Meat Science Research Articles

A review of taste-active compounds in meat: Identification, influencing factors, and taste transduction mechanism.

Poultry and livestock meat are important parts of the human diet. As living standards have improved, food taste has become a major influence on consumer quality assessment and meat purchasing choices. There is increasing research interest in meat taste and meat taste-active compounds, which include free amino acids, flavor nucleotides, taste-active peptides, organic acids, soluble sugars, and inorganic ions. Taste component research is also an important part of sensory science. A deeper understanding of the meat taste perception mechanism and interactions among different taste compounds will promote the development of meat science and sensory evaluation. This article reviews the main taste compounds in meat, factors influencing their concentrations, and the identification and measurement of taste-active compounds, as well as summarizing the mechanisms of taste sensing and perception. Finally, the future of scientific taste component evaluation is discussed. This review provides a theoretical basis for research on meat taste and an important reference for the development of the meat industry.

Webometric analysis of the visibility, reach and impact of food science research publications: institute of agricultural research and training, ibadan (1972-2023)

This study evaluated the visibility, reach and impact of Food Science research publications from the Institute of Agricultural Research and Training (IAR&T) in Ibadan, Nigeria, over the period 1972-2023. Utilizing webometric analysis, data were collected from Google Scholar, Research Gate, and Scopus, focusing on citation metrics, article counts, and online engagement. A total of 745 scholarly articles across various food science disciplines, including Food Microbiology, Human Nutrition, Meat Science, Nutritional Biochemistry, and Food Science Technology and Biotechnology, were analyzed. The study incorporated log file data from the 14 food scientists’ profiles, examining a total of 9,392 cited works. These citations were derived from materials indexed by Google Scholar (5,221 citations), Research Gate (3,358 citations) and Scopus (813 citations). Findings revealed that Food Science Technology and Biotechnology had the highest number of articles and citations, with 257 articles (64.4% of total) on Google Scholar and 3,108 citations (60% of total). Research Gate showed 171 articles (65% of total) with 2,249 citations (67% of total), while Scopus recorded 52 articles (63% of total) with 449 citations (55.2% of total). A paired t-test measuring the evolution of access and growth in published works indicated a statistically significant increase (p < 0.05) across all specializations in Food Science. Citations for Food Science/Technology and Biotechnology rose from 19 (1%) in 1972-1997 to 3,089 (99%) in 1998-2023, highlighting substantial growth in visibility and usage. The geographical distribution analysis showed that Africa had the highest citation metrics, followed by Europe, North America with Asia and South America having relatively lower impact. The study underscores the critical role of digital platforms in enhancing research impact and suggested that improved dissemination strategies are needed, particularly for areas with lower reach such as food Microbiology. These findings provided valuable insights for researchers aiming to enhance the visibility and impact of scientific research in food Science.

Responsible meat production: 70th International Congress of Meat Science and Technology), August 2024, Foz do Iguaçu, Brazil

Responsible meat production: 70th International Congress of Meat Science and Technology), August 2024, Foz do Iguaçu, Brazil

PSLBI-25 Students’ perceptions of an artificial intelligence photo generation tool in upper-level animal science curriculum

Abstract Domesticated livestock behavior (DLB) is an advanced animal science lecture course that emphasizes behavior associated with domestication of various animal species such as livestock, equine, companion animals and exotic species. Meat Science (MS) is an introductory dual lecture and laboratory course that focuses on muscle biology, food-borne illnesses, humane livestock harvesting, and fabrication techniques. With the emerging usage of artificial intelligence (AI) generative technologies, an assignment was developed utilizing the free AI photo generation tool, Craiyon. Students in DLB and MS were tasked with completing an AI assignment, generating images relevant to either DLB or MS concepts, to expose students to AI technologies. Therefore, the objective of this study was to determine students’ perceptions, knowledge, concerns, and willingness to use AI generative tools and evaluate differences relative to course enrolled (DLB compared with MS). Students (n = 60) enrolled in DLB and MS completed a post-completion survey instrument that consisted of demographic and 5-point Likert-scale questions to gauge student perceptions of the AI assignment. Student survey responses were compiled online using Qualtrics and subsequent respondent data was analyzed using JMP. To give some demographic information relative to the population of students enrolled in DLB and MS, 81 and 76% of the students were female while 19 and 24% were male, respectively. Both courses contained students further along in their degree-seeking program (> 80% Junior or Senior classification). Approximately, 43% of respondents were first generation college students and 66% commute over 14 km daily. When asked about their previous experience using AI generative technologies, 75% of respondents reported no previous experience using AI generative programs. Students enrolled in MS showed a greater concern (P ≤ 0.03) of AI technologies limiting their opportunity to interact and socialize with others as compared with DLB students. Student experience, knowledge, and willingness to use AI tools was not impacted by course enrolled (P ≥ 0.14). Most students reported that they had a positive experience with the AI assignment and felt the experience would be useful in their future (53 and 73%, respectively). Additionally, a majority of students reported that the AI assignment allowed them to visualize concepts and offered a unique learning experience. Participants seemed to have a solid understanding of AI technologies reporting knowledge in tool limitations and inaccurate output. Students were neutral regarding concerns in becoming over-reliant on AI tools and AI use hindering the development of transferable skills. Students felt that AI image generation tools boosted creativity and could be useful in the realm of DLB and MS. Overall, students possessed a general knowledge of AI generative technologies and saw value in using AI image generation tools as it relates to domesticated animal behavior and meat science principles.

(Invited) Electroanalytical Meat Science

Meat color is a crucial factor that drives consumers’ purchase decisions at the point of sale. Consumers prefer the bright-cherry red color of beef. A recent study from our research team reported that the US beef industry loses $3.7 billion annually, and 400 million pounds of beef/animal protein is discarded due to meat discoloration (brown color), raising concerns over food security, the economy, and the environment. The red color of meat is strongly associated with the ratio of oxymyoglobin to metmyoglobin. This presentation will discuss our innovative use of electrochemistry to understand the redox signals of meat discoloration covering purified myoglobin protein, various species types, and sarcoplasmic extract studies. The knowledge gained from our research is expected to allow the implementation of new electroanalytical tools useful for meat and food science fields.

Consumer-Focused Meat Science Extension Program Increase Consumer Confidence and Knowledge of Meat Selection and Preparation

Science-based, meat science education is often limited outside of universities, creating possibilities to develop Extension activities to educate and impower consumers in principles of meat science. The Indiana BBQ Bootcamp was developed to provide consumers information on meat selection, proper cooking techniques, food safety, and meat seasoning (spice rubs and marinades) through demonstrations and product sampling. Attendees were surveyed before and after the program to report their confidence in their ability to perform basic meat science techniques. Responses to all survey questions showed significant increase in the attendees’ confidence demonstrating improvement in their meat science knowledge.

Synergizing meat Science and AI: Enhancing long-chain saturated fatty acids prediction

In the field of the food industry, establishing a global predictive model for the content of long-chain saturated fatty acids (LC-SFAs) in red meat is of profound significance. However, this work requires the accumulation of a large number of diverse samples for model calibration. To address these formidable challenges, the Generative Inference Adversarial Autoencoder (GI-AAE) was adopted to enhance the model training process. Through multiple iterations, GI-AAE successfully generated simulated samples of higher quality than traditional generative adversarial networks and autoencoders. After incorporating these generated samples into the training dataset, multiple sets of models showed significant improvements. These results clearly demonstrated that our approach can effectively overcome the challenges posed by generative models in the regression domain, greatly enhancing the model's generalization ability. This advancement holds significant potential for applications in the food industry.

Implementation of a Group Quiz Format in an Introductory Meat Science Course

Collaborative learning methods are increasing in popularity as a way of improving student performance and involvement in undergraduate courses. For this study, a group quiz format was used in an to attempt to improve course grades and engagement in an introductory meat science course. Six group quizzes and six individual quizzes were taken by 70 students during two semesters of the course. For group quizzes, students were randomly assigned to groups of three to four students and given ten minutes to complete the quiz individually followed by three minutes to discuss the quiz and change answers. At the end of the semester, students completed a Likert item questionnaire concerning their opinions on the quiz format. The average scores were not different between the two quiz types in both semesters. Group quizzes also did not improve exam scores or overall course grades for the students. Even though average performance was not improved, students highly preferred the group quizzes to the individual quizzes and valued the exercise.

Bibliometric Analyzes of Some Major Effect Genes Associated with Meat Yield Traits in Livestock

Bibliometric analysis is commonly used to guide decisions regarding research funding and the creation of research policies and offers scientists helpful information about research trends, patterns, and impact. Thus, researchers can track collaborators in this subject and find prospective scientific alliances. Additionally, researchers can develop new research themes by constantly monitoring the most recent trend study topics in this area. Therefore, we performed the comprehensive bibliometric analysis of 4085 documents scanned in the Web of Science (WoS) database in some major effect genes associated with meat yield traits in livestock between 1981 and 2023. The analysis shows that interest in this topic has lately grown. The fact that numerous scholars participated in the investigations, which major research groups conducted, demonstrates the growth of this field's collaborative working culture. The publication of studies in this field in high-impact journals such as Meat Science, Journal of Animal Science and Animal Genetics reveals the scientific impact of this field. Keywords used in studies in this field are generally related to investigating the genetic factors affecting livestock's growth, muscle development and meat quality characteristics. In country-based studies, China and the United States have the most studies in this field. The citation records of articles reveal the significant impact of this field in literature. The scientific community has recently been particularly interested in investigating some major effect genes associated with meat yield traits in livestock.

A Role of Multi-Omics Technologies in Sheep and Goat Meats: Progress and Way Ahead.

Sheep and goat meats are increasingly popular worldwide due to their superior nutritional properties and distinctive flavor profiles. In recent decades, substantial progress in meat science has facilitated in-depth examinations of ovine and caprine muscle development during the antemortem phase, as well as post-mortem changes influencing meat attributes. To elucidate the intrinsic molecular mechanisms and identify potential biomarkers associated with meat quality, the methodologies employed have evolved from traditional physicochemical parameters (such as color, tenderness, water holding capacity, flavor, and pH) to some cutting-edge omics technologies, including transcriptomics, proteomics, and metabolomics approaches. This review provides a comprehensive analysis of multi-omics techniques and their applications in unraveling sheep and goat meat quality attributes. In addition, the challenges and future perspectives associated with implementing multi-omics technologies in this area of study are discussed. Multi-omics tools can contribute to deciphering the molecular mechanism responsible for the altered the meat quality of sheep and goats across transcriptomic, proteomic, and metabolomic dimensions. The application of multi-omics technologies holds great potential in exploring and identifying biomarkers for meat quality and quality control, thereby promoting the optimization of production processes in the sheep and goat meat industry.

Comparative Analysis of Porcine Adipose- and Wharton's Jelly-Derived Mesenchymal Stem Cells.

Mesenchymal stem cells (MSCs) are promising candidates for tissue regeneration, cell therapy, and cultured meat research owing to their ability to differentiate into various lineages including adipocytes, chondrocytes, and osteocytes. As MSCs display different characteristics depending on the tissue of origin, the appropriate cells need to be selected according to the purpose of the research. However, little is known of the unique properties of MSCs in pigs. In this study, we compared two types of porcine mesenchymal stem cells (MSCs) isolated from the dorsal subcutaneous adipose tissue (adipose-derived stem cells (ADSCs)) and Wharton's jelly of the umbilical cord (Wharton's jelly-derived mesenchymal stem cells (WJ-MSCs)) of 1-day-old piglets. The ADSCs displayed a higher proliferation rate and more efficient differentiation potential into adipogenic and chondrogenic lineages than that of WJ-MSCs; conversely, WJ-MSCs showed superior differentiation capacity towards osteogenic lineages. In early passages, ADSCs displayed higher proliferation rates and mitochondrial energy metabolism (measured based on the oxygen consumption rate) compared with that of WJ-MSCs, although these distinctions diminished in late passages. This study broadens our understanding of porcine MSCs and provides insights into their potential applications in animal clinics and cultured meat science.

From Tradition to Green Innovation: The 69th International Congress of Meat Science and Technology (ICoMST), Padova, Italy

From Tradition to Green Innovation: The 69th International Congress of Meat Science and Technology (ICoMST), Padova, Italy

Do Consumers Perceive Cultivated Meat as a Sustainable Substitute to Conventional Meat? Assessing the Facilitators and Inhibitors of Cultivated Meat Acceptance

Conventional meat production has become a force of environmental damage, but global meat consumption is predicted to continue increasing. Therefore, the technology of cultivated meat is undergoing rapid development. The current study explores what factors explain U.S. consumers’ intention to purchase cultivated meat as a sustainable substitute for conventional meat by applying a dual-factor model. A total of 410 completed responses were received from a nationwide survey. Structural equation modeling was conducted to test the model and hypotheses. The results showed that physical health, animal welfare, and food quality significantly encouraged consumer acceptance of cultivated meat as a sustainable substitute for conventional meat. Food technology neophobia significantly inhibits the acceptance of cultivated meat, whereas unnaturalness did not show an impact on cultivated meat acceptance. Furthermore, the acceptance of cultivated meat as a sustainable substitute significantly enhanced consumers’ purchase intention. The findings inform practitioners about promoting cultivated meat in that marketers should emphasize the benefits of cultivated meat with health, animal welfare, food quality, and the environment. While technological language should be used carefully to avoid food technology neophobia, it is also essential to educate consumers on the science of cultivated meat in order for them to understand its benefits to sustainability.

Evaluating the preparation of pre-service school-based agricultural education teachers in laboratory-based courses

This study sought to examine laboratory-based instruction for pre-service school-based agricultural education (SBAE) teachers at various institutions across the nation. While research has indicated that laboratory-based instruction in SBAE programs is commonplace (Shoulders & Meyers, 2012), a myriad of literature has noted SBAE teachers are not adequately prepared to teach, manage, and facilitate learning activities in SBAE laboratories upon completing their teacher education programs (Burris et al., 2005; Hainline & Wells, 2019; Shoulders, 2012). 
 To better understand the current state of SBAE pre-service teacher training in laboratory instruction, we surveyed 33 agricultural education certifying institutions across the country. Many of these institutions indicated they required pre-service teachers to take two laboratory-based instruction courses in the areas of agricultural mechanics (96.9%) and welding metal fabrication livestock (83.9%). However, only 46.7% of the responding institutions required students to take a greenhouse management course, and 29% required pre-service teachers to take a meat science course. The findings of this study also highlight if the laboratory-based courses had a pedagogical component, and the teacher educators were asked to provide their perceptions for a need for expansion of instruction in each context. Recommendations for practice and further investigation were provided.

Molecular Characterization and Quantification of Saponins from Sugar Beet (Beta vulgaris ssp. vulgaris var. altissima)

Consumer demand for sustainably and ecologically produced food has grown in recent years. However, for numerous reasons, this demand has not always been met. New solutions are still being sought, particularly in the area of emulsifiers, an integral ingredient of many food products. The biggest challenge is the limited scope of application offered by current alternatives. While some progress has been made using foam active quillaja saponins, they are neither pleasant‐tasting nor sustainably produced. Only very little is known about other alternatives, and especially the behavior of saponins, particularly on a molecular level, is not very well understood. Moreover, it is often not known which parts of a plant contain the highest levels of saponins and are therefore most suitable for extraction.To expand the current level of knowledge about emulsifying and foam active extracts, saponin extracts were made from oat bran, beetroot as well as sugar beet and characterized in close cooperation with the Department of Food Physics and Meat Science at the University of Hohenheim. Measurements conducted on these extracts showed that foam activity is a good indicator of their emulsifying ability. The most promising one ‐ sugar beet extract ‐ was examined in more detail using taste dilution analysis, which revealed saponin fractions with a slight off‐taste and high foam activity. A series of eight saponins was obtained from these fractions and further characterized, together with three commercially available ones that were identified using non‐targeted screening. The unequivocal identification and structure elucidation was performed using a combination of liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) and both one‐dimensional (1D) and two‐dimensional (2D) nuclear magnetic resonance (NMR) spectroscopy. For most substances, this was the first time that a complete assignment of 1H and 13C NMR signals had been made. All of these saponins possess taste recognition values above 1000 μmol/L, which is higher than most values for the taste‐ active saponins reported in the literature. The foam activity of these substances was measured using a self‐developed small‐scale foam activity assay. It was measured for different concentrations of saponins in a buffer solution. The foam activity of numerous other saponins was also determined, resulting in the most comprehensive overview of the foam activities of individual saponins.In addition to these isolation and characterization activities, an LC‐MS/MS method of performing simultaneous quantitative analyses of all the obtained sugar beet saponins was developed and validated. These were quantified in several sugar beet varieties (root and leaves), different sugar beet compartments, and side streams originating during the sugar beet converting process. Great variations in mass fractions were found in these materials, ranging from 862 mg/kg to 2,452 mg/kg for the various sugar beet root varieties and from 907 mg/kg to 5,398 mg/kg for the sugar beet leave varieties. Sugar beet fiber was identified as the best saponin source, with a total saponin quantity of 12.7 g/kg, followed by dried sugar beet pulp, with a total quantity of 10.3 g/kg. As a by‐product stream, dried sugar beet pulp is highly suitable for the sustainable manufacture of saponins.The results obtained are of key significance to the utilization of sugar beet saponins as well as saponins extracted from other plant materials or by‐product streams for use as food additives.

The potential of metabolomics in meat science: Current applications, trends, and challenges

Metabolites are the final products of metabolism and provide insights into the biochemical balance of tissue systems. A cascade of reactions involving proteins, carbohydrates, and lipids affects meat color, tenderness, and flavor, specifically, metabolites that are key biomolecules in biochemical reactions associated with attainment of acceptable meat quality. Bioinformatics platforms, such as Kyoto Encyclopedia of Genes and Genomes (KEGG) databases and MetaboAnalyst, are utilized to help understanding the role of differentially abundant metabolites and characterizing their roles in cellular function/metabolism. However, the inability to identify all metabolites using a single platform and limited metabolite libraries specifically for meat/food remains a challenge. Therefore, the advances in metabolite separation, easy-to-use data processing, increased resolution of mass-spectrometry, and data analysis will help to make inferences or develop biomarkers related to meat quality. This review discusses how metabolomics can be exploited to characterize meat quality, the challenges, and current trends. SignificanceMetabolites play an important role in attaining consumer-preferred meat quality traits and nutritive value of foods. Visual appearance of fresh foods, such as muscle foods, are utilized by consumers to assess the quality at the retail market before making purchases. Similarly, tenderness and flavor of meats influence eating satisfaction and re-purchase decisions. Inconsistencies in meat quality lead to enormous economic losses to the food industry. For instance, consumers often associate a bright-cherry red color with freshness, and the US beef industry loses $3.74 billion annually due to discoloration during storage. Both pre-and post-harvest factors influence the extent of meat quality changes. Metabolomics offer robust tools to get a snapshot of small molecules such as acids, amino acids, glycolytic- and tricarboxylic acids, fatty acids, and sugars present in post-mortem muscle tissue and their role in meat quality. Further, using bioinformatics platforms enables characterizing the role of differentially present metabolites in meat quality as well as identifying biomarkers for desirable quality traits such as tender meat or color-stable carcasses. Innovative applications of metabolomics can be exploited to elucidate the underpinnings of meat quality and to develop novel strategies to enhance marketability of retail fresh meats.

Review: Meat the Future, by Liz Marshall

Review: <i>Meat the Future</i>, by Liz Marshall

Semi-automated technique for bovine skeletal muscle fiber cross-sectional area and myosin heavy chain determination.

Myosin heavy chain (MyHC) type and muscle fiber size are informative but time-consuming variables of interest for livestock growth, muscle biology, and meat science. The objective of this study was to validate a semi-automated protocol for determining MyHC type and size of muscle fibers. Muscle fibers obtained from the longissimus and semitendinosus of fed beef carcasses were embedded and frozen within 45 min of harvest. Immunohistochemistry was used to distinguish MyHC type I, IIA, and IIX proteins, dystrophin, and nuclei in transverse sections of frozen muscle samples. Stained muscle cross sections were imaged and analyzed using two workflows: 1) Nikon workflow which used Nikon Eclipse inverted microscope and NIS Elements software and 2) Cytation5 workflow consisting of Agilent BioTek Cytation5 imaging reader and Gen5 software. With the Cytation5 workflow, approximately six times more muscle fibers were evaluated compared to the Nikon workflow within both the longissimus (P < 0.01; 768 vs. 129 fibers evaluated) and semitendinosus (P < 0.01; 593 vs. 96 fibers evaluated). Combined imaging and analysis took approximately 1 h per sample with the Nikon workflow and 10 min with the Cytation5 workflow. When muscle fibers were evaluated by the objective thresholds of the Cytation5 workflow, a greater proportion of fibers were classified as glycolytic MyHC types, regardless of muscle (P < 0.01). Overall mean myofiber cross-sectional area was 14% smaller (P < 0.01; 3,248 vs. 3,780) when determined by Cytation5 workflow than when determined by Nikon workflow. Regardless, Pearson correlation of mean muscle fiber cross-sectional areas determined by Nikon and Cytation5 workflows was 0.73 (P < 0.01). In both workflows cross-sectional area of MyHC type I fibers was the smallest and area of MyHC type IIX fibers was the largest. These results validated the Cytation5 workflow as an efficient and biologically relevant tool to expedite data capture of muscle fiber characteristics while using objective thresholds for muscle fiber classification.

(Mis)Understandings in Research Methodology and Chemometrics in Meat Science

(Mis)Understandings in Research Methodology and Chemometrics in Meat Science

Association of the MC4R gene with growth traits and meat quality in Colombian hair sheep.

The objective of this study was to associate the 1016G > A variant of the melanocortin-4 receptor gene with lamb's weight, growth, and meat quality in the Colombian hair sheep breed. A total of 168 lambs, weights were measured at birth weight (BW), at weaning adjusted weaning weight (AWW), at 6 months [adjusted weight (AW180)], at slaughter adjusted slaughter weight (ASW), daily weight gain preweaning daily gain (preWDG), and postweaning daily gain (postWDG) weaning, and after slaughter, pH, texture, and cook-loss (CL) in the longissimus thoracis et lumborum (LTL) muscle according to the American Meat Science Association methodology. The 1016G > A genotypes were obtained by sequencing. Genotypic and allele frequencies, heterozygosities, and Hardy-Weinberg equilibrium (HWE) were estimated. Using a generalized linear model, the genotype and the allelic substitution effect were associated with the evaluated traits. The heterozygous genotype (0.48) and G allele (0.61) were the most frequent. Heterozygosities were similar (0.47), indicating HWE. The genotype affected the BW (p < 0.05), with a higher value for the GG genotype (2.69 kg). AWW (12.75 kg), AW180 (19.67 kg), and ASW (31.21 kg) weights and daily weight gain (preWDG = 115.41 gm; postWDG = 96.16 gm) were not associated. Average pH, Warner-Bratzler shear force, and CL were 5.75 units, 49.46 N, and 32.02%, with no genotype effect. The G > A substitution only affected BW at -388 gm (p < 0.05). The 1016G > A variant is polymorphic and affects the BW but not other growth traits or the meat quality of the LTL muscle.