Reliability of graphite furnace atomic absorption spectrometry as alternative method for trace analysis of arsenic in natural medicinal products

Purpose: To evaluate the comparative efficiency of graphite furnace atomic absorption spectrometry (GFAAS) and hydride generation atomic absorption spectrometry (HGAAS) for trace analysis of arsenic (As) in natural herbal products (NHPs). Method: Arsenic analysis in natural herbal products and standard reference material was conducted using atomic absorption spectrometry (AAS), namely, hydride generation AAS (HGAAS) and graphite furnace (GFAAS). The samples were digested with HNO3–H2O2 in a ratio of 4:1 using microwaveassisted acid digestion. The methods were validated with the aid of the standard reference material 1515 Apple Leaves (SRM) from NIST Results: Mean recovery of three different samples of NHPs, using HGAAS and GFAAS, ranged from 89.3 - 91.4 %, and 91.7 - 93.0 %, respectively. The difference between the two methods was insignificant. A (P= 0.5), B (P=0.4) and C (P=0.88) Relative standard deviation (RSD) RSD, i.e., precision was 2.5 - 6.5 % and 2.3 - 6.7 % using HGAAS and GFAAS techniques, respectively. Recovery of arsenic in SRM was 98 and 102 % by GFAAS and HGAAS, respectively. Conclusion: GFAAS demonstrates acceptable levels of precision and accuracy. Both techniques possess comparable accuracy and repeatability. Thus, the two methods are recommended as an alternative approach for trace analysis of arsenic in natural herbal products.

Wheat blast and its effect on technological quality of grain from two sowing dates.

2016

Efficacy of fungicides for the control of wheat blast: collaborative tests results.

2016

Development and validation of a computationally efficient pseudo 3D model for planar SOFC integrated with a heating furnace

Efficient numerical models facilitate the study and design of solid oxide fuel cells (SOFCs), stacks, and systems. Whilst the accuracy and reliability of the computed results are usually sought by researchers, the corresponding modelling complexities could result in practical difficulties regarding the implementation flexibility and computational costs. The main objective of this article is to adapt a simple but viable numerical tool for evaluation of our experimental rig. Accordingly, a model for a multi-layer SOFC surrounded by a constant temperature furnace is presented, trained and validated against experimental data. The model consists of a four-layer structure including stand, two interconnects, and PEN (Positive electrode-Electrolyte-Negative electrode); each being approximated by a lumped parameter model. The heating process through the surrounding chamber is also considered. We used a set of V-I characteristics data for parameter adjustment followed by model verification against two independent sets of data. The model results show a good agreement with practical data, offering a significant improvement compared to reduced models in which the impact of external heat loss is neglected. Furthermore, thermal analysis for adiabatic and non-adiabatic process is carried out to capture the thermal behaviour of a single cell followed by a polarisation loss assessment. Finally, model-based design of experiment is demonstrated for a case study.

Assessing the risk of groundwater contamination from organic substances in sewage sludge.

In this work, the risk of groundwater contamination from organic substances in sewage sludge from wastewater treatment stations was evaluated in its worst case. The sewage sludge was applied as fertilizer in corn culture, prioritizing the substances for monitoring. The assessing risk took place in a Typic Distrophic Red Latossol (TDRL) area, in the county district of Jaguariúna, SP. The simulators CMLS-94 and WGEN were used to evaluate the risk of twenty-eight organic substances in sewage sludge to leach to groundwater. The risk of groundwater contamination was accomplished for a single sludge dose application in a thousand independent and equally probable years, simulated to esteem the substances leaching in one year after the application date of the sludge. It is presented the substances that should be priorly monitored in groundwater.

Occurrence and damage of head blast in barley in Brazil.

2016

Sowing date reduces the incidence of wheat blast disease.

2016

Effect of elevated atmospheric carbon dioxide concentration on rice blast in open-top chambers in Brazil.

2008

Wheat blast: progress in elucidating its ecology and developing strategies for control.

2006

Genetic dissimilarity among avena cultivars in response to the blast reaction.

2016

Reaction of Brazilian wheat cultivars to wheat blast in the Cerrado Region.

2016

Using a bayesian model for estimating air borne infection risks: wheat blast.

2016

A weather-based simulation model for wheat blast incidence.

2016

Control of Fusarium in Chrysanthemum with sewage sludge, biofertilizer, hydrolyzed fish, chitosan and Trichoderma.

2008

Combined effects of soil biotic and abiotic factors, influenced by sewage sludge incorporation, on the incidence of corn stalk rot.

Abstract: The objectives of this study were to evaluate the combined effects of soil bioticand abiotic factors on the incidence of Fusarium corn stalk rot, during four annual incorporations of two typesofsewagesludge intosoil ina 5-years field assay under tropical conditions and topredict the effectsof these variables on the disease. For each type of sewage sludge, the following treatments were included: control with mineral fertilization recommended for corn; control without fertilization; sewage sludge based on the nitrogen concentration that provided the same amount of nitrogen as in the mineral fertilizer treatment; and sewage sludge that provided two, four and eight times the nitrogen concentration recommended for corn. Increasing dosages of both types of sewage sludge incorporated into soil resulted in increased corn stalk rot incidence, being negatively correlated with corn yield. A global analysis highlighted the effect of the year of the experiment, followed by the sewage sludge dosages. The type of sewage sludge did not affect the disease incidence. Amultiple logistic model using a stepwise procedure was fitted based on the selection of a model that included the three explanatory parameters for disease incidence: electrical conductivity, magnesium and Fusarium population. In the selected model, the probability of higher disease incidence increased with an increase of these three explanatory parameters. When the explanatory parameters were compared, electrical conductivity presented a dominant effect and was the main variable to predict the probability distribution curves of Fusarium corn stalk rot, after sewage sludge application into the soil.