Neural network enhanced aging time measurements of diary product remaining with infrared spectroscopy.

The determination of the drying degree of food residues on surfaces is an important step before efficient cleaning can be achieved. To accomplish this goal, a rapid evaluation based on a neural network and non-invasive measurement technique is introduced. Two common starch-based products and various yogurts from different manufacturers are used as example contaminants to determine the aging time of dried food residue. Near-infrared spectroscopy serves as a modern and fast measurement technique for investigating food compositions. Two analysis methods were compared for processing the measured near-infrared spectral data. The raw data were analyzed using partial least squares regression in conjunction with necessary preprocessing steps. As an alternative method, three different types of neural networks are employed. The aim of this approach is to compensate for the filtering steps before regression, which are typically necessary for multivariate regression. The challenge is to measure three different types of food and obtain a reliable prediction of moisture content in order to draw conclusions about the drying time. The experiments have shown that simple flat neural networks have similar accuracy compared to conventional regression. The use of a convolutional layer in advance demonstrates a significant improvement in prediction compared to other neural networks and even manages to surpass the accuracy of PLS regression. A network with a convolutional layer can also compensate for the sometimes strong variations between food types.

Application of CO2 Gas Hydrates as Leavening Agents in Black-and-White Cookies.

In this unprecedented study, the application of CO2 gas hydrates (GH) as a leavening agent to produce black-and-white cookies by replacing ammonium bicarbonate is investigated. Ammonium bicarbonate, the principal leavening ingredient in black-and-white cookies, has been linked to the creation of a carcinogenic substance known as acrylamide. Three distinct GH concentrations, 20%, 40%, and 50%, were utilized to determine the necessary amount to obtain a good leavening effect. However, the abrupt reduction in temperature brought on by the addition of GH had an inadmissible effect on the cookie dough. Consequently, an innovative kneading method carried out in a closed mixing unit at a high temperature was developed. The specific volume of the cookies when employing 50% GH as a baking agent was more than half that produced when using ammonium bicarbonate. In the cookies with GH, the springiness and hardness, which are the quality-determining textural characteristics of the pastry, remained within an acceptable range. The amount of acrylamide was reduced from 24.8 µg/Kg to around 18 µg/Kg by this research. Therefore, the presented study demonstrates the possibility of using CO2 GH as a leavening agent in black-and-white cookies and in other products for a healthier future.

An Innovative Approach in the Baking of Bread with CO2 Gas Hydrates as Leavening Agents.

Gas (guest) molecules are trapped in hydrogen-bonded water molecules to form gas hydrates (GH), non-stoichiometric solids that resemble ice. High pressure and low temperature are typical conditions for their development, with van der Waals forces joining the host and guest molecules. This article study investigates the application of CO2 gas hydrates (CO2 GH) as a leavening agent in baking, with particular reference to the production of wheat bread. The main intention of this study is to better understand the complex bread dough formed by CO2 GH and its impact on product quality. This may enable the adaptation of CO2 GH in baking applications, such as those that can specifically influence wheat bread properties, and so the final bread quality. The present research further examines the comparative evaluation of yeast bread with the GH bread's impact on bread quality parameters. The amount of GH was varied from 10 to 60%/amount of flour for the GH breads. The GH breads were compared with the standard yeast bread for different quality parameters such as volume, texture, and pore analysis. The results show that the bread with 20% and 40% GH obtained the best results in terms of volume and pore size. Moreover, this article also sheds some light on the future applications of the use of CO2 GH as leavening agents in foods. This knowledge could help to create new procedures and criteria for improved GH selection for applications in bread making and other bakery or food products.

Experimental investigation of CO2 uptake in CO2 hydrates formation with amino acids as kinetic promoters and its dissociation at high temperature.

The dissociation of CO2 gas hydrates (GH) with amino acid kinetic promoters and without promoters was studied at a high temperature of 90 °C for a period of 20 min to understand the percentage of CO2 gas and to select the best promoter that aids CO2 gas entrapment along with stability at a high temperature. The possibility of using four hydrophobic food grade amino acids, namely cysteine, valine, leucine, and methionine, and one surfactant, lecithin, as kinetic promoters for CO2 GH has been studied. The amino acids were added 0.5 g (wt%), and lecithin was added 5 g for the GH production. Furthermore, the amino acids leucine and methionine gave some positive results, therefore, these amino acids were carried further for the experimentation purpose in the production of CO2 GH. Also, a combinational use of these amino acids was studied to investigate the effect on % CO2 retention in comparison to the normal GH. From the results, it was observed that the stability of GH decreases with an increase in temperature, but the addition of promoters, especially leucine + methionine + lecithin increased the CO2 uptake during GH formation.