| dc.contributor.advisor | Rötter, Reimund P. Prof. Dr. | |
| dc.contributor.author | Appiah, Mercy | |
| dc.date.accessioned | 2023-11-28T07:53:39Z | |
| dc.date.available | 2023-12-05T00:50:10Z | |
| dc.date.issued | 2023-11-28 | |
| dc.identifier.uri | http://resolver.sub.uni-goettingen.de/purl?ediss-11858/14994 | |
| dc.identifier.uri | http://dx.doi.org/10.53846/goediss-10232 | |
| dc.format.extent | 184 | de |
| dc.language.iso | eng | de |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject.ddc | 630 | de |
| dc.title | Linking crop modelling and experimentation to fully exploit genotypic diversity in barley for climate change adaptation in Europe | de |
| dc.type | cumulativeThesis | de |
| dc.contributor.referee | Rötter, Reimund P. Prof. Dr. | |
| dc.date.examination | 2023-11-15 | de |
| dc.description.abstracteng | Summary
Future barley production in Europe is projected to face severer and more frequent climate extreme events. Projections have also shown that potential climate-change induced yield losses can be significantly counteracted through implemented autonomous adaptation options and genetic improvement. Designing barley ideotypes supported by crop simulation models (CSMs), which can simulate genotype x environment x management interactions, can accelerate the breeding of cultivars that are better adapted to future conditions, yet this approach still has various limitations. This thesis shows, how a better linkage between modelling and experimentation can contribute to overcoming these limitations and hence to accelerating progress in climate change adaptation for barley production in Europe. Designing ideotypes starts with understanding the conditions of the target environment. We used agroclimatic indicators to provide a detailed target environment description focusing on projected heat and drought stress conditions at three contrasting barley production sites along a European transect (Chapter II). At all sites (Zaragoza, Dundee, Helsinki), temperatures were projected to increase during the future (2031-50) heading and grain filling periods, however heat stress could be avoided by advancing the heading date (through early sowing, choosing early flowering cultivars). Cultivation risks could arise from summer droughts at Helsinki, terminal droughts interrupted by a few high-rainfall events at Zaragoza and, possibly heavy rainfall and waterlogging at Dundee. As autonomous adaptation options were only partly successful in avoiding drought stress, combining those measures with resilient cultivars is crucial.
For reliable CSM-aided ideotype design, CSMs need to accurately capture impacts of climate extremes on crops, which they are still not able to do satisfactorily. The reason is that the data required to improve respective model deficiencies is not sufficiently available. A better linkage between modelling and experimentation can contribute significantly to providing these data as shown in the systematic review (Chapter III) and in model-guided experimental work in the field (Chapter IV) and a semi-controlled environment (Chapter V). Both experiments were conducted within the framework of European research projects that facilitated close collaboration between breeders, crop modelers and plant physiologists.
We collected high quality field data for model evaluation and improvement at a Nordic barley cultivation site, where such data is most rarely available (Chapter IV). The obtained dataset was of high temporal and spatial detail, containing multiple in-season above- and belowground data points. As its quality meets the highest standards for modelling it is well suitable for CSM improvement and contributes to closing a long existing data gap. APSIM calibrated with this high quality data captured in-season growth processes and final outputs most accurately. With these data we could also detect potential areas for model improvement, such as inaccurate soil water dynamics or leaf area development.
The greenhouse trial aimed at increasing our understanding of plant physiological processes to improve CSMs regarding e.g. simulated responses to climate extremes, like drought. In this experiment (Chapter V), we used a high-throughput functional phenotyping platform to examine the water use behavior of four European spring barley cultivars and their response to intermediate drought. The best performing cultivar (cv. RGT Planet) with high and stable yields under drought showed a dynamic (flexible) water use behavior: its high transpiration/assimilation rate under well-watered conditions made it more productive than the water-conserving cultivars which had a much lower transpiration rate. At the onset of drought cv. RGT Planet switched to a more water-conserving behavior allowing it to be more productive than the non-conserving cultivar. A drought ideotype could have such dynamic water use traits combined with high drought resilience (as observed in cv. RGT Planet) and beneficial root traits.
To further support model-guided experimentation all resources including new measurement tools and techniques, robotics, phenotyping and machine learning should be exploited and interdisciplinary research collaborations should be further promoted (as discussed in Chapter VI). | de |
| dc.contributor.coReferee | Beissinger, Timothy M. Prof. Dr. | |
| dc.contributor.thirdReferee | Asseng, Senthold Prof. Dr. | |
| dc.subject.eng | crop model-aided ideotyping | de |
| dc.subject.eng | drought response behavior | de |
| dc.subject.eng | projected conditions in future barley production environments | de |
| dc.subject.eng | high-quality field data for crop model improvement | de |
| dc.subject.eng | high-throughput functional phenotyping plattform | de |
| dc.identifier.urn | urn:nbn:de:gbv:7-ediss-14994-7 | |
| dc.affiliation.institute | Fakultät für Agrarwissenschaften | de |
| dc.subject.gokfull | Land- und Forstwirtschaft (PPN621302791) | de |
| dc.description.embargoed | 2023-12-05 | de |
| dc.identifier.ppn | 187166747X | |
| dc.identifier.orcid | https://orcid.org/0000-0002-3953-6350 | de |
| dc.notes.confirmationsent | Confirmation sent 2023-11-28T08:15:01 | de |