Using Sensory Wheels to Characterize Consumers' Perception for Authentication of Taiwan Specialty Teas

In the context of fair trade and protection of consumer rights, the aim of this study was to combat adulteration, counterfeiting, and fraud in the tea market, and rebuild the image of high-quality Taiwan teas. Experts at the Tea Research and Extension Station, Taiwan (TRES), are engaged in promotion of the systems of origin identification (AOC) and grading for authentication of Taiwan's premium teas. From tea evaluation competitions (bottom-up quality campaign), the flavor descriptions and consumers' perceptions were deconvoluted and characterized for the eight Taiwan specialty teas, namely, Bi-Luo-Chun, Wenshan Paochong, High-Mountain Oolong, Dongding Oolong, Tieh-Kuan-Yin, Red Oolong, Oriental Beauty, and Taiwan black tea. Then, according to the manufacturing processes, producing estates and flavor characters, the specialty teas were categorized into six sensory wheels. The flavor descriptors of the sensory wheels were also recognized in consumers' feedback. In recent years, the performance of international trade in tea also demonstrates that the policy guidelines for authentication of specialty teas are helpful to the production and marketing. Furthermore, the development of sensory wheels of Taiwan's specialty teas is the cornerstone to the establishment of the Taiwan-tea assortment and grading system (TAGs) for communication with the new generation consumers, enthusiasts, sellers, and producers.

Fatty Acids-Based Quality Index to Differentiate Worldwide Commercial Pistachio Cultivars

The fatty acid profiles of five main commercial pistachio cultivars, including Ahmad-Aghaei, Akbari, Chrok, Kalle-Ghouchi, and Ohadi, were determined by gas chromatography: palmitic (C16:0), palmitoleic (C16:1), stearic (C18:0), oleic (C18:1), linoleic (C18:2), linolenic (C18:3), arachidic (C20:0), and gondoic (C20:1) acid. Based on the oleic to linoleic acid (O/L) ratio, a quality index was determined for these five cultivars: Ohadi (2.40) < Ahmad-Aghaei (2.60) < Kale-Ghouchi (2.94) < Chrok (3.05) < Akbari (3.66). Principal component analysis (PCA) of the fatty acid data yielded three significant PCs, which together account for 80.0% of the total variance in the dataset. A linear discriminant analysis (LDA) model that was evaluated with cross-validation correctly classified almost all of the samples: the average percent accuracy for the prediction set was 98.0%. The high predictive power for the prediction set shows the ability to indicate the cultivar of an unknown sample based on its fatty acid chromatographic fingerprint.