| Abstract
| - Ragusano cheeses were produced in duplicate from milk collected from pasture-fed and total mixedration (TMR)-fed cattle at four time intervals. The cheeses were subjected to chemical analysis,conventional sensory testing, and gas chromatography−olfactometry (GCO). Data from each typeof analysis were examined by principal component and factor analysis and by pattern recognition(SIMCA) to see if sufficient information for classification into pasture-fed and TMR-fed groups wascontained therein. The results clearly indicate that there are significant differences in sensory paneland chemical analysis results between the two cheeses. The data were also examined to see ifmodels of sensory responses as a function of analytical or GCO results or both could be constructedwith the modeling technique partial least-squares regression (PLS). Strong PLS models of somesensory responses (green and toasted odor; salt, pungent, bitter, and butyric sensations; and smoothconsistency) were obtained. Keywords: Modeling; composition to property modeling; sensory analysis; chemometrics; GCO;multivariate modeling
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