Proven Solutions
Analyze past trends and anomalies to understand their impact on field productivity to answer: What happened and why?
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Conduct historical time-series analysis to identify field trends, particularly focusing on nutrient and water content.
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Utilize spectral analysis to compare past minimum and maximum values with current field conditions.
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Assess how different field groups responded to various weather conditions.
Start an in-season continuous improvement process in collaboration with Digital Harvest:
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Set alerts for early anomaly detection and compare with historical benchmarks.
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Make data-driven decisions for field actions based on insights gained from historical analysis.
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Continuously monitor field responses to actions for ongoing improvement.
Predictive analytics: What will happen?
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Use a digital model that correlates a field's inputs—like fertilizer, water, and temperature—to its output, such as yield.
Optimization: What actions should be taken for better outcomes?
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Simulate and evaluate various scenarios digitally to observe how outputs change in response to different inputs.
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Digitally test potential solutions and compare them to determine the optimal input-output parameters.