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A new characterization methodology for starch gelatinization
- Wu, Wei, Tao, Jinxuan, Zhu, Peitao, Liu, Hongsheng, Du, Qiliang, Xiao, Jie, Zhang, Wutong, Zhang, Shaobo
- International journal of biological macromolecules 2019 v.125 pp. 1140-1146
- computer vision, gelatinization, neural networks, process control, starch, temperature, uncertainty
- A gelatinization degree control system, with a combination of Artificial Neural Networks (ANNs) and computer vision, was successfully developed. An intelligent measurement framework was purposely designed to achieve a precise investigation on phase transition and morphology change of starch in real time, as well as a process control during gelatinization. Base on a variation of birefringence number, the degree of gelatinization (DG) control system provided a direct and fast methodology without subjective uncertainty in studying starch gelatinization. In the course, the whole system was a cascade structure with the hot-stage temperature chosen as the inner-loop parameter, thus the granule morphology and birefringence at different DG could be easily observed and compared in real time, and the relative transition temperature was simultaneously calculated.