Incidences of mortality of Indian peafowl Pavo cristatus due to pesticide poisoning in India and accumulation pattern of chlorinated pesticides in tissues of the same species collected from Ahmedabad and Coimbatore

Tissue-specific distributions of organic ultraviolet absorbents in free-range chickens and domestic pigeons from Guangzhou, China

The ecological risks of organic ultraviolet absorbents (UVAs) have been of increasing concern. Studies have found that these chemicals could be accumulated in terrestrial animals and pose toxicities. However, tissue distribution of UVAs in terrestrial species was far from well understood. In this study, free-range chickens and domestic pigeons were selected to investigate the occurrence and tissue distribution of UVAs. Total concentrations of eleven UVAs in muscles ranged from 778 to 2874 (mean 1413 ± 666) ng/g lipid weight, which were higher than those in aquatic species worldwide. Since low UVA concentrations in local environment were previously reported, the results implied the strong accumulation of UVAs in studied species. Brain, stomach and kidney were main target organs for studied UVAs, differentiating from the strong liver sequestration in aquatic species. The mean tissue-to-muscle ratios of 1.02-4.23 further indicated the preferential accumulation of target UVAs in these tissues. The tissue-to-blood ratios of benzophenone (BP), 2-ethylhexyl salicylate (EHS) and homosalate (HMS) in brain were 370, 1207 and 52.0, respectively, implying their preferential accumulation in brain. More research is needed to characterize the toxicokinetics and tissue distribution of UVAs in terrestrial wild species, in order to further understand their potential risks.

Assessment of chlorinated pesticide exposure to white-rumped vulture Gyps bengalensis in India

Populations of the critically endangered white-rumped vulture (WRV) Gyps bengalensis have declined drastically due to the use of diclofenac for veterinary purposes in Indian subcontinent. Thirty-two dead WRVs collected from three states, namely Gujarat, Assam and Tamil Nadu in India between 2011 and 2014 were investigated to understand the role of diclofenac in the death, and the results were published. Furthermore, since organochlorine pesticides have been linked to long-term impact on populations in many species of birds across the globe, available tissues of 21 WRVs were tested also for six organochlorine pesticides (DDT, HCH, endosulfan, heptachlor, dieldrin and dicofol) and chlorpyrifos. All vultures were found to have had one or more detectable levels of pesticides in their tissues except one. Similarly, all the pesticides included in the study were detected in at least one of the vultures analysed. DDT (95.2%) was the most frequently detected pesticide followed by HCH (90.5%), and DDT (73.6%) contributed the most to the total pesticide load. Total pesticide load ranged between below detection limit (BDL) and 8753.4 ng/g. High levels of total pesticide load recorded in gut contents showed recent exposure to these legacy pesticides even long after their ban. However, it is perceived that studied pesticides' exposure to birds and their presence in the environment is in decreasing trend in India. Although, varying levels of pesticides were detected, all of which were below the levels reported to be toxic, and also reported earlier in the same species in India. Recorded levels may not create a problem to vultures unlike diclofenac; nevertheless, as continued exposure to the pesticides studied may lead to sub lethal effects in birds, it is prudent to monitor these pesticides along with new generation pesticides and NSAIDs in the critically endangered white-rumped vulture in India, towards its conservation.

Breaking boundaries: Artificial intelligence for pesticide detection and eco-friendly degradation

Pesticides are extensively used agrochemicals across the world to control pest populations. However, irrational application of pesticides leads to contamination of various components of the environment, like air, soil, water, and vegetation, all of which build up significant levels of pesticide residues. Further, these environmental contaminants fuel objectionable human toxicity and impose a greater risk to the ecosystem. Therefore, search of methodologies having potential to detect and degrade pesticides in different environmental media is currently receiving profound global attention. Beyond the conventional approaches, Artificial Intelligence (AI) coupled with machine learning and artificial neural networks are rapidly growing branches of science that enable quick data analysis and precise detection of pesticides in various environmental components. Interestingly, nanoparticle (NP)-mediated detection and degradation of pesticides could be linked to AI algorithms to achieve superior performance. NP-based sensors stand out for their operational simplicity as well as their high sensitivity and low detection limits when compared to conventional, time-consuming spectrophotometric assays. NPs coated with fluorophores or conjugated with antibody or enzyme-anchored sensors can be used through Surface-Enhanced Raman Spectrometry, fluorescence, or chemiluminescence methodologies for selective and more precise detection of pesticides. Moreover, NPs assist in the photocatalytic breakdown of various organic and inorganic pesticides. Here, AI models are ideal means to identify, classify, characterize, and even predict the data of pesticides obtained through NP sensors. The present study aims to discuss the environmental contamination and negative impacts of pesticides on the ecosystem. The article also elaborates the AI and NP-assisted approaches for detecting and degrading a wide range of pesticide residues in various environmental and agrecultural sources including fruits and vegetables. Finally, the prevailing limitations and future goals of AI-NP-assisted techniques have also been dissected.

Nimesulide poisoning in white-rumped vulture Gyps bengalensis in Gujarat, India

Population of white-rumped vulture has not recovered in India to a desired level even after diclofenac was banned in 2006. During 2019, there were two known separate incidents of white-rumped vulture mortality involving four white-rumped vultures in Gujarat. After post-mortem examinations, tissues of all four vultures were received for toxicological investigation at the National Centre for Avian Ecotoxicology, SACON. Tissues were screened for a set of toxic pesticides, and none of them was at detectable level. Subsequently, the tissues were analysed for thirteen NSAIDs and paracetamol. Of all the drugs tested, only nimesulide was detected in all the tissues (17-1395 ng/g) indicative of exposure. Visceral gout was also observed in all the four vultures during post-mortem. Residues of nimesulide in tissues with symptoms of gout indicated that the vultures died due to nimesulide poisoning. Although, other than diclofenac, many NSAIDs are suspected to be toxic to white-rumped vultures, only nimesulide is reported in the recent past with clear symptom of gout in wild dead white-rumped vultures similar to diclofenac. Since, nimesulide appears to act similar to diclofenac in exerting toxic effects, if veterinary use of nimesulide continues, white-rumped vulture are bound to suffer. Hence, it is recommended that nimesulide should be banned by the government to conserve white-rumped vulture in the Indian subcontinent. Further, an effective system is recommended to be put in place to collect the tissues of dead vultures for toxicological investigations and eventual conservation of the critically endangered species.

Animal Harms and Food Production: Informing Ethical Choices

Simple Summary

Consideration of animal welfare in food choices has become an influential contemporary theme. Traditional animal welfare views about food have been largely restricted to direct and intentional harms to livestock in intensive animal agriculture settings. However, many harms to animals arising from diverse food production practices in the world are exerted indirectly and unintentionally and often affect wildlife. Here we apply a qualitative analysis of food production by considering the breadth of harms caused by different food production systems to wild as well as domestic animals. Production systems are identified that produce relatively few and relatively many harms. The ethical implications of these findings are discussed for consumers concerned with the broad animal welfare impacts of their food choices.

Abstract

Ethical food choices have become an important societal theme in post-industrial countries. Many consumers are particularly interested in the animal welfare implications of the various foods they may choose to consume. However, concepts in animal welfare are rapidly evolving towards consideration of all animals (including wildlife) in contemporary approaches such as “One Welfare”. This approach requires recognition that negative impacts (harms) may be intentional and obvious (e.g., slaughter of livestock) but also include the under-appreciated indirect or unintentional harms that often impact wildlife (e.g., land clearing). This is especially true in the Anthropocene, where impacts on non-human life are almost ubiquitous across all human activities. We applied the “harms” model of animal welfare assessment to several common food production systems and provide a framework for assessing the breadth (not intensity) of harms imposed. We considered all harms caused to wild as well as domestic animals, both direct effects and indirect effects. We described 21 forms of harm and considered how they applied to 16 forms of food production. Our analysis suggests that all food production systems harm animals to some degree and that the majority of these harms affect wildlife, not livestock. We conclude that the food production systems likely to impose the greatest overall breadth of harms to animals are intensive animal agriculture industries (e.g., dairy) that rely on a secondary food production system (e.g., cropping), while harvesting of locally available wild plants, mushrooms or seaweed is likely to impose the least harms. We present this conceptual analysis as a resource for those who want to begin considering the complex animal welfare trade-offs involved in their food choices.

Organochlorine Pesticide Residues Among Colonial Nesting Birds in Tamil Nadu, India: A Maiden Assessment from Their Breeding Grounds

Use of pesticides continues to be indiscriminate, and birds are one of the worst affected non-targeted organisms. Information on the ill effects of pesticides on birds far from desired in India. Despite the presence of a wide variety and number of birds, there is exceedingly little data on organochlorine pesticide (OCP) residues in colonial nesting birds in sanctuaries of India. A total of 76 individuals belonging to 14 species of birds found dead between March 2008 and March 2010 were analyzed for pesticide residues in various tissues. Of all the OCPs analyzed, concentration of HCH was found to be the highest. Magnitude of contamination varied widely among species. Accumulation pattern of OCPs in colonial nesting birds was in the order ∑HCH > ∑endosulfan > ∑DDT > heptachlor epoxide > dieldrin. Pesticides, namely p,p-DDE and β-HCH contributed most towards the total OCPs. Concentrations of DDT and its metabolites, HCH and isomers, dieldrin, and heptachlor epoxide were lower than the concentrations reported for various species of birds elsewhere in India. Although the sanctuaries presently studied have official boundaries, physical demarcations are missing and there are no proper earthen dykes particularly in Vedanthangal and Koonthankulam Bird Sanctuaries. During monsoon, runoff not only floods the Sanctuaries but also the cultivated areas nearby. Run off brings in residues of pesticides and fertilizers from the agricultural lands into the sanctuaries. Although OCP results in this study were below threshold limits, it may be noted that the long duration exposure even to low levels of pesticides could create a significant impact at population level. Hence, earthen dykes need to be built to avoid agricultural runoff entering the Sanctuary and also help to hold sufficient amount of water for breeding birds.

The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification

Developing of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and 2D molecular descriptor calculations. Based on the intensities of two characteristic MS peaks, namely, [M] and [M-35], two classification criterions were proposed. According to criterion I, class 1 comprises [M] signals with the intensity higher than 800 NIST units, while class 2 consists of signals with the intensity lower or equal than 800. According to criterion II, class 1 consists of [M-35] signals with the intensity higher than 100, while signals with the intensity lower or equal than 100 belong to class 2. As a result of ANNs learning stage, five models for both classification criterions were generated. The external model validation showed that all ANNs are characterized by high predicting power; however, criterion I-based ANNs are much more accurate and therefore are more suitable for analytical purposes. In order to obtain another confirmation, selected ANNs were tested against additional dataset comprising popular sunscreen agents disinfection by-products reported in previous works.