Accurate and visualiable discrimination of Chenpi age using 2D-CNN and Grad-CAM++ based on infrared spectral images.

Dried tangerine peel ("Chenpi"), has numerous clinical and nutritional benefits, with its quality being significantly influenced by its storage age, referred to as "Chen Jiu Zhe Liang" in Chinese. Concequently, the rapid and accurate identification of Chenpi's age is important for consumers. In this study, Fourier transform infrared spectroscopy (FTIR) was employed to capture spectral images of Chenpi. These FTIR images were then analyzed using a two-dimensional convolutional neural networks (2D-CNN) model, achieving a discrimination accuracy of 97.92%. To address the "black box" nature of the 2D-CNN, Gradient-weighted Class Activation Mapping Plus Plus (Grad-CAM++) was utilized to highlight the important regions contributing to the model's performance. Additionally, six other machine learning models were developped using features identified by the 2D-CNN to validate their effectiveness. The results demonstrated that the combination of FTIR spectral images and 2D-CNN provides a highly effective method for accurately determining the age of Chenpi.

An accurate and reliable analytical strategy for simultaneous determination of target furanocoumarins and flavonoids in cosmetic and pharmaceutical samples by ultra-high performance supercritical fluid chromatography.

Furanocoumarins and flavonoids have various important biological activities and wide application. In the present study, a rapid and reliable supercritical fluid chromatography method was proposed for the separation of 10 target components including 8 furanocoumarins and 2 flavonoids. After detailed condition optimization, the 10 target compounds can be baseline separated on a Trefoil CEL1 (3.0 mm × 150 mm, 2.5 µm) column using gradient elution. A 0.07% (v/v) trifluoroacetic acid in ethanol was determined to be the most proper mobile phase for the separation of target compounds. The column temperature, back pressure, flow rate were set at 36 â„ƒ, 2000 psi, 1.0 mL min-1 to 1.4 mL min-1, respectively. The ten target compounds were analyzed within 24 min using the optimized conditions. Under the optimized conditions, all the target compounds showed good linearity with linear correlation coefficients higher than 0.995, and satisfactory recovery in the range of 83.52-112.92%. All these results showed that the developed ultra-high performance supercritical fluid chromatography method was reliable and effective. Finally, the application of the developed method to cosmetic, Psoraleae fructus and Angelicae dahuricae radix samples were presented. The results highlight the applicability of the ultra-high performance supercritical fluid chromatography method to the analysis of interested compounds in pharmaceutical and cosmetic samples.

A comparative study of three chemometrics methods combined with excitation-emission matrix fluorescence for quantification of the bioactive compounds aesculin and aesculetin in Cortex Fraxini.

Cortex Fraxini is an important traditional Chinese herbal medicine with various medical functions. Aesculin and aesculetin are the main effective components of Cortex Fraxini. The fluorescence signals of the two compounds have a high degree of overlap with each other, making quantitative analysis difficult with conventional analytical methods. In the present study, different chemometrics methods, including lasso regression (LAR), interval partial least squares (iPLS), and multidimensional partial least squares (N-PLS) methods, were employed and combined with excitation-emission matrix (EEM) fluorescence for the purpose of accurate quantification of aesculin and aesculetin in Cortex Fraxini samples. The most satisfactory results were obtained by using the N-PLS method based on the EEM spectra without scatterings, with correlation coefficient of calibration and prediction values higher than 0.9972 and 0.9962, respectively, root mean squared errors for calibration and prediction values lower than 0.0304 and 0.1165, respectively, and recovery values in the range of 83.32%-104.62%. The obtained credible models indicated that the N-PLS method combined with EEM spectra has the advantages of being green, low cost, and accurate and it is a good strategy for the determination of active compounds in complex samples. To further confirm the accuracy of the obtained results, the same samples were analyzed by the recognized ultra-performance liquid chromatography method.

A hybrid variable selection and modeling strategy for the determination of target compounds in different spectral datasets.

In this paper, a hybrid technique is proposed to establish quantitative models for the determination of target compounds in different spectral datasets. The proposed hybrid method is the hybridization of interval partial least squares (iPLS) method with gradient descent (GD) algorithm. Here, the novelty of the proposed method is that the iPLS method is applied to variable selection and the GD algorithm is employed to establish quantitative models based on the selected optimal variables. In the application of the hybrid iPLS-GD method, the factors, i.e., the number of the interval for the iPLS method and the learning rate, the number of iterations for the GD method, that affect the quantitative accuracy of the method are optimized and determined. Then three spectral datasets, including the near-infrared spectroscopy (NIR) dataset, nuclear magnetic resonance (1H NMR) dataset and excitation-emission matrix fluorescence (EEM) dataset, are used to test and verify the performance of the iPLS-GD method. We compare the hybrid iPLS-GD method with the PLS and iPLS methods from the aspects of modeling ability and predictive ability. The results demonstrated that the iPLS-GD method can be used as an effective and promising tool for the determination of target compounds in complex samples in practice.

Development and validation of ultra-high performance supercritical fluid chromatography method for quantitative determination of six compounds in Guizhi Fuling capsule and tablet samples.

A fast and simple ultra-high performance supercritical fluid chromatography method has been developed for the determination of six analytes, namely (paeonol, coumarin, cinnamic alcohol, cinnamic acid, paeoniflorin, and amygdalin) in Guizhi Fuling capsule and tablet samples. The influence of the key chromatographic parameters for the separation purposes was evaluated. The optimal column was Trefoil CEL1 column. The optimal mobile phase was a gradient mixture of carbon dioxide and methanol at flow rate of 1.0 mL/min. The back pressure of the system was set to 1.38 × 107  Pa and the temperature to 45°C. The six compounds were separated within 11 min by the proposed ultra-high performance supercritical fluid chromatography method with satisfactory resolution. Method validation confirmed that the procedure is accurate with the recovery rates from 87.04 to 104.30%, intraday precision values less than 4.81% and interday precision less than 5.22%, and linear with R2 higher than 0.9967. Therefore, this work provides a simple and novel method for the simultaneous analysis of six compounds in Guizhi Fuling capsule and tablet samples.