Using Technology and Big Data to Improve Profits Matt Darr, Agricultural & Biosystems Engineering
2015 THE YEAR OF BIG DATA
Why the New Emphasis on Data Today? Autosteering and swath control technology have driven strong ROI which has led to a proliferation of GPS technology on farm. This leads to free machine data. Typical ROI in Iowa: 3.3% Planting Overlap Error, $7.89/ac 7% Tillage Overlap Error, $0.96/ac
MAJOR INDUSTRIES IN DIGITAL AGRICULTURE Recommendations Crop Modeling In Season Monitoring Production Analysis Production Benchmarking Data Warehousing Increased Value Increased Complexity
PRODUCTION BENCHMARKING
PRODUCTION BENCHMARKING Benchmarking and Data Warehousing are often packaged together as an entry level product.
Source: FarmLink
Source: Farmers Business Network
PRODUCTION ANALYSIS
PRODUCTION ANALYSIS PRODUCTION BENCHMARKING: Data analysis comparing your farm to broad aggregate results from your region looking back on historical results. PRODUCTION ANALYSIS: Data analysis comparing your onfarm practices to identify areas of performance advantages looking back on historical results.
PRODUCTION ANALYSIS: FIELD EXAMPLE 170 Acre Field, Continuous Corn
PRODUCTION ANALYSIS: FIELD EXAMPLE Hybrid A Hybrid B 170 Acre Field, Continuous Corn
PRODUCTION ANALYSIS: FIELD EXAMPLE 200 Yield Comparison of Two Hybrids in a Side-by-Side Test 176 Grain Yield (bu/ac) 150 100 50 131 0 Hybrid A Hybrid B
PRODUCTION ANALYSIS: FIELD EXAMPLE
PRODUCTION ANALYSIS: FIELD EXAMPLE $95/ac difference
PRODUCTION ANALYSIS: PROFIT BENCHMARKING
PRODUCTION ANALYSIS: PROFIT BENCHMARKING If we stop farming the lowest yielding 20% of this field we have the potential to double of per acre field profit.
PRODUCTION ANALYSIS: CROP REMOVAL FERTILITY RECOMMENDATIONS Crop Yield Potassium Removal
IN SEASON MONITORING
IN SEASON MONITORING Field level weather data. Remote sensing imagery from satellites, contracted flights, and UAVs. Shared crop scouting information from grower networks. The goal is to provide information that is either actionable during the current season or useful in changing long term crop production practices.
IMAGERY DECISION AIDS: NITROGEN MANAGEMENT
IMAGERY DECISION AIDS: NITROGEN MANAGEMENT
IMAGERY DECISION AIDS: CROP DAMAGE
IMAGERY DECISION AIDS: WATER MANAGEMENT
CROP MODELING
CROP MODELING Crop models rely on weather, soil models, and plant development models to predict both the need for and the likely response to in-season applications
PRODUCER CHALLENGES WITH EVALUATING NITROGEN MANAGEMENT PRODUCTS Growers face several challenges in utilizing current crop models for in-season decisions. Core Challenges: Variable scales Lack of broad evaluation of performance Crop practice integration Model software updates Limited customer support knowledgebase
Production Benchmarking Value Proposition Production Benchmarking Quicker changes in cultural practices. Seeding rate, Planting date, Nitrogen management, Better hybrid placement. More value opportunity for growers that are farther behind the top producers. Production Analysis Direct evaluation of products and practices that can improve on-farm yield. Generally have to lose before you win. There is always a loser in a side by side test. Variable rate plans can improve input efficiency and margins. In-season Monitoring Identify failure modes to eliminate for future years. Key aspect of a continuous improvement plan. Helpful in informing marketing decisions. Crop and Soil Modeling Better informed use of nitrogen. Technology must still be proven for widespread use.
Using Technology and Big Data to Improve Profits Matt Darr, Agricultural & Biosystems Engineering The over-all point is that new technology will not necessarily replace old technology, but it will date it. By definition. Eventually, it will replace it. It's like people who had black-and-white TVs when color came out. They eventually decided whether or not the new technology was worth the investment. ~ Steve Jobs, former CEO of Apple Inc.