Hyperspectral image control of the heat-treatment process of oat flour to model composite bread properties

Comparative Analysis of Vitamin, Mineral Content, and Antioxidant Capacity in Cereals and Legumes and Influence of Thermal Process

Cereals, as the world's most consumed food, face challenges related to nutrient quality due to climate change and increased production impacting soil health. In this study, we investigated the vitamin and mineral content, polyphenols, and antioxidant activity in cereals from Western Romania, analyzing whole and hulled wheat, rye, oat, and soybeans before and after heat treatment. Samples from 2022 crops were processed into dough and subjected to 220 °C for 30 min. The results reveal that, despite efforts to optimize nutrient content, cereals, particularly after heat processing, exhibited lower vitamin and mineral levels than the recommended daily intake. The decrease in polyphenols and antioxidant capacity was notable, with rye flour experiencing the largest decline (15%). Mineral analysis showed copper levels in decorticated wheat decreased by 82.5%, while iron in rye decreased by 5.63%. Soy flour consistently displayed the highest calcium, magnesium, and potassium levels, whereas oat flour had the highest zinc and copper levels before and after heat processing. The study highlights the concerningly low vitamins and minerals contents in cereals, as well as in the final products reaching consumers in the Western part of Romania, and contributes to the assessment of measures that are meant to improve the contents of these minerals.

Research on the Potential Use of Grape Seed Flour in the Bakery Industry

Grape seeds are one of the most accessible by-products of the wine industry in large quantities (about 2.4 million t/year). Numerous researchers have shown that grape seeds have a high potential for use as a functional ingredient in the food industry due to their high content of protein, fiber, minerals, and polyphenols. The aim of the paper is to evaluate the possibilities of using grape seed flour (GSF) in the bakery industry from both chemical and rheological points of view. Research shows that grape seed flour contains about 42 times more fiber than wheat flour and approximately 9 times more calcium, 8 times more magnesium, and 2 times more potassium. To assess this potential, four samples of bread from flour mixtures with 3%, 5%, 7%, and 9% (w/w) degree of replacement with GSF were prepared, analyzed, and compared with a control sample from 100% wheat flour. From a rheological point of view, the baking qualities deteriorate: the water absorption capacity (CH) decreases from 58.2% to 55.8%, the dough stability increases from 8.50 min to 9.83 min, the α slope varies from −0.066 Nm/min to −0.104 Nm/min, the β slope increases from 0.576 Nm/min to 0.630 Nm/min, and the γ slope varies from −0.100 Nm/min to −0.198 Nm/min. The sensory analyses performed by the panel of evaluators enclosed the sensorial characteristics of the samples with 3% and 5% GSF between the two control samples made from flour types 480 and 1250. The conclusions show that the sample containing 7% and 9% are unsatisfactory from rheological and sensorial points of view and the samples with 3% and 5% can be considered a fiber source and a Cu source, respectively, and are rich in Zn.

Identification of Copper in Stems and Roots of Jatropha curcas L. by Hyperspectral Imaging

The in situ determination of metals in plants used for phytoremediation is still a challenge that must be overcome to control the plant stress over time due to metals uptake as well as to quantify the concentration of these metals in the biomass for further potential applications. In this exploratory study, we acquired hyperspectral images in the visible/near infrared regions of dried and ground stems and roots of Jatropha curcas L. to which different amounts of copper (Cu) were added. The spectral information was extracted from the images to build classification models based on the concentration of Cu. Optimum wavelengths were selected from the peaks and valleys showed in the loadings plots resulting from principal component analysis, thus reducing the number of spectral variables. Linear discriminant analysis was subsequently performed using these optimum wavelengths. It was possible to differentiate samples without addition of copper from samples with low (0.5–1% wt.) and high (5% wt.) amounts of copper (83.93% accuracy, >0.70 sensitivity and specificity). This technique could be used after enhancing prediction models with a higher amount of samples and after determining the potential interference of other compounds present in plants.