Open AccessArticle

Fusarium Species Shifts in Maize Grain as a Response to Climatic Changes in Poland

Elzbieta Czembor

^1,*

Seweryn Frasiński

Monika Urbaniak

Agnieszka Waśkiewicz

Jerzy H. Czembor

and

Łukasz Stępień

Plant Breeding and Acclimatization Institute—National Research Institute, Radzikow, 05-870 Blonie, Poland

Department of Plant-Pathogen Interaction, Institute of Plant Genetics, Polish Academy of Sciences, Strzeszyńska 34, 60-479 Poznan, Poland

Department of Chemistry, Faculty of Forestry and Wood, Poznan University of Life Sciences, 60-625 Poznan, Poland

Author to whom correspondence should be addressed.

Agriculture 2024, 14(10), 1793; https://doi.org/10.3390/agriculture14101793

Submission received: 19 September 2024 / Revised: 4 October 2024 / Accepted: 10 October 2024 / Published: 12 October 2024

(This article belongs to the Special Issue Identification and Management of Fungal Plant Pathogens)

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Abstract

Maize, along with wheat and rice, is the most important crop for food security. Ear rots caused by Fusarium species are among the most important diseases of maize. The distribution of Fusarium species provides essential epidemiological information for disease management. The effect of weather conditions, climate change and geographic localization on the Fusarium population in Poland was evaluated between 2015 and 2018. Grain samples (n = 233) were collected from hybrids at 16 locations (L1–L16). The differences in altitude between locations ranged from 39 to 243 m above sea level, longitude varied between 15°55′ and 23°12′ E, and latitude spanned from 50°12′ to 54°01′ N. Isolates were identified using molecular techniques. The highest Fusarium species frequency was recorded for 2016 (30.70%) and 2017 (28.18%), and the lowest for 2018 (5.36%). F. verticillioides and F. temperatum were the most frequent. Altitude has an effect on F. vericillioides frequency: F. graminearum showed a negative correlation with both latitude and longitude. In Polish conditions, from silking to harvesting, the number of days with higher precipitation and lower temperatures is associated with an increased frequency of F. verticillioides, F. temperatum, F. graminearum and F. avenaceum. This suggests that the Fusarium presence in Poland is significantly influenced not only by climate change but also by extreme weather changes.

Keywords:

climate change; epidemiology; Fusarium species; maize ear rot; translation elongation factor tef-1α; weather conditions

1. Introduction

Maize is a plant of great economic importance around the world. It is a multi-purpose crop that gives a high yield both when grown for grain and for silage. Moreover, maize grown under Polish conditions has started to be used in the food, chemical, paper, fermentation and pharmaceutical industries. It is a raw material for the production of biofuels in connection with the Kyoto Protocol aimed at reducing greenhouse gas emissions. In recent years, the area and the harvest of maize have increased significantly both in Poland and in the world. The global maize growing area reached around 197 million ha, and the production of dry grain is estimated at 1137 Mt, being about 50% greater than that of rice or wheat (757 Mt each) [1]. Maize production is expected to increase by up to 193 Mt by 2030; global production may reach up to 1315 Mt [2].

Fusarium fungi are the most common causes of ear and kernel rot in maize. In addition, they produce mycotoxins in the kernels, which pose a serious health risk to humans and farm animals [3,4,5,6,7,8,9,10,11]. In Europe, the most common ear-rotting fungal species are: F. verticillioides (Sacc.) Nirenberg and F. graminearum Schwabe. Climate change further increases outbreak risks by altering pathogen evolution and host–pathogen interactions and by facilitating the emergence of new pathogenic strains [12,13,14,15,16,17,18].

Ongoing climate change has led to significant alterations in Fusarium species composition [14,17,18]. Currently, 23 monophyletic lineages (species complexes) have been identified, encompassing over 400 phylospecies. Fusarium classification into complexes and species differentiation primarily utilizes partial sequences of tef-1α. If possible, additional RPB2 and/or RPB1 (subunits of RNA polymerase II) sequences are combined to confirm identification. If this is not feasible, reliance on the tef1-α sequence is recommended [19]. The majority of species (approximately 75%) are grouped into six major complexes: Fusarium fujikuroi (FFSC), F. incarnatum-equiseti (FIESC), F. oxysporum (FOX), F. sambucinum (FSAMSC), F. sporotrichioides (FSP), and F. poae, F. solani, and F. tricinctum (FTSC) [20]. Fusarium verticillioides, belonging to FFSC, is confined to regions with dry conditions and temperatures of 25–30 °C. It can now survive and grow in a broader range and appears not only in dry southern parts of Europe but also is isolated in more humid climates with relative high temperatures, such as those in South America or Asia. It has also been isolated with F. proliferatum from samples collected in northern areas with temperatures lower than 25 °C [21]. F. verticillioides is one of the most prevalent and significant producers of fumonisins (FBs), with three analogs being the most prevalent, including FB1 and FB2 [7]. F. proliferatum, another member of the FFSC, can produce FBs, moniliformin (MON), fusarin C, and fusaric acid. Scauflaire (2011) distinguished F. temperatum Scaufl. and Munaut from F. subglutinans sensu lato within FFSC using the translation elongation factor gene (tef-1α) and β-tubulin (tub-2) DNA sequence analyses, mating compatibility and metabolite profiling, and described the species formally [22]. F. subglutinans and F. temperatum are capable of producing fusaproliferin (FP), MON, enniatins (ENNs), and FBs. Additionally, F. temperatum produces beauvericin (BEA) [23,24]. Notably, F. nygamai is a producer of BEA, fusaric acid, and FBs [6,25].

On the other hand, F. graminearum, a member of the FSAMSC, requires a minimum temperature of 10 °C and a water activity (aw) of at least 0.935 [3]. F. graminearum and F. culmorum are able to synthesize type B trichothecenes: nivalenol (NIV), deoxynivalenol (DON), and 3- and 15-acetyldeoxynivalenol (3-ADON and 15-ADON, respectively) [26,27,28], as well as zearalenone (ZEA). ZEA’s ability to bind to estrogen receptors amplifies its estrogenic effects on consumers [29,30].

Members of the F. sporotrichioides—F. poae complex (FSP), as well as the FIESC, exhibit the capability to produce diverse mycotoxins, such as fusarochromanone (FUSCHR), ZEN, T-2 toxin, DAS, NEO, BEA and MON. HT-2 is produced by many species, such as F. langsethiae, and can be found in concentrations higher than those of T-2 toxins in grain samples [31,32]. Species belonging to the FTSC, such as F. avenaceum, F. tricinctum, F. acuminatum and F. arthrosporoides, produce enniatins (ENN) and moniliformin (MON).

Fusarium fungi switch from a biotrophic to a necrotrophic lifestyle during infection, which makes them hemibiotrophic pathogens [4]. In mixed field inoculations, F. verticillioides inhibits F. graminearum growth, reducing deoxynivalenol levels; however, the correlation between ear rot symptoms and DON is not certain. The absence of up-to-date information encompasses critical aspects, such as regular experiments that specifically document weather conditions during silking—a pivotal stage influencing primary infection, toxin accumulation, and pre-harvest considerations [4,32,33,34]. This comprehensive approach is essential for developing robust algorithms that accurately reflect the dynamic interplay between Fusarium, host resistance, environmental factors and agronomic practices [4,34,35,36,37,38,39,40,41,42,43,44,45]. Addressing this research gap not only enhances our understanding of Fusarium epidemiology but also contributes to the development of more effective and context-specific management strategies in the field and in response to climate change. This would enable the development of uniform data platforms to monitor the frequency of individual species. An example is the platform developed in 2000–2013 for F. graminearum and F. culmorum [28].

It was observed that since 1995, the frequency of F. verticillioides has increased in most years, which is justified by the increase in average temperature from June to September when maize plants are in the reproductive stages under Polish conditions. Historically, F. subglutinans sensu lato was estimated to be the prevailing species, but from 1984, F. subglutinans frequency decreased because most isolates have been re-identified as F. temperatum [24,29,46,47,48,49,50,51].

Research conducted by Czembor [34] attempted to systematically monitor the population of Fusarium species in Poland in 2011 and 2012, taking into account weather conditions. The aim of this study was to identify potential trends in the Fusarium species population under Polish conditions between 2015 and 2018 using consistent methodologies in the context of weather conditions.

2. Materials and Methods

2.1. Maize Grain Sampling

A total of 233 grain samples were collected between 2015 and 2018 from cultivars grown in trials conducted in a system of Post-Registration Variety Testing (PRVT) carried out by the Research Centre for Cultivar Testing (COBORU) (https://www.coboru.gov.pl/index_en, accessed on 16 May 2024), using best practices appropriate to the respective area.

In total, 15 cultivars were used as plant materials, and a total of 13,104 kernels were evaluated. D grain types: semi-flint (3 genotypes; 56 samples during 2015–2018), semi-dent (4 genotypes; 51 samples) and dent (7 genotypes; 127 samples) were included. Each year, samples were collected from 6–8 genotypes (cultivars) to obtain a representative number of samples (from 43 samples in 2015 to 86 samples in 2017) (Supplementary Table S1). Based on preliminary observations, cultivars represented different levels of resistance to ear rot at high disease pressure under natural infection. Early cultivars, recommended for cultivation in the north of Poland (FAO ≤ 210; 4 genotypes: H1–H4; 66 samples), mid-early cultivars (FAO 230–260; 5 genotypes: H5–H9; 92 samples) and mid-late cultivars recommended for cultivation in the south of Poland (FAO ≥ 300; 6 genotypes: H10–H15; 76 samples) were studied.

2.2. Sampled Environments

Sampled genotypes (cultivars) were grown in different environmental and climatic conditions: central (C), central-western (CW), south-eastern (SE) and south-western (SW) parts of Poland (Figure 1).

In total, experiments were carried out in 16 localities (Figure 1, Table S2).

The altitude between locations ranged from 39 to 243 m above sea level, longitude varied between 15°55′ and 23°12′ E, and latitude spanned from 50°12′ to 54°01′ N. Field experiments were set up as a randomized complete block design. Plots were sown in three replicates at a density of 83,300 plants per hectare. For each replicate, the plot size was 16.32 m² (10.88 m × 1.50 m), with two rows, and 75 cm distance between rows, resulting in 68 plants per row. Crop rotation was properly implemented, taking into account root crops, legumes and legume-cereal mixtures as forecrops, and this ensured that it did not affect the Fusarium species. The level of pre-sowing fertilization with NPK was determined depending on the soil complex. To create a proper microclimate, experiments were bordered by four rows of cultivars, which were not evaluated. At harvest, kernels from the three replicates were pooled and thoroughly mixed. Representative grain samples of half a kilogram of each hybrid from each locality were collected and stored in a cold room at 4 °C and were made available to isolate Fusarium spp. A total of 233 grain samples were collected: 43 samples in 2015, 54 samples in 2016, 86 samples in 2017 and 50 samples in 2018.

2.3. Fusarium Species Isolation

Fifty maize kernels were selected randomly from each sample. Kernels were soaked in distilled water for 24 h in a shaker. Next, they were surface-disinfected in ethanol (15 s) and rinsed 3 times in distilled water and dried on sterile filter paper. They were placed on water agar (2% Bacto agar, Difco) in Petri dishes, supplemented with neomycin and streptomycin sulfate (100 mg/L and 200 mg/L, respectively), and incubated at 22 °C in darkness for 7–12 days. After incubation, each culture was sub-cultured using the single spore technique. Pure cultures of Fusarium spp. were grown at 22 °C (12 h photoperiod) for 10 days on SNA (to produce macroconidia of uniform size and form) and on PDA (for colony morphology assessment) [52].

2.4. Fungal Species Identification

The identification of Fusarium species isolated from maize kernels was performed using species-specific DNA markers for F. proliferatum, F. subglutinans and F. verticillioides species. Two primer pairs were used for F. temperatum identification: one previously described [53] and the second designed based on the translation elongation factor (1α) sequence: (Temp1: 5′-CACTCGAGCAATGCGCGTTTCT-3′/Temp2: 5′-CGAATTAAGGGAGAACGAGGCAT-3′).

Fusarium graminearum, F. equiseti, F. thapsinum and F. poae species were identified based on the sequence analysis of the translation elongation factor (tef-1α) gene, amplified and sequenced using the primers and procedures described previously [54]. PCRs were conducted using BioRad C-1000 thermal cyclers in a 20 μL volume. Thermo Scientific Phire II Taq DNA polymerase was used, along with SIGMA dNTPs. Amplified DNA fragments were electrophoresed in 1.5% agarose gels (AppliChem, Darmstadt, Germany) and 1× TBE buffer (SIGMA, Kawasaki, Japan). For sequencing, the amplified fragments of the tef-1α gene were purified using exonuclease I (Thermo Scientific, Waltham, MA, USA) and shrimp alkaline phosphatase (Thermo Scientific). Sequence labeling and reading were conducted using protocols validated previously with Applied Biosystems equipment [48]. The obtained sequences were analyzed using Chromas (Technelysium, Brisbane, Australia) and MEGA 4 software packages [55]. Species identification was confirmed based on a comparison to reference GenBank sequences of the respective species using the BLASTn algorithm. It is not possible to choose the “consensus sequences” for individual species, as we also sequenced genotypes to identify them. The sequences are available on request but should not be considered controversial, as we did not use them for any additional phylogenetic analyses. This was not the objective of the study.

2.5. Meteorological Data

Weather conditions (air temperature and precipitation in short-term atmospheric conditions) were monitored by the automatic weather station for all localities where the post-registration variety testing (PRVT) field trials were carried out by the Research Centre for Cultivar Testing (COBORU) network, and grain samples were collected in 2015–2028 (Figures S1–S4). Weather stations were located on the experimental fields. Mean and maximum temperatures (°C) and the amount of precipitation [mm/m²] during the third quarter of 2015–2018 (June, July, August and September) were monitored (during R stages of plant development: from silking influencing primary infection until harvesting time). In addition, the number of days with a temperature below 19 °C, between 19 °C and 22 °C and above 22 °C, as well as days with precipitation, was determined for each month for every decade. A typical month was divided into 10-day periods. In a typical month, we can have 3 decades, with the remaining days not forming a complete 10-day period. Similarly, the number of days with precipitation higher than 0.0 mm/m² was counted.

The effect of climate change (over a long period of time) on Fusarium species frequency was described based on data collected by Sentinel-2 and is available on the internet platform https://esgf-data.dkrz.de/search/cordex-dkrz/ (accessed on 9 October 2024) [16]. It is important to note that climate scenarios are not projections of future climate but rather descriptions of future conditions with high probability. Climate model data used in the analysis were adjusted to local conditions as part of the CORDEX-Adjust project, including daily data for minimum, maximum and average air temperatures and precipitation. Further information on the deviation correction method can be found on the online platform http://is-enes-data.github.io/CORDEX_adjust_add.html (accessed on 9 October 2024). The dataset used in this study comprises transient model simulations spanning from 1971 to 2091. To evaluate the projected levels of changes in basic meteorological variables, time-series data of daily maximum and minimum air temperatures from a partially stored version of the EURO-CORDEX data repository were retrieved (Figures S5 and S6).

2.6. Statistical Analysis

Average occurrences of each Fusarium species in maize grain samples were compared using fixed analysis of variance. The Fisher least significant difference test was used for comparison between Fusarium frequency, years, locations and hybrid. Moreover, the minimum, maximum values, SD (p ≤ 0.05) and CV (%) were determined. Average and maximum Fusarium species frequency, individually and based on distribution locality, are visualized as box-plot charts in the main manuscript and in the form of tables in the Supplementary Materials. Statistics provided in the Supplementary Materials describe the frequency of Fusarium species, including average, minimum, maximum, standard deviation (SD) and coefficient of variation (CV). A one-way ANOVA, followed by Fisher’s LSD post-hoc analysis (p < 0.005), was conducted to elucidate statistically significant differences in the frequency of Fusarium species isolated individually in 2015, 2016, 2017, 2018 and 2015–2018, and in sixteen localities individually in 2015, 2016, 2017, 2018 and 2015–2018. Pearson correlations between the frequencies of Fusarium species were calculated. The coexistence of Fusarium species individually and (A) geographic location, (B) meteorological data variables (number of days with temperatures: T > 22 °C, T: 19–22 °C, T < 19 °C and number of days with precipitation) during maize reproductive stages from R1, silking time, to R6, physiological maturity stage (June, July, August, September), and geographic localization data variables (latitude [(ϕ)], longitude [λ], altitude [m.pm]) was explored and visualized using principal component analysis (PCA) on the correlation matrix. The statistical analysis was performed using Statistica 13.3 software (StatSoft, Tulsa, OK, USA). Hypotheses were tested at α = 0.005.

Temperature and the total days with precipitation for each decade of June, July, August and September were individually calculated for each year and locality. The 1st, 2nd and 3rd decade represent 10-day periods for each month individually. The total frequency of Fusarium species in the sample was presented as a percentage (%) of the number of strains isolated from the number of grains assessed (n = 50 grains representing each sample).

3. Results

3.1. Weather Conditions

According to the presented temperature and precipitation data from 16 weather stations, the localities represent different climatic conditions. Significant differences were also noted for each locality between the years. On average, the warmest year was 2018 (Figures S1–S4). The coldest years were 2016 and 2017. The most days with temperature T > 22 °C were in the 3rd decade of July and in the 1st decade of August. Moreover, in 2015, the most days with a temperature T > 22 °C were in the 1st and 2nd decades in August (on average above 70% in the 1st decade and 60% in the 2nd decade). In 2018, the frequency of days with temperature T > 22 °C in the 3rd decade of July ranged from 90% (L7, L10, L13) to 40% (L14). The frequency in the 1st decade of August ranged from 80% (L1, L5, L6, L9, L10) to 50% (L14). The lowest frequency of days with precipitation greater than 0.0 mm/m² was in 2018. In the years 2015–2018, L7, located in the east of Poland at 114 m a.s.l., and L10, located in the south of Poland at 123 m a.s.l., were analyzed. The relationship with Fusarium species individually is described in the following Sections.

Climate change projection data for Poland are available on the internet platform https://esgf-data.dkrz.de/search/cordex-dkrz/ (accessed on 9 October 2024) [16]. The average annual air temperature for Poland, according to the RCP4.5 scenario for the RACMO22E model for the years 1971–2000, was 7.8 °C. However, from the perspective of 2011–2020 and 2041–2050, the average annual temperatures are projected to be 8.3 °C and 9.3 °C, respectively. This is an increase in the base period by 0.5 °C and 1.5 °C, respectively, from the perspectives of 2011–2020 and 2041–2050. If we analyze monthly precipitation in the period 2011–2020 compared to 1971–2000, June was similar (73.5 and 75.6 mm/m², respectively), July was slightly lower (88.3 and 93.6, respectively), August was much higher (98.0 and 73.6 mm/m², respectively) and September was similar (54.2 and 54.4 mm/m², respectively) (Figures S5 and S6).

3.2. Fusarium Species in Maize Sampes Collected during 2015–2018

To analyze the shifts in Fusarium species composition in maize grain under Polish conditions from 2015 to 2018, n = 233 grain samples, encompassing n = 13,104 kernels, were collected (Tables S1 and S2). Six to eight representative hybrids were evaluated annually within 12 to 16 localities, representing diverse regions of Poland (Figure 1, Table S2). In summary, during 2015–2018, the frequency of isolated Fusarium species in the grain sample was 22.28%, and individually, it ranged from 5.4% in 2015 to 30.7% in 2016 (Figure 2, Table S3).

Twelve Fusarium species were identified, belonging to the F. fujikuroi complex (FFSC), the F. sambucinum complex (FSAMSC), the F. sporotrichioides (FSR)-F. poae (FPO) complex, the F. incarnatum-equiseti (GIN) and the F. tricinctum (FTI) complex (Figure 3, Table S3).

F. verticillioides had the highest average occurrence of 11.71%, followed by F. proliferatum, F. temperatum, F. subglutinans and F. graminearum (Figure 3, Table S3). Other species were present at much lower frequencies or not detected at all, with F. tricinctum, F. equiseti and F. oxysporum having the lowest average occurrence of 0.01%.

The average frequencies of Fusarium species individually isolated in 2015, 2016, 2017 and 2018, along with their maximum occurrences and standard deviations (SDs), are provided in Figure 4A–D.

In Table S3, a one-way ANOVA followed by LSD Fisher post-hoc analysis (p < 0.005) was conducted to elucidate statistically significant differences in the frequencies of Fusarium species isolates. The ANOVA test results indicate that the differences in Fusarium incidence between species were significant in 2016 and 2017. However, the data show that the differences between species were not significant in 2015 and 2018, as indicated by the F-values and p-values for these years.

Overall frequencies of Fusarium species isolated from samples collected in sixteen localities in Poland are presented in Figure 5 and Table S5.

On average, the highest frequency of the Fusarium spp. was found in the grain samples collected in L3 (south-western region of Poland), and the lowest in the grain samples were collected in L16, L11 and L15 (Figure 5, Table S5).

Individually, the frequencies of Fusarium species isolates in samples collected from sixteen localities in 2015, 2016, 2017 and 2018 are presented in Figure 6A–D and in Tables S6–S9.

In the Supplementary Materials, a one-way ANOVA, followed by LSD Fisher post-hoc analysis, was conducted to elucidate statistically significant differences in the frequencies of Fusarium species in the localities (Tables S6–S9).

Frequencies of Fusarium species isolates in samples collected in sixteen localities and hybrid individually in Poland in 2015, 2016, 2017 and 2018 are presented in Tables S10–S13. It was found that the Fusarium population depended on the genotype and kernel type, with significant variability based on geographical origin and over the four years. For example, the H2 cultivar of the early semi-flint (SF) group (FAO ≥ 210) was evaluated each year from 2015 to 2018. The average incidence of Fusarium species was 13.20% in 2015, 24.20% in 2016, 30.20% in 2017 and 14.44% in 2018 (Tables S10–S13).

3.2.1. Fusarium fujikuori Species Complex (FFSC) Frequency

Throughout the period from 2015 to 2018, Fusarium isolates belonging to the FFSC complex emerged as the most prevalent. F. verticillioides, F. proliferatum, F. temperatum and F. subglutinans were detected (Figure 3 and Figure 4, Table S4). F. verticillioides emerged as the predominant species up to 68.00% in 2016 (Figure 3 and Figure 4, Table S4). The highest number of F. verticillioides isolates was isolated from samples collected in the south-west region of Poland (L3: avg 23.00%, max 68.00%) (Figure 5 and Figure 6, Tables S5–S13). In 2015, the average frequency of F. verticillioides was 9.17% (max 30.00%); in 2016, on average, it reached 20.56% (max 68.00%), dropping down to 12.88% in 2017 (max 52.00%) and 2.88% in 2018 (max 14.00%) (Figure 5 and Figure 6, Tables S5–S13). F. temperatum frequency was 2.39% on average (ranging from 0.00% to 20.00%). No significant differences were observed for 2015 and 2016. In 2017, the average frequency of F. temperatum was 4.49% (the highest kernel number compared to other years), ranging from 0.00% to 24.00% (Figure 5 and Figure 6, Tables S5–S13). In 2018, the average frequency of F. temperatum was 0.84%, ranging from 0.00% to 14.00%. The average F. subglutinans frequency was 0.88% and it ranged from 0.00% in 2017 to 3.07% (max 24.00%) in 2016. In 2015 and 2016, frequency differences between localities were significant (Figure 5 and Figure 6, Tables S5–S13). F. proliferatum was isolated with an average frequency of 3.31%, ranging from 0.00% to 36.00%. ANOVA showed that differences were statistically significant.

3.2.2. Fusarium sambucinum Species Complex (FSAMSC) Frequency

The frequency of F. graminearum was 2.42% (Figure 3 and Figure 4, Table S4). In samples collected from hybrid H2, the frequency ranged from 0.00% to 28.00%. In 2018, the average species frequency was 0.2%. The average frequency of F. culmorum was 0.20%. Differences between years were significant; however, between localities in 2015, 2016, 2017 and 2018, the differences were not significant (Figure 5 and Figure 6, Tables S5–S13).

3.2.3. Fusarium sporotrichioides—F. poae Species Complex (FSP) Frequency

The frequency of F. sporotrichioides isolated during 2015–2018 was 0.11%, with a range of 0.0–8.00%, and the differences between samples were not significant (Figure 3 and Figure 4, Table S4). In 2015, the average frequency was 0.33%; in 2016, it was not present; in 2017, the average frequency was 0.14%, with a range of 0.0–8.0%; and in 2018, the species was not isolated. F. poae was isolated with an average frequency of 0.27% in the range of 0.0–10.0%. The differences were statistically significant.

3.2.4. Other Fusarium Species

On average, during 2015–2018, F. tricinctum was isolated with a frequency of 0.01% and F. avenaceum with a frequency 0.64% (Figure 3 and Figure 4, Table S4). Significant differences were noticed for F. avenaceum frequencies, which were within a 0.0–14.0% range. F. equiseti was isolated in 2015, with an average frequency of 0.09% (max. 2.0%), and it was detected in two localities: L9 and L14 (Figure 5 and Figure 6, Tables S5–S13). F. oxysporum was isolated in 2015 (in L10, average 1.47%, with the range of 0.00–4.00%) and 2016, with a frequency of 0.04% within the range of 0.0–2.0% in one locality: L6 (C region of Poland).

3.3. Correlations and Associations Observed between the Frequencies of Fusarium Species,

Table 1 represents the correlation coefficients between different species of the Fusarium genus.

The values range from −1.0 to 1.0, where 1.0 indicates a perfect positive correlation, −1.0 indicates a perfect negative correlation and 0.0 indicates no correlation. A statistically significant positive correlation was observed between the presence of F. verticillioides incidence with the presence of F. subglutinans, F. temperatum, F. graminearum and F. oxysporum, and weakly with F. proliferatum (Table 1).

Moreover, a statistically significant positive correlation was observed between the presence of F. proliferatum, F. temperatum, F. sporotrichioides, F. poae and F. avenaceum. The frequency dynamics of F. temperatum, on the other hand, unveiled complex relationships. Negative correlations were identified with F. graminearum, indicating a potential antagonistic interaction. Conversely, positive correlations were observed with F. proliferatum, F. culmorum and F. avenaceum, and weakly positive with F. verticillioides, F. proliferatum and F. subglutinans, suggesting potential symbiotic relationships. The frequency of F. sporotrichioides displayed interesting correlations with F. poae, F. equiseti and F. avenaceum.

3.4. Correlations and Associations Observed between the Frequencies of Fusarium Species and Weather Conditions

PCA analyses, based on correlation coefficients, aided in interpreting the frequency of Fusarium isolates isolated from grain samples and meteorological data gathered from various regions of Poland individually for the years 2015, 2016, 2017 and 2018. The data, depicting conditions in a reduced-dimensional space, are presented individually for each year in Figure 7, Figure 8, Figure 9 and Figure 10, and a summary correlation and associations observed between Fusarium frequency, precipitations and temperatures are presented in Tables S14 and S15.

The relationship between the number of days with temperatures T > 22 °C, T: 19–22 °C and T < 19 °C and the number of days with precipitation during maize reproductive stages (from R1, silking, to R6, physiological maturity) and the presence of Fusarium is complex, which indicates that the impact is species-specific and varies throughout the growing season. When analyzing the number of days with precipitation and temperatures in the range of T: 19–22 °C in 2015, it was found that there is a strong negative association with F. equiseti and F. sporotrichioides. The number of days with temperatures exceeding T > 22 °C was negatively associated with F. subglutinans, F. verticillioides and F. proliferatum, while Fusarium temperatum frequency was positively associated. F. culmorum frequency showed a strong positive correlation with temperatures T < 19 °C. In 2015, in Locality L10 (South of Poland, Figure 1), Fusarium species were most frequent. In 2016, days with precipitation and days with temperatures T < 19 °C were negatively associated with most Fusarium species, with the exception of F. culmorum, F. poae, and F. proliferatum. Days with temperatures T > 22 °C were strongly negatively associated with F. proliferatum. In the localities L3, L1, L2 (south-west of Poland), L10 (south of Poland) and L8 (west of Poland), all Fusarium species were observed, with the exception of one of the most frequent F. proliferatum and F. poae and F. culmorum. Frequency of F. culmorum was low.

In 2017, the year had the lowest temperatures and the highest amount of precipitation (Supplementary Figure S3, which presents weather conditions for sampled localities in 2015, 2016, 2017 and 2018). Days with T < 19 °C were positively associated with F. verticillioides, while days with precipitation were negatively associated with F. temperatum, F. poae and F. proliferatum. Conversely, they correlated positively with F. graminearum. In locality L3, as in 2015 and 2016, F. proliferatum, F. temperatum and F. poae were the most frequent.

When temperatures were very high and precipitation was low, as in 2018, days with precipitation positively correlated with most Fusarium species, with the exception of F. verticillioides and F. graminearum. The most frequent Fusarium species were found in localities L3, L2 and L12. This suggests that Fusarium presence in Poland is significantly influenced not only by climate change but also by extreme weather changes.

3.5. Correlations and Associations Observed between Fusarium spp. Frequencies and Geographic Region of Poland

PCA analysis based on the correlation coefficients was used in interpreting the structure of Fusarium spp. in a reduced-dimensional space concerning the geographic regions of Poland (Figure 11, Table S16).

Overall, geographic localization plays a significant role in explaining the frequency of Fusarium species dynamics. The dynamic population of F. sporotrichioides, F. equseti, and F. avenaceum showed positive correlation with PC2 and longitude and negative associate with F. temperatum, F. proliferatum and F. subglutinans. Altitude has an effect on F. vericillioides, F. poae, F. temperatum, F. subglutinans and F. proliferatum frequency. Additionally, F. graminearum showed a positive correlation with longitude.

4. Discussion

Over the last 15 years, a significant elevation of temperature has been observed in Poland, which resulted in an increase in maize-growing area. This study provides an update of knowledge regarding the diversity of Fusarium species in maize grain under environmental conditions from 2015 to 2018. Plant health can be compromised by a wide range of environmental factors, including biotic and abiotic stresses and, specifically, plant pathogens and climate changes [56]. Agro-climatic factors affect both the development of the pathogen and host–pathogen interactions. It is possible to predict the temporal and spatial distribution of such factors and identify significant long-term trends. Global climatic changes (GCCs) impact the ecology and epidemiology of plant pathogens, increasing the infection rates, and thus leading to significant drops in crop productivity and food security [14,15,36,56,57,58].

The present study shows current trends in Fusarium population under Polish conditions observed between 2015 and 2018, in the context of plant genotype, weather conditions, climate changes and geographic localization. Twelve to sixteen localities, representing various regions of Poland—south-west, south, west, east, central, central-west, north-east and north-west—were sampled. The results were compared with Fusarium populations described since 2011–2012, when the sampled experiments were located in the same locations. At that time, eight species were isolated, belonging to the F. fujikuori (FFSC), F. sambucinum (FSAMSC), F. sporotrichioides—F. poae (FSP) and F. incarnatum—equiseti (GIN) complexes [34]. In Fusarium research, sequence-based identification has become a standard, and comparison to reference GenBank sequences of the respective species using BLASTn algorithm or Fusarium-ID v.3.0 is considered as the most current approach [21,59].

A study described by Chełkowski [48] in 1989 reported that in Poland, during that time, early maize cultivars were planted and harvested later than they are now, until October. It was observed that since 1995, due to climate change, the frequency of F. verticillioides has increased in most years, and based only on morphological identification, F. subglutinans sensu lato was estimated as the prevailing species from 1984 to 1991. Long-term climate change under Polish conditions, based on data collected by Sentinel-2 [16], helps to interpret these Fusarium species fluctuations. Monthly temperatures during the period 2011–2020, compared to 1971–2000, fluctuated, on average, below 0.5 °C. Monthly precipitation during the period 2011–2020, compared to 1971–2000, in June and July was lower than in August.

Stępień et al. [24] identified Fusarium species in pre-harvest maize using molecular methods. In a group of 42 isolates, 34 isolates were identified as F. temperatum and only 5 as F. subglutinans. Phylogenetic analysis showed that the population of F. temperatum infecting maize in Poland remained quite uniform for over 30 years.

Locatelli [60] described Fusarium species frequency for all continents, including Europe, Africa, South America (Argentina, Brazil, Peru) and China. In Poland, in 2011 and 2012, 25.24% of kernels were colonized by Fusarium species [34], and in a recent study, 22.28%. From 2015 to 2018 the highest Fusarium species frequency was recorded for 2016 (30.70%) and 2017 (28.18%) and the lowest for 2018 (5.36%). In 2015 19.59% kernels were colonized.

In 2018, the low frequency of Fusarium species corresponded to high temperatures and a lack of precipitation throughout the whole country, whereas the highest frequency in 2017 was associated with low temperatures and high precipitation. This shows that in Polish conditions, precipitation and temperatures lower than 19 °C have a more pronounced impact on Fusarium presence, and temperatures ranging 19–22 °C have a suppressing effect.

Similar to 2011 and 2012, F. verticillioides and F. temperatum were the most prevalent species in our study [34]. In the years 2015–2017, the amount of rainfall had a strong positive effect on F. temperatum frequency (as exemplified by the frequencies in 2016 and 2017). This confirms the results obtained in Belgium [22,61], by Robertson [62], in France [63], in Germany [64,65], in Spain [66] and in Switzerland [67]. Moreover, it was reported in China [68], though not confirmed by Qiu et al. [69]. In South America, it was reported by Fumero et al. [70] though not confirmed by Castañares et al. [26,27]. Detection and quantification of fumonisins from Fusarium verticillioides in maize grown in southern India were reported by Nayaka [71].

The effect of local short-term climate change was reported by Gromadzka et al. [50], who observed a significant difference in F. subglutinans and F. verticillioides frequencies in two localities sampled during 2014–2017. Samples of maize ears were collected from Greater Poland and Silesia. Samples originating from the first locality were dominated by F. subglutinans in the four years of study, while in samples collected from the locality second the frequency of F. verticillioides was significantly higher than that of F. subglutinans.

Differences were observed for F. proliferatum during 2011–2012 [34] and in the present study during 2015–2018. This study confirms the findings of Gromadzka et al. [49,50]. Based on monitored weather conditions, it is possible to conclude that F. proliferatum and F. temperatum have a positive relationship with temperatures below 19 °C from the silking to maturity stages.

In our study, the incidence of F. graminearum corresponds to the species presence in 2011 and 2012 [34]. There are many reports stating that F. graminearum frequency varies significantly among years and locations in many geographical areas [7,23,28,64,65,66,67,68,72].

5. Conclusions

The present study shows that in Poland, warmer temperatures have facilitated the spread of Fusarium to higher latitudes and previously unaffected regions. This expansion poses new challenges for agricultural regions previously considered less susceptible to Fusarium-related issues. Areas in northern latitudes are expected to experience the most significant shifts in extreme temperature conditions due to climate change.

Based on the present study, the most important factors are short-term weather anomalies. Variations in temperature and precipitation regimes have directly influenced the frequency of Fusarium species outbreaks. Increased temperatures may be linked to elevated Fusarium species activity, as well as the shifts in precipitation patterns.

Continued monitoring of Fusarium populations is crucial for understanding the shifts and emerging trends. Furthermore, studies are needed to explore the current and future impacts of climate change on Fusarium biogeography, disease incidence and severity, as well as their effects on natural ecosystems, agriculture and food production [13,15]. Effective fungal disease management plays an important role in ensuring food security and safety. The integration of Fusarium spp. population data analytics and artificial intelligence (AI) in agricultural apps, such as AgroVariety, developed for farmers under Polish conditions (https://agrobank.pcss.pl/variety accessed on 9 October 2024), will enhance decision-making processes.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agriculture14101793/s1. Table S1. List of maize cultivars and number of evaluated samples; Table S2. List of sampled localities, their geographic location and samples number; Table S3. Frequency of Fusarium isolated from samples collected individually in 2015, 2016, 2017, and 2018; Table S4. Frequency of Fusarium isolated from samples collected individually in n = 16 localities individually in 2015, 2016, 2017, 2018; Table S5. Frequency of Fusarium individually isolated from samples collected in n = 16 localities individually during 2015–2018; Table S6. Frequency of Fusarium individually isolated from samples collected in n = 16 localities individually in 2015; Table S7. Frequency of Fusarium species individually isolated from samples collected in n = 16 localities individually in 2016; Table S8. Frequency of Fusarium species individually isolated from samples collected in n = 16 localities individually in 2017; Table S9. Frequency of Fusarium species individually isolated from samples collected in n = 16 localities individually in 2018; Table S10. Frequency of Fusarium species individually isolated from samples collected from hybrid individually in n = 16 localities individually in 2015; Table S11. Frequency of Fusarium species individually isolated from samples collected from hybrid individually in n = 16 localities individually in 2016; Table S12. Frequency of Fusarium species individually isolated from samples collected from hybrid individually in n = 16 localities individually in 2017; Table S13. Frequency of Fusarium species individually isolated from samples collected from hybrid individually in n = 16 localities individually in 2018; Table S14. PCA results derived from Fusarium spp. isolated from samples collected in Poland individually for June, July and August decades during 2015–2018 and temperatures; Table S15. PCA results derived from Fusarium spp. isolated from samples collected in Poland individually for June, July and August decades during 2015–2018 and precipitation; Table S16. PCA results derived from Fusarium spp. isolated from samples collected in Poland during 2015–2018 and geographic region of Poland. Figures S1–S6. Weather conditions for sampled localities individually: Figure S1 in 2015; Figure S2. in 2016; Figure S3 in 2017; Figure S4 in 2018; Figure S5. Climate conditions—average and differences in temperature for the period 2071–2100. (Czembor et al., In press [16]); Figure S6. Climate conditions—average and differences in precipitation for the period 2071–2100 (Czembor et al., In press [16]).

Author Contributions

Conceptualization, E.C. and Ł.S. Methodology, E.C., Ł.S., S.F. and M.U. Identification of Fusarium species, S.F., M.U. and E.C. Statistical analysis of data, S.F. and E.C. Data curation, E.C. and S.F. Project management E.C. and S.F. Development of first draft, S.F. and E.C. First draft correction Ł.S., A.W. and J.H.C. All authors have read and agreed to the published version of the manuscript.

Funding

Project “Creating scientific background for biological progress and protection of plant genetic resources as a source of innovation and support for sustainable agriculture and national food security” by resolution No. 104/2015 of the Council of Ministers of 14 July 2015. Project “Creation of bioinformatic management system on national genetic resources of useful plants and the development and protection of social and economic resources in Poland and their use in providing agricultural consulting services” (1/394826/10/NCBR/2018) financed by the National Center for Research and Development as part of the first round of competitive research grants under the strategic research and development program, GOSPOSTRATEG, “Social and Economic Development of Poland in the Context of Globalizing Markets”.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All the data generated or analyzed during this study are included in this published article and its supplementary information files. The relevant contact is Elzbieta Czembor, IHAR-PIB Radzikow, 05-870 Blonie, Poland.

Acknowledgments

We thank Rafał Pudełko and Jerzy Kozyra for their support in collection Sentinel-2 satellite data and providing climate change analysis for Polish conditions.

Conflicts of Interest

The authors declare no conflicts of interest. They declare no personal circumstances or interests that may be deemed to unduly influence the presentation and/or interpretation of reported research findings.

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Figure 1. Geographic localities where pathogen surveys were conducted (grain samples collected). Localities were visualized using the GinkoMaps project (http://www.ginkgomaps.com accessed on 9 October 2024). Grain samples collected in localities (L1–L16) represented the north-western (NW), north-eastern (NE), central (C), central-western (CW), south-eastern (SE) and south-western (SW) regions of Poland. The SW region was represented by L1 sampled during 2015–2018, L2 sampled from 2016 to 2018 and L3 in 2016 and 2017; the NW region was represented by L5 sampled during 2015–2018, and L15 and L16 sampled in 2015; the SE was represented by L4 sampled in 2018; the NE was represented by L13 and L14 sampled 2015–2018; and the C region was represented by L6, L9 sampled during 2015–2018 and L11 sampled in 2018.

Figure 2. Average frequency of Fusarium isolates isolated from n = 233 grain samples, each sample representing n = 50 grains, collected from sixteen localities in Poland individually during 2015 (n = 43), 2016 (n = 56), 2017 (n = 86) and 2018 (n = 50).

Figure 3. Average and maximum frequency of Fusarium isolates isolated from n = 233 grain samples, each sample representing n = 50 grains, collected from sixteen localities during 2015 (n = 54), 2016 (n = 54), 2017 (n = 86) and 2018 (n = 50). Bars represent standard deviation (SD).

Figure 4. Average and maximum frequency of Fusarium species individually isolated from n = 233 grain samples, each sample representing n = 50 grains, collected from sixteen localities in 2015, 2016, 2017 and 2018, respectively. (A) Average and maximum frequency of Fusarium isolates in 2015 (n = 43). (B) Average and maximum frequency of Fusarium isolates in 2016 (n = 54). (C) Average and maximum frequency of Fusarium isolates in 2017 (n = 86). (D) Average and maximum frequency of Fusarium isolates in 2018 (n = 50). Bars represent standard deviation (SD).

Figure 5. Average and maximum frequency of Fusarium isolates isolated from n = 233 grain samples, each sample representing n = 50 grains, collected from sixteen localities (L) during 2015 (n = 43), 2016 (n = 54), 2017 (n = 86) and 2018 (n = 50). Bars represent standard deviation (SD).

Figure 6. Average and maximum frequency of Fusarium isolates isolated from n = 233 grain samples, each sample representing n = 50 grains, collected from sixteen localities (L) individually in 2015, 2016, 2017 and 2018, respectively. (A) Average and maximum Fusarium isolate frequency in 2015 (n = 43). (B) Average and maximum Fusarium isolate frequency in 2016 (n = 54). (C) Average and maximum Fusarium isolate frequency in 2017 (n = 86). (D) Average and maximum Fusarium isolate frequency in 2018 (n = 50). Bars represent standard deviation (SD).

Figure 7. Projections of the scores for the frequency of Fusarium isolated from grain samples in 2015 and weather conditions in sampled localities onto the PC1 and PC2 factor planes, and projections of the scores for localities (L) onto the PC1 and PC2 factor planes in 2015. (A) PCA score plot of PC1 and PC2 factors representing correlations among the frequency of Fusarium species isolates (%) isolated from n = 43 grain samples (n = 50 grains per sample) and weather conditions in the sampled localities (number of days with temperatures T > 22 °C, T: 19–22 °C and T < 19 °C, and number of days with precipitation above 0.0 mm/m² during maize reproductive stages from R1, silking time stage, to R6, physiological maturity stage—June, July, August, September). (B) PCA score plot of PC1 and PC2 factors representing the relationship between localities (L1–L11) based on isolated Fusarium spp. frequency and weather condition data.

Figure 8. Projections of the scores for the frequency of Fusarium isolated from grain samples in 2016 and weather conditions in sampled localities onto the PC1 and PC2 factor planes, and projections of the scores for localities (L) onto the PC1 and PC2 factor planes in 2016. (A) PCA score plot of PC1 and PC2 factors representing correlations among the frequency of Fusarium species isolates (%) isolated from n = 54 grain samples (n = 50 grains per sample) and weather conditions in sampled localities (number of days with temperatures T > 22 °C, T: 19–22 °C and T < 19 °C, and number of days with precipitation above 0.0 mm/m² during maize reproductive stages from R1,silking time stage, to R6, physiological maturity stage—June, July, August, September). (B) PCA score plot of PC1 and PC2 factors representing the relationship between localities (L1–L14 except L5 and L11) based on isolated Fusarium spp. frequency and weather condition data.

Figure 9. Projections of the scores for the frequency of Fusarium isolated from grain samples in 2017 and weather conditions in sampled localities onto the PC1 and PC2 factor planes, and projections of the scores for localities (L) onto the PC1 and PC2 factor planes in 2017. (A) PCA score plot of PC1 and PC2 factors representing correlations among the frequency of Fusarium species isolates (%) isolated from n = 86 grain samples (n = 50 grains per sample) and weather conditions in sampled localities (number of days with temperatures T > 22 °C, T: 19–22 °C and T < 19 °C, and number of days with precipitation above 0.0 mm/m² during maize reproductive stages from R1, silking time stage, to R6, physiological maturity stage—June, July, August, September). (B) PCA score plot of PC1 and PC2 factors representing the relationship between localities (L1–L12 except L10) based on isolated Fusarium spp. frequency and weather condition data.

Figure 10. Projections of the scores for the frequency of Fusarium isolated from grain samples in 2018 and weather conditions in sampled localities onto the PC1 and PC2 factor planes, and projections of the scores for localities (L) onto the PC1 and PC2 factor planes in 2018. (A) PCA score plot of PC1 and PC2 factors representing correlations among the frequency of Fusarium species isolates (%) isolated from n = 50 grain samples (n = 50 grains per) and weather conditions in sampled localities (number of days with temperatures T > 22 °C, T: 19–22 °C and T < 19 °C, and number of days with precipitation above 0.0 mm/m² during maize reproductive stages from R1, silking time stage, to R6, physiological maturity stage—une, July, August, September). (B) PCA score plot of PC1 and PC2 factors representing the relationship between localities (L1–L12 except L8) based on isolated Fusarium spp. frequency and weather condition data.

Figure 11. Projections of the scores for Fusarium frequency isolates isolated from grain samples (n = 233, n = 50 grains in each sample) using PCA and geographic localization data variables (latitude [(ϕ)], longitude [λ], altitude [m.pm]). (A) PCA score plot of PC1 and PC2 factors representing correlations among the frequency of Fusarium species isolates and geographic localization data variables. (B) PCA score plot of PC1 and PC2 factors representing the relationship between localities (L1–L15) based on isolated Fusarium spp. frequency and geographic localization data variables.

Table 1. The correlation coefficient between the frequencies of Fusarium species isolated from dry kernels in samples collected from sixteen localities in Poland during 2015–2018.

Variable	F. proliferatum	F. subglutinans	F. temperatum	F. graminearum	F. culmorum	F. sporotrichioides	F. poae	F. avenaceum	F. oxysporum	F. equiseti	F. tricinctum
F. verticillioides	0.09	0.17	0.11	0.22	0.07	−0.02	0.03	0.06	0.17	0.0	0.02
F. proliferatum	1.00	−0.09	0.23	0.036	0.0	0.14	0.22	0.21	0.11	0.05	0.01
F. subglutinans		1.00	0.08	0.03	−0.01	−0.02	0.23	−0.11	−0.03	−0.03	0.03
F. temperatum			1.00	−0.13	0.3	0.09	0.05	0.24	−0.02	−0.01	−0.01
F. graminearum				1.00	−0.07	−0.01	0.0	−0.06	0.03	−0.02	0.02
F. culmorum					1.00	−0.01	−0.00	0.11	0.03	−0.02	−0.01
F. sporotrichioides						1.00	0.15	0.12	−0.02	0.26	−0.01
F. poae							1.00	−0.07	−0.02	0.36	−0.02
F. avenaceum								1.00	−0.04	−0.03	−0.02
F. oxysporum									1.00	−0.010	−0.01
F. equiseti										1.00	0.01

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Czembor, E.; Frasiński, S.; Urbaniak, M.; Waśkiewicz, A.; Czembor, J.H.; Stępień, Ł. Fusarium Species Shifts in Maize Grain as a Response to Climatic Changes in Poland. Agriculture 2024, 14, 1793. https://doi.org/10.3390/agriculture14101793

AMA Style

Czembor E, Frasiński S, Urbaniak M, Waśkiewicz A, Czembor JH, Stępień Ł. Fusarium Species Shifts in Maize Grain as a Response to Climatic Changes in Poland. Agriculture. 2024; 14(10):1793. https://doi.org/10.3390/agriculture14101793

Chicago/Turabian Style

Czembor, Elzbieta, Seweryn Frasiński, Monika Urbaniak, Agnieszka Waśkiewicz, Jerzy H. Czembor, and Łukasz Stępień. 2024. "Fusarium Species Shifts in Maize Grain as a Response to Climatic Changes in Poland" Agriculture 14, no. 10: 1793. https://doi.org/10.3390/agriculture14101793

APA Style

Czembor, E., Frasiński, S., Urbaniak, M., Waśkiewicz, A., Czembor, J. H., & Stępień, Ł. (2024). Fusarium Species Shifts in Maize Grain as a Response to Climatic Changes in Poland. Agriculture, 14(10), 1793. https://doi.org/10.3390/agriculture14101793

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