Allelopathy: driving mechanisms governing its activity in agriculture.

Allelopathy determines the dynamics of plant species in different environments. Understanding this biological phenomenon could help to develop applications in both natural and agricultural systems. This review summarizes the genetic and environmental characteristics that control the production and release of allelochemicals in agroecosystems. This study highlights the current understanding of the environmental changes caused by allelochemicals and summarizes the knowledge about the mechanisms of action of these compounds. Finally, it reviews novel applications of allelopathy in agricultural production systems, including the role of allelochemicals in consortia and their potential use in no-tillage cropping systems through cover crops or mulches.

Detecting outliers and asserting consistency in agriculture ground truth information by using temporal VI data from modis.

Collecting ground truth data is an important step to be accomplished before performing a supervised classification. However, its quality depends on human, financial and time ressources. It is then important to apply a validation process to assess the reliability of the acquired data. In this study, agricultural infomation was collected in the Brazilian Amazonian State of Mato Grosso in order to map crop expansion based on MODIS EVI temporal profiles. The field work was carried out through interviews for the years 2005-2006 and 2006-2007. This work presents a methodology to validate the training data quality and determine the optimal sample to be used according to the classifier employed. The technique is based on the detection of outlier pixels for each class and is carried out by computing Mahalanobis distances for each pixel. The higher the distance, the further the pixel is from the class centre. Preliminary observations through variation coefficent validate the efficiency of the technique to detect outliers. Then, various subsamples are defined by applying different thresholds to exclude outlier pixels from the classification process. The classification results prove the robustness of the Maximum Likelihood and Spectral Angle Mapper classifiers. Indeed, those classifiers were insensitive to outlier exclusion. On the contrary, the decision tree classifier showed better results when deleting 7.5% of pixels in the training data. The technique managed to detect outliers for all classes. In this study, few outliers were present in the training data, so that the classification quality was not deeply affected by the outliers.

Chemical changes and heavy metal partitioning in an oxisol cultivated with maize (Zea mays, L.) after 5 years disposal of a domestic and an industrial sewage sludge.

The need for solutions to minimize the negative environmental impacts of anthropogenic activities Fhas increased. Sewage sludge is composed of predominantly organic matter and can be used to improve soil characteristics, such as fertility. Therefore, its application in agriculture is an adequate alternative for its final disposal. However, there is a lack of information on its long-term effects on soil changes in tropical areas. Thus, the objectives of this study were to determine (i) the effect of sewage sludge application on heavy metal build-up in soil and maize grains and leaves, and (ii) the effects of soil amendment with sewage sludge on the chemical properties of a Brazilian oxisol. Besides the increasing levels of Zn, Cu, Ni, and Cr, amending soil with sewage sludge also alters the distribution of these metals by increasing the mobile Phases, which correlated significantly with the increase in metal extraction with two single extractants, Mehlich 1 and DTPA (Diethylene triamine pentaacetic acid). The levels of Fe, Mn, Zn, and Cu in maize grains and leaves increased with the type and rate of sewage sludge application. Nevertheless, metal build-up in soil and plants was within the allowed limits. Significant differences were also found in soil characteristics like humic fractionation with the applied sewage doses. The data obtained does not indicate any expressive drawbacks in the use of sewage sludge as a soil amendment, as the heavy metal concentrations observed are unlikely to cause any environmental or health problems, even overestimated loadings, and are in accordance with the Brazilian regulations on farming land biosolid disposal.

Spatial variability of satured soil hydraulic conductivity in the region of Araguaia River - Brazil.

This study evaluates the spatial variability of saturated hydraulic conductivity in the soil in an area of 51,850 ha at the headwaters of the Araguaia River MT/GO. This area is highly vulnerable because it is a location of recharging through natural water infiltration of the Guarani Aquifer System and an area of intense increases in agriculture since its adoption by growers in the last 30 years. Soil samples were collected at 383 points, geographically located by GPS. The samples were collected from depths of 0 - 20 cm and 60 - 80 cm. Exploratory statistics and box-plot were used in the descriptive analysis and semivariogram were constructed to determine the spatial model. The exploratory analysis showed that the mean hydraulic conductivity in the superficial layer was less than at the level of 60-80 cm; however, the greatest variability evaluated with a coefficient of variation also was from this layer. Data tended towards a normal distribution. These results can be explained by the greater soil compaction in the superficial layer. The semivariogram models, adjusted for the two layers, were exponential and demonstrated moderate and strong dependence, with ranges of 5000 and 3000 utm respectively. It was concluded that soil use is influencing the spatial distribution model of the hydraulic conductivity in the region.