Meet Richie Ellingham, Oliver Batchelor, Matt Mattar, and Richard Green at HoloCrop, one of the 22 ventures participating in the Sprout Accelerator Spring26 Cohort.
We caught up with the HoloCrop team for a quick-fire five questions in five minutes to learn more about HoloCrop and what they hope to achieve from their time in the Sprout Accelerator.
1. Tell us about HoloCrop. What are you building?
After talking with more than 50 fruit growers just before harvest, we found huge uncertainty around what their yield would be. One cherry grower mentioned they lost approximately NZD$5 million due to a poor yield estimate.
Currently, most orchards and vineyards sample between 0.1 and 1% of their fruit crop to create a yield estimate. This uncertainty in crop yield measurement affects all parts of the fruit value chain. Growers need to know how many pickers they need for harvest, packhouses need to plan for packaging, logistics and grader optimisation, and sales and distribution teams need to sell fruit before it is harvested.
We significantly increase the crop sampling percentage and provide a higher degree of certainty, creating data that can save individual fruit producers millions through more optimal fruit production. This is just the beginning of what our 3D precision scanning technology can achieve.
2. What problem are you working to solve?
This problem stemmed from the sheer amount of occlusion in horticultural robotics. Leaves constantly hide key parts of a plant, including branches and, most importantly, the fruit.
This creates a host of issues for anyone wanting to collect accurate data in specialty crops in particular.
Since developing our 3D modelling software, we have seen demand for applications ranging from yield estimation and crop sampling for research to horticultural robotics enablement.
3. How does your solution work?
Our product achieves this accuracy through an optimised multi-camera rig.
We use a camera bar with many cameras, depending on the crop, mounted on an autonomous vehicle that drives along crop rows capturing large arrays of images. From these images, we can create 3D models and detect different plant structures in 3D.
Our system also self-validates everything it detects using multiple images. For example, one apple could be detected in 20 different images from multiple angles.
4. What is the next important milestone for your venture?
Customer trials are the next major milestone for the 26/27 season.
If we can build trust by quantifying exactly how much money growers, packhouses, and sales and distribution teams save through better yield monitoring, we can start productising our technology and offering our services to more customers to help improve their returns.
5. What are you hoping to get out of your time with Sprout?
After investigating Sprout, we noticed that many of the companies coming out of the programme seemed reputable and successful compared with many other accelerator programmes.
We’re hoping Sprout will help us build a strong network, further refine our business model and access more customers.
Find out more: holocrop.ai
LinkedIn: https://www.linkedin.com/company/holocrop3d/