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Eavesdropping may provide animal health, welfare insights

Eavesdropping may provide animal health, welfare insights
Author: FeedStuffs
Publish date: Wednesday. August 28th, 2019

Cargill conducting pilot using machine learning to analyze chicken vocalizations.

Cargill is currently researching how audio data collected from birds on poultry farms can be used to help improve animal health and welfare, the company recently reported.

Using machine learning, a form of artificial intelligence (AI) technology, Cargill data scientists have been analyzing chicken vocalizations to try to identify patterns and changes that may signal a health or welfare problem before it is apparent to the human eye.

“Early detection of health concerns will allow for intervention to diagnose the issues and take corrective actions,” said Dries Tromp, digital lead for Cargill’s poultry business. “We are developing an approach that is focused on ensuring chickens are healthy and receive great care, which is essential to the long-term sustainability of the business.”

Cargill is conducting a pilot at two poultry farms in China, where the company operates a fully integrated poultry business. In Canada, Cargill is also using video to record data on a poultry farm that supplies its protein business. There, the company is looking at how the birds’ movements may indicate health changes over time.

In both cases, the teams have had to troubleshoot issues that come from collecting data in the farm environment. For example, they realized that natural temperature fluctuations, dust and other conditions can impact the hardware needed to collect data.

“Developing systems that work is a lengthy progress of trial and error,” said Tromp. “We are still learning and testing and are staying agile in our approach.”

The company also brought together farmers, animal science leaders and technology experts to help craft solutions.

“Together we can harness the power of digital technology to deliver safe and transparent poultry products to consumers,” said Tromp.


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