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.

An overview of recent advances and applications of FT-IR spectroscopy for quality, authenticity, and adulteration detection in edible oils.

Authenticity and adulteration detection are primary concerns of various stakeholders, such as researchers, consumers, manufacturers, traders, and regulatory agencies. Traditional approaches for authenticity and adulteration detection in edible oils are time-consuming, complicated, laborious, and expensive; they require technical skills when interpreting the data. Over the last several years, much effort has been spent in academia and industry on developing vibrational spectroscopic techniques for quality, authenticity, and adulteration detection in edible oils. Among them, Fourier transforms infrared (FT-IR) spectroscopy has gained enormous attention as a green analytical technique for the rapid monitoring quality of edible oils at all stages of production and for detecting and quantifying adulteration and authenticity in edible oils. The technique has several benefits such as rapid, precise, inexpensive, and multi-analytical; hence, several parameters can be predicted simultaneously from the same spectrum. Associated with chemometrics, the technique has been successfully implemented for the rapid detection of adulteration and authenticity in edible oils. After presenting the fundamentals, the latest research outcomes in the last 10 years on quality, authenticity, and adulteration detection in edible oils using FT-IR spectroscopy will be highlighted and described in this review. Additionally, opportunities, challenges, and future trends of FT-IR spectroscopy will also be discussed.