Rapid profiling of Swiss cheese by attenuated total reflectance (ATR) infrared spectroscopy and descriptive sensory analysis.
The acceptability of cheese depends largely on the flavor formed during ripening. The flavor profiles of cheeses are complex and region- or manufacturer-specific which have made it challenging to understand the chemistry of flavor development and its correlation with sensory properties. Infrared spectroscopy is an attractive technology for the rapid, sensitive, and high-throughput analysis of foods, providing information related to its composition and conformation of food components from the spectra. Our objectives were to establish infrared spectral profiles to discriminate Swiss cheeses produced by different manufacturers in the United States and to develop predictive models for determination of sensory attributes based on infrared spectra. Fifteen samples from 3 Swiss cheese manufacturers were received and analyzed using attenuated total reflectance infrared spectroscopy (ATR-IR). The spectra were analyzed using soft independent modeling of class analogy (SIMCA) to build a classification model. The cheeses were profiled by a trained sensory panel using descriptive sensory analysis. The relationship between the descriptive sensory scores and ATR-IR spectra was assessed using partial least square regression (PLSR) analysis. SIMCA discriminated the Swiss cheeses based on manufacturer and production region. PLSR analysis generated prediction models with correlation coefficients of validation (rVal) between 0.69 and 0.96 with standard error of cross-validation (SECV) ranging from 0.04 to 0.29. Implementation of rapid infrared analysis by the Swiss cheese industry would help to streamline quality assurance.
Kocaoglu-Vurma
N A
NA
Dept. of Food Science and Technology, The Ohio State Univ., Columbus, OH 43210, USA.
Eliardi
A
A
Drake
M A
MA
Rodriguez-Saona
L E
LE
Harper
W J
WJ
D002611:Cheese / Q000032:analysis* / Q000145:classification; D045424:Complex Mixtures / Q000737:chemistry; D003258:Consumer Behavior; D005518:Food Preferences; D005524:Food Technology / Q000379:methods; D006801:Humans; D008962:Models, Theoretical; D015999:Multivariate Analysis; D009716:Numerical Analysis, Computer-Assisted; D025341:Principal Component Analysis; D011786:Quality Control; D012677:Sensation; D012984:Software; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*; D013223:Statistics as Topic
D045424:Complex Mixtures