Wheat Samples Research Articles

A highly efficient homogeneous electrochemiluminescence aptasensor for amplified analysis of Ochratoxin A

Ochratoxin A (OTA) is a toxic thermostable subordinate metabolite produced by Aspergillus and Penicillium species. OTA contamination occurs in a wide range of foods and poses a threat to human health. Therefore, it is crucial to construct a sensitive and reliable method for analyzing OTA to ensure food safety. Herein, a simple yet sensitive ECL aptasensor has been constructed for OTA detection through the synergistic amplification between catalytic DNA assembly (CDA) and exonuclease III (Exo III)-initiated recycling reaction. The anti-OTA aptamer-encoded sensing unit specifically recognizes target OTA and leads to the release of the trigger sequence for stimulating the CDA circuit, yielding numerous dsDNA hybrids that carry the re-assembled S strand. Each of the as-assembled S sequence could hybridize with the Ru(bpy)32+-labeled substrate (S*-Ru) to produce a T-shape structure with a blunt 3′ terminus, which can be hydrolyzed and digested by Exo III, leading to the liberation of mononucleotide functionalized with Ru(bpy)32+ (Ru). Simultaneously, the S sequence was released and hybridized with another S*-Ru sequence for initiating the subsequent cycle of Exo III-stimulated digestion process until all the S*-Ru strands are digested, thus resulting in the generation of numerous Ru and remarkably amplified ECL signals for high-performance detection of OTA. With reliable analyte recognition and high signal gain, the ECL system enabled the high-performance and accurate determination of OTA in buffer, wheat, and wine samples, thus showing considerable potential applications for highly efficient determination of contaminants of low concentration in foodstuff.

The Combined ICP-MS, ESEM-EDX, and HAADF-STEM-EDX Approach for the Assessment of Metal Sub-Micro- and Nanoparticles in Wheat Grain.

Metal sub-microparticles (SMPs) and nanoparticles (NPs) presence in food is attributable to increasing pollution from the environment in raw materials and finished products. In the present study, a multifaceted analytical strategy based on Environmental Scanning Electron Microscopy and High-Angle Annular Dark-Field-Scanning Transmission Electron Microscopy coupled with Energy-Dispersive X-ray Spectroscopy (ESEM-EDX, HAADF-STEM-EDX) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was proposed for the detection and characterization of metal and metal-containing SMPs and NPs in durum wheat samples, covering a size measurement range from 1 nm to multiple µm. ESEM-EDX and ICP-MS techniques were applied for the assessment of SMP and NP contamination on the surface of wheat grains collected from seven geographical areas characterized by different natural and anthropic conditions, namely Italy, the USA, Australia, Slovakia, Mexico, Austria, and Russia. ICP-MS showed significant differences among the mean concentration levels of metals, with the USA and Italy having the highest level. ESEM-EDX analysis confirmed ICP-MS concentration measurements and measured the highest presence of particles < 0.8 µm in size in samples from Italy, followed by the USA. Less marked differences were observed when particles < 0.15 µm were considered. HAADF-STEM-EDX was applied to a selected number of samples for a preliminary assessment of internal contamination by metal SMPs and NPs, and to expand the measurable particle size range. The multifaceted approach provided similar results for Fe-containing SMPs and NPs. ICP-MS and ESEM-EDX also highlighted the presence of a significant abundance of Ti- and Al-containing particles, while for STEM-EDX, sample preparation artifacts complicated the interpretation. Finally, HAADF-STEM-EDX results provided relevant information about particles in the low nm range, since, by applying this technique, no particles smaller than 50 nm were observed in accordance with ESEM-EDX.

Firefly Interval Selection Combined With Extreme Learning Machine for Spectral Quantification of Complex Samples

ABSTRACTFirefly algorithm (FA) combined with extreme learning machine (ELM) is developed for spectral interval selection and quantitative analysis of complex samples. The method firstly segments the spectra into a certain number of intervals. Vectors with 1 and 0, which represent the interval selected or not, are used as the inputs of the FA. The RMSEP value predicted by ELM model is used as the fitness function of the FA. The activation function and number of hidden layer nodes of ELM, number of spectral intervals, population number, environmental absorbance, and constant of FA are optimized. The predictive performance of FA‐ELM is compared with full‐spectrum PLS, ELM, genetic algorithm‐ELM (GA‐ELM), and particle swarm optimization‐ELM (PSO‐ELM) by one ultraviolet (UV) spectrum dataset of gasoil and three near‐infrared (NIR) spectral datasets of corn, wheat, and tablet samples. The results show that FA‐ELM has a better performance compared with its competitors in predicting monoaromatics, water, wheat kernel texture, and active pharmaceutical ingredients (APIs) in gasoil, corn, wheat, and tablet samples.

Ro-YOLOv5: One new detector for Impurity in wheat based on Circular Smooth Label

Wheat impurity content is one of the crucial indicators for evaluating wheat quality grades and prices, serving as an essential inspection parameter for grain storage. Due to the substantial intra-class variations in the aspect ratios of wheat impurities, traditional object detection algorithms fail to consider the diverse shapes and sizes of wheat impurities in real-world scenarios, resulting in low detection accuracy and missed detections. To address those issues, a YOLOv5-based wheat impurity automatic detection method, named Ro-YOLOv5, is proposed for computed tomography (CT) images of wheat samples. This method introduces rotated detection boxes and Circular Smooth Label (CSL) to transform angle regression predictions into angle classification predictions, effectively resolving issues related to angle periodicity and boundary exchange in regression; Additionally, the GIOU loss function in YOLOv5 is replaced with the CIOU loss function, which is more suitable for wheat impurity targets, ensuring the lower loss values and stable boundary regression. When creating the impurity-containing wheat dataset, a hybrid filtering method is introduced for leveraging the damping characteristics of the S-L filter for suppressing high-frequency components in projection images, thereby mitigating oscillation phenomena; Moreover, the Blackman filter is employed for image sharpening to preserve more image detail components. Experiments results have shown that the proposed algorithm achieves a mean average precision of 88.83% on the self-made dataset, representing a 7.56% improvement over the original YOLOv5 baseline network. The average detection time is 11.6ms, meeting the performance requirements for detecting wheat impurities.

Green Synthesis of Silver Nanoparticles with Hyssopus officinalis and Salvia officinalis Extracts, Their Properties, and Antifungal Activity on Fusarium spp.

Recent focus has been given to nanoparticles as an alternative fungicidal compound instead of chemical ones. More environmentally friendly ways of synthesis are the highest priority regarding the antifungal agents in the agriculture sector. Therefore, in this research, hyssop (H. officinalis) and sage (S. officinalis) aqueous extracts were prepared and used as a reducing source in the green synthesis of silver nanoparticles (AgNPs). Aqueous extracts and green synthesized AgNPs were examined for phytochemical composition and antioxidant capacity. Hyssop and sage extracts based AgNPs were analyzed using UV-vis spectrometry, SEM-EDS, and TEM-EDS. Antifungal activity against Fusarium spp. isolates collected from different infected crops was determined. Fusarium spp. isolates from strawberry, asparagus, pea, carrot, wheat, and rapeseed samples identified at the molecular level by translation elongation factor 1-alpha (TEF1α) gene amplification and sequencing. Green synthesized AgNPs had lower phytochemical content, however higher antioxidant activity compared to pure extracts. Both hyssop and sage extracts are suitable reducing agents for AgNPs formation, and sage extract results in larger particle size. Aqueous hyssop extract had higher antifungal activity than aqueous sage extract. However, a 10% concentration of whole sage extract based AgNPs solution, added to the PDA medium, and a 5% concentration of hyssop extract based AgNPs inhibited Fusarium spp. the most. F. proliferatum was the most sensitive to all treatments among the other fungi.

Investigating the Efficacy of Dry Region Zinc Solubilizing Bacteria for Growth Promotion of Maize and Wheat under Axenic Conditions

Zinc (Zn) plays a crucial role as a micronutrient, essential for the growth, development, and proper functioning of plants. Pakistani soils are deficient of micronutrient especially zinc. Supplementation of Zn fertilizers cannot do the job because only a small fraction of Zn is available to plants and rest is fixed in soil. To enhance the Zn availability different methods are being used which are expensive. Zinc solubilizing bacteria (ZSB) can be a potential candidate for solubilization of Zn and growth promoting activities in cereals. The present study aimed to evaluate the potential of dry region bacterial strains of Bahawalpur for improving Zn uptake and growth improvement in wheat and maize. Rhizosphere samples of wheat and maize were taken from the dry regions of Bahawalpur and bacterial strains were isolated and tested for their Zn solubilizing ability and screened for urease, siderophore activity, exopolysaccharide production, phosphorus solubilization and plant growth promoting abilities. Under axenic conditions selected isolates were further screened to assessed for improving the growth of wheat and maize seedlings. The rhizobacterial isolates IUB-34, IUB-80, IUB-93 and IUB-96 performed best to improve growth, physiology, biochemical attributes and root colonization. The maximum increase in root and shoot lengths were recorded 32.2 and 35.7% in wheat under IUB-34 application and in maize 43.8 and 39.9%, respectively, under IUB-96 application as compared to uninoculated control. Furthermore, maximum root colonization was also recorded under IUB-34 in wheat and IUB-96 in maize seedlings. Moreover, the biochemical characterization of selected isolates showed IAA (Auxins) production, protease, catalase, cellulose degradation, HCN and ACC-deaminase activities by these strains. However, only IUB-34 and IUB-96 were found positive for oxidase activity. Therefore, study concluded that use of dry region ZSB can solubilize Zn and make it available for plant to improve growth of wheat and maize. So, these isolates may be utilized for coating urea as a biofertilizer to increase the biofortification in cereals.

Calibration transfer by likelihood maximization: A standard-free method for multiple instruments

Most calibration transfer methods involve transfer between two instruments. Yet, in the context of manufacturing, a model might need to be applied to multiple instruments. Another typical constraint is the acquisition of transfer standards for both instruments with the same variables. These limitations become even more restrictive for multiple probes. Some methods are capable of building models adapted to multiple instruments, but all instruments must be considered during calibration. As such, additional instruments cannot be included a posteriori without changing the initial calibration. Calibration transfer by likelihood maximization has the potential to be applied to multiple instruments without creating a new model each time a new instrument is added. The method is also standard-free and can deal with instruments that have different variables. In this paper, we demonstrate the method’s capacity to use the same model to predict protein content in wheat samples from spectra acquired on four different instruments.

Occurrence and characterization of Puccinia triticina in Zimbabwe

Wheat leaf rust caused by Puccinia triticina (Pt) is an important disease of bread wheat in Zimbabwe. This study was carried out to determine the distribution, avirulence/virulence profile(s) and genotypic variation among isolates of the pathogen. In total, 104 single-pustule isolates were established from infected wheat samples that were collected from the main wheat production regions in Zimbabwe in surveys conducted from 2019 to 2021. Phenotyping of the isolates on a set of 46 differential and additional wheat lines revealed a single Pt race, MCDS. For genotypic assessment, 48 Pt isolates, including eight South African races, were genotyped with 19 microsatellite markers. Using the Bayesian model, isolates were subdivided into three clusters in both a DARwin neighbour-joining tree and STRUCTURE analysis. The results confirmed a high genetic similarity between the Zimbabwean Pt isolates and the South African races MCDS, MCPS and MFPS. Furthermore, Pt isolates from Zimbabwe were clonal, which was in accordance with all 104 isolates that typed to race MCDS.

Analysis of the impact of drying on common wheat quality and safety

Mycotoxin contamination in grain has been an ongoing concern in the world. Wheat, as a staple crop in China, is particularly notable for its mycotoxin contamination. The main mycotoxins in wheat include deoxynivalenol (DON) and its derivates, zearalenone (ZEN) and aflatoxin B1 (AFB1). After harvest, drying process is an effective technique and a necessary step to ensure the long-term safe storage of wheat. In this study, the moisture content, the concentrations of total fungi and main mycotoxins in post-harvest wheat of three wheat growing areas in the North China Plain were examined, and the effect of different drying methods on wheat quality was evaluated. The results showed that 87.5% of wheat samples were simultaneously contaminated with two or more mycotoxins. Due to the pre-harvest heavy rainfall, the moisture content, the levels of total fungi and mycotoxins in wheat samples of Liaocheng city were significantly higher compared to other regions. Moreover, the effects of different drying methods on the starch gelatinization and viscosity properties of wheat were investigated. The results showed that both natural air drying and dryer drying altered the crystal structure within starch particles and affected the gelatinization and viscosity properties of wheat starch. However, there is no significant difference between the wheat samples treated with two drying methods.

Assessment of the genetic diversity of the alleles of gliadin-coding loci in common wheat (Triticum aestivum L.) collections in Kazakhstan and Russia.

The study of genetic resources using prolamin polymorphism in wheat cultivars from countries with different climatic conditions makes it possible to identify and trace the preference for the selection of the alleles of gliadine-coding loci characteristic of specific conditions. The aim of the study was to determine the "gliadin profile" of the collection of common wheat (Triticum aestivum L.) from breeding centers in Russia and Kazakhstan by studying the genetic diversity of allelic variants of gliadin-coding loci. Intrapopulation (μ ± Sμ) and genetic (H) diversity, the proportion of rare alleles (h ± Sh), identity criterion (I) and genetic similarity (r) of common wheat from eight breeding centers in Russia and Kazakhstan have been calculated. It has been ascertained that the samples of common wheat bred in Kostanay region (Karabalyk Agricultural Experimental Station, Kazakhstan) and Chelyabinsk region (Chelyabinsk Research Institute of Agriculture, Russia) had the highest intrapopulation diversity of gliadin alleles. The proportion of rare alleles (h) at Gli-B1 and Gli-D1 loci was the highest in the wheat cultivars bred by the Federal Center of Agriculture Research of the South-East Region (Saratov region, Russia), which is explained by a high frequency of occurrence of Gli-B1e (86 %) and Gli-D1a (89.9 %) alleles. Based on identity criterion (I), the studied samples of common wheat from different regions of Kazakhstan and Russia have differences in gliadin-coding loci. The highest value of I = 619.0 was found when comparing wheat samples originated from Kostanay and Saratov regions, and the lowest I = 114.4, for wheat cultivars from Tyumen and Chelyabinsk regions. Some region-specific gliadin alleles in wheat samples have been identified. A combination of Gli-A1f, Gli-B1e and Gli-Da alleles has been identified in the majority of wheat samples from Kazakhstan and Russia. Alleles (Gli-A1f, Gli-A1i, Gli-A1m, Gli-A1o, Gli-B1e, Gli-D1a, Gli-D1f, Gli-A2q, Gli-B2o, and Gli-D2a) turned out to be characteristic and were found with varying frequency in wheat cultivars in eight regions of Russia and Kazakhstan. The highest intravarietal polymorphism (51.1 %) was observed in wheat cultivars bred in Omsk region (Russia) and the lowest (16.6 %), in Pavlodar region (Kazakhstan). On the basis of the allele frequencies, a "gliadin profile" of wheat from various regions and breeding institutions of Russia and Kazakhstan was compiled, which can be used for the selection of parent pairs in the breeding process, the control of cultivars during reproduction, as well as for assessing varietal purity.

Comparative characteristics of the durum wheat newest samples based on a complex of agrobiological characteristics

In 2020–2022 at the Dagestan experimental station of the VIR branch 30 samples of durum wheat of different ecological and geographical origins (Russia, Austria, Mexico, Syria, Egypt) were studied under irrigation conditions under winter sowing. The k-66674 Odari, k-67482 Yarina (Krasnodar Territory) and k-32453 Derbentskaya Chernokolosaya (Republic of Dagestan) varieties were sown as standard samples. Over three years of study, a field and laboratory assessment were given for the following characteristics: length of the growing season, resistance to fungal diseases (powdery mildew, brown and yellow rust) and lodging, grain weight per unit area (1 m2), weight of 1000 grains, number of grains in one ear and the mass of grain from one ear. The varieties are recommended as sources of breeding valuable traits (earliness, productivity, large grain size) for further use in breeding and genetic programs for the creation of new adaptive varieties.

Evaluation of the genotypes of the Kazakh-Siberian nursery (KASIB) in the conditions of the Novosibirsk region

The paper presents the results of evaluation of the KASIB-22 nursery soft wheat samples resistance to the main wheat pathogens. The research material was 44 wheat samples obtained from different regions of Russia and Kazakhstan within the framework of the KASIB shuttle breeding program (A.I. Barayev Research and Production Centre for Grain Farming, Omsk State Agrarian University, ICiG SB RAS, Karabalyk AES, Karaganda AES, North-Kazakhstan AES, FSBSI "Omsk ASC", HE SAU of the Northern Trans-Urals, Aktyubinsk AES, Kurgan Research Institute of Agriculture, Pavlodar AES, agrokomplex "Kurgansemena", Samara Research Institute of Agriculture, Chelyabinsk Research Institute of Agriculture). The following breeding lines were identified as highly productive and possessing high and medium resistance to brown rust, powdery mildew and loose smut: Line Pt-311 (Kurgan Research Institute of Agriculture), Lutescens 1462, Lutescens 1486, Line1616ae14 (Samara Research Institute of Agriculture), Lutescens 1356 (ICiG SB RAS). The yield of the selected samples averaged 42.1–51.2 c/ha. Genotypes Novosibirskaya 41, Line 435/12 and Lutescens 1364 are of interest for selection for quality. The gluten content of the nursery genotypes ranged from 24.1 (Line 23/07 in 2022) to 38.0% (variety Astana 2 in 2021), protein ranged from 13.4 (variety Tertia in 2022) to 19.5% (Lutescens 1364 in 2022). Each of the selected lines is of practical value for breeding, and the samples from the KASIB-22 nursery allow to expand the genetic diversity of spring soft wheat by selecting the most resistant forms to local populations of powdery mildew, leaf rust and loose smut pathogens.

Weed Seeds in Marketed Wheat and their Identification

Weed seeds of fifteen species representing 12 genera and 7 families have been observed, contaminated in wheat samples available in Calcutta ration shops. A key has been prepared for identification of these seeds.

Poly (ionic liquid) cross-linked hydrogel encapsulated with AuPt nanozymes for the smartphone-based colorimetric detection of zearalenone

A poly (ionic liquid) enhanced poly(acrylamide-acrylic acid) (PIL-PAM/AA) hydrogel-based colorimetric sensor was designed to detect zearalenone (ZEN). Different AuxPty nanoparticles were synthesized via the on-pot method. Through the kinetic analysis and the theoretical calculation, Au0.4Pt0.6 possessed the relatively low energy barriers to adsorb and decompose H2O2 so that it exhibited relatively better catalytic activity (Km = 2.02 × 10−3, Vmax = 6.14 × 10−7). AuPt nanoparticles were encapsulated into PIL-PAM/AA hydrogel via the interaction between aptamer and cDNA. In the presence of ZEN, the embedded AuPt nanoparticles were released to complete the catalytic reaction. Coupled with the smartphone application, the established method provided the linear range of 1–250 ng mL−1, with a detection limit of 0.6979 ng mL−1 for ZEN. Meanwhile, it also possessed excellent selectivity and good anti-interference performance. In wheat and corn samples, spiked recoveries were ranging from 75% to 113.30%.

Analysis of unique volatile organic compounds in “Mianhua” made from wheat planted in arid alkaline land

Hebei Province's Huanghua “Mianhua” is a province intangible cultural property made from arid alkaline wheat (AAW). This study aims to assess how different soil conditions affect the volatile organic compounds (VOCs) of “Mianhua” and identify distinct VOCs for land type discrimination. These findings will guide future research on AAW products, enhancing their processing and utilization. 51 VOCs in “Mianhua” from wheat samples grown in arid alkaline land and general land in Huanghua were analyzed by Gas Chromatography-Ion Mobility Spectrometry (GC-IMS). The result of ANOVA, VOC fingerprint, T test, and OPLS-DA revealed VOCs differences based on planting environments. According to multivariate variance contribution rate analysis, most VOCs were more affected by the variety. Land type significantly influenced (E)-2-heptenal (75.3%), Butanol (60.6%), Propyl acetate (60.0%), ethyl pentanoate (45.5%), and ethyl acetate (44.4%). LDA progressively identified Butanol as the characteristic VOC to distinguish “Mianhua” between it made from AAW and general wheat (GW), with a classification accuracy of 75%.

Investigation of Metabolic Responses in Virus-infected Wheat (Triticum aestivum L.) Grown in Azerbaijan

Barley yellow dwarf viruses (BYDV), Wheat streak mosaic virus (WSMV), Wheat dwarf virus (WDV), and Soil-borne wheat mosaic virus (SBWMV) constitute the most dangerous and widespread viruses affecting cereals across all wheat-growing regions worldwide. While numerous foreign scientific reports focus on the impact of climate change on plants, pathogens, and their vectors, only a limited number of studies address cereal viruses. The objective of this study was to investigate the variability of economically significant wheat viruses in several regions of Azerbaijan and to identify certain metabolic enzymes such as malate dehydrogenase (MDH), aspartate aminotransferase (AsAT), and alanine aminotransferase (ALAT) in virus-infected wheat samples. During 2022-2023, it was observed that BYDV and WSMV alternated in prevalence from year to year, with no instances of co-infection recorded. SBWMV was not detected in the tested samples. WSMV incidence rates were 12.4% and 19% in 2022 and 2023, respectively, whereas BYDV was detected at rates of 14.6% and 8.5%, respectively. Our results support a tight relationship between amino acid metabolism and stress responses. The results of the research allow the conclusion that mitochondrial NAD-MDH implements oxidation of NADH reduced in the reaction of glycine decarboxylation during photorespiration and intensifies biosynthesis of 2-oxoglutarate playing the role of the carbon skeleton in the synthesis of amino acids.

Estimation of adaptability parameters of winter common wheat samples at different sowing dates in the forest-steppe of Western Siberia

There has been presented a three-year estimation of winter wheat samples according to adaptability indicators, the trait ‘productivity’, ‘winter resistance’, ‘1000-grain weight’, and ‘number of productive stems per m2’. The purpose of the study was to estimate the adaptive potential of winter common wheat varieties in the forest-steppe of Western Siberia at different sowing dates. The study was conducted in the laboratory for field crop breeding, seed production and cultivation technologies based on SibRIPCB, the branch of Institute of Cytology and Genetics, SB RAS (Novosibirsk region) in 2018–2022. The objects of study were 5 winter common wheat varieties developed by the SibRIPCB, a branch of the Institute of Cytology and Genetics SB RAS. Sowing was carried out in three periods (the first was in August 20, the second was in September 1 and the third was in September 10) with an SSFC-7 seeder in 5 repetitions, the recording plot area was 10 m², the placement of the plots was randomized, the crops were laid in weedfree fallow. As a result, there was established that, according to the trait ‘productivity’, the varieties ‘Novosibirskaya 2’ (bi = 1.42; δd² = 0.08) and ‘Novosibirskaya 3’ (bi = 1.35; δd² = 0.08) combined ecological adaptability and stability. The variety ‘Novosibirskaya 3’ also combined adaptability and stability according to the trait ‘number of productive stems per m2’ (bi = 1.09; δd² = 468.94). The winter variety ‘Krasnoobskaya’ is capable of consistently giving high yields ((Ymax+Ymin)/2 = 4.92; (Sc = 3.42); Hom = 26.2) and maintaining the density of productive stems ((Ymin–Ymax) = -280; Sc = 280.8; (Ymin+Ymax)/2 = 513; Hom = 8.9) at different sowing dates. The variety ‘Pamyati Chekurova’ is responsive to improvements in environmental conditions according to the trait ‘productivity’ (bi = 1.10; KM = 2.20), ‘winter resistance’ (bi = 1.53; KM = 2.72), ‘number of productive stems per m2’ (bi = 1.22; KM = 2.2).

“Green” one-pot synthesis of hemin complex with excellent peroxidase activity: Efficient enhanced chemiluminescence immunosensor for ultrasensitive detection of ochratoxin A

Compared with natural enzymes, nanozymes have the advantages of easy preparation, low cost and high stability. With the booming development of nanozymes, scientists have further defined them as “nanomaterials with enzyme-like properties”. Here, on the one hand, ZIF-L has the characteristics of simple preparation, good stability and large specific surface area. Meanwhile, the array structure of Zn2+ and imidazole in the ZIF-L can replace the amino acids precisely located in the natural enzymes, thus mimicking the microenvironment of the natural peroxidase. On the other hand, based on the chemical similarity of hemin to natural heme, we encapsulated hemin into the ZIF-L backbone by a straightforward “green” one-pot technique. According to the symbiotic stability-enhancing effect, the encapsulated biomolecules can make the ZIF-L matrix more stable while the ZIF-L backbone protects the enzyme from denaturation. Based on this, ZIF-L-Hemin composites with excellent peroxidase properties was successfully prepared. Using ZIF-L-Hemin composites, we constructed a flow-injection chemiluminescence immunoassay for the quick and ultrasensitive detection of ochratoxin A (OTA) in food. The experimental results showed that the detection range of OTA was 0.0015 ∼ 1500 ng mL−1, and the limit of detection (LOD) was 0.47 pg mL−1 (S/N = 3). The OTA analysis of wheat, corn and feed samples showed that the recoveries ranged from 80.83 % to 115.54 %, which successfully demonstrated the usability and potential applications of immunosensor.

Ultrasound-Assisted Extraction Combined with Low-Density Solvent-Based Dispersive Liquid-Liquid Microextraction as an Efficient and Sensitive Method for the Determination of Clodinafop-Propargyl Herbicide in Wheat Samples

Ultrasound-Assisted Extraction Combined with Low-Density Solvent-Based Dispersive Liquid-Liquid Microextraction as an Efficient and Sensitive Method for the Determination of Clodinafop-Propargyl Herbicide in Wheat Samples

Enhanced sensitivity for Aflatoxin B1 detection in food through a h-Zn1Cd5S-based photoelectrochemical aptasensor

Designing photoelectrochemical sensors for detecting ultra-trace amounts of Aflatoxin B1 (AFB1) in complex samples poses a significant challenge. In pursuit of this objective, we engineered hollow-structured ZnCdS (denoted as h-Zn1Cd5S) material and applied an electrodeposition method to introduce Au nanoparticles (AuNPs) on the surface. This approach resulted in a significant enhancement of the photocurrent response of the photoelectrode, attributed to the synergistic effects of the hollow structure and surface plasmon resonance, thereby underscoring its potential for advanced applications. Utilizing density functional theory, we computed the transfer route and energy band formation of photogenerated electrons. Subsequently, we developed an AFB1 photoelectrochemical (PEC) aptasensor based on the competition mechanism, coupled with aptamer probe technology. This aptasensor allows for the ultra-trace determination of AFB1, exhibiting a remarkable detection limit as low as 1.32 fg/mL and a linear range from 1.0 × 10−2 to 100.0 pg/mL. The PEC aptasensor for AFB1 demonstrates excellent sensitivity and selectivity. When applied to the detection of AFB1 in Tsaoko, wheat, and corn samples, its performance aligns closely with high-performance liquid chromatography (HPLC) results, validating its applicability for analyzing real-world samples.