New Technology Identifies Feed Risks and Supports Better Farm Management
Artificial intelligence (AI) is creating new opportunities for livestock producers to improve feed management and reduce waste. Since feed is a major farm expense, protecting its quantity and nutritional value can help farmers control costs and improve livestock production.
The National Animal Nutrition Program (NANP) is developing a digital tool to help producers identify possible feed loss risks and review their management practices. The project involves Hector Menendez, Assistant Professor and SDSU Extension Livestock Grazing Specialist, along with Jordan M. Adams, Julia T. Silva, Karun Kaniyamattam, and Luis O. Tedeschi.
A New Tool for Feed Management
The team is developing the Feed Value Loss Risk Assessment Tool, an interactive application that combines research, expert knowledge, and machine learning. It helps producers assess conditions that may lead to feed quantity loss or reduced nutritional value during different stages of feed management.
These stages include harvesting, storage, handling, mixing, delivery, and feeding. Problems during any of these steps can reduce the amount of useful feed available to livestock.
The application uses a machine-learning method called a Random Forest model. This method examines several factors together to estimate the relative risk of feed value loss. Silage is the first feed type receiving detailed attention, while the tool is also designed to assess hay and grain management risks.
Comparing Management Practices
Producers can enter information about harvesting, storage, processing, feed mixing, delivery, and feed bunk management. The tool combines these details to provide an overall risk assessment.
Users can also adjust management conditions and compare results. This allows them to explore how different practices may affect feed loss risks and identify areas that need improvement.
The risk score does not represent the exact amount or percentage of feed lost. Instead, it indicates the relative risk associated with the selected conditions. A higher score suggests a greater risk of losing feed quantity or nutritional value.
Reducing Waste and Protecting Feed Quality
Feed losses can increase production costs and reduce the nutrients available to animals. Better management during harvesting, storage, and feeding can help producers protect feed quality and use available resources more efficiently.
The tool supports decision-making but does not replace farm experience or professional advice. Its results help producers identify potential problems and consider practical improvements.
Expert Advice Supports Better Decisions
Producers can discuss their results with members of the NANP Feed Management Committee, Extension staff, Natural Resources Conservation Service professionals, livestock nutrition specialists, and other agricultural experts. These professionals can help interpret risk assessments and recommend suitable management practices.
The tool reflects NANP's efforts to connect research, technology, and practical livestock management. As development and evaluation continue, it aims to help producers reduce avoidable feed losses, improve feeding efficiency, protect nutritional value, and support farm profitability.
Farmers, researchers, and agricultural professionals can explore additional feed management resources through the National Animal Nutrition Program website.
Advancing Livestock Feed Management
The Feed Value Loss Risk Assessment Tool brings together animal nutrition research, artificial intelligence, and expert knowledge. As development and evaluation continue, the tool aims to help livestock producers identify risks, protect feed quality, reduce waste, and improve farm profitability.
Farmers, Extension professionals, planners, and researchers can explore additional resources through the National Animal Nutrition Program website and its Feed Management Committee. Factsheets, reports, and decision-support resources also provide information to support more effective livestock feeding practices.
Photo Credit: Pexels - Tara Winstead