Next-generation fluorescent and electrochemical sensors using biomass-derived CQDs

Ensuring food safety across complex supply chains requires rapid, sensitive, and field-deployable methods for detecting chemical contaminants, microbial hazards, and spoilage indicators in real food matrices. Biomass-derived carbon quantum dots (B-CQDs) offer a sustainable sensing platform because of their tunable photoluminescence, abundant surface functionalities, biocompatibility, and compatibility with low-cost synthesis. Distinct from reviews focused primarily on synthesis or fluorescent detection, this review establishes an integrated structure-property-performance framework linking biomass precursor composition, heteroatom doping, surface chemistry, and hybrid architecture to fluorescence, electrochemical, and photoelectrochemical sensing mechanisms. Applications to heavy metals, pesticides, veterinary drugs, synthetic dyes, adulterants, pathogens, and freshness markers are critically compared, together with CQD-MOF, CQD-MIP, and CQD-metal nanocomposites and their integration into smartphones, Internet-of-Things devices, and smart packaging. The analysis yields three principal conclusions. First, sensing performance is governed more strongly by controllable surface states and recognition interfaces than by biomass origin alone. Second, hybrid and ratiometric architectures can improve selectivity, signal reliability, and matrix tolerance through complementary recognition and internal-reference mechanisms, although these benefits depend on sensor design and may be accompanied by increased fabrication complexity. Third, the main barrier to practical deployment is no longer analytical sensitivity but batch reproducibility, mechanistic uncertainty, validation in complex foods, and regulatory compliance. Accordingly, future progress requires standardized synthesis and characterization protocols, migration and toxicity assessment, and data-driven optimization of precursor-structure-signal relationships. These insights define a practical roadmap for translating B-CQD sensors from laboratory demonstrations into reproducible, intelligent, and sustainable food-safety monitoring systems.