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Iteris signs ClearAg agreement with Valent USA
Sep. 14, 2015
Valent U.S.A. LLC
United StatesFollow
United StatesIteris, Inc., a company who providing information solutions to the transportation and agriculture markets, has entered into an agreement with Valent U.S.A. Corporation (Valent), to provide premium, field-level weather, soil content, and crop protection product performance applications through ClearAg™ application programming interfaces (APIs); meteorological and agronomic professional services; and, data science and engineering services. Iteris’ ClearAg APIs and technology and professional resources will support Valent with data acquisition and analysis of crop protection product performance related to weather, soil conditions, and various other factors affecting crop production in the U.S.
Specifically, Iteris will provide Valent with access to current, historical, climatological, and forecasted, field-level weather conditions, as well as crop canopy-level soil moisture and temperature information at varying depths beneath the ground surface. Iteris’ ClearAg meteorologists, agronomists, and scientists will support Valent crop experts to investigate relationships between crop responses and weather and soil conditions over time.
Additionally, Iteris and Valent will collaborate to develop systems that permit customized field or zone modeling capabilities so that soil, vegetation, and/or topographic properties can be specified as a factor in the diagnosis or prognosis of how soil temperature and moisture conditions impact crop growth at several different depths within a soil profile. Iteris will help analyze detailed ClearAg-based datasets and surface elevation data, and provide analytics to deliver custom field modeling capabilities to Valent.
“We look forward to partnering with Valent to deliver unique crop protection analytics products so that our partners can enhance their product performance, providing more effective and cost-efficient products, and by providing better tools and information to Valent staff,” said Tom Blair, senior vice president of Performance Analytics at Iteris. “By leveraging ClearAg content and Iteris’ meteorology, agronomy, and data science experts, Valent can enhance recommendations to producers on what crop protection products to use and when to apply those products for optimum cropping results.”
Valent offers innovative, effective solutions to help growers and farmers produce high quality, high yield crops. As a leader in marketing and sales of both traditional biorational products, Valent’s products include a well-known line of quality herbicide, insecticide, fungicide, and plant growth regulator products for agricultural, seed protection, and professional use.
“Valent U.S.A. Corporation is committed to providing customer-centric farming solutions that leverage the latest technology for our customers, both through our product line, and in the data intelligence available today,” said Eric Johnson, vice president of technology at Valent. “As a result of our partnership with Iteris, Valent will be able to provide our customers with access to pertinent weather and soil information as it relates to crop growth stages. As a result, producers can determine when to apply crop protection product to enhance product performance and response.”
ClearAg is a decision support application for precision farming built upon the ClearAg EMPower™ adaptive forecasting engine, an advanced learning platform for agriculture. As new information becomes available, the ClearAg system adapts to provide the most accurate, location-based information available on a worldwide basis. ClearAg’s patented technologies combine global, multi-sensor weather analyses, ensemble-based weather forecasting, customized soil modeling, and a staff of expert meteorologists to create what the firm believes to be the most accurate, science-based environmental information available. ClearAg leverages Iteris’ precision weather and global soil content with the power of agronomic models to solve complex agricultural challenges.
Source: ClearAg
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