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Abstract Climate changes leading to increasingly longer seasonal drought periods in large parts of the world increase the necessity for breeding drought-tolerant crops. Cultivated potato (Solanum tuberosum), the third most important vegetable crop worldwide, is regarded as drought-sensitive due to its shallow root architecture. Two German tetraploid potato cultivars differing in drought tolerance and their F1-progeny were evaluated under various drought scenarios. Bulked segregant analyses were combined with whole-genome sequencing (BSA-Seq) using contrasting bulks of drought-tolerant and drought-sensitive F1-clones. Applying QTLseqr, 15 QTLs comprising 588,983 single nucleotide polymorphisms (SNPs) in 2325 genes associated with drought stress tolerance were identified. SeqSNP analyses in an association panel of 34 mostly starch potato varieties using 1–8 SNPs for each of 188 selected genes narrowed the number of candidate genes down to 10. In addition, ent-kaurene synthase B was the only gene present under QTL 10. Eight of the identified genes (StABP1, StBRI1, StKS, StLEA, StPKSP1, StPKSP2, StYAB5, and StZOG1) address plant development, the other three genes (StFATA, StHGD and StSYP) contribute to plant protection under drought stress. Allelic variation in these genes might be explored in future breeding for drought-tolerant potato varieties.

Für die Umsetzung einer nachhaltigen Bewirtschaftung von Agrarflächen werden möglichst genaue Informationen über den Zustand der Pflanzen und der Umgebung, in der diese wachsen, benötigt. Unter dem Begriff „Smart Farming“ werden Technologien verstanden, die diese Informationen erheben, auswerten und zielgerichtet anwenden können. Nachfolgend wird der PotatoScanner vorgestellt, welcher in der Lage ist, Umweltparameter auf dem Feld zu erfassen und auszuwerten. Als Anwendungsbeispiel soll die Blattoberflächentemperatur von Pflanzen erfasst werden. Mit diesem Parameter ließe sich der Trockenstress von Pflanzen ermitteln. Darüber hinaus ist der PotatoScanner in der Lage, Messdaten von weiteren auf dem Feld befindlichen Sensoren abzurufen und zu speichern. Dies ist von Vorteil, wenn für die im Feld befindlichen Sensoren eine sichere Übertragungsmöglichkeit, z. B. mittels Mobilfunks, fehlt. Diese Problematik tritt verstärkt im ländlichen Raum auf, da die Bereitschaft der Mobilfunkbetreiber, dort ein flächendeckendes Netz aufzubauen, gering ist. Der PotatoScanner ist in der Lage, dieses Defizit zu kompensieren, wodurch der Einsatz von Sensortechnik auch in Gebieten ermöglich wird, in denen kein Mobilfunknetz vorhanden ist. Im Anschluss an die Vorstellung des Systems wird eine Evaluierung über zwei Wachstumsperioden durchgeführt. Weiterhin wird gezeigt, welche Möglichkeiten zur Datenübertragung auf dem Feld vorhanden und welche Umwelteinflüsse bei dessen Betrieb zu beachten sind.

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 (PPt) for superior tolerance based on relative tuber starch yield data from three drought stress trials. Two subpopulations with superior (MPt) and inferior (MPs) 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 over-represented in both populations selected for superior tolerance, with a higher number in PPt compared to MPt. 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 genotypes. Thus, metabolic and transcript marker-based selection for drought tolerance is a viable alternative to the selection on yield in arid environments.

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.