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Justice SM, Jesch E, Duckett SK. Effects of Dam and Sire Breeds on Lamb Carcass Quality and Composition in Pasture-Based Systems. Animals (Basel) 2023; 13:3560. [PMID: 38003177 PMCID: PMC10668792 DOI: 10.3390/ani13223560] [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: 10/10/2023] [Revised: 11/10/2023] [Accepted: 11/16/2023] [Indexed: 11/26/2023] Open
Abstract
This study explored the impacts of sire and dam breed on carcass quality and composition in a pasture-based system and the use of DXA to rapidly rank carcasses for leanness. Southdown (SD) and Suffolk (SF) ewes were mated to Texel (TX) or SD rams to produce seventy-nine lambs. Lambs were raised on pasture-based systems with limited grain supplementation. Lamb birth weight was greater (p < 0.01) for TX, regardless of dam breed. Lambing rate was lower (p < 0.01) for SD than SF ewes. Circulating myostatin concentrations were greater (p < 0.05) on d 42 than d 75 or d 110 but did not differ by sire breed. Texel-sired lambs had greater (p < 0.01) carcass weight, ribeye area and quality grade compared to SD-sired. Total and primal fat mass as predicted from DXA was higher (p < 0.05) in carcasses from SD than TX sires. Muscles from TX lambs had greater (p < 0.05) polyunsaturated fatty acid (PUFA) composition than SD-sired. Shear force values were influenced (p < 0.01) by dam breed, muscle cut and postmortem age but not by sire breed. The use of TX sires in pasture-based systems improved carcass leanness and muscle PUFA concentrations without altering tenderness.
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Affiliation(s)
- S. Maggie Justice
- Department of Animal and Veterinary Sciences, Clemson University, Clemson, SC 29634, USA;
| | - Elliot Jesch
- Department of Food, Nutrition, and Packaging Sciences, Clemson University, Clemson, SC 29634, USA;
| | - Susan K. Duckett
- Department of Animal and Veterinary Sciences, Clemson University, Clemson, SC 29634, USA;
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2
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Kophamel S, Ward LC, Konovalov DA, Mendez D, Ariel E, Cassidy N, Bell I, Balastegui Martínez MT, Munns SL. Field-based adipose tissue quantification in sea turtles using bioelectrical impedance spectroscopy validated with CT scans and deep learning. Ecol Evol 2022; 12:e9610. [PMID: 36523527 PMCID: PMC9748411 DOI: 10.1002/ece3.9610] [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: 10/27/2022] [Accepted: 11/23/2022] [Indexed: 12/15/2022] Open
Abstract
Loss of adipose tissue in vertebrate wildlife species is indicative of decreased nutritional and health status and is linked to environmental stress and diseases. Body condition indices (BCI) are commonly used in ecological studies to estimate adipose tissue mass across wildlife populations. However, these indices have poor predictive power, which poses the need for quantitative methods for improved population assessments. Here, we calibrate bioelectrical impedance spectroscopy (BIS) as an alternative approach for assessing the nutritional status of vertebrate wildlife in ecological studies. BIS is a portable technology that can estimate body composition from measurements of body impedance and is widely used in humans. BIS is a predictive technique that requires calibration using a reference body composition method. Using sea turtles as model organisms, we propose a calibration protocol using computed tomography (CT) scans, with the prediction equation being: adipose tissue mass (kg) = body mass - (-0.03 [intercept] - 0.29 * length2/resistance at 50 kHz + 1.07 * body mass - 0.11 * time after capture). CT imaging allows for the quantification of body fat. However, processing the images manually is prohibitive due to the extensive time requirement. Using a form of artificial intelligence (AI), we trained a computer model to identify and quantify nonadipose tissue from the CT images, and adipose tissue was determined by the difference in body mass. This process enabled estimating adipose tissue mass from bioelectrical impedance measurements. The predictive performance of the model was built on 2/3 samples and tested against 1/3 samples. Prediction of adipose tissue percentage had greater accuracy when including impedance parameters (mean bias = 0.11%-0.61%) as predictor variables, compared with using body mass alone (mean bias = 6.35%). Our standardized BIS protocol improves on conventional body composition assessment methods (e.g., BCI) by quantifying adipose tissue mass. The protocol can be applied to other species for the validation of BIS and to provide robust information on the nutritional and health status of wildlife, which, in turn, can be used to inform conservation decisions at the management level.
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Affiliation(s)
- Sara Kophamel
- College of Public Health, Medical and Veterinary SciencesJames Cook UniversityTownsvilleQueenslandAustralia
| | - Leigh C. Ward
- School of Chemistry and Molecular BiosciencesThe University of QueenslandSt LuciaQueenslandAustralia
| | - Dmitry A. Konovalov
- College of Science and EngineeringJames Cook UniversityTownsvilleQueenslandAustralia
| | - Diana Mendez
- Australian Institute of Tropical Health and MedicineTownsvilleQueenslandAustralia
| | - Ellen Ariel
- College of Public Health, Medical and Veterinary SciencesJames Cook UniversityTownsvilleQueenslandAustralia
| | - Nathan Cassidy
- North Queensland X‐Ray ServicesTownsvilleQueenslandAustralia
| | - Ian Bell
- Department of Environment and ScienceQueensland GovernmentTownsvilleQueenslandAustralia
| | | | - Suzanne L. Munns
- College of Public Health, Medical and Veterinary SciencesJames Cook UniversityTownsvilleQueenslandAustralia
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Wu X, Liang X, Wang Y, Wu B, Sun J. Non-Destructive Techniques for the Analysis and Evaluation of Meat Quality and Safety: A Review. Foods 2022; 11:3713. [PMID: 36429304 PMCID: PMC9689883 DOI: 10.3390/foods11223713] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 11/04/2022] [Accepted: 11/15/2022] [Indexed: 11/22/2022] Open
Abstract
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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Affiliation(s)
- Xiaohong Wu
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
- High-Tech Key Laboratory of Agricultural Equipment and Intelligence of Jiangsu Province, Jiangsu University, Zhenjiang 212013, China
| | - Xinyue Liang
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Yixuan Wang
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Bin Wu
- Department of Information Engineering, Chuzhou Polytechnic, Chuzhou 239000, China
| | - Jun Sun
- School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
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4
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Delgado-Pando G, Allen P, Troy DJ, McDonnell CK. Objective carcass measurement technologies: Latest developments and future trends. Trends Food Sci Technol 2021. [DOI: 10.1016/j.tifs.2020.12.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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5
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Silva S, Guedes C, Rodrigues S, Teixeira A. Non-Destructive Imaging and Spectroscopic Techniques for Assessment of Carcass and Meat Quality in Sheep and Goats: A Review. Foods 2020; 9:E1074. [PMID: 32784641 PMCID: PMC7466308 DOI: 10.3390/foods9081074] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 07/25/2020] [Accepted: 07/27/2020] [Indexed: 02/06/2023] Open
Abstract
In the last decade, there has been a significant development in rapid, non-destructive and non-invasive techniques to evaluate carcass composition and meat quality of meat species. This article aims to review the recent technological advances of non-destructive and non-invasive techniques to provide objective data to evaluate carcass composition and quality traits of sheep and goat meat. We highlight imaging and spectroscopy techniques and practical aspects, such as accuracy, reliability, cost, portability, speed and ease of use. For the imaging techniques, recent improvements in the use of dual-energy X-ray absorptiometry, computed tomography and magnetic resonance imaging to assess sheep and goat carcass and meat quality will be addressed. Optical technologies are gaining importance for monitoring and evaluating the quality and safety of carcasses and meat and, among them, those that deserve more attention are visible and infrared reflectance spectroscopy, hyperspectral imagery and Raman spectroscopy. In this work, advances in research involving these techniques in their application to sheep and goats are presented and discussed. In recent years, there has been substantial investment and research in fast, non-destructive and easy-to-use technology to raise the standards of quality and food safety in all stages of sheep and goat meat production.
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Affiliation(s)
- Severiano Silva
- Veterinary and Animal Research Centre (CECAV) Universidade Trás-os-Montes e Alto Douro, Quinta de Prados, 5000-801 Vila Real, Portugal;
| | - Cristina Guedes
- Veterinary and Animal Research Centre (CECAV) Universidade Trás-os-Montes e Alto Douro, Quinta de Prados, 5000-801 Vila Real, Portugal;
| | - Sandra Rodrigues
- Mountain Research Centre (CIMO), Escola Superior Agrária/Instituto Politécnico de Bragança, Campus Sta Apolónia Apt 1172, 5301-855 Bragança, Portugal; (S.R.); (A.T.)
| | - Alfredo Teixeira
- Mountain Research Centre (CIMO), Escola Superior Agrária/Instituto Politécnico de Bragança, Campus Sta Apolónia Apt 1172, 5301-855 Bragança, Portugal; (S.R.); (A.T.)
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Sun Y, Wang S, Liu H, Ren R, Dong Q, Xie J, Cao J. Profiling and characterization of miRNAs associated with intramuscular fat content in Yorkshire pigs. Anim Biotechnol 2019; 31:256-263. [PMID: 31018763 DOI: 10.1080/10495398.2019.1573191] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
miRNAs are short noncoding RNAs that post-transcriptionally regulate gene expression by binding to complementary regions of the target mRNA. The miRNAs associated with the deposition of intramuscular fat (IMF) content in pigs, which is an important meat quality trait, still remain to be investigated. In this study, the longissimus dorsi muscles (LDMs) from 234 individuals were collected from Yorkshire pigs at 90 kg body weight and the miRNA deep sequencing was conducted by using two tailed groups which were taken five individuals each from high (2.94 ± 0.04%) and low (1.62 ± 0.02%) IMF samples. The results showed that total 268 mature miRNAs were identified, of which 70 were previously known, 162 were conserved among species and 36 were identified specifically in pigs. Moreover, 28 miRNAs involved in adipogenesis were differentially expressed in the two groups, and five out of 16 miRNAs were validated by quantitative PCR (qPCR) using stem loop primers. Our results may serve as a fundamental basis for understanding the roles of miRNA in IMF development in pigs. The miRNAs identified in our study can be utilized for research IMF trait in pig population and will provide further clues to the study of meat quality regulatory mechanisms.
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Affiliation(s)
- Yan Sun
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Huazhong Agricultural University, Wuhan, PR China.,College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, PR China
| | - Sheng Wang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Huazhong Agricultural University, Wuhan, PR China.,College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, PR China
| | - Huiying Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Huazhong Agricultural University, Wuhan, PR China.,College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, PR China
| | - Ruimin Ren
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Huazhong Agricultural University, Wuhan, PR China.,College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, PR China
| | - Qian Dong
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Huazhong Agricultural University, Wuhan, PR China.,College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, PR China
| | - Junhui Xie
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Huazhong Agricultural University, Wuhan, PR China.,College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, PR China
| | - Jianhua Cao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Huazhong Agricultural University, Wuhan, PR China.,College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, PR China
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Abstract
The main goal of this chapter was to review the state of the art in the recent advances in sheep and goat meat products research. Research and innovation have been playing an important role in sheep and goat meat production and meat processing as well as food safety. Special emphasis will be placed on the imaging and spectroscopic methods for predicting body composition, carcass and meat quality. The physicochemical and sensory quality as well as food safety will be referenced to the new sheep and goat meat products. Finally, the future trends in sheep and goat meat products research will be pointed out.
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