclusive, however, comparisons between Sa and wettability showed a positive linear fit, suggesting that Sa could be a viable metric for relating leaf surface roughness to wettability. The results from the micrometer and sub-micrometer scale surface roughness quantification could be used to improve pesticide spray deposition quality, leading to reductions in pesticide use and negative environmental impact.