The next step in the Wendelstein stellarator line is the large superconducting device Wendelstein 7-X, currently under construction in Greifswald, Germany. Steady-state operation is an intrinsic feature of stellarators, and one key element of the Wendelstein 7-X mission is to demonstrate steady-state operation under plasma conditions relevant for a fusion power plant. Steady-state operation of a fusion device, on the one hand, requires the implementation of special technologies, giving rise to technical challenges during the design, fabrication and assembly of such a device. On the other hand, also the physics development of steady-state operation at high plasma performance poses a challenge and careful preparation. The electron cyclotron resonance heating system, diagnostics, experiment control and data acquisition are prepared for plasma operation lasting 30 min. This requires many new technological approaches for plasma heating and diagnostics as well as new concepts for experiment control and data acquisition.
Climate models predict an increased likelihood of drought, demanding efficient selection for drought tolerance to maintain yield stability. Classic tolerance breeding relies on selection for yield in arid environments, which depends on yield trials and takes decades. Breeding could be accelerated by marker-assisted selection (MAS). As an alternative to genomic markers, transcript and metabolite markers have been suggested for important crops but also for orphan corps. For potato, we suggested a random-forest-based model that predicts tolerance from leaf metabolite and transcript levels with a precision of more than 90% independent of the agro-environment. To find out how the model based selection compares to yield-based selection in arid environments, we applied this approach to a population of 200 tetraploid Solanum tuberosum ssp. tuberosum lines segregating for drought tolerance. Twenty-four lines were selected into a phenotypic subpopulation (PP t) for superior tolerance based on relative tuber starch yield data from three drought stress trials. Two subpopulations with superior (MP t) and inferior (MP s) tolerance were selected based on drought tolerance predictions based on leaf metabolite and transcript levels from two sites. The 60 selected lines were phenotyped for yield and drought tolerance in 10 multi-environment drought stress trials representing typical Central European drought scenarios. Neither selection affected development or yield potential. Lines with superior drought tolerance and high yields under stress were overrepresented in both populations selected for superior tolerance, with a higher number in PP t compared to MP t. However, selection based on leaf metabolites may still be an alternative to yield-based selection in arid environments as it works on leaves sampled in breeder's fields independent of drought trials. As the selection against low tolerance was ineffective, the method is best used in combination with tools that select against sensitive
Potato is an important food crop with high water-use-efficiency but low drought tolerance. The bottleneck in drought tolerance breeding is phenotyping in managed field environments. Fundamental research on drought tolerance is predominantly done in container-based test systems in controlled environments. However, the portability of results from these systems to performance under field conditions is debated. Thus, we analyzed the effects of climate conditions, container size, starting material, and substrate on yield and drought tolerance assessment of potato genotypes compared to field trials. A leave one out assessment indicated a minimum of three field trials for stable tolerance prediction. The tolerance ranking was highly reproducible under controlled-conditions, but weakly correlated with field performance. Changing to variable climate conditions, increasing container size, and substituting cuttings by seed tubers did not improve the correlation. Substituting horticultural substrate by sandy soil resulted in yield and tuber size distributions similar to those under field conditions. However, as the effect of the treatment × genotype × substrate interaction on yield was low, drought tolerance indices that depend on relative yields can be assessed on horticultural substrate also. Realistic estimates of tuber yield and tuber size distribution, however, require the use of soil-based substrates.
Potato is regarded as drought sensitive and most vulnerable to climate changes. Its cultivation in drought prone regions or under conditions of more frequent drought periods, especially in subtropical areas, requires intensive research to improve drought tolerance in order to guarantee high yields under limited water supplies. A candidate gene approach was used to develop functional simple sequence repeat (SSR) markers for association studies in potato with the aim to enhance breeding for drought tolerance. SSR primer combinations, mostly surrounding interrupted complex and compound repeats, were derived from 103 candidate genes for drought tolerance. Validation of the SSRs was performed in an association panel representing 34 mainly starch potato cultivars. Seventy-five out of 154 SSR primer combinations (49%) resulted in polymorphic, highly reproducible banding patterns with polymorphic information content (PIC) values between 0.11 and 0.90. Five SSR markers identified allelic differences between the potato cultivars that showed significant associations with drought sensitivity. In all cases, the group of drought-sensitive cultivars showed predominantly an additional allele, indicating that selection against these alleles by marker-assisted breeding might confer drought tolerance. Further studies of these differences in the candidate genes will elucidate their role for an improved performance of potatoes under water-limited conditions.
As climate changes, maintenance of yield stability requires efficient selection for drought tolerance. Drought-tolerant cultivars have been successfully but slowly bred by yield-based selection in arid environments. Marker-assisted selection accelerates breeding but is less effective for polygenic traits. Therefore, we investigated a selection based on phenotypic markers derived from automatic phenotyping systems. Our trial comprised 64 potato genotypes previously characterised for drought tolerance in ten trials representing Central European drought stress scenarios. In two trials, an automobile LIDAR system continuously monitored shoot development under optimal (C) and reduced (S) water supply. Six 3D images per day provided time courses of plant height (PH), leaf area (A3D), projected leaf area (A2D) and leaf angle (LA). The evaluation workflow employed logistic regression to estimate initial slope (k), inflection point (Tm) and maximum (Mx) for the growth curves of PH and A2D. Genotype × environment interaction affected all parameters significantly. Tm(A2D)s and Mx(A2D)s correlated significantly positive with drought tolerance, and Mx(PH)s correlated negatively. Drought tolerance was not associated with LAc, but correlated significantly with the LAs during late night and at dawn. Drought-tolerant genotypes had a lower LAs than drought-sensitive genotypes, thus resembling unstressed plants. The decision tree model selected Tm(A2D)s and Mx(PH)c as the most important parameters for tolerance class prediction. The model predicted sensitive genotypes more reliably than tolerant genotype and may thus complement the previously published model based on leaf metabolites/transcripts.
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