Review
Plant Disease and Biotechnology
Samane Vatani; Saeed Nasrollanejad; Abdolhossein Taheri; Farzad Aliramaji; Sharbano Vakili; Leila Fahmideh
Abstract
Potato virus Y (PVY) is one of the most important and widely distributed viral diseases of Solanaceae family and the use of resistant cultivars is the most effective control measure of this disease. In this research, the response of seven pepper cultivars was investigated in two conditions, healthy control ...
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Potato virus Y (PVY) is one of the most important and widely distributed viral diseases of Solanaceae family and the use of resistant cultivars is the most effective control measure of this disease. In this research, the response of seven pepper cultivars was investigated in two conditions, healthy control and infection with PVY. This experiment was performed as a factorial in a completely randomized design with four replications. The results showed that under the conditions of viral infection, the growth indices including: height of the plant (31.84%), shoot fresh and dry weight (46.55 and 46.61%), plant fresh and dry weight (50.16 and 50.09%), root fresh and dry weight (54.76 and 51.93%) of all seven cultivars decreased compared to the control conditions.While the amount of chlorophyll a, b and total chlorophyll, carotenoid, the content of phenol and flavonoid and diseases severity of all studied cultivars increased compared to the control conditions. To confirm the infection of treated plants, PVY virus identification was performed by direct ELISA test with IgG-PVY antiserum and RT-PCR test using specific primers PVY-8687F and PVY-9295R.The results of the RT-PCR test showed the amplification of a fragment of 327 base pairs, which indicates the confirmation of the ELISA test and it was consistent with the sequence determination results in the NCBI database (Accession number–KR909091.1) that was previously registered for this isolate. In general, the Cauba cultivar has shown a better reaction in the face of infection with PVY virus. So, this cultivar can be suggested for future studies of pepper cultivars.
Review
Microbial Biotechnology
maryam sajedmarani; Soheila Talesh Sasani; Shohreh Ariaeenejad; Akram Sadeghi
Abstract
Plants with special compounds in their root exudates can strengthen a specific microbial community in the rhizosphere and prevent harmful microbial community from forming. The rhizosphere is a dynamic region around the plant root that is governed by the interaction between the plant and microorganisms. ...
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Plants with special compounds in their root exudates can strengthen a specific microbial community in the rhizosphere and prevent harmful microbial community from forming. The rhizosphere is a dynamic region around the plant root that is governed by the interaction between the plant and microorganisms. Plant root secretions can be influenced by plant species, plant growth stages and stress conditions and can be different; therefore, each microbial strain can regulate the expression of its genes at each stage of plant growth. Microbes are an unknown and huge source of secondary metabolites that play a very important role in the field of medicine and other industries. The present review focuses on factors inducing the production of new secondary metabolites from rhizosphere microbes. Each microbial strain has the potential to produce several compounds, but considering that the production of secondary metabolites is very costly for the cell, their synthesis is highly controlled by the cell. Studies have shown that changing the growth conditions of microbes, such as: temperature, salinity, co-cultivation (bacteria-bacteria, fungi-fungi, bacteria-fungi), change in oxygen concentration, aeration speed, addition of soil elements and rare metal ions, light radiation and also genetic engineering methods such as: insertion of strong inducible promoters, ribosome engineering, chromatin rearrangement, overexpression of pathway-specific regulatory genes and small molecules and chemical stimuli can help to discover new compounds. In this study, the above cases are explained in detail.
Research Paper
Medicinal plant Biotechnology
Leila Akbari; Mehdi Kakaei
Abstract
The most valuable products obtained from the (Peganum harmala L.) are phenolic compounds and other biochemical contents, which widely is used in treating of many diseases. This study has been done with the goal of evaluating the effect of different habitats on some biochemical and physiological parameters ...
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The most valuable products obtained from the (Peganum harmala L.) are phenolic compounds and other biochemical contents, which widely is used in treating of many diseases. This study has been done with the goal of evaluating the effect of different habitats on some biochemical and physiological parameters in pecan plant. First, the samples were identified and collected simultaneously in the four studied habitats. A factorial experiment with a completely randomized design with three replications was conducted in the central laboratory of Razi University in 2023. Results of the analysis of the variance of the studied traits has been showed, that there is a significant difference between the ecotypes and also the two leaf and seed samples in the characteristics of total chlorophyll content, soluble sugar, flavonoid and anthocyanin. The results showed that, there is a significant difference between the ecotype and the sample in chlorophyll b index. The difference between the samples is due to the type of ecotype and the effect of the environment. There is a significant positive correlation between chlorophyll a, chlorophyll b and total chlorophyll. Phenol and flavonoid content showed significant negative correlation with total chlorophyll and positive and significant correlation with anthocyanin. Considering the content of biochemical compounds and the high content of phenols and flavonoids as antioxidant compounds in the studied samples, it can be stated that Ecotype No. 2 can be introduced to researchers as a suitable sample for further studies in the pharmaceutical field. The authors are grateful for the cooperation of the director of the Faculty of Engineering Sciences and Natural Resources, Razi University.
Research Paper
Molecular Plant Breeding
Alireza Tarang; Majid Sattari
Abstract
The use of heterosis in hybrid rice breeding aims to increase productivity, with hybrid varieties yielding 20 to 30 percent more than conventional varieties. Maintaining genetic purity in hybrid seed production is critical to prevent contamination and selfing, especially in cytoplasmic male sterile lines. ...
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The use of heterosis in hybrid rice breeding aims to increase productivity, with hybrid varieties yielding 20 to 30 percent more than conventional varieties. Maintaining genetic purity in hybrid seed production is critical to prevent contamination and selfing, especially in cytoplasmic male sterile lines. This study aimed to identify microsatellite markers to distinguish hybrid rice parental lines and to assess seed purity and characterize the morphology of F1 hybrid rice. Initial trait assessments, including outcrossing levels and sterility stability, are critical for selecting preferred male sterile lines. Eighteen Iranian and exotic cytoplasmic male sterile lines and one thermosensitive genetic male sterile line, were evaluated for various traits in a randomized complete block design. PCR-based molecular markers were used to assess purity, revealing significant trait differences among lines. Selection and prioritization of superior lines such as Fajr A, Neda A and IR58025 A was based on fertility percentage, panicle yield and other traits. The Dasht B line with favorable traits such as proper height and panicle length proved to be a promising candidate for seed production. Molecular tests with PCR-based markers effectively discriminated between male sterile and conservation lines. The drrcms marker showed promise in distinguishing cytoplasmic male sterility lines from different sources, offering potential for genetic purity evaluation and infection testing of seed parents. These results point to valuable alternatives for maintaining genetic integrity in hybrid rice production.
Research Paper
Bioinformatics
Armin Saed-Moucheshi; Ali Shirkhani
Abstract
Dehydrin (DHN) proteins are a group of proteins that effectively respond to abiotic stresses such as cold and drought stress in plants. These proteins are a subset of protective greater group of proteins called type II Late embryogenesis abundant which are protecting other proteins from stresses shock. ...
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Dehydrin (DHN) proteins are a group of proteins that effectively respond to abiotic stresses such as cold and drought stress in plants. These proteins are a subset of protective greater group of proteins called type II Late embryogenesis abundant which are protecting other proteins from stresses shock. Due to the significant effect of dehydrin proteins in plants, specialy under abiotic stresses, the aims of this study were to survey the linear structure along with phylogeny relationship of this proteins’ group in different plants species. The protein linear sequences of different plant species were downloaded from NCBI site and then were aligned using MegaX software. The results of aligning showed highly conserved segments within the considered sequences such as K- and S-segments that are respectively responsible for covering other proteins and protecting them from damaging effects of stresses and transporting dehydrin proteins from cytoplasm to nucleus. Using the sequences’ alignment, phylogenic tree was extracted using Neighbor joining method. Furthermore, linear sequence order of amino acids and their ratio in the structure of these protein were evaluated. Folowing that, the composition of these proteins genomic sequences were considered to compare with the results of amino acids evaluation. The results indicated that dicotyledon and monocotyledon plants can be clearly separated into two distinguished classes based on the amino acid structure of DHN proteins. Similarly, The ratio and order of DNHs linear sequences were distinctly altered between mono- and di-cotyledon plants. Evaluation of genomic base pairs of these proteins showed that there are numerous unchanged motifs with eighter no or a little difference shared among the genomic sequences of DHN proteins.
Review
Bioinformatics
bahman panahi; Bentolhoda Ghavidel; pouya shahgoli
Abstract
Machine learning plays a crucial role in identifying specific stressors that impact plant species and provides a comprehensive understanding of the challenges plants face in natural environments. The use of machine learning algorithms has significantly enhanced our ability to classify and differentiate ...
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Machine learning plays a crucial role in identifying specific stressors that impact plant species and provides a comprehensive understanding of the challenges plants face in natural environments. The use of machine learning algorithms has significantly enhanced our ability to classify and differentiate the types of stress. There are two main methodologies in machine learning: supervised learning and unsupervised learning. In supervised learning, the model is trained using input-output data pairs, while unsupervised learning involves training the model without access to output labels. Unsupervised learning is primarily used for data exploration and dimension reduction. This detailed classification helps us better understand the distinct characteristics associated with different stressors and provides a more nuanced view of the plant stress landscape. Machine learning also enables the quantitative assessment of stress intensity and extent, allowing for an accurate evaluation of its impact on plant health and productivity. This quantitative approach helps researchers measure the true extent of stressors and their effects on the overall health of plant ecosystems. By employing advanced algorithms, machine learning can make predictions about future occurrences of stress and their potential consequences on plant ecosystems. This foresight strengthens preventive measures for sustainable agricultural practices, as researchers and practitioners can anticipate and mitigate potential threats to plant health. The purpose of this review is to provide a comprehensive understanding of the applications and concepts of machine learning in uncovering the complexity of plant stress phenotyping and elucidating the involved molecular mechanisms.
