Source: PURDUE UNIVERSITY submitted to
DEVELOPING A SIMPLE, NATURAL AND NOVEL PROCESSING STRATEGY TO IMPROVE BEEF QUALITY AND PROFITABILITY OF SMALL/MEDIUM-SIZED MEAT PROCESSORS
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
ACTIVE
Funding Source
Reporting Frequency
Annual
Accession No.
1030996
Grant No.
2023-67023-40289
Cumulative Award Amt.
$650,000.00
Proposal No.
2022-10350
Multistate No.
(N/A)
Project Start Date
Sep 15, 2023
Project End Date
Sep 14, 2027
Grant Year
2023
Program Code
[A1601]- Agriculture Economics and Rural Communities: Small and Medium-Sized Farms
Project Director
Kim, Y.
Recipient Organization
PURDUE UNIVERSITY
(N/A)
WEST LAFAYETTE,IN 47907
Performing Department
(N/A)
Non Technical Summary
Local livestock producers continue to encounter a lack of local slaughter capacity and high costs associated with processing services of local meat processors as major hurdles to meet the growing demand of locally-sourced meat products. Limited processing facilities and capabilities, such as small size carcass cooler and storage units, directly influence the high cost for processing service of local meats. Also, providing consistently high quality and wholesome meat products to local consumers is crucial to the continued success of the local, regional, and national meat sectors. Numerous studies have reported that consumers are willing to pay premiums for meat products with guaranteed eating quality. Consumers who shop in the local market generally have a high of expectation of local meat products for production-type related attributes (i.e. certified organic, grass-fed, and/or natural) and/or superior eating quality differences. Failure to meet this expectation due to quality-related issues will erode consumer satisfaction, and subsequently reduce profits for small/local processors over time. The ultimate goal of our research program is to establish novel post-harvest processing systems that can be easily applied to improve beef quality attributes and thus foster the profitability and sustainability of the local meat sectors. Our central hypothesis is that, through application of novel chemo-mechanical process, the palatability attributes of meat will be significantly improved by weakening of the muscle structure and cellular disruption. We will accomplish our overall objective by addressing the following research objectives: Specifically, we will first identify optimal chemo-mechanical processing regimen and document their impacts on eating quality attributes of different beef subprimals. Next, we will develop AI-driven prediction model to implement the chemo-mechanics manufacturing of various beef products for application of these findings across meat processors. Finally, we will evaluate the economic impacts of application of chemo-mechanical processing on local small/mid-size meat processors through cost-benefit analyses. The successful completion of the proposed research can be expected to lead to new avenues of understanding and applicable technologies that can be used to improve meat quality attributes as well as to enhance the overall value of under-utilized/under-valued fresh beef. Further, it will result in a considerable cost reduction for the local meat processors through accelerated processing throughput. This will, in turn, significantly and positively impact the profitability of the small-scale meat processors by increasing consumer confidence in improved meat quality and competitive costs.
Animal Health Component
30%
Research Effort Categories
Basic
50%
Applied
30%
Developmental
20%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
50333201000100%
Goals / Objectives
High costs and inconsistent/inferior meat quality attributes are two major hurdles to the growth of local/small- and mid-scale meat processors. The ultimate goal of our research program is to establish novel post-harvest processing systems that can be easily applied to improve beef quality attributes and thus foster the profitability and sustainability of the local meat sectors. Our central hypothesis is that, through application of novel chemo-mechanical process, the palatability attributes of meat will be significantly improved by weakening of the muscle structure and cellular disruption. We will accomplish our overall objective by addressing the following three specific research objectives:Objective 1: Characterize Chemo-Mechanical Processing Mechanisms to Identify Optimal Processing Regimen and Document Their Impacts on Eating Quality Attributes of Beef Subprimals from Bos Indicus Breed and Cull Cow.Objective 2: Develop Data-Driven Prediction Model, aided by Artificial Intelligence Algorithm, to Implement the Chemo-Mechanics Manufacturing of Various Beef Products for Application of These Findings Across Multiple Equipment and Meat Processors.Objective 3: Evaluate the Economic Costs and Benefits of Chemo-Mechanical Processing on the Local/Small- and Mid-Scale Meat ProcessorsThe successful completion of the proposed research will serve as a foundation and critical information for developing innovative template strategies to maximize positive aging impacts on meat quality and value. Consequently, knowledge generated will have immediate implications for making new discoveries that could be used not only to improve quality, future profitability, and sustainability of the local meat entities, but also to offer consumers more consistent high quality, yet economically priced meat products.
Project Methods
Objective 1: Characterize Chemo-Mechanical Processing Mechanisms to Identify Optimal Processing Regimen and Document Their Impacts on Eating Quality Attributes of Beef Subprimals from Bos Indicus Breed and Cull Cow. We will conduct two independent experiments to identify an optimal chemo-mechanical processing regimen by comparing various cumulative revolutions of tumbler and document its impacts on palatability attributes of various beef muscles from Bos indicus inheritance (experiment 1) and cull-cows (experiment 2). In both experiments, we will use three muscles - boneless strip loins, top sirloins, and top rounds. We will determine meat eating quality attributes as well as evaluate biochemical attributes including the extent of endogenous protease activities (e.g. calpain) upon chemo-mechanical processing and its concomitant impacts on muscle ultrastructural changes, myofibrillar protein degradation, and collagen solubility. We will also determine the impacts of chemo-mechanical activation on other important quality attributes including microbiological shelf-life, as well as display color and oxidative stability and release of nano-plasticizers to ensure the absence of any contaminants from packaging post-process. Upon completion of Objective 1, we will have identified the optimal chemo-mechanical activation regimen based on eating quality attributes of different beef muscles.Objective 2: Develop Data-Driven Prediction Model, aided by Artificial Intelligence Algorithm, to Implement the Chemo-Mechanics Manufacturing of Various Beef Products for Application of These Findings Across Multiple Equipment and Meat Processors. We will develop a transformative chemo-mechanical processing prediction model for practical adoptability for meat processor application. Based on collected data from Objective 1, with Artificial Intelligence (AI)-based Machine Learning approaches, we will develop models for optimizing processor-specific chemo-mechanical manufacturing system operations considering different subprimals types, size, weight, postmortem times, as well as different tumbling capacity across multiple equipment and each processor to maximize the process' efficacy, impacts and adoptability.Objective 3. Evaluate the Economic Costs and Benefits of Chemo-Mechanical Processing on the Local/Small- and Mid-Scale Meat Processors. Here we will evaluate the economic impacts of application of chemo-mechanical processing on local small/mid-size beef producers and meat processors through cost-benefit analyses. These analyses will include the cost saving calculation, operation costs, and premium revenues. We will also collect nationally representative survey data employed in econometrics modeling to identify local consumer willingness to pay under various market conditions.

Progress 09/15/23 to 09/14/24

Outputs
Target Audience:Target audiences will include major beef (meat) producers/processors, producer groups, retailers, and peer meat/food science researchers/students. Changes/Problems:As noted above, for the current reporting period (2023-2024), we were unable to initiate the main research objectives due to significantdelays in securing a graduate student and finalizing funding establishment at Purdue University. However, with the addition of anew PhDstudent (Sung-su Kim), to theproject team this fall, we have begun the cattle selection process for this late fall/spring (2024/2025) slaughter, followed byharvesting,processing, and further data collection. What opportunities for training and professional development has the project provided?As mentioned above, the new PhDstudent has just joined the program and has been actively involved in preparing the project initiation. Meanwhile, PI Kim's former MS student and a visiting scholar continuedon data analysis and further investigation of our previous fresh beef tumbling study in order to provide additional data set for developing a prediction model for the fresh beef tumbling application using AI-based Machine Learning tools. How have the results been disseminated to communities of interest?The project team is currently working on submitting a manuscript to a peer-reviewed journal. What do you plan to do during the next reporting period to accomplish the goals?The project team will work on the Objective 1 to determine the impact of fresh beef tumbling on beef tenderness development as proposed.

Impacts
What was accomplished under these goals? For the current reporting period (2023-2024), we were unable to initiate the main proposed research objectives primarily due to the considerable delays in securing a graduate student and finalizing funding establishment at Purdue University. However, since anew Phd student (Sung-su Kim) has joined the project team this fall, the project team has initiated the cattle selection process for this late fall/spring (2024/2025) slaughter, subsequent harvesting and processing, and further data collection. Meanwhile, during the reporting period, the PI and his former student continued on data analysis and further investigation of our previous fresh beef tumbling study in order to provide additional data set for developing a prediction model for the fresh beef tumbling application using AI-based Machine Learning tools. In the study, we determined the impacts of tumbling of individual beef steaks on tenderness and other quality attributes of beef loins with different quality grades. In two separate experiments, boneless strip loins (M. longissimus lumborum) were collected from 15 cattle (USDA Top Choice and Select grade) at 2 d and 3 d postmortem, respectively. The loins were divided into 7 equal sections, vacuum-packaged, and randomly assigned into combinations of 2 postmortem aging periods and 3 tumbling times (0, 20 and 60 min) along with non-tumbled aged only control. There was no negative impact on water-holding capacity (WHC) and color characteristics in both beef quality grades (p<0.05). In USDA Top Choice, tumbling duration and postmortem time affected myofibril fragmentation index (MFI) values, with 2d postmortem tumbled steaks showing higher MFI compared to non-tumbled steaks. Tumbling did not significantly affect Warner-Bratzler shear force (WBSF). Consumer panel evaluations revealed that 2d postmortem tumbled steaks had higher tenderness and overall liking scores compared to non-tumbled steaks (p<0.05). For USDA Select, non-tumbled steaks, regardless of tumbling duration, had higher WBSF values than tumbled steaks at the same postmortem time (p<0.05). MFI was significantly higher with increased postmortem time, but tumbling had minimal impact on MFI values. Consumer ratings did not show significant differences in tenderness or overall liking scores (p>0.05). Overall, these findings suggest that fresh beef tumbling can be a viable method for ensuring tenderness and shortening the aging process when applied early postmortem.

Publications