Rational flavor masking that suppresses human sensory receptors
味・香りの感知に関わる感覚受容体の反応を調べることで、目に見えない食品の風味を客観的・定量的な数値データ（デジタルデータ）として扱うことが可能です。代替肉開発の課題となる「オフフレーバーのマスキング」や「”肉らしさ”の風味評価」など、応用例とともに本技術をご紹介します。本プレゼンを聴講することで、科学的根拠に基づいておいしさを数値データ化し、AIで解析する、新しい食品開発の基礎知識が得られます。
By examining the responses of sensory receptors involved in perceiving taste and aroma, invisible food flavors can be handled as objective, quantitative numerical data (digital data). We present this technology alongside practical applications, such as "off-flavor masking" and "meatiness flavor evaluation," which are key challenges in alternative meat development. Attending this presentation provides foundational knowledge for new food product development that quantifies deliciousness as numerical data grounded in scientific evidence and analyzes it with AI.