with the collaboration of Iranian Society of Mechanical Engineers (ISME)
Precision Farming
A Data-driven Model for Predicting the Yield of Recoverable Sugar from Sugarcane

F. Nadernejad; D. M. Imani; M. R. Rasouli

Volume 12, Issue 4 , December 2022, , Pages 543-558

https://doi.org/10.22067/jam.2021.69805.1034

Abstract
  IntroductionSugarcane is a strategic agricultural product and increasing productivity and self-sufficiency in its production is of special importance. The most important product of sugarcane is sugar. Various factors like climatic and management conditions affect the yield of sugarcane and recoverable ...  Read More

Image Processing
Identification of Idiocerus stali (Hem.: Cicadellidae) Using Image Processing and Artificial Neural Networks

Z. Azizpour; H. Vahedi; A. N. Lorestani

Volume 12, Issue 2 , June 2022, , Pages 107-118

https://doi.org/10.22067/jam.v12i2.81004

Abstract
  IntroductionPistachio or Green Gold is one of the most important agricultural crops and is especially important for Iranian exports. A group of pistachio's pests mainly feed on pistachio, among which Idiocerus stali is very important. Conventional methods for identifying insects using identification ...  Read More

Spectral Feature Selection from the Hyperspectral Dataset to Identify Pistachio Leaves Infected by Psylla

A. Moghimi; A. Sazgarnia; M. H. Aghkhani

Volume 12, Issue 2 , June 2022, , Pages 159-167

https://doi.org/10.22067/jam.v12i2.82089

Abstract
  IntroductionPistachio production has been adversely affected by Psylla, which is a devastating insect. The primary goal of this study was to select sensitive spectral bands to distinguish pistachio leaves infected by Psylla from healthy leaves. Diagnosis of psylla disease before the onset of visual cues ...  Read More

Estimation of the Best Classification Algorithm and Fraud Detection of Olive Oil by Olfaction Machine

M. R. Zarezadeh; M. Aboonajmi; M. Ghasemi-Varnamkhasti; F. Azarikia

Volume 11, Issue 2 , 2021, , Pages 371-383

https://doi.org/10.22067/jam.v11i2.84105

Abstract
  IntroductionExtra Virgin Olive Oil (EVOO) is one of the most common and popular edible oils which is an important part of the Mediterranean diet. It is a rich source of sterol, phenol compounds and vitamins A and E. EVOO has useful effects on human body and significant reduction of cardiovascular diseases ...  Read More

Early Detection of Fire Blight Disease of Pome Fruit Trees Using Visible-NIR Spectrometry and Dimensionality Reduction Methods

N. Bagheri; H. Mohamadi-Monavar

Volume 10, Issue 1 , 2020, , Pages 37-48

https://doi.org/10.22067/jam.v10i1.71911

Abstract
  Fire Blight (FB) is the most destructive bacterial disease of pome fruit trees around the world. In recent years, spectrometry has been shown to be an accurate and real-time sensing technology for plant disease detection. So, the main objective of this research is early detecting FB of pear trees by ...  Read More

Detection of Two Types of Weed through Machine Vision System: Improving Site-Specific Spraying

S. Sabzi; Y. Abbaspour Gilandeh; H. Javadikia

Volume 8, Issue 1 , 2018, , Pages 15-29

https://doi.org/10.22067/jam.v8i1.60647

Abstract
  Introduction With increase in world population, one of the approaches to provide food is using site-specific management system or so-called precision farming. In this management system, management of crop production inputs such as fertilizers, lime, herbicides, seed, etc. is done based on farm location ...  Read More

Pattern Recognition of Near-Infrared Spectroscopy for Non-Destructive Discrimination of Oranges Based on Taste Index

B. Jamshidi; S. Minaei; E. Mohajerani; H. Ghassemian

Volume 5, Issue 1 , 2015, , Pages 101-110

https://doi.org/10.22067/jam.v5i1.28211

Abstract
  In recent years, application of near-infrared spectroscopy (NIR) as a non-destructive technique combined with chemometric methods has been widely noticed for quality assessment of food and agricultural products. In chemometric methods, quality analyses are important issues which could be related to pattern ...  Read More

Making Weed Management Maps by Artificial Neural Networks for Using in Precision Agriculture

A. Rohani; H. Makarian

Volume 1, Issue 2 , 2011

https://doi.org/10.22067/jam.v1i2.11355

Abstract
  With the rise of new powerful statistical techniques and neural networks models, the development of predictive species distribution models has rapidly increased in ecology. In this research, a learning vector quantization (LVQ) and multi layer perceptron (MLP) neural network models have been employed ...  Read More