Computomics: Discussions On Innovations To Drive Advanced Agriculture Solutions

About Computomics: Discussions On Innovations To Drive Advanced Agriculture Solutions

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.

Publisher

Computomics

Category

science

Language

en

Explicit

No

First episode

29 Feb 2020

Latest episode

15 Oct 2026

Latest episodes

83 episodes in the feed.

1. 

   15 Oct 2026

   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 models Why breeding for resilience can be more important than breeding for maximum yield The challenges of applying AI and AGtech solutions across different regions and cultures Why local knowledge and trust matter when entering new agricultural markets The role of data infrastructure in making AI accessible to smaller breeding programs How to work with messy and inconsistent breeding data Computomics’ work with Chapter 54 and its exploration of opportunities across African markets Mentioned in the episode Chapter 54 (https://chapter54.com/) An accelerator supporting European scale-ups exploring opportunities in African markets. ICRISAT (https://www.icrisat.org/) The International Crops Research Institute for the Semi-Arid Tropics, an agricultural research organization with extensive work in dryland regions. Dorcus C. Gemenet (https://www.linkedin.com/in/dorcus-c-gemenet-436a1225/) 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.

2. 

   16 Jul 2026

   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 LinkedIn (https://www.linkedin.com/in/louisa-burwood-taylor/) Agfunder (https://agfunder.com/) Agfunder News (https://agfundernews.com/)

3. 

   18 Jun 2026

   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.

Who has been a guest on Computomics: Discussions On Innovations To Drive Advanced Agriculture Solutions

Names identified in recent episode analyses. Showing up to five guests.

• Pernille Ollendorff Hede
• Michelle Hagen
• Glendon Ascough
• Dr Michael Kotutwa Johnson
• Keren Moshelion

Reach and audience

Public platform figures. Ratings count people who left a rating, not total listeners.

Spotify

5.0 / 5

2 ratings

Podcast Authority Score: 54 / 100

A composite of feed quality, social presence, YouTube performance and engagement. Read the methodology.

Quality

77

Social presence

0

YouTube

0

Engagement

75

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Based on episode analysis; this does not confirm that the show is currently accepting guests.

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