Rice Research Institute of Iran RRII

Āmol, Iran

Rice Research Institute of Iran RRII

Āmol, Iran
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Ghafarian A.,Islamic Azad University at Khorasgan | Joharchi O.,Islamic Azad University at Khorasgan | Jalalizand A.,Islamic Azad University at Khorasgan | Jalaeian M.,Rice Research Institute of Iran RRII
ZooKeys | Year: 2013

This paper report on a new species of mites of the genus Myrmozercon associated with ant in Iran - Myrmozercon cyrusi Ghafarian and Joharchi sp. n. was collected associated of the Monomorium sp. in Kenevist Rural District in the Central District of Mashhad County, Khorasan Razavi Province, Iran. This new species is described and illustrations provided. Myrmozercon ovatum Karawajew, 1909 is suspected to be a junior synonym of M. brevipes Berlese, 1902 and host-specificity and host range of Myrmozercon are also reviewed. © Azadeh Ghafarian et al.

Khosravi J.,Islamic Azad University at Tehran | Asoodar M.A.,University of Agriculture and Natural Resources Ramin | Alizadeh M.R.,Rice Research Institute of Iran RRII | Peyman M.H.,Guilan University
World Applied Sciences Journal | Year: 2011

Rice is one of the most important food resources in Iran. Considering that Iran is one of the biggest rice importers, plans need to be set to pave the way for becoming self sufficient in the production of this product. Using a suitable rice milling system with low loss and reasonable costs is very important to reach this aim. Therefore, it is necessary to select the proper rice milling system considering all the effective parameters in the efficiency of rice milling systems. For this aim a proper technical Multi-Criteria Decision Making (MCDM) was used to select the most proper rice milling system. The optimization process was accomplished using multiple criteria decision making system compensatory (TOPSIS). Several aspects, the percentage of white rice breakage, the market appeal of final production, energy consumption, the capacity of systems and system's costs were considered as rice milling attributes. Three kinds of traditional and modern rice milling systems were defined as rice milling candidate alternatives. The TOPSIS technique indicated that the percentage of white rice breakage by 0.01 score is the most important decision making factor in selecting rice milling system and system's costs with 0.88 score is a less important parameter. Although the results of TOPSIS technique showed rice milling system 3 with the highest value (0.84) was the most suitable systems. © IDOSI Publications, 2011.

PubMed | Ubonratchathani Rice Research Center, Cambodian Agricultural Research and Development Institute, Max Planck Institute of Molecular Plant Physiology, Copenhagen University and 11 more.
Type: | Journal: Metabolomics : Official journal of the Metabolomic Society | Year: 2016

The quality of rice in terms not only of its nutritional value but also in terms of its aroma and flavour is becoming increasingly important in modern rice breeding where global targets are focused on both yield stability

Farahpour-Haghani A.,Rice Research Institute of Iran RRII | Jalaeian M.,Rice Research Institute of Iran RRII | Landry B.,Museum dhistoire naturelle
Nota Lepidopterologica | Year: 2016

During a survey at the Rice Research Institute of Iran (RRII, Rasht, Guilan) for potential biocontrol agents of water fern, Azolla filiculoides Lam. (Pteridophyta: Azollaceae), larvae of Diasemiopsis ramburialis (Duponchel) (Pyralidae s. l., Spilomelinae) were discovered feeding on water fern. Larvae were found to cause serious feeding damage on leaves of water fern in the laboratory. The biology, life cycle, and the mor-phology of all stages of this species are described and illustrated for the first time. This is also the first record of this cosmopolitan species in Iran. We report water fern as a host for Diasemiopsis ramburialis; until now the host plant of D. ramburialis was unknown.

Alizadeh M.R.,Rice Research Institute of Iran RRII | Rahimi-Ajdadi F.,Rice Research Institute of Iran RRII | Dabbaghi A.,Rice Research Institute of Iran RRII
Australian Journal of Crop Science | Year: 2011

The exact knowledge of stem cutting energy is one of the main parameters for optimizing design of cutting elements in harvesting machines. In this study, cutting energy of rice stem at different internode positions was examined. Four common Iranian rice varieties, namely Khazar, Hybrid and Dorfak (high-yielding and lodging tolerance varieties) and Tarom (local and lodging susceptible variety) were used in the experiment. A pendulum impact type testing apparatus was fabricated and used for the tests. The results indicated that cutting energy significantly (p<0.01) affected by internode position and dimensional characteristics of rice stem. Among the varieties, the highest cutting energy (324 mJ) was registered for Khazar, while the lowest value (79 mJ) was measured for Tarom. There was a highly significant and positive correlation between the cutting energy and stem wall thickness, Major and minor diameters and cross-sectional area of rice stem. The results also revealed that the cutting energy of rice stem in the second internode was decreased by the average of 32.5% compared to third internode position. It was concluded that with increasing cutting height toward the second internode, more energy saving can be achieved by harvesting machines.

Zareiforoush H.,Tarbiat Modares University | Minaei S.,Tarbiat Modares University | Alizadeh M.R.,Rice Research Institute of Iran RRII | Banakar A.,Tarbiat Modares University
Food Engineering Reviews | Year: 2015

Among the cereals, rice is the major foodstuff for a large part of the world’s population. Due to its tremendous importance in the global market, its qualitative economic aspects during processing have always been attended by producers. As the most delicate of the cereals, rice needs the utmost care during post-harvest handling and processing, because in most cases, it is consumed as whole kernel. The growing demand for production of rice with high-quality and safety standards has increased the need for its accurate, fast and objective quality monitoring. Computer vision techniques, as novel technologies, can provide an automated, nondestructive and cost-effective way to achieve these requirements. In recent years, various studies have been conducted to evaluate rice qualitative features based on computer vision techniques. This paper presents the theoretical and technical principles of computer vision for nondestructive quality assessment of rice combined with a review of the recent achievements and applications for quality inspection and monitoring of the product. © 2015, Springer Science+Business Media New York.

Alizadeh M.R.,Rice Research Institute of Iran RRII
Australian Journal of Crop Science | Year: 2011

Paddy husking operation is one of the most important stages during milling process, which effectively determines the quantitative and qualitative losses of rice. In this study, the effect of four levels of husked ratio (HR) of 0.6, 0.7, 0.8 and 0.9 on broken brown rice (BBR), broken milled rice (BMR) and rice whiteness (RW) was examined. Three common Iranian rice varieties, namely Binam, Khazar and Sepidroud were used as raw materials. A commercial rice milling system including rubber rolls husker and blade-type whitener was considered in the experiment. The results revealed that the BBR increased significantly (P<0.01) from 7.42 to 10.28%, 9.17 to 13.39% and 15.17 to 21.82% for Binam, Khazar and Sepidroud varieties, respectively as the HR increased from 0.6 to 0.9. The lowest BMR for varieties of Binam (17.83%), Khazar (23.35%) and Sepidroud (28.90%) were obtained at the HR of 0.8. By increasing the HR from 0.6 to 0.9, the RW decreased from 36.1 to 30.8, 36.5 to 30.1 and 35.4 to 29.8 for Bianm, Khazar and Sepidroud varieties.

Zareiforoush H.,Urmia University | Komarizadeh M.H.,Urmia University | Alizadeh M.R.,Rice Research Institute of Iran RRII
Biosystems Engineering | Year: 2010

The effects of product moisture content (MC), conveyor inclination and rotational speed on paddy grain damage during handling with an adjustable screw auger were evaluated. The experiments were conducted at three levels of MCs, namely 8, 11, and 14% w.b., three conveying inclinations (CIs) (10, 20 and 30° included angle), and five levels of rotational speed (100, 200, 300, 400 and 500. rpm). Paddy grains damage was determined in terms of broken grains (BGs), husked grains (HGs), husked-cracked grains (HCG) and cracked grains (CGs). The results revealed that the values of damaged grains significantly increased with increasing the rotational speed of the screw auger. It was concluded that increasing the MC of the grains significantly reduced the values of BGs, HGs and CGs. Although the effect of conveyor inclination was significant on the value of HGs, inclination did not significantly affect the other characteristics evaluated. The highest values of broken, husked, husk-cracked and CGs were obtained at a MC of 8% w.b., a rotational speed of 500. rpm and an inclination angle of 30°; whilst the lowest values were acquired at the MC of 14% w.b., a rotational speed of 100. rpm and an inclination angle of 10°. © 2010 IAgrE.

Zareiforoush H.,Tarbiat Modares University | Minaei S.,Tarbiat Modares University | Alizadeh M.R.,Rice Research Institute of Iran RRII | Banakar A.,Tarbiat Modares University
Measurement: Journal of the International Measurement Confederation | Year: 2015

In this research, a fuzzy inference system (FIS) coupled with image processing technique was developed as a decision-support system for qualitative grading of milled rice. Two quality indices, namely degree of milling (DOM) and percentage of broken kernels (PBK) were first graded by rice processing experts into five classes. Then, images of the same samples were captured using a machine vision system. The information obtained from the sample image processing was transferred to FIS. The FIS classifier consisted of two input linguistic variables, namely, DOM and PBK, and one output variable (Quality), all in the form of triangle membership functions. Altogether, 25 rules were considered in the FIS rule base using the AND operator and Mamdani inference system. In order to evaluate the developed system, statistical performance of the FIS classifier was compared with the experts' judgments. Results of analysis showed a 89.8% agreement between the grading results obtained from the developed system and those determined by the experts. © 2015 Elsevier Ltd. All rights reserved.

PubMed | Tarbiat Modares University and Rice Research Institute of Iran RRII
Type: Journal Article | Journal: Journal of food science and technology | Year: 2016

Qualitative grading of milled rice grains was carried out in this study using a machine vision system combined with some metaheuristic classification approaches. Images of four different classes of milled rice including Low-processed sound grains (LPS), Low-processed broken grains (LPB), High-processed sound grains (HPS), and High-processed broken grains (HPB), representing quality grades of the product, were acquired using a computer vision system. Four different metaheuristic classification techniques including artificial neural networks, support vector machines, decision trees and Bayesian Networks were utilized to classify milled rice samples. Results of validation process indicated that artificial neural network with 12-5*4 topology had the highest classification accuracy (98.72%). Next, support vector machine with Universal Pearson VII kernel function (98.48%), decision tree with REP algorithm (97.50%), and Bayesian Network with Hill Climber search algorithm (96.89%) had the higher accuracy, respectively. Results presented in this paper can be utilized for developing an efficient system for fully automated classification and sorting of milled rice grains.

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