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Apis mellifera L. (Hymenoptera: Apidae) is fundamental in the production chain, ensuring food diversity through the ecosystem service of pollination. The aim of this work was to evaluate the impact of imidacloprid, orally, topically, and by contact, on A. mellifera workers and to verify the presence of this active ingredient in honey. Toxicity levels were verified by bioassays. In bioassay 1, the levels correspond to the percentages of 100, 10, 1, 0.1, and 0.01% of the recommended concentration for field application of the commercial product Nortox® (active ingredient imidacloprid), with which we obtained the mean lethal concentration (LC 50 ) in 48 h for A. mellifera, determining the concentration ranges to be used in the subsequent bioassays. Bioassays 2 and 3 followed the guidelines of the Organization for Economic Cooperation and Development, which specify the LC 50 (48 h). In bioassay 4, the LC 50 (48 h) and the survival rate of bees for a period of 120 h were determined by contact with a surface contaminated with imidacloprid, and in bioassay 5, the interference of the insecticide with the flight behavior of bees was evaluated. Honey samples were collected in agroecological and conventional georeferenced apiaries and traces of the imidacloprid were detected by means of high-performance liquid chromatography (HPLC-UV) with extraction by SPE C18. Bee survival was directly affected by the concentration and exposure time, as well behavioral performance, demonstrating the residual effect of imidacloprid on A. mellifera workers. Honey samples from a conventional apiary showed detection above the maximum residue limits (MRL) allowed by the European Union (0.05 μg mL -1 ), but samples from other apiaries showed no traces of this insecticide. Imidacloprid affects the survival rate and behavior of Africanized A. mellifera and honey quality., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Michele Potrich reports financial support was provided by National Council for Scientific and Technological Development. Cristiane Lurdes Paloschi reports financial support was provided by Coordination of Higher Education Personnel Improvement. Rodrigo Mendes Antunes Maciel reports financial support was provided by Coordination of Higher Education Personnel Improvement. Leticia da Silva Ribeiro reports was provided by National Council for Scientific and Technological Development., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The soil sorption coefficient normalized to the organic carbon content (K oc ) is a physicochemical parameter used in environmental risk assessments and in determining the final fate of chemicals released into the environment. Several models for predicting this parameter have been proposed based on the relationship between log K oc and log P. The difficulty and cost of obtaining experimental log P values led to the development of algorithms to calculate these values, some of which are free to use. However, quantitative structure-property relationship (QSPR) studies did not detail how or why a particular algorithm was chosen. In this study, we evaluated several free algorithms for calculating log P in the modeling of log K oc , using a broad and diverse set of compounds (n = 639) that included several chemical classes. In addition, we propose the adoption of a simple test to verify if there is statistical equivalence between models obtained using different data sets. Our results showed that the ALOGPs, KOWWIN and XLOGP3 algorithms generated the best models for modeling K oc , and these models are statistically equivalent. This finding shows that it is possible to use the different algorithms without compromising statistical quality and predictive capacity., (Copyright © 2017 Elsevier Ltd. All rights reserved.)