Quantitative PCR (qPCR) for estimating the presence of Fusarium and its mycotoxins in barley grains.

Members within the Fusarium sambucinum species complex (FSAMSC) are able to produce mycotoxins, such as deoxynivalenol (DON), nivalenol (NIV), zearalenone (ZEN) and enniatins (ENNs) in food products. Consequently, alternative methods for assessing the levels of these mycotoxins are relevant for quick decision-making. In this context, qPCR based on key mycotoxin biosynthetic genes could aid in determining the toxigenic fungal biomass, and could therefore infer mycotoxin content. The aim of this study was to verify the use of qPCR as a technique for estimating DON, NIV, ENNs and ZEN, as well as Fusarium graminearum sensu lato (s.l.) and F. poae in barley grains. For this purpose, 53 barley samples were selected for mycobiota, mycotoxin and qPCR analyses. ENNs were the most frequent mycotoxins, followed by DON, ZEN and NIV. 83% of the samples were contaminated by F. graminearum s.l. and 51% by F. poae. Pearson correlation analysis showed significant correlations for TRI12/15-ADON with DON, ESYN1 with ENNs, TRI12/15-ADON and ZEB1 with F. graminearum s.l., as well as ESYN1 and TRI12/NIV with F. poae. Based on the results, qPCR could be useful for the assessment of Fusarium presence, and therefore, provide an estimation of its mycotoxins' levels from the same sample.

Rapid assessment of enniatins in barley grains using near infrared spectroscopy and chemometric tools.

Barley is an important crop worldwide, and it can be affected by various fungi, among them Fusarium is one of the most relevant due to the economic losses caused by mycotoxin contamination. Enniantins (ENNs) are one of the emergent group of mycotoxins that have been found in grains around the world. Nowadays, the main analytical tools available to evaluate these contaminants are based on chromatographic techniques that are efficient but time-consuming and expensive. In this context, the present study aimed to assess the performance of near infrared (NIR) spectroscopy to detect and/or classify the enniatin (ENN) content on barley grains. Sixty samples of barley grains from three different regions of Brazil were investigated and the ENN content determined by UPLC-MS/MS. The levels found were then used to develop multivariate models based on infrared spectral data. The results indicated high incidence off ENN presence in the samples (>70 %) and the PLS-DA model determined by NIR data showed adequate values of sensitivity and sensibility (100 % and 94.2 %, respectively) distinguishing between contaminated and non-contaminated barley samples, demonstrating NIR as a promising tool to monitoring this emergent mycotoxin.

Near infrared spectroscopy and smartphone-based imaging as fast alternatives for the evaluation of the bioactive potential of freeze-dried açai.

The development of green analytical techniques for food industry quality control has become an important issue in the context of the fourth industrial revolution. In this sense, near infrared spectroscopy (NIR) and smartphone-based imaging (SBI) were applied to evaluate the bioactive potential of freeze-dried açai pulps. For this purpose, reference results of ninety-six samples were obtained by determining total anthocyanins (TAC), polyphenol content (TPC), and antioxidant capacity (DPPH, ORAC and TEAC) by traditional methods and correlated to NIR spectra and SBI to build predictive models based on partial square least (PLS) regression. In summary, the NIR-PLS models showed better performance for predicting the TAC, TPC and antioxidant capacity of studied samples; considering the parameters of merit, such as coefficient of determination (0.8) and residual prediction deviation (RPD) (2.2) compared to the SBI-PLS models (0.7 and lower 1.5, respectively). The better performance of NIR-PLS could be potentially justified by a higher sensitivity of the NIR equipment than the smartphone images. In conclusion, these results show that the proposed alternative methods are promising tools for the future context of the 4.0 food industry.

NIR spectroscopy and chemometric tools to identify high content of deoxynivalenol in barley.

Deoxynivalenol (DON) is one of the mycotoxins produced mainly by the Fusarium graminearum species complex in small grain cereals, including barley. This toxin can cause alimentary disorders, immune function depression and gastroenteritis. The negative health effects associated with DON coupled to the increasing concern about green and rapid methods of analysis motivated this study. In this context, near infrared (NIR) spectroscopy data were applied for exploratory analysis to distinguish barley with high and low levels of DON contamination (> or <1250 µg/kg according to the European Union threshold), by Partial Least Squares-Discriminant Analysis (PLS-DA), and to verify the performance of Partial Least Squares-Regression (PLS-R) to predict DON concentration in barley samples. Maximum values of specificity and sensitivity were achieved in the calibration set; 90.9% and 81.9% were observed in the cross-validation set for the PLS-DA classification model. PLS-R quantification of DON in barley presented low values of error (RMSEC = 101.94 µg/kg and RMSEP = 160.76 µg/kg). Thus, we found that NIR in combination with adequate chemometric tools could be applied as a green technique to monitor DON contamination in barley.

In vitro digestion effect on mineral bioaccessibility and antioxidant bioactive compounds of plant-based beverages.

Consumption of plant-based beverages (PBB) is a growing trend; and have been used as viable substitutes for dairy based products. To date, no study has comparatively analyzed mineral composition and effect of in vitro digestion on the bioaccessibility of different PBB. The aim of this research was to investigate the content of essential minerals (calcium (Ca), magnesium (Mg), iron (Fe), zinc (Zn)) and to estimate the effect of in vitro digestion in plant-based beverages, and their antioxidant bioactive compounds (phenolic compounds and antioxidant capacity). Moreover, the presence of antinutritional factors, such as myo-inositol phosphates fractions, were evaluated. Samples of PBB (rice, cashew nut, almond, peanut, coconut, oat, soy, blended or not with another ingredients, fortified with minerals or naturally present) and milk for comparison were evaluated. TPC ranged from 0.2 mg GAEq/L for coconut to 12.4 mg GAEq/L for rice and, the antioxidant capacity (DPPH) ranged from 3.1 to 306.5 µmol TE/L for samples containing peanut and oat, respectively. Only a few samples presented myo-inositol phosphates fractions in their composition, mostly IP5 and IP6, especially cashew nut beverages. Mineral content showed a wide range for Ca, ranging from 10 to 1697.33 mg/L for rice and coconut, respectively. The Mg content ranged from 6.29 to 251.23-268.43 mg/L for rice and cashew nut beverages, respectively. Fe content ranged from 0.76 mg/L to 12.89 mg/L for the samples of rice. Zinc content ranged from 0.57 mg/L to 8.13 mg/L for samples of oat and soy, respectively. Significant variation was observed for Ca (8.2-306.6 mg/L) and Mg (1.9-107.4 mg/L) dialyzed between the beverages, with lower concentrations of Fe (1.0 mg/L) and Zn (0.5 mg/L) in dialyzed fractions. This study provides at least 975 analytically determined laboratory results, providing important information for characterization and comparison of different plant-based beverages.