Characterization of Invasion of Genus Aspergillus on Peanut Seeds Using FTIR-PAS

Detection of Aflatoxin B1 in Single Peanut Kernels by Combining Hyperspectral and Microscopic Imaging Technologies

To study the dynamic changes of nutrient consumption and aflatoxin B₁ (AFB₁) accumulation in peanut kernels with fungal colonization, macro hyperspectral imaging technology combined with microscopic imaging was investigated. First, regression models to predict AFB₁ contents from hyperspectral data ranging from 1000 to 2500 nm were developed and the results were compared before and after data normalization with Box-Cox transformation. The results indicated that the second-order derivative with a support vector regression (SVR) model using competitive adaptive reweighted sampling (CARS) achieved the best performance, with R_C² = 0.95 and R_V² = 0.93. Second, time-lapse microscopic images and spectroscopic data were captured and analyzed with scanning electron microscopy (SEM), transmission electron microscopy (TEM), and synchrotron radiation-Fourier transform infrared (SR-FTIR) microspectroscopy. The time-lapse data revealed the temporal patterns of nutrient loss and aflatoxin accumulation in peanut kernels. The combination of macro and micro imaging technologies proved to be an effective way to detect the interaction mechanism of toxigenic fungus infecting peanuts and to predict the accumulation of AFB₁ quantitatively.

Non-thermal plasma induces changes in aflatoxin production, devitalization, and surface chemistry of Aspergillus parasiticus

Non-thermal plasma (NTP) represents the fourth state of matter composed of neutral molecules, atoms, ions, radicals, and electrons. It has been used by various industries for several decades, but only recently NTPs have emerged in fields such as medicine, agriculture, and the food industry. In this work, we studied the effect of NTP exposure on aflatoxin production, conidial germination and mycelial vitality, morphological and surface changes of conidia and mycelium. When compared with colonies grown from untreated conidia, the colonies from NTP-treated conidia produced significantly higher levels of aflatoxins much earlier during development than colonies from untreated conidia. However, at the end of cultivation, both types of cultures yielded similar aflatoxin concentrations. The increase in the accumulation of aflatoxins was supported by high transcription levels of aflatoxin biosynthetic genes, which indicated a possibility that NTP treatment of conidia was having a longer-lasting effect on colony development and aflatoxins accumulation. NTP generated in the air at atmospheric pressure effectively devitalized Aspergillus parasiticus in conidia and hyphae within a few minutes of treatment. To describe devitalization kinetics, we applied Weibull and Hill models on sets of data collected at different exposure times during NTP treatment. The damage caused by NTP to hyphal cell wall structures was displayed by raptures visualized by scanning electron microscopy. Fourier transform infrared spectroscopy demonstrated that changes in cell envelope correlated with shifts in characteristic chemical bonds indicating dehydration, oxidation of lipids, proteins, and polysaccharides. Key points • Non-thermal plasma increases aflatoxin production shortly after treatment. • Non-thermal plasma rapidly devitalizes Aspergillus parasiticus. • Non-thermal plasma disrupts the cell surface and oxidizes biological components.

Differentiation of S. chartarum (Ehrenb.) S. Hughes Chemotypes A and S via FT-IR Spectroscopy

Stachybotrys (S.) chartarum is a cellulolytic mould with the ability to produce highly cytotoxic macrocyclic trichothecenes. Two chemotypes are defined according to their ability to produce either atranones or satratoxins. S. chartarum has been well known as the causative agent of the lethal disease stachybotryotoxicosis in horses. Further investigations revealed that this disease is strictly correlated with the presence of macrocyclic trichothecenes. Furthermore, their occurrence in water-damaged buildings has been linked to adverse health effects such as the sick building syndrome. As the chemotypes cannot be characterized via phenotypic criteria, different methods such as PCR, MALDI–TOF MS, LC–MS/MS, thin-layer chromatography and cytotoxicity assays have been used so far. Fourier-transform-infrared spectroscopy (FT-IR) is commonly used for the differentiation of bacteria and yeasts, but this technique is also applicable to filamentous fungi. Hence, this study aimed at evaluating to which extent a reliable differentiation of S. chartarum chemotypes A and S is possible. Besides, another objective was to verify if the recently introduced third genotype of S. chartarum can be identified. Therefore, 28 strains including the two chemotypes and the third genotype H were cultivated on malt extract agar (MEA) and potato dextrose agar in three biological replicates. Each sample was applied to FT-IR measurements on day 7, 14 and 21 of cultivation. In this study, we achieved a distinction of the chemotypes A and S via FT-IR spectroscopy after incubation for 7 days on MEA. In terms of genotype differentiation, the PCR detecting satratoxin- and atranone-gene clusters remained the only applicable method.

Detection of potential biodeterioration risks for tempera painting in 16th century exhibits from State Tretyakov Gallery

In this study, we investigated biodeterioration of materials used in tempera painting by analyzing the structure of the microbiome in ancient tempera paintings exhibited in State Tretyakov Gallery, Moscow, Russia. Samples were obtained from 16^th-century paintings, including a grand Russian Orthodox icon “The Church Militant” (all exhibits were without visible signs of biodeterioration), and from surrounding walls and ceilings (with vast zones of visible microbial growth). A number of microorganisms isolated from visible signs of environmental bio-damage were also detected in tempera paintings kept in temperature- and humidity-controlled conditions unfavorable for the growth of microflora. To determine the biodegrading potential of the microbiome for tempera paintings, we developed a set of mock layers from paintwork materials used in tempera painting of 16^th century and their modern analogues and inoculated them with cultures containing filamentous fungi and bacteria. The susceptibility to microbial degradation of individual tempera painting materials was examined by micro-Fourier Transform Infrared (FTIR) spectroscopy, which enabled detection of even invisible signs of biodeterioration. The results indicate that the microorganisms isolated from paintings and surrounding areas in the museum are capable of causing significant damage of various tempera materials, among which varnishes were the most resistant; however, the addition of antiseptic (sodium pentachlorophenolate) can inhibit microbial growth on sturgeon glue.

Detection of mycotoxins and toxigenic fungi in cereal grains using vibrational spectroscopic techniques: a review

Nutrition-rich cereal grains and oil seeds are the major sources of food and feed for human and livestock, respectively. Infected by fungi and contaminated with mycotoxins are serious problems worldwide for cereals and oil seeds before and after harvest. The growth and development activities of fungi consume seed nutrients and destroy seed structures, leading to dramatic declines of crop yield and quality. In addition, the toxic secondary metabolites produced by these fungi pose a well-known threat to both human and animals. The existence of fungi and mycotoxins has been a redoubtable problem worldwide for decades but tends to be a severe food safety issue in developing countries and regions, such as China and Africa. Detection of fungal infection at an early stage and of mycotoxin contaminants, even at a small amount, is of great significance to prevent harmful toxins from entering the food supply chains worldwide. This review focuses on the recent advancements in utilising infrared spectroscopy, Raman spectroscopy, and hyperspectral imaging to detect fungal infections and mycotoxin contaminants in cereals and oil seeds worldwide, with an emphasis on recent progress in China. Brief introduction of principles, and corresponding shortcomings, as well as latest advances of each technique, are also being presented herein.

A review on the application of vibrational spectroscopy to the chemistry of nuts

Nuts are highly appreciated due to their nutritional relevance and flavour, being the source of many desirable and healthy compounds as polyunsaturated fatty acids and antioxidants. Their characterization became the target of many studies in the last years through conventional analytical techniques as chromatographic ones. Due to the limitations associated to these techniques, as time, cost and environmental concerns, spectroscopic techniques have been increasingly pointed as reliable alternatives. Either applied to raw materials quality control or to more complex process, as industrial in-line monitoring, spectroscopic techniques, namely vibrational spectroscopy, are gathering strong acceptance. This paper presents a review on the application of vibrational spectroscopy, infrared and Raman, to nuts characterization. Estimates of several qualitative and quantitative parameters, origin authentication and/or adulteration in almonds, peanuts, pine nuts, hazelnuts, walnuts, Brazil nuts, cashews, chestnuts and pistachios will be covered. Advantages and limitations of these techniques and future trends will also be discussed.

Discrimination and growth tracking of fungi contamination in peaches using electronic nose

A non-destructive method for detection of fungal contamination in peaches using an electronic nose (E-nose) is presented. Peaches were inoculated with three common spoilage fungi, Botrytis cinerea, Monilinia fructicola and Rhizopus stolonifer and then stored for various periods. E-nose was then used to analyze volatile compounds generated in the fungi-inoculated peaches, which was then compared with the growth data (colony counts) of the fungi. The results showed that changes in volatile compounds in fungi-inoculated peaches were correlated with total amounts and species of fungi. Terpenes and aromatic compounds were the main contributors to E-nose responses. While principle component analysis (PC1) scores were highly correlated with fungal colony counts, Partial Least Squares Regression (PLSR) could effectively be used to predict fungal colony counts in peach samples. The results also showed that the E-nose had high discrimination accuracy, demonstrating the potential use of E-nose to discriminate among fungal contamination in peaches.

A novel chemometric classification for FTIR spectra of mycotoxin-contaminated maize and peanuts at regulatory limits

The rapid identification of mycotoxins such as deoxynivalenol and aflatoxin B₁ in agricultural commodities is an ongoing concern for food importers and processors. While sophisticated chromatography-based methods are well established for regulatory testing by food safety authorities, few techniques exist to provide a rapid assessment for traders. This study advances the development of a mid-infrared spectroscopic method, recording spectra with little sample preparation. Spectral data were classified using a bootstrap-aggregated (bagged) decision tree method, evaluating the protein and carbohydrate absorption regions of the spectrum. The method was able to classify 79% of 110 maize samples at the European Union regulatory limit for deoxynivalenol of 1750 µg kg^-1 and, for the first time, 77% of 92 peanut samples at 8 µg kg^-1 of aflatoxin B₁. A subset model revealed a dependency on variety and type of fungal infection. The employed CRC and SBL maize varieties could be pooled in the model with a reduction of classification accuracy from 90% to 79%. Samples infected with Fusarium verticillioides were removed, leaving samples infected with F. graminearum and F. culmorum in the dataset improving classification accuracy from 73% to 79%. A 500 µg kg^-1 classification threshold for deoxynivalenol in maize performed even better with 85% accuracy. This is assumed to be due to a larger number of samples around the threshold increasing representativity. Comparison with established principal component analysis classification, which consistently showed overlapping clusters, confirmed the superior performance of bagged decision tree classification.