A study of the relationships among acidity, sugar and furanic compound concentrations in set of casks for Aceto Balsamico Tradizionale of Reggio Emilia by multivariate techniques

Effect of wood on the phenolic profile and sensory properties of wine vinegars during ageing

“…Therefore, the vinegar substrate composition must explain the differences. Third, Masino et al (2005) observed that sugar degradation in traditional balsamic vinegar may also occur during ageing and that HMF formation is not limited to the step of must cooking. The results suggest that the degradation of the remaining sugars may explain the increase in HMF and 2-furfuraldehyde in balsamic vinegars obtained from cooked must.…”

A theoretical model to predict the age of traditional balsamic vinegar

“…Commercial value of TBV changes a lot with age and special prices are requested for very old vinegar (25 years old or older). Several authors have attempted to solve the problem focusing their efforts on analytical studies (Chiavaro, Caligiani, & Palla, 1988;Plessi, Monzani, & Coppini, 1989;Giudici, 1993;Giudici, Barbagallo, Altieri, & Masini, 1994;Zeppa, Giordano, Gerbi, & Meglioli, 2002;Masino, Chinnici, Franchini, Ulrici, & Antonelli, 2005;Muratore, Licciardello, Restuccia, Puglisi, & Giudici, 2006), chemiometric characterization (Consonni & Gatti, 2004;Cocchi, Bro et al, 2006;Durante, Cocchi, Grandi, Marchetti, & Bro, 2006); and physical measurements (Falcone, Chillo, Giudici, & Del Nobile, 2007). Unfortunately, the results have been very far from proving the vinegar authenticity or differentiating among vinegars of different ages.…”

Discrimination of Chinese traditional soy sauces based on their physico-chemical properties

“…The results were consistent with those obtained by the above CA (Figure 1). The contents of amino nitrogen were higher in samples 4,7,21,24,26,39,44,45,49,50 and 53 than in others of the same labels (Table 1). Therefore, the soy sauce samples of different ranks of the same labels could also be discriminated on the PC1 versus PC2 biplot.…”

“…Pattern recognition techniques have been widely applied to food chemistry, and the subject of food authenticity and quality control covers a wide range of products [4,5]. Multivariate calibration methods, such as cluster analysis (CA), principal component analysis (PCA), and linear discrimination analysis (LDA), K-nearest neighbor (KNN), soft independent modeling of class analogy (SIMCA), discrimination partial least squares (DPLS) and artificial neural networks (ANN) [6,7], are useful techniques for analyzing large and complex data which generally has many variables with different scales, and the combination of chemical analysis with chemometrics generally provides a powerful approach to quality control in food industry.…”