Quantification of starch content in germinating mung bean seedlings by terahertz spectroscopy

Determination of starch digestibility in white sweet potato after acid hydrolysis and heat-moisture treatment using terahertz spectroscopy

Acid hydrolysis and heat-moisture treatment (HMT) have been used to alter digestibility of starch in white sweet potato, providing health benefits. The potential of terahertz spectroscopy for rapid and non-destructive determination of starch digestibility in white sweet potato treated with acetic acid and citric acid, followed by HMT, was investigated. An in vitro starch digestibility assay was employed to measure the contents of rapidly digestible starch (RDS), slowly digestible starch (SDS), and resistant starch (RS). The intensities of the peaks attributed to covalent vibrational modes at 9.0, 10.5, and 13.1 THz showed a strong correlation with RDS content (R2 > 0.95). Moreover, the intensities of the peaks sensitive to non-covalent forces within and between double helices of starch, around 5.0 and 7.9 THz, were correlated with RS content (R2 > 0.65). These results indicate, after acid hydrolysis and HMT, the starch digestibility of white sweet potato can be determined using THz peaks.

Sustainable Materials Enabled Terahertz Functional Devices

Terahertz (THz) devices, owing to their distinctive optical properties, have achieved myriad applications in diverse domains including wireless communication, medical imaging therapy, hazardous substance detection, and environmental governance. Concurrently, to mitigate the environmental impact of electronic waste generated by traditional materials, sustainable materials-based THz functional devices are being explored for further research by taking advantages of their eco-friendliness, cost-effective, enhanced safety, robust biodegradability and biocompatibility. This review focuses on the origins and distinctive biological structures of sustainable materials as well as succinctly elucidates the latest applications in THz functional device fabrication, including wireless communication devices, macromolecule detection sensors, environment monitoring sensors, and biomedical therapeutic devices. We further highlight recent applications of sustainable materials-based THz functional devices in hazardous substance detection, protein-based macromolecule detection, and environmental monitoring. Besides, this review explores the developmental prospects of integrating sustainable materials with THz functional devices, presenting their potential applications in the future.

Overview of Deep Learning and Nondestructive Detection Technology for Quality Assessment of Tomatoes

Tomato, as the vegetable queen, is cultivated worldwide due to its rich nutrient content and unique flavor. Nondestructive technology provides efficient and noninvasive solutions for the quality assessment of tomatoes. However, processing the substantial datasets to achieve a robust model and enhance detection performance for nondestructive technology is a great challenge until deep learning is developed. The aim of this paper is to provide a systematical overview of the principles and application for three categories of nondestructive detection techniques based on mechanical characterization, electromagnetic characterization, as well as electrochemical sensors. Tomato quality assessment is analyzed, and the characteristics of different nondestructive techniques are compared. Various data analysis methods based on deep learning are explored and the applications in tomato assessment using nondestructive techniques with deep learning are also summarized. Limitations and future expectations for the quality assessment of the tomato industry by nondestructive techniques along with deep learning are discussed. The ongoing advancements in optical equipment and deep learning methods lead to a promising outlook for the application in the tomato industry and agricultural engineering.

Quantification of resistant starch content in rice after hydrothermal treatments using terahertz spectroscopy

Since hydrothermal treatments can enhance resistant starch (RS) content in rice and provide health benefits when consumed, a less laborious and non-destructive method to determine RS content is needed. Terahertz (THz) spectroscopy is hypothesized as a suitable method to quantify RS content in rice after hydrothermal treatment with its sensitivity for the intermolecular forces increase in the formation of RS. In this study, we first used the traditional in vitro hydrolysis method to determine the content of RS in rice. Then, the potential of starch absorbance peaks to quantify RS content after three commonly used hydrothermal methods, soaking, mild heat-moisture treatment, and parboiling, was investigated. The second derivative intensities of the peak at 9.0, 10.5, 12.1, and 13.1 THz were confirmed as being correlated with RS content and showed the high accuracy to predict RS content in samples (R2 > 0.96). Our results indicate the RS content of hydrothermally treated rice can be accurately quantified using these peaks.

Determining changes in crystallinity of rice starch after heat-moisture treatment using terahertz spectroscopy

To investigate the potential of Fourier-transform terahertz (FT-THz) spectroscopy to follow crystalline structure changes in rice starch after heat-moisture treatment (HMT), we measured the crystallinity by X-ray diffraction (XRD) spectra and found its correlation with THz spectra. According to A-type crystal structure and Vh-type crystalline structure of amylose-lipid complex (ALC) in rice starch, crystallinity is divided into A-type and Vh-type. The intensity of second derivative spectra peak at 9.0 THz was highly correlated with both A-type and Vh-type crystallinity. Additionally, other three peaks at 10.5 THz, 12.2 THz, and 13.1 THz were also sensitive to Vh-type crystalline structure. These results indicate that after HMT, the crystallinity of ALC (Vh-type) and A-type starch can be quantified using THz peaks.

Measuring heavy metal ions in water using nature existed microalgae as medium based on terahertz technology

Heavy metal pollution in water seriously affects human health. The disadvantages of traditional metal ion detection methods involve long and cumbersome chemical pretreatment in the early stage, and large volume of samples. In this study, microalgae were used as the medium, and terahertz spectroscopy technology was employed to collect the changes of material components in it, so as to deduce the types and concentrations of heavy metal pollution in water. Through the partial least square(PLS), we establish the prediction model of heavy metal concentration, and the results show that the best detection time for Pb²⁺ is 6 h and Ni²⁺ is 18 h. The principal component analysis(PCA) shows that β-carotene is the most affected substance. Afterward we collect five real surface waters in East China and verify that the judgment accuracy of Pb²⁺ and Ni²⁺ are 100% and 93.2% respectively. The results indicate that the time is shorter than the traditional pretreatment time from more than 20-6 h, the sample volume is reduced from 50 mL to 10 mL, the detection accuracy is improved from 10 ng/mL to 1 ng/mL. In a word, we provide a new fast and real-time method for biological monitoring of heavy metal pollution in water.

Study of Crystallinity and Conformation of Poly(lactic acid) by Terahertz Spectroscopy

During crystallization, conformational changes are often accompanied by the formation of interactions. Terahertz (THz) spectroscopy exhibits strong responses to the crystalline poly(lactic acid) (PLA). Therefore, we estimate the relative crystallinity and investigate the effect of conformational transition on the vibration of PLA by THz spectroscopy. By comparing with the results of X-ray diffraction (XRD) and differential scanning calorimetry (DSC), the validity of THz spectroscopy to calculate crystallinity is verified. Furthermore, the peak intensity of PLA at 2.01 THz increases with crystallinity. Combined with Fourier transform infrared spectroscopy (FTIR), the vibrational intensity of PLA at 2.01 THz is highly correlated with the contribution of gt conformation, showing a linear relationship. In addition, the vibrational peak of PLA also reflects the interchain interactions. We believe that the increase in peak intensity with increasing crystallinity originates from the effect of the dipole-dipole interactions between the carbonyl groups. Our study demonstrates the ability of THz spectroscopy to estimate the crystallinity of PLA, and the peak at 2.01 THz shows conformational and interaction sensitivities.

The Application of Terahertz Time-Domain Spectroscopy to Identification of Potato Late Blight and Fusariosis

Fusarium and late blight (fungal diseases of cereals and potatoes) are among the main causes of crop loss worldwide. A key element of success in the fight against phytopathogens is the timely identification of infected plants and seeds. That is why the development of new methods for identifying phytopathogens is a priority for agriculture. The terahertz time-domain spectroscopy (THz-TDS) is a promising method for assessing the quality of materials. For the first time, we used THz-TDS for assessing the infection of seeds of cereals (oats, wheat and barley) with fusarium and potato tubers of different varieties (Nadezhda and Meteor) with late blight. We evaluated the refractive index, absorption coefficient and complex dielectric permittivity in healthy and infected plants. The presence of phytopathogens on seeds was confirmed by microscopy and PCR. It is shown, that Late blight significantly affected all the studied spectral characteristics. The nature of the changes depended on the variety of the analyzed plants and the localization of the analyzed tissue relative to the focus of infection. Fusarium also significantly affected all the studied spectral characteristics. It was found that THz-TDS method allows you to clearly establish the presence or absence of a phytopathogens, in the case of late blight, to assess the degree and depth of damage to plant tissues.

Study of starch aging characteristics based on Terahertz technology

Traditional methods for the determination of starch aging indicators often have a series of shortcomings such as time-consuming, high cost, large human error, damage to samples, environmental pollution, and high requirements for inspectors. Therefore, it is meaningful to find or establish a dynamic fingerprint identification pattern that can detect the aging degree of starch during the process of processing or storage quickly and accurately. It not only provides guidance for starch food processing but also saves a lot of human, material resources, and time. Terahertz technology is an emerging molecular spectroscopy technology in the 21st century. It is with low energy and basically harmless to the human body. It can also realize nondestructive testing of samples. In the experiment, the samples were prepared by the tableting method and the samples containing 20% of 50 mg samples were prepared with polyethylene as the diluent. The thickness of the samples was 1 mm and the diameter was 13 mm. The terahertz time-domain spectrometer was used to obtain the spectral information of aging starch at different aging times. After the pretreatment of the spectrum by vector normalization, first derivative, and multiple scattering correction, the prediction models of aging days, crystallinity, and resilience of aging starch were established, respectively. The determination coefficient (R 2) of the established models is all greater than 95%, indicating that the established models are highly reliable and can be used to predict the aging days, crystallinity, and retrogradation degree of starch. And the R 2 of the prediction model based on the refractive index spectrum is greater than that of the absorption coefficient spectrum. The experimental method obtains the dynamic fingerprint identification map of starch in the aging process, realizes the real-time monitoring and detection of the starch aging process, and provides an effective means for the production and processing of starch-related industries.

Determination of starch crystallinity with the Fourier-transform terahertz spectrometer

We measured the terahertz (THz) spectra of native, amorphous, and dried starches derived from corn and potato using the Fourier-transform (FT) system and compared these spectra to the X-ray diffraction (XRD) patterns. Both native corn and potato starches had seven absorption peaks in the terahertz regions, but five peaks were observed in the amorphous states. While spectral changes slightly occurred in corn starch even after drying, increase and decrease in the terahertz peak intensities were obtained in potato starch during drying. Similar changes in both starches during amorphization and drying were obtained in the X-ray diffraction patterns, and the correlations were found between terahertz peaks and the X-ray signals. Since the intensity of the peak at 9.0 THz was correlated with crystallinity obtained using an X-ray diffraction (r² = 0.98), our data indicate that the Fourier-transform terahertz spectrometer can be a new analytical device to measure the starch crystallinity.

Terahertz spectroscopy combined with data dimensionality reduction algorithms for quantitative analysis of protein content in soybeans

Protein content in soybean is a key determinant of its nutritional and economic value. The paper investigated the feasibility of terahertz (THz) spectroscopy and dimensionality reduction algorithms for the determination of protein content in soybean. First of all, the THz sample spectrum was data processed by pre-processing or dimensionality reduction algorithms. Secondly, by calibration set, using partial least squares regression (PLSR), genetic algorithms-support vector regression (GA-SVR), grey wolf optimizer-support vector regression (GWO-SVR) and back propagation neural network (BPNN) were respectively used to model protein content determination. Afterwards, the model was validated by the prediction set. Ultimately, the BPNN model combined with linear discriminant analysis (LDA) for related coefficient of prediction set (Rp), root mean square error of prediction set (RMSEP), relative standard deviation (RSD), the time required for the operation was respectively 0.9677, 1.2467%, 3.3664%, and 53.51 s. The experimental results showed that the rapid and accurate quantitative determination of protein in soybean using THz spectroscopy is feasible after a suitable dimensionality reduction algorithm.

Characteristic terahertz absorption spectra of paramylon and paramylon-ester compounds

Paramylon is a long-chain polysaccharide, composed of glucose units connected via β-(1,3) glycosidic bonds, that spontaneously forms a three-strand helical bundle. Paramylon-esters can be made by partially or fully replacing saccharide chain hydroxide groups with carboxylic functional groups, such as stearoyl (CH₃(CH₂)₁₆CO) and palmitoyl (CH₃(CH₂)₂₄CO). The paramylon-ester with carboxylic acids has superior characteristics, including high thermal resistance, stability and transparency under visible light, which are necessary for thermoplastic applications. In this study, the absorption coefficient α(ν) and absorbance spectra of paramylons and paramylon-esters were measured in the 0.3-8.0 THz range and compared with the corresponding spectra of glucose and cellulose. Paramylon and paramylon-ester molecules were found to exhibit unique, so-called fingerprint, α(ν)peaks at 4.0, 6.0 and 8.0 THz, and 2.5 and 5.0 THz, respectively. We speculate that the spectral features observed are owing to intermolecular interaction modes of the weakly coupled polysaccharide chains. The paramylons with different molecular weights show very similar absorption features in the low-frequency side, both in spectral shapes and intensities, indicating that absorption is independent of molecular size. The paramylon-esters with varying degrees of substitution (DS) are similar spectral shapes but different intensities. A linear correlation between α(ν) peak intensity and the DS of paramylon-esters was established with the R² value above 0.99. This behavior can be used for the detection and identification of novel paramylon-ester molecules.

Lipids monitoring in Scenedesmus obliquus based on terahertz technology

BACKGROUND

Microalgae are considered as a source of low pollution and renewable fuel due to their ability to synthesize an abundance of lipids. Conventional methods for lipid quantification are time-consuming and chemically contaminated, while spectroscopic method combined with mathematical model is much more attractive due to its ability of qualitative and quantitative analysis of material composition, in this sense, terahertz technology provides not only timely and non-destructive testing without chemical pollution, but also provides information on the functional group vibration mode and structure of the measured components. Therefore, terahertz technology is utilized in our investigation and proposed for microalgae metabolism detection.

RESULTS

The aim of this study was to use terahertz spectroscopy to observe lipid content in Scenedesmus obliquus (S. obliquus). We collected the THz spectra of S. obliquus which were cultivated under nitrogen stress and terahertz spectroscopy was used to analyze changes in substance components (lipids, proteins, carbohydrates and β-carotene). The PLS algorithm was used to model the terahertz data to distinguish the different lipid content of S. obliquus under nitrogen stress. The correlation coefficient of the prediction results of the lipid characteristic band modeling was above 0.991, and the root mean square error was less than 0.132. It indicated that terahertz technology can be used to discriminate S. obliquus cells under different nitrogen stress effectively. The correlation between the terahertz characteristic peak (9.3 THz) and the total lipid content determined by gravimetry reaches 0.960. The final results were compared with the commonly used spectroscopic methods for lipid observation (Raman spectroscopy).

CONCLUSIONS

In this article, we demonstrated the effectiveness of terahertz spectroscopy to monitor changes in microalgae lipid content under nitrogen stress. Terahertz spectroscopy is more suitable for industrial production or ordinary laboratories which require intermediate result with low-frequency screening. When quantifying microalgae lipids, the constraint of terahertz spectroscopy is far less than that of Raman spectroscopy, and it is easier for operator to accurately quantify microalgae lipid. In addition, it is still in early stage for the study of microalgae using terahertz spectroscopy technology, there is still much potential for us to explore.

Terahertz spectroscopy technology as an innovative technique for food: Current state-of-the-Art research advances

With the dramatic development of source and detector components, terahertz (THz) spectroscopy technology has recently shown a renaissance in various fields such as medical, material, biosensing and pharmaceutical industry. As a rapid and noninvasive technology, it has been extensively exploited to evaluate food quality and ensure food safety. In this review, the principles and processes of THz spectroscopy are first discussed. The current state-of-the-art applications of THz and imaging technologies focused on foodstuffs are then discussed. The advantages and challenges are also covered. This review offers detailed information for recent efforts dedicated to THz for monitoring the quality and safety of various food commodities and the feasibility of its widespread application. THz technology, as an emerging and unique method, is potentially applied for detecting food processing and maintaining quality and safety.

Identification of Bacterial Blight Resistant Rice Seeds Using Terahertz Imaging and Hyperspectral Imaging Combined With Convolutional Neural Network

Because bacterial blight (BB) disease seriously affects the yield and quality of rice, breeding BB resistant rice is an important priority for plant breeders but the process is time-consuming. The feasibility of using terahertz imaging technology and near-infrared hyperspectral imaging technology to identify BB resistant seeds has therefore been studied. The two-dimensional (2D) spectral images and one-dimensional (1D) spectra provided by both imaging methods were used to build discriminant models based on a deep learning method, the convolutional neural network (CNN), and traditional machine learning methods, support vector machine (SVM), random forest (RF), and partial least squares discriminant analysis (PLS-DA). The highest classification accuracy was achieved by the discriminate model based on CNN using the terahertz absorption spectra. Confusion matrixes were pictured to show the identification details. The t-distributed stochastic neighbor embedding (t-SNE) method was used to visualize the process of CNN data processing. Terahertz imaging technology combined with CNN has great potential to quickly identify BB resistant rice seeds and is more accurate than using near-infrared hyperspectral imaging.

A Comprehensive Review on Food Applications of Terahertz Spectroscopy and Imaging

Food product safety is a public health concern. Most of the food safety analytical and detection methods are expensive, labor intensive, and time consuming. A safe, rapid, reliable, and nondestructive detection method is needed to assure consumers that food products are safe to consume. Terahertz (THz) radiation, which has properties of both microwave and infrared, can penetrate and interact with many commonly used materials. Owing to the technological developments in sources and detectors, THz spectroscopic imaging has transitioned from a laboratory-scale technique into a versatile imaging tool with many practical applications. In recent years, THz imaging has been shown to have great potential as an emerging nondestructive tool for food inspection. THz spectroscopy provides qualitative and quantitative information about food samples. The main applications of THz in food industries include detection of moisture, foreign bodies, inspection, and quality control. Other applications of THz technology in the food industry include detection of harmful compounds, antibiotics, and microorganisms. THz spectroscopy is a great tool for characterization of carbohydrates, amino acids, fatty acids, and vitamins. Despite its potential applications, THz technology has some limitations, such as limited penetration, scattering effect, limited sensitivity, and low limit of detection. THz technology is still expensive, and there is no available THz database library for food compounds. The scanning speed needs to be improved in the future generations of THz systems. Although many technological aspects need to be improved, THz technology has already been established in the food industry as a powerful tool with great detection and quantification ability. This paper reviews various applications of THz spectroscopy and imaging in the food industry.