Broiler production at mass level has already been achieved and now emphasis is being laid on increasing meat quality by altering various characteristics of broiler meat. Appearance, texture, juiciness, wateriness, firmness, tenderness, odor and flavor are the most important and perceptible meat features that influence the initial and final quality judgment by consumers before and after purchasing a meat product. The quantifiable properties of meat such as water holding capacity, shear force, drip loss, cook loss, pH, shelf life, collagen content, protein solubility, cohesiveness, and fat binding capacity are indispensable for processors involved in the manufacture of value added meat products. Nutrition of birds has a significant impact on poultry meat quality and safety. It is well known that dietary fatty acid profiles are reflected in tissue fatty acid. Management of poultry meat production is reflected mostly on consumption features (juiciness, tenderness, flavour) of meat. After slaughter, biochemical changes, causing the conversion of muscle to meat, determine final meat quality. Postmortem carcass temperature has profound effect on rigor mortis and the physicochemical changes observed in PSE muscles are attributed to postmortem glycolysis, temperature, and pH. Primary processing and further processing have become a matter of concern with respect to nutritional quality of broiler meat. Genetic variation among birds could contribute to large differences in the rate of rigor mortis completion and meat quality. Heritability estimates for meat quality traits in broilers are amazingly high (0.35-0.81), making genetic selection a best tool for improvement of broiler meat quality.

Protein engineering is a young discipline that has been branched out from the field of genetic engineering. Protein engineering is based on the available knowledge about the proteins structure/function(s), tools/instruments, software, bioinformatics database, available cloned gene, knowledge about available protein, vectors, recombinant strains and other materials that could lead to change in the protein backbone. Protein produced properly from genetic engineering process means a protein that is able to fold correctly and to do particular function(s) efficiently even after being subjected to engineering practices. Protein is modified through its gene or chemically. However, modification of protein through gene is easier. There is no specific limitation of Protein Engineering tools; any technique that can lead to change the protein constituent of amino acid and result in the modification of protein structure/function is in the frame of Protein Engineering. Meanwhile, there are some common tools used to reach a specific target. More active industrial and pharmaceutical based proteins have been invented by the field of Protein Engineering to introduce new function as well as to change its interaction with surrounding environment. A variety of protein engineering applications have been reported in the literature. These applications range from biocatalysis for food and industry to environmental, medical and nanobiotechnology applications. Successful combinations of various protein engineering methods had led to successful results in food industries and have created a scope to maintain the quality of finished product after processing.

The paper explores the possibility of utilizing brown rice for preparation of gluten-free pasta using twin screw extruder. Response surface methodology was used to analyse the effect of feed moisture (28-34%), barrel temperature (70-110C) and screw speed(120-220 rpm) on quality responses (degree of gelatinization, minimum cooking time, water absorption, volume expansion, and gruel solid loss) and regression analysis was carried out to fit mathematical models to the experimental data. The selected pasta samples were examined further for pasting properties, color, texture, in vitro starch, and protein digestibility. Higher feed moisture exhibited dominant effect on cooking quality of pasta. The degree of gelatinization showed a positive correlation with feed moisture and barrel temperature. Luminosity enhanced with increasing screw speed and feed moisture. Firmness of cooked pasta elevated with an increase in the barrel temperature. Extrusion cooking significantly increased in vitro protein and starch digestibility, however, higher feed moisture favored protein and starch digestibility. PRACTICAL APPLICATIONSPasta products are normally produced using cold extrusion process 40-50C temperature. Generally single screw extruder is used for pasta manufacture. In the present scenario of convenience and newer products, we explored the possibility of using brown rice along with twin screw extruder for preparation of gluten-free pasta. Effect of feed moisture, barrel temperature, and screw speed on the quality parameters of pasta were studied. Pasta produced at higher feed moisture and screw speed showed higher in vitro starch and protein digestibility.

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A study was carried out to relate the hydration behaviour with processing conditions of low amylose content parboiled rice which was dried at various temperatures (40, 50 and 60°C). The rehydration characteristics of the parboiled rice (dehusked only) was then studied at various soaking temperatures (30, 40 and 50°C) and time ( upto 3 h at every 30 min interval) and equilibrium moisture content of rehydration (EMC) was determined. The data were tested on three hydration equations viz., Peleg's, Exponential and Weibull equations. The experimental data were used to determine the model parameters. The goodness of fit for the models were evaluated by coefficient of determination (R 2 ) and sum of square error (SSE). The results were indicated that the Weibull model fits better than the exponential model and Peleg's equation. Also, water transfer to paddy, was described by applying the Fick's diffusion model and the moisture diffusivity (D) was calculated. The Diffusivity values varied between 1.06 and 4×10 −11 m 2 /s.

The present study aimed to apply artificial neural networking for quantification of quality attributes of agricultural commodity based on color and size. Three feed forward neural network models (NN) were developed: first for conversion of RGB to L*, a* and b* values (NN1), second for identification of ripening stages of tomato and third for correlating projection area/size of tomato with weight. Results showed that NN1 was able to convert RGB to L*, a* and b* values with accuracy percentage of 99%. The best results showed with excellent abilities were at 30 hidden units with R2 of 0.9980 and mean squared error (MSE) of 0.00021, whereas NN2 classified tomatoes in three ripening stages with an accuracy of 96%, with 30 hidden neurons and a 100% classification was performed when a threshold value of 0.7 was used. In addition, NN3 was able to correlate area with weight with an accuracy of 99%, with three hidden neurons. Practical Applications Computer vision system‐based measurement of color and projection areas has been considered for the assessment of tomato quality. Image processing, a nondestructive method for evaluation of quality attributes of agricultural produce, serves as a best tool for measurement of size and color of nonuniform products. The color of whole surface can be evaluated using image analysis. Image processing was used as the basic tool and their functional relationships are expressed in terms of artificial neural network model.

Processing & TechnologyJ o u rnal of F o o d P ro cessi n g & T ec hnolo g y

The present study explores the possibility of using twin screw extruder for preparation of pregelatinized pasta. The effects of extrusion parameters feed moisture (28 and 32%), barrel temperature (60-105 °C) and screw speed (100-200 rpm) on pregelatinized pasta were investigated. Prepared pasta was analysed for quality characteristics in terms of cooking quality, degree of gelatinization, color, texture, pasting properties, bioactive composition. Results indicated that higher screw speed improved the cooking quality of pasta and decreased gruel solid loss. Degree of gelatinization revealed positive relation with temperature and feed moisture. Extrusion conditions, altered the color of pasta, a decrease in L*, increase in a* and b* values was observed. Higher peak viscosity was observed at lower barrel temperature and feed moisture. A significant retention in total phenolic content and flavonoid content was observed with higher feed moisture. Extrusion leads to increase in antioxidant activity and firmness upon increasing screw speed and feed moisture.