Coffee is one of the top ten most adulterated foods. Coffee adulterations are mainly performed by mixing other low-value materials into coffee beans after roasting and grinding, such as spent coffee grounds, maize, soybeans and other grain products. The detection of adulterated coffee by high performance liquid chromatography (HPLC) is recognized as a targeted analytical method, which carbohydrates and other phenolic compounds are usually used as markers. However, the accurate qualitation and quantitation of HPLC analyses are time consuming. This study developed a chemometric analysis or called non-targeted analysis for coffee adulteration. The HPLC chromatograms were obtained by direct injection of liquid coffee into HPLC without sample preparation and the identification of target analytes. The distinction between coffee and adulterated coffee was achieved by statistical method. The HPLC-based chemometric provided more characteristic information (separated compounds) compared to photospectroscopy chemometric which only provide information of functional groups. In this study, green Arabica coffee beans, soybeans and green mung beans were roasted in industrial coffee bean roaster and then ground. Spent coffee ground was dried. Coffee and adulterants were mixed at different ratio before conducting HPLC analysis. Principal component analysis (PCA) toward HPLC data (retention time and peak intensity) was able to separate coffee from adulterated coffee. The detection limit of this method was 5%. Two models were built based on PCA data as well. The first model was used to differentiate coffee sample from adulterated coffee. The second model was designed to identify the specific adulterants mixed in the adulterated coffee. Various parameters such as sensitivity (SE), specificity (SP), reliability rate (RLR), positive likelihood (+LR) and negative likelihood (−LR) were applied to evaluate the performances of the designed models. The results showed that PCA-based models were able to discriminate pure coffee from adulterated sample (coffee beans adulterated with 5%–60% of soybeans, green mung beans or spent coffee grounds). The SE, SP, RLR, +LR and −LR for the first model were 0.875, 0.938, 0.813, 14.1 and 0.133, respectively. In the second model, it can correctly distinguish the adulterated coffee from the pure coffee. However, it had only about a 30% chance to correctly determine the specific adulterant out of three designed adulterants mixed into coffee. The SE, RLR and −LR were 0.333, 0.333 and 0.667, respectively, for the second model. Therefore, HPLC-based chemometric analysis was able to detect coffee adulteration. It was very reliable on the discrimination of coffee from adulterated coffee. However, it may need more work to tell discern which kind adulterant in the adulterated coffee.

The aim of this study was to investigate the physicochemical characteristics and volatile flavor of fried tilapia skins under three frying methods. Conventional deep-fat frying usually increases the oil content of the fried fish skin and leads to lipid oxidation, which reduces the product quality. Alternative frying methods, such as air frying for 6 and 12 min under 180 °C (AF6, and AF12) and vacuum frying at 0.085 MPa for 8 and 24 min under 120 °C (VF8, and VF24) were compared to conventional frying for 2 and 8 min under 180 °C (CF2, and CF8) for tilapia skin. Physical properties of fried skin, such as the moisture content, water activity, L* values and breaking force decreased under all frying methods, while the lipid oxidation and a*, b* values increased with the increase in frying time. In general, VF offered higher hardness of product compared to AF which had a lower breaking force. Especially AF12 and CF8 had the lowest breaking force, which indicated higher crispness. For the oil quality inside the product, AF and VF reduced conjugated dienes formation and retarded oxidation compared to CF. The results of the flavor compositions of fish skin measured using gas chromatography mass spectrometry (GC/MS) with solid phase microextraction (SPME) showed that CF obtained higher unpleasant oily odor (nonanal, 2,4-decadienal, etc.), while AF presented greater grilling flavor (pyrazine derivatives). Because fish skin fried by AF only relied on hot air, Maillard reaction derived compounds, such as methylpyrazine, 2,5-dimethylpyrazine, and benzaldehyde were the leading flavors. This made the aroma profiles of AF very different from VF and CF. Among all the approaches, AF and VF developed lower oil content, mild fat oxidation and better flavor attributes, which proves their practical applications for frying tilapia fish skin.

Seaweeds have a variety of biological activities, and their aromatic characteristics could play an important role in consumer acceptance. Here, changes in aroma compounds were monitored during microbial fermentation, and those most likely to affect sensory perception were identified. Ulva sp. and Laminaria sp. were fermented and generally recognized as safe microorganisms, and the profile of volatile compounds in the fermented seaweeds was investigated using headspace solid-phase microextraction with gas chromatography–mass spectrometry. Volatile compounds, including ketones, aldehydes, alcohols, and acids, were identified during seaweed fermentation. Compared with lactic acid bacteria fermentation, Bacillus subtilis fermentation could enhance the total ketone amount in seaweeds. Saccharomyces cerevisiae fermentation could also enhance the alcohol content in seaweeds. Principal component analysis of volatile compounds revealed that fermenting seaweeds with B. subtilis or S. cerevisiae could reduce aldehyde contents and boost ketone and alcohol contents, respectively, as expected. The odor of the fermented seaweeds was described by using GC–olfactometry, and B. subtilis and S. cerevisiae fermentations could enhance pleasant odors and reduce unpleasant odors. These results can support the capability of fermentation to improve the aromatic profile of seaweeds.