Optimization of taste and aroma evaluation achieved through AI × analytical instruments
本プレゼンテーションでは「AI×分光分析で実現する味・香り評価の最適化」をテーマに、専門家の経験に頼ってきた食品の官能評価や品質管理を、AIとセンシング技術でどう標準化・客観化できるかをご紹介します。分光分析×AIで味わいや品質を予測する「ProfilePrint」の仕組みを用いた、原料受入検査から製造工程管理、完成品評価までの活用事例を解説。あわせて、においセンサ×AIで香り・異臭をグループ分け、数値化する「MUI Robotics」の実装事例を紹介。聴講後には、自社の品質管理・製品開発に活かせる具体的な活用イメージをお持ち帰りいただけます。
Under the theme “Optimizing Taste and Aroma Evaluation with AI × Spectroscopic Analysis,” this presentation demonstrates how AI and sensing technologies can standardize and objectify food sensory evaluation and quality control, traditionally reliant on expert experience. It introduces real-world applications of ProfilePrint, a solution that combines spectroscopic analysis and AI to predict taste and quality, from raw material receiving inspection and process control to finished product evaluation. The session also presents MUI Robotics, which uses odor sensors and AI to classify and quantify aromas and off-odors. Attendees will gain practical ideas and insights applicable to their own quality control and product development activities.