Black rice leaves (Oryza sativa L.) are a major part of rice straw left in open fields after rice harvest as agricultural waste. In this study, crude ethanolic extract (CEE) and various solvent fractions (hexane (Hex), ethyl acetate (EtOAc), n-butanol (n-BuOH), and aqueous fractions) of black rice leaves were investigated for their bioactive compound contents as well as antioxidant, anti-inflammatory, and anticancer activities. The results demonstrated that among all the fractions, the n-BuOH fraction presented the greatest contents of total phenolics and flavonoids, while anthocyanins were found to be abundant in the n-BuOH and aqueous fractions, which also exhibited powerful antioxidant abilities according to DPPH and ABTS radical-scavenging assays and a reducing power assay. Regarding anti-inflammatory activity, CEE and EtOAc reduced the production of NO and cytokine secretion (PGE₂, IL-6, and IL-1β) but displayed less effect on tumor necrosis factor α (TNF-α) release in lipopolysaccharide (LPS)-induced RAW 264.7 cells. They also significantly decreased iNOS and COX-2 protein expression. Additionally, the phenolics-rich ethyl acetate fraction showed the greatest activity against HepG2 liver carcinoma cells, inhibited cell growth, increased the Sub-G1 population, and induced apoptosis via mitochondrion-dependent mechanisms. In conclusion, black rice leaves, a byproduct of rice, exhibited strong antioxidant, anti-inflammatory, and anticancer capacities and might be useful for application in functional foods and the pharmaceutical industry.

A microfluidic distillation system is proposed to facilitate the separation and subsequent determination of propionic acid (PA) in foods. The system comprises two main components: (1) a polymethyl methacrylate (PMMA) micro-distillation chip incorporating a micro-evaporator chamber, a sample reservoir, and a serpentine micro-condensation channel; and (2) and a DC-powered distillation module with built-in heating and cooling functions. In the distillation process, homogenized PA sample and de-ionized water are injected into the sample reservoir and micro-evaporator chamber, respectively, and the chip is then mounted on a side of the distillation module. The de-ionized water is heated by the distillation module, and the steam flows from the evaporation chamber to the sample reservoir, where it prompts the formation of PA vapor. The vapor flows through the serpentine microchannel and is condensed under the cooling effects of the distillation module to produce a PA extract solution. A small quantity of the extract is transferred to a macroscale HPLC and photodiode array (PDA) detector system, where the PA concentration is determined using a chromatographic method. The experimental results show that the microfluidic distillation system achieves a distillation (separation) efficiency of around 97% after 15 min. Moreover, in tests performed using 10 commercial baked food samples, the system achieves a limit of detection of 50 mg/L and a limit of quantitation of 96 mg/L, respectively. The practical feasibility of the proposed system is thus confirmed.

A novel microfluidic ractopamine (RAC) detection platform consisting of a microfluidic RAC chip and a smart analysis device is proposed for the determination of RAC concentration in meat samples. This technology utilizes gold nanoparticles (AuNPs) modified with glutamic acid (GLU) and polyethyleneimine (PEI) to measure RAC concentration in food products. When RAC is present, AuNPs aggregate through hydrogen bonding, causing noticeable changes in their optical properties, which are detected using a self-built UV–visible micro-spectrophotometer. Within the range of 5 to 80 ppb, a linear relationship exists between the absorbance ratio (A_693nm/A_518nm) (Y) and RAC concentration (X), expressed as Y = 0.0054X + 0.4690, with a high coefficient of determination (R² = 0.9943). This method exhibits a detection limit of 1.0 ppb and achieves results within 3 min. The practical utility of this microfluidic assay is exemplified through the evaluation of RAC concentrations in 50 commercially available meat samples. The variance between concentrations measured using this platform and those determined via liquid chromatography–tandem mass spectrometry (LC-MS/MS) is less than 8.33%. These results underscore the viability of the microfluidic detection platform as a rapid and cost-effective solution for ensuring food safety and regulatory compliance within the livestock industry.

Introduction: Sorbic acid (SA) is widely applied as an antimicrobial preservative in processed foods, but its reliable determination remains difficult when complex matrices interfere with direct instrumental analysis. Conventional steam distillation can remove these interferences, although the procedure is time-consuming, equipment-intensive, and poorly suited for rapid or high-throughput food testing. Methods: Here, a poly(methyl methacrylate) (PMMA)-based microfluidic distillation system was developed for rapid sorbic acid separation prior to HPLC-PDA determination. The chip integrates a sample reservoir, buffer channel, condensation microchannel, and distillate collection zone within a compact, thermally controlled platform. Unlike earlier micro-distillation chips developed for formaldehyde, sulfur dioxide, or propionic acid, the present device introduces an SA-oriented vapor-buffering layout and a thermally separated condensation path. Numerical simulations guided the chip layout and thermal design, confirming stable heating and cooling zones at approximately 120 °C and 4 °C, respectively, with simulated temperatures differing from experimental measurements by less than 3%. Results: Operating parameters were optimized experimentally. Maximum distillation performance was obtained at a steam pressure of 4 bar, a distillation time of 30 min, and a condensation channel width of 2.5 mm, yielding distillation efficiencies close to 98%. Validation using sorbic acid standards from 50 to 2500 mg/L showed strong agreement with conventional steam distillation, with an R2 of 0.9964 and a mean relative accuracy of 95.68 ± 3.8%. Additional precision, device-to-device reproducibility, and matrix-effect tests confirmed acceptable repeatability and chip-to-chip consistency. Application to commercial food samples yielded relative accuracies of 92%–107% compared to the TFDA/CAAPIC reference workflow, with deviations below 8% and a limit of detection (LOD) of 60 mg/L. Discussion: The resulting platform establishes an SA-oriented micro-distillation pretreatment strategy that combines vapor-buffered chip design, simulation-guided thermal management, and complex-matrix validation for food safety analysis.