Abstract. Fakhri M, Riyani E, Ekawati AW, Arifin NB, Yuniarti A, Widyawati Y, Saputra IK, Samuel PD, Arif MZ, Hariati AM. 2021. Biomass, pigment production, and nutrient uptake of Chlorella sp. under different photoperiods. Biodiversitas 22: 5344-5349. Chlorella sp. is well-known as a functional feed in fish culture and has been utilized in the food industry. In phototrophic cultivation, photoperiod plays a fundamental part in the growth and pigment content of microalgae. This work was purposed to evaluate the effect of light:dark cycle on the growth rate, production of biomass and pigment and nutrient utilization of Chlorella sp. Four photoperiods (8:16, 12:12, 18:6, and 24:0 h light:dark regimes) under a constant light intensity of 4500 lux were applied in this study. The results demonstrated that increasing light duration led to increased cell growth, biomass, and pigment production of Chlorella sp. The best cell concentration, specific growth rate, and biomass production were 28.5 x 106 cells mL-1, 1.47 day-1, and 0.815 g L-1 dry weight, respectively, under continuous illumination. The maximum chlorophyll a of 19.205 mg L-1 and carotenoid of 4.656 mg L-1 were obtained at 24:0 h photoperiod. The highest uptake of nitrate (66.331%) and phosphate (76.191%) by Chlorella sp. were achieved under 24 h light regime. Improving the uptake of nutrients resulted in enhanced growth and pigment content of Chlorella sp. We conclude that continuous illumination is the best photoperiod to produce biomass and pigment and improve the nutrient removal of Chlorella sp.
The Covid-19 pandemic caused a large amount of medical mask waste to be buried in the environment. Medical masks are one of the categories of B3 waste that should require a special treatment process. In fact, in the current pandemic conditions, medical mask waste can be found along with household waste without special treatment and separation. Medical masks have the potential to contain pathogenic microbial populations that attack the human respiratory system. On the other hand, microbes themselves are a group of organisms that are susceptible to mutation. Management of medical mask waste that does not comply with B3 waste management standards will have an impact on the emergence of new problems in the future. The purpose of this study was to identify the distribution of microorganism populations in mask waste samples taken randomly from household waste disposal sites. The medical mask waste sample will then be isolated and identified to determine the medical mask waste sample’s microbiome variations. Based on the research results, it was found that 47% of the microorganisms detected were coliform microorganisms, 20% of other organisms were unidentified microorganisms, and the remaining 33% were pathogenic microorganisms.
The Covid-19 pandemic, which is happening all over the world, needs serious attention. Covid-19 initiated by an RNA type virus can cause more severe problems later on due to its ability to mutate. Integrated molecular research is required to determine the characteristics and potential of various variants of Covid-19 in mutations. This study was conducted by directing phylogenetic analysis on 17 samples of Covid-19 sequences from several countries taken from the NCBI database and followed by ORF analysis of each Covid-19 sample for further characterization. Based on the study, it is known that from 17 samples of Covid-19 sequences, Covid-19 sequences from Taiwan have the lowest similarity compared to 16 other Covid-19 sequences. These results are confirmed by the ORF analysis of each sample, which shows that the longest ORF in the Covid-19 sequence from Taiwan is an ORF 20 with lengthened by 4405 amino acids, and the shortest ORF is an ORF 38 with lengthened by 50 amino acids. However, 16 other sequence samples have the longest ORF 6, ORF 6, with lengthened by 4405 amino acids and the shortest ORF 44 with lengthened by 50 amino acids. The difference in ORF variation affects the similarity level of Covid-19 sequences from several countries. It is due to variations in ORF that produce amino acid variations that determine the Covid-19 phenotype.
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