Application of PLSR in correlating physical and chemical properties of pork ham with different cooling methods

Partial least squares regression (PLSR) was applied to understand the relationship between physical and chemical properties of pork leg ham with different cooling treatments, i.e., cold room, air blast and vacuum cooling. The results indicated that overall 69.8% variation of physical matrix was explained by chemical matrix. For the univariate analysis of physical attributes, the results showed that gumminess (88.1%) and hardness (86.5%) were best explained by chemical matrix, followed by springiness (78.7%), Warner–Bratzler Shear force (61.3%), and a* (60.0%). Graphical display of the regression coefficients indicated that different cooling treatments had different effects on the physical property of pork ham. Therefore, to predict the physical quality with chemical attributes, separate regression formulations should be adopted for different cooling methods. These findings have practical importance in attempts to predict physical properties from chemical components. In addition, they can also be used to control the physical properties by adjusting the components in the meat system.