Post-slaughter traceability

Comparison of beef traceability in serial and parallel fabrication systems using RFID and two-dimensional barcodes

Traceability of beef attributes from small- and mid-sized farms through supply chains is a market barrier. The objective of this trial was to determine the influence of fabrication method on beef traceability system requirements. Individual identities of 54 animals were maintained through harvest, processing, packaging, and distribution. At harvest, each animal’s unique radio frequency identification (RFID) animal identification number was transferred to a harvest label on each carcass quarter. Following transportation to a processor, nine carcasses were processed on alternating days by one of the two methods. Carcasses were fabricated, using a serial fabrication method (SFM), into wholesale cuts one at a time or fabricated using a parallel fabrication method (PFM), by processing multiple hindquarters or forequarters simultaneously into wholesale cuts. In-process labels were generated by scanning the two-dimensional (2D) barcode on the harvest label with a handheld mobile computer and printed from a wireless mobile printer. Tracking of SFM and PFM carcass quarters was accomplished by creating in-process labels for lugs and individual wholesale cuts, respectively. The process was recorded and the data was captured from video analysis. The mean number of in-process labels generated per carcass for SFM was 3.7 and for PFM was 30.9 (P < 0.01). The amount of time required for generating in-process labels for SFM (2 min 16 s) was less than PFM (8 min 45 s) (P = 0.01). The amount of time required to label each carcass was less (P < 0.01) for SFM (18 s) than for PFM (3 min 10 s) with in-process labels. Total cost of traceability, including fixed and consumable cost per carcass, was nearly twice as much for PFM ($17.98) than SFM ($9.02). Traceability, within both processing methods, was found to have 100% fidelity, as verified using DNA marker genotyping. Overall, the number of labels generated for traceability was less for SFM than that for PFM. The overall time spent on generating, applying, and removing labels was less for SFM than that for PFM. The total cost of traceability was approximately half for SFM compared with that for PFM; however both methods were able to track product accurately. Tracking of beef from individual animals, using RFID ear tags and 2D barcodes, appears to be feasible for the fabrication methods used in this study.

Application of LogitBoost Classifier for Traceability Using SNP Chip Data

Consumer attention to food safety has increased rapidly due to animal-related diseases; therefore, it is important to identify their places of origin (POO) for safety purposes. However, only a few studies have addressed this issue and focused on machine learning-based approaches. In the present study, classification analyses were performed using a customized SNP chip for POO prediction. To accomplish this, 4,122 pigs originating from 104 farms were genotyped using the SNP chip. Several factors were considered to establish the best prediction model based on these data. We also assessed the applicability of the suggested model using a kinship coefficient-filtering approach. Our results showed that the LogitBoost-based prediction model outperformed other classifiers in terms of classification performance under most conditions. Specifically, a greater level of accuracy was observed when a higher kinship-based cutoff was employed. These results demonstrated the applicability of a machine learning-based approach using SNP chip data for practical traceability.

Whole-chain traceability, is it possible to trace your hamburger to a particular steer, a U. S. perspective

Traceability through the entire food supply chain from conception to consumption is a pressing need for the food industry, consumers and government regulators. A robust, whole-chain traceability system is needed that will effectively address food quality, food safety and food defense issues by providing real-time, transparent and reliable information from beef production through slaughter and distribution to the consumer. Traceability is an expanding part of the food safety continuum that minimizes the risk of foodborne diseases, assures quality and cold-chain integrity. Traceability can be a positive competitive marketing edge for beef producers who can verify specific quality attributes such as humane production or grass fed or Certified Organic. In this review we address the benefits as well as the remaining issues for whole-chain traceability in the beef industry, with particular focus on ground beef for the markets in the United States.

Radio frequency identification technologies for livestock management and meat supply chain traceability

Barge, P., Gay, P., Merlino, V. and Tortia, C. 2013. Radio frequency identification technologies for livestock management and meat supply chain traceability. Can. J. Anim. Sci. 93: 23–33. Animal electronic identification could be exploited by farmers as an interesting opportunity to increase the efficiency of herd management and traceability. Although radio frequency identification (RFID) solutions for animal identification have already been envisaged, the integration of a RFID traceability system at farm level has to be carried out carefully, considering different aspects (farm type, number and species of animals, barn structure). The tag persistence on the animal after application, the tag-to-tag collisions in the case of many animals contemporarily present in the reading area of the same antenna and the barn layout play determinant roles in system reliability. The goal of this paper is to evaluate the RFID identification system performance and determine the best practice to apply these devices in livestock management. RFID systems were tested both in laboratory, on the farm and in slaughterhouses for the implementation of a traceability system with automatic animal data capture. For this purpose a complete system for animal identification and tracking, accomplishing regulatory compliance as well as supply chain management requirements, has been developed and is described in the paper. Results were encouraging for identification of calves both in farms and slaughterhouses, while in swine breeding, identification was critical for small piglets. In this case, the design of a RFID gate where tag-to-tag collisions are avoided should be envisaged.