Industry-Leading Predictive Models
XLSOR technology utilizes advanced Machine Learning models and precise calibration to account for variability in fruit from different regions, seasons, developmental status, and pre- and post-harvest conditions. XLSOR’s models can be customized for various fruit varieties in any growing region worldwide.
The XLSOR Process
Data Collection
XLSOR collects essential orchard data, including bloom time and location.
Fruit Scanning
2 or 3 in-orchard scans occur throughout the season, assessing sweetness, ripeness, chlorophyll levels, and nutrient profiles.
Cloud ML Analytics
Scan data and real-time climate analytics are integrated into our Machine Learning (ML) models to generate harvest and quality predictions.
Comprehensive Reports
XLSOR provides detailed reports on treatment and harvest timing, storage duration, and early-season recommendations to maximize crop quality.
Continuous Learning and Adjustment
XLSOR’s ML models improve with each harvest, enhancing reports and helping predict climate change impacts.
One Scan, Multiple Results.
XLSOR Chlorophyll Content™: When to pick
Dry Matter Content: Sweetness potential
Brix: Consumer delight
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