Impact of local hydrothermal treatment during bread baking on soluble amylose, firmness, amylopectin retrogradation and water mobility during bread staling

Abstract

The impact of hydrothermal processing undergone by bread dough during baking on the degree of starch granule disruption, on leaching of soluble amylose, on water mobility, on firmness and on amylopectin retrogradation during staling has been investigated. Two heating rates during baking have been considered (4.67 and 6.31°C/min) corresponding respectively to baking temperature of 220 and 240°C. An increase in firmness and in the amount of retrogradated amylopectin accompanied by a decrease in freezable water has been observed during staling. Although a lower heating rate yielded in larger amount of retrogradated amylopectin retrogradation, it resulted in a lower firmness. Additionally, the amount of soluble amylose and the relaxation times of water measured by Nuclear Magnetic Resonance NMR (T 20, T 21 and T 22 ) decreased during staling. It was demonstrated that the amount of soluble amylose was higher for bread crumb baked at lower heating rate, indicating that an increasing amount of amylose is leached outside the starch granules. This was corresponding to a greater amount of retrograded amylopectin during staling. Moreover, it was found that the degree of gelatinization differs locally in a same bread slice between the top, the centre and the bottom locations in the crumb. This was attributed to the differences in kinetics of heating, the availability of water during baking and the degree of starch granule disruption during baking. Based on first order kinetic model, it was found that staling kinetics were faster for samples baked at higher heating rate.

Comparison of physicochemical and mechanical properties of edible films made from navy bean and corn starches

“…The composition of starches is presented in Table 1. The amylose content in commercial corn starch, as a reference, was similar to the values determined in other studies, showing that the results obtained in the present study are reliable 28 . Navy bean starch contained the highest amylose content (346 g kg −1 ), which was within the range of 286–414 g kg −1 as reported in other studies 29 .…”

“…The amylose content in commercial corn starch, as a reference, was similar to the values determined in other studies, showing that the results obtained in the present study are reliable. 28 Navy bean starch contained the highest amylose content (346 g kg −1 ), which was within the range of 286-414 g kg −1 as reported in other studies. 29 The amylose content in isolated corn starch was similar to commercial corn starch, although the residual protein content in laboratory-prepared two samples was slightly higher than commercial corn as a result of different extraction and isolation processes.…”

Physicochemical stability of bread fortified with tilapia-waste flour

“…The results of moisture content and a w of bread formulated with different tilapia-waste flour levels are displayed in Table 2. Similar initial values for moisture and a w in breads have been previously reported (Aguirre, Osella, Carrara, Sánchez, & Buera, 2011;Besbes, Bail, & Seetharaman, 2016). BTF0%, BTF2.5%, and BTF5% presented the highest (P < 0.05) moisture and a w values, while BTF20% exhibited the lowest (P < 0.05).…”

Increasing productivity and reducing energy consumption in the pizza industry by the synergetic combination of cooking technologies

“…During the baking process, products undergo several heating-rate depending changes, such as starch granule gelatinization and disruption, protein solubilization, gluten network formation, generation of aroma compounds, and crust browning (Besbes et al, 2016;Gunasekaran, 2016;Papasidero et al, 2016;Purlis and Salvadori, 2007;Schenkel et al, 2013;Wang & Sun, 2003;Zhang et al, 2017).…”

“…Meanwhile, during the cooking process, the phenomenon with the highest proportion of energy demand (23%-26% of energy consumption) is weight loss due to a reduction in water content (Besbes et al, 2016;Deshlahra et al, 2009;Le-bail et al, 2010). Few studies have been conducted to model the thermal performance of ovens for baking pizzas (Nicolas et al, 2017;Pour-Damanab et al, 2014) or to evaluate the use of thermal vision systems to guarantee product quality (Ma et al, 2014).…”