Diversity in susceptibility reactions of winter wheat genotypes to obligate pathogens under fluctuating climatic conditions

Climate change significantly impacts wheat production, with a 1°C temperature increase potentially decreasing yields by 6%. Changes in climatic patterns also affect the distribution and prevalence of economically important pathogens. Powdery mildew (*Blumeria graminis* f. sp. *tritici*) and rust diseases (*Puccinia graminis* f. sp. *tritici*, *Puccinia triticina*, *Puccinia striiformis* f. sp. *tritici*) are major obligate wheat pathogens. Powdery mildew can reduce yields by up to 45%, while rusts have caused yield losses as high as 50%. In Serbia, yellow rust (*P. striiformis* f. sp. *tritici*) became predominant over leaf rust (*P. triticina*) in 2014 due to altered climate conditions. Pest control is challenging due to the continuous adaptation of pathogens. While many studies focus on the impact of abiotic factors on wheat yield and quality, the combined effects of biotic and abiotic factors on yield losses and disease occurrence are often neglected. Heeb (2019) highlighted the challenges in developing general models for predicting climate change-induced pest outbreaks at a local scale. Abiotic stressors like high/low temperatures, drought, and salinity can alter plant-pest interactions by influencing plant physiology and defense responses. Combinatorial stress needs to be treated as a unique condition, prioritizing the development of plants with enhanced tolerance to combined stresses. This study hypothesized that the relationship among obligate wheat pathogens is influenced by plant physiological responses to fluctuating climate and that pathogen occurrence cannot be solely explained by climatic effects on pathogen life cycles and plant resistance genes. The study aimed to analyze the combined effect of abiotic and biotic factors on obligate pathogen prevalence in winter wheat, focusing on the reactions of susceptible genotypes to extreme climate fluctuations and pathogen pressure. Data came from a high-throughput screening platform for obligate pathogens in 2158 winter wheat genotypes with diverse genetic backgrounds.

Existing research primarily focuses on the impact of abiotic factors on plant pathogen distribution and the development of predictive models for pathogen outbreaks. However, the combined effects of biotic and abiotic factors on the prevalence of economically important pathogens, particularly in wheat, have been largely overlooked. Studies have documented the significant yield reductions caused by powdery mildew and various rust diseases in wheat. The shift in the predominant rust species in Serbia from leaf rust to yellow rust in 2014 exemplifies the influence of climate change on pathogen dynamics. While efforts have been made to determine damage thresholds and develop forecasting models, the integration of biotic and abiotic factors into these models remains limited. The complex interplay between abiotic and biotic stressors on plant responses is recognized, but predicting the combined effects remains challenging.

Data were obtained from a phenotyping platform for high-throughput screening of obligate pathogens (*B. graminis* f. sp. *tritici*, *P. graminis* f. sp. *tritici*, *P. triticina*, *P. striiformis* f. sp. *tritici*) in 2158 winter wheat genotypes with diverse genetic backgrounds. Field trials were conducted in Rimski Šančevi, Serbia, from 2016 to 2019, using a methodology adapted from CIMMYT guidelines for rapid assessment of wheat genotypes. Each genotype was sown in 1-m rows with five replicates. The soft wheat variety Barbee, highly susceptible to obligate parasites, was planted to maintain consistent pathogen pressure. Assessments of obligate pathogens were expressed as disease indices (DIs, %), calculated at growth stage 71-73 BBCH (early milk), using modified Cobb's scale. DI was calculated as: DI (%) = [sum (class frequency x score of rating class)]/[(total number of plants) x (maximal score of rating class)] x 100. The mean sowing date was October 20th. The interaction among powdery mildew and rust diseases was analyzed for 1389 susceptible genotypes. Principal component analysis (PCA) characterized the relationship among obligate pathogens in each growing season. Spearman's correlation coefficient was used to quantify the relationship between disease indices. Multiple linear regression (stepwise regression) analyzed factors influencing disease indices, considering genotypes, obligate pathogens, and climatic elements (monthly mean temperatures, relative humidity, and total rainfall). The consistency of the rust species population structure was monitored in collaboration with Dr. Diane Saunders.

The study revealed a non-linear trend in the occurrence and relationships among powdery mildew and rust diseases over the four-year period. Yellow rust was prevalent in 2016 and 2018, while leaf rust predominated in 2017 and 2019. Powdery mildew consistently occurred regardless of the rust species prevalence. Stem rust outbreaks occurred in 2019. Genotypes significantly influenced disease indices (P<0.001), and obligate pathogens significantly influenced each other's indices (P<0.001). PCA showed a negative correlation between leaf rust and yellow rust in 2016 and 2018, while powdery mildew showed no correlation with rusts except for a positive correlation with yellow rust in 2017. In 2019, powdery mildew and stem rust were positively correlated. In 2018, powdery mildew predominated over yellow rust in 33% of genotypes, and yellow rust predominated in 55.5%. Multiple linear regression indicated that January and February temperatures in 2016 and 2018 significantly influenced genotype responses to powdery mildew and yellow rust. In genotypes where yellow rust predominated, January temperature was the most influential factor (P<0.001), while in genotypes where powdery mildew predominated, February temperature was most influential (P<0.001). In 2018, leaf rust predominated over yellow rust in 21% of genotypes despite yellow rust's aggressiveness. Multiple linear regression on genotypes where powdery mildew was minimal showed that February temperature (P=0.001) and yellow rust (P<0.001) influenced leaf rust indices in genotypes where leaf rust predominated. In 2019, stem rust occurred in 35% of genotypes, influenced by November rainfall (P<0.001), leaf rust (P=0.007), and powdery mildew (P=0.001). Stem rust showed a low positive correlation with powdery mildew (r=0.28, P<0.001) and no correlation with leaf rust.

The study's findings highlight the complex and non-straightforward relationship between rust species and powdery mildew in winter wheat. While climatic conditions are essential for pathogen infection and disease development, genotype responses to fluctuating climatic elements significantly influence pathogen interactions and the predominance of specific pathogens. The inconsistency in pathogen predominance, even within the same field and growing season, emphasizes the importance of considering genotype-environment interactions. The observation that leaf rust can predominate over yellow rust in certain conditions, despite yellow rust's generally higher aggressiveness, underscores the influence of genotype-specific responses to fluctuating environmental conditions. The study supports previous research indicating that plant responses to combined stressors are unpredictable and that these combined stresses must be studied as unique conditions to develop effective climate-smart pest management strategies. The results highlight the need for more detailed investigation into the mechanisms by which winter wheat genotypes can avoid severe yellow rust infections even under favorable environmental conditions for the pathogen.

This study demonstrates that fluctuating winter temperatures significantly impact the susceptibility of winter wheat genotypes to obligate pathogens. The complex interaction between biotic and abiotic factors makes accurate disease prevalence forecasting challenging. The findings emphasize the need to treat combined stresses as unique conditions and focus on mechanisms enabling wheat genotypes to escape severe infections to improve climate-smart pest management strategies. Future research should focus on elucidating the underlying mechanisms of these genotype-environment interactions to enhance integrated pest management strategies for wheat production globally.

The study was conducted in a single location in Serbia, limiting the generalizability of the findings to other regions with different climatic conditions. The use of a single susceptible wheat cultivar as a control might have influenced the pathogen pressure across the genotypes. Furthermore, the study focused primarily on susceptible genotypes, and the results may not fully represent the responses of resistant genotypes.