Browsing by Person "Dumont, Benjamin"

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Determining the footprint of breeding in the seed microbiome of a perennial cereal
(2024) Michl, Kristina; David, Christophe; Dumont, Benjamin; Mårtensson, Linda-Maria Dimitrova; Rasche, Frank; Berg, Gabriele; Cernava, Tomislav; Michl, Kristina; Institute of Environmental Biotechnology, Graz University of Technology, 8010, Graz, Austria; David, Christophe; Department of Agroecosystems, Environment and Production, ISARA, 23 rue Jean Baldassini, 69364, Lyon Cedex 07, France; Dumont, Benjamin; Plant Sciences Axis, Crop Science lab, ULiege - Gembloux Agro-Bio Tech, B- 5030, Gembloux, Belgium; Mårtensson, Linda-Maria Dimitrova; Department of Biosystems and Technology, Swedish University of Agricultural Sciences, P.O. Box 103, Lomma, Alnarp, Sweden; Rasche, Frank; Institute of Agricultural Sciences in the Tropics (Hans-Ruthenberg-Institute), University of Hohenheim, 70593, Stuttgart, Germany; Berg, Gabriele; Institute of Environmental Biotechnology, Graz University of Technology, 8010, Graz, Austria; Cernava, Tomislav; Institute of Environmental Biotechnology, Graz University of Technology, 8010, Graz, Austria
Background: Seed endophytes have a significant impact on plant health and fitness. They can be inherited and passed on to the next plant generation. However, the impact of breeding on their composition in seeds is less understood. Here, we studied the indigenous seed microbiome of a recently domesticated perennial grain crop (Intermediate wheatgrass, Thinopyrum intermedium L.) that promises great potential for harnessing microorganisms to enhance crop performance by a multiphasic approach, including amplicon and strain libraries, as well as molecular and physiological assays. Results: Intermediate wheatgrass seeds harvested from four field sites in Europe over three consecutive years were dominated by Proteobacteria (88%), followed by Firmicutes (10%). Pantoea was the most abundant genus and Pantoea agglomerans was identified as the only core taxon present in all samples. While bacterial diversity and species richness were similar across all accessions, the relative abundance varied especially in terms of low abundant and rare taxa. Seeds from four different breeding cycles (TLI C3, C5, C704, C801) showed significant differences in bacterial community composition and abundance. We found a decrease in the relative abundance of the functional genes nirK and nifH as well as a drop in bacterial diversity and richness. This was associated with a loss of amplicon sequence variants (ASVs) in Actinobacteria , Alphaproteobacteria , and Bacilli , which could be partially compensated in offspring seeds, which have been cultivated at a new site. Interestingly, only a subset assigned to potentially beneficial bacteria, e.g. Pantoea, Kosakonia , and Pseudomonas , was transmitted to the next plant generation or shared with offspring seeds. Conclusion: Overall, this study advances our understanding of the assembly and transmission of endophytic seed microorganisms in perennial intermediate wheatgrass and highlights the importance of considering the plant microbiome in future breeding programs.
Proposal and extensive test of a calibration protocol for crop phenology models
(2023) Wallach, Daniel; Palosuo, Taru; Thorburn, Peter; Mielenz, Henrike; Buis, Samuel; Hochman, Zvi; Gourdain, Emmanuelle; Andrianasolo, Fety; Dumont, Benjamin; Ferrise, Roberto; Gaiser, Thomas; Garcia, Cecile; Gayler, Sebastian; Harrison, Matthew; Hiremath, Santosh; Horan, Heidi; Hoogenboom, Gerrit; Jansson, Per-Erik; Jing, Qi; Justes, Eric; Kersebaum, Kurt-Christian; Launay, Marie; Lewan, Elisabet; Liu, Ke; Mequanint, Fasil; Moriondo, Marco; Nendel, Claas; Padovan, Gloria; Qian, Budong; Schütze, Niels; Seserman, Diana-Maria; Shelia, Vakhtang; Souissi, Amir; Specka, Xenia; Srivastava, Amit Kumar; Trombi, Giacomo; Weber, Tobias K. D.; Weihermüller, Lutz; Wöhling, Thomas; Seidel, Sabine J.
A major effect of environment on crops is through crop phenology, and therefore, the capacity to predict phenology for new environments is important. Mechanistic crop models are a major tool for such predictions, but calibration of crop phenology models is difficult and there is no consensus on the best approach. We propose an original, detailed approach for calibration of such models, which we refer to as a calibration protocol. The protocol covers all the steps in the calibration workflow, namely choice of default parameter values, choice of objective function, choice of parameters to estimate from the data, calculation of optimal parameter values, and diagnostics. The major innovation is in the choice of which parameters to estimate from the data, which combines expert knowledge and data-based model selection. First, almost additive parameters are identified and estimated. This should make bias (average difference between observed and simulated values) nearly zero. These are “obligatory” parameters, that will definitely be estimated. Then candidate parameters are identified, which are parameters likely to explain the remaining discrepancies between simulated and observed values. A candidate is only added to the list of parameters to estimate if it leads to a reduction in BIC (Bayesian Information Criterion), which is a model selection criterion. A second original aspect of the protocol is the specification of documentation for each stage of the protocol. The protocol was applied by 19 modeling teams to three data sets for wheat phenology. All teams first calibrated their model using their “usual” calibration approach, so it was possible to compare usual and protocol calibration. Evaluation of prediction error was based on data from sites and years not represented in the training data. Compared to usual calibration, calibration following the new protocol reduced the variability between modeling teams by 22% and reduced prediction error by 11%.