1. Introduction
France is the second largest producer of maize in Europe, with a harvest of 13 million tonnes from an area of 1.5 million hectares in 2020 [
1]. Mycotoxins, produced by fungi, can commonly contaminate maize, before harvest, but also during grain storage. Deoxynivalenol (DON) is the most widespread trichothecene mycotoxin, a group of mycotoxins frequently found in food and feed, and is one of the most important mycotoxins affecting the sanitary quality of maize in the European Union (EU) [
2]. In France, DON is produced principally by
Fusarium graminearum, from the genus
Gibberella. DON, also known as vomitoxin, may have strong emetic effects if consumed in high quantities [
3], and it also decreases grain yield [
4]. Its presence in maize is, therefore, a major health and safety concern [
3,
5]. Similar to many other countries worldwide, the EU has imposed regulations for the levels of DON permissible in food, based on the health risk associated with DON consumption (Commission Regulation 1126/2007). The maximum permissible level of DON in unprocessed maize intended for human consumption is currently 1750 µg/kg. As regards feed, Commission Recommendation 2006/576/EC on the presence mycotoxins in products intended for animal feed recommends a guidance value of 8000 µg/kg for cereals, including maize. Advances in knowledge and technology have enabled producers and processors to improve maize production, treatment and storage methods, to decrease the likelihood of mycotoxins exceeding regulatory thresholds in their produce [
6,
7,
8,
9]. Plant breeding has been touted as the safest and most effective way to reduce DON contamination in maize crops [
10,
11,
12]. Until now, no maize genotypes highly resistant to infection with
F. graminearum or to DON contamination have been produced yet [
11]. Moreover, France has banned the cultivation of genetically modified organisms (GMOs) on its territory [
13]. In this context, there is a need for more effective management strategies to prevent contamination with this mycotoxin. In particular, preharvest strategies could be used to prevent, or at least limit, DON contamination in the field [
14]. Such approaches require the identification of risk factors influencing contamination and the production of DON by
F. graminearum in the field, which can then be targeted by maize producers and processors.
Fusarium graminearum infection and growth, and DON production, are dependent on favorable agronomic conditions. These include kernel damage due to borer insects, related to higher DON accumulation [
15,
16]. The wounds created by insects provide a route of entry for the fungus, distributing fungal propagules as they feed and proliferate, and for microconidia or mycelia already present on the ear tissues [
17]. In North America and Europe, kernel infection, closely correlated with insect injury, appears to be a major infection pathway [
18,
19,
20]. Harvest date has also been highlighted as a risk factor for DON contamination. Experiments in Europe and in New Zealand have shown that the risk of DON contamination tends to increase with later harvest dates [
21,
22,
23]. This may reflect the longer time period available for
F. graminearum to grow and produce toxins [
23]. A late harvest may also shift the susceptible stages to more favorable climatic periods for
F. graminearum growth, such as late rains, which provide moisture, favoring fungal development [
24]. The presence of large amounts of residues from previous crops, such as maize stalks and grains, is considered to constitute a major source of inoculum for
F. graminearum [
25]. The fungus can survive as a saprophyte on the residues of previous crops for two or more years [
26]. In this context, leaving unaltered infected residues on the surface can increase fungal survival. Any practices resulting in the removal, destruction or burial of infected residues, such as crushing and ploughing, is likely to reduce the amount of inoculum [
23,
27,
28,
29]. The management of these residues, mostly through soil tillage (ploughing), is therefore a key element of the cropping practices for decreasing the density of infected residues on the soil surface, making it possible to decrease (1) inoculum production, (2) the number of spores available for dispersal and (3) dispersal itself [
30]. These three agronomic practices (removal, destruction and burial of infected residues) create unfavorable conditions for the growth and development of
F. graminearum, and for DON production. A better understanding of their particular and cumulative impacts would make it possible to adapt agricultural management in the field [
22,
30]. In addition, climatic factors can create favorable conditions for fungal growth and mycotoxin production at particular times in the plant development cycle. It is, therefore, necessary to identify high-risk climatic sequences to adapt the preventive strategy in the field.
Fusarium graminearum infection and growth and DON production result from the complex interaction of several climatic factors at key periods of the maize development cycle.
F. graminearum first forms perithecia (fruiting bodies) on the residue. These structures can develop over a wide range of temperatures (5–30 °C) [
31]. They then forcibly discharge ascospores into the air [
10], this process having an optimal temperature of 16 °C [
32,
33]. Finally, the sporulation, germination and growth of
F. graminearum are optimal at 24–26 °C [
10,
34], whereas DON production is optimal between 28 and 30 °C [
35].
F. graminearum infects maize kernels principally via the silks, which makes flowering a sensitive period for plant infection [
36]. Wounds on the plant, such as those created by borers, can act as points of entry for the fungus [
20], leading to contamination during phenological stages other than flowering. Climatic conditions during flowering, including humidity levels in particular, therefore play an important role in maize infection [
31,
37]. In Serbia, following a period of extremely rainy weather, almost 50% of the samples analyzed were contaminated with DON at concentrations exceeding 1750 µg/kg [
38]. Indeed, rain plays an important role in the dispersal of the fungus: spores are splash-dispersed during rainfall events, enabling them to reach plant spikes and spread over the canopy [
39]. DON production follows the same trend as fungal growth, increasing during a cool and wet growing season [
40], however, its dependence on weather conditions during the final maize ripening period is different, particularly as concerns the occurrence of rain [
41]. Ripening is, therefore, also a very sensitive period for contamination and fungal development. Combination of favorable agronomic and climatic conditions can create a prosperous environment for both fungal contamination and DON production during the sensitive periods of the plant. In the field, risky situations must be highlighted during maize development. Indeed, their early identification makes it possible to develop appropriate preventive strategies before harvesting.
DON may further accumulate during the post-harvest period, mostly during grain transportation and storage [
6], but the implementation of good practices involving drying and storage management has been shown to prevent the further production and accumulation of DON after harvest [
9]. Preharvest management in the field can reduce the amount of contaminated maize, by separating contaminated batches from clean batches at harvest. The use of a preventive strategy in the field can facilitate this approach, through targeting of the maize fields most likely to have high levels of DON concentrations. The aim of this work was, therefore, to identify easy-to-target combinations of agronomic and climatic risk factors promoting high DON content in maize, possibly exceeding regulatory thresholds, which could then be used in the development of preharvest management tools for use in the field.
3. Discussion
We identified and evaluated agronomic and climatic risk factors for DON contamination in the field with a 15-year database containing data from 2032 agricultural farm fields collected across all the French maize-growing regions. Such studies have been limited to date because preharvest strategies in maize fields mostly involve residue and pest management, fungicide application and the development of resistant hybrids [
42]. Pest management was not included in the study due to the lack of information provided by farmers. In France, there is no Fusarium fungicide treatment on maize during cultivation for economic reasons. Most strategies for reducing DON risk in the field are based on the development of plants resistant to
F. graminearum contamination and DON production [
12,
43]. In France, a varietal classification for DON susceptibility exists for maize, but the rate of variety turnover is very high in Europe, including France. Thus, many maize varieties are not evaluated for this criterion, which was therefore difficult to incorporate into our analysis without losing too many samples. GMOs are banned in France and cannot, therefore, be used as a tool for preventing DON contamination [
13]. However, preventive measures that can be applied before and during the growth of the crop in the field are the first and foremost crucial step towards an effective integrated strategy for DON risk [
14,
44]. In this context, we provide a tool for the prevention of DON contamination based on the agronomic and climatic conditions encountered in French maize-growing areas (summarized in
Figure 8). Each situation is associated with a DON risk class, from very low to critical.
We identified the presence of borers, residue management and sowing and harvest dates as agronomic factors associated with DON contamination. Several studies have already evaluated them as risk factors for preharvest DON contamination [
15,
16,
21,
22,
27,
28,
30]. In particular, residue management, harvest dates and the presence of borers were included in a previous prevention matrix created by Arvalis-Institut du végétal in 2007 [
24]. Some preharvest strategies have already been proposed, based on the use of agronomic practices related to lower DON contamination, such as the use of an appropriate selection of maize hybrids, appropriate residue management and avoiding late sowing and harvest dates, for example [
22,
30,
41,
45]. All of these proposals were developed on the basis of field experiments. In our study, we evaluated these factors in real production conditions, at a nationwide scale. Only three agronomic practices were identified as significantly associated with the risk of contamination: the presence of borers, sowing and harvest dates. Given the strong correlation between these last two variables, we decided to choose only the harvest date, most cited in the literature, to avoid complicating our prevention tool. In our study, residue management slightly increased, but not significantly, DON risk. The small number of plots with residue management considered as “inadequate” may not be large enough (20% of the data) to observe statistical differences. These agronomic risk factors explain a very small part (2%) of the variability of DON data around its average observed over 15 years at the national scale in France, compared to climatic conditions (11%). However, the part of the variability explained by all the agronomic factors does not prejudge the significance of their relationship with the DON content.
The climate is often unpredictable and difficult to modulate as a prevention tool. However, three critical periods before, during and at the end of the maize growing season favoring
F. graminearum germination, infection, growth and DON contamination were identified and studied in detail: pre-sowing, flowering and kernel drying. Temperature influences the development of
F. graminearum perithecia on crop residues [
31]. Perithecia developed at temperatures between 12 and 28 °C, and maturation occurred only under warm conditions, around 16, 20 and 24 °C [
31]. In France, March corresponds to the month before sowing. Warmer monthly conditions may create favorable conditions for an early fungus germination without plant hosts to infect. The rate of available inoculum potential can then be lowered for subsequent contaminations. High level of humidity increase
F. graminearum infection rate, especially during the sensitive period of flowering corresponding to July in France [
37,
38]. This ambient humidity may facilitate post-contamination fungal growth by creating a favorable environment [
46], for example, during the post-flowering period corresponding to August in France. Humidity may determine the ability of the fungus to grow after contamination and, consequently, also its ability to produce DON.
F. graminearum grows best at temperatures between 24 and 26 °C [
10,
34], whereas
Fusarium verticillioides continues to grow at temperatures above 28 °C [
47]. A dry period with high temperatures before and during grain filling favors ear infection with
F. verticillioides and
F. temperatum, whereas the frequency of
F. graminearum is higher at lower temperatures and in humid conditions [
48]. A complex combination of competitive (
F. graminearum was outcompeted in mixed inoculations) and facilitative (infection by
F. verticillioides was facilitated by prior infection with
F. graminearum) interactions shapes the
F. graminearum–
F. verticillioides community in maize [
49]. In this context, higher temperatures in the two months immediately preceding harvesting, corresponding to the kernel drying period, may increase the levels of infection with other fungi at the expense of
Fusarium graminearum. Our findings confirm the influence of temperature and moisture conditions on DON contamination during these three key periods of the maize development cycle. We went further, by defining the thresholds above which monthly temperatures and humidity in France can be considered “hot” and “wet”, respectively. Complicated climatic variables were simplified through their transformation into more easily usable variables. Our findings confirm the climatic and agronomic risk factors identified in previous studies. However, we went further by (1) constructing simple, easy-to-use agronomic and climatic explanatory variables and (2) creating a preharvest tool for the prevention of DON contamination in the field.
The national multiyear grid ranks associations between agronomic and climatic conditions from very low to critical in terms of DON contamination risk in French maize-growing areas. Several tools have been created for estimating the risk of DON contamination in wheat, but few such tools exist for maize [
44,
50]. This may be due to the greater variability of the silking period in maize, or the strong relationship between contamination and insect damage [
44,
51]. However, in the first decade of this century, a European tool was created to help farmers, agricultural cooperatives and processors to manage the DON contamination of silage maize in the Netherlands. Asselt et al. [
51] developed a mechanistic model describing fungal infection and subsequent growth and the formation of DON in the Netherlands. Exclusively on the basis of climatic factors (temperature, rainfall, wind speed and relative humidity), the authors were able to classify the various years studied in terms of the risk of DON contamination, from a low to critical DON risk, for farm fields in the Netherlands from 2002 to 2007 [
51]. The authors confirmed the major contribution of humidity and temperature conditions during flowering and later in the growing season to fungal growth and DON contamination in maize [
51]. Temperature before sowing, humidity during post-flowering and temperature at the end of the maize development cycle provide less information about the climatic conditions than the factors included in this tool. We selected these three factors because they appeared to be the most easily understandable for use in an educational tool. Indeed, other agronomic factors, such as sowing date, and climatic factors were also found to have a significant effect on DON concentration. However, our target was to create an easy-to-use tool for farmers and agricultural cooperatives, and we therefore had to make choices about which variables to retain and which to discard. If our target had been to create a forecasting model, we would have considered a combination of all the significant agronomic and quantitative climatic factors. In our study, we made compromises to meet the expectations of the French agricultural sector. Despite the good results obtained, Asselt et al. pointed out that their tool had several limitations, including a lack of information about agricultural practices [
51]. Notably, information about rotation and tillage were absent and would need to be included in further developments of tools of this type [
51]. The authors considered insect damage to be absent due to their low abundance of borers in the Netherlands. However, this factor may need to be included in the future following increases in borer abundance due to climate change. Hooker et Schaafsma [
52], with a database over 7 years in Ontario, observed that the effect due to year (or to weather, perhaps) accounted for 12% (
p-value < 0.0001) of the variation in concentration of DON in maize, similar to the 11% for climatic conditions found in our study. By adding the hybrid factor, they created a prevention tool explaining 42% of DON variability over the 7 years. Our selection of variables accounts for 14% of the variability over the whole of France over a period of 15 years. One reason for this low percentage could be the existence of other factors not considered in our study but with a significant role, such as hybrid susceptibility [
52]. Compared to existing models, the particularities of our tool are as follows: (1) a tool created over a 15-year study at a national scale, taking into account both changes in climate and agricultural practices; (2) using easy-to-target agronomic practices for farmers; (3) qualitative climatic factors adaptable by farmers according to their plot conditions; (4) estimation of the DON risk class before harvesting to adapt possible management.
The prevention tool assigned a risk class to each farm field over 15 years at the national scale. Differences in the significance of the risk class were observed from year to year. The number of observations differed between years, with more than 100 agricultural plots observed in some years, and fewer than 30 in others. The four risk classes also differed in terms of their representativeness, with the possible overrepresentation of certain risk classes at the expense of others. The prevention tool was developed and validated with data and information from agricultural farm fields in the various French maize-growing regions. The same approach has already been used to create a similar prevention tool for fumonisins (FUMO), mycotoxins produced by
Fusarium verticillioides, in maize [
53]. As with the tool created for FUMO, climatic quantitative variables were transformed into climatic qualitative ones, to facilitate their use by farmers who can adapt them to their own climatic conditions. Indeed, farmers characterize themselves if temperatures are considered as “hot” or “normal-to-cold” and if humidity is “dry” or “wet”. Farmers and agricultural cooperatives manage the variables themselves to correspond to their own field realities, which should help to reduce regional effects. While the climatic conditions favoring
F. verticillioides growth and contamination are drought and heat, mild and humid conditions are highlighted for
F. graminearum [
10,
31,
54]. The presence of borers is related to higher DON and FUMO content, which highlights the importance of this factor for mycotoxin contamination in maize. For both tools, the association of a risk class with each combination of simplified categories of the factors considered explained between 10% and 12% of the variability observed for the two mycotoxins over the 15 years studied. This proportion decreases with the number of possible associations of risk factors (from 64 to 5, for example, for DON) due to a loss of information. The number of categories was decreased to combine similar field situations and to create an easier tool to interpret. In the two studies, although most of the plots were well-characterized over the 15-year period, some were considered to be at low-to-medium risk of FUMO or DON contamination while their mycotoxin concentrations exceeded the regulatory thresholds. One reason is probably the broader nature of the situations, based on the grouping together of different agronomic and environmental conditions into the same risk class. Our decision to decrease the number of categories had the consequence of decreasing the amount of variability explained, potentially leading to an underestimation of DON risk in some plots. As EU regulations for mycotoxins are continually tightened, the development and use of accurate tools for preventing the contamination of batches of maize grain will be essential. The good results obtained with this tool for DON, and with the previous tool for FUMO [
53], for the 15-year period studied at nationwide level in France suggest the development of a similar approach in other countries and for other mycotoxins.
One perspective of this work is the possibility of extending the use of this tool to other EU countries. However, there are already large differences in systems and environments at the national scale in France and these differences would be even larger between different European countries. Jajić et al. [
55] compared the levels of maize contamination with DON between several Eastern European countries and concluded that the observed differences were potentially related to specific agricultural factors and climatic conditions. The use of the prevention tool in a region or country other than that in which it was created would require an understanding of its regional component and adaptation of the tool to correspond to new regional realities [
50]. In that context, our DON risk grid would be difficult to apply in its current state in other European countries, but it could be modified to deal with other field realities. The development of a similar approach could be used to select appropriate agronomic practices and meteorological conditions during the plant sensitive periods. The grid could also be fortified by considering the co-contamination of maize with other mycotoxins. Indeed, different fungi can co-contaminate the same maize plant and produce different mycotoxins, such as DON (produced by
Fusarium graminearum) and fumonisins (produced by
Fusarium verticillioides). Scientific interest in the biological effects of mycotoxin mixtures is increasing. Further studies on the nature of the relationship between the two fungi, and between their mycotoxins, are required [
49,
56].
F. graminearum and
F. verticillioides can occur together and produce mycotoxins on the same plant following artificial infections, but the type of interaction may depend on weather conditions [
49,
56,
57]. In the challenging scenario of climate change, the co-occurrence of mycotoxins in maize is problematic for the creation of accurate prevention tools, as the presence of one mycotoxin may affect the production of other mycotoxins. Further studies are required to incorporate this balance between co-contaminants into the prevention tool.