Investigating the effects of ingredient levels on physical quality properties of cooked hamburger patties using response surface methodology and image processing technology.

A three-factor central composite design was adopted to determine the interactive effects of fat (15-30%), water (10-20%) and textured soy protein (3-9%) content on the shrinkage, fat loss and moisture loss of hamburger patties after cooking. Image processing was used to estimate the shrinkage of hamburger patties. Textured soy protein (TSP) content was found to be the most important factor for minimizing fat and moisture loss. Both fat and water content were found to be significantly effective (P<0.05) in the model for shrinkage and moisture loss in linear form. The changes in shrinkage due to fat, water and TSP content were also in linear form. The model for fat loss was in linear and quadratic form, whereas the model for moisture loss was in full quadratic form. The models for shrinkage, fat loss and moisture loss had the R-square values of 0.954, 0.969 and 0.964, respectively.

[1]  Da-Wen Sun,et al.  Colour calibration of a laboratory computer vision system for quality evaluation of pre-sliced hams. , 2009, Meat science.

[2]  R. Ipsen,et al.  Prediction of sensory properties of low-fat yoghurt and cream cheese from surface images , 2008 .

[3]  S. Yu,et al.  Effects of phosphate, water, fat and salt on qualities of low-fat emulsified meatball , 1999 .

[4]  Hamit Köksel,et al.  A classification system for beans using computer vision system and artificial neural networks , 2007 .

[5]  Chaoxin Zheng,et al.  Estimating shrinkage of large cooked beef joints during air-blast cooling by computer vision , 2006 .

[6]  Da-Wen Sun,et al.  Improving quality inspection of food products by computer vision: a review , 2004 .

[7]  H. Ulu.  Effect of wheat flour, whey protein concentrate and soya protein isolate on oxidative processes and textural properties of cooked meatballs , 2004 .

[8]  O. Dağlıoğlu,et al.  The effect of replacing fat with oat bran on fatty acid composition and physicochemical properties of meatballs. , 2003, Meat science.

[9]  Chia-Yu Kuo,et al.  Use of Surface Response Methodology to Optimize Culture Conditions for Iturin a Production by Bacillus Subtilis in solid-state Fermentation , 2008 .

[10]  Jinglu Tan,et al.  Meat quality evaluation by computer vision , 2004 .

[11]  G Bertelsen,et al.  Colour stability and lipid oxidation of fresh beef. Development of a response surface model for predicting the effects of temperature, storage time, and modified atmosphere composition. , 2000, Meat science.

[12]  S. Hsu,et al.  Effects of κ-carrageenan, salt, phosphates and fat on qualities of low fat emulsified meatballs , 2001 .

[13]  S. Hsu,et al.  Effects of processing factors on qualities of emulsified meatball , 1998 .

[14]  I. Yilmaz.  Physicochemical and sensory characteristics of low fat meatballs with added wheat bran , 2005 .

[15]  Cheng-Jin Du,et al.  Prediction of beef eating quality from colour, marbling and wavelet texture features. , 2008, Meat science.

[16]  M. Serdaroğlu.  Improving low fat meatball characteristics by adding whey powder. , 2006, Meat science.

[17]  M. Serdaroğlu,et al.  Effects of fat level (5%, 10%, 20%) and corn flour (0%, 2%, 4%) on some properties of Turkish type meatballs (koefte). , 2004, Meat science.

[18]  Cheng-Jin Du,et al.  Estimating the surface area and volume of ellipsoidal ham using computer vision , 2006 .

[19]  J F Kerry,et al.  Evaluation of surimi, fat and water content in a low/no added pork sausage formulation using response surface methodology. , 2004, Meat science.

[20]  Fernando Mendoza,et al.  Analysis and classification of commercial ham slice images using directional fractal dimension features. , 2009, Meat science.

[21]  K. Muthukumarappan,et al.  Colour degradation and quality parameters of sonicated orange juice using response surface methodology , 2008 .

[22]  L. Ananthanarayan,et al.  Use of response surface methodology to investigate the effects of milling conditions on damaged starch, dough stickiness and chapatti quality , 2009 .

[23]  S. Tassone,et al.  Meat cooking shrinkage: Measurement of a new meat quality parameter. , 2006, Meat science.

[24]  José Miguel Aguilera,et al.  Image analysis of changes in surface color of chocolate , 2005 .

[25]  V. K. Modi,et al.  Quality of buffalo meat burger containing legume flours as binders. , 2004, Meat science.

[26]  Narpinder Singh,et al.  Effect of liquid whole egg, fat and textured soy protein on the textural and cooking properties of raw and baked patties from goat meat , 2002 .

[27]  D. Troy,et al.  The Effects of Tapioca Starch, Oat Fibre and Whey Protein on the Physical and Sensory Properties of Low-fat Beef Burgers , 1998 .

[28]  S. Hsu,et al.  Interactions of konjac, agar, curdlan gum, -carrageenan and reheating treatment in emulsified meatballs , 2000 .

[29]  Da-Wen Sun,et al.  Recent developments and applications of image features for food quality evaluation and inspection – a review , 2006 .

[30]  H. Ulu.  Effects of carrageenam and guar gum on the cooking and textual properties of low fat meatballs , 2006 .

[31]  Juming Tang,et al.  Thermal effects on chicken and salmon muscles: Tenderness, cook loss, area shrinkage, collagen solubility and microstructure , 2008 .

[32]  Da‐Wen Sun,et al.  Automatic measurement of pores and porosity in pork ham and their correlations with processing time, water content and texture. , 2006, Meat science.

[33]  Antti Kause,et al.  Automated image analysis as a tool to quantify the colour and composition of rainbow trout (Oncorhynchus mykiss W.) cutlets , 2006 .

[34]  C. Barry‐Ryan,et al.  Modelling browning and brown spotting of mushrooms (Agaricus bisporus) stored in controlled environmental conditions using image analysis. , 2009 .

[35]  E. A. Davis,et al.  WATER LOSS RATES AND TEMPERATURE PROFILES OF DRY COOKED BOVINE MUSCLE , 1977 .

[36]  M. Serdaroğlu,et al.  Quality of low-fat meatballs containing Legume flours as extenders. , 2005, Meat science.