Platypus grain inspection and sorting system
The Platypus grain inspection system uses advanced photonics and AI to inspect and sort various grains, including corn, wheat, and barley. It offers high-resolution imaging and scalability, with a modular design that can integrate emerging technologies like SWIR imaging.
Overview
The Platypus grain inspection and sorting system is an innovative solution designed to enhance the precision and efficiency of grain quality assessment. Utilizing advanced photonics principles, the system produces high-resolution images that can be analyzed with AI to detect defects and assess haploid features in various grains. Initially tested on wheat and barley, the system is now being adapted for corn. Its modular design allows for scalability and integration with emerging technologies, making it a versatile tool for the agricultural industry.
Technical specifications
Key features:
- High-resolution imaging using advanced photonics principles
- AI-driven image analysis for accurate defect detection
- Modular and scalable design suitable for various grain types
- Compatible with emerging technologies such as SWIR and hyperspectral imaging
- Physical sorting system available for comprehensive grain management
The Platypus system can be scaled to fit different operational needs, including truck-mounted configurations for field use. It also incorporates a user-friendly human-machine interface (HMI) and customizable reporting formats to aid in data interpretation and decision-making.
Technology readiness level
The Platypus grain inspection and sorting system is at Technology Readiness Level 6. It has been successfully tested in controlled environments with wheat and barley and is undergoing adaptation and validation for use with corn. The system is set for further testing in field environments to ensure reliability and user-friendliness under real-world conditions.
About Platypus Vision
Platypus Vision provides advanced machine vision and artificial intelligence systems designed for the seed and grain supply chain. By leveraging photonics and deep learning, their technology automates the inspection, grading, and variety identification of natural products such as wheat, barley, rice, canola, and lentils. The systems are designed to be flexible, offering both automated and supervised modes to suit various operational scales, from farm-level applications to bulk export handlers. Their platform aims to augment or replace manual processes, providing reliable and reproducible analysis in real-time.
This technology is critical for stakeholders across the agribusiness sector, including seed breeders, testing laboratories, and grain traders, who require accurate data for quality control, biosecurity, and commercial grading. By delivering faster inspection results—such as analyzing up to one liter of grain in four minutes—the company helps operators increase efficiency and maintain consistent standards. Their expertise is supported by over 15 years of experience in machine vision and engineering, with their systems used to address the complex challenges of inspecting diverse natural products.
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