Understanding the situation

Walther Farms, a leading producer of russet potatoes, faced a significant challenge with internal defects affecting its crop yield. It not only reduced the potatoes’ marketability but also reduced revenue.

Exploring the challenge

CLA’s data science and artificial intelligence team analyzed the farm’s data, helping the Walther Farms agronomist to identify the defect’s root causes and develop mitigation strategies. CLA’s study included:

  • Reviewing historical data to identify patterns and correlations with the defect
  • Creating an analytical framework to understand the influence of different variables on the defect

This analysis and interpretation resulted in the Walther Farms team being able to identify several data-driven recommendations to improve potato quality:

  • Strategic planting times — Identified strategic planting times to reduce defects and increase revenue
  • Nutrient enhancement — Suggested adjustments in nutrient application to improve potato quality

CLA’s approach emphasized the importance of ongoing data collection to refine predictive models and improve decision-making.

Achieving results

Walther Farms is now better positioned to improve its potato yield and quality, with additional potential revenues of $300,000. The organization plans to work more with CLA to design predictive tools and further improve yield. The ongoing collaboration can help Walther Farms continue to benefit from data-driven insights and strategies.

CLA’s data science and artificial intelligence team dedicated time to grasp the complexities of our internal defect challenges in russet potatoes. Their tailored analysis — informed by our specific pain points — lays a strong foundation for ongoing improvement in our agricultural practices.

Josh Reeves, CFO
Walther Farms

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