INTRODUCTION

The North Caucasus is the main region for the cultivation of winter wheat, the sown area of ​​which is 55% of all winter crops in the Russian Federation. This crop is susceptible to a number of dangerous phytopathogens, including brown rust (Puccinia triticina Erikks.), one of the malicious and common phytopathogens [1]. Due to the favorable climate for the development of the pathogen and large areas of cultivation of the host plant, brown rust remains a significant wheat disease in the North Caucasus [2]. Therefore, the development of effective methods of protection against this harmful pathogen is especially relevant for this region. Traditionally, over large areas of cultivation, the disease is controlled through the use of effective fungicides. But the growing greening of agricultural production requires safe methods of protecting wheat from brown rust, such as cultivating varieties protected by disease resistance genes [3]. It is known that a scientifically based strategy of varietal displacement by aerial landscape niches and proper varietal change is necessary for the correct and effective use of the potential of various varieties [4]. Knowledge of the dynamics of the phenotypic composition of the pathogen’s population in various agroclimatic zones, differing in heat and moisture supply, is also important. Therefore, annual studies of virulence and phenotypic composition of the brown rust population are carried out in various regions of the world [5–7]. In Russia, similar work is carried out in the main grain-producing regions. Fungal virulence is studied in the Lower Volga region, in the Urals, in the West Siberian, Northwest, and Central regions [8–12]. In the North Caucasus, the virulence of the brown rust population in various agroclimatic zones is described for 2006–2015 [2, 13, 14].

The aims of this work were to analyze the phenotypic composition of the North Caucasian population of P. triticina in 2016–2018 in five agroclimatic zones, to identify common and dominant phenotypes, and to assess the phenotypic diversity and the level of differences in the fungal population by years of research.

MATERIALS AND METHODS

To collect the infectious material, routine examinations were performed annually (in the phase of milk-wax ripeness of grain) for breeding and production crops of winter wheat in five agroclimatic zones of the region, differing in heat and moisture supply (Fig. 1). The leaves affected by the disease were collected on wheat crops in each agroclimatic zone and used to isolate monopodule isolates of the fungus. The preparation of monopustular isolates and their reproduction was carried out according to existing techniques [14].

To analyze the virulence of P. triticina isolates, 16 closely isogenic Thatcher lines with Lr genes—1, 2a, 2c, 3, 9, 16, 24, 26, 3ka, 11, 17, 30, B, 10, 14a, and 18—were used. the lines were grown in flowerpots (50 mL) hydroponically using Knop nutrient solution [15]. At the age of one leaf, they were inoculated with a spore suspension of a monopuscular isolate. After the wet chamber, the plants were kept at 18–20°C, illumination intensities of up to 15 000 lux and air humidity of 60–70%. On the 10th–14th day, infectious types (IT) were recorded according to the Mains and Jackson [16] scales as high (IT from 3 to 4) or low (IT from 0 to 2).

The phenotypes were labeled according to the North American nomenclature [17]. The diversity of the population by phenotypic composition was evaluated by the Shannon index [18]. Differences between populations by virulence phenotypes were evaluated using the Rogers index [19]:

$${{{\text{H}}}_{{\text{r}}}} = 1{\text{/}}2\sum {(pi\,1 - pi\,2)} ,$$

where pi 1 is the frequency of the ith phenotype in the first population; pi 2 is the frequency of the ith phenotype in the second population.

RESULTS AND DISCUSSION

In 2016, the prevailing weather conditions favored the development of phytopathogens on winter cereal crops. Brown rust of wheat was noted in all five agroclimatic zones of the region. In the 2017 growing season, the conditions of early spring were favorable for the growth and development of winter crops. However, frequent rains in June and a low temperature regime delayed the maturation of wheat and created conditions for the development of diseases. Brown rust was detected in four agroclimatic zones (except for the eastern steppe) with maximum development in the central zone (6.8%). The following year, 2018, was unfavorable for the development of phytopathogens. Against the background of the abnormally hot weather of April–June, a significant deficit of precipitation was observed (20–30% of the norm), which contributed to the development of soil and atmospheric droughts, which had reached the criteria for a dangerous phenomenon by the end of June. Relative humidity decreased to 45–55%, which was 15–20% below the norm. In this regard, brown rust was noted in three agroclimatic zones: the southern foothill, western Azov, and central zone (with a development of up to 1–2%).

In 2016–2018, 233 monopodular isolates of P. triticina were studied, of which 212 virulence phenotypes were identified. As in previous years [13, 14], the brown rust pathogen population in the region continued to be highly diverse (Table 1). At the same time, the maximum diversity in phenotypic composition was revealed in the population of 2017. Despite the unfavorable conditions of the 2018 growing season, the diversity of P. triticina remained at a high level.

Table 1.   Characteristics of the diversity of the P. triticina population in the North Caucasus by phenotypic composition
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Virulence phenotypes in five agroclimatic zones are given in Table 2, and virulence formulas (ineffective genes) of dominant and repeating phenotypes are given in Table 3. In 2016, out of 90 monoplastic isolates, 76 phenotypes were identified. The PHRS, THRS, PGRS, PBMJ, PBRQ, BBBB, and MHTT phenotypes were repeating, while the remaining were unique. In 2016, the PHRS phenotype dominated, which was identified in the southern foothill, western Azov, and eastern steppe agroclimatic zones. The THRS phenotype was found in the central and eastern steppe zones, PGRS in the western Azov and eastern steppe zones, and PBRQ in the southern foothill zone. These phenotypes contain an average number of virulence alleles. In addition to virulent ones, avirulent (BBBB) and weakly virulent (PBMJ) phenotypes were also repeated in 2016. Generally, phenotypes with a high and average number of virulence alleles prevailed in the 2016 population.

Table 2.   Phenotypic composition of the North Caucasian population of P. triticina in various agroclimatic zones, 2016–2018
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Table 3.   Virulence and frequency (%) of repeating phenotypes of the North Caucasian population of P. Triticina, 2016–2018
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In 2017, the phenotypes DCRL, LBLL (western Azov zone) and PCQB (northern zone) dominated. The avirulent phenotype of BBBB was found, as in 2016, in the northern zone with insufficient heat and moisture supply (Fig. 1). In 2017 and 2018, phenotypes of group B (BBBB, BBBL, BBDT, BHDT, BHLQ, BBBG, BBCB, FBBB, KBBD, QBLL, QBBB) containing the minimum number of virulence alleles prevailed in the southern piedmont zone. This may be due to both biotic (varietal composition) and abiotic (reduced heat supply of the zone) factors.

Fig. 1.
figure 1

Description of agroclimatic zones of the North Caucasus by heat and moisture supply [20].

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Phenotypes with a high content of virulence alleles (MHTT, MDTT, SHTT, PHTT, PHTQ, etc.) prevailed in the western Azov and central zones. Table 3 shows that the phenotypes of P. triticina, which are avirulent (BBBB) or contain a large number of virulence alleles (MHTT, PKTT), are repeated in 2018. In 2017 and 2018, phenotypes virulent to the line with the Lr24 gene (for example, PKTT, SFGQ, CFPQ, TKTS, MKTT, LKSR) were noted in fungal populations. Single isolates virulent to this line were also noted in the North Caucasian population in previous years [13, 14]. In 2016, a phenotype with virulence to the line containing Lr9 (TLGS) was first discovered. In previous years, this phenotype was not observed [13], although this gene has already lost its effectiveness in other regions [9, 11]. In general, differences in the phenotypic composition of the fungus between years, estimated using the Rogers index (R), are significant for each pair of compared populations (for 2016 and 2017, R = 0.96, 2017 and 2018–0.97, 2016 and 2018–0.99).

CONCLUSIONS

Thus, the phenotypic composition of the P. triticina population was monitored in 2016–2018 in various agroclimatic zones of the North Caucasus. Of the 233 monopodular isolates of the fungus analyzed, 212 phenotypes were identified. Recurring phenotypes were identified in each agroclimatic zone. The phenotype with virulence to the line containing Lr9 (TLGS) was detected for the first time. A high level of phenotypic diversity of the North Caucasian fungal population (Sh = 0.92–0.99) and a significant level of differences in the P. triticina population by phenotypic composition between years of research (R = 0.96–0.99) were established.