ABSTRACT
Nondestructive testing with sensor technology is one of the fastest growing and most promising wheat quality information analysis technologies. Nondestructive testing with sensor technology benefits from the latest achievement of many disciplines such as computer, optics, mathematics, chemistry, and chemometrics. It has the advantages of simplicity, speed, low cost, no pollution, and no contact. It is widely used in wheat quality analysis and testing research. This article summarizes nondestructive testing with sensor technology for wheat quality, including the mechanical model, hyperspectral technology, Raman spectroscopy, and near-infrared techniques for wheat mechanical properties, storage properties, and physical and chemical properties (such as moisture, ash, protein, and starch) in the past decade. Based on the current research progress, big data technology needs a lot of research in spectral data mining, modeling algorithm optimization, model robustness, etc. to provide more data support and method reference for the research and application of wheat quality.
ABSTRACT
The enzymatic hydrolyses of laser pretreated corn stover as a novel pretreatment method were examined to establish a simplified kinetic model for the complicated hydrolysis process. The time dependence of the total reducing sugars amount was closely related to the amounts of cellulosic materials and amounts of cellulase. The evaluated model fitted very well with the experimental data of enzymatic hydrolysis of laser pretreated corn stover under different conditions, including cellulase loading, nature of substrate, substrate loading in the reaction medium. The results indicated that the complex kinetics of cellulase enzymatic saccharification could be assessed with the fractal kinetic model. The cellulase enzymatic reaction process was effectively predicted and controlled with the kinetic model. The result showed that the model could effectively reflect dynamic process of enzyme hydrolysis.
