Computomics Podcast - In Conversation

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

Saison 7 · Épisode 11

jeudi 16 juillet 2026 • Durée 21:09

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.

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Deep Learning for Genomic Prediction in Plant Breeding

Saison 7 · Épisode 10

jeudi 18 juin 2026 • Durée 16:09

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.

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From Markers to Machine Learning in Predictive Plant Breeding

Saison 7 · Épisode 9

jeudi 21 mai 2026 • Durée 20:29

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.

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How Data Is Changing the Way We Grow

Saison 7 · Épisode 8

jeudi 16 avril 2026 • Durée 22:49

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:

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Breeding in 3D: Welcome to the Pangenome

Saison 7 · Épisode 7

jeudi 19 mars 2026 • Durée 21:58

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 website
Chris Kubica on LinkedIn

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

Saison 7 · Épisode 6

jeudi 19 février 2026 • Durée 18:51

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:

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

Saison 7 · Épisode 5

jeudi 22 janvier 2026 • Durée 22:14

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:

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The Future of Farming: No Fungicides, Just Genetics

Saison 7 · Épisode 4

jeudi 11 décembre 2025 • Durée 22:17

In this episode of the Computomics podcast, Pernille Ollendorff Hede, CEO and co-founder of Healthycrop, discusses the company's innovative approach to fungal-resistant crops. Healthycrop boosts the production of Nepenthesin, a naturally occurring enzyme in plants, to degrade fungal enzymes, preventing fungal growth without the need for fungicides. Using cis-genesis and gene editing techniques, Healthycrop enhances the plant's natural defense. While these techniques are classified as genetically modified (GM) in Europe, they are considered non-GM in the U.S. Pernille shares the company's mission to revolutionize agriculture by offering sustainable solutions and hopes for regulatory changes in Europe to facilitate broader adoption.

More:

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Data, Dashboards & DNA: The Life of a Bioinformatics Analyst

Saison 7 · Épisode 3

jeudi 13 novembre 2025 • Durée 23:16

In this episode of the Computomics podcast, bioinformatics analyst Michelle Hagen describes how her work bridges biology and data science. As a data analyst in bioinformatics and plant breeding, Michelle transforms raw genetic and environmental data into insights that guide breeding decisions. She particularly enjoys the teamwork, problem-solving, and creativity involved in her job.

Michelle works on Computomics’ Climate-Smart Breeding technology xSeedScore and the Metagenomics Analysis Platform MORPHEUS. Her main tasks involve performing data quality control, running bioinformatics pipelines, and creating interactive dashboards for customers. Her work supports the development of climate-resilient, high-yield crops, and it helps breeders make data-driven breeding faster and more precise.

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Inside Africa’s Leading Veg Breeding Company: The Starke Ayres Story

Saison 7 · Épisode 2

jeudi 16 octobre 2025 • Durée 25:38

Glendon Ascough, Research Director at Starke Ayres, discusses the evolution of the company from a historic seed merchant to Africa’s largest independent vegetable breeding company. He shares his personal journey into plant science, driven by a fascination with genetics, and highlights the company’s focus on breeding disease-resistant vegetable varieties tailored to local and international markets. He talks about the collaboration with Computomics, using machine learning to predict sweet corn hybrid performance. Glendon emphasizes the importance of high-quality, diverse phenotypic data and the shift in breeder mindset required for data-driven approaches.

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Apple Podcasts

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Qualité et score du flux RSS

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Podcasts Similaires Basées sur le Contenu

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