Analyzing the effect of germination on the pasting, rheological, morphological and in- vitro antioxidant characteristics of kodo millet flour and extracts

The present investigationwas carried out to determine the effect of germination on pasting, rheological, morphological properties of Kodo millet flour and in-vitroantioxidant characteristics of its phenolic and γ-amino butyric acid extracts. Rheological analysis depicted complex flour viscosity decreased with an improvement in shear intensity, symbolizing the shear-thinning action of flour upon germination. The frequency and temperature sweep demonstrated a decrease in visco-elasticity as a result of germination wherein, SEM revealed destruction in the continuous composite structure of starch which got entangled in dense protein matrix following germination. The in-vitroantioxidant activities such as total antioxidant capacity, DPPH*, FRAP, metal chelating ability and hydrogen peroxide scavenging activities of both the extracts increased significantly. There was a decrease in pasting properties and gelatinization behaviour whereas, visco-elastic solid behaviour changed to visco-elastic fluid. This research explores the potential of germinated Kodo millet flour for valuable bioactive compounds extraction and its utilization in product development.

Electric Drive Supervisor for Milling Process 4.0 Automation: A Process Analytical Approach with IIoT NIR Devices for Common Wheat

The milling industry envisions solutions to become fully compatible with the industry 4.0 technology where sensors interconnect devices, machines and processes. In this contest, the work presents an integrated solution merging a deeper understanding and control of the process due to real-time data collection by MicroNIR sensors (VIAVI, Santa Rosa, CA)—directly from the manufacturing process—and data analysis by Chemometrics. To the aim the sensors were positioned at wheat cleaning and at the flour blends phase and near infrared spectra (951–1608 nm) were collected online. Regression models were developed merging the spectra information with the results obtained by reference analyses, i.e., chemical composition and rheological properties of dough by Farinograph^® (Brabender GmbH and Co., Duisburg, Germany), Alveograph^® (Chopin, NG Villeneuve-la-Garenne Cedex, France) and Extensograph^®.(Brabender GmbH and Co., Duisburg, Germany) The model performance was tested by an external dataset obtaining, for most of the parameters, R_PRED higher than 0.80 and Root Mean Squares Errors in prediction lower than two-fold the value of the reference method errors. The real-time implementation resulted in optimal (100% of samples) or really good (99.9%–80% of samples) prediction ability. The proposed work succeeded in the implementation of a process analytical approach with Industrial Internet of Things near infrared (IIoT NIR) devices for the prediction of relevant grain and flour characteristics of common wheat at the industrial level.

Classification Method for Viability Screening of Naturally Aged Watermelon Seeds Using FT-NIR Spectroscopy

Viability analysis of stored seeds before sowing has a great importance as plant seeds lose their viability when they exposed to long term storage. In this study, the potential of Fourier transform near infrared spectroscopy (FT-NIR) was investigated to discriminate between viable and non-viable triploid watermelon seeds of three different varieties stored for four years (natural aging) in controlled conditions. Because of the thick seed-coat of triploid watermelon seeds, penetration depth of FT-NIR light source was first confirmed to ensure seed embryo spectra can be collected effectively. The collected spectral data were divided into viable and nonviable groups after the viability being confirmed by conducting a standard germination test. The obtained results showed that the developed partial least discriminant analysis (PLS-DA) model had high classification accuracy where the dataset was made after mixing three different varieties of watermelon seeds. Finally, developed model was evaluated with an external data set (collected at different time) of hundred samples selected randomly from three varieties. The results yield a good classification accuracy for both viable (87.7%) and nonviable seeds (82%), thus the developed model can be considered as a “general model” since it can be applied to three different varieties of seeds and data collected at different time.

Effects of enzyme activities during steeping and sprouting on the solubility and composition of proteins, their bioactivity and relationship with the bread making quality of wheat flour

The aim was to determine the effect of steeping and sprouting on wheat grain proteins and the functional consequences in this regard.

A Review on the Role of Vibrational Spectroscopy as An Analytical Method to Measure Starch Biochemical and Biophysical Properties in Cereals and Starchy Foods

Starch is the major component of cereal grains and starchy foods, and changes in its biophysical and biochemical properties (e.g., amylose, amylopectin, pasting, gelatinization, viscosity) will have a direct effect on its end use properties (e.g., bread, malt, polymers). The use of rapid and non-destructive methods to study and monitor starch properties, such as gelatinization, retrogradation, water absorption in cereals and starchy foods, is of great interest in order to improve and assess their quality. In recent years, near infrared reflectance (NIR) and mid infrared (MIR) spectroscopy have been explored to predict several quality parameters, such as those generated by instrumental methods commonly used in routine analysis like the rapid visco analyser (RVA) or viscometers. In this review, applications of both NIR and MIR spectroscopy to measure and monitor starch biochemical (amylose, amylopectin, starch) and biophysical properties (e.g., pasting properties) will be presented and discussed.

Near infrared and fluorescence spectroscopic methods and electronic nose technology for monitoring foods

There is a clear need for application of proper methods for measuring food quality and safety in the globalized food-webs. Numerous instrumental methods have been established in the course of the 20th century and are developing further, together with data analysis techniques, for such purposes. Among them, near-infrared and fluorescence spectroscopic methods and chemical sensor arrays called electronic noses show particular promise for rapid, non-destructive, non-invasive and cost-effective ways for assessing changes and enhancing control during processing and storage of foods. Their key advantages as analytical tools are 1) their relatively high speed of analysis, 2) the lack of a need to carry out complex sample preparation or processing, 3) their relatively low cost, and 4) their suitability for on-line monitoring or quality control. The present survey attempts to demonstrate examples from the above areas, limiting itself mainly to monitoring some quality indices which contribute to the functionality or acceptability of foods as affected by alternative processing technologies, or loss of freshness/microbial safety, or developing spoilage during storage and marketing. These instrumental methods are correlative techniques: they must be calibrated first against (traditional) reference properties, and the instrumental data are evaluated with the help of chemometric methods. Near-infrared (NIR) spectroscopy can be used in either the reflectance or the transmittance mode. NIR spectra transformed to mathematical derivatives allows subtle spectrum changes to be resolved. Selected examples from the extensive NIRS literature relate to assessment of the quality of frozen fish, predicting cooking loss of chicken patties, detecting complex physico-chemical changes of minced meat as a function of the intensity of high hydrostatic pressure treatment, comparing changes of NIR spectrometric “fingerprints” caused by gamma radiation or high pressure pasteurization of liquid egg white. Changes of NIR spectra reflect several parameters which suit the evaluation of loss of freshness, and onset of spoilage of various foods. NIR spectroscopy shows an application potential for rapid detection of bacterial or mould contamination. It may serve as a tool for detecting initial stages of mobilization processes during germination of cereal grains, or even for GMO screening. Spectrofluorometic measurements have shown potential, e.g. to monitor lipid oxidation and development of meat rancidity, to differentiate between raw and processed milks, and to monitor fish and egg freshness. Electronic noses containing chemical sensor arrays offer a rapid method for evaluation of head-space volatiles of food samples, important for characterizing quality and safety. Such gas sensors may be able to classify storage time, and determine spoilage, either earlier or at the same time as the human senses, or “sniffing out” bacterial pathogens or (toxigenic) fungal growth on certain foods. Electronic nose sensing is also a promising method for detecting quality changes of fruit- and vegetable products non-destructively. In relation to some examples to be presented in the paper, certain software developments as qualitative classification tools made by Hungarian scientists will be pointed out.