Rapid HPLC analysis of triacylglycerols by isocratic elution and light scattering detection

An HPLC method suitable for rapid triacylglycerol analysis by revers phase elution is describe. A Spherisorb column ( 15 cm x 4,6 mm I.D.) with 3 um particle size and C18 stationary phace with 12% carbon loading was used. Alution was scared out under isocratic conditions ( acetone, aceto nitrile and Diethyl ether were used as solvent mixure) and Light Scattering Detector was employed. In addition to being rapid ( 15 min for olive oil) the proposed method shows good repeatability and it may represent suitable technique to charaterize addible fact substances and to determine standards for quality control of fact containing foods

Screening of grated cheese authenticity by NIR spectroscopy

Parmigiano\u2013Reggiano (PR) cheese is one of the oldest traditional cheeses produced in Europe, and it is still one of the most valuable Protected Designation of Origin (PDO) cheeses of Italy. The denomination of origin is extended to the grated cheese when manufactured exclusively from whole Parmigiano-Reggiano cheese wheels that respond to the production standard. The grated cheese must be matured for a period of at least 12 months and characterized by a rind content not over 18%. In this investigation the potential of near infrared spectroscopy (NIR), coupled to different statistical methods, were used to estimate the authenticity of grated Parmigiano Reggiano cheese PDO. Cheese samples were classified as: compliance PR, competitors, non-compliance PR (defected PR), and PR with rind content greater then 18%. NIR spectra were obtained using a spectrophotometer Vector 22/N (Bruker Optics, Milan, Italy) in the diffuse reflectance mode. Instrument was equipped with a rotating integrating sphere. Principal Component Analysis (PCA) was conducted for an explorative spectra analysis, while the Artificial Neural Networks (ANN) were used to classify spectra, according to different cheese categories. Subsequently the rind percentage and month of ripening were estimated by a Partial Least Squares regression (PLS). Score plots of the PCA show a clear separation between compliance PR samples and the rest of the sample was observed. Competitors samples and the defected PR samples were grouped together. The classification performance for all sample classes, obtained by ANN analysis, was higher of 90%, in test set validation. Rind content and month of ripening were predicted by PLS a with a determination coefficient greater then 0.95 (test set). These results showed that the method can be suitable for a fast screening of grated cheese authenticity

Sugar Cane and Sugar Beet Molasses, Antioxidant-rich Alternatives to Refined Sugar

Molasses, the main byproduct of sugar production, is a well-known source of antioxidants. In this study sugar cane molasses (SCM) and sugar beet molasses (SBM) were investigated for their phenolic profile and in vitro antioxidant capacity and for their protective effect in human HepG2 cells submitted to oxidative stress. According to its higher phenolic concentration and antioxidant capacity in vitro, SCM exhibited an effective protection in cells, comparable to or even greater than that of α-tocopherol. Data herein reported emphasize the potential health effects of molasses and the possibility of using byproducts for their antioxidant activity. This is particularly important for consumers in developing countries, as it highlights the importance of consuming a low-price, yet very nutritious, commodity

Prediction of seasonal variation of butters by computing the fatty acids composition with artificial neural networks

The seasonal variation of the fatty acids composition of butters were investigated over three seasons during a 12-month study in the protected designation of origin Parmigiano-Reggiano cheese area. Fatty acids were analyzed by GC-FID, and then computed by artificial neural networks (ANN). Compared with spring and winter, butter manufactured from summer milk creams showed an optimal saturated/un-saturated fatty acids ratio (−8.89 and −5.79%), lower levels of saturated fatty acids (−2.63 and −1.68%) and higher levels of mono-unsaturated (+5.50 and +3.45%), poly-unsaturated fatty acids (+0.65 and +0.17%), and rumenic acid (+0.55 and +3.41%), while vaccenic acid had lower levels in spring and higher in winter (−2.94 and +2.91%). Moreover, the ANN models were able to predict the season of production of milk creams, and classify butters obtained from spring and summer milk creams on the basis of the type of feeding regimens. Practical applications: The investigation on variables that affect the milk fatty acids composition can improve the quality of milk across all systems, and the combination of chromatographic and computational techniques will ensure a secure traceability enabling producers to characterize dairy products