An image segmentation based on a genetic algorithm for determining soil coverage by crop residues

Determination of the soil coverage by crop residues after ploughing is a fundamental element of Conservation Agriculture. This paper presents the application of genetic algorithms employed during the fine tuning of the segmentation process of a digital image with the aim of automatically quantifying the residue coverage. In other words, the objective is to achieve a segmentation that would permit the discrimination of the texture of the residue so that the output of the segmentation process is a binary image in which residue zones are isolated from the rest. The RGB images used come from a sample of images in which sections of terrain were photographed with a conventional camera positioned in zenith orientation atop a tripod. The images were taken outdoors under uncontrolled lighting conditions. Up to 92% similarity was achieved between the images obtained by the segmentation process proposed in this paper and the templates made by an elaborate manual tracing process. In addition to the proposed segmentation procedure and the fine tuning procedure that was developed, a global quantification of the soil coverage by residues for the sampled area was achieved that differed by only 0.85% from the quantification obtained using template images. Moreover, the proposed method does not depend on the type of residue present in the image. The study was conducted at the experimental farm “El Encín” in Alcalá de Henares (Madrid, Spain).

Real-time image processing for crop/weed discrimination in maize fields

This paper presents a computer vision system that successfully discriminates between weed patches and crop rows under uncontrolled lighting in real-time. The system consists of two independent subsystems, a fast image processing delivering results in real-time (Fast Image Processing, FIP), and a slower and more accurate processing (Robust Crop Row Detection, RCRD) that is used to correct the first subsystem's mistakes. This combination produces a system that achieves very good results under a wide variety of conditions. Tested on several maize videos taken of different fields and during different years, the system successfully detects an average of 95% of weeds and 80% of crops under different illumination, soil humidity and weed/crop growth conditions. Moreover, the system has been shown to produce acceptable results even under very difficult conditions, such as in the presence of dramatic sowing errors or abrupt camera movements. The computer vision system has been developed for integration into a treatment system because the ideal setup for any weed sprayer system would include a tool that could provide information on the weeds and crops present at each point in real-time, while the tractor mounting the spraying bar is moving

Crop row detection in maize fields inspired on the human visual perception

This paper proposes a new method, oriented to image real-time processing, for identifying crop rows in maize fields in the images. The vision system is designed to be installed onboard a mobile agricultural vehicle, that is, submitted to gyros, vibrations, and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of two main processes: image segmentation and crop row detection. The first one applies a threshold to separate green plants or pixels (crops and weeds) from the rest (soil, stones, and others). It is based on a fuzzy clustering process, which allows obtaining the threshold to be applied during the normal operation process. The crop row detection applies a method based on image perspective projection that searches for maximum accumulation of segmented green pixels along straight alignments. They determine the expected crop lines in the images. The method is robust enough to work under the above-mentioned undesired effects. It is favorably compared against the well-tested Hough transformation for line detection.

Automatic expert system based on images for accuracy crop row detection in maize fields

This paper proposes an automatic expert system for accuracy crop row detection in maize fields based on images acquired from a vision system. Different applications in maize, particularly those based on site specific treatments, require the identification of the crop rows. The vision system is designed with a defined geometry and installed onboard a mobile agricultural vehicle, i.e. submitted to vibrations, gyros or uncontrolled movements. Crop rows can be estimated by applying geometrical parameters under image perspective projection. Because of the above undesired effects, most often, the estimation results inaccurate as compared to the real crop rows. The proposed expert system exploits the human knowledge which is mapped into two modules based on image processing techniques. The first one is intended for separating green plants (crops and weeds) from the rest (soil, stones and others). The second one is based on the system geometry where the expected crop lines are mapped onto the image and then a correction is applied through the well-tested and robust Theil–Sen estimator in order to adjust them to the real ones. Its performance is favorably compared against the classical Pearson product–moment correlation coefficient.

Nematodes as indicators of the effect of soil fumigants on soil functioning

Debido al futuro incierto de la mayor parte de los fumigantes edáficos usados actualmente en la Unión Europea, que pueden implicar riesgos para la salud humana/animal y el medio ambiente, es necesario desarrollar programas de manejo integrado para el control de plagas de cultivos. Estos programas se incluyen como obligatorios en el Reglamento (EC) No. 1107/2009. De acuerdo con este Reglamento, es obligatoria la evaluación del riesgo asociado al uso de productos fitosanitarios sobre los organismos edáficos no diana y sus funciones, además de llevar a cabo ensayos con diferentes especies indicadoras para obtener datos de toxicidad que puedan ser usados posteriormente en la evaluación de riesgo. Sin embargo, la baja representatividad de algunas de estas especies indicadoras en el área Mediterránea supone una gran limitación. En esta situación, el Panel Científico de Productos Fitosanitarios y sus Residuos de la Autoridad Europea en Seguridad Alimentaria (EFSA), ha señalado la necesidad de modificar los datos ecotoxicológicos requeridos para evaluar los efectos adversos de los productos fitosanitarios de una manera más integrada, incluyendo criterios funcionales y estructurales mediante organismos como bacterias, hongos, protozoos y nematodos. De este modo, la EFSA ha recomendado el uso de los nematodos en la evaluación de la funcionalidad y estructura del suelo. Los nematodos están globalmente distribuidos y son morfológicamente diversos; esto junto con su gran abundancia y diversidad de respuestas a las perturbaciones edáficas, los convierte en indicadores adecuados del estado del suelo. Puesto que los nematodos interaccionan con muchos otros organismos que participan en diferentes eslabones de la red trófica edáfica, jugando papeles importantes en procesos edáficos esenciales en los agroescosistemas, la diversidad de nematodos es, a menudo, usada como indicador biológico de los efectos de las prácticas agrícolas en el estado del suelo. En los últimos años, diferentes índices basados en la comunidad nematológica han facilitado la interpretación de datos complejos sobre la ecología del suelo. Los índices de la red trófica edáfica, basados en la abundancia de grupos funcionales definidos como grupos C-P y grupos tróficos, permiten la evaluación de la funcionalidad de la red trófica edáfica. Por otra parte, la dificultad en la identificación taxonómica de nematodos para explicar su uso limitado como indicadores ecológicos, es ampliamente discutida, y existe cierta controversia en cuanto a la eficacia de los diferentes métodos de identificación de nematodos. Se argumenta que la identificación morfológica es difícil y puede llevar mucho tiempo debido a la falta de expertos especializados, y se afirma que las técnicas moleculares pueden resolver algunas limitaciones de las técnicas morfológicas como la identificación de juveniles. Sin embargo, los métodos de identificación molecular tienen también limitaciones; la mayoría de las bases de datos de secuencias de ADN están fuertemente orientadas hacia los nematodos fitoparásitos, los cuales representan sólo una parte de la comunidad edáfica de nematodos, mientras que hay poca información disponible de nematodos de vida libre a pesar de representar la mayoría de los nematodos edáficos. Este trabajo se centra en el estudio de los efectos de fumigantes edáficos en la funcionalidad del suelo a través del uso de diferentes indicadores basados en la comunidad de nematodos, como los índices de la red trófica, índices de diversidad, abundancia de los taxones más relevantes etc. También se han analizado otros indicadores funcionales relacionados con la supresividad edáfica, el ciclo de nutrientes o la actividad de la microfauna del suelo. En el capítulo 1, la diversidad de nematodos estudiada en una explotación comercial de fresa y sus alrededores durante dos campañas consecutivas en el suroeste español, fue baja en los suelos fumigados con fumigantes químicos ambas campañas y, aunque se observó una recuperación a lo largo de la campaña en la zona tratada, los suelos fumigados mostraron una condición perturbada permanente. La comunidad de nematodos estuvo más asociada al ciclo de nutrientes en la zona sin cultivar que en los suelos cultivados, y se observó poca relación entre la biomasa de las plantas y la estructura de la comunidad de nematodos. Los surcos sin tratar dentro de la zona de cultivo funcionaron como reservorio tanto de nematodos fitoparásitos como beneficiosos; sin embargo estas diferencias entre los surcos y los lomos de cultivo no fueron suficientes para mantener la supresividad edáfica en los surcos. Los suelos tratados fueron menos supresivos que los suelos sin tratar, y se observaron correlaciones positivas entre la supresividad edáfica y la estructura de la red trófica edáfica y la diversidad de nematodos. En el capítulo 2, se evaluaron los efectos de dos pesticidas orgánicos con efecto nematicida y dos nematicidas convencionales sobre las propiedades físico químicas del suelo, la diversidad de nematodos y la biomasa de las plantas en condiciones experimentales en dos tipos de suelo: suelos agrícolas poco diversos y suelos provenientes de una zona de vegetación natural muy diversos. El mayor efecto se observó en el tratamiento con neem, el cual indujo un gran incremento en el número de dauerlarvas en los suelos pobres en nutrientes, mientras que el mismo tratamiento indujo un incremento de poblaciones de nematodos bacterívoros, más estables y menos oportunistas, en los suelos del pinar ricos en materia orgánica. En el capítulo 3, se comparó la eficacia de métodos moleculares (TRFLP, Terminal Restriction Fragment Length Polymorphism) y morfológicos (microscopía de alta resolución) para la identificación de diferentes comunidades denematodos de España e Irlanda. Se compararon estadísticamente las diferencias y similitudes en la diversidad de nematodos, otros indicadores ecológicos y de la red trófica edáfica. Las identificaciones mediante el uso de TRFLP sólo detectó un porcentaje de los taxones presentes en las muestras de suelo identificadas morfológicamente, y los nematodos omnívoros y predadores no fueron detectados molecularmente en nuestro estudio. Los índices calculados en base a los nematodos micróboros mostraron más similitud cuando se identificaron morfológica y molecularmente que los índices basados en grupos tróficos más altos. Nuestros resultados muestran que, al menos con la técnica usada en este estudio, la identificación morfológica de nematodos es una herramienta fiable y más precisa que la identificación molecular, puesto que en general se obtiene una mayor resolución en la identificación de nematodos. En el capítulo 4, se estudiaron también los efectos de los nematicidas químicos sobre la comunidad de nematodos y la biomasa de las plantas en condiciones experimentales de campo, donde se aplicaron en una rotación de cultivo judía-col durante un ciclo de cultivo. Se aplicaron dos tipos de enmiendas orgánicas con el objetivo de mitigar el efecto negativo de los productos fitosanitarios sobre la diversidad edáfica. El efecto de los nematicidas sobre las propiedades del suelo y sobre la comunidad de nematodos fue más agudo que el efecto de las enmiendas. La incorporación de los restos de cosecha al final del ciclo de cultivo de la judía tuvo un gran efecto sobre la comunidad de nematodos, y aunque el número total de nematodos incrementó al final del experimento, se observó una condición perturbada permanente de la red trófica edáfica a lo largo del experimento. ABSTRACT Due to the uncertain future of the soil fumigants most commonly used in the EU, that might involve risks for human/animal health and the environment, there is a need to develop new integrated pest management programs, included as mandatory in the Regulation (EC) No. 1107/2009, to control crop diseases. According to this Regulation, evaluating the risk associated to the use of the plant production products (PPP) on non-target soil fauna and their function, and developing assays with different indicator species to obtain toxicity data to be used in the risk evaluation is mandatory. However, the low representativeness of some of these indicator species in the Mediterranean area is a relevant limitation. In this situation, the Scientific Panel of Plant Protection Products and their Residues of the European Food Safety Authority (EFSA) has pointed out the necessity of modifying the ecotoxicological data set required to evaluate non-target effects of PPP in a more integrated way, including structural and functional endpoints with organism such as bacteria, fungi, protists and nematodes. Thus, EFSA has recommended the use of nematodes in the assessment of the functional and structural features of the soil. Nematodes are globally distributed and morphologically diverse, and due to their high abundance and diversity of responses to soil disturbance, they are suitable indicators of the soil condition. Since nematodes interact with many other organisms as participants in several links of the soil food web, playing important roles in essential soil processes in agroecosystems, nematode diversity is often used as a biological indicator of the effects of agricultural practices on soil condition. In the last years, various indices based on soil nematode assemblages, have facilitated the interpretation of complex soil ecological data. Soil food web indices based on the abundances of functional guilds defined by C-P groups and trophic groups, permit evaluating soil food web functioning. On the other hand, the difficulty of nematode taxonomical identification is commonly argued to explain their limited used as ecological indicators, and there is a certain controversy in terms of the efficacy of various nematode identification methods. It is argued that the morphological identification is difficult and time consuming due to the lack of specialist knowledge, and it is claimed that molecular techniques can solve some limitations of morphological techniques such as the identification of juveniles. Nevertheless, molecular identification methods are limited too, since most of the DNA-based databases are strongly oriented towards plant-parasitic nematodes that represent only a fraction of the soil nematode community, while there is little information available on free-living nematodes, which represent most soil nematodes. This work focuses on the study of the effects of soil fumigants on soil functioning through the use of different indicators based on soil nematode community as soil food web indices, diversity indices, the abundance of more relevant taxa etc. Other functional indicators related to soil suppressiveness, nutrient cycling, or the activity of soil microfauna have been also studied. In chapter 1, nematode diversity assessed in a commercial strawberry farm and its surroundings for two consecutive growing seasons in southern Spain, was low in fumigated soils with chemical pesticides throughout both seasons and, although yearly recovery occurred within the treated fields, fumigated soils showed a permanent perturbed condition. The nematode community was more closely associated to nutrient cycling in the non-cropped than in the cropped soils, and the link between plant biomass and nematode community structure was weak. Non-treated furrows within the treated fields were a reservoir of both beneficial and plant-parasitic nematodes, but such difference between furrows and beds was not enough to maintain more suppressive soil assemblages in the furrows. Treated soils were less suppressive than unmanaged soils, and there was a positive and significant correlation between soil suppressiveness and soil food web structure and diversity. In chapter 2, the effects of two organic pesticides with nematicide effect and two chemical nematicides on soil physicalchemical properties, soil nematode diversity and plant biomass in experimental conditions were assessed in two types of soils: low diversity soils from an agricultural farm, and high diversity soils from a natural vegetation area. The larger effect was observed on the neem treatment, which induced a large boost of dauer juveniles in the nutrient-depleted soil, while the same treatment induced the increase of more stable, less opportunistic, populations of generalist bacterivore nematodes in the pine forest soil, rich in organic matter. In chapter 3, comparison of the efficiency of molecular (TRFLP, Terminal Restriction Fragment Length Polymorphism) and morphological (microscopy at high magnification) identification methods was carried out in different nematode communities from five sites of different land uses in Spain and Ireland. Differences and similarities on nematode diversity and other ecological and soil food web indices assessed by both methods, were statistically compared. Molecular identification with TRFLP only detected a percentage of the taxa present in the soil samples identified morphologically, and omnivores and predators were not detected molecularly in our study. Indices involving microbial feeding nematodes were more similar between identification methods than indices involving higher trophic links. Our results show that, at least with the technique used in this study, identifying nematodes morphologically is a reliable and more precise identification tool than molecular identification, since a higher taxonomic resolution is in general obtained compared to TRFLP. In chapter 4, the effect of chemical nematicides on nematode community descriptors and plant biomass was also studied in field conditions in an experimental area in which dazomet and dimethyl disulfide was applied in a bean-cabbage rotation system for a single season. Organic amendments were incorporated into the soil with the aim of mitigate the negative effect of the pesticides on soil diversity. The effect of the nematicides was much more noticeable than the effect of the amendments on soil properties and nematode community descriptors. The incorporation of bean crop residues into the soil at the end of bean crop cycle affected soil nematode community descriptors to a great extent, and although total number of nematodes increased at the end of the experiment, a permanent perturbed soil food web condition was observed along the experiment.

Occurrence and analysis of selected pharmaceutical compounds in soil from Spanish agricultural fields

This work describes the analysis of 15 pharmaceutical compounds, belonging to different therapeutic classes (anti-inflammatory/analgesics, lipid regulators, antiepileptics, ?-blockers and antidepressants) and with diverse physical?chemical properties, in Spanish soils with different farmland uses. The studied compounds were extracted from soil by ultrasound-assisted extraction (UAE) and determined, after derivatization, by gas chromatography with mass spectrometric detection (GC?MS). The limits of detection (LODs) ranged from 0.14 ng g?1 (naproxen) to 0.65 ng g?1 (amitriptyline). At least two compounds where detected in all samples, being ibuprofen, salicylic acid, and paracetamol, the most frequently detected compounds. The highest levels found in soil were 47 ng g?1 for allopurinol and 37 ng g?1 for salicylic acid. The influence of the type of crop and the sampling area on the levels of pharmaceuticals in soil, as well as their relationship with soil physical?chemical properties, was studied. The frequent and widespread detection of some of these compounds in agricultural soils show a diffuse contamination, although the low levels found do not pose a risk to the environment or the human health.

Community Structure in Soil Porous System

Diffusion controls the gaseous transport process in soils when advective transport is almost null. Knowledge of the soil structure and pore connectivity are critical issues to understand and modelling soil aeration, sequestration or emission of greenhouse gasses, volatilization of volatile organic chemicals among other phenomena. In the last decades these issues increased our attention as scientist have realize that soil is one of the most complex materials on the earth, within which many biological, physical and chemical processes that support life and affect climate change take place. A quantitative and explicit characterization of soil structure is difficult because of the complexity of the pore space. This is the main reason why most theoretical approaches to soil porosity are idealizations to simplify this system. In this work, we proposed a more realistic attempt to capture the complexity of the system developing a model that considers the size and location of pores in order to relate them into a network. In the model we interpret porous soils as heterogeneous networks where pores are represented by nodes, characterized by their size and spatial location, and the links representing flows between them. In this work we perform an analysis of the community structure of porous media of soils represented as networks. For different real soils samples, modelled as heterogeneous complex networks, spatial communities of pores have been detected depending on the values of the parameters of the porous soil model used. These types of models are named as Heterogeneous Preferential Attachment (HPA). Developing an exhaustive analysis of the model, analytical solutions are obtained for the degree densities and degree distribution of the pore networks generated by the model in the thermodynamic limit and shown that the networks exhibit similar properties to those observed in other complex networks. With the aim to study in more detail topological properties of these networks, the presence of soil pore community structures is studied. The detection of communities of pores, as groups densely connected with only sparser connections between groups, could contribute to understand the mechanisms of the diffusion phenomena in soils.

Remote sensing of LAI, chlorophyll and leaf nitrogen pools of crop- and grasslands in five European landscapes.

Leaf nitrogen and leaf surface area influence the exchange of gases between terrestrial ecosystems and the atmosphere, and play a significant role in the global cycles of carbon, nitrogen and water. The purpose of this study is to use field-based and satellite remote-sensing-based methods to assess leaf nitrogen pools in five diverse European agricultural landscapes located in Denmark, Scotland (United Kingdom), Poland, the Netherlands and Italy. REGFLEC (REGularized canopy reFLECtance) is an advanced image-based inverse canopy radiative transfer modelling system which has shown proficiency for regional mapping of leaf area index (LAI) and leaf chlorophyll (CHLl) using remote sensing data. In this study, high spatial resolution (10–20 m) remote sensing images acquired from the multispectral sensors aboard the SPOT (Satellite For Observation of Earth) satellites were used to assess the capability of REGFLEC for mapping spatial variations in LAI, CHLland the relation to leaf nitrogen (Nl) data in five diverse European agricultural landscapes. REGFLEC is based on physical laws and includes an automatic model parameterization scheme which makes the tool independent of field data for model calibration. In this study, REGFLEC performance was evaluated using LAI measurements and non-destructive measurements (using a SPAD meter) of leaf-scale CHLl and Nl concentrations in 93 fields representing crop- and grasslands of the five landscapes. Furthermore, empirical relationships between field measurements (LAI, CHLl and Nl and five spectral vegetation indices (the Normalized Difference Vegetation Index, the Simple Ratio, the Enhanced Vegetation Index-2, the Green Normalized Difference Vegetation Index, and the green chlorophyll index) were used to assess field data coherence and to serve as a comparison basis for assessing REGFLEC model performance. The field measurements showed strong vertical CHLl gradient profiles in 26% of fields which affected REGFLEC performance as well as the relationships between spectral vegetation indices (SVIs) and field measurements. When the range of surface types increased, the REGFLEC results were in better agreement with field data than the empirical SVI regression models. Selecting only homogeneous canopies with uniform CHLl distributions as reference data for evaluation, REGFLEC was able to explain 69% of LAI observations (rmse = 0.76), 46% of measured canopy chlorophyll contents (rmse = 719 mg m−2) and 51% of measured canopy nitrogen contents (rmse = 2.7 g m−2). Better results were obtained for individual landscapes, except for Italy, where REGFLEC performed poorly due to a lack of dense vegetation canopies at the time of satellite recording. Presence of vegetation is needed to parameterize the REGFLEC model. Combining REGFLEC- and SVI-based model results to minimize errors for a "snap-shot" assessment of total leaf nitrogen pools in the five landscapes, results varied from 0.6 to 4.0 t km−2. Differences in leaf nitrogen pools between landscapes are attributed to seasonal variations, extents of agricultural area, species variations, and spatial variations in nutrient availability. In order to facilitate a substantial assessment of variations in Nl pools and their relation to landscape based nitrogen and carbon cycling processes, time series of satellite data are needed. The upcoming Sentinel-2 satellite mission will provide new multiple narrowband data opportunities at high spatio-temporal resolution which are expected to further improve remote sensing capabilities for mapping LAI, CHLl and Nl.

Scaling in Soil and Other Complex Porous Media

Scaling is becoming an increasingly important topic in the earth and environmental sciences as researchers attempt to understand complex natural systems through the lens of an ever-increasing set of methods and scales. The guest editors introduce the papers in this issue’s special section and present an overview of some of the work being done. Scaling remains one of the most challenging topics in earth and environmental sciences, forming a basis for our understanding of process development across the multiple scales that make up the subsurface environment. Tremendous progress has been made in discovery, explanation, and applications of scaling. And yet much more needs to be done and is being done as part of the modern quest to quantify, analyze, and manage the complexity of natural systems. Understanding and succinct representation of scaling properties can unveil underlying relationships between system structure and response functions, improve parameterization of natural variability and heterogeneity, and help us address societal needs by effectively merging knowledge acquired at different scales.

How do various maize crop models vary in their responses to climate change factors?

Comments This article is a U.S. government work, and is not subject to copyright in the United States. Abstract Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha 1 per °C. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

The use of non-reflecting boundary conditions in soil dynamics

In this paper some aspects of the use of non-reflecting boundaries in dynamic problems, analyzed in time domain, are considered. Current trends for treating the above mentioned problems are summarized with a particular emphasis on the use of numerical techniques, such as Boundary Element Method (BEM) or mixed and hybrid formulations, Finite Element Method (FEM) plus BEM. As an alternative to these methods, an easy time domain boundary condition, obtained from the well known consistent transmitting boundary developed by Waas for frequency domain analysis, can be applied to represent the reactions of the unbounded soil on the interest zone. The behaviour of this proposed boundary condition is studied when waves of different frequency to the one used for its obtention are acting on the physical edge of the model. As an application example,an analysis is made of the soil-structure interaction of a rigid strip foundation on a horizontal non-linear elastic layer on bed rock. The results obtained suggest the need of time domain solutions for this type of problem

Computer simulation of random parckings for self-similar particle size distributions in soil and granular materials: porosity and pore size distribution

A 2D computer simulation method of random packings is applied to sets of particles generated by a self-similar uniparametric model for particle size distributions (PSDs) in granular media. The parameter p which controls the model is the proportion of mass of particles corresponding to the left half of the normalized size interval [0,1]. First the influence on the total porosity of the parameter p is analyzed and interpreted. It is shown that such parameter, and the fractal exponent of the associated power scaling, are efficient packing parameters, but this last one is not in the way predicted in a former published work addressing an analogous research in artificial granular materials. The total porosity reaches the minimum value for p = 0.6. Limited information on the pore size distribution is obtained from the packing simulations and by means of morphological analysis methods. Results show that the range of pore sizes increases for decreasing values of p showing also different shape in the volume pore size distribution. Further research including simulations with a greater number of particles and image resolution are required to obtain finer results on the hierarchical structure of pore space.

Intermittent pluri-sink model and the emergence of complex heterogeneity patterns: a simple paradigm for explaining complexity in soil chemical distributions

The spatial complexity of the distribution of organic matter, chemicals, nutrients, pollutants has been demonstrated to have multifractal nature (Kravchenco et al. [1]). This fact supports the possibility of existence of some emergent heterogeneity structure built under the evolution of the system. The aim of this note is providing a consistent explanation to the mentioned results via an extremely simple model.

Spatio-temporal distribution of pyrethroids in soil in Mediterranean paddy fields

Purpose The demand of rice by the increase in population in many countries has intensified the application of pesticides and the use of poor quality water to irrigate fields. The terrestrial environment is one compartment affected by these situations, where soil is working as a reservoir, retaining organic pollutants. Therefore, it is necessary to develop methods to determine insecticides in soil and monitor susceptible areas to be contaminated, applying adequate techniques to remediate them. Materials and methods This study investigates the occurrence of ten pyrethroid insecticides (PYs) and its spatio-temporal variance in soil at two different depths collected in two periods (before plow and during rice production), in a paddy field area located in the Mediterranean coast. Pyrethroids were quantified using gas chromatography?mass spectrometry (GC?MS) after ultrasound-assisted extraction with ethyl acetate. The results obtained were assessed statistically using non-parametric methods, and significant statistical differences (p < 0.05) in pyrethroids content with soil depth and proximity to wastewater treatment plants were evaluated. Moreover, a geographic information system (GIS) was used to monitor the occurrence of PYs in paddy fields and detect risk areas. Results and discussion Pyrethroids were detected at concentrations ?57.0 ng g?1 before plow and ?62.3 ng g?1 during rice production, being resmethrin and cyfluthrin the compounds found at higher concentrations in soil. Pyrethroids were detected mainly at the top soil, and a GIS program was used to depict the obtained results, showing that effluents from wastewater treatment plants (WWTPs) were the main sources of soil contamination. No toxic effects were expected to soil organisms, but it is of concern that PYs may affect aquatic organisms, which represents the worst case scenario. Conclusions A methodology to determine pyrethroids in soil was developed to monitor a paddy field area. The use of water fromWWTPs to irrigate rice fields is one of the main pollution sources of pyrethroids. It is a matter of concern that PYs may present toxic effects on aquatic organisms, as they can be desorbed from soil. Phytoremediation may play an important role in this area, reducing the possible risk associated to PYs levels in soil.

Soil P and cation availability and crop uptake in a forage rotation under conventional and reduced tillage

Long-term conservation tillage can modify vertical distribution of nutrients in soil profiles and alter nutrient availability and yields of crops.