Authors

VAHEDI HABIB*, ABDOLLAZADEH FARZAD**

Departments

* Food Technology (Ph.D.). Department of Basic Sciences, Faculty of Health, Health Sciences Research Center, Mazandaran University of Medical Sciences, Sari, Iran - **Young Researchers and Elite Club, Boukan Branch, Islamic Azad University, Boukan, Iran

Abstract

Wheat bread as an integral part of the food basket is of paramount importance to meet the nutritional requirements and nutrient supply. Recently, there has been an increased attention to bulky breads because modern methods of processing and baking dough are in a way through which bread waste is reduced and they result in longer lasting of bread and preserve bread vitamins and proteins. Moreover, having additives in baking industry has also become more common. So that, they are generally used to improve the quality, to enhance efficiency and ease of working with dough, to delay staling, and hence to reduce waste. Neural Networks are a branch of artificial intelligence with computer algorithms on different classification and pattern recognition, parameter estimation, and so on. The aim of this research study was to use artificial network in order to predict appropriate models for the effect of adding hydrocolloids on baguette bread staling. The results showed that adding hydrocolloids would delay staling and adding guar in a long time has the greatest impact on baguette bread sustainability.

Keywords

Baguette bread, Hydrocolloids, Neural network, Stale.