首页> 美国卫生研究院文献>Foods >Integration of Partial Least Squares Regression and Hyperspectral Data Processing for the Nondestructive Detection of the Scaling Rate of Carp (Cyprinus carpio)
【2h】

Integration of Partial Least Squares Regression and Hyperspectral Data Processing for the Nondestructive Detection of the Scaling Rate of Carp (Cyprinus carpio)

机译:偏最小二乘回归与高光谱数据处理的集成用于无损检测鲤鱼的缩放比例

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

The scaling rate of carp is one of the most important factors restricting the automation and intelligence level of carp processing. In order to solve the shortcomings of the commonly-used manual detection, this paper aimed to study the potential of hyperspectral technology (400–1024.7 nm) in detecting the scaling rate of carp. The whole fish body was divided into three regions (belly, back, and tail) for analysis because spectral responses are different for different regions. Different preprocessing methods, including Savitzky–Golay (SG), first derivative (FD), multivariate scattering correction (MSC), and standard normal variate (SNV) were applied for spectrum pretreatment. Then, the successive projections algorithm (SPA), regression coefficient (RC), and two-dimensional correlation spectroscopy (2D-COS) were applied for selecting characteristic wavelengths (CWs), respectively. The partial least square regression (PLSR) models for scaling rate detection using full wavelengths (FWs) and CWs were established. According to the modeling results, FD-RC-PLSR, SNV-SPA-PLSR, and SNV-RC-PLSR were determined to be the optimal models for predicting the scaling rate in the back (the coefficient of determination in calibration set ( ) = 96.23%, the coefficient of determination in prediction set ( ) = 95.55%, root mean square error by calibration ( ) = 6.20%, the root mean square error by prediction ( )= 7.54%, and the relative percent deviation ( ) = 3.98), belly ( = 93.44%, = 90.81%, = 8.05%, = 9.13%, and = 3.07) and tail ( = 95.34%, = 93.71%, = 6.66%, = 8.37%, and = 3.42) regions, respectively. It can be seen that PLSR integrated with specific pretreatment and dimension reduction methods had great potential for scaling rate detection in different carp regions. These results confirmed the possibility of using hyperspectral technology in nondestructive and convenient detection of the scaling rate of carp.
机译:鲤鱼的结垢率是限制鲤鱼加工自动化和智能水平的最重要因素之一。为了解决常规人工检测的缺点,本文旨在研究高光谱技术(400–1024.7 nm)在检测鲤鱼结垢率方面的潜力。由于不同区域的光谱响应不同,整个鱼体被分为三个区域(腹部,背部和尾部)进行分析。频谱预处理使用了不同的预处理方法,包括Savitzky-Golay(SG),一阶导数(FD),多元散射校正(MSC)和标准正态变量(SNV)。然后,应用连续投影算法(SPA),回归系数(RC)和二维相关光谱(2D-COS)分别选择特征波长(CWs)。建立了使用全波长(FW)和CW进行比例缩放率检测的偏最小二乘回归(PLSR)模型。根据建模结果,确定FD-RC-PLSR,SNV-SPA-PLSR和SNV-RC-PLSR是预测背面缩放率的最佳模型(校准集中的确定系数()= 96.23%,预测集中的确定系数()= 95.55%,校准的均方根误差()= 6.20%,预测的均方根误差()= 7.54%,相对百分比偏差()= 3.98 ),腹部(= 93.44%,= 90.81%,= 8.05%,= 9.13%和= 3.07)和尾巴(= 95.34%,= 93.71%,= 6.66%,= 8.37%和= 3.42)地区。 。可以看出,PLSR结合特定的预处理和降维方法在不同鲤鱼区域的结垢率检测方面具有巨大潜力。这些结果证实了使用高光谱技术对鲤鱼的结垢率进行无损且方便的检测的可能性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号