This report relates to the extensive consumer testing of sensory samples prepared from a number of previous MSA research collections, in particular, three Beef Information Nucleus (BIN) groups from which the collection is reported in L.EQT.1620.
Both contracts L.EQT.1720 and L.EQT.1809 relate to the sensory testing of these samples and for convenience are reported jointly as the product was intermixed for testing to better relate the source groups for statistical evaluation.
The projects were initiated to allow for further expansion and increased accuracy of the Meat Standards Australia (MSA) prediction model adding both new cut x cook combinations, further ageing data and extending the depth of data for combinations, which had not been tested for a considerable period and or had very low data volume in the AUSBlue database.
The projects have jointly met all objectives with the resulting data central to considerable expansion of the MSA prediction model with the new V2.0 version encompassing more than double (311) cut by cook combinations relative to the SP2009 version (169).
In addition to testing 26 additional muscle combination were cooked using new cook methods; Combi Oven moist heat roasting (COM) and Sous-Vide (SVD) cooking of diced product. In addition bone in cooking forms of ribs and osso bucco have been compared to boneless equivalents and data expanded considerably for slow cook/casserole (SC2), stir fry (SFR) and Yakiniku (YAK). Oyster blade have also been evaluated grilled in conventional and “flatiron” form.
The data, generated by 185 picks each utilising 60 consumers (11,100 consumers and 7,770 samples in total), has been processed to combine all available animal and processing history together with MSA grading data. The data was then forwarded to Dr Ray Watson and Dr Garth Tarr for statistical analysis related to both the individual trial outcomes and for inclusion in the data set utilised to develop the MSA V2.0 model.
The ensuing analysis has been progressively peer reviewed by the MSA Beef Pathways Committee over 18 months and a final model version approved for release.
The projects have dramatically expanded MSA prediction capability and represent a substantial step toward enabling the prediction of consumer satisfaction for any beef carcase portion cooked by alternative methods.
This basis is expected to add value to MSA based industry branding programs and increase revenue across the supply chain.