Computomics Podcast - In Conversation

Computomics Podcast - In Conversation

By ComputomicsScienceNatural Sciences
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Computomics Podcast - In Conversation episodes

  • Gene editing with CRISPR and its impact on plant breeding

    In this episode we talk to Gabino Sanchez, Director Business Development at Hudson River Biotechnology (HRB). He gives detailed insights on CRISPR technology, how it evolved and that it can be a game changer for many companies. Learn about the Partnership between Computomics and HRB and the joint solution AccelATrait. Another important topic is legislation and regulations in Europe and other countries. How should edited plants be positioned versus genetically modified organisms (GMO).

    27 min
  • Trends and Hot Topics in Consumer Foods

    Learn from Cyrille about the hot topics in consumer foods from food inflation, the shift in consumer behaviour, the long term story of climate change and the reduction of emissions. What is the cause for food inflation and how does geo politics and labor affect the supply chain and with that food inflation? How does the shift in consumer behaviour impact food companies? What is quick commerce? And what role does plant breeding play in consumer foods?

    30 min
  • Insights into the Wheat Initiative and what role "Spätzle" played

    Get to know Dr. Alisa-Noemi Sieber and gain insights into the Wheat Initiative in this episode of the Computomics podcast. What is the idea behind the Wheat Initiative, who is part of it and what are first results? Additionally, learn what a pre-breeders work is and what role the Swabian specialty "Spätzle" played in the work life of Alisa. Last but not least understand what role plant breeding plays to support the UN Sustainability Goals (SDG).

    23 min
  • Insights into the MAZE project - Accessing diversity of maize to improve quantitative traits

    In this episode Prof. Dr. Chris Schön shares insights about her research especially within the MAZE project which is funded by the German Federal Ministry of Education and Research (BMBF). The goal of the MAZE project is to analyze the diversity of landraces and make them available to widen the diversity of germplasm we use today.

    More information:

    All details about the MAZE project
    Computomics' participation in MAZE Phase 2

    31 min
  • The Seed Industry, ASTA and the Future of CSS & Seed Expo

    In this first episode of season 3 we are speaking with Andy LaVigne, the President and CEO of the American Seed Trade Association (ASTA). He tells us how he ended up in agriculture, gives insights on the focus and main challenges of ASTA, explains how the pandemic changed and impacted the seed industry, shares ASTA’s plans for the setup of the CSS & Seed Expo 2021 and much more.

    27 min
  • Role of Large AGTech Corporations in Driving Innovation

    Kevin Falk is a recent PhD graduate of Iowa State University where he focused on soybean breeding, plant phenomics and image analytics. In 2019 he started with Corteva Agriscience as an Integrated Field Sciences Research Scientist where he sits on the IFS Global Innovation team. Kevin is also on the National Association of Plant Breeders education committee, has a passion for science communication and enjoys bringing his camera with them wherever he goes. This week we talk about the field of agriculture and innovation and the role that "Big-Ag" plays in driving that innovation.

    32 min
  • Predicting Phenotypes in Untested Locations

    In this episode we discuss the need to integrate environmental data into phenotype predictions. Our Computomics xSeedScore Scientist Björn leads us through what type of data is needed to untangle complex traits and how a focus on the client's needs is integral in providing data that is actionable and useful.

    20 min

About Computomics Podcast - In Conversation

From the publisher's feed

Computomics sits down with guest experts to talk AI, agriculture, farming, crops, and food - sometimes zooming out to big trends, sometimes digging into one specific research project. The question that keeps coming up: can things like machine learning actually help solve the food challenges the world's facing?