NIR-HSI as a tool to predict deoxynivalenol and fumonisins in maize kernels: a step forward in preventing mycotoxin contamination.

BACKGROUND: Maize is frequently contaminated with deoxynivalenol (DON) and fumonisins B1 (FB1) and B2 (FB2). In the European Union, these mycotoxins are regulated in maize and maize-derived products. To comply with these regulations, industries require a fast, economic, safe, non-destructive and environmentally friendly analysis method. RESULTS: In the present study, near-infrared hyperspectral imaging (NIR-HSI) was used to develop regression and classification models for DON, FB1 and FB2 in maize kernels. The best regression models presented the following root mean square error of cross validation and ratio of performance to deviation values: 0.848 mg kg-1 and 2.344 (DON), 3.714 mg kg-1 and 2.018 (FB1) and 2.104 mg kg-1 and 2.301 (FB2). Regarding classification, European Union legal limits for DON and FB1 + FB2 were selected as thresholds to classify maize kernels as acceptable or not. The sensitivity and specificity were 0.778 and 1 for the best DON classification model and 0.607 and 0.938 for the best FB1 + FB2 classification model. CONCLUSION: NIR-HSI can help reduce DON and fumonisins contamination in the maize food and feed chain. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Probability models for growth and aflatoxin B1 production as affected by intraspecies variability in Aspergillus flavus.

The probability of growth and aflatoxin B1 (AFB1) production of 20 isolates of Aspergillus flavus were studied using a full factorial design with eight water activity levels (0.84-0.98 aw) and six temperature levels (15-40 °C). Binary data obtained from growth studies were modelled using linear logistic regression analysis as a function of temperature, water activity and time for each isolate. In parallel, AFB1 was extracted at different times from newly formed colonies (up to 20 mm in diameter). Although a total of 950 AFB1 values over time for all conditions studied were recorded, they were not considered to be enough to build probability models over time, and therefore, only models at 30 days were built. The confidence intervals of the regression coefficients of the probability of growth models showed some differences among the 20 growth models. Further, to assess the growth/no growth and AFB1/no- AFB1 production boundaries, 0.05 and 0.5 probabilities were plotted at 30 days for all of the isolates. The boundaries for growth and AFB1 showed that, in general, the conditions for growth were wider than those for AFB1 production. The probability of growth and AFB1 production seemed to be less variable among isolates than AFB1 accumulation. Apart from the AFB1 production probability models, using growth probability models for AFB1 probability predictions could be, although conservative, a suitable alternative. Predictive mycology should include a number of isolates to generate data to build predictive models and take into account the genetic diversity of the species and thus make predictions as similar as possible to real fungal food contamination.

Time-course of germination, initiation of mycelium proliferation and probability of visible growth and detectable AFB1 production of an isolate of Aspergillus flavus on pistachio extract agar.

The aim of this work was to assess the temporal relationship among quantified germination, mycelial growth and aflatoxin B1 (AFB1) production from colonies coming from single spores, in order to find the best way to predict as accurately as possible the presence of AFB1 at the early stages of contamination. Germination, mycelial growth, probability of growth and probability of AFB1 production of an isolate of Aspergillus flavus were determined at 25 °C and two water activities (0.85 and 0.87) on 3% Pistachio Extract Agar (PEA). The percentage of germinated spores versus time was fitted to the modified Gompertz equation for the estimation of the germination parameters (geometrical germination time and germination rate). The radial growth curve for each colony was fitted to a linear model for the estimation of the apparent lag time for growth and the growth rate, and besides the time to visible growth was estimated. Binary data obtained from growth and AFB1 studies were modeled using logistic regression analysis. Both water activities led to a similar fungal growth and AFB1 production. In this study, given the suboptimal set conditions, it has been observed that germination is a stage far from the AFB1 production process. Once the probability of growth started to increase it took 6 days to produce AFB1, and when probability of growth was 100%, only a 40-57% probability of detection of AFB1 production was predicted. Moreover, colony sizes with a radius of 1-2 mm could be a helpful indicator of the possible AFB1 contamination in the commodity. Despite growth models may overestimate the presence of AFB1, their use would be a helpful tool for producers and manufacturers; from our data 5% probability of AFB1 production (initiation of production) would occur when a minimum of 60% probability of growth is observed. Legal restrictions are quite severe for these toxins, thus their control from the early stages of contamination throughout the food chain is of paramount importance.

Conidia survival of Aspergillus section Nigri, Flavi and Circumdati under UV-A and UV-B radiation with cycling temperature/light regime.

BACKGROUND: Bio-geographical differences in fungal infection distribution have been observed around the world, confirming that climatic conditions are decisive in colonization. This research is focused on the impact of ultraviolet radiation (UV) on Aspergillus species, based on the consideration that an increase in UV-B radiation may have large ecological effects. RESULTS: Conidia of six mycotoxigenic Aspergillus species isolated from vineyards located in the northeast and south of Spain were incubated for 15 days under light/dark cycles and temperatures between 20 and 30 °C per day. Additionally, 6 h of exposure to UV-A or UV-B radiation per day were included in the light exposure. UV irradiance used were 1.7 ± 0.2 mW cm(-2) of UV-A (peak 365 nm) and 0.10 ± 0.2 mW cm(-2) of UV-B (peak 312 nm). The intrinsic decrease in viability of conidia over time was accentuated when they were UV irradiated. UV-B radiation was more harmful. CONCLUSION: Conidial sensitivity to UV light was marked in Aspergillus section Circumdati. Conidia pigmentation could be related to UV sensitivity. Different resistance was observed within species belonging to sections Flavi and Nigri. An increase in UV radiation could lead to a reduction in the Aspergillus spp. inoculum present in the field (vineyards, nuts, cereal crops). In addition, it could unbalance the spore species present in the field, leading to a higher predominance of dark-pigmented conidia.

An attempt to model the probability of growth and aflatoxin B1 production of Aspergillus flavus under non-isothermal conditions in pistachio nuts.

Human exposure to aflatoxins in foods is of great concern. The aim of this work was to use predictive mycology as a strategy to mitigate the aflatoxin burden in pistachio nuts postharvest. The probability of growth and aflatoxin B1 (AFB1) production of aflatoxigenic Aspergillus flavus, isolated from pistachio nuts, under static and non-isothermal conditions was studied. Four theoretical temperature scenarios, including temperature levels observed in pistachio nuts during shipping and storage, were used. Two types of inoculum were included: a cocktail of 25 A. flavus isolates and a single isolate inoculum. Initial water activity was adjusted to 0.87. Logistic models, with temperature and time as explanatory variables, were fitted to the probability of growth and AFB1 production under a constant temperature. Subsequently, they were used to predict probabilities under non-isothermal scenarios, with levels of concordance from 90 to 100% in most of the cases. Furthermore, the presence of AFB1 in pistachio nuts could be correctly predicted in 70-81 % of the cases from a growth model developed in pistachio nuts, and in 67-81% of the cases from an AFB1 model developed in pistachio agar. The information obtained in the present work could be used by producers and processors to predict the time for AFB1 production by A. flavus on pistachio nuts during transport and storage.

Equisetum arvense hydro-alcoholic extract: phenolic composition and antifungal and antimycotoxigenic effect against Aspergillus flavus and Fusarium verticillioides in stored maize.

BACKGROUND: Maize is a very important cereal for human and animal diet, but it can be contaminated by moulds and their mycotoxins. On the other hand, natural plant products with antimicrobial properties could possibly used to control mycotoxigenic fungi in foods and feeds. In this study, Equisetum arvense extract was tested for the efficacy on Aspergillus section Flavi and Fusarium section Liseola growth. Natural contaminated maize was used in this study and extract was added under different water activities (a(w)) - 0.90 and 0.95 - for Aspergillus section Flavi and Fusarium section Liseola, respectively. Moulds were inoculated in maize and incubated during 30 days. RESULTS: We confirm that E. arvense extract may be effective for the inhibition of Aspergillus section Flavi in maize with high levels of this mould. Moreover, this extract showed a good inhibition of growth on Fusarium section Liseola levels. Aflatoxin and fumonisin production was not affected by the extract. CONCLUSIONS: E. arvense extract could be an alternative to synthetic fungicides to control maize mycobiota level in moist grain.

Inbred Selection for Increased Resistance to Kernel Contamination with Fumonisins.

In temperate world-wide regions, maize kernels are often infected with the fumonisin-producing fungus Fusarium verticillioides which poses food and feed threats to animals and humans. As maize breeding has been revealed as one of the main tools with which to reduce kernel contamination with fumonisins, a pedigree selection program for increased resistance to Fusarium ear rot (FER), a trait highly correlated with kernel fumonisin content, was initiated in 2014 with the aim of obtaining inbred lines (named EPFUM) with resistance to kernel contamination with fumonisins and adapted to our environmental conditions. The new released EPFUM inbreds, their parental inbreds, hybrids involving crosses of one or two EPFUM inbreds, as well as commercial hybrids were evaluated in the current study. The objectives were (i) to assess if inbreds released by that breeding program were significantly more resistant than their parental inbreds and (ii) to examine if hybrids derived from EPFUM inbreds could be competitive based on grain yield and resistance to FER and fumonisin contamination. Second-cycle inbreds obtained through this pedigree selection program did not significantly improve the levels of resistance to fumonisin contamination of their parental inbreds; however, most EPFUM hybrids showed significantly better resistance to FER and fumonisin contamination than commercial hybrids did. Although European flint materials seem to be the most promising reservoirs of alleles with favorable additive and/or dominance effects for resistance to kernel contamination with fumonisins, marketable new Reid × Lancaster hybrids have been detected as they combine high resistance and yields comparable to those exhibited by commercial hybrids. Moreover, the white kernel hybrid EPFUM-4 × EP116 exploits the genetic variability within the European flint germplasm and can be an alternative to dent hybrid cultivation because white flint grain can lead to higher market prices.

Quantification and classification of deoxynivalenol-contaminated oat samples by near-infrared hyperspectral imaging.

Deoxynivalenol (DON) is the most occurring mycotoxin in oat and oat-based products. Near-infrared hyperspectral imaging (NIR-HSI) has been proposed as a promising methodology for analysing DON contamination in the food industry. The present study aims to apply NIR-HSI for DON detection in oat kernels and to quantify and classify naturally DON-contaminated oat samples. Unground and ground oat samples were scanned by NIR-HSI before their DON content was determined by HPLC. The data were pre-treated and analysed by PLS regression and four classification methods. The most efficient DON prediction model was for unground samples (R2 = 0.75 and RMSEP = 403.18 µg/kg), using twelve characteristic wavelengths with a special interest in 1203 and 1388 nm. The random forest algorithm of unground samples according to the EU maximum limit for unprocessed oats (1750 µg/kg) achieved a classification accuracy of 77.8 %. These findings indicate that NIR-HSI is a promising tool for detecting DON in oats.

Modelling Aspergillus flavus growth and aflatoxins production in pistachio nuts.

Aflatoxins (AFs) are the main contaminants in pistachio nuts. AFs production in pistachio has been attributed to Aspergillus flavus. The aim of this study was to apply existing models to predict growth and AFs production by an A. flavus isolated from pistachios as a function of moisture content and storage temperature of pistachios in order to test their usefulness and complementarities. A full factorial design was used: the moisture content levels assayed were 10, 15, 20, 25 and 30% and incubation temperatures were 10, 15, 20, 25, 30, 37 and 42 °C. Both kinetic and probability models were built to predict growth of the strain under the assayed conditions. Among the assayed models, cardinal ones gave a good quality fit for radial growth rate data. Moreover, the progressive approach, which was developed based on a reduced number of experimental points led to an improved prediction in the validation step. This is quite significant as may allow for improved experimental designs, less costly than full factorial ones. Probability model proved to be concordant in 91% of the calibration set observations. Even though the validation set included conditions around the growth/no-growth interface, there was a 100% agreement in the predictions from the data set (n = 16, cut off = 0.5) after 60 days. Similarly, the probability for AF presence was rightly predicted in 89% of the cases. According to our results EC maximum aflatoxin levels would be surpassed in a period as short as 1 month if pistachio nuts reach 20 °C, unless %mc is ≤10%.

Optimising the number of isolates to be used to estimate growth parameters of mycotoxigenic species.

The aim of the present work was to mathematically assess the minimum number of isolates that would lead to equivalent growth parameters estimates to those obtained with a high number of strains. The datasets from two previous works on 30 Aspergillus carbonarius isolates and 62 Penicillium expansum isolates were used for this purpose. First, the datasets were used to produce a global estimation of growth parameters µ (growth rate, mm/d) and λ (time to visible growth, d) under the different experimental conditions, providing also a 95% confidence interval. Second, a computational algorithm was developed in order to obtain an estimation of the growth parameters that one would obtain using a lower number of isolates and/or replicates, using a bootstrap procedure with 5000 simulations. The result of this algorithm was the probability that the obtained estimation falls in the 95% confidence interval previously produced using all sample isolates. Third, the algorithm was intensively applied to obtain these probabilities for all possible combinations of isolates and replicates. Finally, these results were used to determine the minimum number of isolates and replicates needed to obtain a reasonable estimation, i.e. inside the confidence interval, with a probability of 0.8, 0.9 and 0.95. The results revealed that increasing the number of isolates may be more effective than increasing the number of replicates, in terms of increasing the probability. In particular, 12-17 isolates of A. carbonarius led to the same growth parameters as the total 30 (p = 0.05) or 9 isolates with p = 0.20; by contrast, 25-30 isolates of P. expansum led to the same growth parameters as the total 62 (p = 0.05) or 18-21 isolates with p = 0.20. As far as we know, this is the first study that provides a systematic evaluation of the number of isolates and replicates needed when designing an experiment involving mycotoxigenic moulds responses to environmental factors, and may serve to support decision making in this kind of studies or other similar ones.

Ochratoxigenic moulds and effectiveness of grape field antifungals in a climatic change scenario.

BACKGROUND: The presence of ochratoxin A (OTA) in grapes and grape derivatives has been reported mainly in the Mediterranean area. Consequently, great efforts are being made to prevent the growth of Aspergillus on grapes. However, the European Commission suggests that climate change may result in increased temperatures and longer drought periods in southern Europe. Therefore the aim of this study was to investigate how ochratoxigenic fungal growth and the efficiency of fungicides used at present might be affected by environmental conditions predicted with climate change. RESULTS: The effectiveness of grape field antifungals (Switch, Flint Max and Equisetum arvense extract) under two alternating temperature, photoperiod and relative humidity (RH) scenarios (current: 20/30 °C, 16 h light/8 h darkness, 80% RH; predicted: 25/37 °C, 16 h light/8 h darkness, 75% RH) on the growth and OTA production of two Aspergillus carbonarius isolates and one Aspergillus ochraceus isolate on grapes was investigated. CONCLUSION: Predicted conditions reduced A. carbonarius and limited A. ochraceus growth. Antifungals reduced fungal infection (by 40-84%), although no correlation between climatic conditions and effectiveness of the antifungals was found. However, Switch always showed the greatest reduction and E. arvense (0.02 g mL(-1) extract) the least. Higher temperatures affected OTA production by the isolates in different ways. In general, Switch and Flint Max reduced OTA production, while E. arvense stimulated it.

Impact of cycling temperatures on Fusarium verticillioides and Fusarium graminearum growth and mycotoxins production in soybean.

BACKGROUND: Fusarium graminearum and F. verticillioides are two very important mycotoxigenic species as they cause diverse diseases in crops. The effects of constant and cycling temperatures on growth and mycotoxin production of these species were studied on soybean based medium and on irradiated soya beans. RESULTS: F. graminearum grew better when was incubated at 15, 20 and 15-20 °C (isothermal or cycling temperature) during 21 days of incubation. Maximum levels of zearalenone and deoxynivalenol (39.25 and 1040.4 µg g(-1), respectively) were detected on soya beans after 15 days of incubation and the optimal temperature for mycotoxin production was 15 °C for zearalenone and 20 °C for deoxynivalenol. F. verticillioides grew better at 25 °C in culture medium and at 15/20 °C and 15/25 °C on soybean seeds. Fumonisin B(1) was produced only in culture medium, and the maximum level (7.38 µg g(-1)) was found at 15 °C after 7 days of incubation. CONCLUSION: When growth and mycotoxin production under cycling temperatures were predicted from the results under constant conditions, observed values were different from calculated for both species and substrate medium. Therefore, care should be taken if data at constant temperature conditions are to be extrapolated to real field conditions.

Relevant Fusarium Mycotoxins in Malt and Beer.

Mycotoxins are secondary fungal metabolites of high concern in the food and feed industry. Their presence in many cereal-based products has been numerously reported. Beer is the most consumed alcoholic beverage worldwide, and Fusarium mycotoxins originating from the malted and unmalted cereals might reach the final product. This review aims to describe the possible Fusarium fungi that could infect the cereals used in beer production, the transfer of mycotoxins throughout malting and brewing as well as an insight into the incidence of mycotoxins in the craft beer segment of the industry. Studies show that germination is the malting step that can lead to a significant increase in the level of all Fusarium mycotoxins. The first step of mashing (45 °C) has been proved to possess the most significant impact in the transfer of hydrophilic toxins from the grist into the wort. However, during fermentation, a slight reduction of deoxynivalenol, and especially of zearalenone, is achieved. This review also highlights the limited research available on craft beer and the occurrence of mycotoxins in these products.

Deterministic and Probabilistic Dietary Exposure Assessment to Deoxynivalenol in Spain and the Catalonia Region.

Deoxynivalenol (DON) remains one of the most concerning mycotoxins produced by the Fusarium genus due to the wide occurrence in highly consumed cereal-based food and its associated toxicological effects. Previous studies conducted in Spain and other European countries suggested that some vulnerable groups such as children could be exceeding the tolerable daily intakes. Thus, the aim of this study was to conduct a comprehensive and updated dietary exposure assessment study in Spain, with a specific analysis in the region of Catalonia. Cereal-based food samples collected during 2019 were analysed using liquid chromatography coupled to tandem mass spectrometry for multi-mycotoxin detection including DON and its main metabolites and derivatives. Consumption data were gathered from the nation-wide food surveys ENALIA and ENALIA2 conducted in Spain, and a specific survey conducted in Catalonia. The data were combined using deterministic and semi-parametric probabilistic methods. The results showed that DON was widely present in cereal-based food highly consumed in Spain and the Catalonia region. Exposure to DON among the adult population was globally low; however, among infants aged 3-9 years, it resulted in the median of 192 ng/kg body weight/day and the 95th percentiles of 604 ng/kg body weight/day, that would exceed the most conservative safety threshold for infants. Bread and pasta were the main contributing foodstuffs to the global exposure to DON, even among infants; thus, those foods should be considered a priority for food control or to develop strategies to reduce the exposure. In any case, further toxicological and epidemiological studies are required in order to refine the safety thresholds accounting for the sensitivity of the infant population.

Hyperspectral imaging for the classification of individual cereal kernels according to fungal and mycotoxins contamination: A review.

One of the most common concerns in the cereal industry is the presence of fungi and their associated mycotoxins. Hyperspectral Imaging (HSI) has been proposed recently as one of the most potent tools to manage fungal associated contamination. The introduction of a spatial dimension to the spectral analysis allows the selection of the specific regions of the sample for further screening. Single kernel analysis would enable the discrimination of the highly contaminated kernels to establish a mitigation strategy, overcoming the contamination heterogeneity of cereal batches. This document is a detailed review of the HSI recently published studies that aimed to discriminate fungi and mycotoxin contaminated single cereal kernels. The most relevant findings showed that fungal infection and mycotoxins levels discrimination accuracies were above 90% and 80%, respectively. The results indicate that NIR-HSI is suitable for the detection of fungal-related contamination in single kernels and it has potential to be applied at food industry stages.

Occurrence and Dietary Exposure Assessment to Enniatin B through Consumption of Cereal-Based Products in Spain and the Catalonia Region.

Enniatin B (ENNB) is a mycotoxin produced by moulds from the Fusarium genera and its toxic effects are still not fully elucidated, hence a safe reference exposure value has not been established yet. ENNB is the most prevalent emerging mycotoxin and is widely found in cereal-based products, nevertheless, there are no comprehensive exposure assessment studies. For that reason, the aim of this study was to characterise the occurrence of ENNB and estimate the exposure of the Spanish and Catalan populations. A total of 347 cereal-based products were collected in 2019 and were analysed using liquid chromatography-tandem mass spectrometry. Consumption data were obtained from the national food consumption surveys (ENALIA) and a regional survey conducted in Catalonia. The global exposure was estimated using deterministic and probabilistic methods. The results showed a high occurrence of close to 100% in all foodstuffs, with a range from 6 to 269 µg/kg, and a strong correlation with the levels of deoxynivalenol. Children aged one-nine years were the most exposed, showing mean estimates in the range 308-324 ng/kg bw/day and 95th percentiles 697-781 ng/kg bw/day. This study stresses the need for further toxicological data to establish reference doses and conclude formal risk assessment, accounting for the co-occurrence with deoxynivalenol.

Influence of Agronomic Factors on Mycotoxin Contamination in Maize and Changes during a 10-Day Harvest-Till-Drying Simulation Period: A Different Perspective.

Agronomic factors can affect mycotoxin contamination of maize, one of the most produced cereals. Maize is usually harvested at 18% moisture, but it is not microbiologically stable until it reaches 14% moisture at the drying plants. We studied how three agronomic factors (crop diversification, tillage system and nitrogen fertilization rate) can affect fungal and mycotoxin contamination (deoxynivalenol and fumonisins B1 and B2) in maize at harvest. In addition, changes in maize during a simulated harvest-till-drying period were studied. DON content at harvest was higher for maize under intensive tillage than using direct drilling (2695 and 474 µg kg-1, respectively). We found two reasons for this: (i) soil crusting in intensive tillage plots caused the formation of pools of water that created high air humidity conditions, favouring the development of DON-producing moulds; (ii) the population of Lumbricus terrestris, an earthworm that would indirectly minimize fungal infection and mycotoxin production on maize kernels, is reduced in intensive tillage plots. Therefore, direct drilling is a better approach than intensive tillage for both preventing DON contamination and preserving soil quality. Concerning the simulated harvest-till-drying period, DON significantly increased between storage days 0 and 5. Water activity dropped on the 4th day, below the threshold for DON production (around 0.91). From our perspective, this study constitutes a step forward towards understanding the relationships between agronomic factors and mycotoxin contamination in maize, and towards improving food safety.

Biocontrol of Mycotoxigenic Fungi Using Bacteria Isolated from Ecological Vineyard Soils.

The presence of mycotoxin-producing Aspergillus species in vineyards is a problem for food safety and the economy. In addition, rising temperatures due to climate change are modifying microbial communities, causing the replacement of some fungal species and the rise of mycotoxins such as aflatoxins. The use of microorganisms as biological control agents (BCAs) is one of the most promising strategies to prevent fungal growth and toxin production. In this study, 513 microorganisms were isolated from organic vineyard soils in different regions of Spain. The 480 bacteria and 33 yeasts isolated were sequentially screened to select those with the most suitable characteristics to be used as BCAs. After identifying 16 isolates meeting all requirements, six bacterial isolates were selected to test their potential to control three relevant toxigenic grape fungi in vitro: A. carbonarius, A. niger and A. flavus. Isolates of Arthrobacter sp., Rhodococcus sp. and Bacillus mycoides showed an excellent ability to reduce the growth and mycotoxin concentration of the above-mentioned fungi and represent potential candidates for further study regarding their possible industrial application as a BCA.

Modelling the effect of temperature and water activity in the growth boundaries of Aspergillus ochraceus and Aspergillus parasiticus.

The aim of this work was to model the growth of Aspergillus parasiticus and Aspergillus ochraceus, both mycotoxin producers, near to the growth/no growth boundaries and validate those models in sterile maize grain, peanuts and coffee beans. Malt extract agar was adjusted to six different water activities: 0.93, 0.91, 0.89, 0.87, 0.85 and 0.80. Plates were incubated at 10, 15, 20, 25, 30, 37 and 42 °C. For each of the 42 conditions, 10 Petri dishes were inoculated. Both kinetic and probability models were applied to colony growth data. The results of the present study indicate that the developed probability modelling approach could be satisfactorily employed to quantify the combined effect of temperature and water activity on the growth responses of A. ochraceus and A. parasiticus. However, validation of kinetic results led to poor goodness of prediction. In this study, the validation samples were placed near to the expected boundaries of the models in order to test them under the worst situation. Probability of growth prediction under extreme growth conditions was somewhat compromised, but it can be considered acceptable.

Near-infrared hyperspectral imaging for deoxynivalenol and ergosterol estimation in wheat samples.

The present study aimed to evaluate the use of hyperspectral imaging (HSI)-NIR spectroscopy to assess the presence of DON and ergosterol in wheat samples through prediction and classification models. To achieve these objectives, a first set of bulk samples was scanned by HSI-NIR and divided into two subsamples, one that was analysed for ergosterol and another that was analysed for DON by HPLC. This method was repeated for a second larger set to build prediction and classification models. All the spectra were pretreated and statistically processed by PLS and LDA. The prediction models presented a RMSEP of 1.17 mg/kg and 501 µg/kg for ergosterol and DON, respectively. Classification achieved an encouraging accuracy of 85.4% for an independent validation set of samples. The results confirm that HSI-NIR may be a suitable technique for ergosterol quantification and DON classification of samples according to the EU legal limit for DON.