Portable infrared laser spectroscopy for on-site mycotoxin analysis

Mycotoxins are toxic secondary metabolites of fungi that spoil food, and severely impact human health (e.g., causing cancer). Therefore, the rapid determination of mycotoxin contamination including deoxynivalenol and aflatoxin B(1) in food and feed samples is of prime interest for commodity importers and processors. While chromatography-based techniques are well established in laboratory environments, only very few (i.e., mostly immunochemical) techniques exist enabling direct on-site analysis for traders and manufacturers. In this study, we present MYCOSPEC - an innovative approach for spectroscopic mycotoxin contamination analysis at EU regulatory limits for the first time utilizing mid-infrared tunable quantum cascade laser (QCL) spectroscopy. This analysis technique facilitates on-site mycotoxin analysis by combining QCL technology with GaAs/AlGaAs thin-film waveguides. Multivariate data mining strategies (i.e., principal component analysis) enabled the classification of deoxynivalenol-contaminated maize and wheat samples, and of aflatoxin B(1) affected peanuts at EU regulatory limits of 1250 μg kg(−1) and 8 μg kg(−1), respectively

A closed expression for the UV-divergent parts of one-loop tensor integrals in dimensional regularization

Starting from the general definition of a one-loop tensor N-point function, we use its Feynman parametrization to calculate the UV-divergent part of an arbitrary tensor coefficient in the framework of dimensional regularization. In contrast to existing recursion schemes, we are able to present a general analytic result in closed form that enables direct determination of the UV-divergent part of any one-loop tensor N-point coefficient independent from UV-divergent parts of other one-loop tensor N-point coefficients. Simplified formulas and explicit expressions are presented for A-, B-, C-, D-, E-, and F-functions.Comment: 19 pages (single column), the result of previous versions is further evaluated leading to a closed analytic expression for the UV-divergent part of an arbitrary one-loop tensor coefficient, title is modified accordingly, a sign error in the appendix (C_{00000000}) has been corrected, a mathematica notebook containing an implementation of the newly derived formula is attache

Locality optimized unstructured mesh algorithms on GPUs

Unstructured-mesh based numerical algorithms such as finite volume and finite element algorithms form an important class of applications for many scientific and engineering domains. The key difficulty in achieving higher performance from these applications is the indirect accesses that lead to data-races when parallelized. Current methods for handling such data-races lead to reduced parallelism and suboptimal performance. Particularly on modern many-core architectures, such as GPUs, that has increasing core/thread counts, reducing data movement and exploiting memory locality is vital for gaining good performance. In this work we present novel locality-exploiting optimizations for the efficient execution of unstructured-mesh algorithms on GPUs. Building on a two-layered coloring strategy for handling data races, we introduce novel reordering and partitioning techniques to further improve efficient execution. The new optimizations are then applied to several well established unstructured-mesh applications, investigating their performance on NVIDIA’s latest P100 and V100 GPUs. We demonstrate significant speedups (1.1–1.75×) compared to the state-of-the-art. A range of performance metrics are benchmarked including runtime, memory transactions, achieved bandwidth performance, GPU occupancy and data reuse factors and are used to understand and explain the key factors impacting performance. The optimized algorithms are implemented as an open-source software library and we illustrate its use for improving performance of existing or new unstructured-mesh applications

Fusarium langsethiae and mycotoxin contamination in oat grain differed with growth stage at inoculation

High levels of mycotoxins are occasionally observed in Norwegian oat grain lots. Mycotoxins of primary concern in Norwegian oats are deoxynivalenol (DON) produced by Fusarium graminearum and HT2- and T2-toxins (HT2 + T2) produced by Fusarium langsethiae. Improved understanding of the epidemiology of Fusarium spp. is important for the development of measures to control mycotoxins. We studied the susceptibility to F. langsethiae after inoculation at early (booting, heading, flowering) or late (flowering, milk, dough) growth stages in three oat varieties in greenhouse experiments. The varieties had previously shown different levels of resistance to F. graminearum: Odal, Vinger (both moderately resistant), and Belinda (susceptible). The level of F. langsethiae DNA and HT2 + T2 were measured in harvested grain. In addition, we observed differences in aggressiveness (measured as the level of F. langsethiae DNA in grain) between F. langsethiae isolates after inoculation of oats at flowering. Substantial levels of F. langsethiae DNA (mean ≥ 138 pg per μg plant DNA) and HT2 + T2 (≥348 μg/kg) were detected in grain harvested from oats that were spray-inoculated at heading or later stages, but not at booting (mean ≤ 10 pg/μg and ≤ 25 μg/kg, respectively), suggesting that oats are susceptible to F. langsethiae from heading and onwards. Vinger was the most resistant variety to F. langsethiae/HT2 + T2, whereas Odal and Belinda were relatively susceptible. We observed that late inoculations yielded high levels of other trichothecene A metabolites (mean sum of metabolites of 35–1048 μg/kg) in addition to HT2 + T2, in harvested grain, an indication that infections close to harvest may pose a further risk to food and feed safety.publishedVersio

Cultivation area affects the presence of fungal communities and secondary metabolites in Italian durum wheat grains

In this study, durum wheat kernels harvested in three climatically different Italian cultivation areas (Emilia Romagna, Umbria and Sardinia) in 2015, were analyzed with a combination of different isolation methods to determine their fungal communities, with a focus on Fusarium head blight (FHB) complex composition, and to detect fungal secondary metabolites in the grains. The genus Alternaria was the main component of durum wheat mycobiota in all investigated regions, with the Central Italian cultivation area showing the highest incidence of this fungal genus and of its secondary metabolites. Fusarium was the second most prevalent genus of the fungal community in all cultivation environments, even if regional differences in species composition were detected. In particular, Northern areas showed the highest Fusarium incidence, followed by Central and then Southern cultivation areas. Focusing on the FHB complex, a predominance of Fusarium poae, in particular in Northern and Central cultivation areas, was found. Fusarium graminearum, in the analyzed year, was mainly detected in Emilia Romagna. Because of the highest Fusarium incidence, durum wheat harvested in the Northern cultivation area showed the highest presence of Fusarium secondary metabolites. These results show that durum wheat cultivated in Northern Italy may be subject to a higher FHB infection risk and to Fusarium mycotoxins accumulation

Stable isotope dilution assay for the accurate determination of mycotoxins in maize by UHPLC-MS/MS

A fast, easy-to-handle and cost-effective analytical method for 11 mycotoxins currently regulated in maize and other cereal-based food products in Europe was developed and validated for maize. The method is based on two extraction steps using different acidified acetonitrile–water mixtures. Separation is achieved using ultrahigh-performance liquid chromatography (UHPLC) by a linear water–methanol gradient. After electrospray ionisation, tandem mass spectrometric detection is performed in dynamic multiple reaction monitoring mode. Since accurate mass spectrometric quantification is hampered by matrix effects, uniformly [13C]-labelled mycotoxins for each of the 11 compounds were added to the sample extracts prior to UHPLC-MS/MS analysis. Method performance parameters were obtained by spiking blank maize samples with mycotoxins before as well as after extraction on six levels in triplicates. The twofold extraction led to total recoveries of the extraction steps between 97% and 111% for all target analytes, including fumonisins. The [13C]-labelled internal standards efficiently compensated all matrix effects in electrospray ionisation, leading to apparent recoveries between 88% and 105% with reasonable additional costs. The relative standard deviations of the whole method were between 4% and 11% for all analytes. The trueness of the method was verified by the measurement of several maize test materials with well-characterized concentrations. In conclusion, the developed method is capable of determining all regulated mycotoxins in maize and presuming similar matrix effects and extraction recovery also in other cereal-based foods