The poultry and swine industries have transformed feed efficiency over the past two decades. Through systematic improvement in nutrition, enzyme utilization, and animal genetics, they now produce vastly more protein from fewer resources. The challenge is not simply reducing methane emissions from cows, but reducing methane per unit of milk produced while maintaining farmer profitability and food security.

But here's the complexity: feed intake in dairy cattle is difficult to measure in controlled research facilities; in pasture-based systems where 88% of global cattle graze, measurement becomes extraordinarily challenging. Yet without precise data, researchers cannot translate laboratory findings into reliable commercial recommendations. This measurement gap between what science discovers and what farmers can practically implement represents agriculture's critical bottleneck. When you combine this with the variability in dairy systems—roughly 20% natural variation in methane emissions even among genetically similar control animals—the path forward requires nuanced, system-level analysis rather than simple silver bullets.

Today we are joined by Ermias Kebeab from UC Davis, whose research demonstrates that genetic selection offers a permanent, cumulative, and heritable pathway to improved feed efficiency. Kebeab's recent work evaluated the EcoFeed index developed by STgenetics, a genomic breeding value tool based on over 10,000 animals—7,623 growing Holstein heifers and 2,538 lactating cows. Results showed that selecting for improved residual feed intake (RFI) reduces lifetime emissions without compromising productivity. A one-standard-deviation improvement in genomic RFI decreased feed consumption by 2.73% and reduced lifetime CO2 equivalent emissions by 2.42% per animal—equivalent to 868 kg CO2e savings per cow. A three-standard-deviation improvement showed even greater potential, reducing feed intake by 8.2% and emissions by 7.31%, while simultaneously lowering feed costs by $199 per female.

Ermias's research bridges research discovery with practical implementation across both the Global North and Global South. Kebeab's work on grape pomace byproducts—incorporated at 10-15% of dairy rations—demonstrates milk yield improvements alongside methane intensity reductions, while pre-fermenting almond hulls shows additional potential when economic trade-offs are favorable.

Crucially, he emphasizes that the Global South's emissions reduction challenge differs fundamentally from the North. Where dairy systems produce less than 2,000 kg milk annually, the priority must be productivity improvement rather than limiting animal numbers. Rising energy and fertilizer costs disproportionately impact low and middle-income countries, making locally-adapted tropical breeds and resilient farming systems more viable than input-intensive Western genetics.

Send us Fan Mail

Artificial intelligence is advancing at an astonishing pace—improvements measured in five-thousand-fold increases from week to week according to AI researchers at Singularity University. Yet in agriculture, most farmers remain largely disconnected from these advances, using AI only at the most basic level for administrative tasks like finance, report writing, and form filling. This widening gap threatens to leave the agricultural sector further and further behind as the world accelerates into what might be called the "bullet train moment" of AI adoption.

Today we are joined by Aidan Connolly, CEO of Agritech Capital, who has spent the past years advising agricultural organizations on AI readiness. Aidan joins Ash Cloud to discuss how to restructure agricultural businesses for AI-driven decision-making without waiting for others to lead the way.

The big challenge is that AI systems can only work with the data available to them. In agriculture, that data is fundamentally flawed. Most farm information is still captured by humans in notebooks, then transcribed into databases. Each step introduces errors, misinterpretation, and gaps that make datasets unsuitable for the sophisticated decision-making AI promises to deliver. Meanwhile, the major AI companies racing forward at incomprehensible speeds won't wait for agriculture to catch up.

When you consider that farmers are constantly gathering sensory information through sight, sound, and observation while working in the field, data that never enters any database, the informational chasm becomes even more apparent. Yet animal production systems offer unique opportunities. Dairy cows milked three times daily provide recurring windows to assess milk quality, animal health, fertility, and nutrition. Hens laying eggs daily, pigs weighed multiple times, animals with collars and sensors, these continuous data streams contain vastly more untapped value than the sector has realized.

Send us Fan Mail

“I’m yet to meet a grazier that doesn’t want a 5-15% feed conversation ratio improvement.” says Tom Williams, CEO of Number 8 Bio.

Producers motivated by not losing 10% of their feed to the atmosphere.

Enteric methane from livestock represents one of the rare climate challenges where environmental impact aligns with economic opportunity. Methane is a potent greenhouse gas and it also represents wasted nutrition. Approximately 10% of feed energy consumed by ruminants escapes as methane rather than supporting growth or milk production. Few climate solutions offer both emissions reduction and immediate productivity gains for those implementing them.

But here's the challenge: the rumen contains billions of microorganisms competing, collaborating, and interacting across complex metabolic pathways. Human knowledge of this biological complexity remains incomplete. Finding molecules that reduce methane without compromising animal health or performance requires casting an extraordinarily wide net.

Today we are joined by Tom Williams, founder and CEO of Number 8 Bio, a synthetic biology company developing feed additives to reduce enteric methane emissions.

Number 8 Bio's journey demonstrates rapid adaptation to scientific reality. Initially engineering yeast to produce bromoform and seaweed molecules, the team quickly recognized cost barriers for feed additive markets. They pivoted entirely, developing an automated in vitro rumen screening system processing approximately 100 tests weekly. Over several years, they screened thousands of potential products—peptides, enzymes, probiotics, natural extracts, small molecules, and combinations—seeking winners through systematic trial rather than theoretical prediction.

The company now focuses on a single organic molecule showing methane reductions and productivity improvements in grazing systems. Initial feedlot trials revealed hydrogen buildup and intake reductions, so Williams followed the science toward pasture-based applications first. The discovery platform—now enhanced with bioreactors predicting live animal productivity outcomes—positions Number 8 Bio to develop additional molecules for different markets and stacking strategies as regulatory pathways allow.

Send us Fan Mail