Comment on "MALDI-MS Imaging Analysis of Fungicide Residue Distributions on Wheat Leaf Surfaces"

Assessing Pesticide Residue and Spray Deposition in Greenhouse Eggplant Canopies to Improve Residue Analysis

Pesticide residue analysis is critically important for ensuring food safety and regulating international trade. In a greenhouse setting, we assessed pesticide residue and exposure patterns using liquid chromatography-mass spectrometry and Allura Red tracer analysis. Our results show significant effects of eggplant canopy position and spray concentration on deposition parameters. Specifically, spray coverage, spray density, deposition, and residue were generally greater for leaves in the higher canopy. Deposition and residue, unlike spray coverage and spray density, linearly correlated with spray concentration. Pesticide residues on leaves linearly correlated with depositions on artificial targets, and a correction factor was constructed to estimate residues from tracer depositions. This comparative analysis suggests that tracer analysis using Allura Red in combination with artificial targets is a time- and cost-saving alternative to conventional residue analysis for assessing spray parameters under high-volume spraying scenarios. A better understanding of pesticide residue and spray patterns will not only enhance the safety of our food supply chain but also improve pest control efficacy within the sustainable integrated pest management framework.

Quantifying pesticide deposits and spray patterns at micro-scales on apple (Malus domesticus) leaves with a view to arthropod exposure

BACKGROUND

Pesticides used in commercial crop systems can adversely affect non-target arthropod populations. The spatial distribution of pesticide residues is rarely studied at scales relevant to these populations. Here, we combine two methods for assessing pesticide spray deposits at spatial scales relevant to non-target arthropods found in apple orchards. Pesticide residues were determined on individual apple leaves through conventional residue analysis; water-sensitive paper was used to investigate spatial distributions in deposits at the micro-scale. We also evaluated how accurately a digital image analysis program estimated pesticide residues.

RESULTS

We found that mean pesticide spray coverage on water-sensitive paper varied by up to 6.1% (95% CI 9.4%, 2.7%) within an apple orchard, and leaf residues varied by up to 0.95 (95% CI 0.54, 1.36) mg kg^-1 within a tree. Leaf residues based on analytical chemistry were six times lower than pesticide deposition estimated through image analysis of water-sensitive paper, although these correlated strongly. This correlation allowed estimation of actual residues by application of a correction factor.

CONCLUSION

Our method demonstrates accurate estimation of pesticide deposits at the individual leaf scale through digital analysis of water-sensitive paper and is a low-cost, rapid alternative to conventional residue analysis techniques. © 2018 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.