Determination of pesticides in the respirable fraction of airborne particulate matter by high-performance liquid chromatography–tandem mass spectrometry

Potential harmful effects of pesticides include risks to human health of workers involved in the wet spray application in cultivated areas. Inhalation exposure depends on several factors including pesticide concentrations in the respirable fraction of airborne particulate matter (PM4). To ensure a high level of protection, the use of tractors with cabins provides protection against dust, aerosols, and vapors. Since tractors not providing maximum protection are still in use, PM4 was sampled during spreading operations in agricultural fields inside and outside tractor cabins. Sample preparation technique based on accelerated solvent extraction and solid-phase extraction cleanup was optimized before analysis of nine pesticides in PM4. Meptyldinocap, deltamethrin, myclobutanil, fluopyram, methoxyfenozide, dimethomorph, fluopicolide, cyflufenamid, and metrafenone were simultaneously determined by high-performance liquid chromatography–electrospray ionization–tandem mass spectrometry (HPLC–ESI–MS–MS). The results demonstrated the efficacy of the tractor cabs used in the sampling sites. © 2017 Taylor & Francis

AUTONOMOUS SYSTEMS & SAFETY ISSUES: THE ROADMAP TO ENABLE NEW ADVANCES IN INDUSTRIAL APPLICATIONS

The paper addresses the safety issues related to the development of new solutions based on autonomous systems for industrial applications and the necessity to develop experimental environments for investigating these cases; a set of examples is proposed in order to provide cases and challenges as well as to suggest approaches to address these problems

Hydrophilic Interaction Liquid Chromatography-Tandem Mass Spectrometry Analysis of Fosetyl-Aluminum in Airborne Particulate Matter

Fosetyl-aluminum is a synthetic fungicide administered to plants especially to prevent diseases caused by the members of the Peronosporales and several Phytophthora species. Herein, we present a selective liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to analyze residues of fosetyl-A1 in air particulate matter. This study was performed in perspective of an exposure assessment of this substance of health concern in environments where high levels of fosetly-Al, relatively to airborne particulate matter, can be found after spraying it. The cleanup procedure of the analyte, from sampled filters of atmospheric particulate matter, was optimized using a Strata X solid-phase extraction cartridge, after accelerated extraction by using water. The chromatographic separation was achieved using a polymeric column based on hydrophilic interaction in step elution with water/acetonitrile, whereas the mass spectrometric detection was performed in negative electrospray ionization. The proposed method resulted to be a simple, fast, and suitable method for confirmation purposes

Autonomous Vehicles Management in Agriculture with Bluetooth Low Energy (BLE) and Passive Radio Frequency Identification (RFID) for Obstacle Avoidance

Obstacle avoidance is a key aspect for any autonomous vehicles, and their usage in agriculture must overcome additional challenges such as handling interactions with agricultural workers and other tractors in order to avoid severe accidents. The simultaneous presence of autonomous vehicles and workers on foot definitely calls for safer designs, vehicle management systems and major developments in personal protective equipment (PPE). To cope with these present and future challenges, the “SMARTGRID” project described in this paper deploys an integrated wireless safety network infrastructure based on the integration of Bluetooth Low Energy (BLE) devices and passive radio frequency identification (RFID) tags designed to identify obstacles, workers, nearby vehicles and check if the right PPE is in use. With the aim of detecting workers at risk by scanning for passive RFID-integrated into PPE in danger areas, transmitting alerts to workers who wear them, tracking of near-misses and activating emergency stops, a deep analysis of the safety requirements of the obstacle detection system is shown in this study. Test programs have also been carried out on an experimental farm with detection ranging from 8 to 12 meters, proving that the system might represent a good solution for collision avoidance between autonomous vehicles and workers on foot