Early detection and monitoring for Aspergillus flavus contamination in maize kernels

Early identification and monitoring of soft rot contamination in postharvest kiwifruit based on volatile fingerprints using headspace-gas chromatography-ion mobility spectrometry

Soft rot is one of the most devastating fungal diseases occurring in kiwifruit during postharvest storage. Whereas, the approaches for rapid, precise and non-destructive testing of early soft rot contamination are still scarce. This study successfully employed headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) to evaluate volatile organic compounds (VOCs) of soft rot kiwifruit contaminated with three pathogenic fungi including B. dothidea, Diaporthe spp., A. alternata. A total of 88, 106, 110 and 99 VOCs were detected in non-infected, B. dothidea, Diaporthe spp., A. alternata-infected kiwifruit, respectively. Specific fingerprints were established with 15, 26 and 11 characteristic VOCs emitted by three pathogenic fungi invading kiwifruit and not present in non-infected kiwifruit, accomplishing effective discrimination between healthy and disease kiwifruit. Additionally, alternative potential volatile biomarkers for soft rot kiwifruit were screened, such as α-terpinene, α-terpinolene, 3-p-menthanol, 3-hepten-2-one, ethyl 2-methylbutanoate, etc. These findings promised non-destructive and timely monitoring for disease occurrence during kiwifruit postharvest.

Finite element analysis of corn kernel damage: a viscoelastic model approach for impact-induced damage prediction

BACKGROUND

In the present study, we address the quality degradation of corn during post-harvest processing by developing a viscoelastic composite model to predict kernel damage during post-harvest processing. The model, based on high-resolution scanning and inverse modeling techniques, provides an accurate representation of the complex internal components of corn kernels, which allows for the analysis of their stress response and damage susceptibility trends under different impact conditions.

RESULTS

The results show that the viscoelastic model has a relative error of 2.4% compared to the drop test data, thus demonstrating that the viscoelastic model has a very high accuracy in predicting impact damage and is able to accurately localize the flour-like endosperm as the main region of impact damage. The model showed a high correlation (0.99) between predicted and experimental damage rates by response surface methodology.

CONCLUSION

Kernel damage during processing is reduced by reducing the proportion of flour-like endosperm in maize kernels. A new method for reducing damage during food handling and processing operations is proposed, providing an important reference for improving kernel durability and contributing to the development of gentler processing techniques to improve the quality of maize products. © 2025 Society of Chemical Industry.

Chitosan nanoparticles loaded with Lactobacillus rhamnosus bioactive metabolites: Preparation, characterization, and antifungal activity

Aspergillus flavus is a severe danger to worldwide maize (Zea mays) cultivation, due to its extreme toxicity of aflatoxins produced by the fungi, and its ability to cause economic losses while also posing a health concern to humans and animals. Among the measures that may be considered for A. flavus control, applying coatings based on natural ingredients appears to be the most promising. The current work examines the antagonistic ability of Lactobacillus rhamnosus bioactive metabolites added to chitosan nanoparticles against A. flavus on maize kernels. The chitosan nanoparticles loaded with L. rhamnosus bioactive metabolites were characterized using the transmission electron microscope (TEM), zeta potential, size distribution, polydiversity index (PDI), pH, encapsulation efficiency and Fourier transform infrared spectroscopy (FTIR). The TEM revealed that the chitosan nanoparticles loaded with bioactive metabolites were spherical and smooth on the surface, and by increasing the concentration of bioactive metabolites added to the chitosan nanoparticles, the diameter of the chitosan nanoparticle grew. The zeta potential and size distribution values increased as the quantity of L. rhamnosus bioactive metabolites increased in the chitosan nanoparticles. The FTIR analysis indicated the presence of several functional groups, including alkynes, alkene, aliphatic primary amines, and other functional groups. The chitosan nanoparticles loaded with L. rhamnosus bioactive metabolites at a concentration of 7 mg/mL showed significant antifungal activity against A. flavus, reducing their growth in maize kernels by 89.42 % after 10 days of storage. They also reduced the percentage of germination inhibition rate and viability percentage. It could be concluded that adding L. rhamnosus bioactive metabolites to chitosan nanoparticles might have significant implications for food safety by using it in the industry to reduce the fungal contamination of grains.

Gas chromatography-ion mobility spectrometry (GC-IMS) technique and its recent applications in grain research

Grains are the primary source of food for most people worldwide and constitute a major source of carbohydrates. Many novel technologies are being employed to ensure the safety and reliability of grain supply and production. Gas chromatography-ion mobility spectrometry (GC-IMS) can effectively separate and sensitively detect volatile organic compounds. It possesses advantages such as speed, convenience, high sensitivity, no pretreatment, and wide applicability. In recent years, many studies have shown that the application of GC-IMS technology for grain flavor analysis can play a crucial role in grains. This article elucidates the working principle of GC-IMS technology, reviews the application of GC-IMS in grains in the past 5 years. GC-IMS technology is mainly applied in four aspects in grains. In grain classification, it distinguishes varieties, quality, origin, production year, and processing methods based on the trace differences in volatile organic compounds, thereby fulfilling various grain classification requirements such as origin tracing, geographical indication product recognition, variety identification, production year identification, and detection of counterfeit and inferior grain samples. In optimizing the processing technology of grains and their products, it can improve food flavor, reduce undesirable flavors, and identify better processing parameters. In grain storage, it can determine the storage time, detect spoilage phenomena such as mold and discoloration during storage, eliminate pests affecting storage, and predict the vitality of seeds after storage. In aroma evaluation of grains and their processed products, it can assess the impact of new raw materials, new technologies, fermentation processes, and even oral processing on the quality of grain products. This article also summarizes the characteristics of GC-IMS technology, compiles typical grain flavor compounds, and provides prospects for the future application of GC-IMS. © 2024 Society of Chemical Industry.

Moldy odors in food - a review

Food products are susceptible to mold contamination, releasing moldy odors. These moldy odors not only affect the flavor of food, but also pose a risk to human health. Moldy odors are a mixture of volatile organic compounds (VOCs) released by the fungi themselves, which are the main source of moldy odors in moldy foods. These VOCs are secondary metabolites of fungi and are synthesized through various biosynthetic pathways. Both the fungi themselves and environmental factors affect the release of moldy odors. This review summarized the main components of musty odors in moldy foods and their producing fungi. In addition, this review focused on the functions of moldy volatile organic compounds (MVOCs) and the biosynthetic pathways of the major MVOCs, and summarized the factors affecting the release of MVOCs as well as the detection methods. It expected to provide a basis for ensuring food safety.

Array-optimized artificial olfactory sensor enabling cost-effective and non-destructive detection of mycotoxin-contaminated maize

The MobileNetV3-based improved sine-cosine algorithm (ISCA-MobileNetV3) was combined with an artificial olfactory sensor (AOS) to address the redundancy in olfactory arrays, thereby achieving low-cost and high-precision detection of mycotoxin-contaminated maize. Specifically, volatile organic compounds of maize interacted with unoptimized AOS containing eight porphyrins and eight dye-attached nanocomposites to obtain the scent fingerprints for constructing the initial data set. The optimal decision model was MobileNetV3, with more than 98.5% classification accuracy, and its output training loss would be input into the optimizer ISCA. Remarkably, the number of olfactory arrays was reduced from 16 to 6 by ISCA-MobileNetV3 with about a 1% decrease in classification accuracy. Additionally, the developed system showed that each online evaluation was less than one second on average, demonstrating outstanding real-time performance for ensuring food safety. Therefore, AOS combined with ISCA-MobileNetV3 will encourage the development of an affordable and on-site platform for maize quality detection.

Sulcatone as a Plant-Derived Volatile Organic Compound for the Control of the Maize Weevil and Its Associated Phytopathogenic Fungi in Stored Maize

Stored maize is frequently attacked by different pests, such as insects and microorganisms. The aim of the present study was to evaluate the bioactivities of sulcatone (6-methyl-5-hepten-2-one) against the maize weevil Sitophilus zeamais and the phytopathogenic fungi Fusarium verticillioides, Aspergillus flavus, and A. parasiticus. Sulcatone showed a strong repellent effect with a maximum value of -92.1 ± 3.2% at 40 µM in two-choice olfactometer bioassays and an LC95 value of 17.2 µL/L air (95% 16.5-18.1) in a fumigant toxicity experiment. The antifungal effect of sulcatone was evaluated through the fumigant method, reporting MIC values of 3.5, 3.8, and 3.9 mM for F. verticillioides, A. parasiticus, and A. flavus, respectively. Additionally, a silo-bag experiment containing all pests was conducted to evaluate the potential use of sulcatone in a real storage system. Sulcatone caused 71.69 ± 1.57% weevil mortality in silo-bags and proved to be effective as a fungicidal and antimycotoxigenic agent since both ergosterol and fumonisin B1 content were significantly reduced by 60% in silo-bags containing sulcatone. This study demonstrated that sulcatone has the potential to be used for the control of both insects and fungi of stored maize, without affecting the germination of grains.

Exploration of Volatileomics and Optical Properties of Fusarium graminearum-Contaminated Maize: An Application Basis for Low-Cost and Non-Destructive Detection

Fusarium graminearum (F. graminearum) in maize poses a threat to grain security. Current non-destructive detection methods face limited practical applications in grain quality detection. This study aims to understand the optical properties and volatileomics of F. graminearum-contaminated maize. Specifically, the transmission and reflection spectra (wavelength range of 200-1100 nm) were used to explore the optical properties of F. graminearum-contaminated maize. Volatile organic compounds (VOCs) of F. graminearum-contaminated maize were determined by headspace solid phase micro-extraction with gas chromatography-tandem mass spectrometry. The VOCs of normal maize were mainly alcohols and ketones, while the VOCs of severely contaminated maize became organic acids and alcohols. The ultraviolet excitation spectrum of maize showed a peak redshift as fungi grew, and the intensity decreased in the 400-600 nm band. Peak redshift and intensity changes were observed in the visible/near-infrared reflectance and transmission spectra of F. graminearum-contaminated maize. Remarkably, optical imaging platforms based on optical properties were developed to ensure high-throughput detection for single-kernel maize. The developed imaging platform could achieve more than 80% classification accuracy, whereas asymmetric polarization imaging achieved more than 93% prediction accuracy. Overall, these results can provide theoretical support for the cost-effective preparation of low-cost gas sensors and high-prediction sorting equipment for maize quality detection.

Early warning of Aspergillus contamination in maize by gas chromatography-ion mobility spectrometry

Introduction

As one of the main grain crops in China, maize is highly susceptible to Aspergillus infection during processing, storage and transportation due to high moisture at harvest, which results in the loss of quality. The aim of this study is to explore the early warning marker molecules when Aspergillus infects maize kernels.

Methods

Firstly, strains MA and MB were isolated from moldy maize and identified by morphological characterization and 18S rRNA gene sequence analysis to be Aspergillus flavus (A. flavus) and Aspergillus niger (A. niger). Next, fresh maize was moldy by contaminated with strains MA and MB. The volatile organic compounds (VOCs) during the contamination process of two fungal strains were analyzed by gas chromatography-ion mobility spectrometry (GC-IMS). A total of 31 VOCs were detected in maize contaminated with strain MA, a total of 32 VOCs were detected in maize contaminated with strain MB, including confirmed monomers and dimers. Finally, heat maps and principal component analysis (PCA) showed that VOCs produced in different growth stages of Aspergillus had great differences. Combined with the results of GC-IMS, total fungal colony counts and fungal spores, it was concluded that the Aspergillus-contaminated maize was in the early stage of mold at 18 h.

Results

Therefore, the characteristic VOCs butan-2-one, ethyl acetate-D, Benzaldehyde, and pentan-2-one produced by maize at 18 h of storage can be used as early mildew biomarkers of Aspergillus infection in maize.

Discussion

This study provided effective marker molecules for the development of an early warning and monitoring system for the degree of maize mildew in granaries.

Characterization and genomic analysis of Bacillus megaterium with the ability to degrade aflatoxin B1

Coix seed is a good product for both medicinal and food use, which is highly susceptible to aflatoxin B1 (AFB1) contamination during field transport, storage, and processing. The aim of this study is to find microbial strains that can solve the problem of contamination of coix seed. In this study, the AFB1-degrading microorganism SX1-1 was isolated and identified as a Bacillus megaterium based on morphology, microscopy, and 16S rDNA sequencing. The optimum culture conditions for SX1-1 to degrade AFB1 were determined to be 12 h. The optimum degradation conditions were 72 h, 57°C, and an initial pH of 8.0. The highest degradation of AFB1 was observed in the fermentation supernatant of the SX1-1 strain, with a degradation rate of 97.45%. In addition, whole-genome sequencing analysis of this strain revealed the presence of a number of enzymes that could potentially degrade AFB1. Importantly, SX1-1 was able to degrade AFB1-contaminated coix seed in situ by 50.06% after co-culture. In conclusion, this strain had a high AFB1 degradation ability, and has great potential and great application as a biocontrol agent for AFB1 degradation of coix seed.

Morphed aflaxotin concentration produced by Aspergillus flavus strain VKMN22 on maize grains inoculated on agar culture

This study identified and monitored the levels of aflatoxins (B1 and B2) produced by Aspergillus flavus isolate VKMN22 (OP355447) in maize samples sourced from a local shop in Johannesburg, South Africa. Maize samples underwent controlled incubation after initial rinsing, and isolates were identified through morphological and molecular methods. In another experiment, autoclaved maize grains were intentionally re-inoculated with the identified fungal isolate using spore suspension (106 spore/mL), after which 1 g of the contaminated maize sample was inoculated on PDA media and cultured for seven days. The aflatoxin concentrations in the A. flavus contaminated maize inoculated on culture media was monitored over seven weeks and then measured using liquid chromatography-mass spectroscopy (LC-MS). Results confirmed the successful isolation of A. flavus strain VKMN22 with accession number OP355447, which consistently produced higher levels of AFB1 compared to AFB2. AF concentrations increased from week one to five, then declined in week six and seven. AFB1 levels ranged from 594.3 to 9295.33 µg/kg (week 1-5) and then reduced from 5719.67 to 2005 µg/kg in week six and seven), while AFB2 levels ranged from 4.92 to 901.67 µg/kg (weeks 1-5) and then degraded to 184 µg/kg in week six then 55.33 µg/kg (weeks 6-7). Levene's tests confirmed significantly higher mean concentrations of AFB1 compared to AFB2 (p ≤ 0.005). The study emphasizes the importance of consistent biomonitoring for a dynamic understanding of AF contamination, informing accurate prevention and control strategies in agricultural commodities thereby safeguarding food safety.

Quality Changes and Fungal Microbiota Dynamics in Stored Jujube Fruits: Insights from High-Throughput Sequencing for Food Preservation

Postharvest rot is an urgent problem affecting the storage of winter jujube. Therefore, the development of new technologies for efficient and safe preservation is very important. This study aimed to elucidate the fungal microbiota found on the epidermis of jujube during the storage period using high-throughput sequencing, as well as to monitor the changes in quality indexes throughout this period. Through internal transcribed spacer (ITS) sequencing, we identified two phyla (Basidiomycota and Ascomycota) and six genera (Cryptococcus, Bulleromyces, Sporidiobolus, Alternaria, Pseudozyma, and Sporobolomyces), which potentially contribute to the spoilage and deterioration of jujube, referred to as "core fungal taxa". A high correlation was further found between preservation indices (including decay rate, firmness, and total soluble solids) and the growth of multiple core fungi over time. These findings will provide insights and a theoretical basis for further research on preservation techniques related to biological control during date fruit storage.

GC-IMS and multivariate analyses of volatile organic components in different Chinese breeds of chickens

This study examined the difference in volatile flavor characteristics among four different local breeds of chicken by headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with multivariate analysis. In total, 65 volatile organic compounds (VOCs) were identified (17 aldehydes, 12 alcohols, 7 ketones, 5 esters, 2 acids, and 22 unidentified, i.e., 26.15% aldehydes, 18.46% alcohols, 10.77% ketones, 7.69% esters, 3.08% acids, and 33.84% unidentified), of which 43 were annotated. The chicken meats from the four breeds exhibited good separation in topographic plots, VOC fingerprinting, and multivariate analysis. Meanwhile, 20 different volatile components, with variable importance in projection value > 1, were selected as potential markers to distinguish different breeds of chicken by partial least squares discriminant analysis (PLS-DA). These findings provide insights into the flavor traits of chicken meat. Also, HS-GC-IMS combined with multivariate analysis can be a convenient and powerful method for characterizing different meats.

Monitoring of carbon dioxide and equilibrium moisture content for early detection of physicochemical and morphological changes in soybeans stored in vertical silos

In the context of grain storage, impurities and soybeans defects in soybeans can significantly impact the equilibrium moisture content. This, cause moisture migration and heating of the stored product, leading to increased respiratory activity. Furthermore, temperature measurements within stored grain mass do not provide sufficient information for effective grain quality monitoring, primarily due to the grains excellent thermal insulating properties. To address this issue, we propose a different approach: monitoring the equilibrium moisture content and CO2 concentration as indicators of soybean respiration within the intergranular spaces of the stored grain mass. This study propose monitoring the CO2 concentration in the intergranular air along with environmental variables for early detection of physicochemical and morphological changes in soybeans stored in vertical silos using near infrared spectroscopy, X-ray diffraction and scanning electron microscopy. Thermogravimetry and spectrometry analyses revealed that the interrelationships among variables had a direct impact on soybean quality attributes. Specifically, the presence of soybeans with 5.2 % impurities led to an increased in respiration rates, resulting in a CO2 concentration of up to 5000 ppm and the consumption of up to 3.6 % of dry matter. Consequently, there were changes in the percentage of ash, proteins, fibers, and oils compositions. These findings highlight the potential for indirect assessments, enabling the prediction of physicochemical quality and contamination of soybeans stored in vertical silos through continuous monitoring of CO2 concentration and equilibrium moisture content.

Aflatoxins: Occurrence, biosynthesis, mechanism of action and effects, conventional/emerging detection techniques

Aflatoxins (AFs) are toxic secondary metabolites prevalent in various food and agricultural products, posing significant challenges to global food safety. The detection and quantification of AFs through high-precision analytical techniques are crucial in mitigating AF contamination levels and associated health risks. Variousmethods,including conventional and emerging techniques, have been developed for detecting and quantifyingAFsinfood samples. This review provides an in-depth analysis of the global occurrence of AF in food commodities, covering their biosynthesis, mode of action, and effects on humans and animals. Additionally, the review discusses different conventional strategies, including chromatographic and immunochemical approaches, for AF quantification and identification in food samples. Furthermore, emerging AF detection strategies, such as solid-state gas sensors and electronic nose technologies, along with their applications, limitations, and future perspectives, were reviewed. Sample purification, along with their respective advantages and limitations, are also discussed herein.

The biodiversity of Aspergillus flavus in stored rice grain leads to a decrease in the overall aflatoxin B1 production in these species

Aspergillus flavus is a significant fungus that poses a threat to food safety by producing mycotoxins in various crops. In this study, A. flavus isolates were obtained from storage rice collected from seven provinces in southern China, and their AFB1 production, biosynthesis genes presence, and diversity were detected. Results showed that 56 out of the 81 A. flavus isolates produced detectable levels of AFB1, and 71 isolates (87.6 %) possessed aflR gene in their AF synthesis gene cluster, while only 41 isolates (50.6 %) had the ver-1 gene present. Genetic diversity analysis using inter-simple sequence repeats (ISSR) markers revealed seven main clusters among the isolates and the genetic similarity coefficients of 81 A. flavus isolates ranged from 0.53 to 1.00. Additionally, coculture assays were conducted using two toxigenic and two atoxigenic isolates from the same grain depot to investigate the effect of intraspecific inhibition on AFB1 production and to assess the AFB1 contamination risk of storage rice. The in situ results demonstrated that the atoxigenic isolates effectively inhibited the AFB1 contamination of toxigenic isolates. These findings provide insight into the genetic diversity of A. flavus isolates populations and highlight the potential food safety hazards of them in stored rice grain in China.

The Impact of the Foliar Application of Amino Acid Aqueous Fertilizer on the Flavor of Potato Tubers

The quality of the flavor of potatoes is a crucial determinant in the commercial success of a potato variety. Plant nutrition promotes the synthesis of amino acids, and the application of exogenous amino acids has the potential to enhance the flavor quality of potatoes. In this experiment, Dian Shu 1418 and Dian Shu 23 were used as the materials, and different amino acid foliar spray trials were designed. The free amino acid content in potato tubers is determined based on high-performance liquid chromatography, and volatile tuber flavor compounds are detected using gas chromatography-mass spectrometry. The results showed that the amino acid foliar spray effectively increased the content of glycine, methionine, and phenylalanine in the tubers, subsequently increasing the levels of 2,3-dimethyl-pyrazine and 2-ethyl-3-methyl-pyrazine, enhancing the roasted fragrance characteristics of the potatoes. The experimental results provide a reference for cultivating flavor enhancement in potato tubers.

UPLC-Q-Exactive Orbitrap-MS-Based Untargeted Lipidomic Analysis of Lipid Molecular Species in Spinal Cords from Different Domesticated Animals

Lipids are crucial components for the maintenance oof normal structure and function in the nervous system. Elucidating the diversity of lipids in spinal cords may contribute to our understanding of neurodevelopment. This study comprehensively analyzed the fatty acid (FA) compositions and lipidomes of the spinal cords of eight domesticated animal species: pig, cattle, yak, goat, horse, donkey, camel, and sika deer. Gas chromatography-mass spectrometry (GC-MS) analysis revealed that saturated fatty acids (SFAs) and monounsaturated fatty acids (MUFAs) were the primary FAs in the spinal cords of these domesticated animals, accounting for 72.54-94.23% of total FAs. Notably, oleic acid, stearic acid and palmitic acid emerged as the most abundant FA species. Moreover, untargeted lipidomics by UPLC-Q-Exactive Orbitrap-MS demonstrated that five lipid classes, including glycerophospholipids (GPs), sphingolipids (SPs), glycerolipids (GLs), FAs and saccharolipids (SLs), were identified in the investigated spinal cords, with phosphatidylcholine (PC) being the most abundant among all identified lipid classes. Furthermore, canonical correlation analysis showed that PC, PE, TAG, HexCer-NS and SM were significantly associated with genome sequence data. These informative data provide insight into the structure and function of mammalian nervous tissues and represent a novel contribution to lipidomics.

Functional, Physical, and Volatile Characterization of Chitosan/Starch Food Films Functionalized with Mango Leaf Extract

Active packaging is one of the currently thriving methods to preserve highly perishable foods. Nonetheless, the integration of active substances into the formulation of the packaging may alter their properties-particularly mass transfer properties-and therefore, the active compounds acting. Different formulations of chitosan (CH), starch (ST), and their blends (CH-ST), with the addition of mango leaf extract (MLE) have been polymerized by casting to evaluate their food preservation efficiency. A CH-ST blend with 3% MLE using 7.5 mL of the filmogenic solution proved to be the most effective formulation because of its high bioactivity (ca. 80% and 74% of inhibition growth of S. aureus and E. coli, respectively, and 40% antioxidant capacity). The formulation reduced the water solubility and water vapor permeability while increasing UV protection, properties that provide a better preservation of raspberry fruit after 13 days than the control. Moreover, a novel method of Headspace-Gas Chromatography-Ion Mobility Spectrometry to analyze the volatile profiles of the films is employed, to study the potential modification of the food in contact with the active film. These migrated compounds were shown to be closely related to both the mango extract additions and the film's formulation themselves, showing different fingerprints depending on the film.

Accurate and non-destructive monitoring of mold contamination in foodstuffs based on whole-cell biosensor array coupling with machine-learning prediction models

Mold contamination in foodstuffs causes huge economic losses, quality deterioration and mycotoxin production. Thus, non-destructive and accurate monitoring of mold occurrence in foodstuffs is highly required. We proposed a novel whole-cell biosensor array to monitor pre-mold events in foodstuffs. Firstly, 3 volatile markers ethyl propionate, 1-methyl-1 H-pyrrole and 2,3-butanediol were identified from pre-mold peanuts using gas chromatography-mass spectrometry. Together with other 3 frequently-reported volatiles from Aspergillus flavus infection, the volatiles at subinhibitory concentrations induced significant but differential response patterns from 14 stress-responsive Escherichia coli promoters. Subsequently, a whole-cell biosensor array based on the 14 promoters was constructed after whole-cell immobilization in calcium alginate. To discriminate the response patterns of the whole-cell biosensor array to mold-contaminated foodstuffs, optimal classifiers were determined by comparing 6 machine-learning algorithms. 100 % accuracy was achieved to discriminate healthy from moldy peanuts and maize, and 95 % and 98 % accuracy in discriminating pre-mold stages for infected peanuts and maize, based on random forest classifiers. 83 % accuracy was obtained to separate moldy peanuts from moldy maize by sparse partial least square determination analysis. The results demonstrated high accuracy and practicality of our method based on a whole-cell biosensor array coupling with machine-learning classifiers for mold monitoring in foodstuffs.

Advances in microbial analysis: based on volatile organic compounds of microorganisms in food

In recent years, microbial volatile organic compounds (mVOCs) produced by microbial metabolism have attracted more and more attention because they can be used to detect food early contamination and flaws. So far, many analytical methods have been reported for the determination of mVOCs in food, but few integrated review articles discussing these methods are published. Consequently, mVOCs as indicators of food microbiological contamination and their generation mechanism including carbohydrate, amino acid, and fatty acid metabolism are introduced. Meanwhile, a detailed summary of the mVOCs sampling methods such as headspace, purge trap, solid phase microextraction, and needle trap is presented, and a systematic and critical review of the analytical methods (ion mobility spectrometry, electronic nose, biosensor, and so on) of mVOCs and their application in the detection of food microbial contamination is highlighted. Finally, the future concepts that can help improve the detection of food mVOCs are prospected.

Variation with In Vitro Analysis of Volatile Profiles among Aspergillus flavus Strains from Louisiana

Volatile organic compounds (VOCs) produced by A. flavus strains were first captured and identified to discern between non-aflatoxigenic and toxigenic phenotypes, and more recently to help with detecting fungal infection, but not with the goal of using VOCs produced by non-aflatoxigenic strains to inhibit growth and/or production of one or more mycotoxins (e.g., aflatoxin and cyclopiazonic acid) by toxigenic aspergilli. In this study, four Aspergillus strains from Louisiana (one non-aflatoxigenic and three toxigenic) were grown on various substrates and had their headspaces captured and analyzed by solid-phase microextraction/gas chromatography/mass spectroscopy (SPME/GC/MS), to find biocontrol and biomarker compounds. Here, we present a collection of nearly 100 fungus-related VOCs, many of which were substrate dependent. Thirty-one were produced across multiple replicates and the rest were observed in a single replicate. At least three VOCs unique to non-aflatoxigenic strain LA1 can be tested for biocontrol properties (e.g., euparone, 4-nonyne), and at least four VOCs unique to toxigenic strains LA2-LA4 can be explored as biomarkers (e.g., 2-heptanone, glycocyamidine) to detect their presence while infecting crops in the field or in storage.

E-Nose Technology for Mycotoxin Detection in Feed: Ready for a Real Context in Field Application or Still an Emerging Technology?

Mycotoxin risk in the feed supply chain poses a concern to animal and human health, economy, and international trade of agri-food commodities. Mycotoxin contamination in feed and food is unavoidable and unpredictable. Therefore, monitoring and control are the critical points. Effective and rapid methods for mycotoxin detection, at the levels set by the regulations, are needed for an efficient mycotoxin management. This review provides an overview of the use of the electronic nose (e-nose) as an effective tool for rapid mycotoxin detection and management of the mycotoxin risk at feed business level. E-nose has a high discrimination accuracy between non-contaminated and single-mycotoxin-contaminated grain. However, the predictive accuracy of e-nose is still limited and unsuitable for in-field application, where mycotoxin co-contamination occurs. Further research needs to be focused on the sensor materials, data analysis, pattern recognition systems, and a better understanding of the needs of the feed industry for a safety and quality management of the feed supply chain. A universal e-nose for mycotoxin detection is not realistic; a unique e-nose must be designed for each specific application. Robust and suitable e-nose method and advancements in signal processing algorithms must be validated for specific needs.

Volatile Metabolite Profiling of Wheat Kernels Contaminated by Fusarium graminearum

Traditional methods used to detect fungi or mycotoxins are time-consuming and prevent real-time monitoring. In this study, solid-phase microextraction combined with full two-dimensional gas chromatography time-of-flight mass spectrometry was utilized to detect volatile organic compounds (VOCs) produced by fungi during grain infestation predictive F. graminearum PH-1 infestation in wheat. The results show that the VOCs emitted by F. graminearum can distinguish strains at different growth stages. The growth matrices (potato dextrose agar medium and wheat kernels) play a large role in VOC production. The infection of wheat sample F. graminearum showed that a specific relationship between VOCs and the composition of fungal flora, for example, 5-pentyl-cyclohexa-1,3-diene, 3-hexanone, and 1,3-octadiene, was positively correlated with the infection rate of PH-1. In the correlation study of fungal mycotoxins and VOCs, zearalenone produced by F. graminearum was predicted based on the VOCs released. Further analysis determined the correlation of three VOCs, 6-butyl-1,4-cycloheptadiene, hexahydro-3-methylenebenzofuran-2(3H)-one, and (E,E)-3,5-octadien-2-one, with zearalenone production, confirming the ability of VOCs as characteristic markers of mycotoxins.

Characterization of the Key Aroma Constituents in Fried Tilapia through the Sensorics Concept

The object of this study was tilapia fish that were fried in soybean oil. Volatile compounds were extracted from the fish by ASE-HVE and were studied by GC-O-MS and the AEDA analysis method. A total of 30 aroma compounds were initially determined, and these compounds contribute to the aroma of fried tilapias. The key volatile compounds in fried tilapia were quantitatively analyzed by GC-MS, and the volatile compounds in soybean-fried tilapia were studied by flavor recombination and deletion experiments. Trimethylamine, hexanal, 2,3-dimethylpyrazine, dimethyl trisulfide, trans-2-octenal, 2,3-dimethyl-5-ethylpyrazine, (E)-2-nonenal, 2-propyl-pyridine, and (E,E)-2,4-decadienal were finally determined to be the key volatile compounds in soybean-fried tilapia.

Screening of Bacillus velezensis E2 and the Inhibitory Effect of Its Antifungal Substances on Aspergillus flavus

Aspergilus flavus is the main pathogenic fungus that causes food mold. Effective control of A. flavus contamination is essential to ensure food safety. The lipopeptides (LPs) produced by Bacillus strains have been shown to have an obvious antifungal effect on molds. In this study, an antagonist strain of Bacillus velezensis with obvious antifungal activity against A. flavus was isolated from the surface of healthy rice. Using HPLC-MS analysis, the main components of LPs produced by strain E2 were identified as fengycin and iturins. Further investigations showed that LPs could inhibit the spore germination, and even cause abnormal expansion of hyphae and cell rupture. Transcriptomic analyses showed that some genes, involved in ribosome biogenesis in eukaryotes (NOG1, KRE33) and aflatoxin biosynthesis (aflK, aflR, veA, omtA) pathways in A. flavus were significantly down-regulated by LPs. In conclusion, this study provides novel insights into the cellular and molecular antifungal mechanisms of LPs against grain A. flavus contamination.

Accelerating vinegar aging by combination of ultrasonic and magnetic field assistance

Most fermented foods need a natural aging process to enrich desired flavours. This process is normally the bottleneck for cost-effective production. Therefore, it is desirable to accelerate the process and obtain products with the same flavour profile. Here, we used physical interventions (ultrasonic field, alternating magnetic field, or combination of both) to assist the aging process with naturally brewed vinegar as a case example. Flavour profiles of different physical-assisted aging process were compared with that of the naturally aged vinegar by using gas-chromatography mass-spectrometry (GC-MS) and electronic nose. Principal component analysis (PCA) and Pearson correlation analyses show that ultrasonic and alternating magnetic fields treatment could accelerate the aging process of vinegar. The highest accelerating aging effect was combination of ultrasonic and magnetic field followed by individual ultrasonic or magnetic field and natural process (combination of ultrasonic and magnetic field > ultrasonic or magnetic field individual > natural process). These results suggest that physical field intervention could potentially be used for acceleration of aging of fermented products without affecting flavour quality.

Volatile Profile and Biosynthesis of Post-harvest Apples are Affected by the Mechanical Damage

Mechanical damage to fruit causes flavor changes during post-harvest supply chains. It is important to identify the main volatiles and explore their biosynthesis mechanism. In this study, the volatile changes in apples caused by mechanical damage were analyzed by gas chromatography-ion mobility spectrometry. Hexanal and ethyl acetate were accumulated and identified as potential volatile biomarkers to detect damaged apples. The study on the lipoxygenase (LOX) pathway and transcription factors (TFs) shows that mechanical damage up-regulated the expression of MdLOX-like, MdLOX3b, MdLOX7b, MdLOX7c, MdLOX2a, and MdAAT in the LOX pathway and that of one MYB TF (MdMYB-like), five ERF TFs (MdERF073, MdERF003, MdERF114, MdERF15, and MdERF2), and five WRKY TFs (MdWRKY23, MdWRKY17, MdWRKY46, MdWRKY48, and MdWRKY71). Notably, MdAAT was significantly correlated to MdMYB-like, MdWRKY23, MdWRKY71, MdERF15, and MdERF2. Thus, TFs may attribute to the accumulation of hexanal and ethyl acetate by regulating the expression of LOX pathway-related genes.