苹果内在组分与隐性缺陷的透射光谱在线检测基础研究

项目名称： 苹果内在组分与隐性缺陷的透射光谱在线检测基础研究

项目编号： No.31501216

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 农业科学

项目作者： 郭志明

作者单位： 北京市农林科学院

项目金额： 20万元

中文摘要： 苹果在我国现代农业经济中占有重要地位，现阶段迫切需要产后内部品质商品化处理技术，特别是快速无损、可在线的检测技术和方法。针对苹果内在组分与隐性缺陷检测的难点问题，研究提出全透射光谱技术的苹果多指标同步在线检测思路，探析苹果组织光传输机理、光谱响应规律、信号增强机制与处理方法等科学问题。研究拟通过试验模拟与光学仿真，利用苹果组织内光传输的吸收特性和散射特性解析光的有效穿透深度和能量分布规律；分析苹果组织光学特性参数与内在品质的相关关系；研究苹果病变组织的光散射特性，分析典型隐性缺陷苹果与正常果的光谱响应差异；研究透射光谱的微弱信号增强与消澡方法，设计水果内在组分与隐性缺陷透射光谱在线检测系统，优化系统以提升在线透射光谱质量，优选多元校正方法和模式识别方法构建内在组分定量分析模型和隐性缺陷判别模型，实现苹果多指标同步在线检测。本项目研究为水果内部品质的无损检测技术和装备提供理论依据和方法参考。

中文关键词： 光谱分析；内在品质；隐性缺陷；在线检测；苹果

英文摘要： Apple plays a critical role for increasing farmers' income and developing green friendly economic in China's modern agricultural. Currently, postharvest commercial processing technologies for apple internal quality detection are urgently needed especially the rapid non-destructive, online detection technology and systems. In view of the difficulty of apple internal quality and hidden defects detection, we proposed a novel idea that simultaneous determination internal quality and hidden defects in apple using online near-infrared (NIR) transmittance spectroscopy. Apple tissue optical transmission mechanism, spectral response characteristics, signal enhancement mechanism and processing methods will be research. The absorption and reduced scattering coefficients will be used in Monte Carlo models to simulate light transport in the fruit tissue. Through experiment test and optical simulation, light absorption and scattering properties in apple tissues will be calculated. The patterns of diffuse reflectance, light penetration depth, and scattering energy distribution will be determined for the apples. Relationships between texture attributes and the optical properties will be identified. The differences of light scattering properties between diseased tissue and intact apple will be investigated, and then identification models will be developed using NIR transmittance spectra combined pattern recognition methods. Transmittance spectra weak detection signals will be effective achieve. An online determination system based on NIR transmittance spectroscopy will be developed and used for signal acquisition related to the internal quality and hidden defects. Combination of system parameters will be optimizing to improve the quality of online transmission spectra. Multivariate calibration methods and pattern recognition methods will be compared and selected to build internal quality quantitative models and hidden defects classification models, respectively. Finally, we will construct mathematical models for simultaneous determination internal quality and hidden defects in apple by online detection system based on NIR transmittance spectroscopy. This project will provide a theoretical foundation methods reference for fruit internal quality rapid, non-destructive, online detection technology and equipment, and will be quite helpful to reduce the apple postharvest economic loss, enhance market competitiveness.

英文关键词： spectral analysis;internal quality;hidden defects;online detection;apple