Datasets on the optimization of alginate extraction from sargassum biomass using response surface methodology.

This article presents data associated with the extraction of sodium alginate from waste Sargassum seaweed in the Caribbean utilizing an optimization approach using Response Surface Methodology [1]. A Box-Behnken (BBD) Response Surface Methodology using Design Expert 10.0.3 software on the alkaline extraction process was used. Data consists of the effects of 4 process variables (temperature, extraction time, alkali concentration and excess volume of alkali: dried seaweed) on the yield of sodium alginate. The model was validated, and extracts were characterization using High Performance Liquid Chromatography (HPLC), Gel Permeation Chromatography (GPC), Fourier Transform Infrared Spectroscopy (FTIR) and Nuclear Magnetic Resonance (NMR). The data illustrates the applicability of our model in potentially valorizing this waste product into a valuable resource. Furthermore, our methodology can be applied to other macroalgae for efficient extraction of sodium alginate of commercial quality.

Value of the data • This data can be used in combination with other datasets for developing future studies associated with alginate extraction from Sargassum biomass. • This data can be extrapolated and adapted to solve optimization problems associated with inefficient extraction processes. • The data can be used for comparison purposes with alginate extraction from other sources of macroalgae. • The data serves as a basis for a waste-to-resource platform aimed at viable valorization of Sargassum within the Caribbean Region, currently experiencing the negative effects of this invasive species.

Data description
The datasets illustrated here give characterized polymer concentrations from extracts determined over the design space from a total of 29 runs. Table 1 gives the crude polymer concentrations derived from the experimental methodology composed by Design of Experiments. Predicted concentrations generated based on experimental validation are shown in Table 2 . Further isolation of the alginate polymer through purification using bleaching is given in Table 3 . Product quality assurance measurements utilizing color measurements were also considered as shown in Table 4 . Product characterization was as follows: polymer concentrations were determined using HPLC ( Fig. 1 ) while GPC ( Fig. 2 ) was used for molecular weight estimation. The signal intensities taken from NMR characterization obtained for different alginate samples, and calculated parameters for the alginate uronic acid sequences are given in Table 5 . Supplementary data, available from DOI: 10.17632/svn6c6zgx7.1, gives the raw datasets compiled from extraction, optimization, characterization and quality assurance experimental methodologies comprising the multistage extraction process.

Extraction of alginate and experimental design
Seaweed pre-treatment and acid treatment were done according to methods in our previous work [2] . Alkaline extraction was carried out over a temperature range 22-80 °C, a concentration range of 1-10% w/v Na 2 CO 3 , an excess volume range of 5-15 mL (Na 2 CO 3 : seaweed) and at reaction times ranging from 0.5-6 h. Box-Behnken experimental design (BBD) was chosen to investigate the effects of the aforementioned factors on extraction yield giving 29 experimen-tal runs [1] . This crude yield was found using High Performance Liquid Chromatography (HPLC), with concentrations presented in Table 1 .

Multistage extraction
Multistage extraction was carried out using methods derived in our previous work [2] . Optimum conditions were determined and validated in our study [1] using Derringer's desirability function found in Design Expert. Model validation was carried out at the optimum conditions and concentrations are presented in Table 2 .

Bleaching and precipitation of alginate
The purity of bleached and unbleached alginate samples was found using HPLC by comparing the alginate extracted to that of a commercial standard sample of concentration 0.2 g/ml ( Table  3 ).

Color analysis
Color measurements were carried out on the purified alginate powder, and the Whiteness Index (WI) determined using the Hunter (L, a, b) color measurement system [3] . The equation used is available [1] . The dataset for the color analysis is presented in Table 4 .

HPLC
The HPLC methodology was adapted from Awad and Aboul-Enein [4] . Alginate standards were made utilizing a 1 g/L analytical sodium alginate solution, within the calibration range of 0.05-0.25 g/L. The calibration curve and equation is presented in Fig. 1 .

NMR
NMR analysis was carried out according to ASTM F2259-10 [6] . The chemical shifts of the anomeric proton signals were A (guluronic acid anomeric proton) at around 5.08 ppm; B1 (H-5 proton of the central guluronic acid residue in a GGM triad) at 4.76 ppm; B2 (H-5 proton of the central guluronic acid residue in a MGM triad) at 4.73 ppm; B3 (anomeric proton of the mannuronic acid residue neighboring a mannuronic acid) at 4.70 ppm; B4 (anomeric proton of the mannuronic acid residue neighboring a guluronic acid) at 4.68 ppm and C (guluronic acid proton 5) at 4.48 ppm. The signals from the NMR spectra are given in Table 5 . The following equations were used to determine the uronic acid sequence [6] :

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.