Tue, Aug 16, 2022: 5:00 PM-6:30 PM
ESA Exhibit Hall
Background/Question/MethodsBees are some of the crucial pollinator in the world, and they can help the crop producing, pollination and even maintain biodiversity. Identification of pollen is a major way to determine the main plant source to bees. This information can be used as a reference for government and policies to ensure the ecosystem sustainable. To understand what kind of honey plants are there around the Chiayi University. We used the pollen traps to collected the pollen from Apis mellifera once a week for ten months from 2017 to 2018 in Chiayi University, Taiwan. Next Generation Sequencing (NGS) with the two barcodes (rbcL and trnL) was used to identify the plant species. Then using the Jaccard similarity coefficient and Bray-Curtis dissimilarity index to compare the species abundance and composition between two plant barcodes.
Results/ConclusionsThe results revealed that the pollen were separated into 191 taxa. Most of them can be identified to genus (107, 56.2%) and only 44 of sequences (23.0%) can be identified to species. The results in rbcL barcode identified 22 species (15.7%), 84 genera (60.2%) and 29 families (20.7%) records and the others are orders and phylum . On the other hand, the trnL barcode identified over half of data to genus, 30 species (28.3%) and 22 families (20.8%). However, the similarity of taxon data in two barcodes only 28.8%. The top three species of main pollen in rbcL data is Luffa (5.8%), Leucaena (4.0%) and Paederia (3.4%). Nevertheless, the results of trnL are quite different from rbcL barcode. The dominant pollen source of genus in trnL data is Paederia (20.5%), and the second and third are Bidens (5.0%) and Bauhinia (3.4%). Interestingly, there were native species, alien species, cultivated crops and cash crops but without any endemic species. Therefore, the primer difference, insufficient data base and the different taxonomic resolution for pollen that made the results not resemble in two barcodes. Moreover, Establishment of barcoding database is important and necessary for application of molecular approaches to pollen identification in Taiwan.
Results/ConclusionsThe results revealed that the pollen were separated into 191 taxa. Most of them can be identified to genus (107, 56.2%) and only 44 of sequences (23.0%) can be identified to species. The results in rbcL barcode identified 22 species (15.7%), 84 genera (60.2%) and 29 families (20.7%) records and the others are orders and phylum . On the other hand, the trnL barcode identified over half of data to genus, 30 species (28.3%) and 22 families (20.8%). However, the similarity of taxon data in two barcodes only 28.8%. The top three species of main pollen in rbcL data is Luffa (5.8%), Leucaena (4.0%) and Paederia (3.4%). Nevertheless, the results of trnL are quite different from rbcL barcode. The dominant pollen source of genus in trnL data is Paederia (20.5%), and the second and third are Bidens (5.0%) and Bauhinia (3.4%). Interestingly, there were native species, alien species, cultivated crops and cash crops but without any endemic species. Therefore, the primer difference, insufficient data base and the different taxonomic resolution for pollen that made the results not resemble in two barcodes. Moreover, Establishment of barcoding database is important and necessary for application of molecular approaches to pollen identification in Taiwan.