Workshop Report: Advancing Outcomes in Precision Livestock Farming
Read the workshop report from the 2023 Animal Agtech Innovation Summit, Written by Daniel Foy, CEO & Co-Founder of AgriGates, upon request from the Summit
Read the workshop report from the 2023 Animal Agtech Innovation Summit, Written by Daniel Foy, CEO & Co-Founder of AgriGates, upon request from the Summit
Join in and listen to this episode’s discussion on Machine Learning (ML) in Food Animal Agriculture: An old tool with new applications on Farm, with
Summary The use of AI in food animal farming requires consideration of data ownership and quality, as well as a proactive approach to data management.
Joining in on Digital Skills Training for Beginners in Agriculture discussion topic in this Episode are Rob Thomas and Erin Davison from LaunchCode along with
By Daniel Foy & James Reynolds DVM, MPVM Food animal welfare as a science is relatively novel and new, only spanning a few decades. For example, the
Joining in on the Data & Food animal welfare topic in this Episode are Dr. Jennifer Walker, Director of Milk Quality and cow care champion
Still, in its infancy, food animal AgriTech has barely scratched the surface of its appropriate applications, deployment, potential business models, and value in food animal
Joining this Episode are returning guests Dr. Liliana Fadul, Ph.D., who is a Data Scientist at Lactenet in Canada, Dr. Vivi Thorup, assistant professor at
With the ever-growing number of disparate, siloed, black-box, and bottlenecked digital and data tools that are on the market offering farmers a plethora of proposed
Introduction Revolutions create significant change no matter the circumstance; there are clear winners and always definite losers; we have seen this with the dotcom bubble
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In this episode, Daniel Foy, the Co-Founder & CEO of AgriGates speaks with Lilian Fadul and Michel Baldin about farm-level data, farm-level data ownership, and
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Overview With so many different data and information systems aggregating on farms and ranches today, that can be either local, cloud, sensor-based tools, and platforms,