The need to increase wheat yield and quality, tolerance to biotic and abiotic stresses, adaptation to climate change, and the increase in the world population have increased the need for wheat breeding through its wild ancestors, including emmer wheat (Triticum turgidum   .dicoccoides). Emmer wheat's ability to produce high yields in poor soils, and its resistance to disease and tolerance to drought and heat stress have made it an important species with a very rich gene pool. In the present study, in order to investigate the genetic diversity of Amr wheat germplasm in terms of phenological and agromorphological characteristics as well as grain quality traits including iron, zinc and soluble protein concentrations, 150 Amr wheat genotypes originating from different countries (Iran, Syria, Turkey, Lebanon, Iraq and occupied Palestine) were evaluated in an alpha lattice design with two replications in the 1401-1402 crop year under rainfed and supplementary irrigation conditions at the research farm of the Agricultural and Natural Resources Campus of Razi University. The results of the combined analysis of variance showed that the effect of environment was significant for all measured traits except spike length and peduncle length, the effect of genotype was significant for all traits except leaf chlorophyll index, and the interaction effect of genotype × environment was significant for all traits except leaf chlorophyll index and days to spike. The highest general heritability (0.86) was obtained for the plant height trait under dryland conditions, which can indicate the possibility of successful selection for this trait. Based on the results of phenotypic and genotypic correlation analysis in both conditions, plant height had a positive and significant correlation with spike length and number of grains per spike, as well as spike length with number of grains per spike and peduncle length. In both conditions, a positive and significant correlation was observed between the grain iron and zinc content traits, and it is likely that these two traits can be increased simultaneously. In supplementary irrigation conditions, a negative and significant correlation was observed between zinc content and grain soluble protein. Cluster analysis using UPGMA and WARD methods was performed based on the measured traits, and according to the results of the false F, the Amer wheat genotypes were divided into four groups under dryland conditions and into two groups under supplementary irrigation conditions. Keywords: Genetic diversity, drought tolerance indices, phenological traits, grain quality traits, morphological traits, Amer wheat  

  abstract Porous weirs in river engineering have recently attracted the attention of researchers due to their advantages over the solid type. The hydrodynamics of this type of overflows is more complicated due to the flow of both internal and overpassing. In this research, the aim of the numerical analysis of the hydrodynamics of the wide-edge porous spillway body is. For this purpose, a total of 243 different models including 9 different overflow geometries with three different porosity of materials (40%, 47% and 50%) and 9 different flow rates between 10 and 30 liters per second have been analyzed in three dimensions using FLOW-3D numerical model. is In this research, the determination of the optimal granulation arrangement of the materials, the determination of the discharge coefficient based on different porosities, as well as the comparison with the theoretical relationships, as well as the examination of the hydraulic parameters and the presentation of relationships in this regard, have been discussed.

   آگاهي از وضعيت تغذيه­اي باغات ميوه به منظور افزايش كميت و كيفيت محصول يك امر ضروري و اجتناب­ناپذير است. همچنين، مديريت پايدار حاصلخيزي خاك يكي از مؤلفه­هاي مهم مديريت خاك در راستاي كشاورزي پايدار است كه ارزيابي آن از طريق سنجش ويژگي­هاي شيميايي و زيستي امكان­پذير مي­باشد. اين پژوهش با هدف بررسي تأثير چالكودهاي تلفيقي مختلف از كودهاي آلي، شيميايي و زيستي بر رفع كلروز آهن در درختان هلو و شليل، تعادل عناصر غذايي در برگ و ميوه درختان تيمار شده و برخي ويژگي­هاي شيميايي و زيستي خاك انجام گرفت. پيش از اعمال تيمارهاي چالكود، نمونه­هاي خاك از دو عمق 30-0 و 60-30 سانتي­متري به ‌صورت مركب از باغ مورد مطالعه تهيه و ويژگي­هاي شيميايي (pH، EC، ماده آلي و فسفر و پتاسيم فراهم) و زيستي (تنفس پايه، كربن زيست­توده ميكروبي، تنفس ناشي از سوبسترا و كسر متابوليك) آن­ها تعيين شدند. اين پژوهش به صورت آزمايش فاكتوريل در قالب بلوك­هاي كامل تصادفي در 3 بلوك و 5 تيمار اجرا شد. اواسط اسفند 1398، تيمارهاي آزمايشي به صورت چالكود در يك سوم بيروني سايه­انداز درختان به اين صورت اعمال شدند: كود دامي كاملاً پوسيده (A)، كود دامي + اوره + فسفات آمونيوم + كلات آهن سكوسترين (B)، كود دامي + اوره + فسفات آمونيوم + كلات آهن سكوسترين + باكتري باسيلوس (C)، كود دامي + اوره + فسفات آمونيوم + كلات آهن سكوسترين + تيوباسيلوس + گوگرد پودري (D)، كود دامي + اوره + فسفات آمونيوم + كلات آهن سكوسترين + باكتري باسيلوس + تيوباسيلوس + گوگرد پودري (E). مقادير نيتروژن، فسفر، پتاسيم، آهن، منگنز، مس و روي در برگ و ميوه درختان در سال­هاي 1399 و 1400 و كلروفيل برگ در سال 1400 اندازه­گيري شدند. پس از برداشت ميوه­ها در تابستان 1400، نمونه­هاي خاك از دو عمق 30-0 و 60-30 سانتي­متر و از كنار محل چالكود با استفاده از اوگر برداشته شد. ويژگي­هاي شيميايي و زيستي در خاك­هاي تيمار شده، اندازه­گيري و با ويژگي­هاي خاك قبل از چالكود مقايسه شدند. نتايج نشان داد كه كمترين و بيشترين مقادير كلروفيل برگ و عناصر غذايي در برگ و ميوه هلو و شليل به ترتيب در تيمارهاي A و E به دست آمدند. بر اساس آناليز واريانس كيت-نلسون، عملكرد 1/50 و 2/43 كيلوگرم در درخت به عنوان عملكرد بحراني براي تفكيك جامعه با عملكرد بالا (تيمارهاي D و E) از جامعه با عملكرد پايين (تيمارهاي A، B و C) به ترتيب در درختان هلو و شليل به دست آمد. آهن و فسفر، محدودكننده­ترين عناصر غذايي در برگ و ميوه هلو و شليل در جامعه با عملكرد پايين بودند. همچنين، نتايج نشان داد كه pH خاك­هاي چالكود شده به طور معني­داري نسبت به خاك شاهد كاهش يافت و كمترين مقدار pH مربوط به تيمار E بود. همچنين، با افزايش عمق، مقدار pH در خاك­هاي چالكود شده كاهش پيدا كرد، در حالي­كه در خاك شاهد افزايش يافت. مقدار EC خاك­هاي چالكود شده به طور معني­داري بيشتر از خاك شاهد بود. با اين حال، افزايش EC در خاك­هاي تيمار شده به اندازه­اي نبود كه منجر به شوري خاك شود. اثر تيمارهاي چالكود بر افزايش مقدار ماده آلي خاك معني­دار بود. مقدار ماده آلي خاك در عمق 30-0 سانتي­متري، از 09/2 تا 23/2 درصد متغير بود كه بيشترين و كمترين مقدار آن به ترتيب براي خاك شاهد و تيمار E به دست آمد. دامنه اين پارامتر در عمق 60-30 سانتي­متري، 90/2-69/1 درصد بود كه بر خلاف لايه اول، بيشترين مقدار در تيمار E و كمترين مقدار در خاك شاهد اندازه­گيري شد. مقدار فسفر فراهم خاك به طور معني­داري نسبت به شاهد افزايش پيدا كرد، در حالي­كه بين مقادير اين پارامتر در خاك­هاي چالكود شده، تفاوت معني­داري وجود نداشت. مقدار پتاسيم فراهم در خاك­هاي چالكود شده به طور معني­داري نسبت به شاهد افزايش پيدا كرد و اين تفاوت در عمق 60-30 سانتي­متري چشمگيرتر بود. تيمارهاي چالكود به طور معني­داري تنفس پايه، تنفس ناشي از سوبسترا و كربن زيست­توده ميكروبي را نسبت به شاهد افزايش دادند، در حالي­كه اثر آن­ها بر كسر متابوليك معني­دار نبود. به طور كلي، مي­توان گفت كه مديريت تلفيقي چالكود در تيمار E، بيشترين تأثير را در بهبود كلروز آهن، تعادل تغذيه­اي درختان و كيفيت شيميايي و زيستي خاك داشت.

   One of the most important topics in mycological sciences is the topic of identifying nonedible mushrooms and identifying them from edible mushrooms. Today, the number of people who get poisoned by consuming nonedible mushrooms is increasing. As a result, the detection and separation of edible mushrooms from nonedible ones is of great importance. Considering the research in this field and the need to perform high-cost and somewhat inaccessible tests such as GC, methods should be sought. It was an alternative to these tests. The method of artificial intelligence and electronic nose is a non-destructive and accessible method with a much lower cost compared to GC. In fact, the purpose of this experiment is to study an olfactory system to distinguish edible mushrooms from poisonous mushrooms based on electronic nose technology and to help maintain health and treat diseases and reduce poisoning caused by poisonous mushrooms. Therefore, in this research, an olfactory system was used to detect and identify edible and nonedible mushrooms. ANN methods, PCA principal component analysis, LDA linear discriminant analysis, QDA 2nd degree linear discriminant analysis and SVM support vector machine were used to analyze the data obtained from the olfactory system. The classification of the data obtained from the signals obtained from the sensor array showed that the LDA, QDA and ANN methods have a very good performance in separating mushrooms based on their edible and nonedible nature and high accuracy in classification. Obtained. The use of QDA method to separate and classify different types of edible and nonedible mushrooms was more effective and accurate than LDA method.

  Tomato paste is the main tomato product that is prepared commercially or traditionally at home. According to the definition of the World Health Organization, adding any unauthorized and harmful substances to the food basket of humans and animals is called fraud. Sometimes the profit seeker puts in food to reduce the production costs and get more profit and endangers human health. Therefore, it is necessary to use new methods with a fast and high response level to identify additives in the paste. It is completely reduced or destroyed, in this case such a food item is corrupted and it is called rotten. In this research, it is tried to be able to provide the nutritional health of the communities with the help of smelling machine, in addition to detecting corruption in tomato paste, by identifying common frauds, including the identification of unauthorized preservative additives in tomato paste. In this research, the work was carried out in two sections, examining the experiments of the fraud section and the experiments of the corruption section. In order to evaluate these changes, the physicochemical tests of the paste, which included the measurement of pH, acidity, Brix, sediment weight percentage and smell test, were performed. According to the results of the confusion matrix of LDA and C-SVM methods, both methods performed well in detecting different percentages of potassium sorbate and sodium benzoate. LDA also performed better than C-SVM with 100% recognition accuracy. C-SVM and PCA could distinguish with high accuracy the samples containing sodium benzoate and potassium sorbate in 0.1 and 0.05 percent. The PLS model was the best model for predicting acidity and the MLR model was the best model for predicting sediment weight percentage, Brix and pH. TGS2620 sensors,. MQ135, TGS2602 had the highest sensitivity in identifying adulterated tomato paste samples.

   in this study, using three electric nose devices to detect and estimate the amount of oil odor per 500 km of car operation, refractometer to determine the concentration of each sample of oil, calorimeter to measure the amount of paint after every 500 km of operation, engine oil operation We estimated. We used PCA, LDA and neural network to >Based on the scoring and loading diagrams of various data (olfactory data, color data and integrated color, odor and brix data in both standard and normal methods) in the PCA principal component analysis method to detect distance or kilometers traveled. The results showed that the variance of the color data of the first and second major components was 98% and 1%, respectively. The most changes were observed in the color data. All samples of oils were well separated and >According to the neural network perturbation matrix, the 0.7372, R2 = 0.8677 and R2 = 0.6045, respectively, which are the values of R2 for the PLS model. For color change, brix and mileage were higher, and in general the data predicted in the PCR model were closer to the actual data Arshak, K., Moore, E., Lyons, G. M., Harris, J., Clfford, S. 2004. A review of gas sensors employed in electronic nose applications. Sensor Review. 24(2): 181-198.    Adibzadeh, A.; Dizaji, H.Z.; Aghilinategh, N. (2020) "Feasibility of Detecting Sugarcane Varieties by Electronic Nose Technique in Sugarcane Syrup". Iranian Biosystems Engineering journal. 51(1), 1-10. (In Farsi).   Https://doi.org/10.22059/IJBSE.2019.287027.665209.    Scott, S.M., James, D., Zulfiqur, A. 2007. Data analysis for electronic nose systems. Microchimica Acta. 156(3-4):  

   Food fraud has increased dramatically in recent years. In addition to affecting product quality and causing financial losses, food fraud also has adverse effects on consumer health. And it has raised a lot of concerns about food consumption. One of the most widely used foods in the food industry are edible oils. Which is used in cooking. Solid vegetable oils, or oils such as palm oil, are high in saturated fatty acids, which can cause high blood fats, high cholesterol, and eventually clogged arteries. Cardiovascular از are the most important causes of death. The oils used in the food basket of people should have at least 2% of saturated and trans fatty acids. One of the reasons for usingPalm oil is cheaper than other sesame, corn, soybean and sunflower oils, and due to higher prices of other oils than palm oil, the share of imports of this oil compared to other oils has increased in the last two years. In cooking, a variety of oils are used, each taken from a separate source From grains such as corn to fruits such as olives, nuts such as walnuts, almonds and hazelnuts, and seeds such as canola, safflower and sunflower. It is difficult to find a way to easily determine the quality of edible oils. Therefore, in recent years, olfactory, visual, taste and computer methods have been used more in the food industry. Electric nose is a new method that is considered in agriculture and food industry today In this study, a system has been used to detect and estimate the amount of palm in edible oils. The optoelectronic system consisted of ten metal oxide semiconductor sensors. During the test, the voltage response of the sensors at a certain schedule to inject the head space into the sensor housing and then clean the housing in the next step was done automatically and collected by the data system. Types of edible oils were prepared by mixing with palm oil in different proportions. The properties extracted from the signals obtained from the electrical nose were processed by principal component analysis and artificial neural network methods. Based on the results, the olfactory machine is able to detect palm oil