A High-Frequency and Real-Time Ground Remote Sensing System for Obtaining Water Quality Based on a Micro Hyper-Spectrometer.

The safeguarding of scarce water resources is critically dependent on continuous water quality monitoring. Traditional methods like satellite imagery and automated underwater observation have limitations in cost-efficiency and frequency. Addressing these challenges, a ground-based remote sensing system for the high-frequency, real-time monitoring of water parameters has been developed. This system is encased in a durable stainless-steel shell, suited for outdoor environments, and features a compact hyperspectral instrument with a 4 nm spectral resolution covering a 350-950 nm wavelength range. In addition, it also integrates solar power, Wi-Fi, and microcomputers, enabling the autonomous long-term monitoring of water quality. Positioned on a rotating platform near the shore, this setup allows the spectrometer to quickly capture the reflective spectrum of water within 3 s. To assess its effectiveness, an empirical method correlated the reflective spectrum with the actual chlorophyll a(Chla) concentration. Machine learning algorithms were also used to analyze the spectrum's relationship with key water quality indicators like total phosphorus (TP), total nitrogen (TN), and chemical oxygen demand (COD). Results indicate that the band ratio algorithm accurately determines Chla concentration (R-squared = 0.95; RMSD = 0.06 mg/L). For TP, TN, and COD, support vector machine (SVM) and linear models were highly effective, yielding R-squared values of 0.93, 0.92, and 0.88, respectively. This innovative hyperspectral water quality monitoring system is both practical and reliable, offering a new solution for effective water quality assessment.

A colorimetric smartphone-based sensor for on-site AA detection in tropical fruits using Fe-P/NC single-atom nanoenzyme.

Ascorbic acid is one of the important vitamins to maintain human life activities and plays an irreplaceable role in regulating human redox metabolism. Fresh fruit can provide plenty of AA to maintain human metabolic balance. Thus, it is great significant to develop a rapid and convenient method for detection of AA to evaluate the freshness and nutritional quality of fruits. In this work, Fe single-atom nanoenzyme (Fe-SAN) based colorimetric sensor assisted with smartphone was designed for rapid and on-site AA detection in tropical fruits. Firstly, Fe-SAN with high oxidase-mimicking activity was synthesized by using green tea leaves as sources of carbon and nitrogen and NaH2PO2 as P source to obtain Fe-P/NC SAN, in which P was used to reconstruct the distribution of electronic to enhance the oxidase-mimicking activity of Fe-SAN. Besides, the as-synthesized Fe-P/NC SAN with remarkable oxidase-like activities could oxidize 3,3́,5,5́-tetramethylbenzidine (TMB) to blue colored oxidized TMB. AA could inhibit the oxidation of TMB, leading to blue fading. Based on the above principle, colorimetric sensor integrated with smartphone RGB mode was fabricated and exhibited a good linear detection range (0.5-100 µM) and low detection limit of 0.315 µM for AA detection under optimal conditions. More importantly, the developed sensor could rapidly and accurately detect AA in real sample, such as pineapple, wax apple and mango. Therefore, this research provides a new cost-effective method for the efficient and exact detection of AA in tropical fruit, which has a broad application prospect.