Assessment of Different Measurement Methods Using 1H-NMR Data for the Analysis of the Transesterification of Vegetable Oils

Non-Invasive Methods for Predicting the Quality of Processed Horticultural Food Products, with Emphasis on Dried Powders, Juices and Oils: A Review

This review covers recent developments in the field of non-invasive techniques for the quality assessment of processed horticultural products over the past decade. The concept of quality and various quality characteristics related to evaluating processed horticultural products are detailed. A brief overview of non-invasive methods, including spectroscopic techniques, nuclear magnetic resonance, and hyperspectral imaging techniques, is presented. This review highlights their application to predict quality attributes of different processed horticultural products (e.g., powders, juices, and oils). A concise summary of their potential commercial application for quality assessment, control, and monitoring of processed agricultural products is provided. Finally, we discuss their limitations and highlight other emerging non-invasive techniques applicable for monitoring and evaluating the quality attributes of processed horticultural products. Our findings suggest that infrared spectroscopy (both near and mid) has been the preferred choice for the non-invasive assessment of processed horticultural products, such as juices, oils, and powders, and can be adapted for on-line quality control. Raman spectroscopy has shown potential in the analysis of powdered products. However, imaging techniques, such as hyperspectral imaging and X-ray computed tomography, require improvement on data acquisition, processing times, and reduction in the cost and size of the devices so that they can be adopted for on-line measurements at processing facilities. Overall, this review suggests that non-invasive techniques have the potential for industrial application and can be used for quality assessment.

Brown adipose tissue mapping in rats with combined intermolecular double-quantum coherence and Dixon water-fat MRI

Brown adipose tissue (BAT) is a promising therapeutic target in obesity studies. Recently, MRI has been proposed for the mapping of BAT. However, because of the limitation of spatial resolution, similar to the existing positron emission tomography and computed tomography techniques for BAT detection, it fails to distinguish BAT cells when they are mixed with other cells. In this work, a new MRI method is proposed, combining intermolecular double-quantum coherence and the chemical shift-encoded Dixon method. Its contrast depends on the water to fat ratio at the cellular scale, which is smaller than the imaging voxel size. The feasibility of this MRI method was shown with computer simulations and phantoms, and preliminary imaging of BAT of rats at 7 T. Both computer simulations and experimental results are consistent with theoretical predictions. The method provides a novel contrast mechanism and can map BAT distribution exclusively. In particular, a mixture of BAT cells and white adipose tissue cells was detected in an older rat, which was undetectable by other noninvasive methods. This method may be applicable to a wide range of uses in BAT-related studies, including the formation and variation of BAT.