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PartnershipUpdated on 9 October 2026

Improving the Accuracy and Representativeness of Incoming Corn Sampling and Quality Evaluation

Senior Business Development at Japfa Pte Ltd

About

Moisture is currently measured manually, which can lead to variation in results and makes it difficult to calculate storage shrinkage accurately. Dryer settings rely on operator experience more than on consistent information from each incoming load. Quality assessment processes also depend on manual sampling and testing, which can introduce variability and limit the speed and consistency of decision-making.

In addition, bulk deliveries can vary in composition, while the pneumatic probe used for sampling is less effective when the material is not free-flowing. As a result, the sample used for acceptance decisions may not fully represent the entire load.

Impact

These measurement and sampling limitations can affect the accuracy of shrinkage analysis and the consistency of dryer performance. Variability in sampling and quality assessment may also reduce confidence in the information available for intake and processing decisions. Strengthening the accuracy, representativeness, and timeliness of incoming-load evaluation would help improve operational efficiency, process consistency, and control over one of the largest raw-material streams in feed production.

Success Criteria

Success will be measured by the ability to consistently obtain representative load-level quality data prior to acceptance, with transparent accuracy requirements and traceable sampling methods.The solution should improve confidence in intake decisions, support process optimisation, and enable accurate reconciliation of silo-level shrinkage against received volumes.

Interested in collaborating? Pitch your solutions here!

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About us: Japfa Pte Ltd

Join our Sharing Session on 27 October 2026, Tuesday, 2.30pm - 3.15pm SGT (UTC+8) Here!

Intent

  • Seeking

Type

  • Technology & Solutions
  • Expertise & Support

Topic / Sector

  • AgriTech
  • Food Manufacturing
  • Food Tech

Organisation

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