Volume 20 (2024)
Volume 19 (2023)
Volume 18 (2022)
Volume 17 (2021)
Volume 16 (2020)
Volume 15 (2019)
Volume 14 (2018)
Volume 13 (2017)
Volume 12 (2016)
Volume 11 (2015)
Volume 10 (2014)
Volume 9 (2013)
Volume 8 (2012)
Volume 7 (2011)
Volume 6 (2010)
Volume 5 (2009)
Volume 4 (2008)
Volume 3 (2007)
Volume 2 (2006)
Volume 1 (2005)
Food Engineering
Investigation of wild sage seed mucilage drying process (Salvia macrosiphon L.) with infrared radiation

Ghazale Amini; Fakhreddin Salehi; Majid Rasouli

Volume 17, Issue 4 , September and October 2021, , Pages 595-604


  Introduction: The dispersion of water soluble hydrocolloids (gums) in the aqueous system provides great technical importance, because they can improve the gel or enhance the thickening properties of food products. Wild sage seeds have significant amounts of gum with good functional properties that after ...  Read More

Classification of Parus strawberry fruit by combining image processing techniques and intelligent methods

Farhad Fatehi; Hadi Samimi Akhijahani

Volume 16, Issue 6 , January and February 2021, , Pages 87-99


  Nowadays, in modern agriculture, the combination of image processing techniques and intelligent methods has been used to replace smart machine instead of humans. In this study, an artificial image processing and artificial neural network (ANN) method was used to classify strawberry fruit of Parus variety. ...  Read More

Study on Firmness and texture changes of pear fruit when loading different forces and stored at different periods using artificial neural network

Mohammad Vahedi Torshizi; Mohsen Azadbakht

Volume 15, Issue 6 , January and February 2020, , Pages 113-132


  This study evaluated the effect of different dynamic and static loadings and different storage periods on the firmness of pear fruit. Pear fruit was first segregated into three groups of 27 pear in order to undergo three loadings: static thin-edge compression loading, static wide-edge compression loading ...  Read More

Modeling of hardness and drying kinetics of "quince" fruit drying in an infrared convection dryer using the artificial neural network

Amir Gitiban; Narmela Asefi

Volume 15, Issue 4 , September and October 2019, , Pages 465-475


  Introduction: Dried fruits are one of the most important non-oil exports and the efforts should be made to grow the economy of the country by increasing their exports to world markets. Meanwhile, quince juice contains various minerals including iron, phosphorus, calcium, potassium and rich in vitamins ...  Read More

Using artificial neural networks to predict thermal conductivity of pear juice

Zeynab Raftani Amiri; Hengameh Darzi Arbabi

Volume 11, Issue 6 , January and February 2016, , Pages 770-778


  Thermal conductivity is an important property of juices in the prediction of heat- and mass-transfer coefficients and in the design of heat- and mass-transfer equipment for the fruit juice industry. An artificial neural network (ANN) was developed to predict thermal conductivity of pear juice. Temperature ...  Read More

Prediction the moisture content of kiwifruit in vacuum drier using artificial neural network

Hossein Majidzadeh; Bagher Emadi; Abdolali Farzad

Volume 11, Issue 1 , March and April 2015, , Pages 107-117


  In this study, the moisture content of kiwifruit in vacuum dryer was predicted usingartificial neural networks (ANN) method. The drying temperatures (50, 60 and 70ºC), vacuum pressures(500, 550 and 600 mmHg), thicknesses of kiwifruit slices (3, 5 and 7mm) and drying times were considered as the ...  Read More

Prediction of Milk Components Impact on Recovery and Extraction of Enteric Viruses Genome Using Artificial Neural Networks and Adaptive Nero Fuzzy Inference System (ANFIS)

Mahood Sadeghi; Masoud Yavarmanesh; Mostafa Shahidi Noghabi

Volume 10, Issue 2 , July 2014


  Nowadays, it has demonstrated that viruses can be transmitted by water and foods. Therefore, it causes the research to develop for detecting different viruses in water and foods. Among foods, milk can transfer potentially pathogenic viruses. On the other hand, to achieve every method for recovery and ...  Read More

Optimization of Orange Osmotic Dehydration Process Using Response Surface Method and Estimation of Dehydration Parameters by Artificial Neural Network

Emad Aydani; Mahdi Kashani-Nejad; Mohsen Mokhtarian; Hamid Bakhshabadi

Volume 9, Issue 3 , October 2013


  In this study, Response Surface Methodology (RSM) was used to optimize osmo-dehydration of orange slice. Effect of osmotic solution temperature in the range of 30 to 60 °C, immersion time from 0 to 300 min and sucrose concentration from 35 to 65 brix degree on water loss, solid gain, moisture content, ...  Read More

Investigation of Malting Process Using Artificial Neural Network

Alireza Ghodsvali; Mohsen Mokhtarian; Hamid Bakhshabadi; Fatemeh Arabamerian

Volume 9, Issue 3 , October 2013


  Malting is a complex biotechnological process that includes steeping; germination and drying of cereal grains under controlled conditions of temperature and humidity. In this research malting process parameters were predict by modular neural network with different activation function included, logsig-logsig, ...  Read More