Analysis and classification of coffee beans using single coffee bean mass spectrometry with machine learning strategy.

Coffee is a daily essential, with prices varying based on taste, aroma, and chemical composition. However, distinguishing between different coffee beans is challenging due to time-consuming and destructive sample pretreatment. This study presents a novel approach for directly analyzing single coffee beans through mass spectrometry (MS) without the need for sample pretreatment. Using a single coffee bean deposited with a solvent droplet containing methanol and deionized water, we generated electrospray to extract the main species for MS analysis. Mass spectra of single coffee beans were obtained in just a few seconds. To showcase the effectiveness of the developed method, we used palm civet coffee beans (kopi luwak), one of the most expensive coffee types, as model samples. Our approach distinguished palm civet coffee beans from regular ones with high accuracy, sensitivity, and selectivity. Moreover, we employed a machine learning strategy to rapidly classify coffee beans based on their mass spectra, achieving 99.58% accuracy, 98.75% sensitivity, and 100% selectivity in cross-validation. Our study highlights the potential of combining the single-bean MS method with machine learning for the rapid and non-destructive classification of coffee beans. This approach can help to detect low-priced coffee beans mixed with high-priced ones, benefiting both consumers and the coffee industry.

Zinc Ion-Based Switch-on Fluorescence-Sensing Probes for the Detection of Tetracycline.

Tetracycline (TC) is an antibiotic that has been widely used in the animal husbandry. Thus, TC residues may be found in animal products. Developing simple and sensitive methods for rapid screening of TC in complex samples is of great importance. Herein, we demonstrate a fluorescence-sensing method using Zn2+ as sensing probes for the detection of TC. Although TC can emit fluorescence under the excitation of ultraviolet light, its fluorescence is weak because of dynamic intramolecular rotations, leading to the dissipation of excitation energy. With the addition of Zn2+ prepared in tris(hydroxymethyl)amino-methane (Tris), TC can coordinate with Zn2+ in the Zn2+-Tris conjugates to form Tris-Zn2+-TC complexes. Therefore, the intramolecular motions of TC are restricted to reduce nonradiative decay, resulting in the enhancement of TC fluorescence. Aggregation-induced emission effects also play a role in the enhancement of TC fluorescence. Our results show that the linear dynamic range for the detection of TC is 15-300 nM. Moreover, the limit of detection was ~7 nM. The feasibility of using the developed method for determination of the concentration of TC in a complex chicken broth sample is also demonstrated in this work.

Direct Mass Spectrometric Analysis of Semivolatiles Derived from Real Samples at Atmospheric Pressure.

This study demonstrated a facile ionization method with the use of real samples for the ionization of their main compositions at ambient conditions for mass spectrometric analysis. Analyte ions derived from the real samples were readily observed in the mass spectrum when placing the samples close (≤1 mm) to the inlet of the mass spectrometer applied with a high voltage. No additional accessories such as an ionization emitter, a plasma generator, or a high voltage power supply were required for this approach. Ionization of semivolatiles derived from the samples occurred between the samples and the inlet of the mass spectrometer presumably owing to the dielectric breakdown induced by the electric field provided by the mass spectrometer. Real samples including plants, medicine tablets, and gloves with contaminants were used as the model samples. The putative ionization mechanisms are also discussed in this study.