藻類および水生植物のグリーン抽出法がアミノ酸組成と電子舌分析を用いた味覚検出に及ぼす影響

The growing demand for sustainable protein sources has increased interest in algae and aquatic plants as alternatives to animal-derived proteins. These resources are rich in protein, amino acids, and umami compounds but require suitable extraction methods to maximize yield and quality. This study compared three green extraction techniques-maceration (MAE, 80 °C, 2 h), ultrasound-assisted extraction (UAE, 750 W, 20 kHz, 50% amplitude, 35 °C, pH 12, 1 h), and enzyme-assisted extraction (EAE, 5% β-glucanase/flavourzyme, 55 °C, pH 6.5, 1 h)-on five raw materials: wakame (commercial seaweed), hair seaweed, sea lettuce, water silk algae, and Wolffia. The result revealed that both raw materials and extraction methods significantly (p < 0.05) affected protein yield, amino acid, physicochemical properties, and taste detection with e-tongue. Wolffia extracted by MAE yielded the highest protein overall, followed by UAE and EAE methods, when compared with commercial seaweed. The relationship between amino acid profiles and taste detection was investigated by principal component analysis (PCA) and hierarchical cluster analysis (HCA); the samples with higher glutamic and aspartic acids were linked with umami taste, while histidine contributed to bitter taste. Overall, the findings highlighted that extraction efficiency was influenced more by the extraction method-material compatibility than the raw material alone.