A review on tomato authenticity: quality control methods in conjunction with multivariate analysis (chemometrics)

Authenticity and traceability have been two of the most important issues in the food chain. Authenticity in particular, is closely related with both food quality and safety issues. Vegetables stand for a category of foods heavily affected by adulteration either in terms of geographic origin (national or international level) or production methods (organic or conventional production, fertilizers, pesticides, genetically modified vegetables). This review aims at addressing most of the currently applied methods for ensuring quality control of vegetables; a) instrumental: ion chromatography, high pressure liquid chromatography, atomic absorption spectrophotometry, electronic nose and mass spectroscopy and b) sensory analysis. The results of all the above mentioned methods were analyzed by means of multivariate analysis (principal component analysis, discriminant analysis, cluster analysis, canonical analysis, and factor analysis). All ensuing results and conclusions are summarized in eight comprehensive tables.     

Agricultural produces: synopsis of employed quality control methods for the authentication of foods and application of chemometrics for the classification of foods according to their variety or geographical origin

A review of quality control methods and applications of multivariate statistical techniques on the authentication and classification of agricultural products is presented. The products reported within the frame of this article were vegetables, fruits, juices, jams, wines, cereals, bakery products, oils, tea, coffee, honey, sugar-syrups, salad dressings, and gums. The perspective of multivariate statistics as a promising tool to authenticate and classify these food products according to their geographical origin or variety was demonstrated. Several representative figures and informative synoptical tables for agricultural food products were provided both for the quality control methods employed and the multivariate analyses implemented.     

基于人工神经网络的织物疵点检测

根据疵点的特征对常见织物疵点进行了简单的划分。采用直方图均衡化、二值化、中值滤波、腐蚀和膨胀等方法对织物图像进行一系列的预处理,对织物疵点的特征参数进行提取,利用人工BP神经网络来判别疵点的类别并进行分类。结果表明,利用BP神经网络识别织物疵点并进行分级是行之有效的。     

Implementation of chemometrics for quality control and authentication of meat and meat products

Multivariate analysis has been established as a very powerful and effective tool in classifying and grouping individual products. Principal Component Analysis, Canonical analysis, Cluster and Partial Least Squares were found to be indispensable for classifying food products according to variety and/or geographical origin. Meat and meat products were correctly classified for authentication purposes to various groups following instrumental and/or sensory analyses.     

Implementation of quality control methods (physico-chemical, microbiological and sensory) in conjunction with multivariate analysis towards fish authenticity

Nowadays authenticity of foods and fish in particular has become of crucial importance because of high number of adulteration cases. Authenticity control has gained ground thanks to the development of several rapid physico‐chemical and microbiological methods aiming at distinguishing one species from another based on solid scientific evidence. It has been proven that despite the precision and accuracy of robust analytical and protein and DNA‐based techniques, detection of authenticity could not be claimed without resorting to multivariate analysis. This review summarizes both the most advanced and state of the art used techniques for detecting fish and seafood authenticity (both in terms of species and geographical origin). Another issue reported in this review is the preservation of fish and seafood through the implementation of old and novel techniques (ice, modified atmosphere packaging). Several informative tables were included in this paper referring to the employed quality control and sensory analysis methods and multivariate analysis for fish and seafood.     

Moisture sorption isotherms and isosteric heat of sorption of coffee in different processing levels

The desorption isotherms and thermodynamic properties of coffee from different processing stages were obtained during the drying process of this product. The isotherms were determined by a static gravimetric method for various temperature and humidity conditions. Equilibrium moisture content (M_e) data were correlated by several mathematical models and an artificial neural network (ANN) model. The M_e for coffee fruits, pulped coffee and green coffee increased with an increase in the water activity (a_w) at any particular temperature. At a constant a_w, coffee fruits samples had higher M_e than the remaining coffee samples. Based on statistical parameters, the ANN model, modified Henderson and GAB models were adequate to describe the sorption characteristics of the samples. Isosteric heat of sorption was evaluated by means of the Clausius–Clapeyron equation. It decreased with increasing moisture content. The coffee fruits had higher isosteric heat of sorption than that pulped coffee and green coffee.     

Invited review: Modelling quality changes of fruits and vegetables during drying: a review

Fruits and vegetables have received much attention as these materials have been reported to contain various phytochemicals, which are claimed to exert many health benefits. When extraction of bioactive compounds cannot be performed on fresh fruits and vegetables, drying needs to be conducted to keep the materials for later use. Dried fruits and vegetables have also been regarded as alternative fat‐free snacks and received more attention from the food industry during the past decade. This implies that not only nutritional changes, but also other changes including physical and microstructural changes are of importance and need to be optimised, preferably through the use of various modelling approaches. The objective of this article is to provide a brief review of some advances in modelling quality changes of fruits and vegetables during drying. These include modelling of nutritional, colour and selected physical changes. Approaches to monitoring and modelling microstructural changes are also mentioned.     

色谱指纹图谱技术在咖啡质量控制应用中的研究进展

本文就三种色谱技术(液相色谱、气相色谱和全二维色谱)及其在咖啡质量控制应用中的研究进展进行综述。通过对咖啡的起源、分布、主要成分和风味特征,以及色谱指纹图谱的构建方法进行描述,进一步揭示色谱指纹图谱技术在其品控方面的重要性和应用前景。色谱技术作为一种物理化学的分离分析方法,克服了传统光学、质谱分析方法的缺点,即分析之前需要复杂的样品处理和分离过程。因此,色谱技术是最重要的一种分析方法,同时也是目前应用最广泛的分析方法之一。色谱技术兼有分离效率高、分析速度快、检测灵敏度高等特点,使得其在咖啡的质量控制中占有不可或缺的地位。在实际应用中,通常将色谱技术与化学计量学进行结合以实现对咖啡产品的质量控制。     

Recent developments of artificial intelligence in drying of fresh food: A review

ABSTRACT

Intellectualization is an important direction of drying development and artificial intelligence (AI) technologies have been widely used to solve problems of nonlinear function approximation, pattern detection, data interpretation, optimization, simulation, diagnosis, control, data sorting, clustering, and noise reduction in different food drying technologies due to the advantages of self-learning ability, adaptive ability, strong fault tolerance and high degree robustness to map the nonlinear structures of arbitrarily complex and dynamic phenomena. This article presents a comprehensive review on intelligent drying technologies and their applications. The paper starts with the introduction of basic theoretical knowledge of ANN, fuzzy logic and expert system. Then, we summarize the AI application of modeling, predicting, and optimization of heat and mass transfer, thermodynamic performance parameters, and quality indicators as well as physiochemical properties of dried products in artificial biomimetic technology (electronic nose, computer vision) and different conventional drying technologies. Furthermore, opportunities and limitations of AI technique in drying are also outlined to provide more ideas for researchers in this area.     

添加猪油对馒头品质的改善

研究了猪油对酵母发酵性能,馒头品质及馒头老化的影响。实验结果表明,猪油能增加面团的膨发体积,改善馒头体积,色泽和组织结构,并在延缓馒头化方面起到了一定作用。     

复配型面包品质改良剂在板栗面包中的应用

首次利用面包品质改良剂对板栗面包的焙烤品质及延缓老化的作用效果进行了研究。依据各种改良剂对面包防老化效果的不同,确定出试验用改良剂为黄原胶、α-淀粉酶、单甘酯。分别以三种面包品质改良剂做单因素实验,实验结果表明:当黄原胶以板栗粉与面包粉总重量的0.5%、1%、1.5%、2%的比例添加到板栗面包中时,对板栗面包的感官品质及老化指标均产生了显著影响,当添加量为1%时,不但板栗面包具有良好的焙烤品质而且延缓了面包的老化;当α-淀粉酶按不同的比例添加时,在添加量为0.01%或0.005%时,板栗面包的抗老化效果及焙烤性能均较对照组好,但当添加量为0.03%、0.06%时,致使板栗面包芯发粘,面包醒发性能受阻;在单甘酯的单因素实验中,不同添加量的单甘酯对板栗面包的老化均有延缓作用,但对面包的焙烤品质均产生负面影响。选择几种改良剂的较优添加量做正交实验,实验结果表明:在板栗面包制作过程中按板栗粉及面包粉总重用量添加1.5%黄原胶、0%α-淀粉酶、0.3%单甘酯时,板栗面包具有良好的焙烤品质,且在贮存7d后,面包芯硬度比对照组下降44%,延缓了面包老化,延长了其货架期。     

Monitoring the authenticity of low-fat yogurts by an artificial neural network

The growing consumption of low- and reduced-fat dairy products demands routine control of their authenticity by health agencies. The usual analyses of fat in dairy products are very simple laboratory methods; however, they require manipulation and use of reagents of a corrosive nature, such as sulfuric acid, to break the chemical bounds between fat and proteins. Additionally, they generate chemical residues that require an appropriate destination. In this work, the use of an artificial neural network based on simple instrumental analyses, such as pH, color, and hardness (inputs) is proposed for the classification of commercial yogurts in the low- and reduced-fat categories (outputs). A total of 108 strawberry-flavored yogurts (48 probiotic low-fat, 36 low-fat, and 24 full-fat yogurts) belonging to several commercial brands and from different batches were used in this research. The statistical analysis showed different features for each yogurt category; thus, a database was built and a neural model was trained with the Levenberg-Marquardt algorithm by using the neural network toolbox of the software MATLAB 7.0.1. Validation with unseen data pairs showed that the proposed model was 100% efficient. Because the instrumental analyses do not require any sample preparation and do not produce any chemical residues, the proposed procedure is a fast and interesting approach to monitoring the authenticity of these products.     

基于BP神经网络的服装质量预测及其前景

文章通过调查和分析我国服装企业传统的质量管理中存在的问题,阐述了基于BP神经网络的服装质量预测的理论方法及其前景。     

An Updated Review of Meat Authenticity Methods and Applications

Adulteration of foods is a serious economic problem concerning most foodstuffs, and in particular meat products. Since high-priced meat demand premium prices, producers of meat-based products might be tempted to blend these products with lower cost meat. Moreover, the labeled meat contents may not be met. Both types of adulteration are difficult to detect and lead to deterioration of product quality. For the consumer, it is of outmost importance to guarantee both authenticity and compliance with product labeling. The purpose of this article is to review the state of the art of meat authenticity with analytical and immunochemical methods with the focus on the issue of geographic origin and sensory characteristics. This review is also intended to provide an overview of the various currently applied statistical analyses (multivariate analysis (MAV), such as principal component analysis, discriminant analysis, cluster analysis, etc.) and their effectiveness for meat authenticity.     

近红外光谱分析技术快速测定儿童高钙奶粉理化指标的研究

从化学计量学角度研究了近红外光谱技术测定儿童高钙奶粉理化指标的原理。使用多元线性回归法分别建立了近红外检测的儿童高钙奶粉水分、蛋白、脂肪、乳糖和蔗糖的快速测定模型。将近红外法测定结果和标准方法测定结果进行比较,结果吻合理想。近红外光谱法具有分析快速、操作方便、节约检测成本的优点,非常适合用于奶粉生产过程中的质量控制。     

煎炸油品质快速检测新方法研究进展

煎炸油的品质将直接影响煎炸食品的营养与安全。为了对煎炸油品质进行监控,目前我国出台了煎炸油卫生检测标准以及相应的检测方法。这些检测方法虽然可操作性强、成本低,但需消耗大量有机试剂、操作费时、繁琐,研究并开发快速、无损及可靠的检测方法很有必要。随着现代科学与技术的发展,一些新的快速检测技术与方法已用于煎炸油质量的快速检测。本文主要介绍电子鼻与电子舌技术、介电常数法、电导率法、低场核磁共振法、红外光谱法以及色谱法用于煎炸油样品中理化指标快速检测的原理以及具体应用。