Current methods for evaluating exposure in ecosystems contaminated with hydrophobic organic contaminants typically focus on sediment exposure. However, a comprehensive environmental assessment ...requires a more holistic approach that not only estimates sediment concentrations, but also accounts for exposure by quantifying other pathways, such as bioavailability, bioaccumulation, trophic transfer potential, and transport of hydrophobic organic contaminants within and outside of the aquatic system. The current study evaluated the ability of multiple metrics to estimate exposure in an aquatic ecosystem. This study utilized a small lake contaminated with polychlorinated biphenyls (PCBs) to evaluate exposure to multiple trophic levels as well as the transport of these contaminants within and outside of the lake. The PCBs were localized to sediments in one area of the lake, yet this area served as the source of PCBs to aquatic invertebrates, emerging insects, and fish and terrestrial spiders in the riparian ecosystem. The Tenax extractable and biota PCB concentrations indicated tissue concentrations were localized to benthic invertebrates and riparian spiders in a specific cove. Fish data, however, demonstrated that fish throughout the lake had PCB tissue concentrations, leading to wider exposure risk. The inclusion of PCB exposure measures at several trophic levels provided multiple lines of evidence to the scope of exposure through the aquatic and riparian food web, which aids in assessing risk and developing potential future remediation strategies.
With the increasing demand on pesticide residue laboratories to increase their scope of analysis, high-resolution accurate mass (HRAM) systems have found increasing popularity in this area. The ...systems have the advantage of much more reliable confirmation as high resolution increases the ability to distinguish between masses which are close together and the mass accuracy achieved limits the number of structural formulae. To date, much of the work involving these systems has revolved around developing screening methods and little has been done on use of these systems for quantitative methods. Here we describe the development and validation of a quantitative method for the analysis of 167 pesticide residues and polychlorinated biphenyls (PCBs) in samples of fruit and vegetables according to the protocol described in EU SANTE guidance document. The determination method involves analysis using a GC QExactive orbitrap in full scan mode using EI. The samples were then extracted using the standard mini-Luke method. After extraction with acetone/dichloromethane/petroleum ether 40–60 °C, a solvent exchange into ethyl acetate is carried out. Recovery work was carried out in cucumber, lemon and broccoli representing high water content, high acid content and high chlorophyll content commodity groups. The results show that the default MRL of 10 ppb can be achieved for more than 93% of the pesticides studied. Mass accuracy, ion ratio and matrix effect studies show that the method is robust and provides a viable alternative to triple quadrupole mass spectrometer systems for the quantification of pesticide residues in fruit and vegetable samples.
The analysis of pesticides and other contaminants in food presents ongoing challenges, particularly for laboratories conducting routine testing. Updated regulatory requirements require testing for ...expanded lists of pesticides and at ever lower detection levels. Multiresidue methods assist such laboratories in handling demands for high throughput, but detecting ever-lower maximum residue limits can be difficult with such methods. One approach to address these demands is to develop methods that use high-resolution accurate mass (HRAM) mass spectrometry (MS). Jim Garvey, the Head of Food Chemistry at the Department of Agriculture, Food, and the Marine, in Celbridge, Ireland, recently spoke to us about how his group develops methods, including those using HRAM-MS, to meet ever-changing demands in pesticide analysis.
In regulatory laboratories, where potentially hundreds of different types of sample and active ingredients can be evaluated every year, a unique set of conditions provided by agricultural product ...manufacturers in their regulatory methods are faced with the decision to purchase a new and different analytical column or not follow the enforcement method provided by the manufacturer. Because of this, a multi-analyte method has been developed at the Irish Department of Agriculture, Food and The Marine, contributed to by the regulatory laboratories in Belgium and the Czech Republic, analyzing more than 70 active ingredients using high performance liquid chromatography (HPLC) and more than 35 active ingredients by ultrahigh-pressure liquid chromatography (UHPLC). The method has been designed for use by quality control laboratories and is suitable for determining a range of active substances in a wider range of formulated products as well as the technical AI itself. The method has been validated for linearity, precision, accuracy, and specificity for seven technical active ingredients as defined by FMC Corporation. The method and results are described in this article.
An understudied area in the field of social media research is the design of decision support systems that can aid the manager by way of automated message component generation. Recent advances in this ...form of artificial intelligence has been suggested to allow content creators and managers to transcend their tasks from creation towards editing, thus overcoming a common problem: the tyranny of the blank screen. In this research, we address this topic by proposing a novel system design that will suggest engagement-driven message features as well as automatically generate critical and fully written unique Tweet message components for the goal of maximizing the probability of relatively high engagement levels. Our multi-methods design relies on the use of econometrics, machine learning, and Bayesian statistics, all of which are widely used in the emerging fields of Business and Marketing Analytics. Our system design is intended to analyze Tweet messages for the purpose of generating the most critical components and structure of Tweets. We propose econometric models to judge the quality of written Tweets by way of engagement-level prediction, as well as a generative probability model for the auto-generation of Tweet messages. Testing of our design demonstrates the need to take into account the contextual, semantic, and syntactic features of messages, while controlling for individual user characteristics, so that generated Tweet components and structure maximizes the potential engagement levels.
•A reworking of the verbiage in the descriptive reporting section as well as the results section, the removal of an explicit algorithm, as well as a few unnecessary tables and plots to shorten the length of the manuscript.•Changes made to the abstract to make the contributions more pointed and obvious to the reader.•An interpretation of the 6 contexts leveraged in the analysis.•Adjustment of data table to remove non-sensical reports, such as “0” in variance and standard deviation.•A reporting of the clustering performance of “high”/”low” engagement count data.•A specification for the endogenous model estimation approach.
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