Rapid Determination of the Geographical Origin of Chinese Red Peppers (Zanthoxylum Bungeanum Maxim.) Based on Sensory Characteristics and Chemometric Techniques

Leaf traits of prickly ash and its correlation with ecological and geographical factors of origin

The morphological, physiological, and biochemical characteristics of leaves result from the long-term adaptation of plants to their environment and are closely related to plant growth and development. In this study, 37 prickly ash germplasm resources from 18 production areas were utilized as the subjects of research. Logistic equations, principal component analysis, and cluster analysis were employed to comprehensively evaluate the leaf traits of prickly ash germplasm resources, with an analysis of their correlation with ecological and geographical factors in the production areas. The results showed that the leaf traits of prickly ash germplasms of different origins are substantially different and diverse. The coefficient of variation for the 14 leaf traits was greater than 10%. The coefficient of variation of the compound leaflet number was the highest among all the considered leaf traits, and the coefficient of variation of leaf thickness was the lowest, at 49.86% and 11.37%, respectively. The leaf traits of the prickly ash germplasm originating from Chongqing in Yongchuan, Chongqing in Rongchang, and Yunnan in Honghe ranked highest, whereas the leaf traits of the prickly ash germplasm from Henan in Jiaozuo, Gansu in Tianshui, and Shanxi in Yuncheng ranked lowest. The results of the correlation analysis showed that among the ecological and geographical factors of the origins, latitude had the strongest correlation with the leaf traits of the prickly ash germplasm. As latitude increased, the leaves of prickly ash gradually decreased in size, weight, and leaf shape index. The factor with the second strongest correlation was temperature. The leaves of the prickly ash germplasm originating from warmer climate areas were larger and heavier than those from areas with colder climates. Altitude and longitude did not significantly affect the leaf traits of the prickly ash germplasm, but at similar latitudes, the leaves of the prickly ash germplasm in high-altitude areas were smaller, and the leaves of the prickly ash germplasm in low-altitude areas were larger. These findings can provide valuable references for breeding and the sustainable utilization of new varieties of prickly ash resources.

A Geographical Origin Classification of Durian (cv. Monthong) Using Near-Infrared Diffuse Reflectance Spectroscopy

The objective of this research was to classify the geographical origin of durians (cv. Monthong) based on geographical identification (GI) and regions (R) using near infrared (NIR). The samples were scanned with an FT-NIR spectrometer (12,500 to 4000 cm-1). The NIR absorbance differences among samples that were collected from different parts of the fruit, including intact peel with thorns (I-form), cut-thorn peel (C-form), stem (S-form), and the applied synthetic minority over-sampling technique (SMOTE), were also investigated. Models were developed across several classification algorithms by the classification learner app in MATLAB. The models were optimized using a featured wavenumber selected by a genetic algorithm (GA). An effective model based on GI was developed using SMOTE-I-spectra with a neural network; accuracy was provided as 95.60% and 95.00% in cross-validation and training sets. The test model was provided with a testing set value of %accuracy, and 94.70% by the testing set was obtained. Likewise, the model based on the regions was developed from SMOTE-ICS-form spectra, with the ensemble classifier showing the best result. The best result, 88.00FF% accuracy by cross validation, 86.50% by training set, and 64.90% by testing set, indicates the classification model of East (E-region), Northeast (NE-region), and South (S-region) regions could be applied for rough screening. In summary, NIR spectroscopy could be used as a rapid and nondestructive method for the accurate GI classification of durians.

Application of Multiple-Source Data Fusion for the Discrimination of Two Botanical Origins of Magnolia Officinalis Cortex Based on E-Nose Measurements, E-Tongue Measurements, and Chemical Analysis

Magnolia officinalis Rehd. et Wils. and Magnolia officinalis Rehd. et Wils. var. biloba Rehd. et Wils, as the legal botanical origins of Magnoliae Officinalis Cortex, are almost impossible to distinguish according to their appearance traits with respect to medicinal bark. The application of AFLP molecular markers for differentiating the two origins has not yet been successful. In this study, a combination of e-nose measurements, e-tongue measurements, and chemical analyses coupled with multiple-source data fusion was used to differentiate the two origins. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were applied to compare the discrimination results. It was shown that the e-nose system presented a good discriminant ability with a low classification error for both LDA and QDA compared with e-tongue measurements and chemical analyses. In addition, the discriminating capacity of LDA for low-level fusion with original data, similar to a combined system, was superior or equal to that acquired individually with the three approaches. For mid-level fusion, the combination of different principals extracted by PCA and variables obtained on the basis of PLS-VIP exhibited an analogous discrimination ability for LDA (classification error 0.0%) and was significantly superior to QDA (classification error 1.67-3.33%). As a result, the combined e-nose, e-tongue, and chemical analysis approach proved to be a powerful tool for differentiating the two origins of Magnoliae Officinalis Cortex.

Discriminant Analysis of the Geographical Origin of Asian Red Pepper Powders Using Second-Derivative FT-IR Spectroscopy

This study aimed to discriminate between the geographical origins of Asian red pepper powders distributed in Korea using Fourier-transform infrared (FT-IR) spectroscopy coupled with multivariate statistical analyses. Second-derivative spectral data were obtained from a total of 105 red pepper powder samples, 86 of which were used for statistical analysis, and the remaining 19 were used for blind testing. A one-way analysis of variance (ANOVA) test confirmed that eight peak variables exhibited significant origin-dependent differences, and the canonical discriminant functions derived from these variables were used to correctly classify all the red pepper powder samples based on their origins. The applicability of the canonical discriminant functions was examined by performing a blind test wherein the origins of 19 new red pepper powder samples were correctly classified. For simplicity, the four most significant variables were selected as discriminant indicator variables, and the applicable range for each indicator variable was set for each geographical origin. By applying the indicator variable ranges, the origins of the red pepper powders of all the statistical and blind samples were correctly identified. The study findings indicate the feasibility of using FT-IR spectroscopy in combination with multivariate analysis for identifying the geographical origins of red pepper powders.

Geographical origin discrimination of pepper (Capsicum annuum L.) based on multi-elemental concentrations combined with chemometrics

The concentrations of twenty-four elements in twenty-five peppers from three cultivated regions in Guizhou Province (China) were analyzed. The chemometric data processing, including one-way analysis of variance, principal component analysis, linear discriminant analysis (LDA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were executed to differentiate the peppers. Consequently, the contents of 16 elements (Arsenic, Ba, Cu, Co, Cr, Ni, Pb, Sn, Sb, Mo, Sr, Y, Zn, Ca, P, and Fe) were significantly different among the three regions (p < 0.05). The correct discrimination rates of 25 peppers were 92.0% for LDA and 96.0% for OPLS-DA. The variable importance in the projection (VIP) values were ranged from 1.063 to 1.262 for seven elements (Tin, Fe, Zn, Y, Cr, Sr, and Mo) indicating that they played an important role for the geographical origin traceability of pepper. To sum up, multi-element concentrations together with chemometric data-processing can be promising for the geographical origin differentiation of pepper.