For agribusiness companies working across the agricultural value chain, getting ahead of major market movements such as supply disruptions and price spikes is critical. Making data-driven decisions and forecasts based on the most comprehensive data platform across global agriculture, climate, and economy will help you do just that.&nbsp;

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Gro’s daily-updating models such as the Gro Drought Index lead market-moving events up to 4 months in advance, and our global Yield Forecast Models, key indicators of price, predict end-of-season yields up to 10 months ahead of final government reporting. Designed by our team of analysts, climate scientists, and data scientists, these models monitor crop conditions daily to forecast supply-side shocks.&nbsp;

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Forecast crop production around the world with Gro's daily-updating, end-of-season yield estimates and supply modeling.

In a changing climate, Gro's short-term weather and long-term climate data are important indicators of food supply.

Gain insights into the economics behind producers' planting decisions with Gro's farmer profitability data.

Global data and predictive modeling

Gro's data and analytics are easily accessed via applications, Excel add-in, or directly through an API.

Gro's 50+ subject matter experts across climate, ag, and economics are available 24/7.

The methodology behind Gro's insights are fully transparent — this is not a “black box."

Key features

Additional Resources

Gro Intelligence has over 2 million unique, proprietary data series that address a range of questions across crop yield and production, supply and demand, growing conditions, and climate scenarios. Gro's data series are built by our team of 50+ domain experts and scaled through artificial intelligence, generating predictive models and real-time applications. Our products provide accurate forecasts and holistic views into the most pressing challenges across climate, agriculture, and the economy.&nbsp;In this report, we focus on the performance of our Global Yield Forecast Models across corn, soy, and wheat, as well as our US Planting Intentions Model and US Prevent Plant Models for corn, soy, wheat, and cotton.&nbsp;You will learn how:&nbsp;<ul><li>Historically, for the past seven years, Gro’s US Corn Yield Forecast Model has been on average within 98.3% of the USDA final January report by September. Our US Soybean Yield Forecast Model has been on average within 99% of the USDA’s final number by September for the last four years.</li><li>In critical global regions, where the current marketplace does not have many machine learning-based predictive models, such as Ukraine, Brazil, and China, Gro’s 2022 Global Yield Forecast Models were on average 95% accurate up to 10 months ahead of final government reporting.</li><li>Gro’s suite of machine-learning models provide an unprecedented combination of accuracy, global coverage, granularity down to the district level, and daily in-season updates to enable our customers to move ahead of the market.</li></ul>Download the 2022 performance report <a href="https://info.gro-intelligence.com/2022-performance-report-on-yield-forecast-and-acreage-models?utm_campaign=End%20of%20the%20Year%20Report%20-%20January%202023&amp;utm_medium=email&amp;_hsmi=2&amp;_hsenc=p2ANqtz--DAawbx4JnPmIhs6GrNfist1fGwSINeh_jnpFQ9_1aaJrTOxCIMEY1Xq-DyHJPXbhZ9TUpn5frwnku07Tb0UXCk7b3NiU9gn6sw5XtheL7Ena6_aw&amp;utm_content=2&amp;utm_source=hs_email" target="_blank" rel="noopener noreferrer">here</a>.

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2022 Performance Report: Gro Yield Forecast Models and Acreage Models

As global&nbsp;<a href="https://www.gro-intelligence.com/insights/extreme-heat-threatens-crop-prospects-around-the-world">temperatures reach historic extremes</a>, land surface temperature (LST) becomes an especially critical input when predicting the impact of heat stress on crop planting, development, production, and yield. In July, to complicate matters further, NASA’s two satellites that house MODIS sensors – which detect and measure land surface temperature among many other datasets – are experiencing an outage due to a data lapse from its Adaptive Processing System where data from several NASA satellites is processed for users.In 2022, after witnessing a series of other satellite data lapses, Gro’s research and development teams created a Gro LST measure to safeguard against outages like the one we’re experiencing now, ensuring Gro’s measurement of land surface temperature is not disrupted by a single-source outage.“Gro LST” is a generative AI model that incorporates observations from multiple LST and air temperature sources, shares information across them, and delivers a consistent and complete representation of a synthetic LST time-series. The result is an aggregated LST metric that can approximate a valid LST observation every day for all target geographies regardless of data availability from underlying LST and air temperature sources.&nbsp;While datasets ingested from the NASA MODIS sensors remain an input to Gro LST, they are one of many, ensuring Gro LST can continue to provide the same highly accurate LST values to our models.&nbsp;<figure class="image"><img src="https://res.cloudinary.com/gro-intelligence/image/upload/v1690819466/new-website/Temperature_Availability_FINAL_3ff788f51a.png"></figure>Today, Gro LST is a key input to&nbsp;<a href="https://www.gro-intelligence.com/platform/models" target="_blank" rel="noopener noreferrer">Gro’s yield forecast models</a>, preserving model performance during data disruptions or outages from other temperature sources.&nbsp;While these types of outages are relatively short-lived, they can be unpredictable and data lags can last for several weeks.&nbsp;Geospatial data disruptions or delays are caused by a number of factors including faulty satellites, government shutdowns,&nbsp;lags in availability, and even cloud cover.&nbsp;Given the current MODIS outage, the contingencies built into Gro LST have proved to be beneficial and we anticipate that there will be no practical impact to the quality of Gro’s yield forecasts.To learn more about Gro models and methodology,&nbsp;<a href="https://www.gro-intelligence.com/contact">contact a member of our team here</a>.&nbsp;

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Gro’s Temperature Generative AI Model: Building Resiliency to Data Disruption

<a href="https://www.dtn.com/">DTN</a>®, a data, analytics, and technology company, and Gro Intelligence, an AI company with a focus on agricultural markets and climate, have blended their data and modeling expertise to provide grain marketers and buyers with predictive county-level grain supply insights that can help reduce risk.&nbsp;The Gro Supply Location Monitor is a cloud-based application that connects exclusive grain market and pricing information from DTN with Gro’s AI-driven, predictive insights to better assess the economics and risk of buying, storing, and handling grain at over 4,000 facilities across the United States.Access to more precise in-season U.S. production and price data throughout the season enables companies to tap into a more accurate view of risk, investment opportunities, profit potential, and price fluctuations. Whether as a primary source across multiple facilities or as a secondary source verifying in-person monitoring, buying and lending teams can leverage the Supply Location Monitor to streamline their buying, selling, and planning processes."In today’s volatile markets grain marketers are seeking solutions that can help them reduce harvest uncertainty. We know that better data drives better decisions and with DTN pricing data and unique commodity insights as part of Gro Intelligence Supply Location Monitor, organizations can make smarter, agile decisions with confidence," said Grey Montgomery, DTN Global Leader for Strategy, Corporate Development and Growth Markets."DTN and Gro are bringing together exclusive boots-on-the-ground insights with comprehensive, real-time visibility that Gro’s satellite data coupled with AI and machine learning can add," said Jim Heneghan, SVP of Agribusiness at Gro. "This Monitor is a dynamic extension of this opportunity."Even deep on-the-ground knowledge cannot make up for the decisioning accuracy needed in the face of extreme weather events such as droughts and flooding, which has increased in-season volatility in corn and soybean yields. This past growing season, the USDA significantly lowered its final yield numbers for corn and soybeans from their original estimates, which Gro’s Yield Forecast Models - a critical input into the Supply Location Monitor - forecasted months in advance.&nbsp;In addition to Gro’s county-level Yield Forecast Models that update daily, the Supply Location Monitor incorporates Gro’s unique, proprietary data across climate and environmental conditions, Gro’s acreage estimates, as well as ingested private and public sources across historical production and harvested area to provide highly accurate in-season production and market depth information.Visit<a href="https://www.gro-intelligence.com/applications/supply-location-monitor"> here</a> to learn more about the Gro Supply Location Monitor or <a href="mailto: todd.meyer@dtn.com">contact</a> the team directly.

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Agribusiness

Maximize supply chain efficiency

Make origination and logistical decisions much sooner

Global data and predictive modeling

Yield & supply

Climate & weather

Farmer profits & budgets

Key features

Flexible platform

Analyst expertise

Transparency

Additional Resources

2022 Performance Report: Gro Yield Forecast Models and Acreage Models

Gro’s Temperature Generative AI Model: Building Resiliency to Data Disruption

DTN and Gro Intelligence Provide New Insights on U.S. Grain Facilities