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Plant-based screening experiments were conducted with the aim of identifying biocontrol bacteria and fungi for seed treatment of maize. Candidate microorganisms were evaluated for their protective effects against soilborne infections by species of Fusarium, Globisporangium (syn. Pythium) and Rhizoctonia. The microorganisms tested were bacteria and fungi from maize roots or other sources, including some active microbial components of commercial biocontrol products. Due to the method of isolation chosen, the majority of bacteria from maize roots were spore formers, most of them species of the genera Bacillus,Brevibacillus and Paenibacillus. In pot tests with the potting substrate inoculated with F. culmorum, the level of control provided by seed treatment with the most efficacious bacterial and fungal isolates was comparable or close to the chemical reference seed treatment thiram. The most effective bacteria were species of Pseudomonas, Burkholderia and Streptomyces. Among a subset of approx. 100 bacteria studied, the in vivo and in vitro activities against F.culmorum were only weakly correlated, although some strains deviated from this pattern. The most effective fungi were two strains of Clonostachys rosea and isolates of Trichoderma. The latter and a strain of Gliocladium virens provided also protection against R.solani. Activity against Globisporangium ultimum was recorded for one isolate of Trichoderma and the two strains of C. rosea. A reduction in the impact of seedborne F. culmorum was also observed after seed treatment with two strains of F. oxysporum f. sp. strigae. The results are discussed in relation to previous reports on rhizosphere bacteria of maize and their use in biocontrol of plant pathogens or for plant growth promotion.

The study describes the development and employment of plant tests based on artificial inoculation of seeds or the potting substrate for evaluating the potential of microorganisms to control seedling blight of maize caused by seed- and soil-borne fusaria. Nine strains of Fusarium were isolated from maize kernels and identified morphologically and by molecular methods as belonging to the species Fusarium verticillioides, F. subglutinans, F. cerealis, F. poae and F. proliferatum. In order to determine pathogenicity, maize kernels were inoculated by immersion in suspensions of conidia of these isolates and sown in a pasteurized substrate in seed trays. Based on plant dry weight, the isolates of F. verticillioides and F. subglutinans were more pathogenic than the other isolates. Using an isolate of F. subglutinans, the efficacy of a set of 25 potential fungal and bacterial antagonists was assessed using inoculation of maize kernels by placement in mixtures of the pathogen and the antagonists. The results obtained with this methodology indicate the potential of a number of different microorganisms applied as seed treatments, including some reported previously as biocontrol agents, to control seed-borne seedling blight of maize. In order to develop a method for the testing of biocontrol agents against soil-borne attack, isolates of F. subglutinans, F. cerealis and F poae from maize kernels together with isolates of F. avenaceum, F. culmorum and F. graminearum originating from maize silage and wheat were used to artificially inoculate the potting substrate. The results showed large differences in pathogenicity, with the most aggressive isolates belonging to F. culmorum and F. graminearum.

Fusarium mycotoxins and their derivatives are frequently detected in freshly harvested forage maize. This study assessed the time course effects during ensiling of forage maize on the fate of Fusarium mycotoxins, using laboratory-scale silos and artificially contaminated raw material. A multi-mycotoxin liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method was used to determine the levels of deoxynivalenol (DON), zearalenone (ZEN) and their derivatives DON-3-glucoside, 3-acetyl-DON, 15-acetyl-DON, deepoxy-DON, α-zearalenol and β-zearalenol. A significant increase of DON was observed during ensiling, whereas the levels of DON-3-glucoside and its acetylated forms proportionally decreased. In contrast, levels of ZEN, α-zearalenol and β-zearalenol were not affected by the ensiling process. Based on these findings, ensiling is not a practical method for reducing the total amount of Fusarium mycotoxins present at harvest.

Forage maize is often infected by mycotoxin-producing Fusarium fungi during plant growth, which represent a serious health risk to exposed animals. Deoxynivalenol (DON) and zearalenone (ZEN) are among the most important Fusarium mycotoxins, but little is known about the occurrence of their modified forms in forage maize. To assess the mycotoxin contamination in Northern Germany, 120 natural contaminated forage maize samples of four cultivars from several locations were analysed by liquid chromatography-high resolution mass spectrometry (LC-HRMS) for DON and ZEN and their modified forms deoxynivalenol-3-glucoside (DON3G), the sum of 3- and 15-acetyl-deoxynivalenol (3+15-AcDON), α- and β-zearalenol (α-ZEL, β-ZEL). DON and ZEN occurred with high incidences (100 and 96%) and a wide range of concentrations, reaching levels up to 10,972 and 3910 µg/kg, respectively. Almost half of the samples (46%) exceeded the guidance value in complementary and complete feeding stuffs for ZEN (500 µg/kg), and 9% for DON (5000 µg/kg). The DON related mycotoxins DON3G and 3+15-AcDON were also present in almost all samples (100 and 97%) with amounts of up to 3038 and 2237 µg/kg and a wide range of concentrations. For the ZEN metabolites α- and β-ZEL lower incidences were detected (59 and 32%) with concentrations of up to 423 and 203 µg/kg, respectively. Forage maize samples were contaminated with at least three co-occurring mycotoxins, whereby 95% of all samples contained four or more mycotoxins with DON, DON3G, 3+15-AcDON, and ZEN co-occurring in 93%, together with α-ZEL in 57% of all samples. Positive correlations were established between concentrations of the co-occurring mycotoxins, especially between DON and its modified forms. Averaged over all samples, ratios of DON3G/DON and 3+15-AcDON/DON were similar, 20.2 and 20.5 mol%, cultivar-specific mean ratios ranged from 14.6 to 24.3 mol% and 15.8 to 24.0 mol%, respectively. In total, 40.7 mol% of the measured DON concentration was present in the modified forms DON3G and 3+15-AcDON. The α-ZEL/ZEN ratio was 6.2 mol%, ranging from 5.2 to 8.6 mol% between cultivars. These results demonstrate that modified mycotoxins contribute substantially to the overall mycotoxin contamination in forage maize. To avoid a considerable underestimation, it is necessary to analyse modified mycotoxins in future mycotoxin monitoring programs together with their parent forms.

Grains of the three differentially Fusarium-susceptible winter wheat cultivars “Ritmo” (highly susceptible), “Inspiration” (moderately to highly susceptible) and “Dekan” (lowly to moderately susceptible) from up to eight trial locations in Schleswig-Holstein (Northern Germany) and maize-free crop rotations were analysed for their mycotoxin concentration from 2008 to 2017 (“Inspiration” and “Dekan” since 2012). The deoxynivalenol (DON) and zearalenone (ZEA) concentrations of wheat grain samples differed significantly between individual years and within each year between the trial locations due to weather conditions during flowering. Significant relationships were found between the two weather variables cumulative precipitation (added up by all daily cumulative precipitation) and average temperature (averaged for all daily means of temperature) during the period of wheat flowering and DON and ZEA concentrations in wheat grain at harvest. These relationships were determined for “Ritmo” from 2008 to 2014 ( $$R^{2}_{{{\text{adj}} .}}$$ = 0.81 for DON; $$R^{2}_{{{\text{adj}} .}}$$ = 0.75 for ZEA) and for both “Inspiration” ( $$R^{2}_{{{\text{adj}} .}}$$ = 0.84 for DON; $$R^{2}_{{{\text{adj}} .}}$$ = 0.82 for ZEA) and “Dekan” ( $$R^{2}_{{{\text{adj}} .}}$$ = 0.78 for DON; $$R^{2}_{{{\text{adj}} .}}$$ = 0.77 for ZEA) from 2012 to 2016. Based on this, multiple regression models were developed for the three cultivars for the prediction of DON and ZEA contamination in wheat grain: model 1 = highly susceptible; model 2 = moderately to highly susceptible; model 3 = lowly to moderately susceptible. The models included the covariates cumulative precipitation and average temperature during wheat flowering and the interaction term of precipitation and temperature. The predictive power of the three models was evaluated with data not utilized in the development of the models, i.e. weather conditions during wheat flowering and DON and ZEA concentrations in wheat grain at harvest at the same trial locations in the years 2015 to 2017 for model 1 and in 2017 for model 2 and model 3. The models showed a high predictive power by regressing observed versus predicted values (model 1: R2 = 0.89 for DON, R2 = 0.91 for ZEA; model 2: R2 = 0.91 for DON, R2 = 0.84 for ZEA; model 3: R2 = 0.86 for DON, R2 = 0.89 for ZEA). Model 1 predicted correctly whether the concentrations of DON and ZEA were either lower or higher than the European maximum levels of 1250 µg DON/kg and 100 µg ZEA/kg in 95.2% of the cases. Models 2 and 3 performed 85.7% and 100% correct predictions for DON in 2017, respectively. Model 2 predicted correctly whether the ZEA concentration was either lower or higher than the maximum level of 100 µg ZEA/kg in 100% of the cases in 2017, whereas model 3 performed 85.7% correct predictions. The models are therefore useful for the prediction of DON and ZEA concentrations in wheat grain from maize-free crop rotations based on cumulative precipitation and average temperature during wheat flowering and for differentially susceptible wheat cultivars.

The geographic distribution and DNA-disease severity of the anastomosis groups (AG) 1 IA, AG 1 IB and AG 2-2 IIIB within the teleomorph Thanatephorus cucumeris and R. cerealis (CAG 1, AG-D) within the teleomorph Ceratobasidium cereale, which are known to be pathogenic to maize, were determined by analysing maize roots from different regions with high proportions of maize within the crop rotation in Germany and France in the experimental years 2014 (n = 53) and 2015 (n = 63) using qPCR. For the interpretation of the measured values, a weighted risk index (RI%) was conducted considering cropping history and soil physical properties at the sampled sites. A positive detection of at least one of the tested species was possible in 83% of the samples analysed in both experimental years 2014 and 2015. In 2014, R. cerealis (53%) was most prevalent, while in 2015, AG 2-2 IIIB (70%) shows the highest detection frequency. Regarding the cropping system at the sampled sites, the binucleate Rhizoctonia spp. leads to higher risk indices (RI%) if maize is grown in wide to limited crop rotations with high content of cereals, whereas AG 2-2 IIIB is more present and achieved higher disease severities if maize is grown in monoculture. The other tested members of the teleomorph T. cucumeris, AG 1 IA and AG 1 IB, showed high detection frequencies especially in the experimental year 2014. Regarding the DNA-disease severity, compared to the results of AG 2-2 IIIB, for these two anastomosis groups only a latent infection was observed. Soil type or cropping history had no serve influence on the DNA-disease severity of these two Rhizoctonia spp. in maize.

The selective and sensitive analysis of mycotoxins in highly complex feed matrices is a great challenge. In this study, the suitability of OrbitrapTM-based high-resolution mass spectrometry (HRMS) for routine mycotoxin analysis in complex feeds was demonstrated by the successful validation of a full MS/data-dependent MS/MS acquisition method for the quantitative determination of eight Fusarium mycotoxins in forage maize and maize silage according to the Commission Decision 2002/657/EC. The required resolving power for accurate mass assignments (&lt, 5 ppm) was determined as 35,000 full width at half maximum (FWHM) and 70,000 FWHM for forage maize and maize silage, respectively. The recovery (RA), intra-day precision (RSDr), and inter-day precision (RSDR) of measurements were in the range of 94 to 108%, 2 to 16%, and 2 to 12%, whereas the decision limit (CC&alpha, ) and the detection capability (CC&beta, ) varied from 11 to 88 &micro, g/kg and 20 to 141 &micro, g/kg, respectively. A set of naturally contaminated forage maize and maize silage samples collected in northern Germany in 2017 was analyzed to confirm the applicability of the HRMS method to real samples. At least four Fusarium mycotoxins were quantified in each sample, highlighting the frequent co-occurrence of mycotoxins in feed.

Real-time identification of the occurrence of dangerous pathogens is of crucial importance for the rapid execution of countermeasures. For this purpose, spatial and temporal predictions of the spread of such pathogens are indispensable. The R package papros developed by the authors offers an environment in which both spatial and temporal predictions can be made, based on local data using various deterministic, geostatistical regionalisation, and machine learning methods. The approach is presented using the example of a crops infection by fungal pathogens, which can substantially reduce the yield if not treated in good time. The situation is made more difficult by the fact that it is particularly difficult to predict the behaviour of wind-dispersed pathogens, such as powdery mildew (Blumeria graminis f. sp. tritici). To forecast pathogen development and spatial dispersal, a modelling process scheme was developed using the aforementioned R package, which combines regionalisation and machine learning techniques. It enables the prediction of the probability of yield- relevant infestation events for an entire federal state in northern Germany at a daily time scale. To run the models, weather and climate information are required, as is knowledge of the pathogen biology. Once fitted to the pathogen, only weather and climate information are necessary to predict such events, with an overall accuracy of 68% in the case of powdery mildew at a regional scale. Thereby, 91% of the observed powdery mildew events are predicted.