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Li Y, Wang H, Yang Z, Wang X, Wang W, Hui T. Rapid Non-Destructive Detection Technology in the Field of Meat Tenderness: A Review. Foods 2024; 13:1512. [PMID: 38790812 PMCID: PMC11120403 DOI: 10.3390/foods13101512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 05/07/2024] [Accepted: 05/08/2024] [Indexed: 05/26/2024] Open
Abstract
Traditionally, tenderness has been assessed through shear force testing, which is inherently destructive, the accuracy is easily affected, and it results in considerable sample wastage. Although this technology has some drawbacks, it is still the most effective detection method currently available. In light of these drawbacks, non-destructive testing techniques have emerged as a preferred alternative, promising greater accuracy, efficiency, and convenience without compromising the integrity of the samples. This paper delves into applying five advanced non-destructive testing technologies in the realm of meat tenderness assessment. These include near-infrared spectroscopy, hyperspectral imaging, Raman spectroscopy, airflow optical fusion detection, and nuclear magnetic resonance detection. Each technology is scrutinized for its respective strengths and limitations, providing a comprehensive overview of their current utility and potential for future development. Moreover, the integration of these techniques with the latest advancements in artificial intelligence (AI) technology is explored. The fusion of AI with non-destructive testing offers a promising avenue for the development of more sophisticated, rapid, and intelligent systems for meat tenderness evaluation. This integration is anticipated to significantly enhance the efficiency and accuracy of the quality assessment in the meat industry, ensuring a higher standard of safety and nutritional value for consumers. The paper concludes with a set of technical recommendations to guide the future direction of non-destructive, AI-enhanced meat tenderness detection.
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Affiliation(s)
- Yanlei Li
- Mechanical and Electrical Engineering College, Beijing Polytechnic College, Beijing 100042, China; (H.W.); (Z.Y.); (X.W.)
- Modern Agricultural Engineering Key Laboratory at Universities of Education Department of Xinjiang Uygur Autonomous Region, Alaer 843300, China
| | - Huaiqun Wang
- Mechanical and Electrical Engineering College, Beijing Polytechnic College, Beijing 100042, China; (H.W.); (Z.Y.); (X.W.)
| | - Zihao Yang
- Mechanical and Electrical Engineering College, Beijing Polytechnic College, Beijing 100042, China; (H.W.); (Z.Y.); (X.W.)
| | - Xiangwu Wang
- Mechanical and Electrical Engineering College, Beijing Polytechnic College, Beijing 100042, China; (H.W.); (Z.Y.); (X.W.)
| | - Wenxiu Wang
- Food Science and Technology College, Hebei Agricultural University, Baoding 071001, China;
| | - Teng Hui
- Food Science College, Sichuan Agricultural University, Ya’an 625014, China;
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2
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Di Paolo M, Ambrosio RL, Lambiase C, Vuoso V, Salzano A, Bifulco G, Barone CMA, Marrone R. Effects of the Aging Period and Method on the Physicochemical, Microbiological and Rheological Characteristics of Two Cuts of Charolais Beef. Foods 2023; 12:foods12030531. [PMID: 36766061 PMCID: PMC9914319 DOI: 10.3390/foods12030531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/17/2023] [Accepted: 01/19/2023] [Indexed: 01/27/2023] Open
Abstract
Wet-aging (WA) and dry-aging (DA) methods are usually used in the beef industry to satisfy the consumers' tastes; however, these methods are not suitable for all anatomical cuts. In this study, WA and DA were applied to improve the quality of two cuts of Charolais beef (Longissimus dorsi and Semitendinosus). For 60 days (i.e., 2 days, 15 days, 30 days and 60 days of sampling), a physicochemical, rheological, and microbiological analysis were performed at WA (vacuum packed; temperature of 4 ± 1 °C) and at DA (air velocity of 0.5 m/s; temperature of 1 ± 1 °C; relative humidity of 78 ± 10%) conditions. The results showed that the aging method influenced the aging loss (higher in the DA), cooking loss (higher in the WA), malondialdehyde concentration (higher in the DA) and fatty acid profile (few changes). No differences in the drip loss and color were observed, which decreased after 30 days of aging. The WBSF and TPA test values changed with increasing an aging time showing that the aging improved the tenderness of meat regardless of the aging method. Moreover, the aging method does not influence the microbiological profile. In conclusion, both WA and DA enhanced the quality of the different beef cuts, suggesting that an optimal method-time and aging combination could be pursued to reach the consumers' preferences.
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Affiliation(s)
- Marika Di Paolo
- Department of Veterinary Medicine and Animal Production, University of Naples Federico II, 80137 Naples, Italy
| | - Rosa Luisa Ambrosio
- Department of Veterinary Medicine and Animal Production, University of Naples Federico II, 80137 Naples, Italy
| | - Claudia Lambiase
- Department of Agricultural Sciences, University of Naples Federico II, 80055 Portici (Na), Italy
| | - Valeria Vuoso
- Department of Veterinary Medicine and Animal Production, University of Naples Federico II, 80137 Naples, Italy
| | - Angela Salzano
- Department of Veterinary Medicine and Animal Production, University of Naples Federico II, 80137 Naples, Italy
| | - Giovanna Bifulco
- Department of Veterinary Medicine and Animal Production, University of Naples Federico II, 80137 Naples, Italy
| | | | - Raffaele Marrone
- Department of Veterinary Medicine and Animal Production, University of Naples Federico II, 80137 Naples, Italy
- Correspondence: ; Tel.: +39-081-2536469
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Vasconcelos L, Dias LG, Leite A, Ferreira I, Pereira E, Silva S, Rodrigues S, Teixeira A. SVM Regression to Assess Meat Characteristics of Bísaro Pig Loins Using NIRS Methodology. Foods 2023; 12:foods12030470. [PMID: 36766001 PMCID: PMC9914495 DOI: 10.3390/foods12030470] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 01/05/2023] [Accepted: 01/16/2023] [Indexed: 01/20/2023] Open
Abstract
This study evaluates the ability of the near infrared reflectance spectroscopy (NIRS) to estimate the aW, protein, moisture, ash, fat, collagen, texture, pigments, and WHC in the Longissimus thoracis et lumborum (LTL) of Bísaro pig. Samples (n = 40) of the LTL muscle were minced and scanned in an FT-NIR MasterTM N500 (BÜCHI) over a NIR spectral range of 4000-10,000 cm-1 with a resolution of 4 cm-1. The PLS and SVM regression models were developed using the spectra's math treatment, DV1, DV2, MSC, SNV, and SMT (n = 40). PLS models showed acceptable fits (estimation models with RMSE ≤ 0.5% and R2 ≥ 0.95) except for the RT variable (RMSE of 0.891% and R2 of 0.748). The SVM models presented better overall prediction results than those obtained by PLS, where only the variables pigments and WHC presented estimation models (respectively: RMSE of 0.069 and 0.472%; R2 of 0.993 and 0.996; slope of 0.985 ± 0.006 and 0.925 ± 0.006). The results showed NIRs capacity to predict the meat quality traits of Bísaro pig breed in order to guarantee its characterization.
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Affiliation(s)
- Lia Vasconcelos
- Mountain Reserach Center (CIMO), Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
- Laboratory for Sustainability and Technology in Mountain Regions, Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
| | - Luís G. Dias
- Mountain Reserach Center (CIMO), Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
- Laboratory for Sustainability and Technology in Mountain Regions, Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
| | - Ana Leite
- Mountain Reserach Center (CIMO), Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
- Laboratory for Sustainability and Technology in Mountain Regions, Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
| | - Iasmin Ferreira
- Mountain Reserach Center (CIMO), Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
- Laboratory for Sustainability and Technology in Mountain Regions, Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
| | - Etelvina Pereira
- Mountain Reserach Center (CIMO), Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
- Laboratory for Sustainability and Technology in Mountain Regions, Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
| | - Severiano Silva
- Veterinary and Animal Research Centre (CECAV), Associate Laboratory of Animal and Veterinary Science (AL4AnimalS), University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal
| | - Sandra Rodrigues
- Mountain Reserach Center (CIMO), Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
- Laboratory for Sustainability and Technology in Mountain Regions, Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
| | - Alfredo Teixeira
- Mountain Reserach Center (CIMO), Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
- Laboratory for Sustainability and Technology in Mountain Regions, Polytechnic Institut of Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
- Correspondence:
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Kamruzzaman M. Optical sensing as analytical tools for meat tenderness measurements - A review. Meat Sci 2023; 195:109007. [DOI: 10.1016/j.meatsci.2022.109007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 09/11/2022] [Accepted: 10/12/2022] [Indexed: 11/09/2022]
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Ouyang Q, Liu L, Zareef M, Wang L, Chen Q. Application of portable visible and near-infrared spectroscopy for rapid detection of cooking loss rate in pork: Comparing spectra from frozen and thawed pork. Lebensm Wiss Technol 2022. [DOI: 10.1016/j.lwt.2022.113304] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Onopiuk A, Szpicer A, Pogorzelski G, Wierzbicka A, Poltorak A. Analysis of the impact of exogenous preparations of cysteine proteases on tenderness of beef muscles Semimembranosus and Longissimus thoracis et lumborum. Livest Sci 2022. [DOI: 10.1016/j.livsci.2022.104866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Meng X, Gao Z, Liang Y, Zhang C, Chen Z, Mao Y, Huang B, Kui K, Yang Z. Longissimus Dorsi Muscle Transcriptomic Analysis of Simmental and Chinese Native Cattle Differing in Meat Quality. Front Vet Sci 2020; 7:601064. [PMID: 33385016 PMCID: PMC7770222 DOI: 10.3389/fvets.2020.601064] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 11/09/2020] [Indexed: 12/20/2022] Open
Abstract
With the rapid development of economy, the demand for beef, with regard to quantity and quality, by consumers has been increasing in China. Chinese native cattle are characterized by their abundant genetic resources, unique origins, large breeding stocks, and robust environmental adaptability. Thus, to explore the genetic mechanisms on regulating meat quality in Chinese native cattle is of great importance to satisfy increased requirements for beef production. In this study, we investigated three breeds of cattle, namely Yunling, Wenshan, and Simmental, at the age of 12 months. Animals were classified into three groups (n = 5/breed). Growth traits including body weight and body size and plasma hormone levels were measured. Body weight of Wenshan cattle was significantly lower than that of Yunling and Simmental cattle (P < 0.05). Again, body size indexes, such as withers height, body slanting length, chest circumference, and hip and rump length, were significantly lower in Wenshan cattle than those in Yunling and Simmental cattle (P < 0.05). However, there were no significant differences in those indexes between Yunling and Simmental cattle (P > 0.05). Cattle were slaughtered at the age of 18 months and then meat color, pH, pressing losses, muscle tenderness, and cooking losses were measured at 0, 1, 2, 3, 5, and 7 days. Data revealed differences in meat quality among the three breeds analyzed. Based on transcriptomic sequencing and bioinformatic analysis, we observed 3,198 differentially expressed genes related to meat quality, of which 1,750 genes were upregulated. Moreover, we found two important signaling pathways closely linked to meat quality, namely adipocytokine signaling pathway [e.g., Leptin receptor (LEPR)] and protein processing in the endoplasmic reticulum [e.g., signal transducer and activator of transcription 3 (STAT3), heat shock protein (HSPA12A), and calpain 1 (CAPN1)]. The results of transcripts were further verified by qRT-PCR. Using correlation analysis between gene expression levels and shear force, we also identified two functional genes (e.g., HSPA12A and CAPN1) associated with meat quality. Overall, this study provides new sights into novel targets and underlying mechanisms to modulate meat quality in Chinese native cattle.
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Affiliation(s)
- Xiangren Meng
- School of Tourism and Culinary Science, Yangzhou University, Yangzhou, China.,Jiangsu Huai-yang Cuisine Engineering Center, Yangzhou University, Yangzhou, China
| | - Ziwu Gao
- School of Tourism and Culinary Science, Yangzhou University, Yangzhou, China.,Jiangsu Huai-yang Cuisine Engineering Center, Yangzhou University, Yangzhou, China
| | - Yusheng Liang
- Mammalian Nutrition Physiology Genomics, Department of Animal Sciences and Division of Nutritional Sciences, University of Illinois, Urbana, IL, United States
| | - Chenglong Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Zhi Chen
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Yongjiang Mao
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Bizhi Huang
- Academy of Grassland and Animal Science, Yunnan, China
| | - Kaixing Kui
- Academy of Grassland and Animal Science, Yunnan, China
| | - Zhangping Yang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
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EFFECT OF ROSEMARY EXTRACT ADDITION ON OXIDATIVE STABILITY AND QUALITY OF HEMP SEED OIL. FOOD AND BIOPRODUCTS PROCESSING 2020. [DOI: 10.1016/j.fbp.2020.08.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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9
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Bresolin T, Dórea JRR. Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems. Front Genet 2020; 11:923. [PMID: 32973876 PMCID: PMC7468402 DOI: 10.3389/fgene.2020.00923] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 07/24/2020] [Indexed: 12/17/2022] Open
Abstract
High-throughput phenotyping technologies are growing in importance in livestock systems due to their ability to generate real-time, non-invasive, and accurate animal-level information. Collecting such individual-level information can generate novel traits and potentially improve animal selection and management decisions in livestock operations. One of the most relevant tools used in the dairy and beef industry to predict complex traits is infrared spectrometry, which is based on the analysis of the interaction between electromagnetic radiation and matter. The infrared electromagnetic radiation spans an enormous range of wavelengths and frequencies known as the electromagnetic spectrum. The spectrum is divided into different regions, with near- and mid-infrared regions being the main spectral regions used in livestock applications. The advantage of using infrared spectrometry includes speed, non-destructive measurement, and great potential for on-line analysis. This paper aims to review the use of mid- and near-infrared spectrometry techniques as tools to predict complex dairy and beef phenotypes, such as milk composition, feed efficiency, methane emission, fertility, energy balance, health status, and meat quality traits. Although several research studies have used these technologies to predict a wide range of phenotypes, most of them are based on Partial Least Squares (PLS) and did not considered other machine learning (ML) techniques to improve prediction quality. Therefore, we will discuss the role of analytical methods employed on spectral data to improve the predictive ability for complex traits in livestock operations. Furthermore, we will discuss different approaches to reduce data dimensionality and the impact of validation strategies on predictive quality.
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Affiliation(s)
- Tiago Bresolin
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, United States
| | - João R R Dórea
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, United States
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