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In this work, milk samples collected in a cohort of intensive dairy farms of the Po Valley (Italy) were screened for their (poly)-phenolic profile to check the occurrence of phenolic metabolites of biological interest. The selected dairy farms were previously classified on the basis of their cow feeding system, considering the utilization of corn silage as the main ingredient of the rations. Overall, ultra-high-pressure liquid chromatography coupled with mass spectrometry using an Orbitrap analyzer, followed by unsupervised and supervised statistics, allowed identifying clear different phenolic distributions in the milk samples. Accordingly, a great variability in the phenolic profiles of the different milk samples was observed, with two main phenolic clusters outlined by the unsupervised hierarchical clustering approach and not fully correlated to the nutritional strategy considered. The variables’ importance in the projection approach allowed selecting the most important metabolites, resulting in samples’ discrimination. Among the most discriminative compounds, we found phenolic metabolites (such as hippuric acid and 4-hydroxyhippuric acid), followed by lignans (such as enterolactone) and isoflavonoids (such as equol and O-desmethylangolensin). Taken together, our findings suggested that both the feeding systems and the ability of dairy cows to process parent phenolic compounds were the main factors providing the final (poly)-phenolic profile of the milk samples. Future targeted and ad hoc studies appear of great interest to evaluate the potential biological effects of these compounds on cow health.

Mycotoxins should be monitored in order to properly evaluate corn silage safety quality. In the present study, corn silage samples (n = 115) were collected in a survey, characterized for concentrations of mycotoxins, and scanned by a NIR spectrometer. Random Forest classification models for NIR calibration were developed by applying different cut-offs to classify samples for concentration (i.e., μg/kg dry matter) or count (i.e., n) of (i) total detectable mycotoxins; (ii) regulated and emerging Fusarium toxins; (iii) emerging Fusarium toxins; (iv) Fumonisins and their metabolites; and (v) Penicillium toxins. An over- and under-sampling re-balancing technique was applied and performed 100 times. The best predictive model for total sum and count (i.e., accuracy mean ± standard deviation) was obtained by applying cut-offs of 10,000 µg/kg DM (i.e., 96.0 ± 2.7%) or 34 (i.e., 97.1 ± 1.8%), respectively. Regulated and emerging Fusarium mycotoxins achieved accuracies slightly less than 90%. For the Penicillium mycotoxin contamination category, an accuracy of 95.1 ± 2.8% was obtained by using a cut-off limit of 350 µg/kg DM as a total sum or 98.6 ± 1.3% for a cut-off limit of five as mycotoxin count. In conclusion, this work was a preliminary study to discriminate corn silage for high or low mycotoxin contamination by using NIR spectroscopy.

In this study, an untargeted metabolomics approach based on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) was used for investigating changes in chemical profiles of cow milk considering diets based on mycotoxins-contaminated corn silages. For this purpose, 45 milk samples were classified into five clusters according to the corn silage contamination profile, namely (1) low levels of Aspergillus- and Penicillium-mycotoxins, (2) low levels of fumonisins and other Fusarium-mycotoxins, (3) high levels of Aspergillus-mycotoxins, (4) high levels of non-regulated Fusarium-mycotoxins, (5) high levels of fumonisins and their metabolites, and subsequently analyzed by UHPLC-HRMS followed by a multivariate statistical analysis (both unsupervised and supervised statistical approaches). Overall, the milk metabolomic profile highlighted potential correlations between the quality of contaminated corn silages (as part of the total mixed ration) and milk composition. Metabolomics allowed to identify 628 significant milk metabolites as affected by the five levels of corn silage contamination considered, with amino acids and peptides showing the highest metabolite set enrichment (134 compounds). Additionally, 78 metabolites were selected as the best discriminant of the prediction model built, possessing a variable importance in projection score &gt, 1.2. The average Log Fold-Change variations of the discriminant metabolites provided evidence that sphingolipids, together with purine and pyrimidine-derived metabolites were the most affected chemical classes. Also, metabolomics revealed a significant accumulation of oxidized glutathione in milk samples belonging to the silage cluster contaminated by emerging Aspergillus toxins, likely involved in the oxidative imbalance. These preliminary findings provide new insights into the potential role of milk metabolomics to provide chemical indicators of mycotoxins-contaminated corn silage feeding systems.

In this work, a retrospective screening based on ultra-high-performance liquid chromatography (UHPLC) coupled with high-resolution mass spectrometry (HRMS) based on Orbitrap-Q-Exactive Focus™ was used to check the occurrence of regulated and emerging mycotoxins in bulk milk samples. Milk samples were collected from dairy farms in which corn silage was the main ingredient of the feeding system. The 45 bulk milk samples were previously analyzed for a detailed untargeted metabolomic profiling and classified into five clusters according to the corn silage contamination profile, namely: (1) low levels of Aspergillus- and Penicillium-mycotoxins, (2) low levels of fumonisins and other Fusarium-mycotoxins, (3) high levels of Aspergillus-mycotoxins, (4) high levels of non-regulated Fusarium-mycotoxins, (5) high levels of fumonisins and their metabolites. Multivariate statistics based on both unsupervised and supervised analyses were used to evaluate the significant fold-change variations of the main groups of mycotoxins detected when comparing milk samples from clusters 3, 4, and 5 (high contamination levels of the corn silages) with cluster 1 and 2 (low contamination levels of the corn silages). Overall, 14 compounds showed a significant prediction ability, with antibiotic Y (VIP score = 2.579), bikaverin (VIP score = 1.975) and fumonisin B2 (VIP score = 1.846) being the best markers. The k-means clustering combined with supervised statistics showed two discriminant groups of milk samples, thus revealing a hierarchically higher impact of the whole feeding system (rather than the only corn silages) together with other factors of variability on the final mycotoxin contamination profile. Among the discriminant metabolites we found some Fusarium mycotoxins, together with the tetrapeptide tentoxin (an Alternaria toxin), the α-zearalenol (a catabolite of zearalenone), mycophenolic acid and apicidin. These preliminary findings provide new insights into the potential role of UHPLC-HRMS to evaluate the contamination profile and the safety of raw milk to produce hard cheese.

Effects of commercial and pure lactic acid bacteria (LAB) inoculants on fermentation and levels of aflatoxins and other mycotoxins in corn silage that was experimentally contaminated in the field with a toxigenic strain of Aspergillus flavus (ITEM 8069) were determined. Late-season corn hybrid plants were inoculated with A. flavus at silk emergence, and fresh-chopped corn was harvested at the ⅔ milk line stage (dry matter [DM]: 428 ± 6.5 g/kg) and ensiled directly (control, CTR) or after treatment with 9 LAB inoculants. Commercial inoculants contained Lactobacillus (L.) buchneri LB1819 and Lactococcus lactis O224 or Enterococcus faecium, Lactobacillus plantarum, Lactococcus lactis SR3.54 (respectively SiloSolve FC or SiloSolve MC, Chr. Hansen A/S, Horsholm, Denmark), L. buchneri and L. plantarum (Pioneer brand 11C33, Pioneer Hi-Bred International, Des Moines, USA). One pure strain of L. brevis DSMZ 20054, two pure strains of L. plantarum (LP ATCC 8014 and LP PB) and three of L. rhamnosus (LR ATCC 7469, LR LR7 and LR RI) were also used. Each silage received an inoculant at final expected dose of approximately 250,000 CFU/g of freshly chopped forage, and was ensiled in 20 L mini-silos, compacted to density of 160 kg dry-mass/m3, stored at room temperature, and opened after 30 or 120 days. The commercial and pure inoculants had few effects on fermentation relative to CTR. Ensiling time and LAB treatment had no effect on silage pH. However SiloSolve FC silage had lower ethanol levels than CTR group, while 1,2 propanediol level doubled as ensiling time increased and the high values were with SiloSolve FC and Pioneer CFT. Aerobic stability increased with ensiling time, with the longest stability in SiloSolve FC and L. rhamnosus ATCC 7469 silage. Lowest aflatoxin B1 (AFB1) concentrations were in the L. rhamnosus LR7 and L. plantarum ATCC 8014 silages (about 8–10 μg/kg DM) and the highest concentration was in L. brevis DSMZ 20054 silage (34.2 μg/kg DM). Concluding, future investigations should be carried out to examine the relationship between LAB and mycotoxinegic fungi during ensiling.

Sixty-four corn silages were characterized for chemicals, bacterial community, and concentrations of several fungal metabolites. Silages were grouped in five clusters, based on detected mycotoxins, and they were characterized for being contaminated by (1) low levels of Aspergillus- and Penicillium-mycotoxins, (2) low levels of fumonisins and other Fusarium-mycotoxins, (3) high levels of Aspergillus-mycotoxins, (4) high levels of non-regulated Fusarium-mycotoxins, (5) high levels of fumonisins and their metabolites. Altersetin was detected in clusters 1, 3, and 5. Rugulusovin or brevianamide F were detected in several samples, with the highest concentration in cluster 3. Emodin was detected in more than 50.0% of samples of clusters 1, 3 and 5, respectively. Kojic acid occurred mainly in clusters 1 and 2 at very low concentrations. Regarding Fusarium mycotoxins, high occurrences were observed for FB3, FB4, FA1, whereas the average concentrations of FB6 and FA2 were lower than 12.4 µg/kg dry matter. Emerging Fusarium-produced mycotoxins, such as siccanol, moniliformin, equisetin, epiequisetin and bikaverin were detected in the majority of analyzed corn silages. Pestalotin, oxaline, phenopirrozin and questiomycin A were detected at high incidences. Concluding, this work highlighted that corn silages could be contaminated by a high number of regulated and emerging mycotoxins.