The aim of this study was to investigate the influence of microwave drying on the protein quality of japonica sorghum following an intermittent drying test. Using label-free technology and liquid chromatography-tandem mass spectrometry for proteomic analysis, the effects of microwave drying on sorghum differential protein expression, functional classification, and metabolic pathways were analyzed at the molecular level. After sorghum was dried using a microwave, 85 differential proteins were identified. Among them, 51 showed up-regulated expression while 34 had down-regulated expression. The up-regulation and down-regulation of differential protein expressions significantly changed them, and proteins with larger up-regulated and downregulated expressions were postulated to affect biological and metabolic processes of sorghum during subsequent processing. Differential proteins were significantly (P ˂ 0.01) involved in metabolic pathways, such as carbon metabolism, glycolysis/ gluconeogenesis, carbon fixation in photosynthetic organisms, biosynthesis of amino acids, amino sugar and nucleotide sugar metabolism, and the TCA cycle. For the protein interaction network, glyceraldehyde-3-phosphate dehydrogenase of the downregulated proteins was postulated to be the key factor affecting the entire metabolic system or signal transduction pathway. Up-regulated proteins, including phosphoglycerate mutase and phosphopyruvate hydratase, as well as down-regulated proteins such as glyceraldehyde-3-phosphate dehydrogenase and fructose-bisphosphate aldolase, not only directly or indirectly affected a variety of metabolic processes, but were specifically closely related to glycolysis and glycometabolism. Overall, this study showed that among the related metabolic pathways, differential protein changes in glycometabolism pathways may have the greatest impact on metabolic processes. The research results discussed herein can provide theoretical support for the industrial application of microwave drying and deep processing of sorghum.
This paper explores the gray system theory and mathematical morphology in image edge detection and target recognition applications. Through experiments that ingenious combination of the gray system theory and mathematical morphology, the use of gray system theory to extract the edge of the image for the conditions, the multi-level geodetic expansion to expand to fill the target area, through which the algorithm can improve the detection of image accuracy, enhanced noise immunity, effectively identify the target.
By means of ANSYS analysis platform, base conditions in the same , static analysis > thermostructure analysis and thermo-mechanical coupled analysis were carried out for indexable turning tools designed.By longitudinal individual analysis and the overall lateral comparative analysis of simulation results, get the deformation and stress changes law of turning tools under different conditions.From the point of view of deformation and stress, it can be obtained that temperature has an important influence on tool life.Under certain conditions, There is a reasonable tool overhang to make the maximum deformation and maximum stress are smaller.
Purchasing plays an important role in the logistics management. Since the price of materials fluctuates constantly, to revise the formulated material purchasing strategy timely is a necessary procedure to reduce the operating cost. This paper proposes a method to find the revising purchasing quantity of the original strategy in the price fluctuating situation. This method combines with the idea of the financial risk measurement technique of CVaR under the assumption that the decision maker is the type of risk aversion. This paper proves the effectiveness of the method and verifies it with an application case.
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