scholarly journals Statistical Modelling of Gluten Production by Varying Mixing Time, Salt and Water Levels During Dough Mixing

2009 ◽  
Vol 5 (3) ◽  
Author(s):  
Dayang N Abang Zaidel ◽  
Nyuk L Chin ◽  
Yus Aniza Yusof ◽  
Russly Abdul Rahman ◽  
Roselina Karim
Keyword(s):  
Volume Expansion ◽  
Food Industry ◽  
Mixing Time ◽  
Statistical Modelling ◽  
Water Levels ◽  
Coefficient Of Determination ◽  
Dough Mixing ◽  
Modelling Studies ◽  
Main Factors ◽  
Central Composite

Gluten is widely discussed in dough and breadmaking subjects but the focus has not been on the production of gluten itself for usage and application in the food industry. This paper presents some modelling studies of gluten production using response surface methodology (RSM) by varying three main factors that contribute towards gluten formation during dough mixing, which are the mixing time, salt and water levels. The gluten produced was measured for its quantity in terms of wet and dry gluten contents and for quality, in terms of volume expansion of fried gluten and extensibility of gluten. Two wheat flour types, the strong and weak were used as comparison. The experiment was designed following a standard RSM design, known as the central composite design. The results of analysis of variance indicated that the proposed mathematical model obtained can adequately describe the production of gluten within the studied factor limits. The coefficient of determination, R2 of all the responses were higher than 0.80. Results show that salt gave the most significant effect (0.0001

Modelling response of infiltration loss toward water table depth using RBFN, RNN, ANFIS techniques

2021 ◽  
Vol 25 (2) ◽  
pp. 227-234
Author(s):  
Sandeep Samantaray ◽  
Abinash Sahoo
Keyword(s):  
Neural Network ◽  
Mean Square Error ◽  
Water Table ◽  
Environmental Sustainability ◽  
Model Development ◽  
Water Table Depth ◽  
Water Levels ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Inference System

Accurate prediction of water table depth over long-term in arid agricultural areas are very much important for maintaining environmental sustainability. Because of intricate and diverse hydrogeological features, boundary conditions, and human activities researchers face enormous difficulties for predicting water table depth. A virtual study on forecast of water table depth using various neural networks is employed in this paper. Hybrid neural network approach like Adaptive Neuro Fuzzy Inference System (ANFIS), Recurrent Neural Network (RNN), Radial Basis Function Neural Network (RBFN) is employed here to appraisal water levels as a function of average temperature, precipitation, humidity, evapotranspiration and infiltration loss data. Coefficient of determination (R2), Root mean square error (RMSE), and Mean square error (MSE) are used to evaluate performance of model development. While ANFIS algorithm is used, Gbell function gives best value of performance for model development. Whole outcomes establish that, ANFIS accomplishes finest as related to RNN and RBFN for predicting water table depth in watershed.

Modeling and Optimizing of Mechanically Agitated Vessels by Central Composite Rotatable Design Method

2011 ◽  
Vol 9 (1) ◽  
Author(s):  
Ramin Zadghaffari ◽  
Jafarsadegh Moghaddas ◽  
F. Fakheri ◽  
H. Razmi ◽  
H. Heidari
Keyword(s):  
Gas Flow ◽  
Design Method ◽  
Mixing Time ◽  
Central Composite Rotatable Design ◽  
Two Phase ◽  
Injection Point ◽  
Tracer Injection ◽  
Operating Variables ◽  
Central Composite ◽  
Rotatable Design

A central composite rotatable design (CCRD) methodology was used to analyze the effect of some operating variables on gas-liquid two phase mixing time in an agitated tank driven by dual 6-blade Rushton turbines. The variables chosen were the impellers rotational speed (x1), gas flow rate (x2), probe location (x3) and tracer injection point (x4). The mathematical relationship of mixing time on the four significant independent variables can be approximated by a nonlinear polynomial model. Predicted values were found to be in good agreement with the experimental values (R-sq of 95.9 percent and R-Sq (Adj) of 95.7 percent for response Y). This study has shown that central composite design could efficiently be applied for the modeling of mixing time, and it is an economical way of obtaining the maximum amount of information with the fewest number of experiments.

scholarly journals Customer Satisfaction, Product Quality and Performance of Companies

2015 ◽  
Vol 14 (4) ◽  
pp. 329-344 ◽  
Author(s):  
Petr Suchánek ◽  
Jiří Richter ◽  
Maria Králová
Keyword(s):  
Customer Satisfaction ◽  
Product Quality ◽  
Business Performance ◽  
Food Industry ◽  
Research Question ◽  
Financial Data ◽  
Main Factors ◽  
And Performance

Abstract This paper presents an analysis of quality, customer satisfaction and business performance in food industry. The main objective of the research is to determine the influence of quality on customer satisfaction and on business performance and competitiveness. In particular, this paper answers the following research question: Does the quality of a product result in a satisfied customer and thereby in a well-performing business? Customer satisfaction is defined as the satisfaction of the customer with a product and the business performance as a capability to generate profit. Therefore, satisfaction was examined by the means of a survey using questionnaires, and the performance was measured by financial data. We managed to find a correlation between the main factors, although partial results were due more factors mostly statistically insignificant.

scholarly journals Aktivitas Antibakteri Komposit Ag – Tulang Ikan Cakalang pada Staphylococcus aureus

Jurnal MIPA ◽  
2018 ◽  
Vol 7 (2) ◽  
pp. 29
Author(s):  
Elmi C.J. Pandelaki ◽  
Audy D. Wuntu ◽  
Henry F. Aritonang
Keyword(s):  
Staphylococcus Aureus ◽  
Antibacterial Activity ◽  
Bacterial Infections ◽  
Food Industry ◽  
Mixing Time ◽  
Nitrate Solution ◽  
Silver Nitrate Solution ◽  
Inhibition Zone ◽  
Skipjack Tuna ◽  
Fish Bones

Telah dilakukan penelitian untuk mengetahui aktivitas antibakteri komposit Ag – tulang ikan cakalang pada Staphylococcus aureus. Tulang ikan cakalang dikeringkan, dihaluskan dan diayak 65 mesh kemudian dicampur dengan larutan perak nitrat dengan perbandingan Ag : tulang ikan sebesar 5:1 , 4:2, dan 3:3  selama 1 jam pada suhu 70 ℃. Campuran kemudian di kalsinasi pada suhu 650 ℃ selama 2 jam. Uji aktivitas antibakteri dari komposit yang terbentuk dikerjakan dengan metode sumuran menggunakan bakteri Staphylococcus aureus. Hasil penelitian menunjukkan aktivitas antibakteri pada perbandingan 4:2 dengan lama waktu pencampuran 1 jam paling efektif untuk menghambat bakteri Staphylococcus aureus dengan diameter zona hambat sebesar 25 mm. Penelitian ini menunjukkan valorisasi dari produk sampingan industri makanan seperti tulang ikan untuk membentuk bahan yang berpotensi berharga sebagai bahan implan tulang yang resistan terhadap infeksi bakteriResearch has been conducted to determine the antibacterial activity of Ag - Bone skipjack tuna toward Staphylococcus aureus. Skipjack tuna bone dried, mashed and sifted 65 mesh then mixed with silver nitrate solution with a ratio of Ag : fish bones of 5:1, 4:2, and 3:3 for 1 hour at 70 ℃. The mixture was then calcined at 650 ℃ for 2 hours. Antibacterial activity test of the composites formed was done by the method of wells using the bacteria Staphylococcus aureus. The results showed that antibacterial activity at a ratio of 4: 2 with a one-hour mixing time was most effective for inhibiting Staphylococcus aureus bacteria with a 25 mm inhibition zone diameter. This study shows the valorization of food industry byproducts such as fish bones to form potentially valuable ingredients for bone implants resistant to bacterial infections

scholarly journals Clean Label in Bread

Foods ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 2054
Author(s):  
Maite Cristina Alava Vargas ◽  
Senay Simsek
Keyword(s):  
Water Absorption ◽  
Shelf Life ◽  
Mixing Time ◽  
Bread Quality ◽  
Staple Food ◽  
Chemical Additives ◽  
Dough Mixing ◽  
Definition Of ◽  
Interest In Research

Bread is considered a staple food worldwide, and therefore there is much interest in research around the topic. The bread industry is usually looking for ways to improve its formulations. Therefore, other ingredients such as dough conditioners, crumb softeners, emulsifiers, and surfactants can be added to enhance bread quality. These ingredients perform functions such as helping standardize processes in the industry, reducing dough-mixing time, increasing water absorption, improving bread quality, and extending its shelf life. Consumers are concerned about the effect of these ingredients on their health, and this has increased the popularity of clean-label bread formulations. A clean label generally indicates that a product is free of chemical additives, has an ingredient list that is easy to understand, has undergone natural or limited processing, and/or is organic and free of additives or preservatives. However, there is no scientific definition of the term “clean label.” Researchers have focused on these clean-label initiatives to replace dough strengtheners and preservatives in bread formulations and give consumers what they perceive as a healthier product.

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