Helps producers measure forage nutrient values while harvesting and at feeding
To help beef and dairy producers more accurately and quickly measure certain nutrient values of the forages they’re harvesting and feeding their livestock, John Deere is introducing the new HarvestLab™ 3000. When mounted to John Deere self-propelled forage harvesters, HarvestLab 3000 can monitor forage constituents at harvest, or it can be removed and used in stationary mode to evaluate forage nutrient quality at feeding.
John Deere HarvestLab 3000 uses Near-Infrared Spectroscopy (NIRS) to evaluate constituent characteristics such as moisture, dry matter, protein, starch, neutral detergent fiber (NDF) or acid detergent fiber (ADF). Results are immediate and allow owners to take more frequent and representative samples rather than relying on periodic, non-representative samples measured via wet-chemistry analysis. In the field, broader light spectrum measures up to 10 nutrient values 4,000 times per second, providing permanent, real-time data gathering. Operators can view constituent measurements while harvesting and then quickly make on-the-go adjustments to maximize feed quality.
When mounted to forage harvesters, HarvestLab 3000 offers integrated, automatic length of cut adjustments based on moisture ranges preset by the operator. This feature helps ensure optimum bunker density and high-quality silage. In addition, inoculants can be more precisely applied during harvest based on sugar and dry-matter readings. The end result is high-quality silage with greater feed value and reduced spoilage.
HarvestLab 3000 can be used to map and document important crop characteristics such as moisture or starch content in different forage crops and silage tops. “This is a huge benefit for beef and dairy producers, custom harvesters and livestock nutritionists wanting to optimize the nutritional value of the feed,” said John Mishler, John Deere precision-ag technology tactical marketing manager. “These nutrient values can be wirelessly transmitted to the John Deere Operations Center for analysis, future crop and nutrient application planning and for archiving field and crop history.”
Utilizing the stationary mode of HarvestLab 3000, nutritionists can analyze feed rations for crude protein, fiber, and other characteristics to adjust rations for optimal nutrition and to reduce feed variability. Different forages and silages can be measured as often as possible. These measurements guarantee precise tracking of the silage put into the bunk or silo, and the quality changes taking place in the silage, before its put into a dairy ration.
Traditional laboratory analysis expense and time delays are eliminated when using HarvestLab 3000. For custom harvesters, this drives down ownership costs, and simplifies customer invoicing by providing new levels of detail previously unavailable.
Compared to its predecessor, HarvestLab 3000 offers many improvements. “The unit’s memory has been expanded from 32 MB to 2 GB and the user’s web interface has been improved. Saving history data is now possible, and advanced diagnostics make it easier for users to more quickly troubleshoot issues if they arise,” Mishler said.
Customers can add Harvest Lab to their model year 2018 orders for John Deere self-propelled-forage harvesters. For customers wanting to field install a HarvestLab 3000 or to purchase a stand-alone unit, it will be available to order later this fall. For more details visit johndeere.com or talk with your local John Deere dealer.
Deere & Company (www.JohnDeere.com) (NYSE: DE) is a world leader in providing advanced products and services and is committed to the success of customers whose work is linked to the land – those who cultivate, harvest, transform, enrich and build upon the land to meet the world’s dramatically increasing need for food, fuel, shelter and infrastructure. Since 1837, John Deere has delivered innovative products of superior quality built on a tradition of integrity. For more information, visit John Deere at its worldwide website at www.JohnDeere.com.