Search Results (103)

This study investigated the perceptions of animal welfare and the consumption of alternative protein sources among future professionals in agronomy, food science, and veterinary medicine. A sample of 769 participants from three faculties [ESALQ (“Luiz de Queiroz” College of Agriculture), FZEA (School of Animal Science and Food Engineering), and FMVZ (School of Veterinary Medicine and Animal Science)] of the University of São Paulo was used. These faculties have different teaching focuses: agronomy, food and animal production, and veterinary, respectively. A relationship between the perception of animal welfare and alternative sources of protein based on the participants’ educational background was verified, specifically: (i) participants from the FZEA (food science) and FMVZ (veterinary) units would be interested in consuming farmed meat and expressed interest in trying it; (ii) students from the ESALQ (agronomy) have a low level of knowledge about animal welfare and are not very interested in knowing how animals are reared, and few participants attribute the presence of the health inspection seal as influencing their purchasing intention; (iii) participants, regardless of their academic background, did not express an intention to reduce their red meat consumption; (iv) the ESALQ was the campus which showed the most skepticism about animal sentience; (v) most participants from the FMVZ and FZEA reported being willing to pay 4–5% more for products that guarantee animal welfare. The findings suggest that the academic context influences individuals’ perceptions and food choices, highlighting the need for educational strategies that foster a greater awareness of animal welfare, encourage the adoption of more sustainable practices, and promote the acceptance of alternative protein sources within the agri-food sector. Full article

Reliable quality and size inspection of shrimp meat is essential in food processing to ensure food safety, enhance production efficiency, and promote sustainable practices. However, significant scale differences in shrimp meat categories and the presence of subtle local defects pose challenges to traditional manual inspection methods, resulting in low efficiency and high rates of false positives and negatives. To address these challenges, we propose a lightweight multi-scale object detection framework specifically designed for automated shrimp meat inspection in food processing environments. Our framework incorporated a novel downsampling module (ADown) that was engineered to reduce parameters while preserving essential features. Additionally, we propose dual-scale information selection convolution (DSISConv), multi-scale information selection convolution (MSISConv), and a lightweight multi-scale information selection detection head (LMSISD) to improve detection accuracy across diverse object scales. Furthermore, a bidirectional complementary knowledge distillation strategy was employed, which enabled the lightweight model to learn crucial features from a larger teacher model without increasing inference complexity. Experimental results validated the effectiveness of our approach. Compared to the YOLOv11n (baseline) model, the proposed framework improved precision by 1.0%, recall by 0.8%, mAP50 by 0.9%, and mAP50-95 by 1.3%, while simultaneously reducing parameters by 7.1%, model size by 8.0%, and GFLOPs by 22.2%. The application of knowledge distillation yielded further improvements of 0.1% in precision, 1.2% in recall, 0.5% in mAP50, and 0.5% in mAP50-95. These results indicated that the proposed approach provided an effective and efficient solution for real-time shrimp meat inspection, balancing high accuracy with low computational requirements. Full article

The application of Industry 4.0 technologies in the halal meat supply chain (HMSC) is an emerging but underexplored area. While technologies like 3D printing, AI, AR, metaverse, digital twins, robotics, and big data analytics are widely discussed in food production, their specific use in HMSC lacks comprehensive analysis. These technologies can address challenges such as cross-contamination, fraud, and traceability issues, but few studies have examined their practical implementation, highlighting the need for further empirical research. This review explores how Industry 4.0 technologies enhance efficiency, traceability, and transparency in HMSC and highlights the potential use of AR for real-time product verification, metaverse for virtual inspections, AI and robotics for improving efficiency, compliance, and hygiene, and digital twins for training and product quality monitoring. The review also identified research gaps, particularly the lack of focus on intelligent packaging, in vitro meat, and the 3D printing of halal meat products. The findings stress the need for greater exploration of these technologies in the HMSC, emphasizing their transformative potential in creating a transparent and efficient halal food system. Further research on emerging technologies like 3D printing and in vitro meat is essential, especially regarding their impact on halal standards and sustainability, ensuring future growth. Full article

Data from post-mortem inspections conducted using official controls on the meat production of slaughtered pigs are generally considered valuable for identifying herd health issues and ensuring meat safety. However, several studies highlighted that a multi-stage assessment of lung changes would provide more useful information on animal health than the implemented binary (yes/no) recording. For this purpose, a new scheme was developed and subsequently used by trained official veterinarians at four slaughterhouses in Austria. Implementation of the multi-stage assessment was carried out in parallel with the conventional assessment, and data collected from both schemes were analyzed and compared to evaluate effectiveness. The analysis of the data (n = 20,345) showed that the most common alteration was low-grade (28.4%), followed by moderate-grade (11.3%,) and then high-grade pneumonia (5.2%). In the case of pleurisy, 88.9% of the carcasses showed no alterations of the pleura, and 11.1% had pathological changes (low-grade pleurisy = 4.7%, moderate-grade pleurisy = 2.7%, high-grade pleurisy = 3.7%). Analysis of the results showed a strong heterogeneity of the frequency of alterations between the batches reflecting various underlying animal health issues. Among the influencing factors, the origin of the pigs had the greatest influence. The project demonstrated that the new evaluation can be carried out easily with no extra time effort once staff are trained and the technological platform for reporting is adapted. The more detailed information ensures more useful feedback is provided to the farmers and supervising veterinarians, thereby ensuing animal welfare and contributing to sustainable, improved animal husbandry. Full article

The Indonesian maritime territory harbors a rich diversity of marine resources, making up approximately 37% of global fish species diversity. Tuna, particularly in Maluku Province, stands out as a vital economic asset with growing production and export numbers. Current practices for processing and evaluating tuna meat, however, face significant limitations due to basic infrastructure and reliance on manual inspection methods, leading to potential contamination risks and treatment identification errors. This research addresses these challenges by implementing an advanced deep learning solution based on convolutional neural networks (CNNs) to automatically identify three distinct treatment categories for tuna loin: No-Treatment, CO-Treatment, and CS-Treatment. Trained on a comprehensive image dataset, the model demonstrated exceptional performance with 95% accuracy. While field testing confirmed the model’s strong performance in correctly identifying treatment categories, occasional classification errors highlighted areas for improvement in data preprocessing. This study provides a significant step forward in automated fish processing assessment technology, offering a promising solution to longstanding challenges in the marine processing industry. Full article

As global income levels and population increase, meat consumption and production are rising, raising concerns about climate change, animal welfare, and environmental sustainability. Offal offers a sustainable, nutrient-rich, and economical alternative to muscle meat, providing proteins, vitamins, and minerals. This study was triggered by the scarcity of information on the microbiological quality of edible bovine offal, which is often associated with poor hygienic conditions during handling and processing at slaughterhouse. This study assessed the superficial microbiota present on cattle liver and tongue in a vertical slaughterhouse across various stages of the procurement process and on days with different slaughter volumes, with three sampling points: immediately after post-mortem inspection (Point 1); after the arrival of the viscera in the preparation room (Point 2); and in the refrigeration chamber at 3 °C (Point 3). Samples were analysed according to ISO methods for enumeration of mesophilic aerobic bacteria, Enterobacteriaceae, generic Escherichia coli, presumptive Escherichia coli O157, and Staphylococcus aureus and detection of presumptive Escherichia coli O157, Staphylococcus aureus, and Salmonella spp. Microbiological counts were within the acceptability values stipulated in the amendment of Regulation EC 1441/2007 to Regulation EC 2073/2005 for cattle carcasses. In general, both viscera showed higher microbial counts on days with higher slaughter volumes, with the exception of Enterobacteriaceae and Staphylococcus counts on the tongue. There was also an increase in microorganism levels across the offal processing stages. Out of 144 samples, 20.83% were contaminated with presumptive Escherichia coli O157, 3.47% Salmonella spp., and 25% S. aureus. Therefore, although 20.83% of the samples tested were presumptive for E. coli O157, it is important to note that a considerable number of these presumptive positives may in fact have been negative after confirmation by molecular methods. However, the presence of presumptive E. coli O157 at high levels is one reason that the prevention of offal contamination requires more stringent measures. Preventing offal contamination requires stricter measures during slaughter procedures to ensure safety, reduce food losses, and enhance sustainability in meat production. Full article

The complex multi-stage process of meat processing encompasses critical phases, including slaughtering, cooling, cutting, packaging, warehousing, and logistics. The quality and nutritional value of the final meat product are significantly influenced by each processing link. To address the major challenges in the meat processing industry, including device heterogeneity, model deficiencies, rapidly increasing demands for data analysis, and limitations of cloud computing, this study proposes an Internet of Things (IoT) architecture. This architecture is centered around an intelligently decoupled gateway design and edge-cloud collaborative intelligent meat inspection. Pork freshness detection is used as an example. In this paper, a high-precision and lightweight pork freshness detection model is developed by optimizing the MobileNetV3 model with Efficient Channel Attention (ECA). The experimental results indicate that the model’s accuracy on the test set is 99.8%, with a loss function value of 0.019. Building upon these results, this paper presents an experimental platform for real-time pork freshness detection, implemented by deploying the model on an intelligent gateway. The platform demonstrates stable performance with peak model memory usage under 600 MB, average CPU utilization below 20%, and gateway internal response times not exceeding 100 ms. Full article

The proviral load (PVL) of the bovine leukemia virus (BLV) is a useful index for estimating disease progression and transmission risk. Real-time quantitative PCR techniques are widely used for PVL quantification. We previously developed a dual-target detection method, the “Liquid Dual-CoCoMo assay”, that uses the coordination of common motif (CoCoMo) degenerate primers. This method can detect two genes simultaneously using a FAM-labeled minor groove binder (MGB) probe for the BLV long terminal repeat (LTR) region and a VIC-labeled MGB probe for the BoLA-DRA gene. In this study, we evaluated the diagnostic and analytical performance of the Dual-CoCoMo assay targeting the LTR region by comparing its performance against the commercially available Takara multiplex assay targeting the pol region. The diagnostic sensitivity and specificity of the Liquid Dual-CoCoMo assay based on the diagnostic results of the ELISA or original Single-CoCoMo qPCR were higher than those of the Takara multiplex assay. Furthermore, using a BLV molecular clone, the analytical sensitivity of our assay was higher than that of the Takara multiplex assay. Our results provide the first evidence that the diagnostic and analytical performances of the Liquid Dual-CoCoMo assay are better than those of commercially available multiplex assays that target the pol region. Full article

With the increasing importance of meat quality inspection, traditional manual evaluation methods face challenges in terms of efficiency and accuracy. To improve the precision and efficiency of pork quality assessment, an automated detection method based on computer vision technology is proposed for evaluating different parts and freshness of pork. First, high-resolution cameras were used to capture image data of Jinfen white pigs, covering three pork cuts—hind leg, loin, and belly—across three different collection times. These three parts were categorized into nine datasets, and the sample set was expanded through digital image processing techniques. Next, five convolutional neural network models—VGGNet, ResNet, DenseNet, MobileNet, and EfficientNet—were selected for feature recognition experiments. The experimental results showed that the MobileNetV3_Small model achieved an accuracy of 98.59%, outperforming other classical network architectures while being more lightweight. Further statistical analysis revealed that the p-values for ResNet101, EfficientNetB0, and EfficientNetB1 were all greater than 0.05, indicating that the performance differences between these models and MobileNetV3_Small were not statistically significant. In contrast, other models showed significant performance differences (p-value < 0.05). Finally, based on the PYQT5 framework, the MobileNetV3_Small model was deployed on a local client, realizing an efficient and accurate end-to-end automatic recognition system. These findings can be used to effectively enhance the efficiency and reliability of pork quality detection, providing a solid foundation for the development of pork safety monitoring systems. Full article

Spotty liver disease (SLD) affects free-range laying hens, leading to mortality and reduced egg production. Campylobacter species, including Campylobacter hepaticus, have been associated with SLD cases worldwide. However, the cause of SLD-like lesions found in broilers in Japan still remains unclear. The present study aimed to investigate the involvement of Campylobacter spp. in broiler SLD by conducting microbiological, molecular biological, serological, histopathological, and immunohistopathological examinations using specimens of liver, bile, cecum, and serum from SLD-like and non-SLD chickens. C. jejuni was predominantly isolated and detected in approximately 40% of both non-SLD livers and SLD-like livers, with no significant difference between them. However, C. hepaticus was neither isolated nor detected in this study. Gross and histopathology revealed multifocal necrotizing hepatitis, suppurative granulomatous hepatitis, and cholangiohepatitis. Hepatitis stages are classified as no hepatitis, subclinical, acute, and chronic hepatitis. C. jejuni was more frequently present in acute-stage SLD-like livers, and high IgG antibody levels were noted in both subclinical and SLD-like-affected chickens, indicating C. jejuni infection. Immunohistochemical examination also supported these findings. The findings suggest that C. hepaticus was not involved in SLD-like in broilers in Japan, but C. jejuni translocation from the intestines to the liver may be a contributing factor. Full article

Roe deer meat is a prized game product in many European countries. However, concerns exist regarding the accuracy of the amount of declared roe deer in processed game meat foods. This study aimed to develop a reliable method for the detection and quantification of roe deer in commercialized game meat products. A TaqMan probe-based quantitative real-time PCR (qPCR) assay was designed, targeting a single-copy 120-bp region of the roe deer agouti signaling protein (ASIP) encoding gene. The method employed the normalized ∆Cq approach to establish a calibration curve for roe deer detection and quantification within 0.05–50% (w/w) in complex raw and processed matrices. The method proved to be specific for roe deer identification, achieving limits of detection and quantification of 0.04 ng of roe deer DNA and 0.05% (w/w) of roe deer in simulated pâté. Following validation with blind samples, highlighting the precision and trueness of the approach, the assay was applied to 46 market samples from four European origins (Poland, Portugal, France, and Spain). The analysis revealed significant discrepancies between declared roe deer content and actual levels in all roe deer labeled products. The global analysis of results, combining the previous survey on red deer species with present roe deer data, identified 61% of mislabeled/adulterated samples due to the absence of deer species, substitution of roe deer with red deer, substitution of fallow deer with other deer species and red deer with pork, and undeclared addition of roe deer. This study demonstrates the effectiveness of the developed qPCR method for accurate roe deer meat authentication in foods, showing its usefulness as a tool for routine food inspection to ensure labeling compliance. Full article

Osteomyelitis is a significant cause of total carcass condemnation in pigs at the slaughterhouse. The decision for total condemnation of a pig carcass for osteomyelitis is often based on traditional perceptions of the risk of pyaemia, leading to controversy among Official Veterinarians (OV) in the industry. This review aims to provide a more comprehensive understanding of the etiopathogenesis of osteomyelitis in pigs, the microorganisms involved, and the risk factors. It also highlights the urgent need for a more uniform method to evaluate osteomyelitis cases, which could significantly reduce economic losses in the industry. Lesions originating from tail-biting, tail docking, castration, teeth resection, and raw management are described as risk factors for osteomyelitis. Osteomyelitis is caused by the entry of pathogens into the animal’s bloodstream through an open wound. Trueperella monocytogenes, Staphylococcus aureus, and Streptococcus spp. are the most described pathogens. At slaughter, OVs condemn carcasses with osteomyelitis due to pyaemia. Signs of acute disease are essential to identify pyaemia cases. In chronic cases, total carcass condemnation can be avoided depending on the number of lesions and vertebrae affected. A clear overall image of the problem would help authorities in various countries adopt a more homogenous approach. Full article

Trichinellosis is a major foodborne zoonotic disease responsible for 41 human cases, according to the European Union One Health Zoonoses Report. In southern Spain, a quality management system (QMS) was applied to satellite laboratories (SLs) that conduct meat inspections of Trichinella spp. ensuring excellence practices. This study aimed to determine how eventual deviations from standard procedures may influence risk levels using Canonical Discriminant Analysis (CDA). Data were collected during slaughterhouses and game handling establishments’ official audits in 18 SLs located in the provinces of Cordoba and Seville during a 6-year period. Technical requirement deviations regarding technique and trial information, such as performing tests or calculations incorrectly or not following technical procedures, significantly increased risk level differences. Imminent risk levels were detected if the above-mentioned deviations arose. Quality assurance compromising deviations were responsible for 1150 times risk level differences, suggesting finding such may be critical for risk determination. A lack of significant influence of records and documents compromising deviations (incomplete forms or missing-erroneous or illegible data) was found. These results strengthen Trichinella spp. control strategies by pinpointing crucial aspects within QMS that require improvement, particularly in addressing deviations related to technique, trial information, and quality assurance procedures to mitigate associated risks effectively. Full article

Bovine leukemia virus (BLV) is prevalent worldwide, causing serious problems in the cattle industry. The BLV proviral load (PVL) is a useful index for estimating disease progression and transmission risk. We previously developed a quantitative real-time PCR (qPCR) assay to measure the PVL using the coordination of common motif (CoCoMo) degenerate primers. Here, we constructed a novel duplex BLV-CoCoMo qPCR assay that can amplify two genes simultaneously using a FAM-labeled MGB probe for the BLV LTR gene and a VIC-labeled MGB probe for the BoLA-DRA gene. This liquid duplex assay maintained its original sensitivity and reproducibility in field samples. Furthermore, we developed a dry duplex assay composed of PCR reagents necessary for the optimized liquid duplex assay. We observed a strong positive correlation between the PVLs measured using the dry and liquid duplex assays. Validation analyses showed that the sensitivity of the dry duplex assay was slightly lower than that of the other methods for the detection of a BLV molecular clone, but it showed similar sensitivity to the singleplex assay and slightly higher sensitivity than the liquid duplex assay for the PVL quantification of 82 field samples. Thus, our liquid and dry duplex assays are useful for measuring the BLV PVL in field samples, similar to the original singleplex assay. Full article

Osteomyelitis is the leading cause of total carcass condemnation in finishing pigs in Portugal, causing significant economic losses in swine production. The present study sought to determine a possible link between osteomyelitis in pig carcasses, pre-slaughter factors, and concomitant post-mortem inspection findings. For this purpose, meat inspection data were collected from 100,489 finishing pigs slaughtered in a northern Portuguese abattoir. Information regarding total carcass condemnation, slaughter season, origin, sex, tail-biting lesions, and husbandry invasive procedures (tail docking and teeth resection) was collected. The main cause of total carcass condemnation was osteomyelitis (61.03%). A total of 36.16% of osteomyelitis cases were present in the anterior region and 52.20% in the posterior region. In the anterior region, 94.78% of osteomyelitis cases were in the mandibular bone. Pigs with clipped teeth and carcasses with pleurisies were associated with a higher occurrence of osteomyelitis (p = 0.00262 and p < 0.0001, respectively). Second- and third-grade tail-biting lesions were also linked to a higher occurrence of osteomyelitis (p = 0.00128 and p < 0.0001, respectively). Slaughter inspection and monitoring procedures should be revised to better assess welfare factors and correlate management practices with the occurrence of osteomyelitis in pig carcasses. Full article