sayed javad sajadi

Mass and diverse production is the most obvious face of today's world. Despite Production has important role in development, it causes major climate changes and environmental pollution. Environmental pollution is one of the most important crises in today's society, an issue that threatens the fate of mankind and harms the human right to a healthy environment, which is a fundamental right. Pollution caused by production is mostly due to lack of standards, poor quality of products and lack of control. Pollution caused by production can never be reduced to zero; but with basic action, pollution can be minimized. The basic solutions are that in the field of production, one should pay attention to the goals of deterrence, apply strict production standards and update the standards. Products should be made from renewable materials based on environmental standards and in line with sustainable development. The "factor of pollution" of the environment, due to creating the source of pollution and violating the rights of others, has civil liability and must compensate for the resulting losses; because the right to access healthy environment is one of the fundamental human rights, and polluting production damages this right. In Iran's legal system, about the civil liability, the "fault theory" is the criterion. This theory is not effective for environmental pollution. Also According to this theory, Demand for environmental damage is difficult. For this reason "strict liability" and Conventional citation can be effective to reduce the environmental pollution of product.

Rapeseed with the scientific name (Brassica napus L.) are one of the most important oilseed crops in the world. Considering the country's increasing need to import oil and the importance of rapeseed among oilseeds plants, increasing the yield and percentage of oil is very important. Therefore, identification the traits that increase seed yield, play an important role in the success of breeding programs. Yield is a complex trait that is affected by many factors. direct selection of a variety for yield is not often very effective, so investigating the relationships between grain yield and other traits for indirect selection may be effective. In such a situation, correlations may not clarify the relationships well, therefore, multivariate statistical methods and path analysis can help in understanding the nature of the relationship between traits for direct or indirect selection and improve the efficiency of selection in breeding programs plants become useful.

In this study, eight genotypes of spring rapeseed (SPN-202, SPN-204, SPN-206, SPN-207, SPN-217, SPN-225, SPN-227, SPN-182) along with 56 rapeseed hybrids (F1) were planted in a randomized complete block design with three replications in 2019-2020 crop years in the research farm of Gorgan Agricultural Research Station. During the experiment, phenological, morphological traits, yield and yield components were recorded. The normality of the data was evaluated based on the Kolmogorov-Smirnov method. In order to understand the relationships between traits and to identify the traits affecting on grain yield, at first, correlation coefficients were estimated, then stepwise regression were done. Then, path analysis based on correlation coefficients was used to determine the direct and indirect effects of traits. Finally, all traits were grouped based on principal component analysis.

The results of analysis of variance indicate a significant difference for all studied traits at the probability level of one percent. The coefficient of variation (C.V) for the traits varied from 1.37 (physiological maturity) to 10.31 (number of sub-branches), which indicates that there is sufficient accuracy in conducting the research. The results of correlation evaluation showed that number of pod per lateral branches (0.864), number pods per Plant (0.865), number of lateral branches (0.466), physiological maturing (0.329) and number of grain per pod (0.358) had a positive and significant correlation with grain yield (P<0.01). Stepwise regression analysis showed that the traits of number of pods per plant, number of grain per pod and 1000-grain weight has a decisive role on grain yield. Based on the results of path analysis, number of pods per plant had the most direct effect (0.881) and number of grain per pod had the most indirect effect (0.053) through the number of pods per plant on grain yield. In order the results of principal component analysis, four components were able to explain 75.91% of the changes in the measured data of 64 rapeseed varieties.

Results of the path analysis showed that number of pods per plant, number of grain per pod and 1000-grain weight had a direct positive effect on grain yield. Also, the stepwise regression analysis showed that the stated traits have the highest regression coefficients. Therefore, selection for these traits can be very effective in achieving high performance

Olive (Olea europaea L.) is a historic and significant Mediterranean tree that has been widely used for its curative properties and oily nature. Images of 150 randomly selected fruits were captured and processed in three replications to investigate the genetic diversity among 98 olive genotypes. The difference in all traits between genotypes was significant (P˂0.01), indicating a high level of genetic diversity among the olive genotypes. D1 outperformed other genotypes in terms of fruit area, major axis length, convex area, filled area, and equiv. diameter. The major axis length of the fruit exhibited a significant positive correlation with the perimeter, equivalent diameter, major axis length, and area of the stone (P≤0.01). Also, there was a significant, positive correlation between the minor axis lengths of the fruit and stone. The explained percentage of the traits’ associated markers indicated that the fruits’ major axis length had the highest cumulative coefficient (39%) with five bands. The IJS9-A and ScoT21-B genes regulated the most significant number of traits. The former regulated seven characteristics, i.e. fruit area, major axis length, minor axis length, convex area, filled area, equivalent diameter, and perimeter. In comparison, the latter regulated six characteristics, i.e. fruit area, major axis length, convex area, filled area, and the equivalent diameter of the fruit. Cluster analysis was used for categorizing genotypes into two groups. The findings of this study can be applied in hybridization and production programs for developing genotypes with more suitable fruits.

Bilateral diallel crosses of eight rapeseed genotypes were used to graphically analyze and estimate of genetic parameters for agronomic and physiological characteristics. F1 along with their parents (64 genetypes) were planted in a randomized complete block design with three replications at Gorgan Agriculture Research Station, in 2019-2020. The results of analysis of variance showed that a and b components were significant for all traits. The results of the Jinks-Hayman test indicated that hypothesis of the genetic analysis were satisfied for pod length, number of pod per lateral branches, number of pods per plant and 1000-grain weight traits. Analysis revealed significant values for D and H1 estimation for all traits, which indicated the existence of both additive and non-additive effects on genetic control of these traits. While the proportion of non-additive variance was higher than the additive effects for all traits, which was in agreement with high mean levels of the degree of dominance. The positive and significant sign of F confirmed that there are much more dominant alleles than recessive alleles in parents, regardless of whether they have a negative or positive effect. Based on Hayman graphical analysis, 1000-grain weight was influenced by the dominance of genes. Narrow-sense inheritance levels were low for all traits, which could indicate a greater impact of environmental and non-additive effects on their genetic control. The results showed that selection-based methods were not very effective in canola yield improving and production of hybrids and exploiting the effects of gene dominance is necessary.

Mathematical modeling is a powerful tool for prediction of Ion Sensitive Field Effect Trnsistor (ISFET) response and optimization of its functional parameters. In this study the optimal values of drain current, drain voltage and initial concentrations of substrate and enzyme parameters were determined to achieve maximum of ISFET response for detection of Aflatoxin B1 (AFB1). Optimization was performed by using Genetic Algorithm (GA) and based on numerical solution of ISFET governing differential equations by means of Finite Element Method (FEM) and COMSOL Multiphysics software. The objective function of GA was defined through substituting simulated model by Artificial Neural Network (ANN) metamodel. The results showed that ISFET simulated FEM model has a MAPE equal to 1.06 % in prediction of ISFET response compared with experimental results. With FEM model, 1296 virtual experiments were simulated to achieve necessary data base for train ANN metamodel. By evaluation of different ANN structures, trained ANN with 4-45-1 structure was selected which has MAPE equal to 0.04 %, 0.07% and 0.05% at train, validation and test phase respectively. ISFET optimization results states that by using of GA determined optimal values of drain current, drain voltage and initial concentrations of substrate and enzyme parameters, extremum response of ISFET equal to 44.44 % was achieved.

Rice is a major source of food for more than half of the world's population. Rice is one of the smallest genomes in grain size, and it has been used as an ideal crop for evolutionary research of cereals and important crop species. Rice is a diploid plant and its genome length is short. Rainfed lowland rice is the second most important rice ecosystem, representing about 25% of the total rice production area. Fields do not receive irrigation, relying entirely on rainfall or drainage from higher lands in a watershed. Quality is of paramount importance as rice is consumed in full grain form. In Iran, rice quality is generally more important than yield, and Iranian tastes prefer aromatic rice with long grain length and low grain breadth. The purpose of this study was to identify effective markers on morphological traits, with a total of 20 indicative markers identified in both crop conditions. According to the results obtained from this assessment, they can be used in breeding programs.

This study was carried out in a research field of Gonbad-e-Kavous University in the year 2015-2016, in the form of Latis design in 3 replications, from 90 rice genotypes under normal conditions and drought stress using 11 drought tolerant markers. In this experiment, six physical traits of grain (brown and white rice) and three qualitative traits of rice grain were evaluated. These included: grain length, grain width, grain size, grain circumference, Equilibrium grain balance and Eccentricity of rice grain and percentage of protein, Amylose content and gelatinization temperature. DNA extractions were then extracted according to the CTAB method.

The beneficial results of microsatellite markers indicated that there were 54 polymorphic alleles, with the highest number of RM333 and RM589 with 7 alleles. In the analysis of the main components of SSR markers related to drought tolerance, the first 10 components were able to justify 55.58% of the variation. Clustering results divided genotypes into six groups. Investigating the adhesive patterns formed on acrylamide gel from 11 markers on 90 rice genotypes. The genotypes were grouped together in order to match the allelic pattern. Amylose content, protein content, gelatinization temperature for qualitative traits and quantitative traits of grain length and width (brown and white rice) of each group as a measure of groups. A comparison was made for drought tolerance, with a total of 20 groups identified. The results of the analysis of the relationship between the measured traits showed that among the 104 effective alleles on the traits, the effect of the RM6349-D allele with 9.99 had the greatest effect on the traits of the grain environment. Seedlings are affected by 8 alleles, the equivalent diameter of seeds with 7 alleles, length and area characteristics of seedlings with 6 alleles

Band pattern showed that genotypes can be grouped into a group in terms of matching the allelic pattern. The analysis of the main components of SSR-related drought tolerance markers with 10 components could justify more than 50% of the variation. Cluster analysis by line grouping identified the value of each group for the traits assessed.

Aflatoxin B1 (AFB1) is one of the most toxic Aflatoxins that contaminates agricultural products and causes deathlike effects on human health. Determination of AFB1 in food by biosensors is fast, low cost and accurate. In this paper, modeling and simulation of chemical reactions in the AFB1 potentiometric biosensor is performed to determine the optimal reaction rate constants. Enzymatic reactions are simulated using COMSOL software and reaction rates are optimized by Artificial Neural Network (ANN) and Genetic Algorithm (GA). The fitness function of GA is defined by deploying ANN. The data generated during the simulation step were used to train and evaluate the performance of the neural network. Compared with experimental data, COMSOL model simulated biosensor response with MAPE equal to 0.1023 %. In addition trained ANN with 5-48-1 structure predicted biosensor response with MAPEs equal to 0.7074 %, 0.9458 %, 0.7473 % and 0.7492 % for train, validation, test and total data sets respectively. Reaction rates were optimized by Artificial Neural Network (ANN) and Genetic Algorithm. Modeling results showed that trained Neural Network using Genetic Algorithm optimized reaction rates has the lowest MAPE equal to 0.0026 % compared with other models in prediction of AChE enzyme inhibition by AFB1.