| Literature DB >> 33715023 |
Thomas Miedaner1, Peter Juroszek2.
Abstract
Wheat productivity is threatened by global climate change. In several parts of NW Europe it will get warmer and dryer during the main crop growing period. The resulting likely lower realized on-farm crop yields must be kept by breeding for resistance against already existing and emerging diseases among other measures. Multi-disease resistance will get especially crucial. In this review, we focus on disease resistance breeding approaches in wheat, especially related to rust diseases and Fusarium head blight, because simulation studies of potential future disease risk have shown that these diseases will be increasingly relevant in the future. The long-term changes in disease occurrence must inevitably lead to adjustments of future resistance breeding strategies, whereby stability and durability of disease resistance under heat and water stress will be important in the future. In general, it would be important to focus on non-temperature sensitive resistance genes/QTLs. To conclude, research on the effects of heat and drought stress on disease resistance reactions must be given special attention in the future.Entities:
Year: 2021 PMID: 33715023 PMCID: PMC8205889 DOI: 10.1007/s00122-021-03807-0
Source DB: PubMed Journal: Theor Appl Genet ISSN: 0040-5752 Impact factor: 5.699
Fig. 1The ‘disease triangle’ concept simplified with focus on potential climate change effects. Few examples of driving factors are highlighted. Some likely consequences of future interactions are shown in the outside positioned circles. Other environmental parameters (e.g., soil type) and management options (e.g., fertilizer and irrigation inputs, soil tillage and sowing methods) are not shown, although they also influence the effects of future climate change on plant-pathogen interactions
Simulated fungal disease risks of winter wheat in Europe using plant disease models driven by climate change scenarios, usually downscaled to a regional level. Projections until 2050 considered
| Disease (Pathogen) | Country (Region) | Change of disease riska | Reference |
|---|---|---|---|
Powdery mildew ( | Germany (NRW) Germany (LS) | + − | Volk et al. ( Racca et al. ( |
Leaf rust ( | Germany (NRW) Germany (LS) | + + | Volk et al. ( Racca et al. |
| Europe | + | Bregaglio et al. ( | |
| Luxemburg | + | Junk et al. ( | |
Scotland Poland France France | + + + + | Davies et al. ( Wojtowicz et al. ( Caubel et al. ( Launay et al. ( | |
Yellow rust ( | Germany (NRW) Europe | + + | Volk et al. ( Bregaglio et al. ( |
Stem rust ( | NW Europe | + | Prank et al. ( |
| NW Europe, UK | + | Davies et al. ( | |
Eyespot ( | Germany (NRW) | o | Volk et al. ( |
Septoria tritici blotch ( | Germany (NRW) France | + - | Volk et al. ( Gouache et al. ( |
Septoria nodorum blotch ( | Germany (NRW) | o | Volk et al. ( |
Tan spot ( | Germany (NRW) Germany (LS) | o + | Volk et al. ( Racca et al. |
Fusarium head blight ( | Germany (NRW) | + | Volk et al. |
| Scotland | + | Davies et al. | |
| UK | + | Madgwick et al. |
aChange of disease risk: − decrease, o unchanged, + increase, NRW = Northrhine-Westfalia, LS = Lower Saxony
Footnote 1: Most studies consider the infection risk (e.g., Volk et al. 2010; Racca et al. 2012; Bregaglio et al. 2013; Junk et al. 2016; Caubel et al. 2017; Launay et al. 2020), whereas few studies consider inoculum accumulation risk (Volk et al. 2010) or wind velocity patterns supporting long-distance spore distribution (Prank et al. 2019) or duration of latency period (e.g., Wojtowicz et al. 2017) or disease incidence (Madgwick et al. 2011) or disease severity (Gouache et al. 2013). Footnote 2: Speculations based on expert knowledge usually consider the complete disease cycle (e.g., Boland et al. 2004). These are not shown in Table 1, but can be found in the review article by Juroszek and von Tiedemann (2013a) related to future risks of wheat diseases. Footnote 3: Results of simulations of future disease risk until 2100 are not shown; however, usually the risk continues to increase (e.g., Racca et al. 2012; Junk et al. 2016; Caubel et al. 2017; Wojtowicz et al. 2017; Launay et al. 2020) or to decrease (e.g., Gouache et al. 2013), respectively. Rarely, the risk of a certain disease first increased (2050) and subsequently decreased (2100) in the simulation studies. For review see Juroszek and von Tiedemann (2013a, b, 2015)
Fig. 2Yellow rust severity of selected German cultivars in the adult-plant stage (EC 49–71) inoculated in the field with mixtures of Yr races that were predominant in the respective year; Yr severity was tested in the given years at Berlin-Dahlem and based on the 1–9 scale, with 1–3 = resistant, 4–6 = intermediate, 7–9 = susceptible (Kerstin Flath, Julius-Kuehn Institute, pers. commun.)
New epidemics of wheat stem rust in Eurasia (Shamanin et al. 2016; Saunders et al. 2019; https://rusttracker.cimmyt.org/?p=7083)
| Year | Region | Damage |
|---|---|---|
| 2013 | Central Germany UK, Denmark | Regional epidemic, winter wheat sporadic occurrence |
| 2015(+ 2016) | Western Siberia/Russia and Kasachstan | > 1 million hectares spring wheat, 20–30% yield loss |
| 2016 | Sicily/Italy | ~ 20–30.000 ha durum wheat, 20–60% disease incidence |
| 2017 | Central Sweden | Late-maturing wheat and barley |
Fig. 3Stem rust risk in Europe under average climate conditions for the last 30 years (left) and predicted climate in 2050 (right) (Davies et al. 2007, with permission of the authors)