New research shows X-ray technology may offer beef processors the clearest path to finding hidden metallic contaminants before they reach consumers.
Research: Evaluation of Foreign Metal Material Detection Methods for Hide-on and Hide-off Beef Cattle. Image Credit: BearFotos / Shutterstock
In a recent study published in the Journal of Food Protection, researchers evaluated the detection efficacy of three primary technologies, X-ray, traditional metal detection, and ultrasound, in identifying ten different metallic objects embedded at various depths and muscle tissue states in beef tissue.
Study findings revealed that while X-ray technology achieved a perfect detection probability (p̂ = 1.000) across all variables, metal detection and ultrasound performance were significantly hindered by object size and depth. These findings suggest that X-ray imaging is currently the only tested method that reliably detects embedded metallic objects across all tested depths, tissue states, and object types.
Beef Foreign Metal Detection Background
The United States Department of Agriculture Food Safety Inspection Service (USDA-FSIS) defines “foreign material” as any non-animal object found within the target sample, including metal, glass, or lead shot. Historically, these contaminants have posed a substantial risk, with reports from 2017 indicating that these contaminants accounted for 45.4% of the 853 total complaints filed with the FSIS Consumer Complaint Monitoring System (CCMS).
Furthermore, these reports revealed that metal was the second most common contaminant (15.5%) and that beef was the most frequently implicated commodity, accounting for 28.2% of all foreign material cases. The 2022 National Beef Quality Audit (NBQA) further underscored this issue, revealing that 100% of surveyed cull cow and bull beef processors reported encountering buckshot or birdshot within a one-year period.
Scientists believe that these contaminants often enter the supply chain "upstream" through animal handling or medical treatments beyond the processor's immediate control, underscoring the urgent need to validate the physical and operational constraints of current screening technologies.
X-Ray, Metal Detection, and Ultrasound Design
The present study aimed to address these knowledge limitations and inform present and future foreign material screening by using beef cattle to evaluate detection outcomes across 270 detection trials/combinations, reflecting replication across technology (specifically X-ray, electromagnetic [traditional] metal detection, and ultrasound), tissue depth (n = 3), and muscle state, prerigor hide-on (to simulate a live animal), prerigor hide-off, and postrigor hide-off (chilled for 24 hours to simulate a processed carcass).
The ‘foreign metal objects’ dataset comprised ten metal objects commonly found in beef processing. These objects were selected for their variation in density and size, and included:
• Medical & Industrial: A 16 G x 1.5 in (16-gauge, 1.5-inch) aluminum needle, an aluminum dart, and steel wire (~2.5 in length).
• Ballistics: A 1 oz (one-ounce) lead rifled slug, 8.40 mm "double 00" buckshot, 3.56 mm copper-plated three shot, 4.5 mm stainless steel BBs, a copper-plated .223 bullet, 4.57 mm steel BBs, and 2.54 mm lead seven shot.
Each object was placed beneath muscle samples at standardized depths: shallow (20–30 mm), intermediate (40–50 mm), and deep (70–80 mm). Finally, the study data were analyzed using logistic regression via the GLIMMIX procedure in SAS 9.4, with a logit link to estimate predicted probabilities of detection (p̂).
Embedded Metal Detection Findings
Statistical analysis revealed a significant four-way interaction (p < 0.001) among the detection method, muscle state, depth, and metal item type. Most importantly, the results revealed that the X-ray technology demonstrated the highest analytical robustness, maintaining a 100% detection rate (p̂ = 1.000) regardless of muscle depth or the presence of the hide.
Performance evaluations found that X-rays’ sensitivity to density contrast enabled them to identify even thin, low-density metallic objects, such as aluminum needles and steel wire, which are traditionally difficult to visualize.
In contrast, the efficacy of metal detection was highly dependent on object mass and proximity to the coil. While traditional metal detection successfully detected large items like the lead slug and .223 bullet at shallow depths, its overall probability dropped to p̂ = 0.311 at 40–50 mm and p̂ = 0.237 at 70–80 mm. Alarmingly, the smallest item, the lead seven shot (2.54 mm), was never detected under any condition.
Finally, ultrasound exhibited the poorest overall utility (p̂ = 0.344). While detection reached p̂ = 0.556 at shallow depths, it decreased to 0.167 at the deepest level (70–80 mm).
The data suggest that ultrasound detection was lowest in postrigor samples (p̂ = 0.185) and was generally limited by tissue heterogeneity, depth, object size, and operator-dependent imaging constraints. Ultrasound failed to detect thin objects, such as needles and wires, in nearly all tested scenarios.
Beef Processing Safety Implications
The present study confirms that X-ray technology was the most reliable of the three tested methods for identifying embedded metallic contaminants, particularly those located deep within the carcass. The results indicate that while traditional metal detectors are widely used due to their cost-effectiveness, they should not be relied upon as a stand-alone control point for small or deeply embedded materials.
The authors noted that detection performance may vary across commercial systems due to differences in configuration, power, resolution, coil design, probe frequency, coupling conditions, and operator expertise. These findings advocate a "hurdle-based” approach to food safety, integrating multiple detection layers to protect consumers from the range of foreign metallic materials encountered in the beef industry.
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