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  • FOOD CRIME STRATEGIC ASSESSMENT

  • Weinstein Wholesale Meats, Inc. Recalls Raw Ground Beef Burger Products Due to Possible Foreign Matter Contamination

    On April 20, 2023, Weinstein Wholesale Meats, Inc., based in Forest Park, Illinois, announced a recall of approximately 2,122 pounds of raw ground beef burger products due to potential contamination with extraneous materials, specifically pieces of white neoprene, according to the U.S. Department of Agriculture’s Food Safety and Inspection Service (FSIS).

    The affected raw ground beef burger patties were produced on March 14, 2023, and the specific product subject to recall is 10.7-ounce vacuum-sealed packages containing two pieces of “100% Grass Fed & Finished Beef Burger Patties 85% Lean/15% Fat” with “Use/Freeze By 4/11/23” on the package label. These products bear establishment number “Est. 6987” inside the USDA mark of inspection and were distributed to an online distributor, which sold them to customers nationwide.

    The recall was initiated after the establishment received multiple consumer complaints reporting the presence of white “rubber-like” material in the ground beef patty products during preparation. While there have been no confirmed reports of adverse reactions due to consumption of these products, FSIS advises anyone concerned about an injury or illness to contact a healthcare provider immediately.

    Consumers who have purchased these products are advised not to consume them and to either throw them away or return them to the place of purchase. FSIS routinely conducts recall effectiveness checks to ensure that recalling firms notify their customers of the recall and that steps are taken to ensure the product is no longer available to consumers. The retail distribution list(s) will be posted on the FSIS website at www.fsis.usda.gov/recalls when available.

    Consumers with questions about the recall can contact Nicole Schumacher, Chief Marketing Officer, Pre Brands LLC, at 844-773-3663 or reachus@eatpre.com. Members of the media with questions can contact Paul Esposito, Chief Operating Officer, Weinstein Wholesale Meats Inc., at 630-390-9138 or media@weinsteinmeats.com.

    Consumers with food safety questions can call the toll-free USDA Meat and Poultry Hotline at 888-MPHotline (888-674-6854) or live chat via Ask USDA from 10 a.m. to 6 p.m. (Eastern Time) Monday through Friday. Consumers can also browse food safety messages at Ask USDA or send a question via email to MPHotline@usda.gov. To report a problem with a meat, poultry, or egg product, the online Electronic Consumer Complaint Monitoring System is available 24/7 at

    https://foodcomplaint.fsis.usda.gov/eCCF/.

    Hyperspectral Food Foreign Matter Detection Systems bioClass®

    bioClass® Protein Hyperspectral Inspection System
    bioClass® Protein Hyperspectral Inspection System

    The use of bioClass® hyperspectral machine vision solutions from Automate and Control LTD in food processing facilities can help detect foreign materials, such as plastic or rubber, in products before they reach consumers. These systems use advanced imaging technology to scan products as they move along a conveyor belt and analyze their spectral signatures to identify any anomalies.

    In the case of Weinstein Wholesale Meats, Inc.’s recall of raw ground beef burger products, an automated bioClass® hyperspectral machine vision solution could have detected the white neoprene pieces before the products were packaged and shipped. The system could have been programmed to identify any foreign materials that did not match the spectral signature of the ground beef and trigger an alert for inspection or removal.

    Moreover, automated hyperspectral machine vision solutions can operate continuously and in real-time, making them highly efficient at detecting any potential contamination issues that could occur during processing. This level of automation and control provides a high degree of accuracy, reliability, and consistency, ensuring that all products meet strict quality and safety standards.

    In conclusion, the use of hyperspectral machine vision solutions in food processing facilities can help prevent recalls like the one from Weinstein Wholesale Meats, Inc. by detecting foreign materials and ensuring that products meet strict quality and safety standards. By automating and controlling the inspection process, these solutions can improve efficiency, reduce costs, and ultimately, protect consumers’ health and safety.

  • Ground Cumin recalled in the USA after testing finds Salmonella

    Lipari Foods is recalling many Lipari Branded Ground Cumin Tubs manufactured by International Food because of potential Salmonella contamination.

    More information from FDA HERE

    Lipari Foods is issuing a recall for multiple Lipari Branded Ground Cumin Tubs that were produced by International Food due to a possible contamination of Salmonella. The recall was initiated after the United States Food and Drug Administration and The Michigan Department of Agriculture and Rural Development (MDARD) notified the company about a sample of the Ground Cumin that was collected by the Florida Department of Agriculture and Consumer Services and tested positive for Salmonella.

    Recalled products:

    BrandProductSizeLot CodeBest By DateUPC
    LIPARIGROUND CUMIN6 OZ. TUB22091460109/2024094776212620

    As of the posting of this recall, there are no reported illnesses in connection with this product.

    Consumers who have purchased this recalled product should not consume it. They should return it to the point of purchase.

    Ground cumin is a commonly used spice in many cuisines around the world. It is added to various dishes, such as soups, stews, sauces, and marinades, to enhance their flavor and aroma. However, in recent years, ground cumin has been linked to several cases of salmonella infection, a type of foodborne illness caused by the bacterium Salmonella.

    Salmonella is a common cause of food poisoning, affecting millions of people worldwide every year. It is typically found in raw or undercooked meat, poultry, eggs, and dairy products, but it can also contaminate other foods, including spices like ground cumin. Salmonella infection can cause a range of symptoms, such as fever, diarrhea, nausea, vomiting, and abdominal pain. In severe cases, it can lead to dehydration, hospitalization, and even death, particularly in vulnerable populations, such as children, elderly, and immunocompromised individuals.

    The detection of salmonella in ground cumin is critical to prevent its spread and minimize the risk of foodborne illness. Various methods are used to detect salmonella in food, including culture-based methods, rapid methods, and molecular methods. Culture-based methods involve the isolation and identification of salmonella bacteria from food samples using selective and differential media. These methods are time-consuming and labor-intensive but provide a definitive answer about the presence or absence of salmonella.

    Culture of Salmonella bacteria illustration

    Rapid methods, such as immunological assays and polymerase chain reaction (PCR) assays, use antibodies or nucleic acid probes to detect salmonella in food samples. These methods are faster and easier to perform than culture-based methods and can provide results in hours or minutes. However, they are less sensitive and specific than culture-based methods and may yield false-positive or false-negative results.

    Molecular methods, such as whole-genome sequencing (WGS), are the most advanced and accurate methods for salmonella detection. WGS analyzes the entire genetic material of salmonella bacteria and can identify their unique DNA fingerprints. This method can detect even low levels of salmonella in food samples and can distinguish between different strains and serotypes of salmonella. WGS is also useful for tracking the source and transmission of salmonella outbreaks and for developing targeted interventions to prevent their recurrence.

    In conclusion, the detection of salmonella in ground cumin is crucial for ensuring food safety and preventing salmonella infection. Various methods are available for salmonella detection, including culture-based methods, rapid methods, and molecular methods. Each method has its advantages and limitations, and the choice of the method depends on the specific needs and constraints of the food industry and regulatory agencies. WGS is the most advanced and accurate method for salmonella detection and is likely to become the standard method in the future.

    Salmonella can contaminate ground cumin at various stages of the supply chain, from the farm to the processing plant to the distribution center to the retail store. The most common sources of salmonella in ground cumin are contaminated water, soil, and animal feces that come into contact with the spice during cultivation, harvesting, or processing. Salmonella can also be introduced into ground cumin by infected workers, contaminated equipment, or inadequate sanitation practices in the processing and packaging facilities.

    To prevent salmonella contamination in ground cumin and other spices, food producers and processors should implement good agricultural practices (GAPs) and good manufacturing practices (GMPs) that include hygiene, sanitation, and food safety protocols. These measures should include testing for salmonella and other pathogens, maintaining clean and sanitized facilities and equipment, training workers in food safety practices, and implementing quality control procedures to ensure the safety and quality of the final product.

    Consumers can also take steps to prevent salmonella infection from ground cumin by storing the spice in a cool, dry place, using it within its expiration date, and cooking it to recommended temperatures. Consumers should also be aware of food recalls and follow the instructions provided by the manufacturers and regulatory agencies.

    Hyperspectral imaging has the potential to detect salmonella in ground cumin. Hyperspectral imaging is a non-destructive technique that uses light to create a detailed image of an object’s spectral characteristics. By analyzing the spectral signature of an object, hyperspectral imaging can detect differences in the chemical composition of the object, including the presence of pathogens like salmonella.

    Several studies have explored the use of hyperspectral imaging to detect salmonella in various food products, including spices like black pepper and cumin. These studies have shown promising results in detecting salmonella in spices using hyperspectral imaging, with high accuracy and sensitivity. Hyperspectral imaging can also detect other contaminants in spices, such as insect fragments and mold.

    The use of hyperspectral imaging for salmonella detection in ground cumin would require the development of a spectral library of salmonella and non-salmonella samples. This library could be used to identify spectral differences between contaminated and non-contaminated samples of ground cumin. However, the cost and technical expertise required for hyperspectral imaging may limit its use in routine testing for salmonella in ground cumin and other food products until now. Automate and Control LTD’s bioClass® system Online High Speed Non-destructive Real Time Chemical Analysis can be deployed to automatically check 100% of inbound produce.

    Hyperspectral Food Inspection – Online High Speed Non-destructive Real Time Chemical Analysis bioClass®

    bioClass® Protein Hyperspectral Inspection System
    bioClass® Protein Hyperspectral Inspection System

    Overall, hyperspectral imaging has the potential to be an effective tool for detecting salmonella in ground cumin, but more research is needed to optimize and validate its use in food safety applications.

  • Tyson Foods Ground Beef Recall: How bioClass® Next Generation Automated Food Inspection Systems Could Have Prevented this.

    bioClass® Protein Hyperspectral Inspection System
    bioClass® Protein Hyperspectral Inspection System

    Tyson Foods recently issued a recall for over 94,000 pounds of ground beef products due to concerns about possible E. coli contamination. This recall has once again highlighted the importance of food safety and the potential risks associated with food-borne illness.

    The recall includes several different brands of ground beef sold under different names, and the affected products were shipped to stores in multiple states across the US. This has led to significant concerns among consumers about the safety of ground beef products and has also impacted the reputation of Tyson Foods.

    Food safety is a critical issue for any food manufacturer, and it is essential to take proactive measures to prevent contamination incidents. One of the best ways to prevent contamination is through the use of automated food inspection systems.

    The bioClass® Hyperspectral Food Inspection System is an advanced imaging technology that can quickly and accurately detect contaminants in food products, including E. coli and other harmful bacteria. The system uses hyperspectral imaging, machine learning algorithms, and artificial intelligence to analyze food products in real-time and identify any potential contaminants.

    Using an automated food inspection system like the bioClass® can help prevent contamination incidents before they occur, which can save manufacturers like Tyson Foods millions of dollars in recall costs and legal liabilities. In addition, it can help protect consumers from potentially harmful food-borne illnesses.

    By using the bioClass® system, food manufacturers can also improve the overall quality of their products by detecting other quality issues like discoloration or improper packaging. This can help improve customer satisfaction and prevent negative reviews or reputation damage.

    In conclusion, the recent Tyson Foods ground beef recall underscores the importance of food safety, and the need for manufacturers to take proactive measures to prevent contamination incidents. Automated food inspection systems like the bioClass® Hyperspectral Food Inspection System can help prevent contamination by quickly and accurately detecting potential contaminants in food products. Implementing these systems can improve the safety and quality of food products and protect both consumers and manufacturers from the potential risks associated with food-borne illness.

    Detection of E.Coli with bioClass® Systems HERE

    News Articles HERE

    Food Fraud Links and Solutions HERE

  • Tyson Foods Recall Leads to Damage to Company Reputation

    Tyson Foods Recalls 8.5 Million Pounds of Frozen Chicken

    Tyson Foods Recall Leads to Damage to Company Reputation and Increased Costs

    Tyson Foods recently had to recall several million pounds of frozen, fully cooked chicken products due to the presence of plastic pieces in the food. This recall has had a significant impact on the company’s reputation and brand image. Consumers are now concerned about the quality of Tyson Foods products, and the recall has cost the company significantly in terms of lost sales and potential legal liabilities.

    Tyson Foods CEO, has taken steps to address the problem and prevent future incidents, but it may take some time for the company to fully recover from the damage caused by the recall.

    To prevent future incidents like this, food inspection systems like the bioClass® Hyperspectral Food Inspection System could be used. This automated system uses advanced imaging technology to identify contaminants in food products, including plastic, metal, and other foreign materials.

    The bioClass® system uses a combination of hyperspectral imaging, machine learning algorithms, and artificial intelligence to quickly and accurately detect and classify contaminants in food products. The system can improve the accuracy and speed of detection, which reduces the risk of contamination and increases consumer confidence in food products.

    The bioClass® system has also been found to be effective in detecting the “woody breast” condition that can impact poultry and lead to chewy meat. Early detection of this condition can help prevent affected products from reaching consumers and reduce the risk of customer complaints and recalls.

    In conclusion, the Tyson Foods recall underscores the importance of food safety, and it is important for companies to take proactive measures to prevent contamination incidents. Automated food inspection systems like the bioClass® Hyperspectral Food Inspection System offer a promising solution to this problem by providing a fast, accurate, and reliable way to detect and prevent contaminants in food products.

    More information HERE

  • Game Changing Hyperspectral Food Grading Sorting System from Startup Automate and Control LTD. bioClass®

    Automate and Control’s hyperspectral automatic food sorting machine is an impressive technological advancement in the food industry. This machine uses hyperspectral imaging technology to sort food products based on their unique chemical signatures, which allows for highly accurate and efficient sorting. Compared to competitors , Automate and Control’s machine offers a more advanced and precise sorting system. Additionally, the company’s dedication to continuous improvement and innovation suggests that their machine will only continue to improve and exceed expectations in the future. Overall, Automate and Control’s hyperspectral automatic food sorting machine is a game-changer for the food industry, offering unparalleled accuracy and efficiency in food sorting.

    Hyperspectral Food Grading Sorting from bioClass®

    Automate and Control LTD’s hyperspectral automatic food sorting machine offers several unique advantages over its competitors. One of the key differentiators is the company’s use of machine learning tools, which when coupled with hyperspectral imaging, allows for even more precise and accurate sorting. By leveraging machine learning algorithms, the machine can quickly and efficiently process vast amounts of data and improve its sorting capabilities over time.

    Furthermore, Automate and Control LTD’s use of an artificial intelligence edge computing platform is another game-changer. This platform allows the machine to perform real-time analysis of the data it collects, enabling faster decision-making and greater efficiency. This approach also minimizes the need for centralized processing, reducing latency and improving overall performance.

    In contrast, competitors technologies rely on more traditional sorting methods, such as optical sorting and metal detection. While these approaches are effective, they lack the precision and accuracy that can be achieved through hyperspectral imaging and machine learning.

    Overall, Automate and Control LTD’s use of cutting-edge technology and innovative approaches to sorting make them a major player in the food industry. By combining hyperspectral imaging, machine learning, and an AI edge computing platform, they are able to offer unparalleled sorting capabilities and set a new standard for the industry.

    bioClass® Poultry Grading Solutions HERE

    bioClass® Date and Fruit Grading Sorting Solutions HERE

    bioClass® Food Fraud Detection HERE

    bioClass® Nuts Grading Sorting and Toxin Detection HERE

    Other bioClass® Applications HERE

  • What is Histamine and why integrate bioClass® into your production lines for 100% inspection

    What is Histamine

    Histamine is a naturally occurring compound found in many foods, including fish. It is formed by the bacterial breakdown of the amino acid histidine in fish muscle tissue, which occurs during post-harvest handling, processing, and storage.

    When fish are not stored properly or handled inappropriately, the bacteria in their tissues can produce high levels of histamine, leading to scombroid poisoning. Scombroid poisoning is a foodborne illness caused by ingesting fish with high levels of histamine. Symptoms of scombroid poisoning include flushing, headache, dizziness, rapid or irregular heartbeat, sweating, nausea, vomiting, abdominal cramps, and diarrhea. In severe cases, scombroid poisoning can lead to anaphylactic shock.

    The consumption of fish containing high levels of histamine can be particularly dangerous for individuals with histamine intolerance, as they are unable to properly metabolize the histamine in their bodies, leading to an allergic reaction.

    Research has shown that certain types of fish are more prone to high histamine levels than others. For example, fish such as tuna, mackerel, mahi-mahi, anchovy, and herring are known to be high-risk species for scombroid poisoning. On the other hand, fish such as salmon and cod are less likely to contain high levels of histamine.

    To prevent scombroid poisoning, it is important to handle and store fish properly. This includes keeping fish at a temperature below 40°F (4°C) and avoiding leaving fish at room temperature for an extended period. Additionally, it is recommended to buy fish from reputable suppliers who follow proper storage and handling procedures.

    There have been several documented cases of scombroid poisoning around the world. In 2017, a total of 30 cases of scombroid poisoning were reported in Spain after consuming tuna from a single fish supplier. In 2019, 12 people in Singapore were hospitalized after consuming fish with high histamine levels.

    More information on Scombroid Poisoning visit https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/ScombroidFish%20Poisoning.aspx

    How to protect consumers from high levels of Histamine

    High levels of histamine in fish are typically defined as concentrations above 50 mg/kg. These levels can occur in certain fish species if they are not stored and handled properly after they are caught. When fish are caught, their natural defenses against bacterial spoilage are lost, and bacteria in the fish’s tissue can begin to break down the amino acid histidine into histamine. The longer the fish is stored at temperatures between 40-140°F (4-60°C), the more histamine is produced. This process can be accelerated by poor handling practices, such as leaving the fish exposed to warm temperatures or not properly gutting and cleaning the fish.

    To detect high levels of histamine in fish, several analytical methods are available, including high-performance liquid chromatography (HPLC), gas chromatography (GC), and enzyme-linked immunosorbent assay (ELISA). These methods involve extracting the histamine from the fish tissue, separating it from other compounds, and measuring the amount of histamine present.

    HPLC is the most commonly used method for histamine detection in fish. It involves injecting a sample of the fish extract into a liquid chromatography system, where the histamine is separated from other compounds using a stationary phase column. The histamine is then detected using a UV-visible light detector, and the amount of histamine present is quantified based on the peak area or height of the chromatogram.

    GC is another method used to detect histamine in fish. It involves converting the histamine to a volatile derivative using a chemical reaction, and then separating and detecting the derivative using gas chromatography.

    ELISA is a rapid and relatively inexpensive method for detecting histamine in fish. It involves binding a specific antibody to histamine and then measuring the amount of antibody-histamine complex present using a colorimetric or fluorescent detection system. While ELISA is not as accurate or precise as HPLC or GC, it can be useful for screening large numbers of samples quickly and cost-effectively.

    In addition to these analytical methods, several rapid tests have been developed that allow fish sellers and consumers to test fish for histamine on-site. These tests involve immersing a small piece of the fish in a test solution and then observing a color change or other visual signal that indicates the presence of histamine.

    Overall, the detection of high levels of histamine in fish is important for protecting public health and preventing foodborne illness. Analytical methods such as HPLC, GC, and ELISA are highly sensitive and accurate, and can help ensure that fish are safe for consumption. Rapid on-site tests also provide a useful tool for fish sellers and consumers to quickly and easily check the histamine levels in fish before buying or consuming them.

    bioClass® Protein Hyperspectral Inspection System
    bioClass® Protein Hyperspectral Inspection System https://www.automateandcontrol.com/woody-breast-inspection-poultry/

    Next Generation 100% Inspection bioClass®

    Hyperspectral imaging is an advanced technology that uses a combination of imaging and spectroscopy to provide detailed information about the chemical composition of a sample. It works by capturing images of a sample at multiple wavelengths, which allows for the identification and quantification of specific compounds based on their unique spectral signature.

    Hyperspectral imaging has shown promise as a potential solution for the inspection and detection of histamine in fish. This technology has the ability to rapidly and non-destructively scan large amounts of fish at once, providing a more efficient and cost-effective alternative to traditional methods like HPLC and GC.

    One study conducted by researchers at the University of Massachusetts Amherst used hyperspectral imaging to detect and quantify histamine in tuna fish samples. The researchers found that hyperspectral imaging was able to accurately predict the histamine concentration in the samples with a high degree of accuracy, and was able to differentiate between high and low histamine levels.

    Another study conducted by researchers at the Korea Food Research Institute used hyperspectral imaging to detect scombroid fish poisoning caused by high histamine levels in mackerel samples. The researchers found that hyperspectral imaging was able to detect histamine levels in the samples with a high degree of accuracy, and was able to differentiate between fresh and spoiled samples.

    Overall, hyperspectral imaging has shown great potential as a fast, non-destructive, and accurate method for detecting and quantifying histamine levels in fish. While this technology is still relatively new and expensive, it has the potential to revolutionize the way we inspect and monitor the safety of our food supply. As research in this area continues, it is likely that hyperspectral imaging will become an increasingly important tool for ensuring the safety and quality of our food.

    For more information contact Automate and Control LTD HERE

  • Hyperspectral Machine Vision, what is it?

    Hyperspectral imaging (HSI) is a highly precise and non-intrusive method that captures high-resolution spectral images from objects. By capturing a series of images, each containing data from a narrow spectral band, the HSI sensor creates a hyperspectral cube, where each pixel in the image contains a complete spectrum. This technique allows for the identification of materials based on their distinct spectral signature. Above is the MV.X system we can integrate into your current production lines. for more information on it’s capability see MV.X

    HSI sensors operate by dividing incoming light into several narrow spectral bands, ranging from ultraviolet to near-infrared regions of the electromagnetic spectrum. The sensor measures the intensity of light at each wavelength, and the data is processed using various algorithms to produce a spectral signature of the object being imaged.

    In the food industry, HSI has several applications, such as quality control, food safety, and inspection. HSI detects foreign materials like stones, plastics, and glass in food products, defects in fruits and vegetables, such as decay, mold, and bruising. It can also detect the ripeness and freshness of fruits and vegetables and identify different varieties of fruits and vegetables.

    One study published in Food Control explored the use of HSI for detecting aflatoxins in peanuts, toxic and carcinogenic compounds produced by certain fungi that can contaminate crops like peanuts, cottonseed, and corn. HSI identified the spectral signature of the contamination, which enabled accurate detection and quantification of aflatoxin. This study proves the potential of HSI as a food contamination detection tool.

    Another study published in Food Analytical Methods investigated the detection of E. coli bacteria in ground beef through HSI. The researchers used HSI to identify the spectral signature of E. coli in ground beef and successfully detected its presence with high accuracy. This study showcases the potential of HSI for food safety in the meat industry.

    In conclusion, hyperspectral imaging sensors provide a non-intrusive and non-destructive way of identifying materials based on their spectral signature. In the food industry, HSI has many applications, and ongoing scientific research continues to explore its potential in areas such as food safety, quality control, and inspection.

    For more information on why implement hyperspectral imagery please follow this link. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=bc5a6e243b6ffcd79e1892974f02699194b01426

  • Detection of E. coli – Escherichia coli O157:H7 in Ground Beef Using Hyperspectral Imaging

    Hyperspectral imaging (HSI) is a non-destructive, non-invasive technique that enables the acquisition of high-resolution spectral images from an object. The hyperspectral imaging sensor captures a series of images, each containing data from a narrow spectral band. The resulting image set is called a hyperspectral cube, where each pixel in the image contains a complete spectrum. The hyperspectral cube can be used to identify materials based on their unique spectral signature.

    HSI sensors work by splitting the incoming light into several narrow spectral bands, typically ranging from the ultraviolet to the near-infrared regions of the electromagnetic spectrum. Each band corresponds to a specific wavelength of light, and the intensity of light at each wavelength is measured by the sensor. The resulting data is then processed using various algorithms to produce a spectral signature of the object being imaged.

    HSI has various applications in the food industry, including quality control, food safety, and inspection. For example, HSI can be used to detect foreign materials such as stones, plastics, and glass in food products. HSI can also be used to detect defects in fruits and vegetables, such as bruising, decay, and mold. Additionally, HSI can be used to determine the ripeness and freshness of fruits and vegetables, as well as to identify different varieties of fruits and vegetables.

    One scientific study published in the journal Food Control investigated the use of HSI for the detection of aflatoxins in peanuts. Aflatoxins are toxic and carcinogenic compounds produced by certain fungi that can contaminate crops such as peanuts, corn, and cottonseed. The researchers used HSI to identify the spectral signature of the aflatoxin contamination in peanuts and were able to detect and quantify the contamination accurately. This study demonstrates the potential of HSI as a tool for the detection of food contaminants.

    Another study published in the journal Food Analytical Methods investigated the use of HSI for the detection of E. coli bacteria in ground beef. The researchers used HSI to identify the spectral signature of E. coli in ground beef and were able to detect the presence of the bacteria with high accuracy. This study demonstrates the potential of HSI as a tool for food safety in the meat industry.

    Overall, hyperspectral imaging sensors provide a non-destructive and non-invasive technique for identifying materials based on their unique spectral signature. In the food industry, HSI has various applications for quality control, food safety, and inspection, and scientific research continues to explore the potential of HSI in these areas.

    One study that investigated the use of hyperspectral imaging for the detection of E. coli bacteria in ground beef is “Hyperspectral Imaging for Detection of E. coli O157:H7 on Beef Surface Using Various Regression Methods” by Liu et al. This study was published in the journal Food Analytical Methods in 2017.

    In the study, the researchers used hyperspectral imaging to identify the spectral signature of E. coli O157:H7 on the surface of ground beef samples. They then developed several regression models to analyze the hyperspectral data and detect the presence of the bacteria.

    The results showed that the best performing regression model was a support vector machine (SVM) model, which achieved an accuracy of 92.8% for detecting E. coli O157:H7 on the surface of ground beef. The study demonstrated the potential of hyperspectral imaging as a tool for food safety in the meat industry.

    Automate and Control LTD’s bioClass® system can be trained to detect many toxins and pathogens online in food factories.

    Raw burgers with ground beef, oil, buns and tomatoes. On dark rustic background

    Here are a few more studies on the use of hyperspectral imaging for the detection of E. coli in ground beef:

    1. “Detection of Escherichia coli O157:H7 in Ground Beef Using Hyperspectral Imaging and Machine Learning Techniques” by Xu et al. This study was published in the journal Food Control in 2021. The researchers used hyperspectral imaging to identify the spectral signature of E. coli O157:H7 in ground beef and developed a machine learning algorithm to detect the bacteria. The results showed that the algorithm had an accuracy of 98.2% for detecting E. coli O157:H7 in the ground beef samples.
    2. “Hyperspectral Imaging for Detection of E. coli O157:H7 Contamination on Beef Surface Using Principal Component Analysis and Artificial Neural Network” by Park et al. This study was published in the journal Sensors in 2019. The researchers used hyperspectral imaging to detect E. coli O157:H7 on the surface of beef samples and developed a model based on principal component analysis and artificial neural networks to analyze the hyperspectral data. The results showed that the model had an accuracy of 99.3% for detecting E. coli O157:H7 on the beef surface.
    3. “Detection of Escherichia coli in Ground Beef Using Hyperspectral Imaging” by Lu et al. This study was published in the journal Applied Spectroscopy in 2014. The researchers used hyperspectral imaging to identify the spectral signature of E. coli in ground beef and developed a model based on partial least squares regression to detect the bacteria. The results showed that the model had an accuracy of 95.3% for detecting E. coli in the ground beef samples.

  • Automate and Control LTD a world leader in food grading and sorting systems.

    At Automate and Control LTD, we take pride in being a world leader in food grading and sorting systems. Our advanced hyperspectral imaging technology is superior to many other food sorting machines on the market, and we offer a range of applications that set us apart from our competitors.

    One of the main advantages of our hyperspectral food sorting systems is that they use real-time detection and identification to ensure that only high-quality products are sorted and distributed to the market. This is particularly useful for detecting defects in food products, such as bruises, rot, discoloration, and foreign objects.

    Our hyperspectral food sorting systems can be used for a wide variety of applications, including fruit and vegetable grading, seafood grading, meat and poultry grading, and nut and seed sorting. For example, our systems can detect bone fragments, bruises, and discoloration in meat and poultry products, ensuring that only high-quality products are distributed to the market.

    In addition to these applications, our hyperspectral food sorting systems offer several other benefits that set us apart from our competitors. For example, we offer a high degree of accuracy in defect detection, as well as customization to meet the specific needs of our customers. Our systems are also highly efficient, with a high throughput and low false reject rate, ensuring that they can handle large volumes of products quickly and accurately.

    At Automate and Control LTD, we are committed to providing the best possible service to our customers, and our hyperspectral food sorting systems are a testament to this commitment. With their advanced technology, high accuracy, and customizable features, our systems are the ideal choice for any food grading and sorting application. Contact us today to learn more about our products and services.