Variability of organophosphorus insecticide residues in large size crops grown in commercial farms in Brazil

Caldas, Eloísa Dutra; Jardim, Andréia Nunes Oliveira; Ambrus, Árpád; Souza, L.C.K.R. de

doi:10.1080/02652030500479708

Cited by 16 publications

(14 citation statements)

References 20 publications

(25 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…There are many chemical-based approaches to residue analysis of insecticides on crops and food items, such as, HPLC [44,45], ELISA [46], gas chromatography [47,48]. While all of these methods are highly accurate and able to detect very low residue levels, they require specially trained personnel, fairly sophisticated laboratory conditions, and are time-consuming.…”

Section: Discussionmentioning

confidence: 99%

Using Spatial Structure Analysis of Hyperspectral Imaging Data and Fourier Transformed Infrared Analysis to Determine Bioactivity of Surface Pesticide Treatment

et al. 2010

View full text Add to dashboard Cite

Many food products are subjected to quality control analyses for detection of surface residue/contaminants, and there is a trend of requiring more and more documentation and reporting by farmers regarding their use of pesticides. Recent outbreaks of food borne illnesses have been a major contributor to this trend. With a growing need for food safety measures and -smart applications‖ of insecticides, it is important to develop methods for rapid and accurate assessments of surface residues on food and feed items. As a model system, we investigated detection of a miticide applied to maize leaves and its miticidal bioactivity over time, and we compared two types of reflectance data: fourier transformed infrared (FTIR) data and hyperspectral imaging (HI) data. The miticide (bifenazate) was applied at a commercial field rate to maize leaves in the field, with or without application of a surfactant, and with or without application of a simulated -rain event‖. In addition, we collected FTIR and HI from untreated control leaves (total of five treatments). Maize leaf data were collected at seven time intervals from 0 to 48 hours after application. FTIR data were analyzed using conventional analysis of variance of miticide-specific vibration peaks. Two unique FTIR vibration peaks were associated with miticide application (1,700 cm −1 and 763 cm −1 ). The integrated intensities of these two OPEN ACCESSRemote Sensing 2010, 2 909 peaks, miticide application, surfactant, rain event, time between miticide application, and rain event were used as explanatory variables in a linear multi-regression fit to spider mite mortality. The same linear multi-regression approach was applied to variogram parameters derived from HI data in five selected spectral bands (664, 683, 706, 740, and 747 nm). For each spectral band, we conducted a spatial structure analysis, and the three standard variogram parameters (-sill‖, -range‖, and -nugget‖) were examined as possible -indicators‖ of miticide bioactivity. We demonstrated that both FTIR peaks and standard variogram parameters could be used to accurately predict spider mite mortality, but linear multi-regression fits based on standard variogram parameters had the highest accuracy and were successfully validated with independent data. Based on experimental manipulation of HI data, the use of spatial structure analysis in classification of HI data was discussed.

show abstract

Section: Discussionmentioning

confidence: 99%

Using Spatial Structure Analysis of Hyperspectral Imaging Data and Fourier Transformed Infrared Analysis to Determine Bioactivity of Surface Pesticide Treatment

et al. 2010

View full text Add to dashboard Cite

show abstract

“…89, 90 Esse fator indica que num lote de laranjas, por exemplo, existe uma unidade que apresenta uma concentração 3 vezes maior que a concentração média de todas as unidades presentes no lote. A metodologia para o cálculo da IESTI utiliza diferentes equações dependendo da massa da unidade (Unit -U) do alimento e de sua proporção em relação à maior porção consumida, isto é, se o consumo pode incluir mais de uma unidade (p.ex., laranja) ou é parte dela (p.ex., melancia).…”

Section: A Exposição Agudaunclassified

Exposição humana a substâncias químicas potencialmente tóxicas na dieta e os riscos para saúde

Jardim¹,

Caldas²

2009

Quím. Nova

View full text Add to dashboard Cite

Recebido em 16/9/08; aceito em 11/2/09; publicado na web em 23/7/09 CHEMICAL DIETARY EXPOSURE AND THE RISKS TO HUMAN HEALTH. Humans are exposed to a variety of chemicals from the consumption of food, including undesirable compounds such as pesticides and mycotoxins. Chemical human risk assessment is a process intended to estimate the risk to a given population from the exposure to a chemical (or to a chemical group having the same mechanism of action). The process consists of four steps, namely hazard identification, hazard characterization, exposure assessment and risk characterization. Chemical dietary risk assessment is an essential procedure to establish safe food standards. In this review the tools and data sources currently used in the risk assessment process will be discussed.Keywords: food; chemical exposure; dietary risk assessment. INTRODUÇÃONos alimentos que consumimos está presente uma grande variedade de substâncias químicas, como aquelas essenciais para a manutenção da saúde, como vitaminas, minerais e proteínas, e algumas potencialmente tóxicas, como micotoxinas, resíduos de pesticidas, aditivos e metais pesados. A falta de algum nutriente ou a presença excessiva no alimento de substâncias tóxicas pode significar um risco à saúde humana.A preocupação com a presença de substâncias químicas nos alimentos iniciou-se na década A avaliação do risco objetiva estimar o risco a um dado organismo alvo, sistema ou (sub)população, incluindo a identificação das incertezas esperadas, após a exposição a um agente particular, levando em consideração as características inerentes ao agente e as do sistema alvo.3 Avaliar o risco causado pela exposição humana a substâncias químicas na dieta é amplamente reconhecido como um processo fundamental no desenvolvimento de padrões alimentares seguros. 4 A avaliação é conduzida, por exemplo, pelos governos durante o processo de registro de aditivos alimentares ou de substâncias que serão utilizadas no manejo agropecuário, como pesticidas e drogas veterinárias. No caso de contaminantes presentes nos alimentos, os estudos subsidiam ações gerenciais que levem ao controle da contaminação e diminuição da exposição humana.No Brasil, a Agência Nacional de Vigilância Sanitária (ANVISA) é responsável pelo processo de registro de aditivos, pesticidas e drogas veterinárias e pela condução de avaliação do risco da exposição humana a estas substâncias e a contaminantes em alimentos. Enquanto a avaliação do risco é um processo de base científica, o gerenciamento do risco envolve tomada de decisões pelas agências reguladoras que levam em consideração, além de informações técnicas relevantes relacionadas ao dano à saúde e ao risco, fatores políticos, sociais e econômicos. A troca de informações sobre o risco entre avaliadores, gerenciadores, mídia, grupos de interesse e público em geral se dá no âmbito da comunicação de risco.3 A avaliação, o gerenciamento e a comunicação do risco são processos que interagem entre si, sendo partes de um processo maior, a análise do risco (Figura 1) Neste tr...

show abstract

“…In order to obtain more representative residue measurements, several crop units may be homogenized together to form a composite sample. The variability among composite samples is smaller than that among crop unit residues, but it may still frequently produce CV of 70-80% (Ambrus 1996(Ambrus , 2000bCaldas et al 2006).…”

Section: Introductionmentioning

confidence: 96%

Investigating Factors Affecting Unit-to-Unit Variability in Non-Systemic Pesticide Residues by Stochastic Simulation Modelling

Huo

Salazar³

et al. 2008

Human and Ecological Risk Assessment: An International Journal

View full text Add to dashboard Cite

The estimation of acute dietary intake plays a key role in the safety assessment of pesticide residues and needs knowledge of the unit-to-unit variability in residues. There is limited knowledge of contributions of factors to often observed large unit-tounit variability in residues. A stochastic simulation study was conducted to investigate the effects of sample size and heterogeneity in factors driving residue dissipation of non-systemic pesticides on the unit-to-unit variability among individual apples. The heterogeneity in driving factors was expressed in terms of variability in three dissipation parameters. The variability factor (VF), calculated as the ratio of residues in individual fruit at the 97.5th percentile and the mean residue, was used to represent the unit-to-unit variability. As the rate of dissipation increased, the variability in the corresponding parameter led to larger increases in the variability VF of residues over time. Thus, under field conditions, the relative in pesticide residues is expected to increase with time although the absolute level of residues decreases. The coefficient of variation (CV) was used to describe residue variability in samples of small sizes (5, 10, 20, 40, and 80). When sample size was fewer than 40 fruit, the sample CV increased steeply with decreasing sample size. Measuring residues as concentrations, instead of per fruit, also led to an average 4-8% increase in the CV of residues because of variability in fruit expansion.

show abstract

Variability of organophosphorus insecticide residues in large size crops grown in commercial farms in Brazil

Cited by 16 publications

References 20 publications

Using Spatial Structure Analysis of Hyperspectral Imaging Data and Fourier Transformed Infrared Analysis to Determine Bioactivity of Surface Pesticide Treatment

Using Spatial Structure Analysis of Hyperspectral Imaging Data and Fourier Transformed Infrared Analysis to Determine Bioactivity of Surface Pesticide Treatment

Exposição humana a substâncias químicas potencialmente tóxicas na dieta e os riscos para saúde

Investigating Factors Affecting Unit-to-Unit Variability in Non-Systemic Pesticide Residues by Stochastic Simulation Modelling

Contact Info

Product

Resources

About