This review describes the current state of knowledge relating to scientific literature on welfare indicators for goats. Our aim was to provide an overview of animal-based indicators for on-farm welfare assessments. We performed a literature search and extracted 96 relevant articles by title, abstract, and full-text screening. Out of these articles, similar indicators were aggregated to result in a total of 32 welfare indicators, some of which were covered in multiple articles, others in only a single one. We discuss a set of three established assessment protocols containing these indicators, as well as all individual indicators which were covered in more than one article. As single indicators, we identified lameness, body condition score (BCS), qualitative behaviour assessment (QBA), and human–animal relationship (HAR) tests with substantial evidence for sufficient validity to assess welfare in goats. A multitude of indicators (e.g., hair coat condition) was studied less intensively but was successfully used for welfare assessments. For some indicators (e.g., oblivion, lying behaviour), we highlight the need for future research to further validate them or to optimise their use in on-farm welfare assessments. Moreover, further investigations need to include kids, bucks, and meat and fibre goats, as well as extensively kept goats as the literature predominantly focuses on dairy goats in intensive production systems.

This review describes the current state of knowledge relating to scientific literature on welfare indicators for goats. Our aim was to provide an overview of animal-based indicators for on-farm welfare assessments. We performed a literature search and extracted 96 relevant articles by title, abstract, and full-text screening. Out of these articles, similar indicators were aggregated to result in a total of 32 welfare indicators, some of which were covered in multiple articles, others in only a single one. We discuss a set of three established assessment protocols containing these indicators, as well as all individual indicators which were covered in more than one article. As single indicators, we identified lameness, body condition score (BCS), qualitative behaviour assessment (QBA), and human–animal relationship (HAR) tests with substantial evidence for sufficient validity to assess welfare in goats. A multitude of indicators (e.g., hair coat condition) was studied less intensively but was successfully used for welfare assessments. For some indicators (e.g., oblivion, lying behaviour), we highlight the need for future research to further validate them or to optimise their use in on-farm welfare assessments. Moreover, further investigations need to include kids, bucks, and meat and fibre goats, as well as extensively kept goats as the literature predominantly focuses on dairy goats in intensive production systems.

The value society assigns to animal welfare in agricultural productions is increasing, resulting in ever-enhancing methods to assess the well-being of farm animals. The aim of this study was to review the scientific literature to obtain an overview of the current knowledge on welfare assessments for sheep and to extract animal-based welfare indicators as well as welfare protocols with animal-based indicators. By title and abstract screening, we identified five protocols and 53 potential indicators from 55 references. Three out of the five protocols include animal-based as well as resource-based indicators. All of them were assessed as being practicable on-farm but lacking reliability. Some of the single indicators are endorsed by the literature and widely used in the field like assessment of behaviour, lameness or body condition score. Others (e.g., Faffa Malan Chart FAMACHA©, dag score or pain assessment) are regularly mentioned in the literature, but their reliability and usefulness are still subject of discussion. Several indicators, such as pruritic behaviour, eye condition, lying time or tooth loss are relatively new in the literature and still lack evidence for their validity and usefulness. This literature review serves as a starting point for the development of valid and practicable welfare protocols for sheep.

A major challenge in soil science is to monitor and understand the state and change of soils at a national scale to inform decision making and policy. To address this, there is a need to identify key parameters for soil health and function and determine how they relate to other parameters, including traditional soil surveys. Here we present a national‐scale dataset of topsoil sampled as part of a wider agri‐environment monitoring scheme in Wales, UK. Over 1,350 topsoils (0–15 cm) were sampled across a very wide range of habitats and a range of physical, chemical and biological soil quality indicators were measured. We show consistent differences in soil physicochemical properties across habitat types, with carbon decreasing and pH increasing across the habitat productivity gradient from bogs through woodlands and grasslands to arable systems. The soils within our dataset are largely within the limits identified as important for supporting habitat function, with the exception of excessive phosphate levels in mesotrophic grassland. Cluster detection methods identified four soil functional classes based on measured topsoil properties, which were more related to habitat type than the genesis‐based soil classification from soil maps. These soil functional classes can be interpreted as phenoforms within the soil genoforms found by traditional soil classification. This shows the importance of land‐use management in determining the soil health and functional capacity of soils. Our work provides an account of the current state of soil health in Wales, its relationship to soil function and a baseline for future monitoring to track changes against agri‐environment and other policy targets. HIGHLIGHTS: We measured soil physicochemical properties in ~1,350 sites in a variety of temperate habitats There was a strong gradient in soil carbon and pH, with other variables being correlated with these Mesotrophic grassland sites had phosphate levels above the identified limit for good functioning Soil classes from topsoil properties were more related to land use than soil map classifications

Circularity can help to prevent depletion of the earth’s limited material resources, which are vital for human’s modern society. Circular economy strategies of slowing and closing loops of resources have the ultimate goal of keeping materials useful (i.e. in-use) while avoiding losses (dissipation) and hibernation of materials; therefore, appropriate indicators that can measure these aspects are necessary. We propose a measurement of the circularity of materials by quantifying their in-use occupation, that is, the maintenance of materials in a useful state in products for as long as possible, avoiding dissipation or hibernation. Specifically, two indicators were developed: in-use occupation ratio (UOR) and final retention in society (FRS). These indicators were applied in two case studies (materials in a laptop and wood products) with three scenarios each (linear, reuse, and recycling). The reuse scenarios generally presented a higher UOR (41–48% for laptop materials and 53% for wood) compared to recycling scenarios (29–45% for laptop materials and 52% for wood). Only two scenarios of wood products resulted in retaining materials for the next generation (FRS > 0%). We argue that the differentiation between supply, in-use, and hibernation phases is essential for a circular economy. The occupation of materials is shown in charts to facilitate understanding by non-experts and can provide a scientific basis for policies supporting technologies or products with increased in-use occupation and retention of materials.

Nowadays, consumers are more aware about what they eat and how it is packaged. Food quality is of paramount importance and consumers are eager to be constantly updated about the perishability and shelf-life of the food products they buy. This gave rise to intelligent packaging (IP) materials and devices that can communicate with all people throughout the entire food route. One of the main colour-based IP systems is based on the use of anthocyanin (ATH)-based natural dyes by exploiting their pH-dependent colour changes that can be easily readable by the naked eye.This review focuses on recent studies regarding ATH-based sensor packaging materials development for IP applications, offering valuable insights regarding the main factors that affect the efficacy of the developed IP, such as the material where the ATH is anchored, ATH type and concentration, the ingredients used in the formulation of the sensor and the storage conditions of the food product. Additionally, the last ATH-based IP developed are also summed and discussed in detail to identify the major bottlenecks that need to be overcome for accelerating the commercial application of ATH-based sensors in IP.Although ATH-based indicators are able to correctly indicate food shelf-life in several products at a laboratory scale, their industrial production is still impaired by the production methods used for this type of sensors. Furthermore, ATHs are labile compounds that require stabilization in the packaging material to yield stable, standardized and durable IP materials.

Zoning protected areas is essential for ecological protection and environmental management. However, the protected areas generated via bottom-up processes depend highly on the attitudes of local authorities. Moreover, the performance of protected areas will inevitably be weakened by human activities if there exists an inconsistency between protection and land development. To reveal and solve these problems through top-down approaches, a novel framework for the improvement of protected areas (ERL) is presented in this study. First, the ecological conditions of both the previously-established ERL and land use status quo were assessed through morphological spatial pattern analysis (MSPA) and a set of graph-based indicators (e.g., connectivity indices). Second, the low-quality parts of the ERL were improved based on a comparison with the observed land use condition. The results indicated that the ecologically important areas that were excluded from the previously-established ERL can be effectively identified by the combination of MSPA and graph-based indicators. The percentages of high-quality components moderately increased after the improvement. Specifically, low-level core patches can be upgraded by incorporating the ecologically important pixels that were previously neglected. Moreover, many low-quality small islets can be enhanced to better serve the function of temporary habitats. In summary, these results are expected to provide practical guidance for ecological conservation planning and management. More importantly, our proposed zoning framework can be further generalized to the analysis in many other fast-growing regions.

Finfish farming is the most common aquaculture mode in Europe. In Norway, the industry faces sustainability challenges. One major challenge is fish escape, which is a threat to both the environment and the industry's reputation. The more complex the operation, the greater the risk of escape, and their safety management needs improvement. A recommended strategy is to implement a safety indicator programme to monitor the risk levels before, during, and after an operation.The main objective of this study is to identify risk influencing factors (RIFs) and develop safety indicators for fish farm operations based on accident reports, using a qualitative graphical network to visualise and systematise causal chains. We have used a six-step methodology to develop safety indicators that can be applied to the case of fish escape: 1) The study was limited to fish escape accidents caused by the hazardous events hole in the net and submerged net. 2) Operations of high risk were identified, and chains of events were established, starting with these operations and ending with the accident (fish escape), based on fish escape report data and accident analyses. 3) A qualitative Bayesian network (BN) was drawn to specify the influence between the contributing causes and conditions in the causal chains. 4) RIFs were identified based on the BN (seven environmental, four organisational, eight operational, and 12 technical). 5) Safety indicators were developed to measure the condition of the RIFs. Update frequency of indicators, methods of measurement, and recommended states were also suggested. 6) The safety indicators were evaluated according to the chosen quality criteria. Based on the resulting list of safety indicators, we suggest a safety indicator programme for the operation fish crowding.The causal chains, RIFs, and safety indicators can also be used as a supplement in internal audits and quality improvement work, development of preventive measures, and training of fish farm personnel.

The progress of the aquaculture industry in Iran as an environmental and economical maintainable process needs an efficient and low-cost tool for regular checking of adjacent environments. Biological monitoring by macroinvertebrate is operative for assessment of water quality. Sampling operation was carried out to investigate the influence of aquaculture wastewater on macroinvertebrate communities at 4 stations over one year (spring, summer, autum and winter) in the Chehel Chai River. 2040 (19% spring, 18% summer, 25% autumn and 38% winter) macroinvertebrate specimens belonging to 6 orders and 14 families were recognized. The most abundance among the stations belonged to the Diptera and Chironomidae. Two groups of macroinvertebrate assemblages (sensitive to tolerance) and three groups of stations (upstream, outfall and down1 and down2) were identified with Heat map analysis. The study was showed that rainbow trout farm most often significantly increase in the influence of fine particulate organic material (FPOM %), NO3 and PO4. According to HFBI results, organic water pollution at different stations was classified as good (upstream), appropriate, relatively poor and poor (outfall). The combined results of the biomarkers were showed that the outfall station had more organic contamination than its predecessor station (relatively poor water quality) which required more efficient management based on the self-purification capacity of the Chehel Chai River.

Batteries are multi-physical systems and during actual operating conditions they are submitted to variable ambient operating conditions which can affect the dynamic behavior and the degradation. Therefore, a good understanding of the dynamic behavior and the degradation laws under actual operating conditions is the key to a durability improvement and to the development of better energy management strategies. The purpose of the proposed study is to use an experimental database issued from a three years monitoring of a ten postal vehicle fleet to model the batteries with respect to operating conditions. Based on an electrical circuit model, an optimization algorithm and a Kalman filter, the scientific contribution is to propose a simple but efficient method, using vehicle operating data only, to estimate on-board the state of charge and state of health indicators linked to internal resistance and available capacity. The proposed model presents a very good accuracy and state of health indicators estimations show promising results. In the future, the proposed method could be applied on-board to estimate and analyze the state of health during the entire battery lifetime in order to provide an accurate state of charge estimation and to contribute to a better understanding of the degradation laws.