矿物填充保鲜膜的研制与应用

研究了利用无机矿物填料填充改性聚乙烯薄膜制备果蔬保鲜膜的方法.通过各项基本性能的测试,自制的保鲜膜完全符合果蔬保鲜包装的要求.同时,通过对几种果蔬的实际包装试验,证明该保鲜膜可以有效的抑制果蔬的呼吸强度,延缓果蔬衰老,维持良好的贮藏质量.     

1-MCP在果蔬保鲜上的应用

介绍了乙烯作用抑制剂1-MCP的性质、使用方法,并综述1-MCP在果蔬(苹果、秦王桃、番茄、鲜枣等)的保鲜上的应用     

Pesticide residues in fruits and vegetables in Jordan using liquid chromatography/tandem mass spectrometry

A total of 158 fruit and vegetable samples produced in Jordan were examined for the presence of pesticide residues using the multi-residue analysis technique by Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS) and the QuEchERS extraction method. A total of 73 samples (46%) were free from detectable residues, while 85 samples (54%) contained residues. Among the tested samples, 34 (22%) contained residues above Maximum Residue Levels (MRLs) and 51 (32%) contained residues at or below MRLs. Most of the detected residues were found in sweet pepper, peach and apricot samples. Only watermelon samples were free from detectable residues, while tomato and melon samples exhibited residues below MRLs. Out of the 113 pesticides tested, 22 pesticides were found above the limit of detection, 9 of which (hexaconazole, propargite, propiconazole, myclobutanil, thiamethoxam, thiacloprid, clothianidin, clofentezine and pyridaben) had residues that violate MRLs according to European regulations. A continuous monitoring programme for pesticide residues in Jordanian fruits and vegetables is highly recommended.     

超声波提取白英果红色素的工艺研究

白英浆果有大量的红色素，是一种天然色素资源，超声波提取技术具有时间短、效率高、提取量高等特点，同时可防止提取物在长时间、高温条件下发生降解、褪色等变化。研究了超声波提取白英浆果红色素的提取剂的种类、用量、提取温度和时间对色素提取量的影响，并用正交试验优化出试验条件下白英果红色素的最佳提取工艺条件：乙醇浓度80％，固液比1：6kg/L，浸提温度40℃，超声浸提时间70min。     

基于LabVIEW的干燥过程果蔬内部温度测试

温度是影响果蔬干燥过程的重要参数之一。采用探针法设计了一种测试干燥过程果蔬内部温度的系统。该系统以LabVIEW为平台开发虚拟面板,实时显示图形数值温度数据并进行数据保存,有效运用Tab控件实现菜单式友好用户界面;NI9205模块采集信号经过A/D转换,经下位机NI CompactDAQ的USB总线传送至计算机,构建完整的USB数据采集过程。实际应用表明,系统能实时监测干燥过程果蔬内部的温度变化,为干燥过程果蔬内部热传递现象的研究提供有效途径。     

Fruits and Vegetables Freshness Categorization Using Deep Learning

The nutritional value of perishable food items, such as fruits and vegetables, depends on their freshness levels. The existing approaches solve a binary class problem by classifying a known fruitvegetable class into fresh or rotten only. We propose an automated fruits and vegetables categorization approach that first recognizes the class of object in an image and then categorizes that fruit or vegetable into one of the three categories: pure-fresh, medium-fresh, and rotten. We gathered a dataset comprising of 60K images of 11 fruits and vegetables, each is further divided into three categories of freshness, using hand-held cameras. The recognition and categorization of fruits and vegetables are performed through two deep learning models: Visual Geometry Group (VGG-16) and You Only Look Once (YOLO), and their results are compared. VGG-16 classifies fruits and vegetables and categorizes their freshness, while YOLO also localizes them within the image. Furthermore, we have developed an android based application that takes the image of the fruit or vegetable as input and returns its class label and its freshness degree. A comprehensive experimental evaluation of proposed approach demonstrates that the proposed approach can achieve a high accuracy and F1score on gathered FruitVeg Freshness dataset. The dataset is publicly available for further evaluation by the research community.     

COMBINED INNOVATIVE HEAT PUMP DRYING TECHNOLOGIES AND NEW COLD EXTRUSION TECHNIQUES FOR PRODUCTION OF INSTANT FOODS

There is an increased demand for convenient foods including ready-to-eat and instant products. These products are desired with minimum concentration of synthetic chemicals. This creates challenges for the food industry and dryers manufactures to develop new technologies to process difficult-sensitive materials and to supply final products with high quality and improved properties. Fruits and vegetables are mainly composed of water, carbohydrates, proteins and lipids. Due to modification of chemical and physical bonds the compounds the material becomes viscous and sticky during processing. Conventional dryers have limitations in handling such sensitive materials. Heat pump dryers have been applied in the production of a diversity of ready-to-eat foods and dried instant products for the last five years at SINTEF-NTNU. Besides being energetically efficient and environmentally friendly, the heat pump drying technology provides a wide range of drying conditions as required to produce powders with improved characteristics. This work describes the new technologies and processing line for the production of instant foods as well as the measurements on the properties and quality attributes for raw, intermediate and final instant products.     

Mathematical model for intermittent microwave convective drying of food materials

Intermittent microwave convective drying (IMCD) is an advanced technology that improves both energy efficiency and food quality in drying. Modeling of IMCD is essential to understand the physics of this advanced drying process and to optimize the microwave power level and intermittency during drying. However, there is still a lack of modeling studies dedicated to IMCD. In this study, a mathematical model for IMCD was developed and validated with experimental data. The model showed that the interior temperature of the material was higher than the surface in IMCD, and that the temperatures fluctuated and redistributed due to the intermittency of the microwave power. This redistribution of temperature could significantly contribute to the improvement of product quality during IMCD. Limitations when using Lambert’s law for microwave heat generation were identified and discussed.     

Decontamination by ultrasound application in fresh fruits and vegetables

Changes in consumer eating habits, health concerns, and convenient and practical foods have led to an increased demand for fruit and vegetable products. Food safety is essential considering that there are reports of outbreaks involving the consumption of fruits and vegetables contaminated with pathogens. Washing associated with sanitizer procedure is considered as a critical step to satisfy hygienic and sanitary requirements and maintain the sensory and nutritional characteristics of fruits and vegetables. Chemical compounds are widely applied to clean and sanitize fresh fruits and vegetables, and some of these chemicals, such as the inorganic chlorine compounds, produce by-products that are dangerous to human health. The use of ultrasound is a technology that is gaining ground in the food industry. Ultrasound is a form of energy generated by sound waves at frequencies that are too high to be detected by the human ear. In ultrasound, the removal of dirt and food residues from surfaces and the inactivation of microorganisms occur as a consequence of cavitation, which is the formation, growth and collapse of bubbles that generate a localized mechanical and chemical energy. There are indications that this technology can be used in the food industry, alone or associated with chemical sanitizers. In this paper, we discuss the principles, mechanisms and effects of ultrasound on fruits and vegetables as a sanitization technology.     

European Union proficiency tests for pesticide residues in fruit and vegetables from 2009 to 2016: Overview of the results and main achievements

The European Union Reference Laboratory for pesticide residues in Fruits and Vegetables (EURL-FV) is organising, every year since 2004, the European Commission Proficiency Test for multiresidue analysis of pesticides in fruits and vegetables (EUPT-FV), which is directed to all National Reference Laboratories (NRLs) and all Official Laboratories (OfLs) responsible for pesticide residue control in the European Union. This work provides an updated overview of the last eight editions of EUPT-FV (2009–2016), highlighting the main difficulties encountered by the participant laboratories and the key achievements in the field of sample extraction and data dispersion and statistical evaluation. The number of participant laboratories was every year increasing from 151 in 2009 (EUPT-FV11) to 191 in 2016 (EUPT-FV18), and the total number of pesticide residue results reported by the laboratories in this period was close to 18,000. The percentage of acceptable, questionable and unacceptable z scores values assigned in each one of these eight EUPT-FVs has remained very similar with average values of 91.8, 3.5, and 4.7 percent, respectively. The large amount of data results evaluated has led to a strengthening in the use of the 25 percent fit-for-purpose relative standard deviation (FFP-RSD) as well as the use of an internationally accepted 50 percent target expanded measurement uncertainty default value when reporting results for multiresidue analysis of pesticides.