Pork primal cuts recognition method via computer vision

Huang, Huazi; Zhan, Wei; Du, Zhiqiang; Hong, Shengbing; Dong, Tianyu; She, Jinhui; Min, Chao

doi:10.1016/j.meatsci.2022.108898

Cited by 22 publications

(7 citation statements)

References 15 publications

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“…Pork is one of the most widely consumed meats worldwide and accounts for more than 60% of meat consumption in China [ 16 ]. Due to ongoing economic development, consumers are paying increasing attention to the quality of pork.…”

Section: Discussionmentioning

confidence: 99%

MiR-196b-3p and miR-450b-3p are key regulators of adipogenesis in porcine intramuscular and subcutaneous adipocytes

Liu

You

et al. 2023

BMC Genomics

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Background As components of white adipose tissue, porcine intramuscular (IM) and subcutaneous (SC) adipocytes undergo similar differentiation and adipogenesis processes. However, the adipogenic capacity of IM adipocytes is weaker than that of SC adipocytes. Identifying key regulators underlying this difference between IM and SC adipocytes will benefit pig breeding. Results In this study, we used BGISEQ-500 sequencing technology to analyze the expression of small RNAs in primary cultured IM and SC adipocytes on day 8 after adipogenic induction, and found 32-fold higher miR-196b-3p expression, as well as 8-fold lower miR-450b-3p expression in IM adipocytes than in SC adipocytes. Functional studies revealed that miR-196b-3p inhibits adipogenesis by targeting CD47 via the AMPK signaling pathway, and its effect was attenuated by the specific p-AMPKα activator AICAR. We also found that miR-450b-3p promotes adipogenesis by targeting SIRT1 via the Wnt/β-catenin signaling pathway, and its effect was weakened by the Wnt/β-catenin signaling activator LiCl. Conclusions Our findings suggest that miR-196b-3p and miR-450b-3p are novel key regulatory factors that play opposite roles in porcine adipogenesis, helping us decipher the regulatory differences between porcine IM and SC fat deposition.

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Section: Discussionmentioning

confidence: 99%

MiR-196b-3p and miR-450b-3p are key regulators of adipogenesis in porcine intramuscular and subcutaneous adipocytes

Liu

You

et al. 2023

BMC Genomics

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“…Color features are a kind of pixel-level based features, which have less relationship with changes in viewpoint, size, and orientation, so they have strong robustness, and they are also less susceptible to interference factors such as noise and illumination changes, so in this study, RGB, L*a*b*, HSV, and three color space models (X. H. Huang, et al, 2022) were selected to extract the feature parameters of each color space and L*a*b* color space under second-order and third-order moments to quantitatively describe the color characteristics of lamb.…”

Section: Image Feature Extractionmentioning

confidence: 99%

Freshness prediction of modified atmosphere packaging lamb meat based on digital images from mobile portable devices

Jin,

Li,

Zhang

2023

J Food Process Engineering

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This study aimed to quickly assess lamb meat freshness using smartphones under various modified atmosphere packaging and storage times (0–10 days). Lamb meat images were collected across different periods and packaging types (50% O2 + 40% CO2 + 10% N2; 70% O2 + 20% CO2 + 10% N2; air). Key color features were extracted, and significant differences in five color features were identified. Three distinct color feature combinations were chosen for models: support vector regression (SVR), genetic algorithm‐back propagation (GA‐BP) neural network, and convolutional neural network (CNN). Results showed SVR models with varied color feature inputs outperformed BP and CNN models. The SVR model with 12 input features yielded the best results, enabling effective spoilage level analysis of lamb meat under different storage times. This work establishes a foundation for future smartphone app development, utilizing Raspberry Pi hardware to evaluate lamb meat freshness under diverse storage conditions.Practical applicationsThis study introduces a cell phone‐based method to rapidly determine lamb spoilage in air conditioning packages during different storage times. Using cell phone images, we collected data on lamb samples stored for 0–10 days under three packaging conditions. We extracted significant color features and selected three combinations as inputs for prediction models: SVR, GA‐BP neural network, and CNN. The SVR model with 12 feature values demonstrated the best performance. This research lays the foundation for a cell phone application based on Raspberry Pi hardware, enabling users to assess lamb freshness in various storage conditions. The potential benefits include efficient quality control in the food industry, increased consumer confidence, and improved preservation of lamb products through optimized storage and packaging. Overall, this study contributes to food quality evaluation and provides practical applications for professionals and consumers.

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“…Huang et al used a residual network (ResNet) to extract pork features to classify the types of pork original cuts into four categories: Ham, loin, belly, and neck, and applied machine vision to recognize different pork cuts with an accuracy of 94.47%. The main reasons that the different recognition results for some images still exist are the effects of the dataset size and the lighting environment in which the images were taken [ 170 ]. Table 4 summarizes the application of machine vision systems using different data processing methods on various meat.…”

Section: Machine Visionmentioning

confidence: 99%

Non-Destructive Techniques for the Analysis and Evaluation of Meat Quality and Safety: A Review

Liang

Wang

et al. 2022

Foods

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With the continuous development of economy and the change in consumption concept, the demand for meat, a nutritious food, has been dramatically increasing. Meat quality is tightly related to human life and health, and it is commonly measured by sensory attribute, chemical composition, physical and chemical property, nutritional value, and safety quality. This paper surveys four types of emerging non-destructive detection techniques for meat quality estimation, including spectroscopic technique, imaging technique, machine vision, and electronic nose. The theoretical basis and applications of each technique are summarized, and their characteristics and specific application scope are compared horizontally, and the possible development direction is discussed. This review clearly shows that non-destructive detection has the advantages of fast, accurate, and non-invasive, and it is the current research hotspot on meat quality evaluation. In the future, how to integrate a variety of non-destructive detection techniques to achieve comprehensive analysis and assessment of meat quality and safety will be a mainstream trend.

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Pork primal cuts recognition method via computer vision

Cited by 22 publications

References 15 publications

MiR-196b-3p and miR-450b-3p are key regulators of adipogenesis in porcine intramuscular and subcutaneous adipocytes

MiR-196b-3p and miR-450b-3p are key regulators of adipogenesis in porcine intramuscular and subcutaneous adipocytes

Freshness prediction of modified atmosphere packaging lamb meat based on digital images from mobile portable devices

Non-Destructive Techniques for the Analysis and Evaluation of Meat Quality and Safety: A Review

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