Protein potential of Desmodesmus asymmetricus grown in greenhouse as an alternative food source for aquaculture

During ten months, batch culture of Desmodesmus asymmetricus microalgae was carried out under greenhouse conditions. The inoculation ratio was 1:1 (inoculum:treated water). The cultures were maintained for 5 days with natural light and constant aeration mixed with carbon dioxide. The biomass was concentrated by centrifugation and dried by lyophilization; subsequently, total proteins and amino acid concentration were quantified. A relationship between biomass production and seasonal variation was observed, the lowest dry biomass production was recorded in June (38.8 ± 1.0 mg L−1 day−1) and July (43.3 ± 0.1 mg L−1 day−1); while the highest values were greater than 70 mg L−1 day−1 in March. There was a high positive correlation between wet and dry biomass (r = 0.97, p < 0.001) with a mean conversion of 26%. The mean percentage of protein was 26.1 ± 2.6%, the highest percentage was registered in March (31.03 ± 1.48%) as well as the concentration of amino acids. Regarding amino acids, arginine obtained the highest concentration (4.08 ± 0.43 g 100 g−1), followed by aspartic acid (3.36 ± 0.23 g 100 g−1), while the lowest values were for methionine (0.55 ± 0.21 g 100 g−1), histidine (0.77 ± 0.07 g 100 g−1) and tyrosine (1.01 ± 0.17 g 100 g−1). Finally, according to the essential amino acid index (in fish ≥ 0.90, in crustaceans > 0.80), the biomass of D. asymmetricus has potential as a food supplement for the production of feed in aquaculture.


Introduction
Microalgae are photosynthetic microorganisms, whose size are between 2-200 µm, and they can grow autotrophically or heterotrophically. There are many types of organization: unicellular, filamentous or colonial. Cells can have external structures such as membranes, cell walls or silica exoskeletons (Randrianarison and Aqeel Ashraf 2017). They are the simplest organisms in the plant kingdom with a great capacity to adapt to different environments, they use light energy and fix carbon dioxide (CO 2 ) more efficiently than higher plants; in addition, they promote greater CO 2 fixation in symbiotic systems (heterotrophic/nitrifying bacteria consortium) and an efficient treatment for the nutrient removal, thus producing high amounts of microalgal biomass (Christaki et al. 2011;Gaignard et al. 2018;Sepehri et al. 2020). Currently, there are 100,000 identified species (Guiry et al. 2014) and distributed worldwide in practically all environments (Posten and Feng 2016;Geada et al. 2017).
The first records about the use of microalgae as food date back 2000 years, when Chinese used the Nostoc genus to survive during famine. Another reference about the application of microalgae in nutrition was associated with the treatment of patients with leprosy, who were fed with a soup enriched with Chlorella sp. and they were observed to have an increase in their weight, energy, and general health (Milledge 2011;Sigamani et al. 2016). The development of the culture of microalgae began in Japan as a solution to the food shortage caused by World War II, consequently, microalgae-based enriched products began to be developed. Thenceforth, many studies related to biomass production have focused on obtaining biofuels, wastewater treatment and as a protein-rich food source for human and animal consumption, mainly for aquaculture (Spolaore et al. 2006;Christaki et al. 2011;Yaakob et al. 2014;García et al. 2017;Koyande et al. 2019).
Several studies have shown that microalgae are an attractive source of metabolites, such as polyunsaturated fatty acids (PUFA), carotenoids, phycobilins, peptides and polysaccharides. as well as being a good source of vitamins A, B1, B2 and B12 (Skjånes et al. 2013;De Morais et al. 2015). Currently, several products are marketed in the form of tablets, powder, solution or in mixtures with snacks, cookies, noodles, drinks, candies, gums, wines and cereals (Sathasivam et al. 2019;Levasseur et al. 2020). The main countries that lead the world production are China, India, Taiwan, Germany and a few countries in Latin America (Koyande et al. 2019;Levasseur et al. 2020).
There are two well-known genus: Arthospira (commercially known as Spirulina) and Chlorella, which have reached productions of 12,000 and 5000 tons per year, respectively. In the last decades, many researchers have focused their studies on the biomass production of other species such as Haematococcus, Dunaliella, Botryococcus, Phaeodactylum, Porphyridium, Chaetoceros, Crypthecodinium, Isochrysis, Nannochloris, Nitzschia, Schizochytrium, Tetraselmis and Skeletonema. (Plaza et al. 2009;Matos et al. 2017;Sathasivam et al. 2019;Levasseur et al. 2020). Despite this, the percentage that has been studied is still small compared to all the potential species worldwide. Likewise, there is still little research on the development of organoleptically acceptable products, their compounds, benefits, isolation techniques, performance improvement, determination of their bioactivity and toxicity (Stengel et al. 2011;Buono et al. 2014;Levasseur et al. 2020).
In aquaculture, the protein supplied in feed comes mainly from fishmeal. This ingredient is expensive because it comes from the production of fisheries and its high demand worldwide (Amaya et al. 2007;FAO 2018FAO , 2020. As an alternative solution, new commodity markets have been developed such as high-quality processed animal by-products (hydrolyzed feather meal, blood meal, meat and bone meal), vegetables flour, protein concentrates obtained from oilseeds and legume grains. Similarly, it is known that in salmonid farming, fish oil in feed has been replaced by other fats of animal and vegetable origin, although these "second generation" ingredients are not without limitations (Hua et al. 2019).
This sector needs to grow; therefore, several institutions have begun to investigate the use of "third generation ingredients", which is defined as ingredients that come from lower trophic levels (Shah et al. 2018;Glencross et al. 2020). In this way, microalgae biorefineries emerge as an option, furthermore, there is an advantage for the reuse of industrial emissions, since their waste "outputs" (CO 2 , nutrients, heat) turn out to be the essential "inputs" for the cultivation of microalgae, which would allow rapid cell growth and a greater accumulation of biomass. Ingredients produced from microalgae as aquafeeds could have competitive advantages over land crops, for example in terms of input costs, smaller cultivation area and carbon credits from CO 2 conversion (Roy and Pal 2014;Allen et al. 2019;Perez-Velazquez et al. 2019;Levasseur et al. 2020).
In Peru, there is a need to carry out biotechnology studies on native microalgae because they are scarce. In this way, its potential could be explored in different industries, for example, in the aquaculture, cosmetic, food, pharmaceutical, renewable energy, etc. For this reason, the objective of this study was to evaluate the cultivation of the native microalgae Desmodesmus asymmetricus under greenhouse conditions to determine biomass production values, protein and amino acid concentrations, as well as its potential as an ingredient for the aquaculture industry.

Culture of microalgae
The culture of the microalgae D. assymetricus was carried out in batch mode. The strain code of the Banco de Germoplasma de Organismos Acuáticos (Instituto del Mar del Perú-IMARPE) is IMP-BG-249. The inoculum in exponential phase (∼1.0 ± 0.5 × 10 6 cells mL −1 ) was obtained from Laboratorio de Alimento Vivo (IMARPE). The microalgae were cultivated in vertical tubular bioreactors of 30 L at Laboratorio de Invernadero y Sala de procesos (IMARPE), according to the procedure manual described by Oscanoa et al. (2018). It was considered to have a number of bioreactors necessary to reach 900 L of harvest. The inoculation ratio was 1:1 (microalgal inoculum:treated freshwater); freshwater was filtered with 10, 5 and 1 µm cartridges and irradiated with ultraviolet light. The culture medium used was liquid foliar fertilizer Bayfolan®, dose of 0.28 mL L −1 (Morales-Ventura et al. 2012;Fernandez-Linares et al. 2019). Constant aeration mixed with 0.5 mL L −1 CO 2 flow were supplied. The conditions of cultures were natural light, pH 7.02 ± 0.53, dissolved oxygen 8.62 ± 0.42 mg L −1 and salinity 0.36 ± 0.15 ppm.

Monitoring of abiotic parameters
Microalgae culture was conducted from January to October 2018, whose seasons are distributed as follows: summer (January, February, March), autumn (April, May), winter (June, July, August, September) and spring (October, November, December). The cultures were kept for 5 days. A weekly harvest was carried out.

Biomass Production
The cultures were harvested in 500 L tanks and concentrated by means of centrifugation method. For this, a Westfalia semi-industrial separator (OTC3, Oelde, Germany) was used at 10,000 rpm and output flow between 120-200 L h −1 . The samples were placed in steel trays, they were spread in layers of 1 cm maximum thickness and were frozen (-20 °C) and stored for later drying. The harvest cell density (HCD) and the wet biomass production (WBP) were determined in this stage.
Subsequently, the biomass obtained was dried in a Labconco lyophilizer (18L, Kansas, USA) at a vacuum pressure between 0.022-0.070 mbar. The collector temperature was -56 °C. The biomass was dried using the following temperature ramp: -15 °C for 8 h; then 0.5 °C min −1 to 5 °C for 15 h; finally, 0.5 °C min −1 until 25 °C for 7 h. The samples were withdrawn and homogenized in a mortar until the pulverized dry biomass was obtained. The dry biomass production (DBP) was determined considering the concentration of dry biomass (mg L −1 ) divided by the time of cultivation (days). The percentage of conversion from wet to dry biomass (%WB/DB) was determined. The chemical analyzes of the samples were carried out in the Laboratorio de Análisis Instrumental (IMARPE).

Protein content and amino acid profile
The percentage of protein was estimated according to the method of Hartree (1972), which consists of extracting proteins from 5 mg of biomass by adding a solution of sodium carbonate, sodium and potassium tartrate, copper sulfate and reagent of Folin-Ciocalteau to produce a blue-colored complex and compare it to a bovine serum albumin (BSA) standard for quantification, by UV spectrophotometry at a wavelength of 650 nm.
Concerning to determination of the amino acid profile, 30 mg of dry biomass of the microalgae were mixed with 2 mL of 6 M hydrochloric acid and incubated in a dry bath at 112 °C during 22 h for the acid hydrolysis reaction (Hirs et al. 1954). Then, 50 μL of the hydrolyzed sample was transferred to a test tube to which 100 μL of 2.5 mM L-aminobutyric acid (internal standard) and 4850 μL of ultrapure water were added. The solution was filtered on a 0.45 μm PTFE syringe filter and 10 μL of the filtrate was derivatized, using the 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate reagent (Cohen and Michaud 1993) following the instructions of the AccQ-Fluor reagent kit (Waters Corporation, Milford, MA, USA). Next, 5 μL of the derivatized amino acid solution was injected into the Hitachi Elite LaChrom HPLC (Hitachi High Technologies, Tokyo, Japan), equipped with an L-2200 autosampler, L-2130 HTA pump, L-2350 column oven and fluorescence detector L-2485. A Thermo Scientific™ Hypersil GOLD™ C18 column of 150 mm × 4.6 mm × 5 µm (Thermo Fisher Scientific, Walthman, MA, USA) was used. The HPLC equipment was programmed to operate with the following conditions: column temperature 37 °C, excitation wavelength 250 nm, emission wavelength 395 nm, flow rate 1 mL min −1 . The mobile phases were as follows: (A) 140 mM sodium acetate pH 5.1 and (B) Acetonitrile with the following gradient: 0-2 min, 100% A; 2-24 min, 100-83.5% A; 24-30 min, 83.5-75% A; 30.1-38 min 100% A. Finally, the data acquisition and analysis were performed with the EZChrom Elite v3.2.1 software (Agilent Technologies, Santa Clara, CA, USA). The tryptophan (Trp) and cysteine (Cys) amino acids were not identified by the applied analytical technique.
Once the amino acid values were determined, the chemical score and the essential amino acid index (EAAI) were estimated. The chemical score was calculated as the ratio of the value of each essential amino acid (EAA) of the microalgal sample with the value of the corresponding amino acid of a standard protein as described by Peñaflorida (1989). In the event that the chemical score was greater than 1, this value was approximated as 1. The EAA requirements from standard protein used in this study is shown in Table 1. The EAAI evaluates the degree of EAA of the whole sample in relation to the composition or requirements of EAA of the organism (Ju et al. 2008;Zhang et al. 2009). The formula proposed by Peñaflorida (1989) was used to calculate the EAAI (Eq. 1), where: aa i = percentage of EAAi in the total of EAA of the sample, AA i = percentage of EAAi in the total EAA in the standard and n = quantity of essential amino acids determined.

Statistical analysis
The Pearson correlation index (r) was calculated to determine the correlation between the variables. The data from the mean comparisons were analyzed by analysis of variance (ANOVA) with a significance level of 0.05 and the Tukey post-hoc test. The Kruskal Wallis test was applied for the data that did not meet the ANOVA assumptions. Finally, in order to know the interrelationships between the factors analyzed (abiotic parameters and amino acid profile), the Principal Component Analysis-PCA was applied. The

Abiotic parameters
A moderate positive correlation was observed between IL-GT and PAR-GT, while a high correlation between PAR-IL and PAR-CT (Fig. 1). The highest temperature inside greenhouse (GT) was above 26 °C during January and February while the lowest temperature was 19 °C during June and July (Fig. 1A). The GT for these last months were significantly lower compared to the other months evaluated (p = 1.000). The CT values were between 26-28 °C in warm seasons and ∼20 °C in cold seasons (Fig. 1D). The highest IL average was obtained in March (221 ± 137 Klux) with significant differences compared to June (p < 0.001) (Fig. 1A); in the same way with PAR, the highest average was obtained in March (336 ± 162 µmol m −2 s −1 ) with significant differences compared to June (p < 0.001) (Fig. 1B). When graphing PAR with GT, the same trend is also observed (Fig. 1C).

Biomass production
The total culture volume produced in ten months was 31,370 L, which represented a final production of 45 kg of wet biomass and 10 kg of dry biomass. The lowest dry biomass production (DBP) was recorded during the months with the lowest temperature: June (38.8 ± 1.0 mg L −1 day −1 ) and July (43.3 ± 0.1 mg L −1 day −1 ); in addition, no significant differences were obtained between them (p = 0.999). While the highest values of DBP were obtained in months of warm temperatures, whose values were higher than 70 mg L −1 day −1 (Fig. 2). A moderate positive correlation was observed between DBP -IL (r = 0.845, p = 0.002); while, there is a high correlation between DBP with PAR and CT (r = 0.920, p < 0.005; r = 0.937, p < 0.005 respectively).
There was a high correlation between the dry and wet biomass weight (r = 0.971, p < 0.010), with an average conversion of 26% (Fig. 3).

Proteins
According to our results, the mean protein percentage of the 10 months of culture was 26.1 ± 2.6% (Fig. 4), its highest value was obtained in March (31.03 ± 1.48%) with significant differences compared to April, May and July (p = 0.001).
Apparently, according to Fig. 5, there would be a direct relationship between WBP and total protein concentration, however, when performing a correlation between the variables, a low relationship was found. In the same way, it happened with CT (r = 0.433, p = 0.211) and PAR (r = 0.521, p = 0.122), only a significant direct correlation was observed with IL (r = 0.796, p = 0.026). However, when the outlier corresponding to June was eliminated a significant positive correlation was obtained between the mean percentage of proteins and DBP (r = 0.832, p < 0.001).

Amino acids profile
The highest concentration of amino acids was recorded in March (Z = 2.84) (Fig. 6). Arginine (Arg) was the amino acid with the highest concentration (4.08 ± 0.43 g 100 g −1 ), followed by aspartic acid (Asp) (3.36 ± 0.23 g 100 g −1 ), in contrast to methionine (Met) (0.55 ± 0.21 g 100 g −1 ), histidine (His) (0.77 ± 0.07 g 100 g −1 ) and tyrosine (Tyr) (1.01 ± 0.17 g 100 g −1 ) (p < 0.001), which were the lowest concentration. The final average of all amino acids is shown in Table 3. In our study, the chemical score was determined for different species (Table 2), it was observed that for fish the lowest value was > 0.70, while the limiting amino acid for P. vannamei was isoleucine (chemical score = 0.57).
Concerning the EAAI, the highest value was for P. maxima (0.92) and the lowest value was for P. vannamei (0.85).

Abiotic parameters
For the production of microalgae biomass, mainly for proteins, we should consider that the concentration of nutrients, composition of the culture medium, temperature and light are factors that influence the biochemical composition of biomass, as well as their interrelationships with other environmental parameters; therefore, these are parameters that should be optimized to improve biomass and protein production (Barbosa et al. 2003;Rasdi and Qin 2015;Khan et al. 2018;Sarker and Salam 2020). Light (Illuminance (IL) and PAR) is the source of energy to carry out photosynthesis, it mainly affects the growth and metabolism of microalgae. Temperature affects enzyme activity, nutritional requirements and gas solubility in cultures (Ras et al. 2013). For this reason, it is very important to know the optimal conditions and the tolerance limits of different parameters for each species (Ma et al. 2016, Jazzar et al. 2016. Illuminance values between 20-500 klx should be used for the light to be effective, while a range of 27-500 µmol m −2 s −1 should be considered for PAR (Singh and Singh 2015). In our study, the greenhouse cultures of D. asymmetricus remained within the average of these values. In addition, the temperature, illuminance and PAR showed the highest values in warm months and the lowest values in cold months. On the other hand, some species of microalgae resist wide pH ranges, such as the genus Chlorella and Desmodesmus. The optimal growth of microalgae under normal conditions occurs between pH of 7 to 9 (Park et al. 2011;Ma et al. 2014;Beltrán-Rocha et al. 2017;Morales et al. 2018). In our study, an adequate pH of 7.02 ± 0.53 was maintained. Most microalgal species survive under mesophilic temperature conditions (16-27 °C), a value > 35° C would cause a collapse in the microalgal growth (Ras et al. 2013; Hernández-Pérez and Labbé 2014; IMARPE 2018; Barten 2020). According to the latter, in the case of genus Desmodesmus, the culture temperature between 25-28 °C was adequate.

Biomass production
Seasonal variation throughout the year influences biomass production (Eustance et al. 2015;Janssen 2016). In winter, production decreases due to the low intensity of light and temperature, while in summer it increases (Pérez-López et al. 2017). Light intensity is necessary for photosynthesis, at low intensity the photosynthesis rate decreases because photochemical reactions are limited by the availability of light and the ability of cells to absorb them, which affects microalgal growth (Masojídek et al. 2013).
According to our results, DBP changes as a function of seasonal variations and it would be affected by CT and PAR, since there was a direct correlation between them. Authors such as Gomez et al. (2016) mentioned that the relationship between light intensity and photosynthesis rate are independent of temperature at low intensities (< 100 µmol m −2 s −1 ). It depends on the dark reactions of photosynthesis and the level of nutrients. The microalgae will grow slowly in low luminosity, but it will be more efficient at capturing light, despite of this energy will not be used properly. If the light intensity is high (> 200 µmol m −2 s −1 ), the development of microalgae will be limited by carbon fixation and the cells will use less of their own resources as in the synthesis of chlorophyll. Furthermore, Ras et al. (2013) indicate that the effect of temperature in the cultures responds constantly to the environmental temperature; therefore, the cell temperature will be equal to the temperature of the culture medium in comparison with other physicochemical parameters. In addition, the optimal temperature range has low influence on biomass production, in contrast to light (light intensity, photoperiod, wavelength, light source and photosynthetically active radiation) (Ma et al. 2016;Vecchi et al. 2020).

Proteins
Proteins were the first substances recognized as vital for all organisms, hence their name comes from the Greek word "protos" which means "of first importance" and they constitute one of the most abundant components of most living beings. Proteins are macromolecules constituted by hydrogen, carbon, oxygen and nitrogen; sometimes, it can include elements such as iron, cobalt or phosphorus. They are formed by a specific sequence of their own constituent elements: amino acids. There are 20 different amino acids that are linked through peptide bonds, all of them have an amino group (-NH 2 ) and a carboxyl group (-COOH) attached to the same carbon atom (alpha carbon) and differ in their side chains or R groups (Allison 2011).
In aquaculture, the evaluation of protein and amino acid requirements are important for the formulation of diets with greater efficiency and thus achieve sustainable aquaculture (Hua et al. 2019). An adequate intake of amino acids (from proteins) stimulates growth in fish. In addition, the  percentage of protein determines the production costs, mainly in the diet of marine fish, since they require high levels; for this reason, this compound is considered the most important for fish culture (Sanz 2000). The nutritional value of a protein source is a function of its digestibility and its amino acid profile (Trushenski et al. 2006). However, like other organisms, fish do not have a true requirement for protein, but have a specific requirement for a well-balanced profile of essential and nonessential amino acids in the diet (Gaye-Siessegger et al. 2007;De Almeida and Possebon 2014;Massamitu et al. 2015).
In fish farming, the protein requirement is influenced by the energy-protein balance, amino acid composition, digestibility of the diet, quantity of non-protein energy in the diet, muscle composition, blood histochemistry, intestinal health and gene expression (Glencross 2009;Conde-Sieira and Soengas 2017). The excess of energy in the diets can be a limit of consumption, since the fish ingest until they cover their energy requirements. Many authors affirm that there is a decrease in the protein requirement of fish as they increase their weight and age. Protein requirement can be altered due to a change in water temperature (Singh et al. 2009;Mizanur et al. 2014). Many studies report that salmonids can only tolerate low inclusion levels (< 10% of the diet) of microalgae meal such as Arthrospira, Chlorella, Entomoneis, Isochrysis, Nannochloropsis, Phaeodactylum and Tetraselmis. Also, there are some studies that indicate that the diet can be replaced up to 20% with a mixture of Scenedesmus/Chlamydomonas and Desmodesmus/Nanofrustulum (generally considered a benthic genus, however, they can be found in water columns) (FAO 2009;Walker and Berlinsky 2011;Tibbetts 2018). Table 3 shown a compilation of several investigations about the nutritional composition of different species of microalgae. The Scenedesmaceae family (genus Scenedesmus and Desmodesmus) has reported between 8-56% of dry weight protein, similar to our study (26.1 ± 2.6% of protein). On the other hand, genus such as Chlorella and Arthrospira obtained values between 67 and 73%, respectively (Tibbetts 2018;Batista et al. 2020;Colombo et al. 2020;Glencross et al. 2020;Raji et al. 2020). In the microalgae, the percentage of protein is dependent on the supplied nitrogen source; the protein decreases if the nitrogen concentration decreases in the medium and its assimilation is strongly dependent on light, it incorporates or reduces nutrients such as nitrate (NO 3 − ) through the regulation of the synthesis and activity of the enzyme nitrate reductase. Another form of assimilation and incorporation occurs when light supplies ATP through photophosphorylation. Another indirect pathway occurs through the photosynthetic production of carbon compounds to accept the reduced nitrogen. This last methodology is carried out According to our results, a significant direct correlation was observed between the percentage of total proteins and the illuminance (IL). In addition to the above, the intensity of light influences the biochemical composition of biomass due to the effect on photosynthesis, a high intensity of light produces stress in microalgae and increases storage compounds such as lipids, carbohydrates and carotenoids as a replacement for proteins (He et al. 2015;Nzayisenga et al. 2020;Sui et al. 2021). In June (atypical data respect to the percentage of proteins), probably the lower IL compared to the other months (94.5 ± 64.4 klux) has doubled the chlorophyll content, since the species of the genus Scenedesmus adapt their photosynthetic apparatus between 6 and 8 h of culture (Senge and Senger 1990;Singh and Singh 2015), as a consequence, they would fix more nitrogen by increasing the protein content (Evans 1989;Evans and Clarke 2019).

Amino acids profile
Amino acids are structural units of proteins, they are generally classified as: essential, non-essential and conditional, the latter has been proposed by some researchers in recent years (Li et al. 2009;Wu et al. 2014). A deficiency of amino acids results in inadequate use of the nutrients in the diet; therefore, there is low growth and low feeding efficiency in organisms (Kaushik and Seiliez 2010). Essential amino acids have carbon skeletons that are not synthesized by organisms or are synthesized in insufficient amounts; therefore, they must be provided from the diet. In contrast, non-essential amino acids are specific for each organism and they are synthesized de novo to satisfy their requirements (Wu 2010).
For many years, without much evidence, it was assumed that organisms (including humans) could synthesize sufficient amounts of all non-essential amino acids and that they were unnecessary in diets to achieve adequate growth or maintain good health. However, the increase in the number of investigations in various organisms has shown that some amino acids, traditionally classified as non-essential (glutamine, glutamic acid and arginine), play important roles in multiple cell signaling pathways, thus regulating gene expression, intracellular protein turnover, nutrient metabolism and oxidative immune defense. In addition, they can generate a benefit in the species of interest when it is supplied in adequate amounts in the diet (Li et al. 2009;Pianesso et al. 2015;Alagawany et al. 2020;Hoseini et al. 2020).
In fish farming, fish must be fed balanced levels of nutrients in their diets for successful aquaculture (Hixson 2014). The balance of proteins and amino acids is important to achieve optimal performance as in fish growth as in physiological and immune function (Hoseini et al. 2019). Amino acids are important molecules for living organisms with functions in protein and hormone synthesis, immune and antioxidant responses, and other physiological functions (Li et al. 2007;Wu 2009). A balanced amino acid profile in the diet is more important than protein levels in teleost diets, as each amino acid has some vital functions in the fish body (Wilson 2003;Andersen et al. 2016). Table 3 shows the analysis of amino acid profile of D. asymmetricus and the values were compared with other food sources such as: soy (Barka and Blecker 2016), egg (Christaki et al. 2011), Scenedesmus (Tibbetts 2018), Arthrospira (Kent et al. 2015;Tibbetts 2018) and Chlorella (Kent et al. 2015;Koyande et al. 2019), which shows that microalgae can produce the amino acids commonly found in proteins. In our results, the essential amino acids values were lower compared to other organisms. Highlights the value of arginine, which is in the average value of 4.1 ± 0.43 g 100 g −1 dry weight. Arginine is an essential amino acid in fish with different physiological roles in health and growth performance (Wilson 2003).
Several methods have been developed to evaluate the protein quality of a given product, due to its formulation depends on the type of organism and the feeding technique, as well as the amount of amino acids absorbed. According to De Bhowmick and Hayes (2022), protein quality is related to the composition and bioavailability of amino acids, which is directly proportional to the digestibility of ingested protein.
The most used methods to evaluate the protein quality of a product are amino acid score (AAS), essential amino acid index (EAAI), chemical score (CS), biological value (BV), protein digestibility (either in vitro or in vivo), net protein utilization (NPU), protein efficiency ratio (PER), protein digestibility corrected amino acid score (PDCAAS), and digestible indispensable amino acid index (DIAAS) (Wang et al. 2021). Despite the existence of updated and reliable indexes, the EAAI is still used as a reference index for the protein quality of the product (Acquah et al. 2020).
Concerning the EAAI, authors such as Oser 1959, Zhang et al. (2009) and Ju et al. (2008 proposed that values of EAAI > 0.95 in different organisms and a value close or equal to 1.0 for shrimp, indicate that the diet contains an amino acid profile similar to that found in the entire body of the organism. The ingredients with EAAI > 0.90 were considered good quality protein foods; EAAI equal 0.80 were considered as useful and values < 0.70 were inadequate. However, the characteristics of an ingredient to satisfy the amino acid requirements of an animal depends on the rate of consumption, bioavailability (digestibility) and composition (Li et al. 2010) because these characteristics change according to the interaction between the food and the organism that consumes it. Likewise, the values obtained from the chemical score indicate that foods with low EAA require the inclusion of nutrients, either by other sources of protein or synthetic amino acid supplements. In this way, it seeks to obtain a performance similar to a high-quality diet (Nunes et al. 2014).
The EAAI found for the different organisms was greater than 0.80, therefore, it was classified as a useful protein material according to Ju et al. (2008). The EAAI value was equal to the biofloc of bacteria reported by Ju et al. (2008) and it was close to the value of soybean meal (0.87) intended as food for Penaeus monodon (Peñaflorida, 1989). In our study, the EAAI result was within the range reported for different microalgae (marine and freshwater), which range from 0.76-1.00 (Kent et al. 2015;Tibbetts et al. 2018;Cobos et al. 2020). Hence, D. asymmetricus can be classified as a food with good quality proteins and useful for the growth of different aquatic organisms for example Peruvian grunt (Anisotremus scapularis), Fine flounder (Paralichthys adspersus), Streaked prochilod (Prochilodus lineatus) and shrimp (Penaeus vannamei).
According to Morançais et al. (2018) the temperature used in the culture system can influence its amino acids concentration. The PCA results showed a direct correlation between temperature (CT and IL) and the amino acids methionine and tyrosine. These results agree with those reported by James et al. (1989), who observed a similar behavior for Chlorella at temperatures between 25 and 30 °C. Likewise, Uslu et al. (2009) indicated similar results for these amino acids in a Spirulina species that was cultivated at different temperatures, in warm (33.9 ± 0.4 °C) and cold (18.6 ± 0.5 °C) months.

Conclusions
Our results provide an overview of Desmodesmus asymmetricus production under greenhouse conditions (temperature between 18 and 27 °C and lighting from 130 to 221 Klux), which was adapted to cultivation during a period of 10 months (January to October). The highest biomass production was obtained in March (approximately 70 mg L −1 day −1 ). Likewise, the highest percentage of proteins (31%) was obtained in this month. The amino acid analysis showed a maximum content for arginine (4.1 g 100 g −1 ) and aspartic acid (3.4 g 100 g −1 ). Regarding the potential as food supplement in the production of feed for aquatic organisms, D. assymetricus obtained EAAI values greater than 0.90 for fish such as S. aurata, P. maxima, P. lineatus, P. argentus and 0.80 for the crustacean P. vannamei, these values show that it is a suitable food for this purpose. It is recommended to carry out studies on the formulation of diets in aquaculture. In addition, the profitability and safety of the biomass of this microalgae must be evaluated, in order to get a new food input for aquaculture.