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This study aimed to develop a method based on hyperspectral imaging (400–1 000 nm) combined with chemometrics to identify the diverse geographical origins of Lycium barbarum fruit. Hyperspectral images of L. barbarum fruit from Ningxia, Gansu, Inner Mongolia, Qinghai and Xinjiang were acquired, and spectral data was extracted from the region of interest (ROI) by threshold segmentation method. Multiple preprocessing methods were employed to eliminate the interference information from the spectra, and the results showed that the discriminant model based on normalized reflectance spectrum (NR) exhibited better performance. Furthermore, the successive projection algorithm (SPA), competitive adaptive reweighted sampling (CARS), particle swarm optimization (PSO), iteratively retaining informative variables (IRIV), and CARS + IRIV were used to select characteristic wavelengths. The results showed that the simplified model based on the wavelengths selected by CARS + IRIV had the best performance. In the models ranging from binary to quintuple classifications, the selected characteristic wavelengths accounted for only 15.6% to 27.7% of the full spectra. The prediction accuracy was 97.7%, 90.9%, 89.2%, and 87.1%, respectively. In addition, a confusion matrix was employed to visualize the optimal simplified classification model in order to intuitively distinguish the classification categories. Satisfactory sensitivity, specificity and Kappa coefficients were obtained in classifying L. barbarum. The results illustrated that hyperspectral imaging technology combined with chemometric methods could effectively identify the geographical origin of L. barbarum and provide crucial technical support for the development of the L. barbarum industry.

This study explored the feasibility of applying visible and near-infrared (400?1 000 nm), and mid- and short-wave near infrared (900?1 700 nm) spectroscopy for detecting Camellia oleifera fruit with different degrees of natural mildew. The near infrared spectra of the equatorial shady and sunny sides, and the junction surfaces of samples with different degrees of mildew were collected in two wavelength bands. The average spectra were analyzed by principal component analysis (PCA), revealing that samples with different mildew degrees could be clustered into different groups, and the first and second principal components (PC1 and PC2) were effective in distinguishing the samples in each category. The full-spectrum partial least squares-discriminant analysis (PLS-DA) model based on the original spectra performed better than of its counterpart based on the preprocessed spectra. In the selection of characteristic wavelengths, successive projections algorithm (SPA) was found to be superior to PC loadings in establishing the simplified models for both spectral ranges. The correct classification rate and kappa coefficient were 84.4% and 0.766 7 for the prediction set, respectively. Based on the observation of confusion matrices for the prediction set, the specificities of the two optimal simplified models for the prediction of each degree of mildew were equivalent to each other and above 0.84. However, mid- and short-wave near infrared spectra in the wavelength range of 900–1 700 nm provided slightly higher sensitivity (0.72) in classifying samples with moderate degree of mildew. Our study showed that near-infrared spectroscopy could be used to detect the degree of natural mildew of C. oleifera fruit, and visible and near-infrared spectroscopy showed comparable results to mid- and short-wave near infrared spectroscopy. Considering its lower cost, visible and near-infrared spectroscopy has a better application prospect for real-time detection.

Single‐benzene fluorophores have attracted increasing interest owing to their simple molecular structure and unique photophysical properties. Developing novel single‐benzene fluorophores with facile synthesis, bright and tunable dual‐state emissions, and diversified functions is highly desirable. Herein, a strategy of controlling electron density on amino of 2,5‐diaminoterephthalates is proposed to modulate their dual‐state emission, acidichromism, Cu2+ detection, and lipid droplets (LDs) staining. A series of efficient dual‐state single‐benzene fluorophores based on 2,5‐diaminoterephthalate skeleton with tunable emissions in blue to red region and large Stokes shifts is facilely developed. The obtained fluorophores with various substituents on amino groups exhibit different acidichromism property. Two of fluorophores (ABB and ABM) with high electron density on amino groups exhibit high sensitivity and selectivity toward Cu2+ detection with a ratiometric and "turn‐off" fluorescence mechanism for ABM and ABB, respectively. The limit of detection for Cu2+ is determined to be 1.40 × 10−7 and 4.35 × 10−9 mol L−1 for ABB and ABM, respectively. Moreover, three of fluorophores (ABT, ABB, and ABM) with green to red emission display superior LDs‐targeting capability with high specificity, and brightness. This molecular design philosophy provides a new way of designing highly bright dual‐state fluorophores for practical applications. [ABSTRACT FROM AUTHOR]

Pharmaceutical contaminants are causing great attention for the public people, urgently requiring to be eliminated from the environment. Herein, commercial pharmaceutical carbamazepine was chosen as a model to be degraded by a heterogeneous Fenton system using natural pyrite as catalyst. The catalyst was characterized by X‐ray diffraction apparatus, high‐resolution transmission electron microscopy, and X‐ray photoelectron spectroscopy. The elements composition and chemical states of pyrite changed significantly after the Fenton reaction, which promoted the production of active species in the electron transfer process. The degradation efficiency of carbamazepine (2.5 mg/L) can reach 99.71% after 30 min with 0.3 g/L of pyrite and 5 mM of H2O2, respectively. The reaction system was suitable for a wide range of pH (3–9). The environmental adaptability examination of pyrite showed that humic acid (HA) had inhibitory effects on the degradation of carbamazepine. While the changes of degradation efficiency of carbamazepine were inconspicuous in the presence of NO3− and SO42−, indicating strong anti‐interference to environment common anions. Free‐radical capturers suggested that hydroxyl radical (∙OH), superoxide radical (∙O2−), and singlet oxygen (1O2) participated in the degradation of carbamazepine. This research has offered a new strategy of "treating wastes with wastes" to use pyrite to remove emerging pollutants. [ABSTRACT FROM AUTHOR]