Determination of trace elements in soybean by X-ray fluorescence analysis and its application to identification of their production areas

Determination of elements in cereals, pseudocereals, and legumes by microwave plasma-atomic emission spectrometry

A novel method for multi-element analysis in cereals, pseudocereals, and legumes was developed for principal (calcium, magnesium, potassium, and phosphorus) and trace (manganese, zinc, iron, copper, and aluminum) element determination using a microwave plasma-atomic emission spectrometer (MP-AES). The method was validated using certified reference analyte values from durum wheat (DUWF-1), corn bran (BRAN-1), quinoa (KINO-1), rice (SRM 1568b), and soy (SRM 3234). Spike recoveries were assessed using field-grown crops that represent staple and minor crops with variable matrix compositions. A closed-vessel microwave-assisted digestion method consisting of 12 mL of deionized water, 2 mL of HNO3, and 2 mL of H2O2 was efficient for the mineralization of all crops. Acceptable measurement agreement was achieved between certified and determined values for all reference materials with recovery ranges from 89 to 120 percent. Plant breeders can use the method to develop and screen crops for improved nutrient density.

Production of Magnesium Dilactate through Lactic Acid Fermentation with Magnesium Carbonate

Magnesium dilactate is increasingly sought after for its applications in the pharmaceutical, food, and dietary supplement industries due to its essential role in various physiological processes. This study explores a sustainable method for synthesizing magnesium dilactate through lactic acid fermentation using tomato juice, coupling the neutralization of lactic acid with hydrated magnesium carbonate hydroxide. Utilizing the lactic acid bacteria Lactobacillus paracasei and Lactobacillus plantarum, fermentation was optimized in a 50% diluted MRS medium supplemented with glucose and tomato juice supplemented with glucose, yielding a maximum lactate concentration of 107 g/L. Notably, fermentation in diluted media proved more effective than in undiluted tomato juice, highlighting the inhibitory effects of certain organic compounds and the physical nature of the original tomato juice. Post-fermentation, magnesium lactate was crystallized, achieving high recovery rates of up to 95.9%. Characterization of the product through X-ray diffraction and scanning electron microscopy confirmed its crystalline purity. This research underscores the viability of tomato juice as a fermentation substrate, promoting the valorization of agricultural by-products while providing an eco-friendly alternative to traditional chemical synthesis methods for magnesium dilactate production.

High Recovery of Ceramic Membrane Cleaning Remediation by Ozone Nanobubble Technology

The persistent issue of ceramic membrane fouling poses significant challenges to its widespread implementation. To address this concern, ozone nanobubbles (ozone-NBs) have garnered attention due to their remarkable mass transfer efficiency. In this investigation, we present a novel ozone-NB generator system to effectively clean a fouled ceramic membrane that is typically employed in the dye industry. The surface characteristics of the ceramic membrane underwent significant alterations, manifesting incremental changes in surface roughness and foulant accumulation reduction, as evidenced in atomic force microscopy, scanning electron microscopy, X-ray fluorescence, and energy-dispersive spectroscopy. Remarkably, the sequential 4 h cleaning process demonstrates an effective outcome leading to an almost 2-fold enhancement in the membrane flux. The initial fouled state of 608 L/h/m2 increased to 1050 L/h/m2 in the 4 h state with a recovery of 50%. We propose such membrane performance improvement governed by the ozone-NBs with a size distribution of 213.2 nm and a zeta potential value of -20.26 ± 0.13 mV, respectively. This effort showcases a substantial innovative and sustainable technology approach toward proficient foulant removal in water treatment applications.

Development of a Gene-Based Soybean-Origin Discrimination Method Using Allele-Specific Polymerase Chain Reaction

A low soybean self-sufficiency rate in South Korea has caused a high import dependence and considerable price variation between domestic and foreign soybeans, causing the false labeling of foreign soybeans as domestic. Conventional soybean origin discrimination methods prevent a single-grain analysis and rely on the presence or absence of several compounds or concentration differences. This limits the origin discrimination of mixed samples, demonstrating the need for a method that analyzes individual grains. Therefore, we developed a method for origin discrimination using genetic analysis. The whole-genome sequencing data of the Williams 82 reference cultivar and 15 soybean varieties cultivated in South Korea were analyzed to identify the dense variation blocks (dVBs) with a high single-nucleotide polymorphism density. The PCR primers were prepared and validated for the insertion-deletion (InDel) sequences of the dVBs to discriminate each soybean variety. Our method effectively discriminated domestic and foreign soybean varieties, eliminating their false labeling.

Towards Verifying the Imported Soybeans of China Using Stable Isotope and Elemental Analysis Coupled with Chemometrics

Verifying the geographical origin of soybeans (Glycine max [Linn.] Merr.) is a major challenge as there is little available information regarding non-parametric statistical origin approaches for Chinese domestic and imported soybeans. Commercially procured soybean samples from China (n = 33) and soybeans imported from Brazil (n = 90), the United States of America (n = 6), and Argentina (n = 27) were collected to characterize different producing origins using stable isotopes (δ2H, δ18O, δ15N, δ13C, and δ34S), non-metallic element content (% N, % C, and % S), and 23 mineral elements. Chemometric techniques such as principal component analysis (PCA), linear discriminant analysis (LDA), and BP-artificial neural network (BP-ANN) were applied to classify each origin profile. The feasibility of stable isotopes and elemental analysis combined with chemometrics as a discrimination tool to determine the geographical origin of soybeans was evaluated, and origin traceability models were developed. A PCA model indicated that origin discriminant separation was possible between the four soybean origins. Soybean mineral element content was found to be more indicative of origin than stable isotopes or non-metallic element contents. A comparison of two chemometric discriminant models, LDA and BP-ANN, showed both achieved an overall accuracy of 100% for testing and training sets when using a combined isotope and elemental approach. Our findings elucidate the importance of a combined approach in developing a reliable origin labeling method for domestic and imported soybeans in China.

Peculiar properties of tuber starch in a potato mutant lacking the α-glucan water dikinase 1 gene GWD1 created by targeted mutagenesis using the CRISPR/dMac3-Cas9 system

Glucose chains in starch are phosphorylated and contribute to structural stabilization. Phosphate groups contained in starch also play a role in retaining moisture. α-Glucan water dikinase 1 (GWD1) is involved in the phosphorylation of glucose chains in starch. In this study, we generated potato mutants of the GWD1 gene using the CRISPR/dMac3-Cas9 system. Observation of the phenotypes of the GWD1-deficient mutants revealed their physiological roles in tuber starch formation. The 4-allele mutants showed growth retardation and a delay in tuber formation. A significant decrease in phosphorus content was detected in the tuber starch of the gwd1 mutant. This mutant starch showed a higher amylose content than the wild-type starch, whereas its gelatinization temperature was slightly lower than that of the WT starch. The peak viscosity of the mutant starch was lower than that of the WT starch. These observations revealed that the starch of the gwd1 mutants had peculiar and unique properties compared to those of WT, sbe3 and gbss1 mutant starches. The amount of tissue-released water due to freeze-thawing treatment was determined on tubers of the gwd1 mutant and compared with those of WT and the other mutants. Significantly less water loss was found in the gwd1, sbe3 and gbss1 mutant tubers than in the WT tubers. Our results indicate that the GWD1 gene is not only important for potato growth, but also largely effective for the traits of tuber starch.

Soybean sorting based on protein content using X-ray fluorescence spectrometry

The purpose of this research was to evaluate performance of an energy-dispersive X-ray fluorescence (XRF) sensor to classify soybean based on protein content. The hypothesis was that sulfur signals and other XRF spectral features can be used as proxies to infer soybean protein content. Sample preparation and equipment settings to optimize detection of S and other specific emission lines were tested for this application. A logistic regression model for classifying soybean as high- or low-protein was developed based on XRF spectra and protein contents. Additionally, the model was validated with an independent set of samples. Global accuracies of the method were 0.83 (training set) and 0.81 (test set) and the corresponding kappa indices were 0.66 and 0.61, respectively. These numbers indicated satisfactory performance of the sensor, suggesting that XRF spectral features can be applied for screening protein content in soybean.

A review of conventional and rapid analytical techniques coupled with multivariate analysis for origin traceability of soybean

Soybean has developed a reputation as a superfood due to its nutrient profile, health benefits, and versatility. Since 1960, its demand has increased dramatically, going from a mere 17 MMT to almost 358 MMT in the production year 2021/22. These extremely high production rates have led to lower-than-expected product quality, adulteration, illegal trade, deforestation, and other concerns. This necessitates the development of an effective technology to confirm soybean's provenance. This is the first review that investigates current analytical techniques coupled with multivariate analysis for origin traceability of soybeans. The fundamentals of several analytical techniques are presented, assessed, compared, and discussed in terms of their operating specifics, advantages, and shortcomings. Additionally, significance of multivariate analysis in analyzing complex data has also been discussed.

An overview on multi-elemental profile integrated with chemometrics for food quality assessment: toward new challenges

Food products, especially those with high value-added, are commonly subjected to strict quality controls, which are of paramount importance, especially for attesting to some peculiar features related, for instance, to their geographical origin and/or the know-how of their producers. However, the sophistication of fraudulent practices requires a continuous update of analytical platforms. Different analytical techniques have become extremely appealing since the instrumental analysis tools evolution has substantially improved the capability to reveal and understand the complexity of food. In light of this, multi-elemental composition has been successful implemented solving a plethora of food authentication and traceability issues. In the last decades, it has existed an ever-increasing trend in analysis based on spectrometry analytical platforms in order to obtain a multi-elemental profile that combined with chemometrics have been noteworthy analytical methodologies able to solve these problems. This review provides an overview of published reports in the last decade (from 2011 to 2021) on food authentication and quality control from their multi-element composition in order to evaluate the state-of-the-art of this field and to identify the main characteristics of applied analytical techniques and chemometric data treatments that have permit achieve accurate discrimination/classification models, highlighting the strengths and the weaknesses of these methodologies.

Distinguishing Korean and Chinese red pepper powder using inductively coupled plasma and X-ray fluorescence-based analysis

This study aimed to distinguish between Korean and Chinese red pepper powder (RPP) using inorganic elemental analysis data combined with orthogonal partial least squares-discriminant analysis (OPLS-DA). Elemental concentrations were obtained for 31 Korean and 31 Chinese RPP samples that were collected in Korea. Energy dispersive X-ray fluorescence spectroscopy detected 11 elements in these samples. Rb and Cl concentrations were selected as the variables which best allowed distinguishing between Korean and Chinese RPP using an S-plot from OPLS-DA. Rb and Cl concentrations in the Korean RPP samples were ≤ 1.6 mg/100 g (measured by inductively coupled plasma-optical emission spectroscopy) and ≤ 215 mg/100 g, respectively. A blind trial demonstrated that Korean RPP containing ≥ 50 g/100 g of Chinese RPP could be identified by applying predetermined ranges of Rb and Cl concentrations, suggesting that analysis of these two elements is a possible approach to distinguish between Korean and Chinese RPP.

Wheat authentication：An overview on different techniques and chemometric methods

Wheat (Triticum aestivum L.) is one of the most important cereal crops and is consumed as a staple food around the globe. Wheat authentication has become a crucial issue over the last decades. Recently, many techniques have been applied in wheat authentication including the authentication of wheat geographical origin, wheat variety, organic wheat, and wheat flour from other cereals. This paper collected related literature in the last ten years, and attempted to highlight the recent studies on the discrimination and authentication of wheat using different determination techniques and chemometric methods. The stable isotope analysis and elemental profile of wheat are promising tools to obtain information regarding the origin, and variety, and to differentiate organic from conventional farming of wheat. Image analysis, genetic parameters, and omics analysis can provide solutions for wheat variety, organic wheat, and wheat adulteration. Vibrational spectroscopy analyses, such as NIR, FTIR, and HIS, in combination with multivariate data analysis methods, such as PCA, LDA, and PLS-DA, show great potential in wheat authenticity and offer many advantages such as user-friendly, cost-effective, time-saving, and environment friendly. In conclusion, analytical techniques combining with appropriate multivariate analysis are very effective to discriminate geographical origin, cultivar classification, and adulterant detection of wheat.

Identification of loci controlling mineral element concentration in soybean seeds

BACKGROUND

Mineral nutrients play a crucial role in the biochemical and physiological functions of biological systems. The enhancement of seed mineral content via genetic improvement is considered as the most promising and cost-effective approach compared alternative means for meeting the dietary needs. The overall objective of this study was to perform a GWAS of mineral content (Ca, K, P and S) in seeds of a core set of 137 soybean lines that are representative of the diversity of early maturing soybeans cultivated in Canada (maturity groups 000-II).

RESULTS

This panel of 137 soybean lines was grown in five environments (in total) and the seed mineral content was measured using a portable x-ray fluorescence (XRF) spectrometer. The association analyses were carried out using three statistical models and a set of 2.2 million SNPs obtained from a combined dataset of genotyping-by-sequencing and whole-genome sequencing. Eight QTLs significantly associated with the Ca, K, P and S content were identified by at least two of the three statistical models used (in two environments) contributing each from 17 to 31% of the phenotypic variation. A strong reproducibility of the effect of seven out these eight QTLs was observed in three other environments. In total, three candidate genes were identified involved in transport and assimilation of these mineral elements.

CONCLUSIONS

There have been very few GWAS studies to identify QTLs associated with the mineral element content of soybean seeds. In addition to being new, the QTLs identified in this study and candidate genes will be useful for the genetic improvement of soybean nutritional quality through marker-assisted selection. Moreover, this study also provides details on the range of phenotypic variation encountered within the Canadian soybean germplasm.

Portable X-ray fluorescence for environmental assessment of soils: Not just a point and shoot method

Portable XRF is a rapid, mobile, high throughput, and potentially cost effective instrumental analytical technique capable of elemental assessment. It is widely used for environmental assessment of soils in a variety of contexts such as agriculture and pollution both in-situ and ex-situ, to varying levels of success. Portable XRF performance for soil analysis is often validated against wet chemistry techniques but a range of factors may give rise to elementally dependent disparities affecting accuracy and precision assessments. These include heterogeneity, analysis times, instrument stability during analyses, protective thin films, incident X-rays, sample thickness, sample width, analyte interferences, detector resolution, power source fluctuations and instrumental drift. Light elements comprising water and organic matter (i.e. carbon, oxygen) also negatively affect measurements due to X-ray scattering and attenuation. The often-overlooked phenomenon of variability in both soil organic matter and water can also affect soil density (e.g. shrink-swell clays) and thus sample critical thickness which in turn affects the effective volume of sample analyzed. Compounding this, for elements having lower characteristic fluorescence energy, effective volumes of analyses are lower and thus measurements may not be representative of the whole sample. Understanding the effects and interplay between determined elemental concentrations and soil organic matter, water, and critical thickness together with the subtlety of theoretical effective volumes of analyses will help analysts mitigate potential problems and assess the applicability, advantages and limitations of PXRF for a given site. We demonstrate that with careful consideration of these factors and a systematic approach to analysis which we summarize and present, PXRF can provide highly accurate results.

Enhanced XRF Methods for Investigating the Erosion-Resistant Functional Coatings

The development of erosion-resistant functional materials usable as plasma facing first wall components (PFC) is crucial for increasing the lifetime of future fusion reactors. Generally, PFCs have to be quality checked and characterized regarding their composition, before integrating them into the fusion reactor vessel. Enhanced X-ray fluorescence (XRF) methods represent an effective alternative to conventional analysis methods for the characterization of refractive metallic coatings on large areas of fusion materials. We have developed and applied XRF methods as fast and robust methods for the characterization of the thickness and composition uniformity of complex functional coatings. These coatings consist of tungsten included in multilayer configuration and deposited on low or high Z substrates. We have further developed customized calibration protocols for quantifying the element composition and layer thickness of each investigated sample. The calibration protocols are based on a combination of standard samples measurements, Monte Carlo simulations, and fundamental parameter theoretical calculations. The calibrated results are discussed considering a selection of relevant PFC samples. The deposition uniformity was successfully investigated for different PFC-relevant tiles and lamella shaped samples with W layers below and over the W L-line saturation thickness. Also, the 2D thickness mapping capability of the XRF method was demonstrated by studying the plasma post-erosion pattern.

XRF techniques to quantify heavy metals in vegetables at low detection limits

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Calibration routines for quantification of Pb in vegetables with XRF are optimized.

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These XRF methods achieved detection limits of 0.3 μg g⁻¹ for Pb in dry vegetables.

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Pb in raw vegetables is quantified at levels as low as 1 μg g⁻¹ with ED-XRF.

Sample preparation techniques, measurement routines and custom calibrations were developed and optimized for the quantification of Pb and additional heavy metals in dried and wet consumable vegetable tissues via WD-XRF and/or portable ED-XRF spectroscopy. After mitigating matrix influences fundamental to XRF quantification of heavy metals in a carbon matrix, the custom measurement and calibration routines were capable of detecting and quantifying Pb in dried prepared vegetable samples at concentrations relevant to the World Health Organization. The viability of each calibration was evaluated with measurements of vegetables grown in metals-rich garden soil collected from residential properties. Although robust calibrations for dried vegetables were obtained with WD-XRF, the slight compromise in the precision and accuracy of measurements with portable ED-XRF is offset by the portability of this technology. Heavy metal concentrations in wet coarsely-homogenized raw consumable vegetable tissues were quantified; however, further work is needed to test the viability of ED-XRF calibrations.

"Manganese-induced neurotoxicity: a review of its behavioral consequences and neuroprotective strategies"

Manganese (Mn) is an essential heavy metal. However, Mn’s nutritional aspects are paralleled by its role as a neurotoxicant upon excessive exposure. In this review, we covered recent advances in identifying mechanisms of Mn uptake and its molecular actions in the brain as well as promising neuroprotective strategies. The authors focused on reporting findings regarding Mn transport mechanisms, Mn effects on cholinergic system, behavioral alterations induced by Mn exposure and studies of neuroprotective strategies against Mn intoxication. We report that exposure to Mn may arise from environmental sources, occupational settings, food, total parenteral nutrition (TPN), methcathinone drug abuse or even genetic factors, such as mutation in the transporter SLC30A10. Accumulation of Mn occurs mainly in the basal ganglia and leads to a syndrome called manganism, whose symptoms of cognitive dysfunction and motor impairment resemble Parkinson’s disease (PD). Various neurotransmitter systems may be impaired due to Mn, especially dopaminergic, but also cholinergic and GABAergic. Several proteins have been identified to transport Mn, including divalent metal tranporter-1 (DMT-1), SLC30A10, transferrin and ferroportin and allow its accumulation in the central nervous system. Parallel to identification of Mn neurotoxic properties, neuroprotective strategies have been reported, and these include endogenous antioxidants (for instance, vitamin E), plant extracts (complex mixtures containing polyphenols and non-characterized components), iron chelating agents, precursors of glutathione (GSH), and synthetic compounds that can experimentally afford protection against Mn-induced neurotoxicity.

Validation and comparable analysis of aluminum in the popular Chinese fried bread youtiao by wavelength dispersive XRF

Aluminum (Al) is an element in alum commonly used as a raising agent for Chinese flour products, especially for a typical fried food youtiao. In the present study, the feasibility of wavelength dispersive X-ray fluorescence spectrometry (WDXRF) for analysis of aluminum levels in youtiao was examined. Youtiao samples spiked with known amounts of aluminum were used for calibration. Linearity, accuracy, precision, and detection and quantification limits were tested, based on three calibration curves. For further validation, test youtiao samples were analyzed by both WDXRF and inductively coupled plasma optical emission spectrometry (ICP-OES). Comparison of the two methods showed that measurement performance was not significantly different. Taken together, these results indicate that WDXRF can form the basis of a rapid and simple methodology for measuring the aluminum content of youtiao, and that it is a good candidate for replacing ICP-OES for analyzing Al-containing flour products.

A nondestructive approach for discrimination of the origin of sesame seeds using ED-XRF and NIR spectrometry with chemometrics

An energy dispersive X-ray fluorescence (ED-XRF) spectrometer and a near infrared (NIR) spectrometer combined with chemometrics were applied for origin discrimination of 48 Korean, 44 Chinese, and 21 Indian sesame seed samples used for development of a discriminant calibration model. Multi-elemental ED-XRF analysis based on Mg, Al, Si, P, S, Cl, K, Ca, Mn, Fe, and Cu was used for comparisons among origins. All elements, except for Fe, showed differences and 96.5% of seed samples were assigned to the correct origin using discriminant analysis based on chemical analytical results. NIR measurements were performed for spectral scanning. Classification of seeds using NIR discriminant analysis achieved 89.4% of seed samples assigned to the correct origin. Both ED-XRF and NIR are useful as nondestructive tools for discrimination of sesame seed origins.

Non-invasive sensing for food reassurance

The main food quality traits of interest using non-invasive sensing techniques are sensory characteristics, chemical composition, physicochemical properties, health-protecting properties, nutritional characteristics and safety. A wide range of non-invasive sensing techniques, from optical, acoustical, electrical, to nuclear magnetic, X-ray, biosensor, microwave and terahertz, are organized according to physical principle.