Dataset Information

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

ABSTRACT: 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 (w _f,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.

Supplementary information

The online version contains supplementary material available at 10.1007/s10811-022-02799-8.

SUBMITTER: van Oort PAJ

PROVIDER: S-EPMC9390115 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

van Oort P A J PAJ Rukminasari N N Latama G G Verhagen A A van der Werf A K AK

Journal of applied phycology 20220819 5

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 (w f,max ). To estimate th ...[more]

PMID: 36033834

Similar Datasets

Project description:BACKGROUND:Chronic kidney disease (CKD) is a progressive condition that leads to irreversible damage to the kidneys and is associated with an increased incidence of cardiovascular events and mortality. As novel interventions become available, estimates of economic and clinical outcomes are needed to guide payer reimbursement decisions. OBJECTIVE:The aim of the present study was to systematically review published economic models that simulated long-term outcomes of kidney disease to inform cost-effectiveness evaluations of CKD treatments. METHODS:The review was conducted across four databases (MEDLINE, Embase, the Cochrane library and EconLit) and health technology assessment agency websites. Relevant information on each model was extracted. Transition and mortality rates were also extracted to assess the choice of model parameterisation on disease progression by simulating patient's time with end-stage renal disease (ESRD) and time to ESRD/death. The incorporation of cardiovascular disease in a population with CKD was qualitatively assessed across identified models. RESULTS:The search identified 101 models that met the criteria for inclusion. Models were classified into CKD models (n = 13), diabetes models with nephropathy (n = 48), ESRD-only models (n = 33) and cardiovascular models with CKD components (n = 7). Typically, published models utilised frameworks based on either (estimated or measured) glomerular filtration rate (GFR) or albuminuria, in line with clinical guideline recommendations for the diagnosis and monitoring of CKD. Generally, two core structures were identified, either a microsimulation model involving albuminuria or a Markov model utilising CKD stages and a linear GFR decline (although further variations on these model structures were also identified). Analysis of parameter variability in CKD disease progression suggested that mean time to ESRD/death was relatively consistent across model types (CKD models 28.2 years; diabetes models with nephropathy 24.6 years). When evaluating time with ESRD, CKD models predicted extended ESRD survival over diabetes models with nephropathy (mean time with ESRD 8.0 vs. 3.8 years). DISCUSSION:This review provides an overview of how CKD is typically modelled. While common frameworks were identified, model structure varied, and no single model type was used for the modelling of patients with CKD. In addition, many of the current methods did not explicitly consider patient heterogeneity or underlying disease aetiology, except for diabetes. However, the variability of individual patients' GFR and albuminuria trajectories perhaps provides rationale for a model structure designed around the prediction of individual patients' GFR trajectories. Frameworks of future CKD models should be informed and justified based on clinical rationale and availability of data to ensure validity of model results. In addition, further clinical and observational research is warranted to provide a better understanding of prognostic factors and data sources to improve economic modelling accuracy in CKD.

Dataset Information

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

Supplementary information

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets