近红外光谱仪和化学计量学在农产品加工中的应用综述

C. Kumaravelu, A. Gopal
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引用次数: 26

摘要

本文综述了近红外光谱及化学计量学在农业食品加工业中光谱数据分析的最新进展。近年来,所有加工行业都需要具有成本效益和非破坏性的质量控制分析系统,以显着改善其产品。在各种加工工业中,农用食品加工业涵盖了从种植者到客户的所有步骤,涉及到本质上不同类型的过程,这些过程需要对安全性、规范一致性和利润优化进行监控。农业食品加工业涵盖范围广泛,以农业、农场、动物和林业产品为原料。在以农业为基础的行业中,如农业大棚、产品库存废物、动物饲料、农业机械、肥料、球茎、种子和幼苗、新鲜蔬菜、水果、谷物、坚果和果仁、通过采用机器视觉技术识别产品的外部缺陷和基于x射线的成像来识别产品的内部缺陷,但近红外光谱技术也可以应用于上述行业,因为它具有非侵入性,非破坏性,分析速度快,适应不同样品状态的灵活性等优点。然而,这种近红外光谱需要一种独特的方法从样品的光谱数据中提取相关的物理和化学信息,这只能通过一种新的统计方法即化学计量算法来实现。本文首先介绍了近红外光谱技术的原理和优点,然后介绍了近红外光谱技术在农业食品加工业中各种有机产品中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A review on the applications of Near-Infrared spectrometer and Chemometrics for the agro-food processing industries
The purpose of this review article is to outline the recent progress in Near Infrared (NIR) spectroscopy and spectral data analysis using Chemometrics in agro-food processing industries. In recent years, all the processing industries have created the need for cost effective and non-destructive quality control analysis systems to improve their products significantly. Among varies process industries, the agro-food processing industries encompasses all steps from the grower to the customer, involves substantially different types of process, which require monitoring for safety, conformance to specification and profit optimization. The agro-food processing industries cover a wide range of activities utilizing agriculture farm, animal and forestry based products as a raw materials. There are certain traditional quality inspection systems in agro based industries such as agricultural green houses, product stock waste, animal feed, farm machinery, fertilizer, flower bulbs, seeds & seedlings, fresh vegetables, fruits, grains, nuts & kernels, oil seeds and plant & animal oil etc. to assess the quality of their food products by employing machine vision technology to identify the external defects of the products and X-Ray based imaging to identify internal defects of the products, but the NIR spectroscopy technique can also be applied for the above said industries, because it is particularly powerful in non-invasive, non-destructive, speed in analysis, flexibility in adapting to different sample states. However, this NIR spectroscopy requires a unique way to extract relevant physical and chemical information from the sample's spectral data and this can be performed by only a new statistical approach namely Chemometric algorithms. In this review, the principles and advantages of NIR spectroscopy are described first and then its application to various organic products in agro-food processing industries.
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