Evolution of operational parameters in a UASB wastewater plant

Abstract The results reported here are based on data of the Nova Pampulha Wastewater Treatment Plant, in the metropolitan region of Belo Horizonte (Minas Gerais, Brazil) containing an upflow anaerobic sludge blanket (UASB) reactor. The objective of this research was to establish the operational parameters of the plant and evolution of elimination of pollutants. Influent and effluent parameters used for this research, were oils, volatile fatty acidity, alkalinity, ammonium, bacteria, flow, chlorides, BOD, detergents, COD, phosphates, total nitrogen, pH, settleable solids, suspended solids (total and volatile), sulphates, sulphides, temperature (air, influent, effluent and reactor) and hydraulic retention time (HRT). Weekly data were collected between January 1998 and June 2000, namely 124 weeks. Methods used for data included conventional statistics, graphical representations and multiple linear regression, applied with the program SPSS, licensed to UPV/EHU with the aim of obtaining equations for the estimation of%age elimination (or increase) of pollutants during anaerobic treatment. The analysis of operational data of the Nova Pampulha plant also includes the temporary and seasonal evolution of control parameters, made by a set of graphical representations for process parameters (flow, HRT, temperature and bacterial count), parameters associated with acid -base equilibrium (acidity, alkalinity and pH), organic constituents (BOD, COD, oils and detergents), inorganic constituents chlorides, phosphates, sulphates, sulphides and nitrogen compounds) and solids (settleable and suspended). By using multiple linear regression, equations could be obtained for estimating the elimination of constituent loads as functions of process parameters and constituent loads in the influents, as possible independent variables. Equations, statistically significant at a 95% confidence level, were obtained for all the eliminations. The calculation is presented in the form of regression equations and some comparative graphics between experimental and predicted data. Data variances were in the region of 20 and 87%. The observation of coefficients of equations for organic matter and suspended solids permits the establishment of parameters associated with elimination or increase of these constituents

Gene expression in coffee

Coffee is cultivated in more than 70 countries of the intertropical belt where it has important economic, social and environmental impacts. As for many other crops, the development of molecular biology technics allowed to launch research projects for coffee analyzing gene expression. In the 90s decade, the first expression studies were performed by Northern-blot or PCR, and focused on genes coding enzymes of the main compounds (e.g., storage proteins, sugars, complex polysaccharides, caffeine and chlorogenic acids) found in green beans. Few years after, the development of 454 pyrosequencing technics generated expressed sequence tags (ESTs) obviously from beans but also from other organs (e.g., leaves and roots) of the two main cultivated coffee species, Coffea arabica and C. canephora. Together with the use of real-time quantitative PCR, these ESTs significantly raised the number of coffee gene expression studies leading to the identification of (1) key genes of biochemical pathways, (2) candidate genes involved in biotic and abiotic stresses as well as (3) molecular markers essential to assess the genetic diversity of the Coffea genus, for example. The development of more recent Illumina sequencing technology now allows large-scale transcriptome analysis in coffee plants and opens the way to analyze the effects on gene expression of complex biological processes like genotype and environment interactions, heterosis and gene regulation in polypoid context like in C. arabica. The aim of the present review is to make an extensive list of coffee genes studied and also to perform an inventory of large-scale sequencing (RNAseq) projects already done or on-going