The Process of Pasting and Gelling Modified Potato Starch with LF-NMR

Recent Trends in the Pre-Drying, Drying, and Post-Drying Processes for Cassava Tuber: A Review

Cassava tuber is an essential staple crop in tropical regions with versatile applications in the food, feed, and industrial sectors. However, its high moisture content and perishable nature necessitate efficient preservation methods to extend its shelf life and enhance its value. Pre-drying, drying, and post-drying processes play pivotal roles in maintaining the quality and usability of cassava products. This review comprehensively examines the current status and future directions in the pre-drying, drying, and post-drying processes of cassava tuber. Various pre-drying or pretreatment methods and drying techniques are evaluated for their impacts on drying kinetics and product quality. Additionally, challenges and limitations in achieving high-quality processing of cassava flour are identified. Future directions in cassava drying methods emphasize the integration of combined pre-drying and drying techniques to optimize resource utilization and processing efficiency. Furthermore, the adoption of advanced online measurement and control technologies in drying equipment is highlighted for real-time monitoring and optimization of drying parameters. The importance of optimizing existing processes to establish a comprehensive cassava industrial chain and foster the development of the cassava deep-processing industry is emphasized. This review provides valuable insights into the current trends and future prospects in cassava drying technologies, aiming to facilitate sustainable and efficient utilization of cassava resources for various applications.

The effect of the electromagnetic field on the physicochemical properties of isolated corn starch obtained of plants from irradiate seeds

Maize grains are composed of the pericarp, endosperm, and germ. Consequently, any treatment, such as electromagnetic fields (EMF) must alter these components, which in turn alters the physicochemical properties of the grain. Since starch is a major component of corn grain, and given the great industrial importance of starch, this study investigates how EMF affects the physicochemical properties of starch. Mother seed were exposed to three different intensities 23, 70, and 118 μT for 15 days. Except for a slight porosity on the surface of the starch of the grains of plants exposed to higher EMF, the starch showed no morphological differences between the different treatments and the control (according to scanning electron microscopy). The X-ray patterns showed that the orthorhombic structure was kept constant, unaffected by the intensity of EMF. However, the pasting profile of starch was affected, and a decrease in the peak viscosity was obtained when the intensity of EMF increased. In contrast to the control plants, FTIR shows characteristic bands which can be attributed to the stretching of the CO bonds at wave number 1.711 cm^-1. EMF can be considered a physical modification of starch.

Application of Machine Learning Using Color and Texture Analysis to Recognize Microwave Vacuum Puffed Pork Snacks

The objective of the study was to create artificial neural networks (ANN) capable of highly efficient recognition of modified and unmodified puffed pork snacks for the purposes of obtaining an optimal final product. The study involved meat snacks produced from unmodified and papain modified raw pork (Psoas major) by means of microwave-vacuum puffing (MVP) under specified conditions. The snacks were then analyzed using various instruments in order to determine their basic chemical composition, color and texture. As a result of the MVP process, the moisture-to-protein ratio (MPR) was reduced to 0.11. A darker color and reduction in hardness of approx. 25% was observed in the enzymatically modified products. Multi-layer perceptron networks (MLPN) were then developed using color and texture descriptor training sets (machine learning), which is undoubtedly an innovative solution in this area.