Computomics Podcast - In Conversation

Computomics
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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? New episodes drop every third Thursday, every other month, in an interview format. Experts talk on biotech and agriculture, real project examples, a look at upcoming events, and plenty on AI, genomics, and where plant breeding is headed.

  1. 5d ago

    S8 E1 - Can AI Make Plant Breeding More Accessible?

    In the first episode of Season 8, Felix Sattler, our very own ;) Bioinformatics Analyst at Computomics, talks about predictive breeding, environmental modeling, and the role of data in improving breeding decisions under challenging growing conditions. Drawing on his pearl millet research in West Africa, Felix reflects on how breeding analytics have evolved from simpler statistical approaches to models that combine genomic, phenotypic, and environmental data. The conversation also looks at genotype-by-environment interactions, field trial design, data quality, and the importance of setting breeding targets that reflect local conditions rather than focusing on yield alone. A broader theme runs through the episode: advanced analytics can only create value when they are paired with the right infrastructure, local knowledge, and practical understanding of how crops are grown and used. Listen to Season 8, Episode 1: Can AI Make Plant Breeding More Accessible? In this episode Using rainfall, humidity, soil, radiation, and other environmental variables in predictive modelsWhy breeding for resilience can be more important than breeding for maximum yieldThe challenges of applying AI and AGtech solutions across different regions and culturesWhy local knowledge and trust matter when entering new agricultural marketsThe role of data infrastructure in making AI accessible to smaller breeding programsHow to work with messy and inconsistent breeding dataComputomics’ work with Chapter 54 and its exploration of opportunities across African markets Mentioned in the episode Chapter 54 An accelerator supporting European scale-ups exploring opportunities in African markets. ICRISAT The International Crops Research Institute for the Semi-Arid Tropics, an agricultural research organization with extensive work in dryland regions. Dorcus C. Gemenet Works with CGIAR-NARS crop breeding programs and was highlighted by Felix as someone working to make new breeding technologies more accessible, including for smallholder farmers and breeding programs in regions such as the Sahel.

    S8 E1 - Can AI Make Plant Breeding More Accessible?

  2. Jul 16

    Agriculture, AI, and the Search for Real-World Impact

    If you are interested in the future of agri-food innovation, this episode offers a clear view of where the sector stands today: more practical, more disciplined, and more focused on technologies that can prove their value in the real world. In the final episode of Season 7 of the Computomics Podcast, we speak with Louisa Burwood-Taylor, Chief Communications and Intelligence Officer at AgFunder, a global venture capital investor working at the intersection of agri-food, AI, biology, climate, and deep tech. Louisa explains why agriculture remains one of the most challenging sectors for startups. A technology may be scientifically strong and technically impressive, but it still has to work across different soils, crops, climates, production systems, and growing cycles. In agriculture, innovation only matters if it can create real value for growers, supply chains, and the wider food system. The episode also looks at the growing role of multi-sector platforms, corporate partnerships, biologicals, robotics, physical AI, and the connection between agriculture, nutrition, and human health. From precision robotics to self-driving labs, Louisa shares a practical and optimistic perspective on where agri-food innovation is heading next. Companies and people mentioned: AgFunder, Verdant Robotics, Gabe Sibley (Verdant Robotics), Reservoir Farms, Atinary, Bayer, John Deere, and Bear Flag Robotics. Louisa Burwood-Taylor on LinkedInAgfunderAgfunder News

    Agriculture, AI, and the Search for Real-World Impact

  3. Jun 18

    Deep Learning for Genomic Prediction in Plant Breeding

    In this Computomics Podcast episode, we launch the new “Make Sense of Science” explainer series, a format designed to break down complex scientific and technical topics into clear, accessible conversations. In this first episode, Computomics machine learning scientist Alaukik Saxena introduces deep learning for genomic prediction in plant breeding. He explains how breeders use DNA marker data, field data, and environmental information to predict important plant traits such as yield, flowering time, or plant height, often before new plants are even grown. The episode also looks at why this is such a challenging task: breeding data is complex, environments differ greatly, and models can easily give overly optimistic results if they are not tested carefully. Alaukik also explains the difference between classical statistical models, machine learning, and deep learning, and where each approach has its strengths. A key message of the episode is that good models depend on good data. Better phenotyping, smarter experimental design, and realistic validation are just as important as the algorithms themselves.

    Deep Learning for Genomic Prediction in Plant Breeding

  4. May 21

    From Markers to Machine Learning in Predictive Plant Breeding

    In this episode of the Computomics podcast, Dr. Rex Bernardo discusses the evolution of predictive plant breeding, from early molecular markers to today’s machine learning and AI approaches. He explains how these tools can support not only trait prediction, but also more complex breeding decisions, such as whether a line is likely to be selected or become a successful variety. The conversation also highlights community-focused work on leafy African vegetables in Minnesota and reflects on how plant breeding education must evolve to prepare future breeders for a more interdisciplinary, data-driven field.

    From Markers to Machine Learning in Predictive Plant Breeding

  5. Apr 16

    How Data Is Changing the Way We Grow

    In this episode, Darryn Keiller, Futurist, Entrepreneur, and founder of WayBeyond, discusses how digital agronomy helps growers make better decisions with data. He explains how farms can combine sensor, environmental, plant-response, and satellite data to improve daily decisions, predict risks, and raise yield and fruit quality. The conversation also covers the challenges of introducing new technology into agriculture, especially around trust and data ownership. Darryn argues that AI will not replace growers, but support them by closing knowledge gaps, and helping younger professionals adapt faster. It also enables farming systems to respond better to climate change, labor shortages, and growing production pressures. More: Darryn Keiller on LinkedInWayBeyond Homepage

    How Data Is Changing the Way We Grow

  6. Mar 19

    Breeding in 3D: Welcome to the Pangenome

    Chris Kubica, Technical Account Manager at Computomics, discusses the importance of pangenomes for modern plant breeding. He explains that traditional genomics relies on a single reference genome, which cannot capture the full genetic diversity of a species. This is a big problem in complex plant genomes, where major parts of breeding-line diversity can be absent from the standard reference. A pangenome combines multiple assemblies to represent more of a species’ variation and to unlock hard-to-find trait signals. Chris introduces Pantograph, Computomics’ “omics browser”, which allows users to visualize and explore structural variation and integrate diverse omics data such as gene expression and variant information. Hear about current and planned capabilities in this informative and enjoyable episode!  More: Pantograph websiteChris Kubica on LinkedIn

    Breeding in 3D: Welcome to the Pangenome

  7. Feb 19

    From Genes to Farmers’ Fields: The Complex World of Potato Breeding

    This episode of the Computomics Podcast features Vanessa Prigge, potato breeder and R[&]D project manager at Saka Pflanzenzucht (Solana Group). She discusses her international research background, the unique challenges of potato breeding - such as vegetative propagation, complex genetics, and long breeding cycles - and the need for compromise-driven selection. Vanessa highlights two major projects: IPMorama, which promotes integrated pest management through resistant varieties, monitoring, and stakeholder collaboration, and POMORROW, which unlocks potato gene bank diversity for future-proof breeding. Together, these efforts aim to make potato breeding more sustainable, collaborative, and future-ready.. More information: Solana Main PageIPMorama Project WebsitePOMORROW project (German language)Vanessa on LinkedIn

    From Genes to Farmers’ Fields: The Complex World of Potato Breeding

  8. Jan 22

    Cold Chains, Climate, and Cutting-Edge Tech: The Future of Produce

    In this episode of the Computomics podcast, Vonnie Estes, VP of Innovation at the International Fresh Produce Association (IFPA), shares insights on the challenges the produce industry faces, particularly around climate change, pest management, and cold chain logistics. She discusses the importance of AI and machine learning in enhancing supply chain efficiency and food safety. Vonnie also highlights IFPA’s initiatives, such as "Supply Chain of the Future" and efforts to reduce single-use plastic in packaging. A grant program supports innovation in the produce sector, offering funding opportunities for startups in developing solutions to industry problems. More: Vonnie Estes on LinkedInInternational Fresh Produce Organization (IFPA)The Fresh Supply Chain of the FutureFresh Takes on Tech podcast

    Cold Chains, Climate, and Cutting-Edge Tech: The Future of Produce
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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? New episodes drop every third Thursday, every other month, in an interview format. Experts talk on biotech and agriculture, real project examples, a look at upcoming events, and plenty on AI, genomics, and where plant breeding is headed.

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