Using online image processing technique for measurement the browning in banana during drying (a new and automatic method)

Determination and controlling of quality parameters can be useful for ordering and marketing of fruits.  Color is the first and the most important parameter in the visual appearance of fruits, specifically in banana.  The aim of this study is to use image-processing technique (online operation) to measure and analyze the color change of banana slices during thin layer drying.  Using online-image-processing technique resulted in designing a machine vision system to control the color change of products automatically.  The results show a linear relation with high correlation coefficient for L*, a* and b* (0.967, 0.962 and 0.991 respectively) between the data of the image-processing technique and the hold-hand colorimeter.  In this study, parameters of chroma, hue and browning index were determined to describe the kinetics of color change in banana slices.  The change of chroma was not significant, but hue was decreased and browning index was increased during drying time.  In addition, the experimental data of the L* and ∆E was fitted using zero and first order models with high correlation coefficient (0.80-0.97).   Keywords: image processing, machine vision, online, banan

Development and application of a new low cost electronic nose for the ripeness monitoring of banana using computational techniques (PCA, LDA, SIMCA, and SVM)

Se ha estudiado la posible aplicación de una nariz electrónica basada en semiconductores de óxido metálico (e-nariz) como un instrumento que no sea destructivo para el seguimiento del cambio en la producción de volátiles de plátano durante el proceso de maduración. La propuesta de e-nariz no necesita ningún equipo de laboratorio avanzado o caro y resultó ser fiable en la grabación de las diferencias significativas entre las etapas de maduración. El Análisis de Componentes Principales (PCA), Análisis Discriminante Lineal (LDA), Modelado Suave Independiente de las Analogías de Clases (SIMCA) y Máquinas Soporte de Vectores (SVM) son técnicas utilizadas para este propósito. Los resultados mostraron que la dirección de la e-nariz distingue entre las diferentes etapas de maduración. La nariz electrónica fue capaz de detectar una clara diferencia en la huella digital de aroma de plátano cuando se utiliza el análisis de SVM en comparación con PCA o LDA y SIMCA. Utilizando el análisis de SVM, era posible diferenciar y clasificar las diferentes etapas de maduración de plátanos, y este método fue capaz de clasificar el 98,66% del total de muestras en su grupo respectivo. Las capacidades matrices de sensores en la clasificación de etapas de maduración usan el análisis de la carga y la SVM y SIMCA También se ha visto que conduce a desarrollar un sistema de e-nariz específico mediante la aplicación de los sensores más eficaces y a ignorar los sensores redundantesPotential application of a metal oxide semiconductor based electronic nose (e-nose) as a non-destructive instrument for monitoring the change in volatile production of banana during the ripening process was studied. The proposed e-nose does not need any advanced or expensive laboratory equipment and proved to be reliable in recording meaning¬ful differences between ripening stages. Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Soft Independent Modelling of Class Analogy (SIMCA) and Support Vector Machines (SVM) techniques were used for this purpose. Results showed that the proposed e-nose can distinguish between different ripening stages. The e-nose was able to detect a clear difference in the aroma fingerprint of banana when using SVM analysis compared with PCA and LDA, SIMCA analysis. Using SVM analysis, it was possible to differentiate and to classify the different banana ripening stages, and this method was able to classify 98.66% of the total samples in each respective group. Sensor array capabilities in the classification of ripening stages using loading analysis and SVM and SIMCA were also investigated, which leads to develop the application of a specific e-nose system by applying the most effective sensors or ignoring the redundant sensors.peerReviewe

Blackfly fever and dermatitis caused by Simulium kiritshenkoi: a human case report in Iran

BACKGROUND: Besides the considerable role of blackflies to the transmission of many disease agents, these flies considered as annoying biting pests of wildlife, livestock, poultry, and humans. There are few literature reports of blackfly fever following Simulium spp. This study describes a case of blackfly fever and dermatitis following blackflies numerous bites in Iran. CASE PRESENTATION: The present report describes a 25-year-old man that was attacked by numerous flies while fishing and camping near Namrood river in Firuzkuh County, Tehran Province, Iran. Pruritic dermatitis with marked edema appeared mainly on the hands and legs and subsequently, the patient's condition worsened with swollen lymph nodes, joints aching, and 40�°C fever. The patient's clinical signs and symptoms were alleviated by injection of intramuscular Dexamethasone Phosphate (DEXADIC®) 8�mg/2�ml after 24�h. CONCLUSIONS: This study reported a human case with blackfly fever and dermatitis following numerous bites of Simulium kiritshenkoi, for the first time in Iran

Description of Chordodes anthophorus (Gordiida) for the first time in Iran with an emphasis on scanning electron microscopy characters

We report a female Chordodes anthophorus from a Giant Asian Mantis (Hierodula membranacea) for the first time from Iran. Scanning electron microscopy (SEM) was used to describe the characters and substructures precisely. We demonstrate characteristic cuticular patterns for Chordodes anthophorus. The presence of five types of areoles including simple, tubercle, crowned and circumcluster areoles and also crowned areoles with long fi laments which is a common feature in females, confi rm our investigation. © 2021 S. Mohtasebi, M. J. Abbaszadeh Afshar, F. Tabatabaie, A. Schmidt-Rhaesa, published by Sciendo

Effectiveness of using integrated algorithm in preserving privacy of social network sites users

Social Network Sites (SNSs) are one of the most significant and considerable topics that draw researches attention nowadays. Recently, lots of people from different areas, ages and genders join to SNSs and share lots of different information about various things. Spreading information can be harmful for users' privacy. In this paper, first we describe some definitions of social networks and their privacy threats. Second, after reviewing some related works on privacy we explain how we can minimize the information disclosure to adversaries by using integrated algorithm. Finally we try to show the effectiveness of proposed algorithm in order to protect the users' privacy. The enhanced security by anonymizing and diversifying disclosed information presents and insures the paper aim

Mass and Surface Area Modeling of Bergamot (Citrus medica) Fruit with Some Physical Attributes

Rosana G. Moreira, Editor-in-Chief; Texas A&M UniversityThis is a paper from International Commission of Agricultural Engineering (CIGR, Commission Internationale du Genie Rural) E-Journal Volume 9 (2007): Mass and Surface Area Modeling of Bergamot (Citrus medica) Fruit with Some Physical Attributes. Manuscript FP 07 029. Vol. IX. October, 2007

Some Physical properties of Date Fruit (cv. Lasht)

Rosana G. Moreira, Editor-in-Chief; Texas A&M UniversityThis is a paper from International Commission of Agricultural Engineering (CIGR, Commission Internationale du Genie Rural) E-Journal Volume 9 (2007): Some Physical properties of Date Fruit (cv. Lasht). Manuscript FP 07 019. Vol. IX. August, 2007

Development and Evaluation of an Electronic Nose System Based on MOS Sensors to Detect and to Distinguish Lemon Essential Oils

Introduction Essences or essential oils are aromatic compounds that are found in different organs of the plants. Essences can be classified into three groups of natural, synthetic and natural like. Most of the methods that are used to detect and to distinguish essential oils are based on chromatographic methods. However, these analytical methods are time consuming and require expert operators to work with required devices. Moreover, it is necessary to prepare the samples. An electronic nose is known as a tool for mimicking the sense of smell. This tool usually consists of an array of sensors which are used to identify and to isolate a variety of complex odors at a low cost. Since there has been no research on the usage of an electronic nose system for detection and separation of essential oils, the purpose of this study is to develop and to evaluate an electronic nose system for identification and classification of various types of commercial lemon essential oils (synthetic types). Materials and Methods The proposed system consists of a sensor chamber, a sample chamber, an array of MOS sensors, electro valves, a pump, a data acquisition cart and, a processor. Essential oils used in this study includes  eight types of synthetic commercial lemon essential oils that were prepared by ((Avishan Khane Tabiat Sabz)) Company located in chemistry and chemical engineering research center of Iran. One gram sample of each essential oil was prepared to be placed in the sample chamber. Each experiment was carried out in 9 replicates and in three stages of 1- Baseline correction (250 s) 2- Sample smell injection (400 s) and 3- Sensors chamber cleaning (200 s). Data received from the sensors signals were initially preprocessed and normalized and then three methods of principal component analyses (PCA), linear discriminant analyses (LDA) and artificial neural network (ANN) were used to process the data. Both PCA and LDA methods were run using the Unscramble x10.4 software and the artificial neural network was used with the help of NeuroSolution 5 software. In ANN, the classification was carried out using a multilayer perceptron (MLP) and Leave-one-out technique. Leave-one-out is an acceptable method for evaluating the performance of the classification algorithms when the number of samples is low. Results and Discussion In order to analyze the data obtained from the sensor array, first, the principal components analysis (PCA) method was used. In this method, the first two principal components of PC 1 and PC 2 totally covered 99% of the data variance. Another plot called as loading plot was used to determine the effects of each sensor responses in pattern recognition analyzes. According to this plot, all sensors had high loading coefficients. In case of distinguishing the lemon essential oils, the results of the linear discriminant analysis (LDA) method showed that this method can distinguish eight types of lemon essential oils with an accuracy of %98. The artificial neural network (ANN) also separated the essential oils with the accuracy of the above %91. Conclusions An Electronic nose system based on semiconductor metal oxide sensors is a powerful tool that can be used as a substitute for traditional methods. In general, this study showed that the electronic nose system based on MOS sensors has the ability to detect and to distinguish commercial lemon essential oils. Considering the wide ranges and economical nature of the essential oils, it is suggested that applications of the electronic nose can be more expanded in the subject of the essential oils of different products

Design, Construction and Performance Evaluation of a Metal Oxide Semiconductor (MOS) Based Machine Olfaction (Electronic Nose) for Monitoring of Banana Ripeness

Aroma is one of the most important sensory properties of fruits and is particularly sensitive to the changes in fruit compounds. Gases involved in aroma of fruits are produced from the metabolic activities during ripening, harvest, post-harvest and storage stages. Therefore, the emitted aroma of fruits changes during the shelf-life period. The electronic nose (machine olfaction) would simulate the human sense of smell to identify and realize the complex aromas by using an array of chemical sensors. In this research, a low cost electronic nose based on six metal oxide semiconductor (MOS) sensors were designed, developed and implemented and its ability for monitoring changes in aroma fingerprint during ripening of banana was studied. The main components are used in the e-nose system include sampling system, an array of gas sensors, data acquisition system and an appropriate pattern recognition algorithm. Linear Discriminant Analysis (LDA) technique was used for classification of the extracted features of e-nose signals. Based on the results, the classification accuracy of 97/3% was obtained. Results showed the high ability of e-nose for distinguishing between the stages of ripening. It is concluded that the system can be considered as a nondestructive tool for quality control during banana shelf-life