@article{BiermannBachKlaeringetal.2022,
  author    = {Biermann, Robin Tim and Bach, Linh T. and Kl{\"a}ring, Hans-Peter and Baldermann, Susanne and B{\"o}rnke, Frederik and Schwarz, Dietmar},
  title     = {Discovering tolerance-A computational approach to assess abiotic stress tolerance in tomato under greenhouse conditions},
  series = {Frontiers in sustainable food systems},
  volume    = {6},
  journal   = {Frontiers in sustainable food systems},
  publisher = {Frontiers Media},
  address   = {Lausanne},
  issn      = {2571-581X},
  doi       = {10.3389/fsufs.2022.878013},
  pages     = {12},
  year      = {2022},
  abstract  = {Modern plant cultivars often possess superior growth characteristics, but within a limited range of environmental conditions. Due to climate change, crops will be exposed to distressing abiotic conditions more often in the future, out of which heat stress is used as example for this study. To support identification of tolerant germplasm and advance screening techniques by a novel multivariate evaluation method, a diversity panel of 14 tomato genotypes, comprising Mediterranean landraces of Solanum lycopersicum, the cultivar "Moneymaker" and Solanum pennellii LA0716, which served as internal references, was assessed toward their tolerance against long-term heat stress. After 5 weeks of growth, young tomato plants were exposed to either control (22/18 degrees C) or heat stress (35/25 degrees C) conditions for 2 weeks. Within this period, water consumption, leaf angles and leaf color were determined. Additionally, gas exchange and leaf temperature were investigated. Finally, biomass traits were recorded. The resulting multivariate dataset on phenotypic plasticity was evaluated to test the hypothesis, that more tolerant genotypes have less affected phenotypes upon stress adaptation. For this, a cluster-analysis-based approach was developed that involved a principal component analysis (PCA), dimension reduction and determination of Euclidean distances. These distances served as measure for the phenotypic plasticity upon heat stress. Statistical evaluation allowed the identification and classification of homogeneous groups consisting each of four putative more or less heat stress tolerant genotypes. The resulting classification of the internal references as "tolerant" highlights the applicability of our proposed tolerance assessment model. PCA factor analysis on principal components 1-3 which covered 76.7\% of variance within the phenotypic data, suggested that some laborious measure such as the gas exchange might be replaced with the determination of leaf temperature in larger heat stress screenings. Hence, the overall advantage of the presented method is rooted in its suitability of both, planning and executing screenings for abiotic stress tolerance using multivariate phenotypic data to overcome the challenge of identifying abiotic stress tolerant plants from existing germplasms and promote sustainable agriculture for the future.},
  language  = {en}
}
@phdthesis{Schauer2006,
  author    = {Schauer, Nicolas},
  title     = {Quantitative trait loci (QTL) for metabolite accumulation and metabolic regulation : metabolite profiling of interspecific crosses of tomato},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-7643},
  school      = {Universit{\"a}t Potsdam},
  year      = {2006},
  abstract  = {The advent of large-scale and high-throughput technologies has recently caused a shift in focus in contemporary biology from decades of reductionism towards a more systemic view. Alongside the availability of genome sequences the exploration of organisms utilizing such approach should give rise to a more comprehensive understanding of complex systems. Domestication and intensive breeding of crop plants has led to a parallel narrowing of their genetic basis. The potential to improve crops by conventional breeding using elite cultivars is therefore rather limited and molecular technologies, such as marker assisted selection (MAS) are currently being exploited to re-introduce allelic variance from wild species. Molecular breeding strategies have mostly focused on the introduction of yield or resistance related traits to date. However given that medical research has highlighted the importance of crop compositional quality in the human diet this research field is rapidly becoming more important. Chemical composition of biological tissues can be efficiently assessed by metabolite profiling techniques, which allow the multivariate detection of metabolites of a given biological sample. Here, a GC/MS metabolite profiling approach has been applied to investigate natural variation of tomatoes with respect to the chemical composition of their fruits. The establishment of a mass spectral and retention index (MSRI) library was a prerequisite for this work in order to establish a framework for the identification of metabolites from a complex mixture. As mass spectral and retention index information is highly important for the metabolomics community this library was made publicly available. Metabolite profiling of tomato wild species revealed large differences in the chemical composition, especially of amino and organic acids, as well as on the sugar composition and secondary metabolites. Intriguingly, the analysis of a set of S. pennellii introgression lines (IL) identified 889 quantitative trait loci of compositional quality and 326 yield-associated traits. These traits are characterized by increases/decreases not only of single metabolites but also of entire metabolic pathways, thus highlighting the potential of this approach in uncovering novel aspects of metabolic regulation. Finally the biosynthetic pathway of the phenylalanine-derived fruit volatiles phenylethanol and phenylacetaldehyde was elucidated via a combination of metabolic profiling of natural variation, stable isotope tracer experiments and reverse genetic experimentation.},
  subject      = {Tomate},
  language  = {en}
}