Results and Discussion

3.1 Scope for bioethanol production from macroalgal biomass

The availability of spectrum of species amenable for biofuel production is one of the unique aspect of algae when compared to other advanced feedstock [35]. Production of different types of biofuels (bioethanol, diesel, bio-oil, and bio-hydrogen) is optimized by prioritizing species.

Characteristics of prioritized macroalgal feedstock for sustainable biofuel production are (i) availability throughout the year (during all seasons) and (ii) presence of higher quantum of sugar.

3.1.1 Macroalgal feedstock availability and selection

Indian coast has about 1153 marine algal species belonging to 271 genera, of which 60 species are commercially important. Rocky beaches, mudflats, estuaries, coral reefs and lagoons are the preferred habitats for macroalgae. Indian coast harbors predominantly intertidal and subtidal algal communities [143]. Macroalgal feedstock (for bioethanol production) distribution along the Indian Coast and islands were compiled from various secondary data sources [144–150] along with the locations based on the current field investigations is represented in Fig.4. Seaweed species belonging to Laminaria genera (Brown algae or Phaeophyta) are not recorded in India and these are algae of cold waters and certain brown algae of orders Dictyotales and Fucales (e.g. Sargassum) are distinctly warm-water plants [151] are abundantly spread and are recorded from Indian Coast. Kappaphycus alvarezii, a red algae is native of Indonesia and Philippines and introduced in India for commercial cultivation purpose [152], which has now colonized in various parts of Gulf of Mannar.

Fig. 4. Distribution of potential macroalgal feedstock of Indian coast

Setting up of bio refinery necessitates easier cultivation strategies apart from ensuring the availability of feedstock during all seasons. During the current field investigations covering 24 months, 25 seaweed species belonging to 19 genera were recorded from intertidal zone. Among these, eight seaweed species abundantly grows during post-monsoon season in the Central West Coast. These species include Enteromorpha intestinalis (938.5 g/m²), Ulva lactuca (1024.5 g/m²), Chaetomorpha media (441.8 g/m²), Gracilaria corticata (1039.5 g/m²₎, Gelidium pusillum (205.4 g/m²), Grateloupia lithophila (196.6 g/m²), Sargassum ilcifolium (1175.7 g/m²) and Padina tetrastromatica (1506.7 g/m²), which were considered for further analysis of biochemical composition (Fig. 5). It was seen that green seaweeds; U.lactuca and E.intestinalis, and red seaweed G.corticata occurred in sufficient quantity during all seasons. Occurrence of Ulva and Enteromorpha in all the seasons is attributed to their euryhaline nature, whereas G.corticata species are strictly marine and are restricted to open ocean environment [153]. Year round optimal biomass production of these macroalgal species, overcomes the seasonal constraints faced by the first and second generation biofuel feedstock [45].

3.1.2 Biochemical Composition of selected seaweeds

Macroalgal species with the higher quantum of sugar plays an important role as the composition of sugar influences the ethanol yield. Biochemical composition of chosen macroalgae were carried out focusing mainly on higher carbohydrate content which is an essential parameter for prioritizing feedstock for bioethanol production (Table 5). Algal biomass are composed of large quantities of carbohydrates in the cell wall mostly in the form of structural (cellulose) and storage (starch) polysaccharides, that serve as substrate for fermentation. Highest total carbohydrate was recorded from green seaweed Ulva lactuca (62.15±12.8 %) followed by G. lithophila (60.5±11.4%), G.pusilum (50.1±3.4%) and E.intestinalis (40.1±14.6%). Among these, G.lithophila and G.pusilum have lower biomass production as compared to Ulva and Enteromorpha, which makes them unsuitable as feedstock for biofuel production. Protein ranged from 3.7±0.94 to 27.3±15.21%. Highest protein content was recorded from C. media (27.3±15.21%) followed by E. intestinalis (20.4±0.67%) and U. lactuca (17.3±1.68%). In green seaweed Ulva, protein concentration ranged from 9 to 33%. Lowest protein recorded was from G. lithophila (3.7±0.94%). In general, protein fraction is lower in brown seaweeds (3-15% DW) compared to green or red seaweeds (10-47% DW) similar to the earlier report [154]. Lipid ranged from 0.5±0.2 to 6±4.4%. Highest lipid was estimated in U. lactuca (6±4.4%) followed by G. pusillum (3.7±1.4%), P. tetrastromatica (2.8±0.3%). Lowest lipid content estimated in G. corticata (0.5±0.2%). Transesterification of lipids extracted from Enteromorpha biomass yielded 90.6% biodiesel [135], which highlights that Enteromorpha as a promising feedstock for biodiesel production.

Elemental analysis of the seaweeds indicates 25.31-37.95% of carbon, 4.52-6.48% hydrogen and 1.88-4.36% Nitrogen. Highest carbon, hydrogen and nitrogen content were recorded respectively from G.pusillum (C: 37.95%), G.pusillum (H: 6.48%) and E.intestinalis (N: 4.36%) respectively. Higher cellulose content was estimated in U.lactuca (14.03±0.14%), followed by E.intestinalis (12.10±0.53%) and C.media (10.53±0.17%) least cellulose content was estimated in G. corticata (0.87±0.07%). Cellulose is a glucan present in green seaweeds, which can be easily hydrolysed by using enzyme and subsequently fermented to produce bioethanol. Green seaweeds are rich in cellulose content (>10%) [37,89,105] when compared to red and brown seaweed (2-10%).

3.1.3 Reducing sugar extraction using pretreatment methods

Chosen seaweeds composed of all the three types of algae (green, red and brown) with varied amounts of sugar and the complexity of the seaweed is reflected between structural and carbohydrate components [105,155,156]. It is therefore important to carefully choose the pretreatment process based on the biomass and an appropriate efficient pretreatment process to achieve a high yield of sugar for low energy input. The reducing sugar was determined using various pretreatment method as shown in Fig. 5. Pretreatment using boiling water yielded very low reducing sugar and it was observed that red and brown algae formed gel during this pretreatment process due to the presence of sugars like Agar, Carrageenan and Alginate which possess hydrocolloid properties [70,157,158]. It is seen that, liquid hot water pretreatment releases most of oligosaccharides [159]. U. lactuca biomass was subjected to four different pretreatments namely; ethanol organ solvent, alkaline, liquid hot water and ionic liquid treatments. Organo solvent and liquid hot water treatment produced highest glucan recovery of 80.8 g/100g DW and 62.9 g/100g DW respectively [160]. Sonication pretreatment also yielded lower reducing sugar, since sonication is most commonly used in extraction of lipid from microalgae [161], highest fatty acid composition of C16:0 and C18:1 was achieved in Spirogyra sp. employing sonication as cell disruptions technique [40]. Higher reducing sugar was extracted from all types of seaweeds during the dilute acid pretreatment. Dilute acid reduces the degree of polymerization resulting in recovery of 80-90% of hemicellulose exposing cellulosic fraction accessible to enzyme digestion [162]. Pre-treated Palmaria palmata, a red alga was exposed to acid hydrolysis, generated 218 mg/g of reducing sugar [133] and Grateloupia lithophila gave 191 mg/g of reducing sugar in the current study. Hence, it is feasible to obtain fermentable sugars with lower inhibitor concentration using extremely lower acid concentration [163]. Benefits of treating biomass with extremely low acid concentration simplifies downstream process such as neutralization and waste treatment. Reducing sugar of 14.7 g/L was obtained from E.intestinalis by dilute acid concentration of

Fig. 5. Reducing sugar (mgg^-1) extracted using various pretreatment methods for selected seaweeds

Table 5 Biochemical composition (%) of seaweeds along Central West Coast of India
Seaweeds	Total carbohydrate	Soluble carbohydrate	Insoluble carbohydrate	Protein	Lipid	Cellulose	C	H	N
U.lactuca	62.15±12.8	5.5±0.07	56.5±12.7	17.3±1.68	6±4.4	14.03±0.14	25.31	5.44	2.61
E.intestinalis	40.1±14.6	7.5±0.02	32.5±14.5	20.4±0.67	2.8±0.1	12.10±0.53	33.00	6.44	4.36
C.media	25.5±11.2	5.3±0.02	20.1±11	27.3±15.21	0.6±0.01	10.53±0.17	30.14	5.31	3.28
G.corticata	28.2±11.1	13.4±0.01	14.7±11	14.4±1.33	0.5±0.2	0.87±0.07	26.46	5.01	1.89
G. pusillum	50.1±3.4	4.7±0.01	45.4±3.4	8±2.04	3.7±1.4	1.55±0.05	37.95	6.48	3.45
G. lithophila	60.5±11.4	14.8±0.01	45.7±11	3.7±0.94	2.4±1.3	6.23±0.16	29.60	6.15	2.52
S. ilcifolium	26.4±13.4	3.6±0.01	22.7±13	12.4±0.67	1.9±0.01	1.30±0.09	26.20	4.52	1.88
P.tetrastromatica	32.5±13.23	3.5±0.02	28.9±13.2	9.7±1.76	2.8±0.3	1.48±0.07	30.68	5.54	2.35

75 mM H₂SO₄ [120]. Sequential acid hydrolysis was carried out to concentrate the sugar: hydrolysate of first cycle was utilized as hydrolyzing liquid for the 2^nd cycle and up to 5^th cycle [117] and generated 72 g/L of reducing sugar at the end of 5^th cycle during 0.9N H₂SO₄ hydrolysis from the seaweed granules. However, loss of liquid volume encountered in the hydrolysate that is attributed to the sorption loss by residue. Pulverized wet biomass of Gelidium amansii, red seaweed was subjected to continuous acid hydrolysis which yielded higher galactose and lower inhibitor concentration than batch reactor [126].

Utilization of red and brown seaweeds biomass for bioethanol production can lead to debate on hydrocolloid versus fuel affecting the existing multibillion hydrocolloid industry [89]. Therefore, for further processes of detoxification, enzyme hydrolysis and fermentation, two seaweeds Ulva lactuca and Enteromorpha intestinalis were selected as both the species satisfy the criteria of potential feedstock for bioethanol production such as; annual availability, carbohydrate rich biomass, producing higher reducing sugar concentration, ease of harvest by mechanical means, amenable to transplanting and reproducing prolifically in given environment [89].

3.1.3.1 Detoxification of acid hydrolysate

Detoxification of inhibitors (HMF and LA) resulting from acid hydrolysis was carried out using activated charcoal [164], which removed 38.8% LA and 70.37% HMF. However activated charcoal also removed sugars 14.5% glucose and 20.3% galactose present in the hydrolysate [141]. In the current study, highest sugar removal of 63.5% and 52% was recorded from activated charcoal for U.lactuca and E.intestinalis acid hydrolysate respectively. Similarly, Ca(OH)₂ was used for neutralizing the hydrolysate, which led to gypsum (calcium sulphate) formation, which was removed through filtration [117] also calcium ions catalyzes alkaline degradation of mono-saccharides in the over liming process, resulting in removal of fermentable sugars [141]. Similar results were observed in the current study, where Ca (OH)₂ treatment removed sugar from U.lactuca (56.1%) and E.intestinalis (23.3%) acid hydrolysate. Least effect of sugar removal was recorded in Na₂CO₃ neutralization process (Table 6) U.lactuca (39.8%) and E.intestinalis (14.7%).

3.2 Enzyme hydrolysis

Enzyme hydrolysis of U.lactuca and E.intestinalis yielded lower reducing sugar, compared to pretreated biomass during the incubation period. In order to overcome recalcitrance in second generation feedstock, the biomass was pretreated prior to enzyme hydrolysis. The pretreatment removed the lignin and hemicellulose exposing the cellulose fibers for enzyme hydrolysis [64,66,99,165]. Pretreated biomass is then subjected to enzyme hydrolysis, where cellulase enzymes bind to cellulose and disintegrate it into simple sugars (glucose). Algal biomass in the current study was pretreated using dilute acid and then subjected to enzyme hydrolysis (Fig. 6a and 6b). Pre-treatment breaks down the crystalline cellulose structure, the major constituents in the biomass cell walls and maximize enzymatic conversion to reducing sugars [53,105,155,166]. Despite longer incubation period for sugar release, enzyme hydrolysis is widely preferred due to the absence of any inhibitors formation [70].

3.3 Bioethanol production from selected macroalgae

Production of bioethanol from carbohydrate rich biomass is economical and sustainable. However, investigations are focused on improving the yield of bioethanol from seaweeds using appropriate microorganisms that have capabilities to convert all sugars present in the seaweeds and achieve ethanol yield of 0.47 g/g reducing sugar [89,167,168]. SHF and SSF process was carried out for E.intestinalis and U.lactuca feedstock.

3.3.1 SHF and SSF

Macroalgal feedstock E.intestinalis (EI) and U.lactuca (UL) were pretreated using 0.7 N and 0.5 N H₂SO₄ respectively. Seaweed hydrolysate was neutralized and then subjected to fermentation using CY and TY strain and conversion efficiency calculated assuming the sugar available in the hydrolysate are fermentable (Table 7). Higher ethanol yield of 1.63 g and 25.8% efficiency was recorded for EITY combination, whereas ULCY produced lower ethanol yield of 0.37 g achieving 12.1% efficiency. Co-fermentation of E.intestinalis hydrolysate yielded 0.8g with 21.7% efficiency, whereas U.lactuca yielded 0.63 g/g achieving 20.4% efficiency [120]. Pretreated E.intestinalis to 75 mM H₂SO₄ and subjected to SHF and obtained ethanol of 8.6 g/L (0.86 g) achieving 30.5% efficiency at 48 h. At the end of fermentation 10 g/L of reducing sugar remained unutilized indicating presence of non-fermentable sugar not consumed by the yeast S.cerevisiae. U.fasciata enzyme hydrolysate was subjected to fermentation and 1.28 g of ethanol yield was produced achieving 88.27% efficiency indicating higher reducing sugar conversion efficiency and ethanol yield than those reported for red and brown seaweeds [169].

SSF of E.intestinalis produced 7.6 g/L with 26.9% efficiency, lower yield was attributed to the suboptimal temperature of 32^oC which is unsuitable for enzyme hydrolysis [120]. In this study, SSF process (Table 8) produced higher efficiency when compared to SHF.

Table 6 Comparison of reducing sugar removal after neutralization process
	Ulva lactuca			Enteromorpha intestinalis
	Before treatment (mg/g)	After treatment (mg/g)	% Sugar removal	Before treatment (mg/g)	After treatment (mg/g)	% Sugar removal
Na2CO3	206.34	124.12	39.8	201.09	171.53	14.7
NaOH		113.78	44.9		153.88	23.5
Activated Charcoal		75.29	63.5		96.50	52.0
Ca(OH)2		90.51	56.1		154.18	23.3

Fig. 6a. Enzyme hydrolysis for direct biomass (DB) and acid pretreated biomass (PB) for E.intestinalis

Fig. 6b. Enzyme hydrolysis for direct biomass (DB) and acid pretreated biomass (PB) for U.lactuca

Table 7 Fermentation of macroalgal feedstock by the process of separate hydrolysis and fermentation (SHF) and Separate hydrolysis and Co-fermentation (SHCF)
Macroalgal feedstock	Process	Combinations	Biomass (g) DW	Initial sugar (g)	Final sugar (g)	Fermented sugar (g)	Ethanol yield (g)	Theoretical yield	Efficiency (%)
Enteromorpha intestinalis	SHF	EICY	50	22.5	10.71	11.79	1.40	6.01	23.4
		EITY			10.13	12.37	1.63	6.31	25.8
	SHCF	EITYCY			15.09	7.41	0.82	3.78	21.7
Ulva lactuca	SHF	ULCY		19.2	13.17	6.03	0.37	3.07	12.1
		ULTY			12.72	6.48	0.52	3.31	15.6
	SHCF	ULTYCY			13.10	6.10	0.63	3.11	20.4
CY: Cashew yeast; TY: Toddy yeast

Table 8 Fermentation of macroalgal feedstock by the process of Simultaneous Saccharification and Fermentation (SSF) and Simultaneous Saccharification and Co-fermentation
Macroalgal feedstock	Process	Combination	Biomass (g) DW	Cellulose (g)	Final sugar (g)	Fermented sugar (g)	Ethanol yield (g)	Theoretical yield	Efficiency (%)
Enteromorpha intestinalis	SSF	EICY	20	1.8	0.34	1.46	0.25	0.74	33.3
		EITY			0.56	1.24	0.49	0.63	77.4
	SSCF	EITYCY			0.52	1.28	0.27	0.65	41.8
Ulva lactuca	SSF	ULCY		1.7	0.54	1.16	0.33	0.59	54.9
		ULTY			0.54	1.16	0.39	0.59	65.5
	SSCF	ULTYCY			0.66	1.04	0.60	0.53	113.0
CY: Cashew yeast; TY: Toddy yeast

The combination of EITY produced higher ethanol yield of 0.49g/g achieving 77.4% efficiency. Simultaneous saccharification and co-fermentation (SSCF) of E. intestinalis produced 0.27 g/g of ethanol with 41.8% efficiency whereas U.lactuca produced efficiency of 113 % indicating fermentation of sugars other than glucan. Candida shehatea, Scheffersomyces stipitis (Pichia stipitis), and Pacchysolen tannophilus are the most promising yeast species for conversion of Xylose [112], which can be used in combination with S.cerevisiae in SSCF process to obtain higher ethanol yield. [104] subjected cellulosic residue of Kappaphycus alvarezii along with galactose synthetic medium to SSCF using single strain S.cerevisiae CBS1782 and recorded 64.3 g/L of ethanol indicating utilization of galactose sugar along with glucose. Co-fermentation of corn stover using S.cerevisiae and commercial strain TMB3400 yielded 40g/L or ethanol with 59% theoretical efficiency [74]. S.cerevisiae and S. stipitis were used for SSCF of Rice straw and produced 15.2g/L of ethanol [170].

Seaweeds contain low amounts of polysaccharides composed of glucose. Production of ethanol, therefore, needs to be from carbohydrates including sulfated polysaccharides, sugar acids and sugar alcohols. However, inability of microorganisms in fermenting all sugars present in seaweeds into ethanol is a major drawback. Therefore, isolation of yeast strains to ferment both pentose (C5) and hexose (C6) sugars are vital for achieving higher ethanol yield.

However, recent studies are focusing on non-controversial cellulosic residue following extraction of hydrocolloid from seaweed biomass [60]. But the lower cellulose content of residue prevents it from being a viable feedstock option considering the emergent demand for bioethanol. This necessitates the selection of seaweed species with higher cellulose content together with higher growth rate for sustainable bioethanol production [89,171]. Red algae has more agar and carrageenan and brown algae has more algin and lower cellulose compared to green seaweeds, that have cellulose making up to 70% of their dry weight (as Cladophorales and Ulvales) [176].

It is evident from the experimental results, that green algae are apt as potential feedstock due to higher carbohydrate and cellulose contents. Higher growth rates have been recorded for green seaweeds ranging from 19.15-24.25% when compared to red macroalgae (3-8%) [89,177,178]. Green seaweeds have production potential that is 2-20 times that of conventional terrestrial energy crops [179]. Red and brown seaweed’s lower cellulose content of residue and lower growth rate prevents it from being a viable feedstock to meet the growing demand for bioethanol. Comparison of ethanol yield from other potential macroalgal feedstock are represented in Table 9

3.3.2 Multivariate analysis of process condition for bioethanol production

Downstream process of bioethanol production from macroalgal biomass is dependent on various factors such as dilute acid pretreatment conditions (acid concentration, temperature, incubation time), enzyme hydrolysis conditions (pH, temperature and incubation time), reducing sugar and fermentation conditions (temperature and incubation time). In order to understand influence of each of these factors in ethanol production, multivariate regression analysis (Table 10) was performed and the probable relationship is given by the equation 2. Overall this model explains 97.3% variation in the data.

Table 9 Comparison of reducing sugar, ethanol yield and percent theoretical yield from various macroalgal biomass
Seaweed species			Reducing sugar g/l		Ethanol yield g/g	%Theoretical yield	References
Green Seaweeds	Chaetomorpha media		27.79		0.057	10.15	*
	Ulva fasciata		21.82		0.43	83.66	[89]
	Ulva lactuca		1.12		0.39	77.03	[94]
	Ulva lactuca		35.43		0.23	45.62	*
	Ulva pertusa		43		0.43	84.36	[70]
	Ulva pertusa		26		0.48	93.51	[97]
	Enteromorpha intestinalis		48.96		0.25	49.37	*
	Enteromorpha intestinalis		45.56		0.21	41.74	[120]
Red Seaweeds	Gelidium elegans		49		0.38	73.63	[70]
	Gelidium amansii		43.5		0.47	92.40	[108]
			42.2		0.38	74.51	[126]
			7.93		0.42	82.34	[172]
			7.93		0.48	93.46
	Gracilaria verrucosa		34.63		0.43	84.31	[60]
			19.70		0.43	84.31	[110]
	Gracilaria corticata		57.90		0.01	0.98	*
	Gracilaria salicornia		13.8		0.079	15.49	[173]
	Gracilaria sp.		11.46		0.42	82.35	[132]
	Grateloupia lithophila		44.45		0.09	17.85	*
	Gelidium pusillum		36.96		0.04	8.49	*
	Eucheuma cottonii (Kappaphycus alvarezii)		11		0.45	89.13	[88]
			81		0.45	88.24	[104]
			20.4		0.21	41.18	[164]
			51.9		0.42	82.36	[117]
	Palmaria palmata		21.84		0.173	33.92	[133]
Brown Seaweeds	Alaria crassifolia		67.20		0.38	74.40	[70]
	Laminaria hyperborea		30		0.43	84.31	[114]
	Padina tetrastromatica		17.9		0.01	2.53	*
	Sargassum sagamianum		25.9		0.386	75.69	[116]
	Sargassum sagamianum		2.55		0.89	174.55	[174]
	Sargassum sagamianum		19.8		0.35	69.32	[125]
	Sargassum ilcifolium		27.04		0.05	9.60	*
	Sargassum fluvellum		9.6				[54]
	Saccharina japonica		6.72		0.343	67.25	[163]
	Saccharina japonica		34		0.41	80.74	[103]
	Saccharina japonica		45.6		0.17	33.11	[52]
	Saccharina japonica		75		0.34	67.45	[116]
	Saccharina latissima		35		0.45	88.24	[36]
	Undaria pinnatifida		42.9		0.22	43.05	[120]
	Undaria pinnatifida		20		0.144	28.24	[107]
Seagrass	Zosteria marina	92		0.059		11.5	[175]
*Current work

Table 10 Coefficients and SE values of multivariate regression analysis
Process	Process condition	Coefficients	Standard Error
Dilute acid pretreatment	Concentration	-4.09	1.14
	Temperature	0.12	0.29
	Incubation Time	-0.13	0.67
Enzyme hydrolysis	pH	10.61*	2.44*
	Temperature	-0.31	0.16
	Incubation Time	-0.04	0.02
	Reducing sugar	0.32*	0.04*
Fermentation process	Temperature	-1.23	2.09
	Incubation Time	-0.12*	0.02*
*p<0.05

Y=-2.75- 4.09 (X₁) + 0.12 (X₂) - 0.13 (X₃) + 10.61 (X₄) - 0.31 (X₅) - 0.04 (X₆) + 0.32 (X₇) - 1.23 (X₈) - 0.12 (X₉)……………….. (Eq. 2)

Where,

Y: Ethanol g/L, X₁: Acid concentration (mM), X₂: Acid hydrolysis Temperature (^oC), X₃: Acid hydrolysis incubation time (min), X₄: buffer pH, X₅: Enzyme hydrolysis temperature (^oC), X₆: Enzyme hydrolysis incubation time (h), X₇: Reducing sugar in (g/L), X₈: Fermentation temperature (^oC), X₉: Fermentation time (h)

This analysis highlights that process conditions such as; acid pretreatment temperature, buffer pH and reducing sugar concentration affects the ethanol yield (Eq. 2). The increase in hydrolysis temperature during acid catalyzed reaction would also enhance the sugar production and decomposition [180,181]. Pretreatment temperature plays a vital role in sugar release as higher temperatures often leads to the formation of inhibitor, which is detrimental to the fermentative microorganisms leading to reduced ethanol yields [69,181]. Enzymes consists of ionic groups on their active sites which varies along with the pH resulting in changes in the activity of the enzyme, its structure, reaction rate and the product formation [182]. Therefore, pH of the reaction medium or buffer needs to be optimum for higher enzyme activity [183,184]. Fermentation process is slower in low sugar medium, whereas the process increases in the medium containing 15-20 g/L of sugar and remains stable up to 200 g/L. Medium with 200 g/L to 300 g/L of sugar concentration lowers the growth of yeast microorganisms [185–187]. However, higher concentration of fermentable sugars yield higher ethanol, whereas non-fermentable sugars (pentose) can affect the fermentation yield due to lack of transport system in yeasts.

4. Scope and opportunities for macroalgal cultivation

Macroalgal cultivation can be attempted in India by taking the advantage of 2.172 million km² exclusive economic zone (including Andaman and Nicobar islands) as well as abandoned aquaculture ponds. Aghanashini estuary (Lat 14.391° to 14.585° N; Long 74.304° to 74.516° E) situated in Kumta taluk, Karnataka consists of such aquaculture ponds called gazni, which serves as potential site (Fig. 7) for macroalgal cultivation [134]. U.lactuca and E.intestinalis abundantly grows in this estuary during all the season and E.intestinalis naturally occurring in gazni ponds are mostly discarded as waste. Ulva and Enteromorpha genus possess a blade-like or filamentous morphology, which can tolerate wide range of environmental conditions such as temperature upto 40 ^oC [51] and tolerate salinities in the range of 10-60 ppt [188] and resulting in higher [135].

The spatial extent of gazani lands in Aghanashini estuary (Fig. 7) is about 2000 ha (much of it not being used for rice cultivation now) and area of 1000 ha could be considered for algal cultivation during the late monsoon months and subsequently, these lands may be used for shrimp culturing or utilized for other forms of fisheries. The algal production happens indeed without any external input of nutrients, and therefore the gaznis hold very good potential for ethanol production, prior to the commencement of fishery operations, and before salinity rises substantially with the cessation of the rainy season. The algal harvests can be effectively made from any gazni at biweekly intervals, two weeks’ time considered fairly good for harvestable regrowth. It means effectively 1000 ha area are available for algal harvests every week. The lean season for fishery (of prawns and fish mainly) alone needs to be utilized for this purpose, so that prospects for ethanol production, by no means, could come in the way of food production. These 1000 ha of aquaculture areas could be effectively available for algal harvests during the off-season, which might benefit about 2500 small farmers, who were once rice cultivators, who had permitted their erstwhile fields to be converted into shrimp farms, which are not in suitable condition for reintroduction of rice without making substantial structural changes. These gazni lands also exhibit positive correlation with water temperature, air and salinity which influences the growth of diatoms such as Pleurosigma balticum, Melosira sp., Nitzschia sigma and Nitzchia spp. that are potential candidates for biodiesel production [189].

Fig. 7. Potential sites for macroalgal cultivation in Aghanashini Estuary

Cultivation of Ulva and Enteromorpha is estimated to produce annual biomass of 45 t/ha [179] and 100 t/ha [51] respectively, which is 2-20 times the production potential of first and second generation feedstock and 3 times the production of brown algae in temperate waters [179]. Commercial cultivation of these seaweeds largely focuses on high-value food (aonori) and aquaculture feed production. Ammonium are abundantly present in aquaculture effluent, which is readily assimilated by Enteromorpha and Ulva in the range of 50-90 µmol N/g DW h, which makes it feasible to cultivate these algae in aquaculture effluents qualifying as species for bioremediation process [190,191]. However, sporadic sporulation of Ulva leads to loss of biomass due to which attempts of cultivating at large scale has failed, also environmental factors responsible for these sporulation have not yet been completely explored [190]. This can be overcome by technique [135], involving artificial seeding under controlled conditions. This allows control over higher seeding density and consequently biomass production. Seeding density of 621,000 swarmers/m and nursery period of five days were quantified as key factors affecting the growth and biomass yield of Ulva sp. This study also highlights the shorter nursery period and culture cycles required for green seaweeds when compared to red and brown seaweeds.

Large-scale cultivation of macroalgae in open ocean eliminates the need for external inputs such as CO₂ cylinders, monitoring of temperature or pH alteration. However in controlled conditions, all these parameters play a crucial role in sustaining biomass productivity. Algae acquire carbon in the form of CO₂ or bicarbonates, at pH 8, seawater has alkalinity of 2.3 meq which allows only 0.5 mM of CO₂ or 6 mg/l of C to be absorbed from the seawater. In order to increase the level of CO₂ absorption pH needs to be increased to nearly 9 which is not feasible as it slows down the photosynthesis [192].In a study [193], brown seaweeds (Sargassum sp.) were cultivated at different pH and temperature and was observed that higher biomass productivity obtained at ambient pH of 7-8.2, indicating that low pH values affected the growth of the algae.

The seaweed industry in India is still at infancy, functioning more like a cottage industry. Seaweeds are collected from the natural stock mainly for the production of agar without any regulations [194]. Macroalgal biomass in addition to being potential feedstock for bioethanol production, also serves as a good food supplement. Enteromorpha was tested as nutritional supplement in preparation of Indian snacks, which resulted in higher iron and calcium content along with increase in proteins, vitamins and dietary fibres [195]. Macroalgal protein, dietary fibres and phytochemicals are utilized in order to enhance the nutritional quality of the food products. Complete utilization of macroalgal biomass into producing biofuel and value added products has potential to ensure India’s energy and food security [134]. The study presents the scope to utilize macroalgal biomass in producing value added products in addition to bioethanol production, bringing resilience to the Industry and improving their economics and usefulness. Prospects of bioethanol with the value added products would support the livelihood of rural population, while aiding as the potential feedstock for biorefinery [36,196].