Abstract Rapid population growth and the increasing needs of society on the one hand, intensive production of agricultural products in arid and semi-arid regions, and the lack of use of fertilizers containing potassium (K) on the other hand have caused the depletion and reduction of the availability and varying rates of potassium release in Iranian soils. Also, the excessive use of chemical fertilizers and improper management in the agricultural sector have faced the country's soils with a shortage of organic matter. In a study conducted during 1402-1403, the effects of various organic fertilizers on potassium forms and biological activities in soil were investigated. Initially, two different soil samples were collected from a depth of 0-30 cm, considering mineralogical differences. Six types of organic fertilizers—cow manure, chicken manure, sheep manure, compost, vermicompost, and mealworm frass manure—were added to soil samples at a concentration of 1.5%. These samples were then incubated for 60 days under controlled conditions, with a temperature of 25°C and maintained at field capacity moisture. At the end of the period, measurements were taken for potassium forms, basal respiration (BR), substrate-indued respiration (SIR), microbial biomass carbon (MBC), and metabolic quotient (qCO2). The results indicated that incorporating various organic fertilizers significantly influenced potassium forms and biological activities in both soils at a 5% probability level. In Soil 1, the highest levels of soluble potassium were found in the chicken treatment (173.8 mg kg?¹) and the frass treatment (167 mg kg?¹). The frass treatment also had the highest exchangeable potassium (542 mg kg?¹) and non-exchangeable potassium (1130.60 mg kg?¹), while the cow treatment showed the highest structural potassium (6580.06 mg kg?¹). In soil 2, the highest level of soluble potassium was found in the chicken manure treatment, measuring 303.5 mg kg?¹, followed closely by the frass treatment at 296.66 mg kg?¹. The frass treatment also exhibited the highest exchangeable potassium at 1343.66 mg kg?¹. In terms of non-exchangeable potassium, the chicken manure treatment had the highest value at 2326.66 mg kg?¹, while the frass treatment showcased the highest levels of structural potassium, measuring 7502 mg kg?¹.

امروزه به دليل رشد سريع جمعيت و توسعه شهرها، كمبود امكانات براي دفع زباله، و همچنين اثرات زيست‌محيطي و بيماري‌هاي ايجادشده درنتيجه‌ي روش‌هاي نامناسب دفع زباله، اهميت مطالعه و بررسي وضعيت جمع‌آوري، حمل‌ونقل،‌ دفع زباله و خصوصيات كمي و كيفي واثرات زيست‌محيطي زباله‌هاي جامد شهري بسيار احساس مي‌شود. هدف از مطالعه حاضر بررسي اثرات زيست‌محيطي روش‌هاي دفع پسماند شهري شهر كرمانشاه با استفاده از روش ارزيابي چرخه زندگي (Life cycle assessment) مي‌باشد. بدين منظور سه روش كمپوست‌سازي، بازيافت و دفن زباله كه از روش‌هاي غالب دفع زباله جامد شهري (Municipal solid waste) هستند، در كلان‌شهر كرمانشاه مورد بررسي قرار گرفت. بدين منظور در ابتدا اطلاعات مورد نياز براي تعيين خصوصيات كمي و مقدار زباله توليدي و تعيين اجزا فيزيكي تشكيل‌دهنده زباله (كاغذ، شيشه، پلاستيك و...) از شهرداري جمع‌آوري شد؛ سپس به‌منظور تكميل اين اطلاعات و بررسي اثرات زيست‌محيطي دفع زباله، روش ارزيابي چرخه زندگي مورداستفاده قرار گرفت؛ همچنين مرز سامانه، واحد عملكردي و سناريوهاي دفع تعيين شد و سپس در مرحله بعد، سياهه انتشار براي هريك از سناريوها فهرست شد. لازم به ذكر است كه در مرحله بعدي از به‌روزترين روش ارزيابي شاخص‌ها كه نرم‌افزار ايستك (EASETECH) مي‌باشد، براي محاسبه ميزان انتشارات و اثرات زيست‌محيطي استفاده شد و در پايان، نتايج تفسير شد. در اين پژوهش با دراختيار داشتن 1000 كيلوگرم پسماند جامد از سه سناريو كمپوست‌سازي، بازيافت و دفن در نرم‌افزار استفاده گرديد. نتايج نشان داد حدود حدود 50 درصد از آسيب‌هاي وارد بر سلامت انسان و محيط‌زيست ناشي از دفع پس از كمپوست مي‌باشد، زيرا راندمان آن حدود 40 درصد است همچنين راندمان دفع پس از مرحله بازيافت تنها 30 درصد است كه نشان از كم بودن مواد قابل بازيافت دارد. همچنين نتايج نشان داد حدود 76/94 كيلوگرم پسماند به صورت پلاستيك، كاغذ و منسوجات بازيافت شده‌اند كه منجربه كاهش 8/68 درصد هزينه‌ها شده است و پس از آن فرآيند MRF با 6/20 و فرآيند كمپوست با 12 درصد قرار دارند. طبق نتايج بدست‌آمده اين سه سناريو دوستدار محيط‌زيست نبوده و در پايان پژوهش پبشنهاداتي جهت بهبود مديريت پسماند در شهر كرمانشاه ارائه گرديد.

 Underground water is one of the important sources of water supply in the world and in Iran. Due to the increase in population and the development of human activities, the quality of underground water is decreasing. This can cause problems for human health, environment and agriculture. Iran is located in an arid and semi-arid region with an average annual rainfall of less than a third of the global amount. The spatial and temporal distribution of regional rainfall is also not uniform, estimates indicate It is that by 2025, Iran will become one of the salt marshes that will face the crisis of water resources shortage, which shows the necessity of managing water resources and considering measures to reduce water consumption. Absence of water resources has been observed in the regions of the country. Underground water resources provide more than half of Iran's annual water needs. It is estimated that 50% of drinking water in the world and about 63% of drinking water in Iran are provided through underground water sources. The increase in agricultural activities and the development of urbanization in dry areas have faced a big challenge for sustainable development, and it has faced a shortage of surface water resources. and the amount of water demand has increased significantly, which is why these sources have been exposed to a high risk of pollution and have faced one of the main challenges for drinking water suppliers. Groundwater is the main source of water in arid and semi-arid regions. The importance of these sources should not be underestimated. In addition to supplying the water needed by a certain region for drinking and irrigation, it is also important for other surrounding regions. That's why its quality is also important. It has been seriously considered In this research, taking into account the important qualitative factors in the study area of Bijar plain of Kurdistan province during the years 1392 to 1401, it was conducted in more than ten wells of Bijar plain area and the results of the collected data are the average of the wells. Hasan Abad 1 and 2, Takht Bijar, Halvai 1 and 2, Qamishlo 1, 2 and 3, and Yasukand, Salavat Abad and Tashe Abad 1 and 2 from the samples taken, which include the physicochemical parameters of the water, such as the pH level, water temperature, color, and nitrate turbidity. and nitrite and ammonia, iron and magnesium, carbon dioxide, COD, and dissolved oxygen are included

در ميان انرژي­هاي تجديدپذير، انرژي بادي به­خاطر عدم آلايندگي محيط­زيست و شرايط اقتصادي بهتر، امروزه بيشتر مورد توجه واقع ‌شده است. هدف از مطالعه حاضر، مدل­سازي يك سيستم بادي در كارخانه توليد روغن زيتون واقع در استان گيلان، به‌منظور تأمين انرژي از ديدگاه ارزيابي چرخه زندگي(Life cycle assessment)   مي‌باشد. در اين مطالعه با توجه به مقدار بالاي كشت زيتون و توليد روغن آن در منطقه، براي تعيين انرژي مصرفي در فرآيند توليد روغن زيتون؛ ابتدا اطلاعات لازم شامل مراحل توليد و تمامي نهاده­ها و انرژي­هاي مختلف بكار رفته در توليد روغن زيتون از كارخانه مورد مطالعه جمع­آوري گرديد و مقادير انرژي ورودي شاخص­هاي انرژي مصرفي محاسبه شد. سپس با توجه به سوخت و الكتريسيته مورد نياز براي توليد روغن زيتون در سامانه مرسوم، سامانه بادي مبتني بر نيروگاه منجيل مدل­سازي شد. در گام بعد با استفاده از روش ارزيابي چرخه زندگي ReCiPe2016، پس از تعيين مرز سامانه و واحد عملكردي براي كارخانه مذكور و تحليل سياهه توسط داده‌هاي جمع‌آوري‌شده و نيز اندازه­گيري پايگاه‌هاي داده به‌طور جامع براي هر دو سناريو پرداخته شد. نتايج برآن بود كل انرژي مصرفي27/4437 مگاژول است كه الكتريسيته با سهم 44/32 درصد انرژي برترين در ميان نهاده­ها براي توليد محصول مي­باشد. نتايج شاخص‌هاي انرژي نيز بيانگر آن بود كه بهره­وري انرژي 23/0 كيلوگرم بر مگاژول و انرژي ويژه 44/4 مگاژول بر كيلوگرم مي‌باشد. نتايج مدل­سازي سامانه‌ي بادي نيز نشان داد به‌طور متوسط تعداد 6-10×01/2 براي سامانه بادي جهت توليد برق با توجه به اقليم و شرايط آب و هوايي مورد نياز براي 1 تن روغن زيتون حاصل گرديد. ارزيابي چرخه زندگي محصول نشان داد در تمامي رده­هاي آسيب، سامانه بادي كمترين مقدار انتشارات را به خود اختصاص داده است. همچنين در دو سامانه مرسوم و بادي، پلي اتيلن ترفتالات بالاترين سهم را در انتشارات رده­هاي آسيب در توليد محصول دارا مي‌باشد. همچنين نتايج نشان داد در مجموع مقادير كل انتشارات سامانه مرسوم، بيشترين ميزان انتشار را به خود اختصاص داده است.     

Pepper (Capsicum annum) from the Solanaceae family is one of the most important vegetable summer crops that is cultivated in different parts of the world. Pepper plants are attacked by many pests such as insects, bacteria, viruses and fungi. Many fungi such as Rhizoctonia solani, Fusarium solani, Verticellum, Alternaria, etc. cause disease in pepper. Common fungal diseases include seed rot, seedling damping off, root rot, stem base rot, etc. To prevent the damage caused by fungal diseases, farmers mainly rely on the use of chemical fungicides, which are efficient and fast-acting, but this is at the expense of human health and the environment, prompting experts to look for successful alternatives and their way. find for biological control in which they use a biological agent against a pathogenic fungus. The purpose of this study was to investigate the fungi that attack the pepper plant roots and to investigate the effect of T. longibrachiatum as a biological control method and fungicides as a chemical method on the fungi that cause pepper root rot. The antagonism test of T. longibrachiatum against pathogenic fungi was investigated in laboratory conditions. This step included placing the disc of pathogenic fungi against the isolated disc of T. longibrachiatum on PDA medium. After one week of incubation, the antagonism ability was measured. In the greenhouse, the effect of treatments including the control alone (without pathogenic fungi and T. longibrachiatum), Fusarium, Rhizoctonia, T. longibrachiatum, Beltanol fungicide and the treatment of pathogenic fungi together with T. longibrachiatum. The effect of the treatments on two soil groups, including sterilized and non-sterilized soils, was done in three repetitions, which formed a total of 12 samples of the statistical population of this study. The effects of the treatments on the characteristics of root and stem length, wet and dry weight of root and stem were measured in greenhouse conditions. The data obtained from the measurements were analyzed using the LSD test comparison between groups (sterilized and non-sterilized soil) at the 5% level. Based on the results of internal transcribed space (ITS) sequencing and PCR, the species of Fusarium and Rhizoctonia fungi included F. solani and R. solani, respectively. T. longibrachiatum had a high antagonistic ability with F. solani and R. solani. The treatment of T. longibrachiatum fungus and Beltanol fungicide reduced the pathogenic effect of F. solani and R. solani, so the measured growth indices increased in the presence of these treatments. respectively, the highest and lowest characteristics of the measured sizes were observed in the treatment of T. longibrachiatum and pathogenic fungi F. solani and R. solani. By adding T. longibrachiatum to samples infected with R. solani along with F. solani in non-sterile soils, the dry weight of the stem increased by 744.17%. Based on the results of the laboratory and greenhouse, T. longibrachiatum as a strong antagonist was able to prevent the growth of F. solani and R. solani, therefore T. longibrachiatum as a strong biological controller plays an important role in controlling various diseases caused by F. solani and R. solani has root rot of pepper. The effect of T. longibrachiatum fungus was higher compared to Beltanol fungicide in inhibiting the pathogenic agent. Therefore, it is recommended to use biological control method instead of chemical control.

   Sugar beet is one of the most suitable plants for sugar production. Sugar beet leaves produce sugar by using sunlight, and these sugars return to the root and are stored there. In general, leaves play the role of a sugar factory. The percentage of beet sugar is very important for both the farmer and the sugar factory, because the price of beet is paid based on this. The purpose of this research was to estimate the amount of sucrose in the sugar beet crop using the image processing method and to determine the best time to harvest the sugar beet crop. For this purpose, data was collected from an area of 1000 square meters of a sugar beet field, one month before the recommended harvest date and one month after that, every other day. Each time, 5 whole sugar beet plants were randomly picked and all the leaves were photographed. In order to estimate the amount of sugar beet and obtain the most suitable harvest time with the image processing method, it is necessary to have a suitable modeling between the harvest index and the harvest time of the product. The most important indicator of sugar beet harvest is sugar grade. For this purpose, using the decision tree method, we tried to select the most effective inputs from the features of the leaves and their images. Then a model was designed to find the maximum sugar level according to the harvest time using the RSM method. The best time to harvest sugar beet with the highest quality sugar was obtained on the 210th day after planting. In the tested area, sugar beet was harvested on the 215th day, which was almost consistent with the modeling calculations by the response surface. To design a decision, it is helpful to be able to inform the farmer of the approximate harvest time, the time elapsed from the day of planting to the harvest of each sample was deducted from the optimal harvest time that has the highest sugar content, and their difference is used as the output of the decision support model. The results of the decision tree showed that the average value of B corresponding to the smallest leaf area, the smallest leaf area value, and the largest leaf area value are suitable inputs for formulating a decision. For the design and modeling of decision support, three methods of response level modeling, Anfis and artificial neural networks were used. The value of R2 in the response surface method, Anfis and neural networks were 0.83, 0.832 and 0.80 respectively, and the Anfis method was selected as the best model with the highest accuracy.

  Among renewable energy sources, solar energy is the

  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):  

  AbstractThe production of organic and quality food is one of the most important human challenges today. Tomato paste has been considered as a popular condiment in Iranian food due to its antioxidants, lycopene, vitamins and minerals. Many tomato paste factories maintain the quality of this product through thermal processes, pasteurization and chemical preservatives. Previous methods can affect the effective management and production of tomato paste. Cold plasma food processing is used to achieve the desired level of quality of a product, especially heat-sensitive food. This emerging technology and non-thermal, safe, healthy, environmentally friendly, cost-effective and low impact It is based on the internal structure of the product. Due to recent advances in plasma technology, this study will be conducted to investigate the effect of using cold plasma treatment on the quality parameters of tomato paste. The research method is that at first, samples of tomato paste prepared from a specific variety of tomatoes were prepared from the tomato paste factory in both traditional (without preservatives) and industrial (with preservatives) and in the laboratory directly below. Laminar hoods were exposed to plasma under relatively uniformly cold plasma using dielectric barrier (DBD) discharge at 3 repetitions and 2 time levels. Samples were subjected to atmospheric pressure and 3 voltage levels (maximum 12 kV) and with Constant frequency of about 6-7 kHz was irradiated, then the effect of cold plasma after 10 days on pH, dye and brix parameters was evaluated and after 5 days of incubation, Aspergillus niger mold was evaluated and the mean treatment was compared with Duncan's test was performed by statistical analysis using   16 software.The results showed that the application of atmospheric cold plasma on industrial tomato paste had no significant effect on the pH of the paste and increased the brix of tomato paste and decreased the number of colonies. Aspergillus niger molds and thus improved the quality of industrial tomato paste over the weeks.  Keywords: Tomato paste, Quality, Atmospheric cold plasma, Food processing

  تجزيه گرمايي زيست توده در محيطبدون اكسيژن يا با اكسيژن اندك را گرماكافت مي‌نامند كه محصول اين فرآيند دي اكسيدكربن، گازهاي سوختي، بخار قيري و جزء جامدي به نام بيوچار است. فرآيند گرماكافتراهي براي تبديل زيست توده به مواد با ارزشتر نظير بيوچار است. بيوچار ماده ايجامد و داراي محتواي كربن بالاست كه رايج ترين مورد استفاده آن در كشاورزي بهعنوان اصلاح كننده خاك است. محققان در سال هاي گذشته تاثير استفاده از بيوچار برخصوصيات فيزيكي وشيميايي خاك را مورد مطالعه قرار داده اند و مشخص شده است كهافزودن بيوچار به خاك كيفيت خاك را بهبود مي‌بخشد. خصوصيات فيزيكي و شيميايي بيوچارتحت تأثير عوامل مختلفي از جمله نوع مواد اوليه، شرايط واحد گرماكافت، سرعت گرمادهي،مدت زمان گرماكافت وللفعوامل متعدد ديگري قرار مي‌گيرد . دامنه گسترده فرآيندگرماكافت منجر به توليد بيوچارهايي   كه ازنظر خواص شيميايي و فيزيكي مختلفي نظير تركيب عنصري و خاكستر، وزن مخصوص، تخلخل،توزيع اندازه منافذ، سطح ويژه، pH، جذب و دفع آب و يون ها و بسياري خواص ديگر متفاوت هستند مي‌شود. هدفاز اين مطالعه، بررسي اثر تغيير دبي هوا و دماي محفظه در گرماكافت اكسايشي بسترثابت بر روي عملكرد بيوچار، محتواي خاكستر، وزن مخصوص و pH بود. بدين منظور يك دستگاه توليد بيوچار اكسايشي بسترثابت با قابليت تغيير در دماي محفظه و دبي هواي خروجي طراحي و ساخته شد.آزمايش‌هادر چهار دبي هواي 20، 25، 30 و 35 ليتر در دقيقه ونيز چهار دماي 350، 400، 450 و500 درجه سانتي‌گراد براي كاه و كلش گندم انجام شد. نتايج نشان داد كه افزايش دبيهواي   خروجي   از محفظه و افزايش دماي محفظه، سبب افزايش ميزانخاكستر وpH شد. درحالي كه تغيير اين پارامترها سبب كاهش وزن مخصوص ظاهري و عملكرد   بيوچارتوليدي شدند.     

   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   

  This study investigates the relationship between the structure of Iranian oak forests and its effect on soil properties around the crown and also the diversity of soil macrofauna affected by the structure of Iranian oak forests in Kermanshah province (Ravansar area). For this purpose, 4 transects were considered in the study area at intervals of 50 m and then due to different structures of branching trees, 8 treatments with three replications were carried out from under their canopy. A total of 96 sections of 50 × 50 cm profiles with 15 cm depth were cut and macrofauna were collected manually. Soil moisture and organic matter content increased significantly in the soil under the canopy of these shrubs due to shading and accumulation of nutrients, so-called "fertile islands". Statistical comparison results showed that the abundance and diversity of soil macrofauna and also Some soil properties within the group and outside the group had a significant difference at the 95% probability level. Increase in macrofauna abundance and diversity within the group showed a significant correlation with litter depth and crown area, due to increased organic matter, nutrient concentration, and organisms' access to food resources in the litter and also outside the group. It was. According to the results of the present study, the effect of the group as a habitat micro-habitat with suitable living conditions and presence of soil organisms can be pointed out. Soil passes through or into surface debris and their populations are highly dependent on ecosystem management practices. In many ecosystems of semiarid regions, shrubs play a key and complex role in providing soil moisture and nutrients.

   مقدمه: انرژي به‌عنوان يكي از مهم­ترين و ضروري ترين عوامل توليد ، داراي اثرات قابل‌توجهي است. با توجه به اين‌كه منابع   سوخت هاي فسيلي رو به اتمام است، پژوهشگران به دنبال جايگزين كردن سوخت بيوديزل كه يك سوخت زيستي قابل‌تجديد و داراي خواصي نزديك به گازوئيل است، مي­باشند. در آزمايش هاي مربوط به توليد بيوديزل و در كنترل كيفيت اين محصول از دستگاه GC استفاده مي­گردد و درصد بيوديزل توليدي را اندازه­گيري مي نمايند. استفاده از دستگاه GC ، به دليل هزينه بسيار بالاي آن در همه جا امكان پذير نيست لذا در اين تحقيق تلاش مي­شود درصد بيوديزل توليدي را با استفاده از بيني الكتريكي و تكنيك­هاي هوش مصنوعي تخمين زد. روغن انتخابي در اين تحقيق روغن پسماند به همراه روغن گياه رزماري مي باشد. اهداف: 1. توليد بيوديزل از روغن پسماند خوراكي و روغن گياه رزماري بوسيله ي واكنش ترانس استريفيكاسيون    2. تخمين درصد بيوديزل توليد شده با استفاده از بيني الكتريكي و تكنيك هاي هوش مصنوعي روش تحقيق: در ابتدا از روغن پسماند خوراكي و روغن گياه رزماري با استفاده از واكنش ترانس استريفيكاسيون و متانول ، بيوديزل توليد مي­شود. روغن پسماند خوراكي از آشپزخانه ها جمع آوري شده و پس از فيلتر شدن ، ناخالصي­هاي آن گرفته مي­شود و روغن گياه رزماري به آن افزوده مي شود . براي توليد بيوديزل پارامترهايي ازجمله مدت زمان همزني، مقدار متانول مصرفي ، سرعت همزني ، مدت زمان سيركوله و مقدار روغن رزماري مصرف شده پس از توليد بيوديزل، متغير و پارامترهايي از جمله   نوع كاتاليزور و نوع الكل ثابت در نظر گرفته   مي­شوند. الكل مورد استفاده در آزمايش حاضر متانول و كاتاليزگر KOH مي­باشد.    جدول 1 ماتريس آزمايش‌هاي توليد بيوديزل سطح 3 سطح2 سطح1 عامل 8:1 6:1 4:1 مقدار متانول مصرفي (مولي) 20 10 2 مدت زمان همزني 1200 900 600 سرعت همزني(دور بر دقيقه ) 9 6 3 مدت زمان سير كوله   (دقيقه ) 5/2 25/1 5/0 مقدار روغن رزماري مصرف شده (گرم)    براي پرهيز از اشتباه و به حداقل رساندن خطا در اندازه‌گيري‌ها مبناي محاسبات جرم در نظر گرفته مي­شود و با استفاده از ترازوي ديجيتال با دقت 01/0 گرم، مواد وزن خواهند شد. براي توليد بيوديزل مقدار 500 گرم از روغن را به ورودي   رآكتور مي­ريزيم و پس از تهيه­ي محلول پتاسيم متواكسيد با توجه به نسبت مولي الكل به روغن   ، محلول به روغن درون رآكتور اضافه مي­شود و آزمايش با شرايط نشان داده شده در جدول 1 توسط رآكتور انجام خواهند شد . پس از اتمام مراحل توليد بيوديزل ، روغن رزماري با نسبت­هاي مختلف به بيوديزل اضافه و از هر كدام از آزمايش ها نمونه گرفته خواهد شد .

  Understanding the phenomenon and its response to various issues in today's engineering affairs, such as air and space, fluid mechanics, etc., is of considerable importance. Knowing and studying the flow characteristics in the channels is one of the important issues in designing various types of structures associated with them as well as planning schemes. The exact determination of the shear stresses of the bed and wall from the theoretical point of view, as well as from the point of view of applied issues such as its role in erosion studies and sedimentation and design of protective coatings, is of particular importance. Compound channels include a deep main channel and one or two flood plains around it, which are relatively smaller than the main channel. Hydraulic studies on these channels are much more complicated than conventional channels because of the interactions between the flood plains and the main canal. In this study, the performance of the Ansys Fluent three-dimensional numerical model in simulating various hydraulic parameters for a rectangular compound channel with smooth and rough beds has been investigated. The model of turbulence and mesh network was simulated with the help of the results of the experimental model and the numerical model of health assessment and various scenarios using the numerical model. Comparison of shear stress values ??shows that with decreasing depth in flood plains, the rate and percentage of shear stress in flood plains increases and decreases in the main channel. By reducing the depth of water in the main channel, the percentage of shear stress in the main canal increases and decreases in flood plains.   Also, increasing roughness can increase the shear stress. The results of the studies also indicate that increasing flow rate increases the flow power and At the intersection of the flood plains and the main canal, the speed is higher and there are vortices in this area. In the present study, the phenomenon of momentum transfer with the aid of transverse velocity vertexes was investigated. By comparing the ratio of different shapes, a stable compound channel was introduced based on the momentum transfer phenomenon. Other work done in this study is to investigate the depth profile of velocity, which is plotted for different simulation scenarios. In this regard, roughness of the profile of the depth profile changes the velocity and reduces the average velocity. The results of this research can play a role in designing sustainable channels, especially at the intersection of the main channel and flood plains.Key words: Three-dimensional numerical model, Ansys Fluent, compound channel, shear stress, momentum transfer, stable channel, flood plain, main channel

  Today, due to the increasing population of the earth, the need for food supplies has increased. On the other hand, due to the reduction of water resources, water management needs, especially in the agricultural sector, are felt. For this purpose, several methods have been used to reduce water consumption, one of the most modern ones being precise irrigation, namely, the field moisture map. In this research, we attempted to extract from a sorghum field to a half-hectare wetland map by multi-capture and image processing. For this purpose, initial experiments were carried out to obtain the best height and best day of the day to be photographed. The farm was then divided into small pieces. Captured from each piece by a multi-capture. From different points of the farm, the samples were taken by recording the coordinates of the spots to obtain the percentage of moisture content of the plant in those points. Finally, the images were aggregated by the Arc GIS software Then the MATLAB software performed various image processing operations on the image. These operations include: plotting, separating the field, finding the neighborhood of points, extracting different data from neighboring points, modeling effective input parameters to estimate the plant's moisture content, applying model output to segmented images, aggregation, and so on. The best model obtained by neural networks consists of four roughness inputs, the mean values of the CM channel channel monochrome channel M, the mean values of the Y single channel channel of the CMY channel, the mean values of the channel B of the RGB channel, and the output of that percentage The weight of the plant was R2 and MSE of the model was 885/0 and 0/004, respectively. In the case of classification of the plant's moisture content into five classes of very watery, loose, moderate, low water and very low water, the perturbation matrix of the model was 90.5%.

  (According to the Environmental Bureau, the rapid growth of the city and industry and the growing population growth has causedThat the amount of atmospheric pollutants has increased more and the suspended particles become the most important air pollution in metropolitan cities.Air pollution causes heart and lung disease.UHC and CO emissions are caused by incomplete combustion of fuel and air mixtures,While NOx and CO2 emissions are generated by the engine in the engine,Also, fine and tiny particles suspended from coarse particles are more dangerous.The purpose of this study was to use various ratios of bioethanol fuel with gasoline in different engine periods in the state of the EGR and to use different ratios of bioethanol fuel with gasoline and different temperatures of the intake air to the engine in different engine periods in the EGR mode with the aim Reducing the amount of pollutants and particulates in both the EGR and the EGR mode in the petrol engine pride.In this research, the Pride engine was used with the Siemens fuel system.For testing, fuel mixtures with bioethanol and conventional gasoline were used, fuel with ratios of 0, 5 and 10% bio-ethanol was used.The experiments were carried out at three levels of inlet air temperature of 12, 15 and 18 degrees Celsius and 1000, 2000 and 3000 rpm.Each experiment was repeated three times.The Airrex Five Gas Testing Machine was used to measure the contamination.Particles suspended by the IAQ 3016 particle counterpart model manufactured in the United States were measured.The effect of fuel type treatments and engine speed on exhaust and particulate exhaust gases in the EGR state and the effect of fuel type treatments, inlet air temperature and engine speed on exhaust and particulate emissions in EGR mode were investigated.Data were analyzed by    software and factorial experiment in a completely randomized design with comparisons of the meanings using Duncans multiple range test.The effect of engine speed and fuel type and the interaction between engine speed and fuel type in the EGR state on all traits were significant at 1% level.And the only interaction between the engine speed and fuel type on carbon dioxide (CO 2) has had a significant effect on the 5% level.Also, the effect of engine speed on particles of 5 microns and the effect of fuel type on particles of 3 microns is also significant at 5% level.In EGR mode, the effect of engine speed on the temperature of the exhaust air and contaminants of carbon monoxide (CO), carbon dioxide (CO2), uncured hydrocarbons (uhc), nitrogen oxides (NOx) and suspended particles at 1% have been.The effect of fuel type on air temperature was not significantBut on other traits it is significant at 1% level except for 0.3 micron particles which is significant at 5% level.Also, the effect of air temperature on all studied traits is significant at 1% level and 0.3 ?m for suspended particles at 5% level.According to the results of Duncans test, with increasing engine speed, the amount of carbon monoxide (CO) and unburned hydrocarbons (uhc) contaminated, but the amount of carbon dioxide (CO 2), nitrogen oxides (NOx) and suspended particles increased .By increasing the percentage of bioethanol, the amount of carbon monoxide (CO), carbon dioxide (CO 2), unreacted hydrocarbons (uhc) and suspended particles decreased, but the amount of nitrogen oxides (NOx) increased.For the effect of engine speed and fuel type in EGR, the amount of pollutant emissions was lower than that of the EGR, but the particle size of 0.3 micron in the EGR state was less than that of the EGR.

  AbstractNowadays, solar energy is one of the cheapest and available renewable energy sources. Among different uses of solar energy, solar collector is one of the most economical ways to use solar energy. In the present study, the outlet water temperature of the solar flat plate collector was modeled using artificial neural networks (ANN) and support vector regression (SVR) and compared with experimental data. Data was collected for 18 days. Water and Bohemite Nano- fluid (ALOOH) with a concentration of 0.2% by weight were used as operating fluid. In order to evaluation of the models, tow structures were tested for both artificial neural network and support vector regression. In the first structure the parameters were input flow, test time, environment temperature and inlet fluid temperature. While in the second structure inputs were input flow, test time, environment temperature, inlet fluid temperature, tow temperatures of absorber plate, and the glass cover temperature. Based on the results, coefficient of determination (R2) and root mean square error (RMSE) in the SVR method for pure water and the first structure, respectively were 0.978991 and 3.2508, respectively, and for the second structure, were 0.998715 and 0.1016, respectively. According to the results, R2 and RMSE for Boehmite Nano fluid and first structure were, 0.958303 and 6/68580, respectively. While these values for the second structure was equal to 0.965097 and 5.4765, respectively. Also, by influencing the type of input fluid as the input of the models, R2 and RMSE were 0.636978 and 281.8210, respectively, and for second structure were 0.939306 and 15.7420. Based on the result for modeling by artificial neural network and for pure water, R2 and RMSE for the first model were 0.99983 and 0.029084, respectively and for the second model were 0.99991 and 0.015617.0, respectively. Also, these values ??for the Bohemite Nano-fluid for the first structure were equal to 0.999 and 0.99896 and for the second structure were 0.9993 and 0.99927 respectively. With the effect of the type of operator fluid as input variable, the R2 and RMSE for the first structure ??were 0.99886 and 0.32567, respectively. Also, these values were 0.99934 and 0.32567, respectively, for the second structure.   Results indicated that the ANN model was better than SVR model for prediction of outlet temperature.   Also by increasing the input parameters, the accuracy of models was increased.Keywords: Artificial neural network, Nano fluid, Outlet fluid temperature, Solar flat plate collector, Support vector regression

AbstractEnergy as one of the most important economic and enviromental factors of production has significant effects and is consididered as a main pillars of development of contries. By considering of coming to the end of fossil fuel, the all countries in the world has an attention to biofuels among all biofuel, has been focused on biodiesel. Production and quality of this fuel is very important issue. Estimination of the trans estrification reaction efficiency is a very important issue in the biodiesel researchs. Therefore in this study evaluated the image processing method and used from response surface methodology (RSM), adaptive neuro-fuzzy inference system (ANFIS) And artificial Neural Network (ANN) to estimination reaction yield. In this study, first biodiesel was produced under different conditions (reaction time, alcohol type (ethanol and methanol), catalyst type (KOH and NaOH)and production method) and reaction yield was achived in the wide   range. Then by using the three methods: 1- Microscopic images 2- Using a special image processing box before centrifugation 3- Using a special image processing box aftre centrifugation, photos was taken from biodiesel sampel in similar conditions. Then by using the image processing provided color channel images in 5 different modes microscopic photos, special compartment photos before centrifugation, combination all methods before centrifugation, special compartment photos after centrifugation   and combination all methods of taking images. By using three modeling methods ANN, RSM and ANFIS, was estimated reaction efficiency properly. The results showed the best way, using of the special image processing compartment without centrifugation by ANFIS modeling method and this method was able to accurately evaluate the trans estrification reaction efficiency with R- squared 0.983, mean squared error 0.002226, mean absolute error 0.02927 and sum squared error 0.12466 performe the best performance in the estimation reaction efficiency. The use of ANN method was able to accurately estimate the reaction efficiency. The use of image processing and ANFIS modeling method, by reducing the cost of analysis compared to the conventional method gas chromatography (GC), estimated reaction efficiency properly.Key words: Biodiesel, Image processing, Gas chromatography (GC), ANN method, Trans esterification, RSM method, ANFIS method.  

  Aquaculture is a good source of protein for the proper combination of essential amino acids. According to the Worlds Food Organization, the annual production of aquaculture has steadily increased over the last seven decades and has risen from around 20 million tons in the early 1950 to 170 million tons in 2015 (FAO, 2016). Generally speaking, public awareness of the importance of nutrition has increased, and the production of important nutritionally proteins to meet the growing demand of the population is one of the most important issues of human societies. In order to control the quality of food in post-harvest technology in the agricultural industry, the availability of visual information from all levels is essential. And since most of the methods for measuring the quality of agricultural products are destructive, time-consuming and expensive, the visual system is considered as a non-destructive tool and is used to control the quality of agricultural products. This research was conducted to determine the algorithm for calendering using image processing. 36 rainbow trout in a weighing range between 200 and 800 grams were prepared randomly. Imaging of samples placed at environment temperature and in the refrigerator every 4 hours and the fish kept in the freezer was carried out weekly until complete degradation. In the image processing step, 527 parameters were extracted from each image of the fish, among which, according to the images and histograms, eight effective parameters were determined using the sensitivity analysis for modeling. Three algorithms ANFIS, ANN and RSM were used for grading and modeling. In the modeling the past time of hunting fishes placed at frizer,refrigerator and environment, the best of three models was ANFIS algorithm with correlation coefficients of 0.982627, 0.988024 and 0.988094, respectively. But in the modeling past time of hunting for all enviornments, the ANN algorithm with the correlation coefficient of 0.981391 was the best model. Fuzzy Inference System was used to grading trout. This decision-making system consists of three FIS proportional to the location of fish storage. Each FIS had two inputs including: past time of hunting in hours and size in pixels and one output as a grade of fish quality.Keywords: detection algorithm, image processing, salmon, duration of storage

  Honey is a natural and sweet substance, which honeybees collect mainly from nectar flowers and process and storage in hives. Adulteration, especially industrial, is made by adding natural syrup or yeast directly to acids. Artificial honey is also made by mixing one or more types of sugar with acid. In this research, the accomplishment construction of a fluid-optimized imaging kit at the Agricultural faculty, Razi University, Kermanshah and fennel honey was also bought from bee keepers in Cangavar. After confirming the origin of honey, 39 samples of adulteration honey using sucrose syrup, fructose syrup and 0.9% fructose syrup with   mixed glucose percentage i   the honey   at 2.5, 5, 7.5, 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100% .   then a natural honey sample, and an artificial honey sample were investigated and compared. In this study, three photographic methods including processing water-soluble honey images (DiW), honey imaging in a special box (black) using petri dish (PD) and microscopic imaging (M), and another adulteration detection method based on physicochemical properties (pH, TDS, EC and MC) and a combination of superior parameters of all mentioned methods was performed. The microscopic and TDS method was distinct from honey type. The (standard ?3). In combination method (C), by using the input parameters of the best model in all previous methods and performing sensitivity analysis, two parameters of (DiW) dissolution method and one parameter of microscopic imaging method (M) were selected and modeled using AFNIS, ANN, and RSM classification systems for hybridization and using the desirability function. The determination coefficient of RSM model was considered 0.9992. Among the best models in all five methods of this research, the RSM model was introduced in the combined method (C) with the least amount of statistical errors compared to other models with the most effective 0.9940 desirability function

  Nowadays for users, quality of fruits and vegetables is do important like produsers. Most of users want to pay more money for better products. In Iran usually old methods of agriculture products in >In this reaserch 200 samplese of local pomegranate from Kermanshah prepared by chance. Then after first prepration, their fisical qualeties were measured. Dufferent part of pomegranates captured by a special case. Then grains of pomegranate were separated and captured them too. PH number and suger amount of that was measured. Taste of that in 5 level: very sweet, sweet, subacid, sour and very soure, tasted by panel members. In producing picture stage with due attention to explains 482 parameters of every pomegranate obtained. In 14 parameter with help of sensitivity analysis for every indicator, determined some parameter for modulation, for grading and modulation 3 parameter (ANFIS, ANN and RSM) used. For classificating pomegranate in 3 level number 1, 2 and 3, ANFIS model with 98. 5% correlate coefficient was best model.   In modulation for estimating suger amount of pomegranate water ANN model with 0.988 correlate coefficient was best model. . In modulation for estimating PH number of pomegranate water ANFIS model with 0.991 correlate coefficient was best model. .   In modulation for estimating taste of pomegranate ANN model with 0.955 correlate coefficient was best model. . In modulation for grading of the grain pomegranate ANN model with 0.98% correlate coefficient was best model. In modulation for beforehand pomegranate weight ANFIS model with 0.998 correlate coefficient was best model. . In modulation for beforehand pomegranate volume ANN model with 0.995 correlate coefficient was best model.