Comparative Chemical Research in Essential Oils from Six Apiaceae Species Growing in the Northern Region of Vietnam

Our study aimed to compare the essential oil(EO)concentration and composition of several Apiaceae species growing in the Northern region of Vietnam.The yields of EOs from materials ranged from 0.03%(root EO of Angelica acutiloba and aerial parts EO of Heracleum bivittatum)-0.27%(leaf EO of Xyloselinum vietnamense).Gas chromatography-mass spectrometry(GC-MS)allowed the identification of 74 components in the EOs of six Apiaceae species,making up 94.4%–100.0%of the oils.In EO from Angelica acutiloba,(Z)-ligustilide accounted for an extremely large proportion(94.9%).EO of Angelica pubescens was dominated by six character-istic components includingα-pinene(21.5%),β-phellandrene(18.1%),p-cymene(12.2%),3-methylnonane(8.7%),o-cymene(8.1%),and D-sylvestrene(6.2%).The EO from Cryptotaenia japonica was characterized by high amounts ofα-selinene(48.7%),β-selinene(23.7%),and trans-β-farnesene(5.4%).The EOs from leaves and stems of Xyloselinum vietnamense were characterized by high concentrations of sabinene(69.8%and 33.8%),4-terpineol(8.7%and 7.4%)andβ-pinene(4.0%and 6.5%)while EOs from aerial parts and root of Xylo-selinum leonidii comprise four characteristic monoterpenes includingα-pinene(28.2%and 52.8%),β-pinene(7.9%and 10.3%),β-phellandrene(7.6%and 15.3%),and sabinene(3.0%and 4.1%).Additionally,cryptone is also one of the major components in the EO of Xyloselinum leonidii(13.2%in the aerial parts oil and 2.8%in the root oil).In the EOs isolated from the aerial parts and root of Heracleum bivittatum,α-pinene(22.5%and 70.2%)andβ-pinene(43.2%and 20.0%)were the predominant monoterpenes.Sabinene appeared in the EO from aerial parts of Heracleum bivittatum with a relatively high concentration(13.5%)while bornyl acetate(5.1%)was also one of the main components in the EO from its aerial parts but was not detected in other Apiaceae species in the present study.These databases help identify and control the quality of plant material studied from the family Apiaceae growing in Vietnam.

GIS-Based Multi-Criteria Evaluation Models for Selection of Suitable Sites for Pacific Oyster(Crassostrea gigas)Aquaculture in the Central Region of Vietnam

Oysters are nutritious food organisms,rich in protein,minerals and vitamins.Production from Pacific oyster(Crassostrea gigas)aquaculture is increasing and supports the livelihoods of coastal communities.To ensure both success and long-term sustainability of oyster production,the determination of suitable sites is an important step in any aquaculture operation.This study applied GIS(Geographic Information System)based MCE(Multi-Criteria Evaluation)for locating suitable sites for Pacific oyster(Crassostrea gigas)farms in coastal regions in Central Vietnam.Remote sensing data were obtained viaMODIS(Moderate Resolution Imaging Spectroradiometer)and high resolution imagery from the Google Earth Engine,while oceanic data were obtained from HYCOM-NCODA(Hybrid Coordinate Ocean Model-Navy Coupled Ocean Data Assimilation)coupled with local hydrodynamic FEM(Finite Element Model)Hydrographic charts and GPS(Global Positioning System)data were used to extract required information layers for GIS based MCE for the suitable site selection of oyster farms.Six thematic layers of biophysical parameters were used to analysis MCE non-constraints including the depth,temperature,salinity,Chl-a(Chlorophyll-a)content,suspended matter concentration and velocity of sea current.Then,an MCE analysis with constraint was used to exclude the areas from suitability maps where oyster aquaculture could not be developed.They were conducted in two subgroups,biophysical subgroup(including un-suitable depth,un-suitable substratum and shore line types,potential regions prone to strong impact of natural disasters and environmental risks,sensitive habitats in MPAs(Marine Protection Areas),and social-infrastructural subgroups(including human settlement in urban area,wastewater system,industrial zones,piers,harbors etc.).A series of GIS models was developed to identify the most suitable areas for oyster culture using MCE with the estimating of factor score(Xi)based on expert knowledge as well as calculating of Weighting(Wi)based on Saaty’s matrix relevant to the importance level of assessed factors in comparison.Suitability scores were ranked on a scale from 1(least suitable)to 8(most suitable).The best suitable sites for oyster aquaculture in coastal areas of the central region of Vietnam have been found.These study results confirmed that a GIS based MCE model is a powerful tool that supports site selection decision-making in aquaculture.