Safeguarding Public Health: Advanced Detection of Food Adulteration Using Nanoparticle-Based Sensors.

Food adulteration, whether intentional or accidental, poses a significant public health risk. Traditional detection methods often lack the precision required to detect subtle adulterants that can be harmful. Although chromatographic and spectrometric techniques are effective, their high cost and complexity have limited their widespread use. To explore and validate the application of nanoparticle-based sensors for enhancing the detection of food adulteration, focusing on their specificity, sensitivity, and practical utility in the development of resilient food safety systems. This study integrates forensic principles with advanced nanomaterials to create a robust detection framework. Techniques include the development of nanoparticle-based assays designed to improve the detection specificity and sensitivity. In addition, sensor-based technologies, including electronic noses and tongues, have been assessed for their capacity to mimic and enhance human sensory detection, offering objective and reliable results. The use of nanomaterials, including functionalized nanoparticles, has significantly improved the detection of trace amounts of adulterants. Nanoparticle-based sensors demonstrate superior performance in terms of speed, sensitivity, and selectivity compared with traditional methods. Moreover, the integration of these sensors into food safety protocols shows promise for real-time and onsite detection of adulteration. Nanoparticle-based sensors represent a cutting-edge approach for detecting food adulteration, and offer enhanced sensitivity, specificity, and scalability. By integrating forensic principles and nanotechnology, this framework advances the development of more resilient food-safety systems. Future research should focus on optimizing these technologies for widespread application and adapting them to address emerging adulteration threats.

Improved organic and pesticide-free rice (Oryza sativa L.) authentication based on multiple stable isotope ratio analysis and rice milling state.

This study looked at the application of multiple bulk stable isotope ratio analysis to accurately authenticate organic rice and counteract organic fraud within the expanding global organic market. Variations of δ13C, δ15N, δ18O, and δ34S in organic, pesticide-free, and conventional rice were assessed across different milling states (brown, milled, and bran). Individual stable isotope ratio alone such as δ15N demonstrated limited capacity to correctly differentiate organic, pesticide-free, and conventional rice. A support vector machine model-incorporating δ13C, δ15N, δ18O, and δ34S in milled rice-yielded overall predictability (95%) in distinguishing organic, pesticide-free, and conventional rice, where δ18O emerged as the pivotal variable based on the feature weights in the SVM model. These findings suggest the potential of multi-isotope and advanced statistical approaches in combating organic fraud and ensuring authenticity in the food supply chain.

Comparative analysis of metabolite profiling and free radical scavenging activity in phenotypic variants of OsCOP1 colored rice mutant seed.

Interest in colored rice has been increasing due to its health benefits. This study examined the metabolite profiling of CONSTITUTIVELY PHOTOMORPHOGENIC 1 (COP1) mutated rice seed (yel-mutant). The wild-type (WT) and the yel-mutant having yellow (y)- and purple (p)-pericarp variants from Chucheong (cc) and Samkwang (sk) cultivars were investigated for differences in bioactive metabolite profiles and free radical scavenging activity. The total fatty acid content decreased by >50% in the yel-mutant against the WT, while no significant difference was observed between yellow- and purple-pericarp variants (p < 0.05). The yel-mutant of both cultivars showed significantly higher flavone contents than their WT (non-detected). Most of the metabolites examined were highly produced in the yel-cc-p and the yel-sk-y than in the other phenotypic variants studied. This study provides further useful information for colored rice breeding by revealing the detailed biofunctional metabolic profile under COP1 mutation in colored rice.