NIR Calibrations for Soybean Seeds and Soy Food Composition Analysis: Total Carbohydrates, Oil, Proteins and Water Contents

Conventional chemical analysis techniques are expensive, time consuming, and often destructive. The non-invasive Near Infrared (NIR) technology was introduced over the last decades for wide-scale, inexpensive chemical analysis of food and crop seed composition (see Williams and Norris, 1987; Wilcox and Cavins, 1995; Buning and Diller, 2000 for reviews of the NIR technique development stage prior to 1998, when Diode Arrays were introduced to NIR). NIR spectroscopic measurements obey Lambert and Beer’s law, and quantitative measurements can be successfully made with high speed and ease of operation. NIR has been used in a great variety of food applications. General applications of products analyzed come from all sectors of the food industry including meats, grains, and dairy products (Shadow, 1998)

NIR Calibrations for Soybean Seeds and Soy Food Composition Analysis: Total Carbohydrates, Oil, Proteins and Water Contents [v.2]

Conventional chemical analysis techniques are expensive, time consuming, and often destructive. The non-invasive Near Infrared (NIR) technology was introduced over the last decades for wide-scale, inexpensive chemical analysis of food and crop seed composition (see Williams and Norris, 1987; Wilcox and Cavins, 1995; Buning and Diller, 2000 for reviews of the NIR technique development stage prior to 1998, when Diode Arrays were introduced to NIR). NIR spectroscopic measurements obey Lambert and Beer’s law, and quantitative measurements can be successfully made with high speed and ease of operation. NIR has been used in a great variety of food applications. General applications of products analyzed come from all sectors of the food industry including meats, grains, and dairy products (Shadow, 1998).
Novel NIR calibrations for rapid, reliable and accurate composition analysis of a variety of several soy based foods and bulk soybean seeds were developed and validated in a six-year collaborative project with a large number of different samples (N >~12, 000). The availability of such calibrations is important for establishing NIR as a secondary method for composition analysis of foods and soybeans both in applications and fundamental research

A Statistical Approach to Estimating Adsorption-Isotherm Parameters in Gradient-Elution Preparative Liquid Chromatography

Determining the adsorption isotherms is an issue of significant importance in preparative chromatography. A modern technique for estimating adsorption isotherms is to solve an inverse problem so that the simulated batch separation coincides with actual experimental results. However, due to the ill-posedness, the high non-linearity, and the uncertainty quantification of the corresponding physical model, the existing deterministic inversion methods are usually inefficient in real-world applications. To overcome these difficulties and study the uncertainties of the adsorption-isotherm parameters, in this work, based on the Bayesian sampling framework, we propose a statistical approach for estimating the adsorption isotherms in various chromatography systems. Two modified Markov chain Monte Carlo algorithms are developed for a numerical realization of our statistical approach. Numerical experiments with both synthetic and real data are conducted and described to show the efficiency of the proposed new method.Comment: 28 pages, 11 figure

High-Order Calibration and Data Analysis in Chromatography

Multiway data analysis and tensorial calibration are gaining widespread acceptance with the rapid development of multichannel chromatographic instruments. By combining chromatographic techniques with chemometrics based on high-order calibration methods, some traditional problems in analysis, such as complicated pretreatment steps, long elution times, or even worse analysis results, can be avoided/improved. This chapter presents an overview from second-order to third-order data that cover theories and applications together with corresponding data processing in chromatography

Kinetic Intersections as a Source of Information on Rate Coefficients

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The TRIZ-CBR synergy: A knowledge based innovation process

Today innovation is recognised as the main driving force in the market. This complex process involves several intangible dimensions, such as creativity, knowledge and social interactions among others. Creativity is the starting point of the process, and knowledge is the force that transforms and materialises creativity in new products, services and processes. In this paper a synergy that aims to assists the innovation process is presented. The synergy combines several concepts and tools of the theory of inventive problem solving (TRIZ) and the case-based reasoning (CBR) process. The main objective of this synergy is to support creative engineering design and problem solving. This synergy is based on the strong link between knowledge and action. In this link, TRIZ offers several concepts and tools to facilitate concept creation and to solve problems, and the CBR process offers a framework capable of storing and reusing knowledge with the aim of accelerating the innovation process