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Productivity Value (productivity + value)
Selected AbstractsProduction of astaxanthin by Haematococcus pluvialis: Taking the one-step system outdoorsBIOTECHNOLOGY & BIOENGINEERING, Issue 2 2009M. Carmen García-Malea Abstract The feasibility of a one-step method for the continuous production of astaxanthin by the microalga Haematococcus pluvialis has been verified outdoors. To this end, influence of dilution rate, nitrate concentration in the feed medium, and irradiance on the performance of continuous cultures of H. pluvialis was firstly analyzed indoors in bubble column reactors under daylight cycles, and then outdoors, using a tubular photobioreactor. At the laboratory scale, the behavior of the cultures agreed with that previously recorded in continuous illumination experiences, and attested that the major factors determining biomass and astaxanthin productivity were average irradiance and specific nitrate supply. The rate of astaxanthin accumulation was proportional to the average irradiance inside the culture, provided that a nitrate limiting situation had been established. The accumulation of astaxanthin under daylight cycles was maximal for a specific nitrate input of 0.5 mmol/g,day. The recorded performance has been modeled on the basis of previously developed equations, and the validity of the model checked under outdoor conditions. Productivity values for biomass and astaxanthin of 0.7 g/L,day and 8.0 mg/L,day respectively, were obtained in a pilot scale tubular photobioreactor operating under continuous conditions outdoors. The magnitude of the experimental values, which matched those simulated from the obtained model, demonstrate that astaxanthin can be efficiently produced outdoors in continuous mode through a precise dosage of the specific nitrate input, taking also into consideration the average irradiance inside the culture. Biotechnol. Bioeng. 2009;102: 651,657. © 2008 Wiley Periodicals, Inc. [source] Batch production of L(+) lactic acid from whey by Lactobacillus casei (NRRL B-441)JOURNAL OF CHEMICAL TECHNOLOGY & BIOTECHNOLOGY, Issue 9 2004Ali O Büyükkileci Abstract The effects of temperature, pH, and medium composition on lactic acid production by Lactobacillus casei were investigated. The highest lactic acid productivity values were obtained at 37 °C and pH 5.5. The productivity was 1.87 g dm,3 h,1 at 37 °C in shake flasks. In the fermenter, a productivity of 3.97 g dm,3 h,1 was obtained at pH 5.5. The most appropriate yeast extract concentration was 5.0 g dm,3. Whey yielded a higher productivity value than the analytical lactose and glucose. Initial whey lactose concentration did not affect lactic acid productivity. MnSO4 ·H2O was necessary for lactic acid production by L casei from whey. Product yields were approximately 0.93 g lactic acid g lactose,1. Copyright © 2004 Society of Chemical Industry [source] Separation of chiral mixtures in real SMB units: The FlexSMB-LSRE®AICHE JOURNAL, Issue 1 2010Pedro Sá Gomes Abstract In this work, a procedure for the separation of a racemic mixture of guaifenesin onto a chiral stationary phase (Chiralpak AD), by means of Simulated Moving Bed (SMB) technology, is presented in four major steps: (1) search for the suitable stationary and mobile phases; (2) determination of sorption parameters and validation by frontal analysis; (3) modeling and design of the SMB unit; and (4) operation and demonstration. A major emphasis is given to the common deviations that "real" SMB units present when compared with the theoretical apparatus (due to tubing and equipment dead volumes, switching time asymmetries and delays, pumps flow rates variations). These deviations are analyzed before and after the design and construction of the FlexSMB-LSRE® unit, a new flexible unit, hereby presented. A detailed model that takes into account tubing and equipment dead volumes, as well as switching time asymmetries and delay, was used to study and compare different dead volumes design and compensating strategies. It is shown that all these approaches can be converged into a switching time compensating strategy. This approach served to predict the experimental operating conditions and run a classical SMB experiment, which afterwards was compared with the simulated profiles obtained for the FlexSMB-LSRE® unit. The result of the separation was guaifenesin enantiomers with purities above 98% and a productivity value of 23 genantiomer/(dm3 CSP day). © 2009 American Institute of Chemical Engineers AIChE J, 2010 [source] Land under pressure: soil conservation concerns and opportunities for EthiopiaLAND DEGRADATION AND DEVELOPMENT, Issue 1 2003B. G. J. S. Sonneveld Abstract This paper evaluates the future impact of soil degradation on national food security and land occupation in Ethiopia. It applies a spatial optimization model that maximizes national agricultural revenues under alternative scenarios of soil conservation, land accessibility and technology. The constraints in the model determine whether people remain on their original site, migrate within their ethnically defined areas or are allowed a transregional migration. Key to this model is the combination of a water erosion model with a spatial yield function that gives an estimate of the agricultural yield in its geographical dependence of natural resources and population distribution. A comparison of simulated land productivity values with historical patterns shows that results are interpretable and yield more accurate outcomes than postulating straightforward reductions in yield or land area for each geographic entity. The results of the optimization model show that in absence of soil erosion control, the future agricultural production stagnates and results in distressing food shortages, while rural incomes drop dramatically below the poverty line. Soil conservation and migration support a slow growth, but do not suffice to meet the expected food demand. In a transregional migration scenario, the highly degraded areas are exchanged for less affected sites, whereas cultivation on already substantially degraded soils largely continues when resettlement is confined to the original ethnic,administrative entity. A shift to modern technology offers better prospects and moderates the migration, but soil conservation remains indispensable, especially in the long term. Finally, an accelerated growth of non-agricultural sectors further alleviates poverty in the countryside, contributing to higher income levels of the total population and, simultaneously, relieving the pressure on the land through rural,urban migration. Copyright © 2002 John Wiley & Sons, Ltd. [source] Prediction of herbage yield in grassland: How well do Ellenberg N-values perform?APPLIED VEGETATION SCIENCE, Issue 1 2007Markus Wagner Wisskirchen & Haeupler (1998) Abstract Question: How useful are Ellenberg N-values for predicting the herbage yield of Central European grasslands in comparison to approaches based on ordination scores of plant species composition or on soil parameters? Location: Central Germany (11°00,-11°37'E, 50°21-50°34'N, 500,840 m a.s.l.). Methods: Based on data from a field survey in 2001, the following models were constructed for predicting herbage yield in montane Central European grasslands: (1) Linear regression of mean Ellenberg N-, R- and F-values; (2) Linear regression of ordination scores derived from Non-metric Multidimensional Scaling (NMDS) of vegetation data; and (3) Multiple linear regression (MLR) of soil variables. Models were evaluated by cross-validation and validation with additional data collected in 2002. Results: Best predictions were obtained with models based on species composition. Ellenberg N-values and NMDS scores performed equally well and better than models based on Ellenberg R- or F-values. Predictions based on soil variables were least accurate. When tested with data from 2002, models based on Ellenberg N-values or on NMDS scores accurately predicted productivity rank order of sites, but not the actual herbage yield of particular sites. Conclusions: Mean Ellenberg N-values, which are easy to calculate, are as accurate as ordination scores in predicting herbage yield from plant species composition. In contrast, models based on soil variables may be useful for generating hypotheses about the factors limiting herbage yield, but not for prediction. We support the view that Ellenberg N-values should be called productivity values rather than nitrogen values. [source] | |||||||||||||