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Additional file 9: Table S3. CAZy families of the caecum. Table showing the relative abundance (calculated from the emPAI score) of eukaryotic and prokaryotic CAZy families identified in the proteomic analysis of the caecum content of L. pedicellatus. File format .DOCX.

Additional file 1. Containing Q-Q plots of GWAS

There is growing awareness among governments, businesses, and the general public of risks arising from changes to our climate on time scales from months through to decades. Some climatic changes could be unprecedented in their harmful socioeconomic impacts, while others with adequate forewarning and planning could offer benefits. There is therefore a pressing need for decision-makers, including policy-makers, to have access to and to use high-quality, accessible, relevant, and credible climate information about the past, present, and future to help make better-informed decisions and policies. We refer to the provision and use of such information as climate services. Established programs of research and operational activities are improving observations and climate monitoring, our understanding of climate processes, climate variability and change, and predictions and projections of the future climate. Delivering climate information (including data and knowledge) in a way that is usable and useful for decision-makers has had less attention, and society has yet to optimally benefit from the available information. While weather services routinely help weather-sensitive decision-making, similar services for decisions on longer time scales are less well established. Many organizations are now actively developing climate services, and a growing number of decision-makers are keen to benefit from such services. This article describes progress made over the past decade developing, delivering, and using climate services, in particular from the worldwide effort galvanizing around the Global Framework for Climate Services under the coordination of UN agencies. The article highlights challenges in making further progress and proposes potential new directions to address such challenges.

Additional file 7. Full derivation of the fitness function used for in silico evolution of organic acid production.

Producing probabilistic subseasonal forecasts of extreme events up to six weeks in advance is crucial for many economic sectors. In agribusiness, this time scale is particularly critical because it allows for mitigation strategies to be adopted for counteracting weather hazards and taking advantage of opportunities. For example, spring frosts are detrimental for many nut trees, resulting in dramatic losses at harvest time. To explore subseasonal forecast quality in boreal spring, identified as one of the most sensitive times of the year by agribusiness end users, we build a multisystem ensemble using four models involved in the Subseasonal to Seasonal Prediction project (S2S). Two-meter temperature forecasts are used to analyze cold spell predictions in the coastal Black Sea region, an area that is a global leader in the production of hazelnuts. When analyzed at the global scale, the multisystem ensemble probabilistic forecasts for near-surface temperature are better than climatological values for several regions, especially the tropics, even many weeks in advance; however, in the coastal Black Sea, skill is low after the second forecast week. When cold spells are predicted instead of near-surface temperatures, skill improves for the region, and the forecasts prove to contain potentially useful information to stakeholders willing to put mitigation plans into effect. Using a cost–loss model approach for the first time in this context, we show that there is added value of having such a forecast system instead of a business-as-usual strategy, not only for predictions released 1–2 weeks ahead of the extreme event, but also at longer lead times.

Additional file 4. Detailed calculation for estimated gains of using a marker in breeding

Additional file 5: Table S15. Index numbers of mutations and corresponding reactions and mutation effects.

Additional file 1. The file provides the Additional Tables S1–S14.

Additional file 7. Field trial GPS coordinates

Additional file 9. Containing a report of Genotyping by Sequencing (GBS) – Reference Pipeline

Additional file 7. Full derivation of the fitness function used for in silico evolution of organic acid production.

Additional file 6. The file provides the additional Figures S1–S15.

Additional file 5: Table S15. Index numbers of mutations and corresponding reactions and mutation effects.

Additional file 1. The file provides the Additional Tables S1–S14.

Large amounts of agricultural wastes are rich in pectins that, in many cases, disrupt the processing of food residues due to gelation. Despite pectins being a promising sustainable feedstock for bio-based chemical production, the current pathways to produce platform molecules from this polysaccharide are hazardous and entail the use of strong acids. The present work describes a sequence of biocatalyzed reactions that involves 1) the extraction of pectin from sugar beet pulp and enzymatic recovery of galacturonic acid (GalA), followed by 2) the enzymatic oxidation of the GalA aldehyde and the recovery of galactaric acid (GA), and 3) the biocatalyzed polycondensation of GA to obtain fully bio-based polyesters carrying lateral hydroxy functionalities. The acid-free pectin extraction is optimized using enzymes and microwave technology. The conditions for enzymatic oxidation of GalA allow the separation of the GA produced by a simple centrifugation step that leads to the enzyme-catalyzed polycondensation reactions.

Background Aspergillus niger fermentation has provided the chief source of industrial citric acid for over 50 years. Traditional strain development of this organism was achieved through random mutagenesis, but advances in genomics have enabled the development of genome-scale metabolic modelling that can be used to make predictive improvements in fermentation performance. The parent citric acid-producing strain of A. niger, ATCC 1015, has been described previously by a genome-scale metabolic model that encapsulates its response to ambient pH. Here, we report the development of a novel double optimisation modelling approach that generates time-dependent citric acid fermentation using dynamic flux balance analysis. Results The output from this model shows a good match with empirical fermentation data. Our studies suggest that citric acid production commences upon a switch to phosphate-limited growth and this is validated by fitting to empirical data, which confirms the diauxic growth behaviour and the role of phosphate storage as polyphosphate. Conclusions The calibrated time-course model reflects observed metabolic events and generates reliable in silico data for industrially relevant fermentative time series, and for the behaviour of engineered strains suggesting that our approach can be used as a powerful tool for predictive metabolic engineering. Electronic supplementary material The online version of this article (10.1186/s13068-017-0950-6) contains supplementary material, which is available to authorized users.