An innovative approach uses neural networking techniques to help determine how feed additives affect the health and well-being of poultry flocks.
“Poultry health and nutrition is integral to sustainable production and the feed additives landscape is becoming increasingly complex as more and more products are launched. This is especially true when looking at the number of products positioned as antibiotic replacements,” explained Will Payne, Ph.D., chief technology officer, Simple Ag Solutions Inc. during during the Virtual Poultry Tech Summit 2020.
Poultry producers often have difficulty choosing the right feed additives for their flock, while food additive manufacturers have difficulties demonstrating the efficacy of their products. While much of the poultry industry has advanced, the way that feed additives are evaluated has remained unchanged for decades.
Enter neural networking
Neural networks are a form of machine learning where computers learn to do a task through data analyzation. It is commonly used for predictive modeling.
The software “enables recommendations, delineating cause-and-effect and, most importantly, highlights value” to help predict the effectiveness of a feed additive on a broiler’s future weight, Payne said.
Better yet, the software learns more the longer it is in use, which means future recommendations could be further customized directly to a poultry farm.
“The simple platform assimilates data from the many sources that are already available, not requiring any new hardware or changes to existing houses,” he added.
The software is still in the pilot phase of development and the company is looking for poultry producers and feed additive manufacturers to participate in testing.
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