By Scout Nelson
Strategic Farming: Let’s Talk Crops! webinar on January 29, 2025, featured a discussion on crop modeling and its role in soybean production. Experts highlighted how predictive models help farmers make better management decisions.
Types of Crop Models
Crop modeling integrates weather, soil conditions, genetics, and management data to estimate yield outcomes.
Two types of models are used: mechanistic models, which rely on scientific processes to predict growth, and AI-driven models, which identify patterns from historical data. Mechanistic models offer clear explanations and accurate results, while AI models detect hidden patterns but lack transparency.
Impact of Planting Dates on Yield
One key insight from the webinar was how planting dates affect soybean yield. A 2023 study in Minnesota found that delaying planting into late May resulted in a yield loss of 0.6 bushels per acre per day, and planting in June led to a 1.5-bushel loss per day. Crop models use long-term climate data to predict these yield trends and help optimize planting schedules.
Yield Gap Approach
The yield gap is the difference between potential and actual yield. Research in 2023-2024 showed that nutrient availability was not a major limiting factor in most fields. Instead of chasing higher yields, improving efficiency might be the best strategy for maximizing profits.
Future of Crop Modeling
By using validated models, agronomists can better predict outcomes of different management practices. These models provide valuable insights into factors like row spacing, variety selection, and yield potential, helping improve decision-making in soybean production.
Photo Credits:istock-ds70
Categories: Minnesota, Crops, Soybeans