Robotics in meat processing

Scientists are currently investigating micro-robotics in the medical field with a potential to provide better medical technology in the near future. When it comes to the food industry, the use of robots has been traditionally limited to picking and palletization. Today, however, robots are used in material handling and secondary or tertiary packing. Recent developments with faster computers and sophisticated sensors have made it possible to use robotics in the meat processing sectors, where their application has reduced processing costs, occupational injuries, improved efficiency and hygiene associated with meat products. Compared to other industries, the working environment in the meat industry is not very conducive to robotics due to the noisy, damp and cold conditions. Slaughtering animals and cutting meat into pieces and disposing waste is an intensive physically demanding task. This chapter reviews the application of robotics in the meat industry and the advancements that have been made until now

A Systematic Review of the Use of Technology to Monitor Welfare in Zoo Animals:Is There Space for Improvement?

SIMPLE SUMMARY: Ensuring appropriate animal welfare to promote wildlife conservation is a top priority of modern zoos, leading to greater effort to improve welfare monitoring approaches. However, more traditional procedures can present some limitations, while the implementation of technology might become an extra tool to comply with the need of a more efficient welfare assessment. This study aimed to summarise the available body of research on technologies used for the assessment of animal welfare in zoos. The results revealed that the majority of publications were published from 2015 onwards suggesting that this research field is still young. So far, the use of technology to assess zoo animal welfare has focused mainly on large mammals likely due to the emotional impact and interest that they have on the public and media worldwide. In addition, despite the employment of both detached and wearable sensors to assess animal welfare in zoos, implementation of algorithms to enable real-time monitoring of the animals is still scarce compared to research on farm animals. Greater application of technologies in zoo research and on more taxa should be the focus of future studies, so that another effective welfare assessment approach can be used together with more traditional procedures to improve zoo animal welfare and ultimately promote wildlife conservation. ABSTRACT: A top priority of modern zoos is to ensure good animal welfare (AW), thus, efforts towards improving AW monitoring are increasing. Welfare assessments are performed through more traditional approaches by employing direct observations and time-consuming data collection that require trained specialists. These limitations may be overcome through automated monitoring using wearable or remotely placed sensors. However, in this fast-developing field, the level of automated AW monitoring used in zoos is unclear. Hence, the aim of this systematic literature review was to investigate research conducted on the use of technology for AW assessment in zoos with a focus on real-time automated monitoring systems. The search led to 19 publications with 18 of them published in the last six years. Studies focused on mammals (89.5%) with elephant as the most studied species followed by primates. The most used technologies were camera (52.6%) and wearable sensors (31.6%) mainly used to measure behaviour, while the use of algorithms was reported in two publications only. This research area is still young in zoos and mainly focused on large mammals. Despite an increase in publications employing automated AW monitoring in the last years, the potential for this to become an extra useful tool needs further research

An ethogram of biter and bitten pigs during an ear biting event: first step in the development of a Precision Livestock Farming tool

peer-reviewedPigs reared in intensive farming systems are more likely to develop damaging behaviours such as tail and ear biting (EB) due to their difficulty in coping with the environment and their inability to perform natural behaviours. However, much less is known about the aetiology of EB behaviour compared to tail biting behaviour. Application of new intervention strategies may be the key to deal with this welfare issue. The discipline of Precision Livestock Farming (PLF) allows farmers to improve their management practices with the use of advanced technologies. Exploring the behaviour is the first step to identify reliable indicators for the development of such a tool. Therefore, the aim of this study was to develop an ethogram of biter and bitten pigs during an EB event and to find potential features for the development of a tool that can monitor EB events automatically and continuously. The observational study was carried out on a 300 sow farrow-to-finish commercial farm in Ireland (Co. Cork) during the first and second weaner stages. Three pens per stage holding c. 35 pigs each, six pens in total, were video recorded and 2.2 h of videos per pen were selected for video analysis. Two ethograms were developed, one for the biter and one for the bitten pig, to describe their behavioural repertoire. Behaviours were audio-visually labelled using ELAN and afterwards the resulting labels were processed using MATLAB® 2014. For the video data, duration and frequency of the observed behavioural interactions were quantified. Six behaviours were identified for the biter pig and a total of 710 interactions were observed: chewing (215 cases), quick bite (138 cases), pulling ear (97 cases), shaking head (11 cases), gentle manipulation (129 cases) and attempt to EB (93 cases). When the behaviour observed was not certain, it was classified as doubt (27 cases). Seven behaviours were identified for the bitten pig in response to the biters behaviour and were divided in: four non-vocal behaviours described as biting (40 cases), head knocking (209 cases), shaking/moving head (225 cases) or moving away (156 cases); and three vocal behaviours identified as scream (74 cases), grunt (166 cases), and squeal (125 cases). Vocal behaviours were classified using a verified set of features yielding a precision of 83.2%. A significant difference in duration was found between all the behaviours (P < 0.001), except between gentle manipulation and chewing where no difference in duration was found (P < 0.338). The results illustrate the heterogeneity of EB behaviours, which may be used to better understand this poorly studied damaging behaviour. They also indicate potential for the development of a PLF tool to automatically, continuously monitor such behaviour on farm by combining the behaviour of the biter pig and the bitten pigs responses

Value of simplified lung lesions scoring systems to inform future codes for routine meat inspection in pigs

peer-reviewedBackground Across the European Union (EU), efforts are being made to achieve modernisation and harmonisation of meat inspection (MI) code systems. Lung lesions were prioritised as important animal based measures at slaughter, but existing standardized protocols are difficult to implement for routine MI. This study aimed to compare the informative value and feasibility of simplified lung lesion scoring systems to inform future codes for routine post mortem MI. Results Data on lung lesions in finisher pigs were collected at slaughter targeting 83 Irish pig farms, with 201 batches assessed, comprising 31,655 pairs of lungs. Lungs were scored for cranioventral pulmonary consolidations (CVPC) and pleurisy lesions using detailed scoring systems, which were considered the gold standard. Using the data collected, scenarios for possible simplified scoring systems to record CVPC (n = 4) and pleurisy (n = 4) lesions were defined. The measurable outcomes were the prevalence and (if possible) severity scoring at batch level for CVPC and pleurisy. An arbitrary threshold was set to the upper quartile (i.e., the top 25% of batches with high prevalence/severity of CVPC or pleurisy, n = 50). Each pair of measurable outcomes was compared by calculating Spearman rank correlations and assessing if batches above the threshold for one measurable outcome were also above it for their pairwise comparison. All scenarios showed perfect agreement (k = 1) when compared among themselves and the gold standard for the prevalence of CVPC. The agreement among severity outcomes and the gold standard showed moderate to perfect agreement (k = [0.66, 1]). The changes in ranking were negligible for all measurable outcomes of pleurisy for scenarios 1, 2 and 3 when compared with the gold standard (rs ≥ 0.98), but these changes amounted to 50% for scenario 4. Conclusions The best simplified CVPC scoring system is to simply count the number of lung lobes affected excluding the intermediate lobe, which provides the best trade-off between value of information and feasibility, by incorporating information on CVPC prevalence and severity. While for pleurisy evaluation, scenario 3 is recommended. This simplified scoring system provides information on the prevalence of cranial and moderate and severe dorsocaudal pleurisy. Further validation of the scoring systems at slaughter and by private veterinarians and farmers is needed

Environmental Risk Factors Influence the Frequency of Coughing and Sneezing Episodes in Finisher Pigs on a Farm Free of Respiratory Disease

Inappropriate environmental conditions in pig buildings are detrimental for both pig and farm-staff health and welfare. With ongoing technological developments, a variety of sensor technology is available and can be used to measure environmental conditions such as air temperature, relative humidity, and ammonia and dust concentrations in real time. Moreover, a tool was recently developed to give farmers an objective assessment of pigs' respiratory health by continuously measuring coughing in finisher pigs. This study assessed baseline levels of coughing on a farm free of respiratory disease, and aimed to identify relationships between environmental conditions and coughing frequency in pigs. Six replicates were conducted. Coughing levels in healthy pigs were overall low, and coughing frequency can be predicted by environmental conditions such as high ammonia concentrations and high ventilation rates. Results of this study can be used as guidelines to determine normal coughing levels in healthy pigs, and to calibrate the alarm systems of tools that measure coughing frequency, such as the cough monitor used in this study. The collection and amalgamation of data from a variety of sources related to health, welfare, and performance are important in order to improve the efficiency and sustainability of the pig industry. This study aimed to assess baseline levels of coughing on a farm free of respiratory disease, and to identify relationships between environmental conditions and coughing frequency in finisher pigs. Six replicates were conducted (690 pigs in total). A cross-correlation analysis was performed and lags of the predictor variables were carried forward for multivariable regression analysis when significant and showing r > 0.25. Results show that coughing frequency was overall low. In the first replicate, coughing was best predicted by exposure to higher ammonia concentrations that occurred with a lag of 1, 7, and 15 days (p = 0.003, p = 0.001, and p −0.70). In conclusion, guidelines on coughing levels in healthy pigs and calibration of the alarm systems of tools that measure coughing frequency can be extrapolated from this study. Environmental risk factors are associated with the respiratory health of finisher pigs

Automatic cough detection for bovine respiratory disease in a calf house

peer-reviewedIn calf rearing, bovine respiratory disease (BRD) is a major animal health challenge. Farmers incur severe economic losses due to BRD. Additional to economic costs, outbreaks of BRD impair the welfare of the animal and extra expertise and labour are needed to treat and care for the infected animals. Coughing is recognised as a clinical manifestation of BRD. Therefore, the monitoring of coughing in a calf house has the potential to detect cases of respiratory infection before they become too severe, and thus to limit the impact of BRD on both the farmer and the animal. The objective of this study was to develop an algorithm for detection of coughing sounds in a calf house. Sounds were recorded in four adjacent compartments of one calf house over two time periods (82 and 96 days). There were approximately 21 and 14 calves in each compartment over the two time-periods, respectively. The algorithm was developed using 445 min of sound data. These data contained 664 different cough references, which were labelled by a human expert. It was found that, during the first time period in all 3 of the compartments and during the second period in 2 out of 4 compartments, the algorithm worked very well (precision higher than 80%), while in the 2 other cases the algorithm worked well but the precision was less (66.6% and 53.8%). A relation between the number of calves diagnosed with BRD and the detected coughs is shown

Adding value to food chain information: using data on pig welfare and antimicrobial use on-farm to predict meat inspection outcomes

peer-reviewedBackground Using Food Chain Information data to objectively identify high-risk animals entering abattoirs can represent an important step forward towards improving on-farm animal welfare. We aimed to develop and evaluate the performance of classification models, using Gradient Boosting Machine algorithms that utilise accurate longitudinal on-farm data on pig health and welfare to predict condemnations, pluck lesions and low cold carcass weight at slaughter. Results The accuracy of the models was assessed using the area under the receiver operating characteristics (ROC) curve (AUC). The AUC for the prediction models for pneumonia, dorsocaudal pleurisy, cranial pleurisy, pericarditis, partial and total condemnations, and low cold carcass weight varied from 0.54 for pneumonia and 0.67 for low cold carcass weight. For dorsocaudal pleurisy, ear lesions assessed on pigs aged 12 weeks and antimicrobial treatments (AMT) were the most important prediction variables. Similarly, the most important variable for the prediction of cranial pleurisy was the number of AMT. In the case of pericarditis, ear lesions assessed both at week 12 and 14 were the most important variables and accounted for 33% of the Bernoulli loss reduction. For predicting partial and total condemnations, the presence of hernias on week 18 and lameness on week 12 accounted for 27% and 14% of the Bernoulli loss reduction, respectively. Finally, AMT (37%) and ear lesions assessed on week 12 (15%) were the most important variables for predicting pigs with low cold carcass weight. Conclusions The findings from our study show that on farm assessments of animal-based welfare outcomes and information on antimicrobial treatments have a modest predictive power in relation to the different meat inspection outcomes assessed. New research following the same group of pigs longitudinally from a larger number of farms supplying different slaughterhouses is required to confirm that on farm assessments can add value to Food Chain Information reports

Methodologies for Assessing Disease Tolerance in Pigs

Features of intensive farming can seriously threaten pig homeostasis, well-being and productivity. Disease tolerance of an organism is the adaptive ability in preserving homeostasis and at the same time limiting the detrimental impact that infection can inflict on its health and performance without affecting pathogen burden per se. While disease resistance (DRs ) can be assessed measuring appropriately the pathogen burden within the host, the tolerance cannot be quantified easily. Indeed, it requires the assessment of the changes in performance as well as the changes in pathogen burden. In this paper, special attention is given to criteria required to standardize methodologies for assessing disease tolerance (DT) in respect of infectious diseases in pigs. The concept is applied to different areas of expertise and specific examples are given. The basic physiological mechanisms of DT are reviewed. Disease tolerance pathways, genetics of the tolerance-related traits, stress and disease tolerance, and role of metabolic stress in DT are described. In addition, methodologies based on monitoring of growth and reproductive performance, welfare, emotional affective states, sickness behavior for assessment of disease tolerance, and methodologies based on the relationship between environmental challenges and disease tolerance are considered. Automated Precision Livestock Farming technologies available for monitoring performance, health and welfare-related measures in pig farms, and their limitations regarding DT in pigs are also presented. Since defining standardized methodologies for assessing DT is a serious challenge for biologists, animal scientists and veterinarians, this work should contribute to improvement of health, welfare and production in pigs

Effects of Nitrogen and Planting Seed Size on Cotton Growth, Development, and Yield

A standardized experiment was conducted during 2009 and 2010 at 20 location-years across U.S. cotton (Gossypium hirsutum L.)-producing states to compare the N use requirement of contemporary cotton cultivars based on their planting seed size. Treatments consisted of three cotton varieties with planting seed of different numbers of seed per kg and N rates of 0, 45, 90, and 134 kg ha⁻¹. Soil at each trial location was sampled and tested for nitrate presence. High levels of soil nitrate (>91 N-NO₃⁻kg ha⁻¹) were found in Arizona and western Texas, and soil nitrate in the range of 45 to 73 kg N-NO₃⁻ ha⁻¹ was found at locations in the central United States. Cotton lint yield responded to applied N at 11 of 20 locations. Considering only sites that responded to applied N, highest lint yields were achieved with 112 to 224 kg ha⁻¹of applied plus pre-plant residual soil NO₃—translating to an optimal N requirement of 23 kg ha⁻¹ per 218 kg bale of lint produced. Among the varieties tested those with medium-sized seed produced higher yields in response to N than did larger and smaller seeded varieties. Varieties with larger seed had longer and stronger fibers, higher fiber length uniformity than small seeded varieties and decreased micronaire. Seed protein and oil increased and decreased slightly in response to increasing amounts of soil nitrate plus applied N, respectively

Evaluating the impact of Relative Total Dose Intensity (RTDI) on patients' short and long-term outcome in taxane- and anthracycline-based chemotherapy of metastatic breast cancer- a pooled analysis

Background: Chemotherapy dose delay and/or reduction lower relative total dose intensity (RTDI) and may affect short- and long-term outcome of metastatic breast cancer (MBC) patients. Methods: Based on 933 individual patients' data of from 3 randomized MBC trials using an anthracycline and taxane we examined the impact of RTDI on efficacy and determined the lowest optimal RTDI for MBC patients. Results: Median time to disease progression (TTDP) and overall survival (OS) of all patients were 39 and 98 weeks. Overall higher RTDI was correlated with a shorter TTDP (log-rank p = 0.0525 for 85% RTDI cut-off). Proportional hazards assumption was violated, there was an early drop in the TTDP-curve for the high RTDI group. It was explained by the fact that patients with primary disease progression (PDP) do have a high RTDI per definition. Excluding those 114 patients with PDP the negative correlation between RTDI and TTDP vanished. However, non-PDP patients with RTDI-cut-off levels <85% showed a shorter OS than patients with higher RTDI levels (p = 0.0086). Conclusions: Optimizing RTDI above 85% appears to improve long-term outcome of MBC patients receiving first-line chemotherapy. Lowering RTDI had no negative influence on short term outcome like OR and TTDP