X-ray detection of defects and contaminants in the food industry

The ability of X-rays to traverse through matter and reveal hidden contaminants or defects has led to their extensive use in manufacturing industries for quality control inspection. The difficulties inherent in the detection of defects and contaminants in food products have kept the use of X-ray in that industry limited mainly to the packaged foods sector. Nevertheless, the need for non-destructive internal product inspection has motivated a considerable research effort in this field spanning many decades. Improvements in technology, especially more compact and affordable high voltage power sources, high speed computing, and high resolution detector arrays, have made many X-ray detection tasks possible today that were previously unfeasible. These improvements can be expected to continue into the future. The purpose of this article is to give a review of research activity related to the use of X-ray imaging for the detection of defects and contaminants in agricultural commodities and discuss improvements in technology required to improve these detection capabilities.     

X-ray images for the control of eye formation in cheese

There is demand for non-destructive monitoring of eye formation in cheese during ripening. The objective of this work was to develop a simple method based on existing equipment in the dairy industry. Images were acquired using a conventional, low resolution online X-ray instrument. Image processing methods for detecting eyes of cheese and measuring volume and size distribution were developed. Sufficient detection of overlapping eyes was obtained. Semihard cheese with propionibacteria ripened under different conditions was analysed. The method was found promising for quality control as it will make possible non-destructive monitoring of eye formation of cheese throughout the ripening period.     

数字图像边缘检测算法及其在农产品加工中的应用

详细回顾现有的边缘检测技术、方法及其在农产品加工中的应用,并对今后的边缘检测进行了展望.     

转基因食用农产品的快速检测方法

商业化转基因农作物广泛种植,转基因农产品被大量用作食品和动物饲料。我国和全球大部分国家都实行转基因生物强制标识制度。转基因农产品的现场监督检测急需稳定可靠的快速检测手段。本文论述了主要的基因水平检测方法包括PCR、基因芯片、环介导等温扩增技术(loop-mediated isothermal amplification,LAMP)和蛋白质水平检测方法(蛋白质免疫印迹法、酶联免疫吸附法、胶体金免疫层析试纸条法)。通过比较分析上述各检测方法的优缺点,LAMP和胶体金试纸条法是当前最理想的现场快速检测方法。     

高光谱成像技术在农产品检测中的应用

介绍高光谱成像技术的原理,总结高光谱在农药残留、农作物品质、肉类品质检测中的应用,并分析其中的不足和优势,提出高光谱成像技术未来在农产品检测中的发展方向。     

Textural analysis of hyperspectral images for improving contaminant detection accuracy

Previous studies demonstrated a hyperspectral imaging system has a potential for poultry fecal contaminant detection by measuring reflectance intensity. The simple image ratio at 565 and 517 nm images with optimal thresholding was able to detect fecal contaminants on broiler carcasses with high accuracy. However, differentiating false positives from real contaminants, especially cecal feces were challenging. Further image processing such as textural analysis in the spatial domain was able to reduce false positive errors. In this study, textural analysis of hyperspectral images was conducted to improve detection accuracy by reducing false positives. Specifically, textural analysis with co-occurrence matrix of hyperspectral images performed well to identify “true” contamination. In addition, co-occurrence matrix textural features including average, variance, entropy, contrast, correlation, moment of poultry hyperspectral images were investigated for selecting optimal features to represent contamination. Image pre-processing with co-occurrence textural analysis, specifically mean of co-occurrence textural feature from the matrix (0° angle and distance equals to one) followed by image ratio was able to improve fecal detection accuracy without additional optical filters that increase cost for system hardware of multispectral imaging system for on-line application. Mention of trade names or commercial products in this article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.     

X-ray micro-computed tomography of cellular food products

Modern food processing is increasingly concerned with the production of products with complex aerated microstructures which determine to a large extent the mechanical and aesthetic properties of these products. The development and analysis of such new materials require non-invasive techniques for visualisation and measurement of the internal microstructure. This paper describes the imaging, visualisation and analysis of the three-dimensional (3D) cellular microstructure of a number of food products (aerated chocolate, mousse, marshmallow and muffin) using X-ray micro-computed tomography. A 3D model of the foam microstructure is determined and, by combining image analysis with a stereological technique, quantitative information is obtained on a number of parameters including spatial cell size distribution, cell wall-thickness distribution, connectivity, and voidage. The work shows that X-ray micro-computed tomography is an elegant and useful tool for the study of the 3D structure of cellular food materials.     

农产品中农药残留检测前处理方法的研究进展

世界上农药年产量高于200万吨, 有1000多种人工合成化合物被用作杀虫剂、杀藻剂、除虫剂、杀菌剂、落叶剂等农药。有机农药的大量施用会造成严重的污染问题, 并对人体健康造成严重威胁。因此, 建立简单、高效和成本低的农药残留快速检测方法非常重要。由于农残检测涉及的样品种类繁多、样品组成复杂和样品形态多变, 这对农残检测造成的干扰增加, 所以需要选择和改进农药残留检测的前处理方法。科研人员在农药残留快速检测技术方面做了大量的研究, 并取得了较大的进步。本文介绍了该领域一些热点技术的研究方法和动态, 并对存在问题进行了分析, 以期为农药残留快速检测的深入研究提供参考。     

农产品中真菌毒素检测方法研究进展

真菌毒素是由特定真菌在适宜条件下产生的有毒小分子次级代谢产物,农产品在生长、加工和储运过程中均存在被真菌毒素污染的可能性,被真菌毒素污染的农产品会严重危害动物和人类的健康。因此建立精确、高效的真菌毒素检测方法对于农产品中真菌毒素的防控和监测具有重要意义。本文主要介绍了真菌毒素的产生和危害,综述了近5年农产品中真菌毒素检测方法(仪器分析法、免疫学分析方法和光谱分析法)的研究进展,分析了这些检测方法的优缺点,并展望了农产品中真菌毒素在未来的发展趋势,为农产品中真菌毒素检测的相关研究和安全监管提供参考和启发。     

农产品和水体中农药残留检测技术研究进展

农药残留是指由于使用农药而残留于农作物、水体、土壤等的农药原体和代谢物。农药具有毒性强、稳定性好、生物聚集性等特点,极易在环境中发生富集,最终进入人体,其残留问题已对人类健康和环境中其他生物体形成极大威胁。因此监测食品或环境中的农药残留水平对人类健康和保护生物多样性具有十分重要的作用。随着科学技术的不断探索和发展,农药残留检测技术也取得了重大突破。本研究总结了农药残留的方式和危害;分析了农药残留检测中常用的前处理方法(液液萃取、固相萃取、QuEChERS提取法和其他方法),对比了几种方法的优缺点;对近年来农药残留的传统分析技术的最新应用和新型的检测分析技术及其应用进行了综述,并对当前领域存在的问题和未来的发展方向进行了总结。     

近红外光谱技术在农产品品质检测中的应用

近红外光谱技术是一种新型的无损检测技术,在许多领域都得到了很好的应用。本文从农产品中各种物质成分含量预测、分类鉴别、腐烂鉴别、实时监测几个方面综述了近红外光谱技术在农产品品质检测上的应用,并对其在仪器硬件的研究和开发、化学计量学方法的探索与研究以及快速在线检测方法的研究等方面的发展趋势进行了展望。     

Determining optimal wavebands using genetic algorithm for detection of internal insect infestation in tart cherry

This paper reports the results of waveband selection for detecting internal insect infestation in tart cherries as a precursor to development of a dedicated multispectral vision system. A genetic algorithm (GA) approach was applied on hyperspectral transmittance images (580–980 nm) and reflectance spectral data (590–1,550 nm) acquired from both intact and infested tart cherries. The GA analysis indicates that the ability of using transmittance imaging approach for detecting internal insect infestation in tart cherries would be limited. According to the GA analysis on the reflectance spectra, visible wavelengths were of less importance than NIR wavelengths for the purpose of distinguishing intact cherries from infested ones. The PLSDA results indicate that models built with three or four GA selected wavelength regions gave similar classification accuracy to the model built with full wavelength region, which demonstrates the efficiency of the GA variable selection procedure. However, due to the stochastic nature of the GA, the efficiency of using these wavebands in a multispectral vision system needs to be verified in future work.     

我国食用农产品污染物快速检测标准分析

快速检测技术在食用农产品质量控制和安全保障中发挥了重要作用。本文介绍了我国食用农产品涉及的主要污染物及对应的快速检测标准体系, 概述了我国食用农产品速测标准的常用技术及其优缺点。结合我国食用农产品的速测标准现状, 提出速测标准存在老化现象突出、标准应用范围有限及部分速测标准水平不高等问题, 并以污染物速测标准现状为依据, 针对性地提出了完善我国食用农产品质量安全的速测标准体系的建议, 重点在于更新标准内容和标准覆盖范围。     

农畜产品无损检测研究专题概述

<正>食品质量与安全是目前国内的热点问题,如何保证农畜产品及其产品的质量与安全还面临较多的问题,这些问题的解决目前仍主要依靠常规微生物检测、理化检测、感官评估等方法。为弥补传统方法的诸多缺陷,国内外学者不断研究食品质量与安全的无损检测方法。无损检测是在不损害或不影响被检测对象使用     

鲜活农产品中单核细胞增多性李斯特菌快速检测技术的研究进展

单核细胞增多性李斯特菌是一种食源性致病菌,其引发的李斯特菌病致死率高达30%。本文综述了单核细胞增多性李斯特菌(Listeria monocytogenes)的生物学特性和毒力因子,着重介绍了单核细胞增多性李斯特菌基于分子生物学、免疫学等技术的几种快速检测方法,旨在为单核细胞增多性李斯特菌的深入研究提供参考。      

微芯片技术在农产品及食品真菌毒素快速检测中的应用

真菌毒素污染的农产品及食品会对人类及牲畜的健康产生严重威胁。目前,真菌毒素的检测主要采用液相色谱-质谱联用法(liquid chromatography-mass spectrometry,LC-MS)、气相色谱-质谱联用法(gas chromatography-mass spectrometry,GC-MS)等传统检测方法。然而,这些检测方法的样品前处理过程比较繁琐、费时,并且在分析过程中还会消耗大量的有毒试剂。微芯片技术所需样品的消耗量少并且分析时间短,可实现样品的集成化、微型化以及高通量检测。微芯片技术在真菌毒素检测中的应用,弥补了上述传统检测方法的不足。本文主要综述了微芯片技术在农产品及食品真菌毒素快速检测中的应用研究进展。首先对农产品及食品中常见的真菌毒素及其毒性进行了简单介绍;接着重点对微芯片技术在真菌毒素检测中的应用进行了详细论述;最后对微芯片应用于真菌毒素检测的发展前景和挑战进行了展望。     

拉曼光谱技术在农产品药物残留检测中的应用

近年来,农产品药物残留超标引发了一系列食品安全问题,为了保障国家食品安全、保护消费者健康,需要对农产品中的药物残留进行定性定量检测。表面增强拉曼散射技术 (Surface-enhanced Raman scattering , SERS) 是一种极具吸引力的工具,可用于高效检测农药残留。本文介绍了表面增强拉曼光谱检测技术的概况,简介了拉曼增强基底,分析了表面增强拉曼光谱技术在药物标准溶液、农产品(肉类、水产品、果蔬和其他部分农产品等)药物残留检测领域中的研究现状,并针对当前农产品药物残留检测的发展趋势进行前景展望。     

曲线匹配算法及其在织物自动对花检测中的应用

针对圆网印花过程中的对花检测问题,在提出的基于机器视觉的圆网印花检测系统的基础上,提出了利用曲线匹配策略得到错花套色的位置误差矢量的方法。为了确保目标边缘图像与标准边缘图像拍摄位置相同,利用Fourier-Mellin曲线匹配,对其进行匹配消除拍摄误差;然后用基于傅里叶变换位移定理的曲线匹配算法,对调整好的目标边缘图像和标准边缘图像进行匹配,检测对花误差。该匹配策略消除了拍摄误差,数据运算量小,实验表明其检测精度和运算速度可以满足织物对花在线检测的要求。     

响应面法优化农产品中抗性淀粉的体外检测

目的 采用响应面法优化农产品中抗性淀粉(Resistant Starch, RS)的体外检测方法。方法 选择谷类、薯类、豆类3类抗性淀粉主要来源的农产品,设计单因素试验和Box-Behnken试验。单因素试验考察了水浴时间、淀粉葡萄糖苷酶（AMYLOGLUCOSIDASE, AMG）作用温度、AMG作用时间、AMG添加量和离心力与离心时间5个条件,并选择AMG作用温度、AMG作用时间、AMG添加量来设计Box-Behnken试验。结果 根据单因素试验,确定了水浴时间为14 h,离心条件选择4500 g离心5 min;根据响应面实验确定对RS含量检测结果影响程度排序为AMG添加量＞AMG作用时间＞AMG作用温度。结合单因素响应面试验,确定最佳检测方法为水浴14 h,4500 g离心5 min,AMG作用温度49℃、AMG添加量0.2 mL、AMG作用时间38 min。结论 优化后的方法重复性良好,适用于玉米、马铃薯和红豆3类样品,且有望适用于其他主要农产品。     

An automatic scheduling method for weaving enterprises based on genetic algorithm

As the multi-varieties and small-batch production mode become more popular in weaving enterprises, the traditional manual operated scheduling exposes the disadvantages of low work efficiency and unsatisfying result. In this paper, by summarizing the weakness previous model, a more practical optimization model is developed for weaving production scheduling to reduce the schedulers’ labor. The model describes the optimization of warp beam looming schedule in weaving process based on the analysis of the schedulers’ working process in weaving enterprises. Genetic algorithm (GA) is adopted to solve the model. To improve the computational efficiency and avoid prematurity convergence of GA, the termination condition is updated and the genetic parameters are optimized based on statistical data. The improved GA with optimized parameters gets solutions superior to manual scheduling with a quicker convergence, which has great practical value.