Rice Research Institute of Iran RRII

Āmol, Iran

Rice Research Institute of Iran RRII

Āmol, Iran
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Khaleghi E.,Shahid Chamran University | Sorkheh K.,Shahid Chamran University | Chaleshtori M.H.,Rice Research Institute of Iran RRII | Ercisli S.,Atatürk University
3 Biotech | Year: 2017

Currently, study of the inter and the intra-population genetic disparity was done by use of the 200 Olea europaea L. which is found growing naturally in the nation of Iran, and this study was carried out by AFLP and IRAP markers. The fingerprints that were similar to the AFLP and the IRAP markers were evidence of high concentrations of heterozygosity and this shows that O. europaea L. is primarily the out crossing species. The average percentage of polymorphism is as shown below: 87.15 and 87.38% of the information used in regard to the AFLP and the IRAP, respectively.The gene disparity numerals on the population researched were 1.087 for HT and 0.871 for HS in regard to AFLP. For the IRAP it was 1.084 for HT and 0.860 for HS.The general values for genetic variations that are found in the O. europaea L. germplasm in the nation of Iran were then assessed through putting together the AFLP and the IRAP information so as to cover a larger genome. Arguing from the AFLP and the IRAP studies, it can be concluded that there are more levels of genetic variation at inter and the intra-population level for the O. europaea. © 2017, Springer-Verlag Berlin Heidelberg.


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.


Tabkhkar N.,Guilan University | Rabiei B.,Guilan University | Samizadeh Lahiji H.,Guilan University | Hosseini Chaleshtori M.,Rice Research Institute of Iran RRII
Agri Gene | Year: 2017

Drought is the most serious abiotic stress that limits crop production in rain-fed environments. In this study genetic diversity of SNAC1 gene investigated in a collection of 83 diverse rice accessions from different geographical origins. Amplification of SNAC1 gene exons was performed by combined hot start-touchdown PCR protocol. The average number of alleles was 9.5 alleles. A total of 6 rare alleles were identified from exons of SNAC1. The average gene diversity index, PIC (Polymorphism information content) and Shannon value were 0.8518, 0.8343 and 2.0469, respectively. Evolutionary study based on Ewens-Watterson test showed that exon 1 of SNAC1 gene was probability under genetic drift. To identify potential SSR markers in SNAC1 gene sequence, SSR distributions within rice SNAC1 gene sequence were mined. Totally 15 microsatellite loci were detected which tri-nucleotide motifs (8) was being most abundant, followed by di- (6) and tetra-nucleotide (1) motifs. Maximum loci were found in 3′ UTR (5) (Untranslated regions), followed by in 5′ UTR (4) and coding sequences (3 for each exon). The present study revealed genetic divergence of SNAC1 gene coding regions and also mined SSR distributions within SNAC1 gene sequence and introduced an optimized PCR method. This information can be used for the development of drought tolerant rice varieties. © 2017


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


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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