The Effect of Gibberellic Acid on the Production Characteristics and Biochemical Parameters of Tetraselmis Suecica in an Enrichment Culture

The use of gibberellic acid as a stimulator of microalgae growth has beensubstantiatedexperimentally.This research aimed to assess the effect of exposure to a wide range of gibberellic acid concentrations on the growth dynamics ofthe microalgaTetraselmissuecicain an enrichment culture. The duration of the experiments was 14 days. It has been shown that gibberellic acid,atconcentrations of 0.39–3.20× 10−8M, stimulates algaegrowth. In this research, the exposure to gibberellic acid at concentrations of 0.39–3.20 × 10−8M was accompanied by a variation in the pattern of growth curves: the maximum number of cells was recorded on day seven of the experiment. A higher concentration of the phytohormone (3.84 × 10−8М) inhibited the increase inculture density. The growth of theT. suecicaculture in the control group was 332%;the growth of the culture exposed to gibberellic acid at a concentration of 0.39 × 10−8M was1136%. The values of the specific growth rate ofT. suecicawere estimated for different periods of cultivation. On day14 of the experiment, the biochemical composition of microalgae biomass was analyzed.According to the results, gibberellic acid stimulated the accumulation of carbohydrates, proteins, and chlorophyll. Nevertheless, the phytohormone had no effect on lipidaccumulation. An assumption was made thatexposure to low concentrations of phytohormone stimulates the growth of microalgae by reducing the lag phase of growth. Keywords: gibberellic acid, microalga, cultivation, lipids, carbohydrates, proteins

Assessment of Nutrients Recovery Capacity and Biomass Growth of Four Microalgae Species in Anaerobic Digestion Effluent

Four microalgae species were evaluated for their bioremediation capacity of anaerobic digestion effluent (ADE) rich in ammonium nitrogen, derived from a biogas plant. Chlorella vulgaris, Chlorella sorokiniana, Desmodesmus communis and Stichococcus sp. were examined for their nutrient assimilation efficiency, biomass production and composition through their cultivation in 3.7% v/v ADE; their performance was compared with standard cultivation media which consisted in different nitrogen sources, i.e., BG-11NO3 and BG-11ΝΗ4 where N-NO3 was replaced by N-NH4. The results justified ammonium as the most preferable source of nitrogen for microalgae growth. Although Stichococcus sp. outperformed the other 3 species in N-NH4 removal efficiency both in BG-11NH4 and in 3.7% ADE (reaching up to 90.79% and 69.69% respectively), it exhibited a moderate biomass production when it was cultivated in diluted ADE corresponding to 0.59 g/L, compared to 0.89 g/L recorded by C. vulgaris and 0.7 g/L by C. sorokiniana and D. communis. Phosphorus contained in the effluent and in the control media was successfully consumed by all of the species, although its removal rate was found to be affected by the type of nitrogen source used and the particular microalgae species. The use of ADE as cultivation medium resulted in a significant increase in carbohydrates content in all investigated species.

The Effect of Nutrients Mixture on The Biomass and Lipid Production from Microalgae Botryococcus braunii Mutated by UV-C Rays

Nutrient is one of the most important factors in the growth of microalgae. This research was conducted to study the effect of nutrient mixture on the biomass and lipid production of Botryococcus braunii. Microalgae B. braunii was cultivated in the commercial nutrient medium of agricultural fertilizer combinations of ammonium sulphate (ZA), urea, and triple superphosphate (TSP). Before the cultivation process, B. braunii was exposed to UV-C rays (254 nm) for 3 minutes. The concentration and type of fertilizer as a nitrogen source divided into four types of mixtures, namely FM-1, FM-2, FM-3, and FM-4 were compared with Walne nutrients to study their effects on microalgae growth and lipids. FM-1 consisting of 150 mg/L of ZA, 7.5 mg/L of urea, and 25 mg/L of TSP led to the best growth for native and mutated microalgae strains compared to Walne nutrients and other nutrient mixtures. The mutated microalgae showed less growth than the native microalgae strains. However, the mutation process significantly increased the lipid content in the microalgae. In native microalgae strains, FM-4 consisting of 136.3 mg/L of urea and 50 mg/L of TSP produced the lowest lipid at 8.96%. After being exposed to UV-C rays, the lipids in FM-4 medium increased to 55.11%. The results show that the use of commercial fertilizers and exposure to UV-C rays on microalgae have high potential in preparing lipids as raw material for biodiesel which can be effectively applied in large-scale microalgae cultivation.

Control of Microalgae Growth in Artificially Lighted Photobioreactors Using Metaheuristic-Based Predictions

A metaheuristic algorithm can be a realistic solution when optimal control problems require a significant computational effort. The problem stated in this work concerns the optimal control of microalgae growth in an artificially lighted photobioreactor working in batch mode. The process and the dynamic model are very well known and have been validated in previous papers. The control solution is a closed-loop structure whose controller generates predicted control sequences. An efficient way to make optimal predictions is to use a metaheuristic algorithm, the particle swarm optimization algorithm. Even if this metaheuristic is efficient in treating predictions with a very large prediction horizon, the main objective of this paper is to find a tool to reduce the controller’s computational complexity. We propose a soft sensor that gives information used to reduce the interval where the control input’s values are placed in each sampling period. The sensor is based on measurement of the biomass concentration and numerical integration of the process model. The returned information concerns the specific growth rate of microalgae and the biomass yield on light energy. Algorithms, which can be used in real-time implementation, are proposed for all modules involved in the simulation series. Details concerning the implementation of the closed loop, controller, and soft sensor are presented. The simulation results prove that the soft sensor leads to a significant decrease in computational complexity.

Influence of Light Conditions on Microalgae Growth and Content of Lipids, Carotenoids, and Fatty Acid Composition

Microalgae are a valuable natural resource for a variety of value-added products. The growth of microalgae is determined by the impact of many factors, but, from the point of view of the implementation of autotrophic growth, light is of primary importance. This work presents an overview of the influence of light conditions on the growth of microalgae, the content of lipids, carotenoids, and the composition of fatty acids in their biomass, taking into account parameters such as the intensity, duration of lighting, and use of rays of different spectral composition. The optimal light intensity for the growth of microalgae lies in the following range: 26−400 µmol photons m−2 s−1. An increase in light intensity leads to an activation of lipid synthesis. For maximum lipid productivity, various microalgae species and strains need lighting of different intensities: from 60 to 700 µmol photons m−2 s−1. Strong light preferentially increases the triacylglyceride content. The intensity of lighting has a regulating effect on the synthesis of fatty acids, carotenoids, including β-carotene, lutein and astaxanthin. In intense lighting conditions, saturated fatty acids usually accumulate, as well as monounsaturated ones, and the number of polyunsaturated fatty acids decreases. Red as well as blue LED lighting improves the biomass productivity of microalgae of various taxonomic groups. Changing the duration of the photoperiod, the use of pulsed light can stimulate microalgae growth, the production of lipids, and carotenoids. The simultaneous use of light and other stresses contributes to a stronger effect on the productivity of algae.