Quality Characteristics of Gluten–free Rice Batter with Addition of Transglutaminase according to Manufacturing Process

2020 ◽  
Vol 36 (02) ◽  
pp. 205-211
Author(s):  
Su-Kyung Ku ◽  
Hae In Yong ◽  
Tae-Kyung Kim ◽  
Hae Won Jang ◽  
Jung-Min Sung ◽  
...  
LWT ◽  
2021 ◽  
pp. 111426
Author(s):  
L. Marchetti ◽  
M.S. Acuña ◽  
S.C. Andrés

2017 ◽  
Vol 33 (2) ◽  
pp. 155-161 ◽  
Author(s):  
Xue-Ru Hai ◽  
Ji-Hyun Park ◽  
Ye-Na Heo ◽  
Min-Joo Kim ◽  
Gui-Seck Bae ◽  
...  

LWT ◽  
2021 ◽  
Vol 135 ◽  
pp. 109959
Author(s):  
Candela Paesani ◽  
Ángela Bravo-Núñez ◽  
Manuel Gómez

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 699
Author(s):  
Lixiang Wang ◽  
Wei Dai ◽  
Dongmei Sun ◽  
Yu Zhao

The quality of a manufacturing process can be represented by the complex coupling relationship between quality characteristics, which is defined by the directed weighted network to evaluate the risk of the manufacturing process. A multistage manufacturing process model is established to extract the quality information, and the quality characteristics of each process are mapped to nodes of the network. The mixed embedded partial conditional mutual information (PMIME) is used to analyze the causal effect between quality characteristics, wherein the causal relationships are mapped as the directed edges, while the magnitudes of the causal effects are defined as the weight of edges. The node centrality is measured based on information entropy theory, and the influence of a node is divided into two parts, which are local and indirect effects. Moreover, the entropy value of the directed weighted network is determined according to the weighted average of the centrality of the nodes, and this value is defined as the risk of the manufacturing process. Finally, the method is verified through a public dataset.


2018 ◽  
Vol 239 ◽  
pp. 679-687 ◽  
Author(s):  
Gianluca Giuberti ◽  
Gabriele Rocchetti ◽  
Samantha Sigolo ◽  
Paola Fortunati ◽  
Luigi Lucini ◽  
...  

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