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Green Microalgae as a Food Source – Growth Kinetics and Biochemical Composition

El-Haji Sarra, Houzi Ghizlane, Kaioua Samiha, Abdelaziz Chaouch

Ecological Engineering & Environmental Technology

2023

Vol. 24, iss. 7

154--160

Microalgae are considered as a renewable natural resource that presents important potentialities to be valorized in several fields. This valorization must necessarily start with a thorough study of the biochemical composition of each species of algae. The objective of this study is to study the evolution of the biochemical composition according to the different stages of growth of three biomasses of microalgae (Fragilaria sp, Scenedesmus protuberans, Polytoma Papilatum) collected from Moroccan aquatic environments. Polytoma Papilatum and Scenedesmus protuberans show high protein content of 89.23±2.58%, 90.4±1.45% respectively in addition to low lipid 2.4±0.23, 1.63±0.2% and carbohydrate 8.08±1.25, 8.19±1.07 respectively. On the other hand, Fragilaria sp has high value of carbohydrate 65.73±3.25% as well as low in protein and lipid contents with values of 33.16±1.76, 1.28±0.29 respectively. The monitoring of the growth kinetics allows differentiating three phases on the growth curve: latent phase, exponential growth phase, and stationary phase. Regarding the biochemical composition, the highest content of proteins, carbohydrates and lipids in relation to the harvested biomass reach its maximum at the stationary phase.

Identification of Groundwater Quality by Statistical Methods and a Mathematical Method in the Khemisset–Tiflet Region

Zahra Elassassi, Ihsane Ougrad, Jihan Faouzi, Abdeslam Abid, Amal Saad, Fouzia Nhari, Mohmed Fadli, Abdelaziz Chaouch

Ecological Engineering & Environmental Technology

2022

Vol. 23, iss. 4

115--124

Groundwater is one of the most important natural resources that is overexploited and extensively polluted by human activity. Furthermore, drinking this dirty water might have major consequences for human health. Before using groundwater, it is consequently required to conduct a precise and regular assessment of its quality. Furthermore, for five monitoring stations in the Khemisset-Tiflet region, cluster analysis (CA), principal component analysis (PCA), and a fuzzy logic technique were utilized to analyze water quality. The CA classified the sample sites into three categories. The PCA identified temporal characteristics of water quality status. Group I include stations characterized by high temperature and low DO, COD, and BOD5 values. Group II includes stations characterized by high values of pH and low concentrations of NO3-, Cl-, SO42- and turbidity. Group III includes stations characterized by high concentrations of NO3-, Cl-, SO42- and turbidity and low concentrations of pH. In addition, fuzzy logic to reveal more information about groundwater quality. In effect, water quality in spring and winter was the best; the parameters responsible for the deterioration of water quality are NO3-, Cl-, SO42- and turbidity.