Evaluation of on-site testing methods with a novel 3-in-1 miniaturized spectroscopic device for cinnamon screening

Principal component analysis-assisted zirconium-based metal-organic frameworks/DNA biosensor for the analysis of various phosphates

Considering the diversity of phosphates and their pivotal roles in physiological processes, detection of various phosphates related to their metabolism is urgent but challenging. Herein, we design a biosensor with zirconium-based MOFs (Zr-MOFs) and fluorophore-modified single-stranded DNA (F-ssDNA) for the analysis of phosphates. Relying on the interaction between Zr clusters and phosphate backbone, F-ssDNA is anchored on the surface of Zr-MOFs, inducing fluorescence resonance energy transfer (FRET) and subsequently quenching the fluorescence of F-ssDNA. Meanwhile, phosphates with different numbers of phosphate groups, molecular structures and coordination environments are able to adjust the FRET between Zr-MOFs and F-ssDNA via a site-occupying effect, recovering the fluorescence of F-ssDNA in distinct cases, which may result in diverse fluorescence signals. Consequently, seventeen phosphates and four phosphate mixtures are discriminated with the assistance of principal component analysis. These results provide new insight into the application of Zr-MOFs and broaden the path for the development of analytical methods for phosphates.

Differentiating True and False Cinnamon: Exploring Multiple Approaches for Discrimination

This study presents a comprehensive literature review that investigates the distinctions between true and false cinnamon. Given the intricate compositions of essential oils (EOs), various discrimination approaches were explored to ensure quality, safety, and authenticity, thereby establishing consumer confidence. Through the utilization of physical-chemical and instrumental analyses, the purity of EOs was evaluated via qualitative and quantitative assessments, enabling the identification of constituents or compounds within the oils. Consequently, a diverse array of techniques has been documented, encompassing organoleptic, physical, chemical, and instrumental methodologies, such as spectroscopic and chromatographic methods. Electronic noses (e-noses) exhibit significant potential for identifying cinnamon adulteration, presenting a rapid, non-destructive, and cost-effective approach. Leveraging their capability to detect and analyze volatile organic compound (VOC) profiles, e-noses can contribute to ensuring authenticity and quality in the food and fragrance industries. Continued research and development efforts in this domain will assuredly augment the capacities of this promising avenue, which is the utilization of Artificial Intelligence (AI) and Machine Learning (ML) algorithms in conjunction with spectroscopic data to combat cinnamon adulteration.