Discovering Tolerance—A Computational Approach to Assess Abiotic Stress Tolerance in Tomato Under Greenhouse Conditions - Biermann, Robin Tim; Bach, Linh T.; Kläring, Hans-Peter; Baldermann, Susanne; Börnke, Frederik; Schwarz, Dietmar (Frontiers in Sustainable Food Systems, 2022)
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 towards their tolerance against long-term heat stress. After five weeks of growth, young tomato plants were exposed to either control (22/18 °C) or heat stress (35/25 °C) conditions for two weeks. Within this period, water consumption, leaf angles and leaf colour 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, dimension reduction and determination of Euclidean distances. As the distances between genotypes and their respective treatments, which served as measure for plasticity, followed a normal distribution, two statistical approaches were applied to classify the diversity panel as more or less heat stress tolerant. The resulting classification of the internal references as “tolerant” highlights the applicability of our proposed tolerance assessment model. To draw conclusions on the selection of scalable phenotypic measures for bigger screenings, a PCA factor analysis was done. The outcome suggests that there can be stress-specific trait correlations, out of which some laborious measures might be replaceable. Therefore, small test screenings are recommended to decrease the workload of further stress-adapted screenings and maintain scalability. 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.