Production of Gluten-free Oat Products using a Novel Near Infrared Sorting Technique

目前，燕麦的质量检测主要是基于人工目视检查， 人工检查大约50，000个玉米粒的样品。这不是时间效率，因为检查员必须 识别所有类型的污染物，然后将其分类（例如大麦，小麦和黑麦），最后 编写质量检验报告。一些研究表明，机器视觉可以成为一种 在不同类型的谷物分离中，替代了人工检测的方式。然而，机器视觉 由于燕麦和大麦籽粒的大小几乎相同，因此分离技术在分离燕麦和大麦籽粒方面是无效的。随着增加 近红外反射率（NIR）和近红外透射率（NIT） 用于许多谷物颗粒的质量评估的技术正变得越来越流行。的优点 近红外技术的另一个优点是光谱信息可用于区分不同类型的谷物。的 本研究的总体目标是调查使用近红外和近红外技术分离的可行性， 无麸质燕麦和其他富含麸质的谷物。该项目的成果将有助于我们的工业合作伙伴， 理查森国际有限公司，提出策略，以加强他们目前的燕麦分拣过程中使用的， 基于NIR/NIT的高速谷物分选机。

Currently, quality inspection of oats is primarily based on human visual inspection where trained personnel manually inspect samples of approximately 50,000 kernels. It is not time-efficient because the inspector must identify all types of contaminants, then separate them into classes (e.g. barley, wheat, and rye), and finally compile a quality inspection report. Several research studies have shown that machine-vision can be an alternative way to human inspection in separating grain of different types. However, the machine vision technique is not effective in separating oat and barley kernels due to their near-identical size. With increasing advances in spectroscopy technology, the near infrared reflectance (NIR) and near infrared transmittance (NIT) techniques are becoming increasingly popular for quality evaluation of many cereal grains. The advantage of near infrared techniques is that spectral information can be used to discriminate different types of grains. The overall objective of this study is to investigate the feasibility of using NIR and NIT techniques for separation of gluten-free oats from other gluten-rich grains. The outcomes of this project will help our industrial partner, Richardson International Ltd., to come up with strategies to enhance their current oat sorting process using a NIR/NIT-based high-speed grain sorter.