食品発酵:プロセス分析技術のツールとしてのNIRスペクトル
Cristina Alamprese1, Silvia Grassi1
1Department of Food, Environmental and Nutritional Sciences (DeFENS), University of Milan, Milan, Italy.
Advances in food and nutrition research
|August 24, 2025
まとめ
近赤外線 (NIR) スペクトロスコピーは人工知能 (AI) と組み合わせて,食品発酵のリアルタイム監視を可能にします. この技術は食品の安全性,持続可能性,様々な発酵製品の品質管理を強化します.
科学分野:
- 食品科学と技術
- バイオテクノロジー
- 分析化学
背景:
- 発酵は食品システムの重要なプロセスで 栄養,安全性,持続可能性,感覚の質を向上させます
- 微生物の代謝を活用して保存し,消化性を高め,様々な種類の食品で生物活性化合物を生成します.
- 従来のモニタリング方法は手動で,リアルタイムデータがないため,プロセスの最適化が困難です.
研究 の 目的:
- 食品発酵のリアルタイムモニタリングと制御のために,高度なセンサー技術,特に近赤外線 (NIR) スペクトロスコピーの応用を探求する.
- インテリジェント発酵システムのための人工知能 (AI) とプロセス分析技術 (PAT) の統合を評価する.
- 伝統的な発酵監視技術の限界を解決する.
主な方法:
- 発酵過程の迅速かつ非侵襲的な分析のために,近赤外線 (NIR) のスペクトロスコーピーを利用した.
- 多変量データ分析と機械学習モデルを使用して,スペクトルデータを解釈し,発酵パラメータを予測しました.
- 飲料,乳製品,植物性食品,肉製品を含む様々な食品にこれらの方法を適用しました.
主要な成果:
- 機械学習と組み合わせたNIRスペクトロスコピーは 発酵の重要なパラメータを予測する上で 堅実なパフォーマンスを示しました
- この技術はアルコール飲料,乳製品,植物性食品,肉製品,パン,コムブチャ,などの様々な食品に有効であることが証明されました.
- 発酵パラメータの予測が成功すれば,プロセスの制御が強化される可能性がある.
結論:
- AIとPATを統合したNIRスペクトロスコピーは 食品発酵をリアルタイムで 制御するための強力なツールです
- スペクトルの複雑さや モデルの解釈能力といった課題は 説明可能なAIや デジタルツインのような高度な技術によって 解決されています
- この技術的進歩により 食品の発酵過程が より持続可能で 精密で効率的になり 工業的生産者や 職人生産者の両方に 利益をもたらしています
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