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Chicken ‘Woody Breast’ Detection Improved with Advanced Machine Learning Model

The AHA! Team — Wed, 30 Apr 2025 05:13:35 +0000

University of Arkansas System Division of Agriculture via EurekAlert! – Accuracy improved to 95 percent with hyperspectral imaging It’s called “woody breast” and for consumers it can mean a chewier chicken sandwich, but for the industry it can mean up to $200 million annual yield loss. Work done by the Arkansas Agricultural Experiment Station is not only making woody breast easier to detect in chicken meat but is accurate up to 95 percent of the time. Hyperspectral camera and machine learning The development could help improve quality assurance and customer confidence in one of the state’s most economically important agricultural products. What allows researchers to see inside the meat is a combination of a hyperspectral camera, which examines the meat through various energy wavelengths, and machine learning to interpret what the camera sees. “We’ve been able to improve accuracy of detection of woody breast by utilizing machine learning to analyze complex data from images with a hyperspectral camera,” said Dongyi Wang, an assistant professor in the biological and agricultural engineering department for the experiment station, the research arm of the University of Arkansas System Division of Agriculture. “The next step will be trying to integrate the system online and make this beneficial for stakeholders,” Wang said, noting this specific application of image analysis had not been done before. Loss in premium meat “Woody breast” meat is harder and chewier than normal chicken breast, but it is still safe to eat, according to Casey Owens, professor of poultry processing and products for the experiment station and a co-author of the study. When detected by processers, either by humans or computer-assisted imaging technology, she said the meat is diverted from whole-breast packaging for further processing into products including chicken nuggets and patties. The loss in premium as a whole-muscle product accounts for yield loss as high as $200 million in Arkansas and over $1 billion in direct and indirect costs annually across the United States poultry industry, Owens added. Up to 20 percent of chicken breast meat can have the defect, which is more common in larger birds of 8 to 9 pounds versus 6- to 7-pound birds. Hyperspectral imaging Hyperspectral imaging is a rapid, non-invasive way to capture detailed data about objects and their composition. This data can be used to classify food products according to food quality, consumer preferences and other product requirements. But hyperspectral images come with tons of data. That’s where machine learning comes in. Chaitanya Pallerla, a food science graduate student who has been working on the project for the past two years with Wang as his adviser, said the new machine learning model is called NAS-WD. When correlated with known data about the “woodiness” of chicken breasts, the model allows for deeper and wider analysis of hyperspectral images to identify the defect. Develop a new model “In hyperspectral imaging, there are common machine learning models being used, but we were able to develop a new model that could be well-suited for correlating more than two variables,” Pallerla said. “We kind of took two different models, made a few changes, and put them together to detect patterns better and correlate the hyperspectral data with hardness of the chicken meat.” The results of their research were published in the journal Artificial Intelligence in Agriculture under the title “Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression.” The results showed that NAS-WD can classify three woody breast defect levels with an overall accuracy of 95 percent, outperforming the traditional models like the Support Vector Machine and Multi-Layer Perception, which offered 80 percent and about 73 percent accuracy, respectively. Push broom Wang said the study offers an example of how to use new algorithms to mine data and dig into key information. The form of hyperspectral imaging used in the research is called “push broom,” which takes an image of several objects once every 40 seconds, compared to a more common industry method of a “snapshot,” which takes an image of individual objects as fast as every 30 milliseconds. The “snapshots” have a lower resolution than the “push broom” method, but software upgrades may one day provide higher resolution for “snapshot” images, Pallerla said. Wang said his team is working on deploying this technology in the real-time system. The study was supported in part by the Agriculture and Food Research Initiative, project award nos. 2023-70442-39232 and 2024-67022-42882, from the U.S. Department of Agriculture’s National Institute for Food and Agriculture. Journal Artificial Intelligence in Agriculture DOI 10.1016/j.aiia.2024.11.003 To read the original article click here.

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Chewy Chicken Breast? Scientists Now Know the Cause

AHA Publisher — Thu, 21 Nov 2019 08:00:07 +0000

University of Delaware via EurekAlert – If they can find common solutions, Abasht said, a far-reaching goal of the work might be to use chickens as a model to study possible treatments for diabetes in humans. University of Delaware researchers have discovered that lipoprotein lipase, an enzyme crucial for fat metabolism, may be contributing to wooden breast syndrome in broiler chickens. Wooden breast syndrome can affect broiler chickens, making the meat hard and chewy. It is a costly problem that can render the birds unmarketable, causing significant economic losses for growers, who sometimes see the disease in up to half their flocks. The UD research team, led by Behnam Abasht, associate professor of animal and food sciences in UD’s College of Agriculture and Natural Resources, have identified gene expression irregularities at the onset of wooden breast syndrome that suggest the disease is a metabolic disorder characterized by abnormal fat accumulation in the breast muscle tissue. The research team reported their results on Wednesday, Nov. 20 in the journal Scientific Reports. The findings could help drive short-term solutions to help growers manage the condition in chickens at the production level through feed additives or supplements, or to reduce the number of birds that develop the condition. “The industry desperately needs a solution right now. Conservative estimates project that wooden breast syndrome is costing the U.S. agricultural community $200 million dollars per year, but this number may be much higher,” said Abasht. The United States leads production of broiler chickens worldwide. Delaware has more than 700 producers who raise commercial broiler chickens and over 1,000 small backyard poultry owners. Wooden breast syndrome is a concern around the world, too, as global consumption of chicken has risen in recent years as a leading source of dietary protein. The research also could inform human health research related to metabolic syndromes, such as diabetes and atherosclerosis, which is associated with fatty deposits in the arteries. Source of the Problem Abasht has been studying wooden breast syndrome in broiler chickens for nearly a decade. In previous work, his research team analyzed the genes involved in the disease and identified biomarkers for the disorder. They also characterized the unique biochemistry of the hardened breast tissue in chickens with the disease. In their current work, the UD research team noticed that the expression of lipoprotein lipase was higher in chickens affected with wooden breast syndrome, leading more fat to accumulate in the chicken’s pectoral (or breast) muscles. Lipoprotein lipase serves as a “metabolic gatekeeper” that determines how much fat is allowed inside a given tissue. This was curious because breast muscle fibers in chicken typically rely on sugar (glucose) molecules for fuel, not fat molecules. The research team used RNA sequencing to determine which genes were being expressed in modern fast-growing broiler chickens and slower-growing legacy chickens. They then employed a new technology, called RNA in situ hybridization, to pinpoint exactly where this gene expression occurred inside the muscle. The researchers found genetic evidence of lipoprotein lipase being expressed in endothelial cells in chickens, which was previously unknown. Present in all blood vessels, endothelial cells serve as a barrier between the blood and the surrounding tissue. Abasht hypothesized that when more fat is oxidized for energy in the breast tissue of chickens, it may be causing the excessive release of free radical molecules that would modify (damage) fats and proteins in the muscle, prompting the chicken’s immune system to kick in to clear up the problem. “We observed that if a particular vein was attacked by immune cells, the same vein typically also expressed higher levels of lipoprotein lipase,” said Abasht. The researchers went a step further and compared this data with the gene expression signals found in two commercial broiler chicken lines, at three weeks of age and again at market age. In their analysis, the researchers found signals consistent with the fact that young chickens may be showing the same changes as market-age broiler chickens with wooden breast syndrome, even before the disease shows up. The findings could provide potential markers to identify chickens that will develop the disease. In recently published research in Genes, the researchers also reported finding common features between wooden breast syndrome in chickens and diabetes complications in humans, specifically diabetic cardiomyopathy, a chronic disease characterized by molecular and structural changes in the heart muscle. Abasht’s research team is currently combing available literature for treating diabetes to see if there are ways to apply similar approaches to help broiler chickens avoid — or cope — with wooden breast syndrome, through diet, supplements or medication. If they can find common solutions, Abasht said, a far-reaching goal of the work might be to use chickens as a model to study possible treatments for diabetes in humans. “Our main focus was to address this problem from an agricultural perspective, but our findings open new horizons for future research that could benefit both agriculture and human health. This is a very interesting prospect for us,” said Abasht. Longer term, Juniper Lake, a UD doctoral student in Abasht’s lab, said that having a deeper understanding of the genetic causes behind the disease could lead to solutions for agricultural producers to selectively breed out the traits that cause wooden breast disease, which has a relatively high heritability. “There’s a lot to be gained from basic research of wooden breast, even if the main goal is to mitigate economic losses in the poultry industry,” said Lake. To read the original article click here.

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