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What Should Farmers Know About Climate Change? Livestock & Carbon Sequestration

By Jonathan Reinbold

Here’s an interesting paradox: livestock is both a major contributor to and a solution for excess carbon in the atmosphere, which is intensifying climate change. The most conservative estimates suggest that raising livestock accounts for nearly 15% of global greenhouse gases emitted each year; the most comprehensive assessments of emissions say more than 50%. However, when herbivores are removed from the land – whether they are wild or domesticated – the land deteriorates. When grasslands are undergrazed, soil health declines and carbon is lost.

Grasslands occupy 31% to 43% of the global land area, and store 28% to 37% of the terrestrial soil organic carbon pool. Practices that increase forage production, such as fertilization, irrigation, sowing favorable grasses and forbs, intensive grazing management, and conversion from cultivation to well-managed pasture, provide the opportunity to sequester atmospheric carbon and enhance soil organic matter.
Improved grazing can sequester between one-half to three tons of carbon per acre per year.

Improved grazing management practices in grasslands could sequester about 409 million tonnes of carbon per year, globally. Grazing land and pasture management practices that increase soil carbon stocks can significantly mitigate carbon emissions and may present opportunities for profitable investment in mitigation.

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What Successful AI Implementation Looks Like in the Protein Industry | Ben Allen, CEO of BinSentry

Video: What Successful AI Implementation Looks Like in the Protein Industry | Ben Allen, CEO of BinSentry

In this conversation, Ben Allen, CEO of BinSentry, explores what separates successful AI implementation from early experimentation across the protein industry. As producers begin integrating artificial intelligence into their operations, the most effective implementations share common themes: strong data foundations, practical use cases, and a focus on solving real operational challenges. Ben discusses why data quality and integration are essential for AI to deliver meaningful results, and why technology alone is not enough. Successful adoption also depends heavily on people, training, and company culture, ensuring teams understand how to use new tools and trust the insights they provide. Looking ahead, the conversation highlights the steps protein producers can take today—from improving data infrastructure to embracing digital tools—to position their operations for long-term success in an increasingly AI-driven industry.