Nitrogen Starvation For Lipid Accumulation In The Microalga Species Desmodesmus Sp.

Recently, to obtain lipids from microalgae has been the object of extensive research, since it is viewed as a promising feedstock for biodiesel production, especially when compared with crops such as soybean and sunflower, in terms of theoretical performance. The reduction of nutrient availability in culture media, especially nitrogen, stresses the microorganisms and affects cell growth, thus inducing lipid accumulation. This is an interesting step in biodiesel feedstock obtention from microalgae and should be better understood. In this study, four levels of nitrogen concentration in the BG-11 culture medium were evaluated in the growth of the chlorophycean microalga Desmodesmus sp. Both cell growth and lipid content were monitored over 7 days of cultivation, which yielded a final cell density of 33 × 10(6) cells mL(-1) with an initial NaNO3 concentration of 750 mg L(-1) in the medium and a maximum lipid content of 23 % with total nitrogen starvation. It was observed that the microalgae presented high lipid accumulation in the fourth day of cultivation with nitrogen starvation, although with moderate cell growth.

Influência da temperatura do ar de secagem no calor latente de vaporização de água em feijão macassar (Vigna unguiculata (L.) Walp.), variedade sempre-verde

In order to determine the energy needed to artificially dry an agricultural product the latent heat of vaporization of moisture in the product, H, must be known. Generally, the expressions for H reported in the literature are of the form H = h(T)f(M), where h(T) is the latent heat of vaporization of free water, and f(M) is a function of the equilibrium moisture content, M, which is a simplification. In this article, a more general expression for the latent heat of vaporization, namely H = g(M,T), is used to determine H for cowpea, always-green variety. For this purpose, a computer program was developed which automatically fits about 500 functions, with one or two independent variables, imbedded in its library to experimental data. The program uses nonlinear regression, and classifies the best functions according to the least reduced chi-squared. A set of executed statistical tests shows that the generalized expression for H used in this work produces better results of H for cowpea than other equations found in literature.