High-throughput phenotyping of nutritional quality components in sweet potato roots by near-infrared spectroscopy and chemometrics methods

Rapid discrimination and quantification of chemotypes in Perillae folium using FT-NIR spectroscopy and GC-MS combined with chemometrics

Perillae Folium (PF) is a well-known food and herb containing different chemotypes, which affect its quality. Herein, a method was proposed to classify and quantify PF chemotypes using gas chromatography-mass spectrometry (GC-MS) and Fourier transform-near infrared spectroscopy (FT-NIR). GC-MS results revealed that PF contains several chemotypes, including perilla ketone (PK) type, α-asarone (PP-as) type, and dillapiole (PP-dm) type, with the PK type being the predominant chemotype. Based on FT-NIR data, different chemotypes were accurately classified. The random forest algorithm achieved >90 % accuracy in chemotype classification. Furthermore, the main components of perilla ketone and isoegomaketone in PF were successfully quantified using partial least squares regression models, with prediction to deviation values of 3.76 and 2.59, respectively. This method provides valuable insights and references for the quality supervision of PF and other foods.

Effects of Steaming on Chemical Composition of Different Varieties of Purple-Fleshed Sweetpotato

Purple-fleshed sweetpotatoes (PFSPs) are rich in anthocyanins and are one of the health foods of interest. In this study, the effects of steaming on the anthocyanin, starch, soluble sugar, volatile organic compounds (VOCs) and pasting properties of nine PFSPs from China were investigated. The anthocyanin content of raw PFSP ranged from 9 to 185 mg/100 g. The total starch content decreased and soluble sugar content increased in all purple potatoes after steaming. Among the nine PFSPs varieties, Guangshu20 showed the greatest decrease in starch content (30.61%) and the greatest increase in soluble sugar content (31.12%). The pasting properties affected the taste of the PFSPs, with Shuangpihuang having the lowest peak viscosity (720.33 cP) and Guangzishu12 having the highest peak viscosity (2501.67 cP). Correlation studies showed that the anthocyanin content and pasting properties were negatively correlated with most of the sensory indicators, whereas the soluble sugar content of steamed PFSPs was significantly positively correlated with sweetness. A total of 54 VOCs were identified in this study, and aldehydes and terpenoids were the major VOCs in PFSPs. This study provides a theoretical basis for the processing of different PFSP varieties.

Fast quantitative analysis and chemical visualization of amylopectin and amylose in sweet potatoes via merging 1D spectra and 2D image

The quantitative analysis and spatial chemical visualization of amylopectin and amylose in different varieties of sweet potatoes were studied by merging spectral and image information. Three-dimensional (3D) hyperspectral images carrying 1D spectra and 2D images of hundreds of the samples (amylopectin, n = 644; amylose, n = 665) in near-infrared (NIR) range of 950-1650 nm (426 wavelengths) were acquired. The NIR spectra were mined to correlate with the values of the two indexes using a linear algorithm, generating a best performance with correlation coefficients and root mean square error of prediction (rP and RMSEP) of 0.983 and 0.847 g/100 mg for amylopectin, and 0.975 and 0.500 g/100 mg for amylose, respectively. Then, 14 % of the wavelengths (60 for amylopectin, 61 for amylopectin) were selected to simplify the prediction with rP and RMSEP of 0.970 and 1.103 g/100 mg for amylopectin, and 0.952 and 0.684 g/100 mg for amylose, respectively, comparable to those of full-wavelength models. By transferring the simplified model to original images, the color chemical maps were created and the differences of the two indexes in spatial distribution were visualized. The integration of NIR spectra and 2D image could be used for the more comprehensive evaluation of amylopectin and amylose concentrations in sweet potatoes.