Growth and plant mass of radish fertirrigated with different doses nitrogen

ABSTRACT The objective of the present study was to evaluate the effect of nitrogen doses applied via fertigation and associated with different types of crop establishment fertilization on growth and biomass of radish. The experiment was conducted in a greenhouse of the Academic Unit of Agricultural Engineering, Federal University of Campina Grande, from April to May 2014. Treatments consisted of five doses of nitrogen fertilizer applied by fertigation (0, 0.7, 1.4, 2.1 and 2.8g per pot) and three types of crop establishment fertilization (humus 2:2; NPK and control), arranged in a 5 x 3 factor design with four repetitions. The 15 treatments were arranged in 60 plots. The nitrogen source used in the study was urea, divided in three applications: the first application was carried out eight days after transplanting, the second, on day 15, and the third, on day 22. The crop establishment fertilization significantly influenced the growth variables and plant mass of the radish on day 35 after transplanting. The highest values of the variables (number of leaves, plant height, bulb diameter, leaf area, fresh mass of the aerial part, dry mass of the aerial part and root/aerial part were observed in the treatment with humus on day 35 after transplanting. The dose of 2.8g nitrogen per pot corresponding to 6.22g of urea per plant provided the highest yield for the variable number of leafs, leaf area and root length on day 35 after transplanting.

Effect of plant-biostimulant on cassava initial growth

ABSTRACT Biostimulants are complex substances that promote hormonal balance in plants, favor the genetic potential expression, and enhance growth of shoots and root system. The use of these plant growth promoters in crops can increase quantitatively and qualitatively crop production. Therefore, the aim of this study was to evaluate the effect of a commercial biostimulant on the initial growth of cassava. The experiment was arranged in a 2 x 5 factorial design, corresponding to two cassava cultivars (Cacau-UFV and Coimbra) and five biostimulant concentrations (0, 4, 8, 12 and 16 mL L-1). At 90 days after planting, the characteristics leaf area, plant height, stem diameter, leaf number, total dry matter and dry matter of roots, stems and leaves were evaluated. The biostimulant promoted linear increases in plant height, leaf number, leaf area, total dry matter, dry matter of stems, leaves and roots. The cultivar Cacau-UFV had a higher growth rate than the cultivar Coimbra. The growth promoter stimulated the early growth of the cassava crop.

Reproductive outcomes in an area adjacent to a petrochemical plant in southern Brazil

OBJECTIVE: To evaluate possible adverse reproductive outcomes in an area adjacent to a petrochemical plant in southern Brazil. METHODS: A review of 17,113 birth records of the main hospital of the municipality of Montenegro, southern Brazil, from 1983 to 1998 was carried out. Three groups of cases were selected: (1) newborns with major congenital malformations; (2) newborns with low birth weight (<2,500 g); and (3) stillborns (>500 g). A control was assigned to each case. Controls were the first newborns weighing > or = 2,500 g without malformations and of case-matching sex. Mother's residence during pregnancy was used as an exposure parameter. Statistical analyses were performed using Chi-square test or Fisher test, odds ratio, 0.05 significance level, and 95% confidence interval. RESULTS: For unadjusted analysis, it was found a correlation between low birth weight and geographical proximity of mother's residence to the petrochemical plant (OR = 1.66; 95% CI = 1.01--2.72) or residence on the way of preferential wind direction (OR = 1.62; 95% CI = 1.03--2.56). When other covariates were added in the conditional logistic regression (maternal smoking habits, chronic disease and age), there was no association. CONCLUSIONS: Despite final results were negative, low birth weight could be a good parameter of environmental contamination and should be closely monitored in the studied area.

Fungal and microbial volatile organic compounds exposure assessment in a waste sorting plant

In the management of solid waste, pollutants over a wide range are released with different routes of exposure for workers. The potential for synergism among the pollutants raises concerns about potential adverse health effects, and there are still many uncertainties involved in exposure assessment. In this study, conventional (culture-based) and molecular real-time polymerase chain reaction (RTPCR) methodologies were used to assess fungal air contamination in a waste-sorting plant which focused on the presence of three potential pathogenic/toxigenic fungal species: Aspergillus flavus, A. fumigatus, and Stachybotrys chartarum. In addition, microbial volatile organic compounds (MVOC) were measured by photoionization detection. For all analysis, samplings were performed at five different workstations inside the facilities and also outdoors as a reference. Penicillium sp. were the most common species found at all plant locations. Pathogenic/toxigenic species (A. fumigatus and S. chartarum) were detected at two different workstations by RTPCR but not by culture-based techniques. MVOC concentration indoors ranged between 0 and 8.9 ppm (average 5.3 ± 3.16 ppm). Our results illustrated the advantage of combining both conventional and molecular methodologies in fungal exposure assessment. Together with MVOC analyses in indoor air, data obtained allow for a more precise evaluation of potential health risks associated with bioaerosol exposure. Consequently, with this knowledge, strategies may be developed for effective protection of the workers.

Nanofiltration for the treatment of coke plant ammoniacal wastewaters

This work addresses the treatment by nanofiltration (NF) of solutions containing NaCN and NH(4)Cl at various pH values. The NF experiments are carried out in a Lab-Unit equipped with NF-270 membranes for model solutions that are surrogates of industrial ammoniacal wastewaters generated in the coke-making processes. The applied pressure is 30 bar. The main objective is the separation of the compounds NaCN and NH(4)Cl and the optimization of this separation as a function of the pH. Membrane performance is highly dependent on solution composition and characteristics, namely on the pH. In fact, the rejection coefficients for the binary model solution containing sodium cyanide are always higher than the rejections coefficients for the ammonium chloride model solution. For ternary solutions (cyanide/ammonium/water) it was observed that for pH values lower than 9 the rejection coefficients to ammonium are well above the ones observed for the cyanides, but for pH values higher than 9.5 there is a drastic decrease in the ammonium rejection coefficients with the increase of the pH. These results take into account the changes that occur in solution, namely, the solute species that are predominant, with the increase of the pH. The fluxes of the model solutions decreased with increased pH. (C) 2010 Elsevier B.V. All rights reserved.

Intelligent Bio-Inspired system for manufacturing scheduling under uncertainties

A novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS), Case-based Reasoning (CBR), and Bio-Inspired Optimization Techniques (BIT) will be described. AC has emerged as a paradigm aiming at incorporating applications with a management structure similar to the central nervous system. The main intentions are to improve resource utilization and service quality. In this paper we envisage the use of MAS paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with AC properties, in order to reduce the complexity of managing manufacturing systems and human interference. The proposed CBR based Intelligent Scheduling System was evaluated under different dynamic manufacturing scenarios.

Self-optimization for dynamic scheduling in manufacturing systems

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).

MASDSheGATS – Scheduling System for Dynamic Manufacturing Environments

This chapter addresses the resolution of scheduling in manufacturing systems subject to perturbations. The planning of Manufacturing Systems involves frequently the resolution of a huge amount and variety of combinatorial optimisation problems with an important impact on the performance of manufacturing organisations. Examples of those problems are the sequencing and scheduling problems in manufacturing management, routing and transportation, layout design and timetabling problems.

Addressing the facilities layout design problem through constraint logic programming

One of the most difficult problems that face researchers experimenting with complex systems in real world applications is the Facility Layout Design Problem. It relies with the design and location of production lines, machinery and equipment, inventory storage and shipping facilities. In this work it is intended to address this problem through the use of Constraint Logic Programming (CLP) technology. The use of Genetic Algorithms (GA) as optimisation technique in CLP environment is also an issue addressed. The approach aims the implementation of genetic algorithm operators following the CLP paradigm.

Research on evaluation system of emergency disposal plan for power plant incidents

This paper starts with the analysis of the unusual inherence mechanism, from two aspects: accumulating and human error. We put forward twelve factors affected the decision of the emergency treatment plan in practice and summarized the evaluation index system combining with literature data. Then we screened out eighteen representative indicators by used the FDM expert questionnaire in the first phase. Hereafter, we calculated the weight of evaluation index and sorted them by the FAHP expert questionnaire, and came up with the frame of the evaluation rule by combined with the experience. In the end, the evaluation principles are concluded.

Self-organization for scheduling in agile manufacturing

Agility refers to the manufacturing system ability to rapidly adapt to market and environmental changes in efficient and cost-effective ways. This paper addresses the development of self-organization methods to enhance the operations of a scheduling system, by integrating scheduling system, configuration and optimization into a single autonomic process requiring minimal manual intervention to increase productivity and effectiveness while minimizing complexity for users. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to build future Decision Support Systems (DSS) for Scheduling in agile manufacturing environments.