Water-holding capacity (WHC) is an important quality trait in meat, that describe the ability of meat to withhold water. Low WCH may result in high drip loss during storage and processing, and will affect yield, production properties and sensorial properties (e.g. juiciness, tenderness). Thus, it is important to know what factors affect WHC through the value chain. However, no fundamental measuring techniques exist for WHC, making it difficult to measure and understand changes during processing, and to reveal and understand molecular mechanisms that influence WHC. Previous research has shown a link between WCH and protein structures in meat, and these may vary between animals and change during processing and storage. By applying rapid spectroscopic methods that may provide information related to changes in both proteins and water, one may achieve a better understanding of the molecular mechanisms that govern WCH, as well as contribute towards development of better measuring techniques for WCH. The goal of the project is to build new knowledge regarding factors affecting WHC, and to develop analytical methods to predict WHC for industrial use.
Much is known regarding various factors that may affect WHC, however the knowledge is fragmented. Several spectroscopic methods have been tested to measure WHC in meat; however, none of these were proven to be reliable and stable. Our approach is to combine results from several research fields to get a broader picture and understanding of what affects WHC, and help improve the precision of the spectroscopic methods.
The project will improve understanding of what affects WHC both in academia and the meat industry, and in addition stimulate the development of reliable online methods for measuring WCH in meat. More knowledge and good measuring tools will enable the Norwegian meat industry to optimize WHC and enable the possibility to perform quality sorting of meat. This will contribute towards improved meat quality and increased profitability within the meat industry.
The project group consists of two R&D-partners (Nofima and ARS USDA Meat Animal Research Center (MARC)) and five industry partners (Nortura, KLF, Fatland, Grilstad and Finsbråten). An extended project group with participants both from industry partners as well as Norwegian universities are important recipients of new knowledge developed in the project. Three fact sheets have been made and one workshop has been arranged to ensure transfer of knowledge, in addition to a demonstration of spectroscopic methods for measuring various meat quality traits.
The scientific activities in the project have been linked to three main activities: 1) model system for testing of spectroscopic methods, 2) analysis of spectroscopic and meat quality data from previous experiments performed by MARC, and 3) new industry trials in Norway and the US.
Model system: We have established a model system for meat proteins to assess how pH and protein degradation (proteolysis) affect the proteins, and to examine if these changes are detectable by spectroscopic techniques: NIR, Raman, FTIR and fluorescence. FTIR and Raman were better suited than fluorescence and NIR with respect to interpretation of results and for estimating changes in pH and proteolysis. The results have been published in 2 scientific articles in a peer-reviewed international journal.
Analysis of US data: Modelling of fat content, tenderness and purge/drip loss based on VISNIR-spectra has been conducted on 600 pigs from MARC. The results are weak, but this could be due to weaknesses in the experimental design.
US industry trial: Samples from more than 800 pigs were taken, and quality measurements as purge and tenderness were made. Protein analysis of a small selection of pigs shows that an increasing degree of proteolysis is contributing towards improved meat quality through reduced purge and more tender meat. In addition, we observed a relationship between WCH and tenderness, where high WHC correlated with more tender meat. Samples have also been analysed for protein composition, to investigate whether other changes in proteins may explain some of the variation seen in meat quality.
Norwegian industry trials: The goal has been to measure WCH using rapid spectroscopic techniques, and to study how pH and protein changes affect WCH. In the first trial, with sampling at two abattoirs, we found similar effects with spectroscopy as we found in the model system. In a new industry trial, in collaboration with Norsvin, we have sampled 122 pigs, and measured drip loss, pH, various spectroscopic measurements and protein degradation. Proteolysis does not appear to explain the variation in WCH as it did in the US trial. In summary, our results show that Raman may have a potential to be used for classification and/or sorting of meat based on both pH and WHC. The results have been published in 2 scientific articles in peer-reviewed international journals.
Water holding capacity (WHC) is one of the most important characteristics of meat, both in terms of quality (i.e. juiciness, tenderness, technological quality) and economy (i.e. yield). Thus there is a strong interest in optimising WHC of meat throughout the value chain.
The primary objective of the project is to build knowledge about biochemical and molecular mechanisms that govern WHC, and to develop analytical techniques and statistical models capable of monitoring these mechanisms. Secondary objectiv es include:
1. Improve knowledge about mechanisms governing WHC and the relationships between them
2. Develop rapid spectroscopic tools for monitoring the most important mechanisms
3. Gain knowledge about what affects the most important mechanisms
4. Tran sfer knowledge about WHC mechanisms and monitoring tools to industry and teaching institutions
Knowledge about biochemical and molecular mechanisms influencing WHC already exists, but data have not been combined and integrated to build a complete overvie w of factors governing this trait. Furthermore, while several spectroscopic techniques have been developed to measure WHC, none have established themselves as reliable. Our approach of using multivariate statistical methodology to combine data from these fields of science, will lead to a more complete overview of the underlying mechanisms and their interactions, and improve the precision of spectroscopic methods.
Critical R&D challenges are:
1) Unravel the complex relationships between biochemical and mo lecular mechanisms affecting WHC
2) Identify and develop spectroscopic methodology suitable for monitoring of the underlying mechanisms of WHC
3) Combine biochemical and molecular data with spectroscopic information in order to develop models describing W HC
It is anticipated that the project will improve the understanding of factors governing WHC within scientific communities and meat industry, and stimulate development of reliable online methods for measuring WHC.