Optimization of Aflatoxin Production of Aspergillus flavus on Peanuts

2014 ◽  
Vol 887-888 ◽  
pp. 605-609
Author(s):  
Chu Shu Zhang ◽  
Jie Sun ◽  
Li Na Yu ◽  
Jie Bi ◽  
Jian Xiong Feng ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Relative Humidity ◽  
Linear Relationship ◽  
Water Content ◽  
Response Surface ◽  
Aspergillus Flavus ◽  
Previous Experiment ◽  
Aflatoxin Production ◽  
Influence Of Water ◽  
Production Conditions

To optimize aflatoxin production of Aspergillus flavus on peanut, the response surface methodology were applied based on previous experiment. The results showed that the influence of water content of peanuts,time and relative humidity were obvious and were not linear relationship. The optimal aflatoxin production conditions were that water content of peanuts was12%, the time was 7 days, relative humidity was 80%.

Use of response surface methodology to study the effect of media composition on aflatoxin production by Aspergillus flavus

2012 ◽  
Vol 29 (1) ◽  
pp. 39-45 ◽  
Author(s):  
Mahboob Ahmad ◽  
Malik M. Ahmad ◽  
Rifat Hamid ◽  
M. Z. Abdin ◽  
Saleem Javed
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Aspergillus Flavus ◽  
Aflatoxin Production ◽  
Media Composition

Use of Response Surface Methodology to Study the Influence of Water Content and Air Pressure on Cake Batter Quality

2007 ◽  
Vol 3 (6) ◽  
Author(s):  
Irene Allais ◽  
Eric Dufour
Keyword(s):  
Response Surface Methodology ◽  
Linear Equation ◽  
Water Content ◽  
Response Surface ◽  
Initial Density ◽  
Air Pressure ◽  
Final Temperature ◽  
Influence Of Water ◽  
Spreading Time ◽  
Water Amount

The first aim of the study was to model the influence of water amount and air pressure on various batter properties using Response Surface Methodology. Batter quality was assessed through density, water content, colour, spreadability and fluorescence spectra. Quadratic models using two variables well represented spreading time, water content and final temperature, but they failed to fairly represent initial density, overrun and L*a*b* values. In addition, simplified models using a single variable also well represented the data: final density was modelled by a linear equation involving pressure, whereas initial density, water content and final temperature were modelled by a linear equation involving water amount. Spreading time was modelled using a quadratic equation using water amount. Experimental results were compared with expertise rules used by operators to control the industrial process. Indeed, operators often used water amount and air pressure as controlling variables. It was found that experimental results were in agreement with expertise rules. The second aim was to investigate the link between smart lab-measurement methods such as fluorescence spectroscopy and simple macroscopical properties used by operators such as water content, density, spreading time and colour. By applying hierarchical clustering analysis to NADH and tryptophan merged spectra, batter samples manufactured at various water amounts and pressure levels were clearly separated at a high level of discrimination. Neither water content nor spreading time were satisfactorily predicted from NADH or tryptophan spectra using PLS.

Demulsification of a Water-in-crude Oil Emulsion with a Corn Oil BasedDemulsifier using the Response Surface Methodology: Modelling and Optimization

2021 ◽  
Vol 14 ◽  
Author(s):  
Abed Saad ◽  
Nour Abdurahman ◽  
Rosli Mohd Yunus
Keyword(s):  
Response Surface Methodology ◽  
Crude Oil ◽  
Water Content ◽  
Response Surface ◽  
Separation Efficiency ◽  
Corn Oil ◽  
Oil Emulsion ◽  
Optimal Values ◽  
Input Variables ◽  
Oil Emulsions

: In this study, the Sany-glass test was used to evaluate the performance of a new surfactant prepared from corn oil as a demulsifier for crude oil emulsions. Central composite design (CCD), based on the response surface methodology (RSM), was used to investigate the effect of four variables, including demulsifier dosage, water content, temperature, and pH, on the efficiency of water removal from the emulsion. As well, analysis of variance was applied to examine the precision of the CCD mathematical model. The results indicate that demulsifier dose and emulsion pH are two significant parameters determining demulsification. The maximum separation efficiency of 96% was attained at an alkaline pH and with 3500 ppm demulsifier. According to the RSM analysis, the optimal values for the input variables are 40% water content, 3500 ppm demulsifier, 60 °C, and pH 8.

Improving the stability of uricase from Aspergillus flavus by osmolytes: Use of response surface methodology for optimization of the enzyme stability

2020 ◽  
Vol 94 ◽  
pp. 86-98 ◽  
Author(s):  
Somayyeh Mirzaeinia ◽  
Mohammad Pazhang ◽  
Mehdi Imani ◽  
Nader Chaparzadeh ◽  
Ali Reza Amani-Ghadim
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Aspergillus Flavus ◽  
Enzyme Stability ◽  
The Stability

scholarly journals Response surface methodology for optimizing the glycerolysis reaction of olive oil by Candida rugosa lipase

2014 ◽  
Vol 20 (1) ◽  
pp. 127-134 ◽  
Author(s):  
Kumar Singh ◽  
Mausumi Mukhopadhyay
Keyword(s):  
Response Surface Methodology ◽  
Reaction Time ◽  
Olive Oil ◽  
Water Content ◽  
Response Surface ◽  
Candida Rugosa ◽  
Candida Rugosa Lipase ◽  
Molar Ratio ◽  
Immobilized Candida Rugosa Lipase ◽  
Central Composite

In the present work, solvent free olive oil glycerolysis for the monoglycerides (MG) and diglycerides (DG) production with an immobilized Candida rugosa lipase was studied. MG and DG production were optimized using experiment design techniques and response surface methodology (RSM). RSM based on five-level, a five-variable central composite design (CCD) was used to optimize MG and DG production: reaction time, temperature, molar ratio of glycerol to oil, amount of lipase, and water content in glycerol. The reaction time, temperature, and amount of lipase were observed to be the most significant factors on the process response. The immobilized Candida rugosa lipase revealed optimum yield of MG and DG as 38.71 and 40.45 wt% respectively following a 5h reaction time with 0.025 g of lipase and 5% water content in glycerol at 40?C temperature. The yield of MG and DG production can be enhanced 1.5 fold by RSM.

scholarly journals Optimizing the tray dryer temperature and time of white corn flour culture

Food Research ◽  
2021 ◽  
Vol 5 (5) ◽  
pp. 95-104
Author(s):  
D. Hunaefi ◽  
Rahmawati R. ◽  
D. Saputra ◽  
R.R. Maulani ◽  
T. Muhandri
Keyword(s):  
Response Surface Methodology ◽  
Aspergillus Niger ◽  
Water Content ◽  
Response Surface ◽  
Water Activity ◽  
Penicillium Citrinum ◽  
Drying Process ◽  
Corn Flour ◽  
Acremonium Strictum ◽  
Candida Famata

This research aimed to optimize the tray dryer temperature and time of white corn flour culture by Response Surface Methodology (RSM). There were two cultures used in this research, namely Amylolytic Culture (AC) and Complete Culture (CC). AC consisted of Penicillium citrinum, Aspergillus niger, Acremonium strictum, and Candida famata, while CC consisted of Penicillium chrysogenum, Penicillium citrinum, Aspergillus niger, Rhizopus stolonifer, Rhizopus oryzae, Fusarium oxysporum, Acremonium strictum, Candida famata, Kodamaea ohmeri and Candida krusei/incospicua. The independent variables in this study were drying temperature and time, where the quality indicators used were total viability of mold and yeast, water content, water activity, and pH. This research used a factor response surface methodology. Data were analyzed by ANOVA with an α level of 95%. The result of this research showed that the optimum drying process for AC starter was 40°C for 10 hrs, with characteristic response viability 8.8×107 CFU/g, water activity 0.43, water content 8.90%, and pH 4.05. CC starter showed an optimum drying process at 49°C for 4.5 hrs, with characteristic response viability 4.9×107 CFU/g, water activity 0.49, water content 7.02%, and pH 3.95. The optimum tray dryer temperatures and times were achieved for AC and CC starters.

scholarly journals OPTIMASI DENGAN ALGORITMA RSM-CCD PADA EVAPORATOR VAKUM WATERJET DENGAN PENGENDALI SUHU FUZZY PADA PEMBUATAN PERMEN SUSU (RSM-CCD Algorithm for Optimizing Waterjet Vacuum Evaporator Using Fuzzy Temperature Control in The Milk Candy Production)

2016 ◽  
Vol 36 (02) ◽  
pp. 226
Author(s):  
Yusuf Hendrawan ◽  
Bambang Susilo ◽  
Angky Wahyu Putranto ◽  
Dimas Firmanda Al Riza ◽  
Dewi Maya Maharani ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Control System ◽  
Central Composite Design ◽  
Water Content ◽  
Response Surface ◽  
Temperature Control ◽  
Vacuum System ◽  
Temperature Control System ◽  
Mixing Speed ◽  
Central Composite

Milk candy is a product which has to be produced under a high temperature to achieve the caramelization process. The use of vacuum system during a food processing is one of the alternatives to engineer the value of a material’s boiling point. The temperature control system and the mixing speed in machine that produce the milk candy were expected to be able to prevent the formation of off-flavour in the final product. A smart control system based on fuzzy logic was applied in the temperature control within the double jacket vacuum evaporator machine that needs stable temperature in the cooking process. The objective of this research is developing vacuum evaporator for milk candy production using fuzzy temperature control. The result in machine and system planning showed that the process of milk candy production was going on well. The parameter optimization of water content and ash content purposed to acquire the temperature point parameter and mixing speed in milk candy production. The optimization method was response surface methodology (RSM), by using the model of central composite design (CCD). The optimization resulted 90.18oC for the temperature parameter and 512 RPM for the mixing speed, with the prediction about 4.69% of water content and 1.57% of ash content.Keywords: Optimization, vacuum evaporator, fuzzy, milk candy, response surface methodologyABSTRAKPermen susu merupakan salah satu produk yang diolah dengan suhu tinggi untuk mencapai proses karamelisasi. Pengolahan pangan dengan sistem vakum merupakan salah satu alternatif untuk merekayasa nilai titik didih suatu bahan. Sistem pengendalian suhu serta kecepatan pengadukan pada mesin produksi permen susu diharapkan dapat mencegah terbentuknya partikel hitam (off-flavour) pada produk akhir. Sistem kontrol cerdas logika fuzzy diaplikasikan dalam pengendalian suhu pada mesin evaporator vakum double jacket yang membutuhkan tingkat stabilitas suhu pemasakan permen susu. Tujuan dari penelitian ini adalah membuat rancang bangun evaporator vakum pada pembuatan permen susu dengan menggunakan pengendali suhu fuzzy. Hasil perancangan mesin dan sistem menunjukkan bahwa proses produksi permen susu dapat berlangsung dengan baik. Optimasi parameter kadar air dan kadar abu dilakukan untuk mendapatkan titik parameter suhu dan kecepatan pengadukan produksi permen susu yang optimum. Metode optimasi menggunakan response surface methodology (RSM) model central composite design (CCD). Hasil optimasi didapatkan parameter suhu 90,18oC dan kecepatan pengadukan 512 RPM, dengan prediksi produk permen susu memiliki nilai kadar air 4,69% dan kadar abu 1,57%.Kata kunci: Optimasi, evaporator vakum, fuzzy, permen susu, response surface methodology

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