Evolution and impact of Smart Analytical Chemistry in non-destructive spectroscopy for food applications

Hussain C. M., Hussain G., KEÇİLİ R.

TrAC - Trends in Analytical Chemistry, vol.200, 2026 (SCI-Expanded, Scopus) identifier

  • Publication Type: Article / Review
  • Volume: 200
  • Publication Date: 2026
  • Doi Number: 10.1016/j.trac.2026.118832
  • Journal Name: TrAC - Trends in Analytical Chemistry
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Chemical Abstracts Core, Chimica, Compendex, EMBASE, DIALNET
  • Keywords: Artificial intelligence, Food safety, Green analysis, Machine learning, Non-destructive spectroscopy, Smart Analytical Chemistry, Sustainability
  • Anadolu University Affiliated: Yes

Abstract

This review critically explores the transformative evolution of Smart Analytical Chemistry (SAC) and its profound impact on the field of non-destructive spectroscopy for food analysis and safety. SAC represents a paradigm shift that integrates green, sustainable, and white analytical chemistry principles with intelligent technologies such as artificial intelligence (AI), machine learning (ML), automation, and miniaturized sensing platforms. This fusion enables the development of highly efficient, portable, eco-friendly, and real-time analytical systems tailored for complex food matrices. The review systematically examines the advancements in spectroscopy-based techniques, including near-infrared (NIR), mid-infrared (MIR), Raman, UV-Vis, fluorescence, and hyperspectral imaging and their smart adaptation for detecting contaminants, assessing authenticity, monitoring nutritional profiles, and ensuring food integrity without sample destruction. By highlighting the synergistic interplay between sustainability goals and technological innovation, this review offers a forward-looking perspective on how SAC is reshaping the landscape of modern food safety, traceability, and quality assurance.