Pioneer, CHS Partnership Focuses on Animal Nutrition
Two-year project will evaluate incoming corn for more complete information on livestock feed quality.
Compiled by staff
Published: Sep 8, 2005
Providing higher energy delivery in livestock rations, Pioneer and CHS have teamed up on a cooperative pilot project to evaluate incoming corn grain for more complete information on its livestock feed to meet the needs of end-use customers.
According to a joint-statement from the two companies explains that the pilot project will be conducted over two years at a minimum of four CHS grain-handling locations beginning this year. The pilot system will incorporate proprietary NIR (near infrared) technology from Pioneer which measures Digestible Energy (DE) of the grain for monogastric animals such as swine and poultry. Knowing the DE concentration of corn grain allows feed compounders to better manage ration formulations and, hence, energy delivery to the herds and/or flocks they are feeding.
Introduction of an NIR measurement system in this pilot this year marks the first time in which corn grain DE can be directly measured and managed in a commercial grain supply chain.
This pilot is part of the Pioneer IndustrySelect program that develops and characterizes seed products and grain supply chain systems to channel grain for targeted end-use markets on the basis of specific end-use driven functionality. The goal is to provide efficient value delivery to customers through information management and targeted product development and production of grain.
The system will potentially allow CHS grain handlers to better manage corn shipments to its livestock customers with DE concentration of the shipment as part of the information package. This will allow end-use customers to better source input materials for more efficient livestock feeding programs.
Initially, four grain-handling facilities will be involved in the program; they include those at Winona, Minn.; Savage, Minn.; Davenport, Iowa; and Myrtle Grove, La. Grain channeled in this system will be positioned to export destinations in Asia and Latin America where the cost of supplying feed energy has a heightened focus.
In addition, corn growers bringing grain to the facilities will be provided with information that shows the DE content for the grain they sell, along with standard grade and non-grade factors such as test weight, damage, foreign material and moisture. The goal is to gain recognition of the amount of variation in grain nutritional functionality that exists in today's corn hybrids and provide information and management assistance to make improvements over time.
"We hope to collect better information on grain for our customers," says Rick Browne, senior vice president, CHS Grain Marketing. "We'll also strengthen the relationship with corn growers who supply our grain facilities by providing them with valuable information on the quality of their corn. This is another way we continue to serve both our grain suppliers and end-use customers."
"This is where we see the industry moving -- analyzing grain for specific end-uses at receiving, then managing and targeting grain shipments toward end-users where it will provide the most benefit," says Diane Bridgewater, vice president and business director, North American Operations, Pioneer. "This pilot project is a way for Pioneer and CHS to assist downstream grain users, as well as corn growers, to better understand the importance of nutrition variation and the positive effect that properly selected corn hybrids, coupled with efficient supply chain management, can have on improving nutritional value delivery."
Since 1981, Pioneer's team of livestock nutritionists and researchers has evaluated corn grain to determine nutritional differences between hybrids and to develop grain assay tools that can be utilized in efficient grain supply chains. Hybrids that produce grain with superior digestible energy are classified as high available energy (HAE) hybrids. During years of proprietary research, Pioneer has utilized more than 400 diverse and discrete grain samples to develop an NIT predictive model that directly predicts DE.
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