Skip to main content
ARS Home » Midwest Area » Wooster, Ohio » Application Technology Research » Research » Publications at this Location » Publication #364203

Research Project: Improved Pest Control Application Technologies for Sustainable Crop Protection

Location: Application Technology Research

Title: 3D optical surface profiler for quantifying leaf surface roughness

Author
item Abbott, John Paul
item Zhu, Heping

Submitted to: Surface Topography: Metrology and Properties
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/27/2019
Publication Date: 10/18/2019
Citation: Abbott, J.R., Zhu, H. 2019. 3D optical surface profiler for quantifying leaf surface roughness. Surface Topography: Metrology and Properties. 7(4):045016. https://doi.org/10.1088/2051-672X/ab4cc6.
DOI: https://doi.org/10.1088/2051-672X/ab4cc6

Interpretive Summary: Pesticide spray application efficiency is significantly affected by leaf wettability which depends, in part, on the roughness of leaf fine scale surfaces. Accurate quantification of leaf surface roughness can lead to creating scientific guidelines for choosing optimal spray parameters to increase spray droplet retention and minimize off-target loss. However, there are few known reliable technologies that can achieve this direct quantification. In this research, a 3-dimentional optical surface profiler was investigated as a new method to measure leaf surface roughness at micro- and nanometer scales. Topography parameters including roughness height and skewness were identified as quantifiable metrics relating to roughness and leaf wettability. The measurement accuracy was validated by comparing the micrometer and sub-micrometer scaled roughness of seven leaf types with multi-scale structure and smooth surfaces. Test results demonstrated that the optical profiler was an effective and fast instrument for accurately measuring and quantifying leaf roughness, especially as relating to wettability. Biologists and engineers could use these metrics to better model leaf wettability and to develop more effective spray application strategies to reduce pesticide waste, cost and environmental impact.

Technical Abstract: 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, but different orders of magnitude for sub-micrometer scale roughness, approximately 0.1 and 0.001, 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.