فهرست مطالب mohsen mardi

Today, using advanced technologies such as the global positioning system (GPS), agricultural drones, satellite mapping, remote sensors, and precision agriculture machinery provides farmers with a lot of big data during production. According to the reports, this can be considered a part of the digital economy in precision agriculture and be economically exploited. The analysis of this data cannot be processed by traditional processing systems due to its complexity. Given the size and complexity of big data, artificial intelligence can transform this data into valuable information through machine learning algorithms. This technology is being used to performance prediction algorithms, reducing agricultural inputs such as fertilizers and poisons, monitoring the growing conditions, pest management, breeding, molecular studies and finally value chain management. Developing programs using artificial intelligence technology will soon be able to manage the time of agricultural products entering the market, in addition to determining the planting time in order to increase productivity. The production of bio fertilizer from agricultural waste can be another achievement of the development of algorithms based on artificial intelligence to reduce the negative environmental effects and increase the economic productivity of the remaining waste from agricultural products. This study discusses the important applications of artificial intelligence in agriculture and its impact on Precision agriculture.

Context:

 Chicken meat is one of the rich sources of protein and is considered one of the most commonly consumed meats in the world. Enhancing poultry production and its products is achievable through chicken breeding. Effective breeding projects for future genetic improvement require an understanding of the genetic potential of a given population.

Evidence Acquisition:

 Articles were selected based on novel molecular markers related to economic traits of chicken in Animal quantitative trait loci (QTL) database, Ensemble genome browser, CorrDB, ChickVD, Galbase, and Google Scholar. These databases contain QTLs, markers, and reference genomes of chicken. Galbase provides research communities with updated possibilities to conduct thorough functional genomics research on chickens. ChickVD manages high-quality sequence variation data, variation analysis in relation to chicken genes, cDNAs, genetic markers, and QTLs. CorrDB compiles all available chicken genetic and phenotypic trait correlation data to aid in the analysis of genetic networks and facilitate systems biology research. Animal Quantitative Trait Loci Database (Animal QTLdb) gathers and compiles all existing data on trait mapping, including QTL (phenotype/expression, eQTL), candidate gene, association data (GWAS), and copy number variations (CNV) for livestock animal genomes. This comprehensive database facilitates the easier identification and comparison of discoveries within and across species. Ensemble genome browser is a powerful tool for analyzing vertebrate genomes, offering valuable insights into comparative genomics, evolutionary processes, sequence variations, and transcriptional regulation.

 valuating the relatedness of the studied broilers and layers is important for maintaining and improving the genetic reserves of the same population. Candidate genes (CGs) are used to determine genes related to economic traits in chickens. Molecular genetic techniques such as whole-genome re-sequencing (WGRS) can identify single nucleotide polymorphisms (SNPs), insertion/deletion polymorphisms (indels), structural variations (SV), CNV, and simple sequence repeats (SSRs) and their chromosomal regions in terms of QTL. Recently, the pan-genome (PG) has become one of the most important tools to study genome variation and changes in important traits. The use of molecular markers and CGs can aid in evaluating the genetic relationships between phenotype and genotype of broilers and layers.

 This review introduces molecular genetic methods and new approaches to identify novel genes related to important biological pathways and significant production and reproductive traits.

In stevia (Stevia rebaudiana), breeding programs are mainly aimed at developing plants with high Rebaudioside-A (RA) content. To this end, in order to screen stevia plants and selection of varieties with the highest amount of desired sweeteners (RA) using molecular markers, the present study was conducted on RNA-seq data of varieties having different amounts of RA. We took advantage of CLC to make de novo transcriptome assembly for each variety with k-mer and contig length values of 20 and 200bp, respectively. The assembly was annotated using the latest Arabidopsis proteome release. To identify signatures of candidate polymorphic SSRs among the stevia varieties, the assembled sequences were used as an input for CandiSSR, followed by designing primer pairs for identified polymorphic SSRs. We identified 368 potential polymorphic SSRs based on the stevia transcriptome analysis, among which 360 were qualified for primer design. Almost 89% of the contig sequences possessing polymorphic SSRs had the best blast hit against Arabidopsis proteome. We found contigs similar to the UDP-Glycosyltransferase protein family and Deoxyxylulose-5-phosphate synthase which are involved in biosynthesis pathway of steviol glycosides. Also, gene set enrichment analysis using PlantGSE through Hypergeometric test (FDR<0.05) identified enriched metabolic pathways in the sequences contained polymorphic SSRs; It is therefore most likely that such connections exist between the SSRs and biosynthesis of steviol glycosides. Hence, it could conceivably be hypothesized that the SSR markers developed in this study would be reliable in molecular breeding of stevia toward selection of varieties with high RA content.

In order to identify yield and yield component QTLs under control and salt-stress conditions, a population of 254 recombinant inbred lines (RILs), derived from a cross between two bread wheat cultivars, (Roshan / Sabalan), was assessed. Parents and their 254 recombinant inbred lines (RILs) were evaluated in an alpha-lattice design with two replications in two control and saline environments of Yazd in 2011-2012 cropping season. Yield and yield-related traits were evaluated at harvest time. The genotyping was carried out using SSR and DArT markers. A, B and D genomes were covered by 411.8, 620.4 and 67.5 cM, respectively. Also, a total of 48 QTLs were detected on 11 chromosomes for grain yield, biological yield, harvest index, thousand-kernel weight, grain number per spike, spike weight and spikelet number per spike. Roshan (salt tolerance) alleles were associated with an increase yield under saline conditions. SSR markers including gwm146, gwm577, gwm249 (on chromosomes 2A and 7B) were tightly associated with different QTLs. The major effect QTLs were located on chromosomes 1A and 7B for grain yield, harvest index and spike weight, which were explained 10.2%, 12.98% and 29 % of the total phenotypic variance, respectively. These QTLs and markers could be suitable for marker-assisted selection and gene stacking techniques. Moreover, co-located QTLs were detected on chromosome 2B for evaluated traits.

Due to the complex assessment of young walnut cultivars (Juglansregia L.) based on morphological traits، advance molecular tools have provided a new prospect for cultivar identification and DNA fingerprinting. In this study، specific molecular keys were identified for 5 Iranian walnut cultivars (Juglansregia L.) using 30 SSR markers. The results showed that 5 SSR markers produced polymorphic bands for studied Iranian walnut cultivars. SSR markers WP-376andABRII-WM-6produced specific molecular keys in walnut cultivars K72، Z30، Z53 and Z60. Due to different genetic background، it was impossible to recommend the B21 and Z67 genotypes as mother’s trees. The specific molecular keys were verified on 39 walnut mother''s trees and the results were confirmed at two independent laboratories. The reported specific molecular keys can be used for identification of 5 Iranian walnut cultivars in juvenile period.

Mexican lime is one of the most important and economic fruit crops in the southern regions of Iran. This crop is susceptible to Citrus Tristeza Virus (CTV) and Witches Broom Disease of Lime (WBDL). Therefore, optimization of regeneration and transformation system for this plant is necessary for its improvement. In this project, the effect of different factors such as internode and epicotyl explants; two different regeneration media containing different concentrations of BAP and NAA, different Agrobacterium strains: “LBA4404” and “EHA105”, each harboring a binary vector pBI were studied in a factorial experiment. The results showed that the etiolated epicotyl was the best explants for regeneration and callus production. There was no significant difference between two regeneration media. Furthermore, EHA105 was the best Agrobacterium strain for this purpose. Polymerase Chain Reaction (PCR) using gus-specific primers has been carried out on DNA extracted from all regenerated plants. Twenty-one shoots were carrying this gene but only 8 shoots out of these 21 showed the expression of this gene. Furthermore, the lack of Agrobacterium-related infections has been confirmed using virG-specific markers.