Nuclear ribosomal DNA (rDNA) was analyzed to identify inter-specific genetic relationships among 8 Cymbidium species (Cymbidium insigne, C. ensifolium, C. marginatum, C. faberi, C. gyokuchin, C. kanran, C. forrestii, and C. goeringii). Nuclear rDNA including 2 internal transcribed spacer (ITS) regions and 5.8S, was amplified using polymerase chain reaction and sequenced. The sequences were compared via pair-wise multiple alignment to determine the genetic relationships among the studied species. The lengths of the ITS1, ITS2, and 5.8S regions were 235 bp, from 255 bp to 257 bp, and from 153 bp to 165 bp, respectively. Sequence similarities in the ITS region ranged from 78.7% between C. gyokuchin and C. kanran to 96.8% between C. ensifolium and C. kanran. A phylogenetic tree was constructed from nuclear rDNA nucleotide sequence data of the 8 cymbidiums and 1 outgroup species to estimate genetic relationships. The tree revealed that cymbidiums could be classified by their ecological traits, such as their temperature preference or inflorescence pattern. The phylogenetic data is applicable for identification, classification, and breeding of cymbidiums.
We conducted experiments to compare the catch rate of bigeye tuna and yellowfin tuna between circle hooks and straight shank hook in the Korean tuna longline fishery at the eastern and central Pacific Ocean from 2005 to 2007. We analyzed difference of fork length, survival and hooking location between a circle hook and a straight shank hook for both tunas, respectively. There was no difference in the mean fork length size of yellowfin tuna caught on the two type of hook but bigeye tuna was significant. In case of survival, there was no difference between two hook type, but the difference of hooking location was significant for both species. We also analyzed to find determinants of both tunas catch rate using generalized linear models (GLMs) which were used latitude, longitude, year, month, depth, hook type, bait type and so on as independent variables. Spatial factors, latitude and longitude, and temporal factors, year and month, affected catch rate of bigeye tuna and yellowfin tuna. And also, depth such as a marine environment factor was influenced on catch rate.