Gholami Rashid

  Abstract In order to investigate the effect of nitrogen and sulfur levels on the growth characteristics and quantitative and qualitative yield of nigella, an experiment was conducted as split plot based on randomized complete blocks design with three replications during 2021-22 cropping year at Campus of Agriculture and Natural Resource, Razi University, Kermanshah, Iran. The factors include the application of nitrogen at three levels (one-third, two-thirds and equivalent to the recommended amount from the source of urea fertilizer) as the main-factor and the application of sulfur at four levels (0, 40, 80 and 120 kg/ha from the source of Ammonium sulfate) were as sub-factor. The results of analysis of variance showed that the effect of nitrogen on harvest index, number of capsules per plant, 1000 grain weight, number of lateral branches, stem diameter, number of leaves per plant, leaf area per plant, number of days from seedling emergence to flowering, grain filling duration, grain filling rate, grain protein, grain ash, and leaf nitrogen were significant at the 1% probability level, and the biological yield and plant height were significant at 5% level. The effect of sulfur fertilizer on harvest index, 1000 grain weight, grain filling rate and grain ash was significant at the 1% probability level, and on the number of days from seedling emergence to flowering, grain filling duration and leaf nitrogen at 5% level. The nitrogen × sulfur interaction effect on grain yield, number of grains per capsule, number of grains per plant, grain weight per plant, grain oil, grain fiber and stem nitrogen at the 5% probability level and on oil yield, oil harvest index and number of days from seedling emergence to physiological maturity was significant at the 1% probability level. Interaction treatment of the recommended amount of nitrogen fertilizer x 120 kg/ha sulfur fertilizer produced the highest values of biological yield (4788 kg/ha), grain yield (1941 kg/ha), oil yield (743 kg/ha), harvest index (38/9%), oil yield index (15.3%), number of capsules per plant (34.92), number of grains per capsule (78.8), number of grains per plant (2921), 1000-grain weight (2.32 g) , grain weight per plant (7.10 g), plant height (66.9 cm), number of lateral branches (12.31), stem diameter (7.31 mm), number of leaves per plant (101.4) ), leaf area per plant (186 cm2), number of days from seedling emergence to flowering (69.8 days), number of days from seedling emergence to physiological maturity (110.6 days), grain filling duration (39.1 days), grain filling rate (163 mg/day), grain protein (28.1%), grain fiber (9.05%), grain oil (38.78%), leaf nitrogen (2.80%) and stem nitrogen (15.1%). In general, the application of the recommended amount of nitrogen with 80-100 kg/ha of sulfur fertilizer can be recommended as a suitable treatment to improve the yield of nigella. Key words: Nigella, grain oil, leaf nitrogen, grain yield, harvest index.

  Coffee is a common drink made from roasted and ground coffee beans. The coffee plant is native to the subtropical regions of Africa and some islands in South and Southeast Asia. When the fruit of the coffee plant ripens, the coffee beans are harvested, processed and finally dried. Dried coffee beans are roasted to different degrees and depending on the desired aroma, different grades are considered for this product. Coffee is slightly acidic and can cause human irritation due to its high caffeine content. Coffee is one of the most valuable basic products, which is the second main commodity after oil. The detection of natural and unnatural impurities and additives in coffee is a constant concern, especially in relation to guaranteeing the quality of the product with the intentional or accidental addition of foreign substances that can harm the consumer, especially of an economic nature. Therefore, researchers are always trying to provide a suitable solution for detecting adulteration in coffee, which is of great importance considering the applicability of the method and obtaining the appropriate result for the tests, non-destructive and fast method. The purpose of this research was to use the olfactory machine system and artificial intelligence to detect fraud in Arabica coffee (Medium Dark). For this purpose, firstly, Arabica coffee beans from a reputable domestic company and samples of fake powders including roasted soybean powder, wheat flour Barley flour and Robusta coffee were prepared in the amount needed in the experiment. To carry out the experiments, Arabica coffee was mixed with adulterated powders with weight percentages of 10, 40, 30, 20 and 50%. For each sample of coffee and powders used for fraud, a 100% specific sample was considered. 10 grams of the mixture of each sample was added to 100 ml of boiling water and kept boiling for 2 minutes. Finally, it was kept at rest and away from heat for one minute until the particles settled and finally the supernatant was used to perform the smell test. After the step of sucking the smell of the sample by the olfactory device, the obtained data were analyzed by PCA, LDA and ANN methods. According to the obtained results, the ANN method provided a better classification than the LDA method.

   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.

Due to important medicinal properties, Garlic (Allium Sativum) known as a strong medicine, and cultivated in many regions of the world. The high sensitivity of this product after peeling, such as changes in color, shape, texture, and appearance, as well as losses of moisture, is problematic. The shelf life of garlic at ambient, refrigerator temperature (4 °C) and freezer (-18 °C) is 21 and 35 days, respectively. There are various methods to prolong the shelf life of food and agricultural products during the storage time, Which the use of Nano packaging films, modified atmosphere packaging and the use of edible coatings can be mentioned. In this research 2 types of packaging films (common and Nano film), 2 types of atmosphere (ambient and MAP) were used. Modified atmosphere packaging (MAP) was included 5 % CO2, 1 % O2 and 94 % N2. The harvested Garlic was peeled manually with high precision. Then stored at 3 temperatures (25, 4 and -18 °C) for 21 days and 2 temperatures (4 and -18 °C) for 35 days.   hysiological properties were evaluated by Spectroscopy method. The POD, SOD, Catalase and protein content were measured weekly. The statistical analysis was investigated in the form of a completely randomized design with a factorial test. The results showed the general increasing in POD and Protein content at 4 C and decreasing trend at 25 C. increasing trend of SOD at 4 C and decreasing at 25 C, increasing trend of catalase at -18 C and decreasing at 4 C were observed. The effect of storage time (during 21 and 35 days) was significant (at 1 %) on all parameters except POD. The effect of temperature (during 21-day period) was significant on Catalase (at 1% level) and SOD (at 5 % level), and was insignificant on POD. The results showed that temperature was insignificant on all parameters during 35-day period. The effect of packaging film was significant on protein content (at 1 % level) and POD (at 5% level) during 21-day period and was insignificant on SOD and Catalase (during 21-day period), Also was insignificant on all parameter except SOD during 35-day period. Finally, the result showed packaging atmosphere had not significant effect on properties.   

In order to maintain the quality of fruits and increase their shelf life, extensive research has been done on packaging methods, especially the use of nanomaterials in packaging. Due to the high medicinal and nutritional properties of garlic and also the sensitivity of its storage period after peeling, the packaging of this product is of great importance. In this study, garlic was packaged in two normal and nano films at temperatures of 25, 4   and -18   ° C and three modes of normal atmosphere, vacuum and modified atmosphere. Measured properties include mechanical properties (Fmax, Emod and deformation percentage), chemical properties (PH and TSS), colorimetric properties (L *, color change and browning index) as well as the amount of gas (O2 and CO2) inside It was packages. Data analysis was performed in two sections of 14 days including all three temperatures and 35 days including refrigerator temperature and freezer temperature. Data were analyzed by statistical methods and artificial neural network (ANN). The trend of changes during the storage period in mechanical properties (except deformation), the amount of CO2, TSS and L * decreased and in pH, the percentage of deformation, color change and browning index were reported as increasing. The results of statistical analysis showed that in the 14-day period, temperature changes had a significant effect on the measured parameters and in the 35-day period, temperature and the interaction of temperature and atmosphere had a significant effect on all parameters. The least changes in the measured properties occurred mainly in the nano film. In neural network (ANN) analysis, the output of the best model for the effect of treatments on properties, validation performance diagram, data regression coefficient (experimental, training and general) as well as data regression line fitting was measured.   

The average annual rainfall in Iran is less than one third of the average annual rainfall in the world. Therefore, in the coming years, it will face serious and risky problems in the field of water resources shortage. That is why the optimal use of these limited water resources is vital and important. One of the complexities in this field is the contradiction of goals in the issues of water resources Exploitation. In this research, for the optimal operation of Dez and Balaroud dams, the coupled simulator-optimizer method was used using the connection of WEAP simulator model and MOICA multi-objective optimizer algorithm. Also in this research, surface water resources in Dez river, from Dez regulatory dam to the end of the study area and near Bandaqir site were investigated quantitatively and qualitatively. exploratory algorithms have been considered by water resources planners due to their ability to solve complex and nonlinear problems. Data and information for two scenarios in a period of 30 years (1397-1367) were defined in the simulator model. In the first scenario, referred to as the reference scenario, without performing the process of optimizing the environmental flow downstream of the study area and near the site of Bandaqir, it was equated with the environmental flow by the Montana method. In the second scenario, called the optimal scenario, the simulator and optimizer models were connected with the aim of optimizing the amount of environmental requirements at the bitumen dam site. In this study, three goals were considered, The first goal is to maximize the total percentage of needs met throughout the system, The second goal is to minimize the amount of violation of the allowable values of quality parameters in the river route And the third goal is to minimize the penalties for violating the authorized capacity of the reservoirs. In the MOICA model with a population of 24 and 1000 replications, the optimal results were plotted on the Parato graph. The final results for each scenario were obtained and compared. The results obtained from the optimal scenario showed, That the supply of demand has increased And qualitative parameters in the river route have found a more favorable situation, Also, the status of reservoir volume changes has improved compared to the reference scenario. Therefore, applying the optimal scenario causes, That the condition of the tanks does not fail in the dry and watery months And do not cause much damage to the system. According to river water quality standards, The worst BOD pollutants are in the Haft Tappeh factory area And EC has been in the place of   Bandaqir and sugarcane Dehkhoda. The final results show The simulated-optimized coupled model has not only sought to increase the percentage of supply in the system It has also paid attention to the standard level of quality parameters in the river route and the status of reservoir reserves. Based on the reference scenario and the changes seen in the volume of the tanks, the volume of the tank has reached the minimum level of operation many times during the 30-year simulation period. However, during the optimization process, none of the tanks have reached the minimum level of operation. Using the simulated-optimized coupled model and using the WEAP model and MOICA  algorithm can be a suitable way to plan and manage water resources in the study area and taking into account all the demands in the area. In fact, in addition to providing acceptable needs, it also examines the trend of quality and pollution in rivers.