TAILIEUCHUNG - Advancements in methods used for identification of lichens

Lichen is a combination of two organisms one is alga and another one is fungus. There is symbiotic relationship between alga and fungus. The algal part provides nutrition to the whole organism and the fungus part provides structural support to the organism. Lichens has been used for many purposes in all over the world because lichens have tremendous properties in them due to the presence of various natural compounds known as primary and secondary metabolites which are not known to other group of plants (unique with respect to higher plants), to take the benefit of these properties correct identification of lichens is necessary. Identification of lichen is very difficult task due to the complex structure of lichens, which consumes lot of time. Exploration of these properties is only possible when lichens are identified correctly, properly, easily and on time. Different types of methods are used to identify lichens and these methods are modified day by day to get better results. Taxonomists mainly use three different approaches for identification of lichens (a) Microscopic approaches (b) chemical approaches (c) Molecular approaches. Molecular approaches are the best and fastest approaches to identify the lichens correctly and easily. With the help of information technology and computer applications all the informative data which is collected during identification is compiled and stored in an application in the form of digital library through which one can easily retrieved the data for future use. This helps the taxonomists in identification, characterization and in quick classification of lichens. | EXCELLENT PUBLISHERS International Journal of Current Microbiology and Applied Sciences ISSN 2319-7706 Volume 8 Number 08 2019 Journal homepage http Review Article https Advancements in Methods Used for Identification of Lichens Sachin Singh1 Mamta Arya2 and Shailesh Kumar Vishwakarma3 Department of Zoology and Biotechnology . Garhwal Unviersity Uttarakhand-246174 India Corresponding author ABSTRACT Keywords Lichens Chemotyping DNA Barcoding PCR Genotyping Article Info Accepted 12 July 2019 Available Online 10 August 2019 Lichen is a combination of two organisms one is alga and another one is fungus. There is symbiotic relationship between alga and fungus. The algal part provides nutrition to the whole organism and the fungus part provides structural support to the organism. Lichens has been used for many purposes in all over the world because lichens have tremendous properties in them due to the presence of various natural compounds known as primary and secondary metabolites which are not known to other group of plants unique with respect to higher plants to take the benefit of these properties correct identification of lichens is necessary. Identification of lichen is very difficult task due to the complex structure of lichens which consumes lot of time. Exploration of these properties is only possible when lichens are identified correctly properly easily and on time. Different types of methods are used to identify lichens and these methods are modified day by day to get better results. Taxonomists mainly use three different approaches for identification of lichens a Microscopic approaches b chemical approaches c Molecular approaches. Molecular approaches are the best and fastest approaches to identify the lichens correctly and easily. With the help of information technology and computer applications all the informative data which is collected during identification is compiled and stored in an application .

• Sinh học
• DNA Barcoding
• PCR genotyping
• Identification of lichens
• Advancements in methods
• Various natural compounds
• Potential DNA barcoding loci
• Plastid genome
• Intraspecies discrimination in rice
• DNA barcoding in rice
• Gulf of mannar
• DNA barcoding on cardinalfishes
• Thoothukudi coast
• DNA barcoding for identification
• Identification of some fish species (Carangidae)
• Vietnam coastal area
• Morphological classification method
• Turkish Journal of Botany
• Tạp chí Thực vật học
• Indian wild coffee species
• Unique fixed nucleotides
• DNA sequence polymorphism
• BMC Plant Biology
• Low copy nuclear gene
• Plant collections
• Ecological diversity
• BMC Genomics
• DNA barcode
• High throughput sequencing
• COI barcode region
• Fungi symbionts
• Tạp chí khoa học
• Công nghệ sinh học
• Khoa học tự nhiên
• Dendrobium transparens
• Pitcher plant
• Cytochrome oxidase I
• Nepenthes genus
• Molecular identification
• Bayesian inference
• Maximum likelihood
• Medicinal plants
• Journal of Zoology
• Cytochrome oxidase I COI
• Black cherry aphid
• Nucleotide diversity
• Plant Biology
• Super barcoding
• Calypogeia species
• DNA fragments
• Multi locus barcoding
• Adinandra lienii
• Mã vạch DNA matK
• Trình tự đoạn gen matK phân lập
• Chi Adinandra thuộc họ Chè Theaceae
• Hỗn hợp phản ứng PCR
• Lepidopteran insects and mtDNA
• Cole crops in MID HILLS
• MID HILLS of Meghalaya
• DNA barcodes
• Major insect pest
• BMC Genetics
• BOLD systems
• Fungal taxonomy
• DNA barcoding technique
• Trình tự gen RpoC1
• Gen RpoC1
• Gen lục lạp
• Xác định quan hệ chủng loài
• Kỹ thuật DNA mã vạch
• Genome Biology
• Assembly free
• Alignment free
• Genome skimming
• DNA reference database
• Second generation sequencing
• P corylifoilia
• M pruriens
• C ternatea
• TrnH psbA
• Species Identification
• Trình tự gen rpoB
• Morinda officinalism
• Ngân hàng gen mã số KR689730
• BMC Bioinformatics
• Cellular barcoding
• Lineage tracing
• Next generation sequencing
• Sequencing error
• PCR error
• COI gene
• Intra and inter species diversity
• Tropical forest
• Genetic distance of leaf beetles
• Journal of Botany
• Hypericum occurring in Sicily
• Hypericum triquetrifolium
• Phytotherapic purposes
• Molecular analyses
• Tyrrhenian Sea
• Cryptic diversity
• Rare species
• Cytochrome c oxidase subunit I (COI)
• Luận văn Thạc sĩ
• Luận văn Thạc sĩ Sinh học
• Rong biển thuộc chi Ulva
• Sinh học thực nghiệm
• Sinh học phân tử DNA barcoding
• Phương pháp điện di Gel agarose
• Approximate Bayesian computation
• Freshwater species
• Neocaridina species