Discrimination of Trichosanthis Fructus from Different Geographical Origins Using Near Infrared Spectroscopy Coupled with Chemometric Techniques

Abstract

Near infrared (NIR) spectroscopy with chemometric techniques was applied to discriminate the geographical origins of crude drugs (i.e., dried ripe fruits of Trichosanthes kirilowii) and prepared slices of Trichosanthis Fructus in this work. The crude drug samples (120 batches) from four growing regions (i.e., Shandong, Shanxi, Hebei, and Henan Provinces) were collected, dried, and used and the prepared slice samples (30 batches) were purchased from different drug stores. The raw NIR spectra were acquired and preprocessed with multiplicative scatter correction (MSC). Principal component analysis (PCA) was used to extract relevant information from the spectral data and gave visible cluster trends. Four different classification models, namely K-nearest neighbor (KNN), soft independent modeling of class analogy (SIMCA), partial least squares-discriminant analysis (PLS-DA), and support vector machine-discriminant analysis (SVM-DA), were constructed and their performances were compared. The corresponding classification model parameters were optimized by cross-validation (CV). Among the four classification models, SVM-DA model was superior over the other models with a classification accuracy up to 100% for both the calibration set and the prediction set. The optimal SVM-DA model was achieved when C =100, γ = 0.00316, and the number of principal components (PCs) = 6. While PLS-DA model had the classification accuracy of 95% for the calibration set and 98% for the prediction set. The KNN model had a classification accuracy of 92% for the calibration set and 94% for prediction set. The non-linear classification method was superior to the linear ones. Generally, the results demonstrated that the crude drugs from different geographical origins and the crude drugs and prepared slices of Trichosanthis Fructus could be distinguished by NIR spectroscopy coupled with SVM-DA model rapidly, nondestructively, and reliably.

Advances in Near Infrared Spectroscopy and Related Computational Methods

“…However, for sake of clarity a tentative and brief overview of these contributions may be helpful to present the Special Issue to the readership. The majority of the articles focuses on applied qualitative and quantitative analyses in a variety of fields [9,11,12,[17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. Roughly, half of these may be associated with pharmaceutical and medical applications [17][18][19][20][21][22][23][24].…”

“…Roughly, half of these may be associated with pharmaceutical and medical applications [17][18][19][20][21][22][23][24]. Most of the remaining applied studies were directed at agricultural applications [25][26][27][28][29][30][31][32][33][34], well reflecting the ever-growing significance of NIR spectroscopy in this area; a good perspective of this topic is included in a focused review article published in the Special Issue [30]. Modern strategies for food analysis also rely on this technique, and few contributions touched that field as well [9,12,33,34].…”

Advances in Near-Infrared Spectroscopy and Related Computational Methods

“…The Special Issue has met a remarkably positive feedback with many contributions submitted by numerous scholars and professional spectroscopists performing their active research in academia and industry, resulting in a collection of 30 publications including two exhaustive review articles [7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36]. The diversity in the application field has been well represented by the submitted manuscripts.…”

“…However, for sake of clarity a tentative and brief overview of these contributions may be helpful to present the Special Issue to the readership. The majority of the articles focuses on applied qualitative and quantitative analyses in a variety of fields [9,11,12,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34]. Roughly, half of these may be associated with pharmaceutical and medical applications [17,18,19,20,21,22,23,24].…”

“…Roughly, half of these may be associated with pharmaceutical and medical applications [17,18,19,20,21,22,23,24]. Most of the remaining applied studies were directed at agricultural applications [25,26,27,28,29,30,31,32,33,34], well reflecting the ever-growing significance of NIR spectroscopy in this area; a good perspective of this topic is included in a focused review article published in the Special Issue [30]. Modern strategies for food analysis also rely on this technique, and few contributions touched that field as well [9,12,33,34].…”