Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data

Recent Advances in THz Detection of Water

The frequency range of terahertz waves (THz waves) is between 0.1 and 10 THz and they have properties such as low energy, penetration, transients, and spectral fingerprints, which are especially sensitive to water. Terahertz, as a frontier technology, have great potential in interpreting the structure of water molecules and detecting biological water conditions, and the use of terahertz technology for water detection is currently frontier research, which is of great significance. Firstly, this paper introduces the theory of terahertz technology and summarizes the current terahertz systems used for water detection. Secondly, an overview of theoretical approaches, such as the relaxation model and effective medium theory related to water detection, the relationship between water molecular networks and terahertz spectra, and the research progress of the terahertz detection of water content and water distribution visualization, are elaborated. Finally, the challenge and outlook of applications related to the terahertz wave detection of water are discussed. The purpose of this paper is to explore the research domains on water and its related applications using terahertz technology, as well as provide a reference for innovative applications of terahertz technology in moisture detection.

A Systematic Review of Advanced Sensor Technologies for Non-Destructive Testing and Structural Health Monitoring

This paper reviews recent advances in sensor technologies for non-destructive testing (NDT) and structural health monitoring (SHM) of civil structures. The article is motivated by the rapid developments in sensor technologies and data analytics leading to ever-advancing systems for assessing and monitoring structures. Conventional and advanced sensor technologies are systematically reviewed and evaluated in the context of providing input parameters for NDT and SHM systems and for their suitability to determine the health state of structures. The presented sensing technologies and monitoring systems are selected based on their capabilities, reliability, maturity, affordability, popularity, ease of use, resilience, and innovation. A significant focus is placed on evaluating the selected technologies and associated data analytics, highlighting limitations, advantages, and disadvantages. The paper presents sensing techniques such as fiber optics, laser vibrometry, acoustic emission, ultrasonics, thermography, drones, microelectromechanical systems (MEMS), magnetostrictive sensors, and next-generation technologies.

Multivariate Analysis on the Properties of Intact Cereal Kernels and Their Association with Viscoelasticity at Different Moisture Contents

The viscoelastic properties of cereal kernels are strongly related to their quality, which can be applied to the development of a more selective and objective classification process. In this study, the association between the biophysical and viscoelastic properties of wheat, rye, and triticale kernels was investigated at different moisture contents (12% and 16%). A uniaxial compression test was performed under a small strain (5%), and the increase in viscoelasticity at 16% moisture content corresponded to proportional increases in biophysical properties such as the appearance and geometry. The biophysical and viscoelastic behaviors of triticale were between those of wheat and rye. A multivariate analysis showed that the appearance and geometric properties significantly influenced kernel features. The maximum force showed strong correlations with all viscoelastic properties, and it can be used to distinguish between cereal types and moisture contents. A principal component analysis was performed to discriminate the effect of the moisture content on different types of cereals and to evaluate the biophysical and viscoelastic properties. The uniaxial compression test under a small strain and the multivariate analysis can be considered a simple and non-destructive tool for assessing the quality of intact cereal kernels.

Evaluation of the Heterogeneity of Wheat Kernels as a Traditional Model Object in Connection with the Asymmetry of Development

Wheat is one of the most important crops in the world, providing food for most of the world’s population. Wheat seeds are a popular model object for many experiments to evaluate various factors that improve germination or protect against various adverse stressful effects. Based on the high significance of increasing the productivity of this cereal crop and the applicability of this object, a detailed statistical evaluation of wheat grain (kernel) morphometry was carried out to assess the asymmetry of parameters of this ideal model. Depending on the location of the kernels in the spikelet of a wheat spike, there was a significant asymmetry between the right and left cheeks of the kernels located closer or further from the center of the spikelet. The expressiveness of asymmetry, and consequently, the kernel deformation was higher in the lower kernels of the spikelet. The degree of symmetry; that is, the similarity of the two halves (cheeks) and the kernel as a whole, was higher in kernels located higher in the spikelet. It seems that the reason for this phenomenon lies in the mechanical nature of kernel deformation. The ultrastructure of A-type and B-type starch grains in the central part of the kernel had significant differences between the upper and lower kernels, which indicated in favor of a high probability of differences by the composition and quality of kernels of the same variety when assessed separately. Uniform development of kernels and smaller differences between them may reveal more valuable genotypes in the future, provided their steady reproduction under adverse conditions of a changing climate.

Overview of Rapid Detection Methods for Salmonella in Foods: Progress and Challenges

Salmonella contamination in food production and processing is a serious threat to consumer health. More and more rapid detection methods have been proposed to compensate for the inefficiency of traditional bacterial cultures to suppress the high prevalence of Salmonella more efficiently. The contamination of Salmonella in foods can be identified by recognition elements and screened using rapid detection methods with different measurable signals (optical, electrical, etc.). Therefore, the different signal transduction mechanisms and Salmonella recognition elements are the key of the sensitivity, accuracy and specificity for the rapid detection methods. In this review, the bioreceptors for Salmonella were firstly summarized and described, then the current promising Salmonella rapid detection methods in foodstuffs with different signal transduction were objectively summarized and evaluated. Moreover, the challenges faced by these methods in practical monitoring and the development prospect were also emphasized to shed light on a new perspective for the Salmonella rapid detection methods applications.