Daniel Fischer

I am currently trying out, how to create a sour-dough bread from scratch. For that, I first started my sourdough starter by mixing 50g rye flour and 50g water into a bowl with loose lid and kept it in our warm, technical room. After 24h I added again 50g rye flour and 50g water, mixed it and put it back to the technical room for 24h. Then on the second day, I added 100g of rye flour and 100g of water (just to remain the 1:1:1 ratio, indicating that the existing sourdough should match the newly added flour and water). On the third day, I took then 200g of the mixture away and added again fresh 100g flour and 100g water. That I did in total three times. During the time I could see that the dough started to small sourish, beer-alike with the fruity note, so not bad at all. When that happened, I decided to go for the first bread.

I mixed in the lunch break

• 100g sour-dough
• 300g Wheat flour
• 200g Rye flour
• 350 ml water
• 12g salt

and placed it for resting 30 minutes (covered with a towel in a bowl). Then I roughly folded and pulled it and placed the dough a cast-iron pot with a floured bottom. That bowl I covered again with a towel and let it rest at room temperature until evening (for about 6 hours). Then I placed the dough in the casst-iron pot into the fridge to let it rest for the night.

On the next day in the morning, I took out the pot to let it warm up a little at room temperature (for about an hour, during breakfast). Here I also sprinkled some wheat flour over it and cut some stripes into it. I then pre-heated the oven to 230 degrees and placed water in the bottom of the oven (I have an oven that has a build-in water bowl to steam, it is a bread program). Once it reached temperature, I added the pot (without lid) into it and backed the bread for about 20 minutes. Then I lowered the temperature to 200 degrees and backed for another 25 minutes.

From the remaining started, I took another 100g away, leaving me with 100g remaining starter, where I added again 100g flour and 200g water, placed it in a warm room for 3-4 hours and placed it then into the fridge.

When I bake then next week, my plan is to out 50g one day before baking day, add 50g flour and 50g water and let it activate 24h. From there I can take then 100g for the backing again. The root I’ll keep then in the fridge, but here I need to see still how to keep it fresh and happy in the fridge.

Introduction

When running computationally intensive workflows with Snakemake, you might encounter issues where too many jobs are running in parallel, causing excessive I/O load, memory pressure, or high latency on your hard drive. This can lead to failed jobs or degraded performance.

Snakemake provides a way to limit parallel execution per rule using the resources directive, but this only works if you also specify a global resource limit when executing the workflow.

In this blog post, we will demonstrate how to properly limit the number of parallel jobs for a specific rule using Snakemake’s resource management system.

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The Problem: Too Many Jobs Running at Once

Consider the following Snakemake rule:

rule process_data:
    input:
        "{sample}.raw"
    output:
        "{sample}.processed"
    resources:
        process_data_jobs=1  # Assign a resource unit for limiting the number of jobs
    shell:
        """
        some_tool --input {input} --output {output}
        """

Why Doesn’t resources Alone Limit Job Execution?

You might expect that setting resources: processing_jobs=1 would automatically limit Snakemake to running only 1 job at a time. However, Snakemake does not enforce resource-based scheduling unless you specify a global limit when launching the workflow.

Without a global limit, Snakemake may still launch too many jobs in parallel, overloading your system.

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The Solution: Enforce Resource Limits

To actually restrict the number of parallel jobs, run Snakemake with:

snakemake --resources process_data_jobs=10

How Does This Work?

• Each job of process_data requests 1 unit of process_data_jobs.
• The global limit processing_jobs=10 ensures that at most 10 jobs (10 / 1 = 10) run in parallel. You can also set different units, if you like

Before setting this limit, too many jobs could be running at once! After applying it, only 10 jobs were allowed to run simultaneously.

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Conclusion

If you are facing high disk latency, I/O pressure, or excessive job execution in Snakemake, the best way to control it is by:

1. Using resources to define per-job resource requirements.
2. Setting a global resource limit (--resources processing_jobs=10) when executing Snakemake.

This approach ensures your workflow runs efficiently and reliably without overloading your system!

Timothy (Phleum pratense L.) is a key forage grass for Finnish agriculture, and improving its yield, winter hardiness, and digestibility is crucial for sustainable production. Our recent study explored the potential of genomic prediction to accelerate breeding progress by leveraging genotyping-by-sequencing and advanced statistical models.

Key findings:
* Heritability estimates ranged from 0.13 (yield at first cut) to 0.86 (digestibility at second cut).
* Genetic correlations suggest trade-offs between yield and winter survival but positive links between digestibility traits.
* Genomic breeding values were estimated using advanced statistical approaches, including a novel scaling of the genomic relationship matrix.
* Predictive ability reached up to 0.62 for digestibility, and validation confirmed moderate accuracy with little dispersion.

Despite concerns that genotype quality might impact predictions, our results show that genomic prediction remains a powerful tool for Timothy breeding in Finland. This research highlights the potential for data-driven breeding strategies to enhance forage crop resilience and quality.

https://link.springer.com/article/10.1007/s00122-025-04860-9

This Christmas we have been to Pälkäne, a little municipality close to Tampere. There is a old church from the 15th century that lost the roof in a storm in the 19th century (as far as I remember from what I read) and now, since 15 years they started using it again for services. However, they plan to build a new (glass-) roof to it, so this year was the last time the service took place in this type.

🌱 Discover Tribiome: a pioneering European project that delves into the complexities of microbiomes in agriculture.

Soil microbiomes 🌿 play a crucial role in the transition towards more sustainable agriculture. By understanding and harnessing this microscopic world 🦠, we can find solutions to current challenges related to the environment, food security, and climate change. 🌾

📹 Watch the presentation video of Tribiome, initiated by Wagralim, the Agri-Food Innovation Cluster of Wallonia and its partners with the help of Studio Chamberlin and learn more about this groundbreaking project:

Wagralim, the Agri-Food Innovation Cluster of Wallonia | ITENE | Universidad de Burgos | ASAJA (Asociación Agraria-Jóvenes Agricultores) | ValGenetics | SIMAVI Software Imagination & Vision | Rete Semi Rurali ETS | Natural Resources Institute Finland / Luonnonvarakeskus | Particula Group | Grupo Fertiberia