Yield Prediction
At a Glance
| Challenge | Accurately predicting yield and pack-out on a per-block basis ahead of harvest to enable precise forward-planning. |
|---|---|
| Solution | Green Atlas Cartographer quickly and accurately estimates fruit counts and fruit size distribution. Combined with historic growth curves and fruit density estimates, a comprehensive yield and pack-out can be predicted. |
| Result | A faster, more comprehensive and precise method of tallying fruit numbers and sizes. Enables forward-planning from in-field logistics to packing shed operations, marketing and sales. |
| Applicable Crops | Most crops and stages after natural fruit-drop and/or thinning. |
Significant Risk in 'Blind' Forecasts
Manual sampling carries compounding error.
Traditional yield estimation relies on counting and measuring a handful of 'typical' trees assumed to be representative of thousands. This carries significant risk:
- Law of Small Numbers: A couple of dozen chosen trees are statistically unlikely to represent average tree performance within a block. A slight manual miscount on a sample tree is multiplied across the entire block, potentially creating massive discrepancies in estimated tonnage.
- Size Variability: Fruit size is not uniform. Without a large dataset taken from the entire orchard, it is nearly impossible to predict the true size distribution (the pack-out), which can significantly affect market value.
Fast, Accurate Counts and Sizes
Replace point sampling with a total orchard census.
Green Atlas Cartographer provides a digital assessment of every tree in the orchard.
- Automated Fruit Counting and Sizing: The system scans at high speed, using sophisticated algorithms to count and measure the diameter of fruit across the orchard, creating a massive, statistically significant dataset.
- Growth Curves: By combining real-time measurements with historic growth data and local environmental factors, the system projects final harvest count, size and tonnage weeks or months in advance of harvest.
Digital Fruit Inventory
Accurate forward yield estimates transform the supply chain.
Moving to an automated, in-field fruit inventory transforms operations from the orchard to the supermarket shelf:
- Operational Precision: Plan the number of bins, trucks, equipment and pickers required for each block, eliminating idle time caused by over or under-estimating the crop.
- Optimised Packing Sheds: Cold storage and packing lines can be scheduled with certainty. If the system predicts an unusual size profile, the shed can prepare the specific packaging needed.
- Sales and Marketing Leverage: Sales teams can commit to forward-contracts with retailers with higher confidence, targeting the right buyers and markets long before the first bin is picked.
Forward-Planning Use Cases
How yield prediction data flows through a business.
In-Field Logistics
Use the Total Count by Row map to calculate the exact number of picking bins needed per row. Increases picker efficiency and reduces unnecessary machinery movements.
Cold Storage and Packing
Provide the packing shed with a Count and Size Distribution Report well in advance. Optimises pre-cooling space, box purchasing, and downstream logistics.
Market and Sales
Use the Pack-Out Prediction to inform wholesalers of expected volume by category. Secures higher prices by allowing pre-selling to the highest-value buyers based on accurate data.
Get Started
Predict your yield with confidence.
Find your nearest Green Atlas service provider to discuss how yield prediction can improve your forward-planning.