Mirlaine R. Freitas

Coloured chemical image-based models for the prediction of soil sorption of herbicides

Herbicides with high soil sorption profiles constitute important organic pollutants leading to detrimental environmental effects, particularly due to prolonged use. Soil sorption is described in terms of log KOC, the logarithm of the soil/water partition coefficient normalized to organic carbon. This work reports the use of molecular drawings to generate molecular descriptors, which are posteriorly correlated with the log KOC values of a series of herbicides. These images are two-dimensional projections of chemical structures, with their atom sizes drawn to be proportional to the corresponding van der Waals radii and each chemical element assigned a different colour to distinguish atom types. The progressive changes in the molecular structures explain the variance in the corresponding soil sorption. Unlike previous QSPR studies on soil sorption, the series of herbicides employed in the present study included different classes of compounds (carboxylic acids, ethers, phenols, amines, amides and carbamates) guaranteeing a diverse chemical structural space. The obtained Partial Least Squares (PLS) and Multiple Linear Regression (MLR) based models for the log KOC values were found to be robust and with high predictive power. Mechanistic interpretation of the effect of different substituents (bonded to the common structural moiety in the herbicides series) on the log KOC values was performed yielding interesting results. These findings allow greater understanding of the chemical groups (or structural characteristics) responsible for high/low soil sorption, which in turn provides key leads for structural optimization to yield environmentally friendly and equally effective herbicides.

Augmented Multivariate Image Analysis Applied to Quantitative Structure–Activity Relationship Modeling of the Phytotoxicities of Benzoxazinone Herbicides and Related Compounds on Problematic Weeds

Two of major weeds affecting cereal crops worldwide are Avena fatua L. (wild oat) and Lolium rigidum Gaud. (rigid ryegrass). Thus, development of new herbicides against these weeds is required; in line with this, benzoxazinones, their degradation products, and analogues have been shown to be important allelochemicals and natural herbicides. Despite earlier structure-activity studies demonstrating that hydrophobicity (log P) of aminophenoxazines correlates to phytotoxicity, our findings for a series of benzoxazinone derivatives do not show any relationship between phytotoxicity and log P nor with other two usual molecular descriptors. On the other hand, a quantitative structure-activity relationship (QSAR) analysis based on molecular graphs representing structural shape, atomic sizes, and colors to encode other atomic properties performed very accurately for the prediction of phytotoxicities of these compounds against wild oat and rigid ryegrass. Therefore, these QSAR models can be used to estimate the phytotoxicity of new congeners of benzoxazinone herbicides toward A. fatua L. and L. rigidum Gaud.

Aug-MIA-QSPR modeling of the soil sorption of carboxylic acid herbicides.

Abstract Soil sorption, described as logKOC (the logarithm of the soil/water partition coefficient normalized to organic carbon), was modeled using the augmented multivariate image analysis applied to quantitative structure–property relationship method for a series of 11 carboxylic acid herbicides. The statistical model was found to be highly predictive and reliable to estimate logKOC of other persistent organic pollutants in the soil, which are analogues of the carboxylic acids used in the QSPR model. The QSPR model derived from images corresponding to the chemical structures of the 11 herbicides is superior to the uniparameter model based on the octanol/water partition coefficient (logP) and, in addition, a pattern recognition model was built using principal component analysis. This model allowed clustering and separating compounds with low/moderate soil sorption from those with moderate/high soil sorption (compounds with the aryloxy function) using the second principal component.

Three-Parameter Modeling of the Soil Sorption of Acetanilide and Triazine Herbicide Derivatives

Herbicides have widely variable toxicity and many of them are persistent soil contaminants. Acetanilide and triazine family of herbicides have widespread use, but increasing interest for the development of new herbicides has been rising to increase their effectiveness and to diminish environmental hazard. The environmental risk of new herbicides can be accessed by estimating their soil sorption (logKoc), which is usually correlated to the octanol/water partition coefficient (logKow). However, earlier findings have shown that this correlation is not valid for some acetanilide and triazine herbicides. Thus, easily accessible quantitative structure–property relationship models are required to predict logKoc of analogues of the these compounds. Octanol/water partition coefficient, molecular weight and volume were calculated and then regressed against logKoc for two series of acetanilide and triazine herbicides using multiple linear regression, resulting in predictive and validated models.

Environmental Perception as a Diagnostic Probe of Environmental Complexity Levels

Abstract Purpose: Educational methods to diagnose and improve the level of environmental conception are required. The present work reports a methodology based on studies about the environmental perception of a university public, divided into general students and those related to the forest sciences, who are involved with disciplines and researches related to e.g. environmental management. Design/Methodology/Approach: The environmental perception obtained from the graphical representation of environment and the most relevant actions indicated by the students to achieve the environmental conservation, divided in four levels of complexity, were correlated using principal component analysis. Findings: The students from both groups having the highest scores in environmental perception prioritize actions related to the comprehension and responsibility levels, while the ideal scenario would be to indicate actions related to competence and citizenship. Thus, the complex concept about environment of the students is still incipient and, therefore, educational strategies can be traced based on the profiles obtained. Practical Implications: The method for environmental perception can be designed for different populations and a scheme relating environmental perception with four levels of actions on behalf of the environmental conservation is proposed to diagnose environmental conceptions, as well as to guide educational strategies about socio-ecological system. Originality/Value: A semi-quantitative method was developed to estimate, clearly and directly, the level of complexity about the environmental knowledge of university students and, consequently, to predict the actions on behalf of the environmental conservation that they would probably perform.

Quantitative modeling of bioconcentration factors of carbonyl herbicides using multivariate image analysis.

The bioconcentration factor (BCF) is an important parameter used to estimate the propensity of chemicals to accumulate in aquatic organisms from the ambient environment. While simple regressions for estimating the BCF of chemical compounds from water solubility or the n-octanol/water partition coefficient have been proposed in the literature, these models do not always yield good correlations and more descriptive variables are required for better modeling of BCF data for a given series of organic pollutants, such as some herbicides. Thus, the logBCF values for a set of carbonyl herbicides comprising amide, urea, carbamate and thiocarbamate groups were quantitatively modeled using multivariate image analysis (MIA) descriptors, derived from colored image representations for chemical structures. The logBCF model was calibrated and vigorously validated (r(2) = 0.79, q(2) = 0.70 and rtest(2) = 0.81), providing a comprehensive three-parameter linear equation after variable selection (logBCF = 5.682 - 0.00233 × X9774 - 0.00070 × X813 - 0.00273 × X5144); the variables represent pixel coordinates in the multivariate image. Finally, chemical interpretation of the obtained models in terms of the structural characteristics responsible for the enhanced or reduced logBCF values was performed, providing key leads in the prospective development of more eco-friendly synthetic herbicides.

Socio-ecological insights into the development of agrarian professionals

There is a lack of information about the factors responsible for the effectiveness of environmental policies in Brazilian agriculture. This study aimed at identifying the perception and practices of agrarian professionals. The data analysis was carried out using a survey and methodological approaches focusing on environmental complexity and categorization of environmental actions. Quantitative analysis was based on descriptive statistics. Atmospheric problems were perceived as the main problems for the current and next two generations, while hydrological problems were indicated as those deserving most urgent solutions. On the other hand, the main developed actions and those planned to be carried out were classified within the responsibility category. Because of the reductionist perceptions, introduction of the concept of a socio-ecological system is indicated by means of methodological interventions during the development of agrarian professionals; also, in order to stimulate actions related to the competence and citizenship category, a methodological intervention focusing on resilience thinking is proposed. Typical actions of individuals with either reductionist or complex conceptions of the environment can be captured and, therefore, educational strategies can be traced based on the profiles obtained.

Nonformal environmental education: a case study with farmers in a town of the South Minas Gerais state, Brazil

Brazil is a central place in the international agricultural markets and this fact has been demanding environmentally oriented agricultural practices by Brazilian farmers and professionals involved in the agricultural market chain. A concise and structured questionnaire was applied to obtain the environmental perception of a group of Brazilian farmers in a town of the south Minas Gerais state, using herbicides as the topic for a case study. A highly variable opinion about taking the environment into account when choosing the most appropriate herbicide was found. Anyway, efficacy has been indicated as the most important factor when choosing an herbicide, followed by the environment and price. The outcomes from the questionnaires, i.e. the insufficient conception and importance given to environment when choosing the herbicide, motivated the creation of a teaching-learning model for the nonformal environmental education using the concept of socio-ecological resilience. This routine puts in practice the resilience thinking currently invoked as a major tool to achieve the conservation of the socio-ecological system, as well as it is complimentary to the outcome-oriented optimization for conservation theory. For the case study about farmers and the use of herbicides, we conclude that a complex reasoning and, ultimately, pro-environmental actions can be improved after experiencing the recommended model for environmental education.