Published data indicate that cricket powder (CP) is a good source of not only protein, fat and fiber, but also minerals. Due to the fact that this product naturally does not contain gluten, it is an interesting addition to the enrichment of gluten-free foods. This paper is a report on the results of starch substitution with CP (at 2%, 6% and 10%) on the properties of dough and bread. The rheology of dough and the texture of the final product were studied. While the changes caused in the dough by the introduction of CP were not pronounced, the bread obtained from it was characterized by significantly increased hardness and improved consistency. Analyses of water behavior at the molecular level with the use of 1H Nuclear Magnetic Resonance (NMR) indicated that CP altered both the bound and bulk water fractions. Moreover, examination of water activity revealed a decreased rate of water transport in samples of bread that contained CP. These results indicate improved availability of water to the biopolymers of bread, which likely plays a role in shaping the textural properties of the product.

The purpose of this study was to produce margarine with reduced trans and saturated fatty acid contents using 10% beeswax oleogel and hydrocolloid-based oleogel containing 3.15% sodium caseinate, 0.5% guar gum, and 0.22% xanthan gum with a melting point, rheological and textural characteristics similar to palm oil. Oleogel samples were used as a substitute for palm oil and partially hydrogenated palm olein oil. Margarine (70% fat) formulated with these oleogels was investigated for solid fat content (SFC), melting point, and rheological and textural properties. The results showed that the replacement of 100% partially hydrogenated palm olein oil (PHPO) and 25% palm oil (PO) with beeswax oleogel and the replacement of 100% PHPO with hydrocolloid-based oleogel resulted in the production of margarine with rheological and textural properties similar to the commercial control margarine. In addition, these samples had a lower content of SFC and a higher melting point than the commercial control sample. The amounts of saturated and trans fatty acids also decreased. These were 28% and 80% in the sample containing beeswax and 15% and 73% in the sample with hydrocolloid-based oleogels for saturated and trans fatty acids, respectively. It was concluded that it is possible to manufacture margarine using the oleogel method while maintaining its physical characteristics and improving its nutritional properties.

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a comparative study of the algorithms in order to determine which algorithm has the highest prediction accuracy. The results showed that the value of the red color has a greater effect than the green and blue colors in predicting the sweetness of orange fruits, as there is a direct relationship between the value of the red color and the level of sweetness. In addition, the logistic regression model algorithm gave the highest degree of accuracy in predicting sweetness.