The main purpose of this research is to apply image processing for plant identification in agriculture. This application field has so far received less attention rather than the other image processing applications domains. This is called the plant identification system. In the plant identification system, the conventional technique is dealt with looking at the leaves and fruits of the plants. However, it does not take into account as a cost effective approach because of its time consumption. The image processing technique can lead to identify the specimens more quickly and classify them through a visual machine method. This paper proposes a methodology for identifying the plant leaf images through several items including GIST and Local Binary Pattern (LBP) features, three kinds of geometric features, as well as color moments, vein features, and texture features based on lacunarity. After completion of the processing phase, the features are normalized, and then Pbest-guide binary particle swarm optimization (PBPSO) is developed as a novel method for reduction of the features. In the next phase, these features are employed for classification of the plant species. Different machine learning classifiers are evaluated including k-nearest neighbor, decision tree, naï ve Bayes, and multi-SVM. We tested our proposed technique on Flavia and Folio leaf datasets. The final results demonstrated that the decision tree has the best performance. The results of the experiments reveal that the proposed algorithm shows the accuracy of 98.58% and 90.02% for the "Flavia" and "Folio" datasets, respectively.

Background: Global climate change and associated adverse abiotic stress conditions, such as drought, salinity, heavy metals, waterlogging, extreme temperatures, oxygen deprivation, etc., greatly in uence plant growth and development, ultimately affecting crop yield and quality, as well as agricultural sustainability in general. This study provides new insights into the analysis of the function of soybean genes in abiotic stress. Drought is one of the signi cant constraints that limit agricultural productivity. Some factors, including climate changes and acreage expansion, indicate the need for developing drought-tolerant Genotypes.Materials and methods: The study of the expression Glutathione Reductase (GR) gene in soybean droughttolerant and sensitive cultivars using real-time PCR. Seeds from (drought-sensitive) and (drought-tolerant) lines were planted under speci c temperature conditions drought stress treatment, in the research greenhouse of Islamic Azad University of Arak, Iran. Changes in gene expression compared to reference genes were recorded using the formula 2 -ΔΔCT . Three technical replications were given for each cDNA sample related to each sampling and used to analyze test data from MINITAB16 software.Results: The results showed that the threshold expression of gene expression (Glutathione) in the Pyramid line had the highest expression of drought resistance and the lowest expression of the Glutathione Reductase gene belonging to the Will line. The theory is also true that chaperone proteins produced during the plant growth cycle are not destroyed to express the Glutathione Reductase gene. The expression cycle of the Glutathione Reductase gene shows that the proteins produced by this gene have a high rate of expression and increase in cell drought stress. This gene expression continues until the pressure ends. The results showed that lines and cultivars with a weak expression against drought stress could have a high expression at the beginning of drought stress but a decrease in gene expression rate during stress. Drought stress-sensitive lines have a decreasing expression in the middle and end of stress during the stress period.

No abstract

The common pistachio psyllid, Agonoscesna pistaciae is a key pest of pistachio trees in Iran. Both adults and nymphs cause great economic damages by sucking sap and produce large amounts of honeydew. The geographical distribution of this pest was studied using maxEnt in different climates of Iran. In the present study, Field experiments were conducted during 2019–2020 on pistachio trees and records of 732 specimens collected from 24 climates of Iran in addition to altitude and climate variable data were used for modeling analysis. The results show that northwest of Iran with climatic characteristics of mild winters; warm summers and arid regime were the most suitable areas for A. pistaciae, while the central, west and southeast regions of Iran with very high temperatures were predicted to be less suitable. The habitat distribution patterns for some species such as A. pistaciae can be modeled using a small number of occurrence records and environmental variables using MaxEnt and could be used in plant protection and implementation of integrated control programs.

Background: Global climate change and associated adverse abiotic stress conditions, such as drought, salinity, heavy metals, waterlogging, extreme temperatures, oxygen deprivation, etc., greatly influence plant growth and development, ultimately affecting crop yield and quality, as well as agricultural sustainability in general. This study provides new insights into the analysis of the function of soybean genes in abiotic stress. Drought is one of the significant constraints that limit agricultural productivity. Some factors, including climate changes and acreage expansion, indicate the need for developing drought-tolerant Genotypes.Materials and methods: The study of the expression Glutathione Reductase (GR) gene in soybean drought-tolerant and sensitive cultivars using real-time PCR. Seeds from (drought-sensitive) and (drought-tolerant) lines were planted under specific temperature conditions drought stress treatment, in the research greenhouse of Islamic Azad University of Arak, Iran. Changes in gene expression compared to reference genes were recorded using the formula 2-ΔΔCT. Three technical replications were given for each cDNA sample related to each sampling and used to analyze test data from MINITAB16 software.Results: The results showed that the threshold expression of gene expression (Glutathione) in the Pyramid line had the highest expression of drought resistance and the lowest expression of the Glutathione Reductase gene belonging to the Will line. The theory is also true that chaperone proteins produced during the plant growth cycle are not destroyed to express the Glutathione Reductase gene. The expression cycle of the Glutathione Reductase gene shows that the proteins produced by this gene have a high rate of expression and increase in cell drought stress. This gene expression continues until the pressure ends. The results showed that lines and cultivars with a weak expression against drought stress could have a high expression at the beginning of drought stress but a decrease in gene expression rate during stress. Drought stress-sensitive lines have a decreasing expression in the middle and end of stress during the stress period.