Pengaruh Perbedaan Varietas Rumput Laut (Kappaphycus SP) dan Variasi Kedalaman terhadap Pertumbuhan dan Produksi Rumput Laut Menggunakan Metode Budidaya “Top Down”

The objective of this study was to investigate the effect of different types of Seaweed (Kappaphycus sp) and depth variation on the growth, production and carrageenan content of Seaweed using a top down cultivation method. Top down method combined the two methods of cultivation, the method of surface and off-bottom method. The types of Seaweed used were Kappaphycus alvarezii (Brown Maumere and Local Maumere) and Bali Seaweed (Kappaphycus striatum). This study was designed using a factorial experimental design, where is comprised of two factors: the types and water depth. Parameters measured were daily growth rate, production and carrageenan content of Seaweeds. The results showed that different types of Seaweed gave a significant effect (P0.05). A combination of Seaweed types and depth variation did not give a significant effect on daily growth rate and production of Seaweeds (P>0.05). The highest carrageenan content was found in Local Seaweed (42.15%). Brown Seaweed produced 40.59% of carrageenan content while Bali Seaweed produced 35.80%

Variability of White Spot Syndrome Virus (WSSV) envelope protein VP28 from diseased shrimp (Litopenaeus vannamei) in Indonesia

White Spot Disease (WSD) is a viral disease affecting crustaceans. Caused by the White Spot Syndrome Virus (WSSV), this disease has caused significant mortality in commercially cultivated marine shrimp species with severe impacts on the shrimp farming industry and may be a threat to wild shrimp stocks. Thorough studies on the molecular biology of this pathogen are urgently needed to improve understanding of the virus at a molecular level, including variation in key viral protein (VP) components of the WSSV virion. This study aimed to isolate and characterize WSSV VP28 gene encoding envelope proteins from Indonesian Pacific white shrimp (Litopenaeus vannamei) isolates. Infected juvenile shrimp were collected from Pangkep, Barru, and Pinrang Districts in South Sulawesi, Indonesia. Genomic DNA was isolated from infected shrimp muscle tissue using a DTAB-CTAB (dodecyle trimethyl ammonium bromide-hexadecyl trimethyl ammonium bromide) DNA extraction procedure. The WSSV VP28 DNA sequences from Pangkep, Barru, and Pinrang isolates were 640-680 bp in length. Homology of Pangkep isolates with isolates from Barru and Pinrang was 97-99%. BLAST-N (Basic Local Alignment Search Tool-Nucleotide) analysis showed isolates from all three sites clustered with WSSV VP28 accessions from China, Indonesia, Japan, South Carolina and Vietnam. These results increase the geographic spread and host taxon coverage of WSSV VP28 sequence data for Indonesia

Recruitment Constraints in Singapore's Fluted Giant Clam (Tridacna squamosa) Populations - A Dispersal Model Approach

10.1371/journal.pone.0058819PLoS ONE83

The Bio Economic Seaweed Model (BESeM) for modelling tropical seaweed cultivation – experimentation and modelling

The Bio Economic Seaweed Model (BESeM) is a model designed for modelling tropical seaweed cultivation. BESeM can simulate the common tropical seaweed cultivation system with multiple harvests per year, clonal reproduction and labour intensive harvesting and replanting activities. Biomass growth is modelled as a sigmoid, with growth being initially exponentially and eventually flattening off towards a maximum weight per plant or per square meter (wf,max). To estimate the latter, longer duration experiments than normal are needed – in the order of 100 days rather than 45 days. Drying (on platforms on the beach) is simulated as well as increase in harvested chemical concentration over time since planting, for harvested chemicals such as agar extracted from Gracilaria or carrageenan extracted from Kappaphycus or Euchema. BESeM has a limited number of parameters which makes it easily amenable to new sites and species. An experiment is presented for a site in Indonesia in which Gracilaria was monitored for 120 days in 6 nearby sites and from which BESeM model parameters were estimated. A simulation example is presented which illustrates how BESeM can be used to find the optimum combination of replanting weight and harvest cycle length (in days) for maximising gross and net farm income