Nofima Mat AS, Osloveien 1, 1430 As, Norway.
Appl Spectrosc. 2010 Jul;64(7):691-9. doi: 10.1366/000370210791666273.
This article presents a method by which noncontact near-infrared (NIR) interactance imaging spectroscopy can be applied to determine the amount of edible meat in single live crabs (Cancer pagurus) on a conveyor belt at high speed. The physiology and optical properties of the crabs are presented and discussed in order to explain the requirements for representative spectroscopic sampling. Two different sampling and calibration strategies are discussed. One strategy is based on the extraction of one average NIR spectrum from certain locations in each crab. The other strategy relies on first making a model based on average spectra from a certain location, and then using this model for pixel-wise prediction of the meat content within the crabs. A measure of the predicted distribution of meat is then used for calibration. Reference measurements of meat content were based on an objective quantitative metric of the meat content. The results show that NIR imaging enables on-line grading of the crabs with a correlation of 0.96 with the measured meat content. Due to seasonal variations in the crabs, a piece-wise regression strategy performs slightly better than a global model. Pixel-wise predictions of meat content provide informative images showing the distribution and amount of meat within each crab.
本文提出了一种方法，通过非接触式近红外（NIR）相互作用光谱学，可以在高速传送带上确定单个活螃蟹（Cancer pagurus）中的可食用肉量。为了解释代表性光谱采样的要求，介绍并讨论了螃蟹的生理学和光学特性。讨论了两种不同的采样和校准策略。一种策略基于从每个螃蟹的某些位置提取一个平均 NIR 光谱。另一种策略则基于首先从某个位置的平均光谱建立模型，然后使用该模型对螃蟹内的肉含量进行逐像素预测。然后使用预测的肉分布的度量值进行校准。肉含量的参考测量值基于肉含量的客观定量指标。结果表明，NIR 成像能够对螃蟹进行在线分级，与测量的肉含量的相关性为 0.96。由于螃蟹的季节性变化，分段回归策略的性能略优于全局模型。肉含量的逐像素预测提供了有信息量的图像，显示了每个螃蟹内的肉的分布和数量。
