Descriptive modelling to predict deoxynivalenol in winter wheat in the Netherlands

Predictions of deoxynivalenol (DON) content in wheat at harvest can be useful for decision-making by stakeholders of the wheat feed and food supply chain. The objective of the current research was to develop quantitative predictive models for DON in mature winter wheat in the Netherlands for two specific groups of end-users. One model was developed for use by farmers in underpinning Fusarium spp. disease management, specifically the application of fungicides around wheat flowering (model A). The second model was developed for industry and food safety authorities, and considered the entire wheat cultivation period (model B). Model development was based on observational data collected from 425 fields throughout the Netherlands between 2001 and 2008. For each field, agronomical information, climatic data and DON levels in mature wheat were collected. Using multiple regression analyses, the set of biological relevant variables that provided the highest statistical performance was selected. The two final models include the following variables: region, wheat resistance level, spraying, flowering date, several climatic variables in the different stages of wheat growing, and length of the period between flowering and harvesting (model B only). The percentages of variance accounted for were 64.4% and 65.6% for models A and B, respectively. Model validation showed high correlation between the predicted and observed DON levels. The two models may be applied by various groups of end-users to reduce DON contamination in wheat-derived feed and food products and, ultimately, reduce animal and consumer health risks.     

Climate change increases deoxynivalenol contamination of wheat in north-western Europe

Climate change will affect the development of cereal crops and the occurrence of mycotoxins in these crops, but so far little research has been done on quantifying the expected effects. The aim of this study was to assess climate change impacts on the occurrence of deoxynivalenol in wheat grown in north-western Europe by 2040, considering the combined effects of shifts in wheat phenology and climate. The study used climate model data for the future period of 2031-2050 relative to the baseline period of 1975-1994. A weather generator was used for generating synthetic series of daily weather data for both the baseline and the future periods. Available models for wheat phenology and prediction of deoxynivalenol concentrations in north-western Europe were used. Both models were run for winter wheat and spring wheat, separately. The results showed that both flowering and full maturation of wheat will be earlier in the season because of climate change effects, about 1 to 2 weeks. Deoxynivalenol contamination was found to increase in most of the study region, with an increase of the original concentrations by up to 3 times. The study results may inform governmental and industrial risk managers to underpin decision-making and planning processes in north-western Europe. On the local level, deoxynivalenol contamination should be closely monitored to pick out wheat batches with excess levels at the right time. Using predictive models on a more local scale could be helpful to assist other monitoring measures to safeguard food safety in the wheat supply chain.     

Climatic models to predict occurrence of Fusarium toxins in wheat and maize

Although forecasting Fusarium infections have useful implications, it may be argued that forecasting Fusarium toxins is more useful to help reduce their entry into the food chain. Several disease incidence models have been commercialized for wheat, but only one toxin prediction model from Ontario, Canada, "DONcast", has been validated extensively and commercialized to date for wheat, and another has been proposed for maize. In the development of these predictive tools, the variation in toxin levels associated with year and agronomic effects was estimated from simple linear models using wheat and maize samples taken from farm fields. In wheat, environment effects accounted for 48% of the variation in deoxynivalenol (DON) across all fields, followed by variety (27%), and previous crop (14 to 28%). In maize, hybrid accounted for 25% of the variation of either DON or fumonisin, followed by environment (12%), and when combined 42% of the variability was accounted for. The robust site-specific, DON forecast model accounted for up to 80% of the variation in DON, and has been used commercially for 5 years in Canada. Forecasting DON and fumonisins in maize is more difficult, because of its greater exposure to infection, the role of wounding in infection, the more important role of hybrid susceptibility, and the vast array of uncharacterized hybrids available in the marketplace. Nevertheless, using data collected from controlled experiments conducted in Argentina and the Philippines, a model was developed to predict fumonisin concentration using insect damage and weather variables, accounting for 82% of the variability of fumonisins. Using mycotoxins as a measure of disease outcome, as opposed to disease symptoms, offers a more robust prediction of mycotoxin risk, and it accounts for mycotoxin accumulation that occurs frequently in the absence of any change in Fusarium symptoms.     

Forecast of mycotoxins levels in soft wheat, durum wheat and maize before harvesting with Qualim��tre?

Some mycotoxins are produced by several Fusarium species during cultivation and are found in wheat and maize grain. Since 2000, Syngenta has organised a large field survey. Agronomic and climatic data and grain samples have been collected for mycotoxin analysis in France and Belgium. The importance of the agroclimatic factors and their interactions on the mycotoxin levels in grain has been estimated. The climate around flowering stage is the major factor for deoxynivalenol (DON) in wheat. The main agronomic criteria are residue management and the variety sensitivity to this mycotoxin. For DON, zearalenone and fumonisins in maize, the climate from flowering stage until harvest is the major factor. Then, according to each mycotoxin, the main agronomic criteria are the harvest condition (date and grain moisture), the corn borer infestation and the variety sensitivity to these mycotoxins. Over the years, the database has been used to define models to predict the mycotoxin risk before harvesting. Grain purchasers enter the required agronomic data via the Syngenta Internet site and define their grain purchasing areas. They also define the flowering period for wheat and corn borer infestation for maize. After calculation which integrates climatic data, the purchasers receive reports with forecasts of mycotoxin levels. Prediction is based on different agro-climatic statistical models specifically configured according to the different regions of production in France and Belgium. This approach is called Qualimètre^? and was the first service in France and Belgium to forecast the grain mycotoxin level for wheat in 2004 and maize in 2006.     

Forecast of mycotoxins levels in soft wheat, durum wheat and maize before harvesting with Qualimètre?

Some mycotoxins are produced by several Fusarium species during cultivation and are found in wheat and maize grain. Since 2000, Syngenta has organised a large field survey. Agronomic and climatic data and grain samples have been collected for mycotoxin analysis in France and Belgium. The importance of the agroclimatic factors and their interactions on the mycotoxin levels in grain has been estimated. The climate around flowering stage is the major factor for deoxynivalenol (DON) in wheat. The main agronomic criteria are residue management and the variety sensitivity to this mycotoxin. For DON, zearalenone and fumonisins in maize, the climate from flowering stage until harvest is the major factor. Then, according to each mycotoxin, the main agronomic criteria are the harvest condition (date and grain moisture), the corn borer infestation and the variety sensitivity to these mycotoxins. Over the years, the database has been used to define models to predict the mycotoxin risk before harvesting. Grain purchasers enter the required agronomic data via the Syngenta Internet site and define their grain purchasing areas. They also define the flowering period for wheat and corn borer infestation for maize. After calculation which integrates climatic data, the purchasers receive reports with forecasts of mycotoxin levels. Prediction is based on different agro-climatic statistical models specifically configured according to the different regions of production in France and Belgium. This approach is called Qualimètre^? and was the first service in France and Belgium to forecast the grain mycotoxin level for wheat in 2004 and maize in 2006.     

A Dutch field survey on fungal infection and mycotoxin concentrations in maize

Mycotoxins are secondary metabolites produced by fungi that can cause adverse health effects. Due to climate change, temperatures are expected to rise and changes in rainfall patterns are foreseen. These developments may increase fungal occurrence and mycotoxin concentrations in maize. It is therefore useful to monitor mycotoxin levels in maize and record the accompanying agronomic factors and weather parameters. This paper describes a field survey in the Netherlands in which information on soil, cultivar, green manure, tillage as well as sowing, emergence, flowering and harvest dates of silage maize were collected from 148 growers. A small number of these growers (42 in total) were visited to collect maize samples revealing that 50% of the samples were contaminated with Fusarium species and mycotoxins were detected in 25% of the samples. The Fusarium species that was most commonly found was F. crookwellense followed by F. graminearum, F. culmorum, F. sporotrichiodes and F. equiseti. In total 31 mycotoxins were analysed. The predominant mycotoxins present were (sum of 3 and 15)-acetyl-DON and nivalenol; other mycotoxins found were alternariol, beauvericin, deoxynivalenol, diacetoxyscirpenol, moniliformin and zearalenone. Nivalenol was present in concentrations up to 1670?μg?kg(-1) and acetylated DON was usually present at higher concentrations than DON. Statistical analysis of the current data showed no correlation between mycotoxins present and agronomic factors recorded. Field studies as described in this paper are useful and need to be continued in the future in order to observe trends in mycotoxin occurrence.     

Climate change impacts on natural toxins in food production systems, exemplified by deoxynivalenol in wheat and diarrhetic shellfish toxins

Climate change is expected to affect food and feed safety, including the occurrence of natural toxins in primary crop and seafood production; however, to date, quantitative estimates are scarce. This study aimed to estimate the impact of climate change effects on mycotoxin contamination of cereal grains cultivated in the terrestrial area of north west Europe, and on the frequency of harmful algal blooms and contamination of shellfish with marine biotoxins in the North Sea coastal zone. The study focused on contamination of wheat with deoxynivalenol, and on abundance of Dinophysis spp. and the possible relationship with diarrhetic shellfish toxins. The study used currently available data and models. Global and regional climate models were combined with models of crop phenology, mycotoxin prediction models, hydrodynamic models and ecological models, with the output of one model being used as input for the other. In addition, statistical data analyses using existing national datasets from the study area were performed to obtain information on the relationships between Dinophysis spp. cell counts and contamination of shellfish with diarrhetic shellfish toxins as well as on frequency of cereal cropping. In this paper, a summary of the study is presented, and overall conclusions and recommendations are given. Climate change projections for the years 2031-2050 were used as the starting point of the analyses relative to a preceding 20-year baseline period from which the climate change signal was calculated. Results showed that, in general, climate change effects lead to advanced flowering and harvest of wheat, and increased risk of contamination of wheat with deoxynivalenol. Blooms of dinoflagellates were estimated to occur more often. If the group of Dinophysis spp. behaves similarly to other flagellates in the future then frequency of harmful algal blooms of Dinophysis spp. may also increase, but consequences for contamination of shellfish with diarrhetic shellfish toxins are uncertain. Climate change will also have indirect effects on toxin contamination, which may be equally important. For example, the frequency of cropping of wheat and maize in north Europe was projected to increase under climate change, which will also increase the risk of contamination of the grains with deoxynivalenol. Risk managers are encouraged to consider the entire range of the predictions of climate change effects on food safety hazards, rather than median or average values only. Furthermore, it is recommended to closely monitor levels of mycotoxins and marine biotoxins in the future, in particular related to risky situations associated with favourable climatic conditions for toxin producing organisms. In particular, it is important to pay attention to the continuity of collecting the right data, and the availability and accessibility of databases. On a European level, it is important to stress the need for harmonisation of terminology and data collection.     

粮食中脱氧雪腐镰刀菌烯醇风险预警研究进展

脱氧雪腐镰刀菌烯醇是小麦和玉米等粮食中常见的真菌毒素,受污染的粮食会严重影响人和动物健康,控制粮食产前镰刀菌感染和脱氧雪腐镰刀菌烯醇的积累是保障粮油食品安全的重要环节。当前,世界各国都十分重视粮食真菌毒素污染风险预警工作,粮食产前脱氧雪腐镰刀菌烯醇的污染预警研究近年来发展迅速,在脱氧雪腐镰刀菌烯醇积累的田间影响因素研究和建立产前风险预警模型中,都取得了一定进展。本文综述了脱氧雪腐镰刀菌烯醇风险预警的最新研究成果,旨在总结和整合现有的研究方法和成果,为开展我国粮食真菌毒素早期预警提供参考。     

Co-occurrence and distribution of deoxynivalenol,nivalenol and zearalenone in wheat from Brazil

Fusarium mycotoxins deoxynivalenol (DON), nivalenol (NIV) and zearalenone (ZEN) were investigated in wheat from the 2009 and 2010 crop years. Samples (n = 745) from commercial fields were collected in four wheat producing regions (WPR) which differed in weather conditions. Analyses were performed using HPLC-DAD. Contamination with ZEN, DON and NIV occurred in 56, 86 and 50%, respectively. Also, mean concentrations were different: DON = 1046 µg kg^?1, NIV < 100 µg kg^?1 and ZEN = 82 µg kg^?1. Co-occurrence of ZEN, DON and NIV was observed in 74% of the samples from 2009 and in 12% from 2010. Wet/cold region WPR I had the highest mycotoxin concentration. Wet/moderately hot region WPR II had the lowest mycotoxin levels. Furthermore, the mean concentration of each mycotoxin was higher in samples from 2009 as compared with those from 2010. Precipitation during flowering or harvest periods may explain these results.     

Impact of durum wheat milling on deoxynivalenol distribution in the outcoming fractions

The milling behaviour of two naturally infected samples of durum wheat grain with contrasting levels of mycotoxins was studied. Although the two samples showed a similar milling behaviour, an increase of ～20% in deoxynivalenol (DON) levels was found in semolina from the sample containing the higher level of mycotoxin. However, even if the highest concentration of DON was found in fractions originating from the grain outer layers, the mycotoxin contamination in semolina and flours were not related to the amount of two compounds (ash or phytic acid) used to monitor these external tissues. The presence of the trichothecene-producing fungi in the inner-most semolina fraction was also shown using specific DNA primers and PCR amplification. Comparison of DON concentrations in the feed stock and corresponding output at each milling step or grinding of semolina fractions followed by sizing showed that concentration of mycotoxin occurs in the finest particles at the first processing steps. Therefore, DON contamination of milling fractions is not simply due to the presence of peripheral grain tissues.     

Selection of climate change scenario data for impact modelling

Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.     

Mycotoxin contamination of cereal grain commodities in relation to climate in North West Europe

This study aimed to investigate mycotoxin contamination of cereal grain commodities for feed and food production in North Western Europe during the last two decades, including trends over time and co-occurrence between toxins, and to assess possible effects of climate on the presence of mycotoxins. For these aims, analytical results related to mycotoxin contamination of cereal grain commodities, collected in the course of national monitoring programmes in Finland, Sweden, Norway and the Netherlands during a 20-year period, were gathered. Historical observational weather data, including daily relative humidity, rainfall and temperature, were obtained from each of these four countries. In total 6382 records, referring to individual sample results for mycotoxin concentrations (one or more toxins) in cereal grains were available. Most records referred to wheat, barley, maize and oats. The most frequently analysed mycotoxins were deoxynivalenol, 3-acetyl-deoxynivalenol, nivalenol, T-2 toxin, HT-2 toxin and zearalenone. Deoxynivalenol had the highest overall incidence of 46%, and was mainly found in wheat, maize and oats. Mycotoxins that showed co-occurrence were: deoxynivalenol and 3-acetyl-deoxynivalenol in oats; deoxynivalenol and zearalenone in maize and wheat; and T-2 toxin and HT-2 toxin in oats. The presence of both deoxynivalenol and zearalenone in wheat increased with higher temperatures, relative humidity and rainfall during cultivation, but the presence of nivalenol was negatively associated with most of these climatic factors. The same holds for both nivalenol and deoxynivalenol in oats. This implies that climatic conditions that are conducive for one toxin may have a decreasing effect on the other. The presence of HT-2 toxin in oats showed a slight decreasing trends over time, but significant trends for other toxins showed an increasing presence during the last two decades. It is therefore useful to continue monitoring of mycotoxins. Obtained results can be used for development of predictive models for presence of mycotoxins in cereal grains.     

Estimating deoxynivalenol contents of wheat samples containing different levels of Fusarium-damaged kernels by diffuse reflectance spectrometry and partial least square regression

Fusarium head blight is a fungal disease causing yield losses and mycotoxin contamination in wheat and other cereals. Wheat kernels (cultivar Ritmo) were sampled in 2001, 2002, 2003, and 2006 and Fusarium-damaged kernels were separated from sound grain based on visual assessment. Subsequently, grain lots containing 0, 20, 40, 60, 80, and 100% of damaged kernels were compiled. Each lot was split and the spectrometric reflectance (wavelengths 350-2500 nm) was measured using subgroup one, while the concentration of the mycotoxin deoxynivalenol (DON) was determined by high-performance liquid chromatography in subgroup two. DON concentrations in batches classified as sound were not significantly different from 0. Estimating DON contents from the percentage of Fusarium-damaged kernels was impeded by vast variability, resulting in a coefficient of determination of 0.49. Using spectrometric data subjected to partial least square regression allowed estimating DON contents with higher accuracy, in particular at elevated percentages of damaged kernels. The coefficient of determination was 0.84 for the relationship between DON contents estimated based on spectrometric data and the DON contents measured. The intercept of a regression line fitted through a plot of estimated versus measured DON contents was 0.89 ± 3.61 mg/kg. Since intercept + standard error was larger than the actual legal limit (1.25 mg DON per kg dry grain in the European Union), the spectrometric procedure was still not precise enough to allow a reliable separation of grain samples with DON contents below 1.25 mg/kg from samples with DON contents above the limit. However, spectrometric data also allowed estimating the DON content of the average damaged kernel within a given lot composed of sound and damaged kernels, which is probably the reason for the reduction of the fraction of unexplained variance by 35% compared to the visual approach and illustrates that spectrometric approaches can make a contribution to reducing DON contents of wheat grain.     

Further mycotoxin effects from climate change

Climate change will affect mycotoxins in food. The 2007 Intergovernmental Panel on Climate Change report is reinterpreted herein to account for what may occur with mycotoxins. Warmer weather, heat waves, greater precipitation and drought will have various impacts, depending on which regions of the world and mycotoxin systems are considered. The humidity issues are more complex as some areas will experience drought and others greater precipitation: in vivo data on the effects of moisture on mycotoxins in crops are more ambiguous than those for temperature. In vitro data on fungal growth and mycotoxin production may not relate directly to the situation in the field or post harvest, but are useful for base-line assumptions. The effects of climate in various regions of the world, i.e. Africa, Europe, Asia, Latin America and North America are considered in terms of mycotoxin contamination. Crops introduced to exploit altered climate may be subject to fewer mycotoxin producing fungi (the “Parasites Lost” phenomenon). Increased mycotoxins and UV radiation may cause fungi to mutate on crops and produce different mycotoxins. Whereas there is relevant information on aflatoxins, deoxynivalenol, and ochratoxin A, more mycotoxins require to be considered: Data on patulin are missing. The current paper considers uniquely ergot alkaloids. Amelioration strategies are provided. There is considerable urgency in the need to address these issues.     

Occurrence and risk assessment of population exposed to deoxynivalenol in foods derived from wheat flour in Brazil

Deoxynivalenol (DON) is the most important of the trichothecenes in terms of amounts and occurrence in wheat. This compound was shown to be associated with a glomerulonephropathy involving an increase of immunoglobulin A in humans. This study assessed the occurrence of DON in wheat flour and the exposure of Brazilian teenagers, adults and elderly to this mycotoxin due to intake of wheat flour-based products. DON extraction in wheat flour was carried out by solid phase extraction and the quantification was performed by ultra-high proficiency liquid chromatography with diode-array detection. A total of 77.9% of all samples were positive for DON, with concentrations ranging from 73.50 to 2794.63 µg kg^?1. The intake was calculated for the average and 90th percentile of the contamination levels of DON in foods based-wheat for teenagers, adults and elderly in Brazil, and compared with the provisional maximum tolerable daily intakes (PMTDI). Females of all age groups were exposed to DON at higher levels when compared to males in regard of consumption of breads and pastas. Teenagers were the main consumers of foods derived from wheat flour, with maximum probable daily intakes of 1.28 and 1.20 µg kg^?1 b.w. day^?1 for females and males, respectively. This population is at an increased risk of exposure to DON due to consumption of wheat flour-based foods in Brazil.     

Determination of Deoxynivalenol and Nivalenol in Wheat by Ultra-Performance Liquid Chromatography/Photodiode-Array Detector and Immunoaffinity Column Cleanup

An ultra-performance liquid chromatography (UPLC®) method has been developed for the simultaneous determination of deoxynivalenol (DON) and nivalenol (NIV) in wheat. Ground sample was extracted with water and the filtered extract was cleaned up through an immunoaffinity column containing a monoclonal antibody specific for DON and NIV. Toxins were separated and quantified by UPLC® with photodiode-array detector (λ?=?220 nm) in less than 3 min. Mean recoveries from blank wheat samples spiked with DON and NIV at levels of 100–2,000 μg/kg (each toxin) ranged from 85 to 95 % for DON and from 81 to 88 % for NIV, with relative standard deviations less than 7 %. Similar recoveries were observed from spiked samples when methanol/water (80:20, v/v) was used as extraction solvent. However, by using a wheat sample naturally contaminated with DON and NIV, the one-way analysis of variance (Student–Newman–Keuls test) between different extraction solvents and modes showed that water extraction provided a significant increase (P?<?0.001) in toxin concentrations (mean values of six replicate analyses) with respect to methanol/water (80:20, v/v). No significant difference was observed between shaking (60 min) and blending (3 min). The limit of detection (LOD) of the method was 30 μg/kg for DON and 20 μg/kg for NIV (signal-to-noise ratio 3:1). The immunoaffinity columns showed saturation of DON/NIV binding sites at levels higher than 2,000 ng in blank wheat extracts spiked with the corresponding amount of mycotoxin, as single mycotoxin or sum of DON and NIV. The range of applicability of the method was from LOD to 4,000 μg/kg, as single mycotoxin or sum of DON and NIV in wheat. The analyses of 20 naturally contaminated wheat samples showed DON contamination in all analyzed samples at level ranging from 30 to 2,700 μg/kg. NIV was detected in two samples at negligible toxin levels (up to 46 μg/kg). This is the first UPLC® method using immunoaffinity column cleanup for the simultaneous and sensitive determination of DON and NIV in wheat.     

Impact of agronomic factors on fusarium mycotoxins in harvested wheat

ABSTRACT

The aim of this study was to model fusarium mycotoxins against agronomic factors in order to identify those that have the greatest impact on mycotoxin levels in harvested wheat. To achieve this, fusarium mycotoxins levels were monitored, and associated agronomic data collected, in approximately 150 English wheat fields/year between 2006 and 2013. Results showed large seasonal variation in fusarium mycotoxin levels, with high levels in 2008 (13% and 29% exceeding legal limit for unprocessed soft wheat intended for human consumption for deoxynivalenol (DON) and zearalenone (ZON), respectively) and 2012 (10% and 15% exceeding legal limit for unprocessed soft wheat intended for human consumption for DON and ZON, respectively) and low levels in 2006 and 2011 (no samples exceeding legal limits for unprocessed soft wheat intended for human consumption for DON or ZON). Analysis of agronomic factors identified previous crop, cultivation and variety as the greatest risk factors. The greatest risk of mycotoxin development in grain was following maize as a previous crop and minimum tillage. The combined effect of these factors gave respective average DON and ZON levels 20 and 14 times higher than other previous crop and cultivation combinations. A newly quantified risk factor was harvest date. A 1-month delay in harvest resulted in a 10 and 25 times greater mean DON and ZON concentration, respectively, when compared to crops harvested around the long-term regional average harvest date. These results highlight the highly seasonal variation in fusarium mycotoxins in wheat and the agronomic factors that should be avoided to minimise fusarium mycotoxin levels in harvested wheat.     

2019年饲料原料霉菌毒素污染状况调查

目的 调查分析2019年饲料原料霉菌毒素污染状况。方法 采用胶体金免疫层析法或上转发光免疫分析(up-conversion immunoassays, UPT)法对安佑集团各分子公司所采购的大宗饲料原料中呕吐毒素、玉米赤霉烯酮和黄曲霉毒素B1含量进行快速检测, 2019年度共检测饲料原料样品20918份。结果 对比安佑集团企业标准, 2019年饲料原料霉菌毒素污染总超标率为3.2%。饲料原料霉菌毒素污染整体情况由重转轻, 上半年污染较重主要是由于麸皮及次粉霉菌毒素污染超标所致, 下半年霉菌毒素污染程度整体较轻, 但9月玉米和玉米干酒糟及其可溶物(distillers dried grains with soluble, DDGS)的玉米赤霉烯酮(zearalenone, ZEN)污染情况较重, 其中DDGS达重度污染; 从产地来源看, 2019年全国各产地麸皮和次粉呕吐毒素(vomitoxin, DON)污染较重; 河南产地米糠黄曲霉毒素B1(aflatoxins B1, AFB1)及四川产地米糠ZEN达重度污染; 山东、江苏、云南、安徽产地玉米AFB1及安徽产地玉米DON达重度污染; 且饲料原料中的霉菌毒素并非单一存在, 多数情况下是多种毒素共存。结论 与2018年饲料原料霉菌毒素污染调查数据(未公开发表)相比, 2019年原料污染程度较轻。     

Limiting mycotoxins in stored wheat

The quality of harvested wheat grain can deteriorate markedly during the post-harvest management stages. Biotic factors, such as grain type and ripeness, coupled with the prevailing abiotic factors, such as water content and temperature, and also preservative concentration will influence the safe storage life and the level of contamination with mycotoxins. These mycotoxins include deoxynivalenol (DON) produced pre-harvest and zearalenone (ZEA) produced post-harvest by Fusarium graminearum and Fusarium poae, respectively, ochratoxin (OTA) produced by Penicillium verrucosum post-harvest in cool damp northern European climates, and perhaps T-2 and HT-2 toxins produced by Fusarium langsethiae. This review presents recent data on the relationship between dry matter losses caused by F. graminearum under different environmental regimes (water activities, temperatures) and the level of contamination with DON. This is important as poor post-harvest drying and storage management may exacerbate DON contamination already present pre-harvest. It is thus critical to relate the environmental factors in stored wheat grain during storage, especially of intergranular relative humidity (RH) and temperature, to safe storage periods without spoilage or risk from increased DON contamination. The growth/no growth and DON/no DON (F. graminearum) and OTA/no toxin production (P. verrucosum) have been used to build a model with a simple interface to link temperature and RH values to the potential risk level which may allow growth or toxin production. This paper also considers the use of modified atmospheres, preservatives and biocontrol to minimise DON and OTA in moist wheat grain. These approaches together with clear monitoring criteria and hygiene could contribute to better post-harvest management of stored temperate cereals and ensure that mycotoxin contamination is minimised during this key phase in the food/feed chain.     

Effects of Fusarium toxin-contaminated wheat and feed intake level on the biotransformation and carry-over of deoxynivalenol in dairy cows

An experiment was carried out to examine the effects of feeding Fusarium toxin-contaminated wheat (8.21 mg deoxynivalenol (DON) and 0.09 mg zearalenone (ZON) per kg dry matter) at different feed intake levels on the biotransformation and carry-over of DON in dairy cows. For this purpose, 14 ruminal and duodenal fistulated dairy cows were fed a diet containing 60% concentrate with a wheat portion of 55% (Fusarium toxin-contaminated wheat (mycotoxin period) or control wheat (control period)) and the ration was completed with maize- and grass silage (50 : 50) on a dry matter basis. Daily DON intakes ranged from 16.6 to 75.6 mg in the mycotoxin period at dry matter intakes of 5.6-20.5 kg. DON was almost completely biotransformed to de-epoxy DON (94-99%) independent of the DON/feed intake, and the flow of DON and de-epoxy DON at the duodenum related to DON intake ranged from 12 to 77% when the Fusarium toxin-contaminated wheat was fed. In the serum samples, de-epoxy DON was detected in the range of 4-28 ng ml^-1 in the mycotoxin period, while concentrations of DON were all below the detection limit. The daily excretion of DON and de-epoxy DON in the milk of cows fed the contaminated wheat varied between 1 and 10 µg and between 14 and 104 µg, respectively. The total carry-over rates as the ratio between the daily excretion of DON and de-epoxy DON into milk and DON intake were in the ranges of 0.0001-0.0002 and 0.0004-0.0024, respectively. Total carry-over rates of DON as DON and de-epoxy DON into the milk increased significantly with increasing milk yield. In the urine samples, de-epoxy DON was the predominant substance as compared with DON with a portion of the total DON plus de-epoxy DON concentration to 96% when the Fusarium toxin-contaminated wheat was fed, whereas the total residues of DON plus de-epoxy DON in faeces ranged between 2 and 18% of DON intake in the mycotoxin period. The degree of glucuronidation of de-epoxy DON was found to be approximately 100% in serum. From 33 to 80% of DON and from 73 to 92% of de-epoxy DON, and from 21 to 92% of DON and from 86 to 100% of de-epoxy DON were glucuronidated in the milk and urine, respectively. It is concluded that DON is very rapidly biotransformed to de-epoxy DON in the rumen and only negligible amounts of DON and de-epoxy DON were transmitted into the milk within the range of 5.6-20.5 kg day^-1 dry matter intake and milk yields (fat corrected milk) between 10 and 42 kg day^-1.