984 resultados para tool-soil interaction


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To express the negative effects of soil compaction, some researchers use critical values for soil mechanical strength that severely impair plant growth. The aim of this study was to identify this critical compaction depth, to test the functionality of a new, portable penetrometer developed from a spring dynamometer, and compare it to an electronic penetrometer traditionally used in compaction studies of agricultural soils. Three soils with distinct texture were conventionally tilled using a disk plow, and cultivated with different plant species. The critical soil resistance defined to establish critical compaction depth was equal to 1.5 MPa. The results of the new equipment were similar to the electronic penetrometer, indicating its viability as a tool for assessing the soil physical conditions for plant growth.

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Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

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One of the main problems faced by humanity is pollution caused by residues resulting from the production and use of goods, e.g, sewage sludge. Among the various alternatives for its disposal, the agricultural use seems promising. The purpose of this study was to evaluate the hydraulic conductivity and interaction of soil with sandy-silty texture, classified as Spodosols, from the Experimental Station Itapirema - IPA, in Goiana, state of Pernambuco, in mixtures with sewage sludge from the Mangueira Sewage Treatment Station, in the city of Recife, Pernambuco at rates of 25, 50 and 75 Mg ha-1. Tests were conducted to let water percolate the natural saturated soil and soil-sludge mixtures to characterize their physical, chemical, and microstructural properties as well as hydraulic conductivity. Statistical data analysis showed that the presence of sewage sludge in soils leads to an increase of the < 0.005 mm fraction, reduction in real specific weight and variation in optimum moisture content from 11.60 to 12.90 % and apparent specific dry weight from 17.10 and 17.50 kN m-3. In the sludge-soil mixture, the quartz grains were covered by sludge and filling of the empty soil macropores between grains. There were changes in the chemical characteristics of soil and effluent due to sewage sludge addition and a small decrease in hydraulic conductivity. The results indicate the possibility that soil acidity influenced the concentrations of the elements found in the leachate, showing higher levels at higher sludge doses. It can be concluded that the leaching degree of potentially toxic elements from the sewage sludge treatments does not harm the environment.

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Considering that the soil aggregation reflects the interaction of chemical, physical and biological soil factors, the aim of this study was evaluate alterations in aggregation, in an Oxisol under no-tillage (NT) and conventional tillage (CT), since over 20 years, using as reference a native forest soil in natural state. After analysis of the soil profile (cultural profile) in areas under forest management, samples were collected from the layers 0-5, 5-10, 10-20 and 20-40 cm, with six repetitions. These samples were analyzed for the aggregate stability index (ASI), mean weighted diameter (MWD), mean geometric diameter (MGD) in the classes > 8, 8-4, 4-2, 2-1, 1-0.5, 0.5-0.25, and < 0.25 mm, and for physical properties (soil texture, water dispersible clay (WDC), flocculation index (FI) and bulk density (Bd)) and chemical properties (total organic carbon - COT, total nitrogen - N, exchangeable calcium - Ca2+, and pH). The results indicated that more intense soil preparation (M < NT < PC) resulted in a decrease in soil stability, confirmed by all stability indicators analyzed: MWD, MGD, ASI, aggregate class distribution, WDC and FI, indicating the validity of these indicators in aggregation analyses of the studied soil.

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Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

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The concept of soil quality is currently the subject of great discussion due to the interaction of soil with the environment (soil-plant-atmosphere) and practices of human intervention. However, concepts of soil quality relate quality to agricultural productivity, but assessment of soil quality in an agronomic context may be different from its assessment in natural areas. The aim of this study was to assess physical quality indices, the S index, soil aeration capacity (ACt/Pt), and water storage capacity (FC/Pt) of the soil from a permanent plot in the Caetetus Ecological Reserve (Galia, São Paulo, Brazil) under a seasonal semideciduous forest and compare them with the reference values for soil physical quality found in the literature. Water retention curves were used for that purpose. The S values found were higher than the proposed limit for soil physical quality (0.035). The A and E horizons showed the highest values because their sandy texture leads to a high slope of the water retention curve. The B horizons showed the lowest S values because their natural density leads to a lower slope of the water retention curve. The values found for ACt/Pt and FC/Pt were higher and lower than the idealized limits. The values obtained from these indices under natural vegetation can provide reference values for soils with similar properties that undergo changes due to anthropic activities. All the indices evaluated were effective in differentiating the effects of soil horizons in the natural hydro-physical functioning of the soils under study.

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The graphical representation of spatial soil properties in a digital environment is complex because it requires a conversion of data collected in a discrete form onto a continuous surface. The objective of this study was to apply three-dimension techniques of interpolation and visualization on soil texture and fertility properties and establish relationships with pedogenetic factors and processes in a slope area. The GRASS Geographic Information System was used to generate three-dimensional models and ParaView software to visualize soil volumes. Samples of the A, AB, BA, and B horizons were collected in a regular 122-point grid in an area of 13 ha, in Pinhais, PR, in southern Brazil. Geoprocessing and graphic computing techniques were effective in identifying and delimiting soil volumes of distinct ranges of fertility properties confined within the soil matrix. Both three-dimensional interpolation and the visualization tool facilitated interpretation in a continuous space (volumes) of the cause-effect relationships between soil texture and fertility properties and pedological factors and processes, such as higher clay contents following the drainage lines of the area. The flattest part with more weathered soils (Oxisols) had the highest pH values and lower Al3+ concentrations. These techniques of data interpolation and visualization have great potential for use in diverse areas of soil science, such as identification of soil volumes occurring side-by-side but that exhibit different physical, chemical, and mineralogical conditions for plant root growth, and monitoring of plumes of organic and inorganic pollutants in soils and sediments, among other applications. The methodological details for interpolation and a three-dimensional view of soil data are presented here.

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Arsenic is a metalloid highly toxic to plants and animals, causing reduced plant growth and various health problems for humans and animals. Silicon, however, has excelled in alleviating stress caused by toxic elements in plants. The aim of this study was to investigate the effects of Si in alleviating As stress in maize plants grown in a nutrient solution and evaluate the potential of the spectral emission parameters and the red fluorescence (Fr) and far-red fluorescence (FFr) ratio obtained in analysis of chlorophyll fluorescence in determination of this interaction. An experiment was carried out in a nutrient solution containing a toxic rate of As (68 μmol L-1) and six increasing rates of Si (0, 0.25, 0.5, 1.0, 1.5, and 2.0 mmol L-1). Dry matter production and concentrations of As, Si, and photosynthetic pigments were then evaluated. Chlorophyll fluorescence was also measured throughout plant growth. Si has positive effects in alleviating As stress in maize plants, evidenced by the increase in photosynthetic pigments. Silicon application resulted in higher As levels in plant tissue; therefore, using Si for soil phytoremediation may be a promising choice. Chlorophyll fluorescence analysis proved to be a sensitive tool, and it can be successfully used in the study of the ameliorating effects of Si in plant protection, with the Fr/FFr ratio as the variable recommended for identification of temporal changes in plants.

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The description of the fate of fertilizer-derived nitrogen (N) in agricultural systems is an essential tool to enhance management practices that maximize nutrient use by crops and minimize losses. Soil erosion causes loss of nutrients such as N, causing negative effects on surface and ground water quality, aside from losses in agricultural productivity by soil depletion. Studies correlating the percentage of fertilizer-derived N (FDN) with soil erosion rates and the factors involved in this process are scarce. The losses of soil and fertilizer-derived N by water erosion in soil under conventional tillage and no tillage under different rainfall intensities were quantified, identifying the intervening factors that increase loss. The experiment was carried out on plots (3.5 × 11 m) with two treatments and three replications, under simulated rainfall. The treatments consisted of soil with and soil without tillage. Three successive rainfalls were applied in intervals of 24 h, at intensities of 30 mm/h, 30 mm/h and 70 mm/h. The applied N fertilizer was isotopically labeled (15N) and incorporated into the soil in a line perpendicular to the plot length. Tillage absence resulted in higher soil losses and higher total nitrogen losses (TN) by erosion induced by the rainfalls. The FDN losses followed another pattern, since FDN contributions were highest from tilled plots, even when soil and TN losses were lowest, i.e., the smaller the amount of eroded sediment, the greater the percentage of FDN associated with these. Rain intensity did not affect the FDN loss, and losses were greatest after less intense rainfalls in both treatments.

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ABSTRACT Groundwater management depends on the knowledge on recharge rates and water fluxes within aquifers. The recharge is one of the water cycle components most difficult to estimate. As a result, despite the chosen method, the estimates are subject to uncertainties that can be identified by means of comparison with other approaches. In this study, groundwater recharge estimates based on the water balance in the unsaturated zone is assessed. Firstly, the approach is evaluated by comparing the results with those of another method. Then, the estimates are used as inputs in a transient groundwater flow model in order to assess how the water table would respond to the obtained recharges rates compared to measured levels. The results suggest a good performance of the adopted approach and, despite some inherent limitations, it has advantages over other methods since the data required are easier to obtain.

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The genotypic differences on growth and yield of common bean (Phaseolus vulgaris L.) in response to P supply were evaluated in a field experiment under biological N2 fixation. Eight cultivars were grown at two levels of applied P (12 and 50 kg ha-1 of P -- P1 and P2 respectively), in randomized block design in factorial arrangement. Vegetative biomass was sampled at three ontogenetic stages. The effects of genotype and phosphorus were significant for most traits, but not the genotype ´ phosphorus interaction. The cultivars presented different patterns of biomass production and nutrient accumulation, particularly on root system. At P1, P accumulation persisted after the beginning of pod filling, and P translocation from roots to shoots was lower. The nodule senescence observed after flowering might have reduced N2 fixation during pod filling. The responses of vegetative growth to the higher P supply did not reflect with the same magnitude on yield, which increased only 6% at P2; hence the harvest index was lower at P2. The cultivars with highest yields also presented lower grain P concentrations. A sub-optimal supply of N could have limited the expression of the yield potential of cultivars, reducing the genotypic variability of responses to P levels.

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The atomic force microscope is not only a very convenient tool for studying the topography of different samples, but it can also be used to measure specific binding forces between molecules. For this purpose, one type of molecule is attached to the tip and the other one to the substrate. Approaching the tip to the substrate allows the molecules to bind together. Retracting the tip breaks the newly formed bond. The rupture of a specific bond appears in the force-distance curves as a spike from which the binding force can be deduced. In this article we present an algorithm to automatically process force-distance curves in order to obtain bond strength histograms. The algorithm is based on a fuzzy logic approach that permits an evaluation of "quality" for every event and makes the detection procedure much faster compared to a manual selection. In this article, the software has been applied to measure the binding strength between tubuline and microtubuline associated proteins.

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One of the most striking results of the human (and mammalian) genomes is the low number of protein-coding genes. To-date, the main molecular mechanism to increase the number of different protein isoforms and functions is alternative splicing. However, a less-known way to increase the number of protein functions is the existence of multifunctional, multitask, or ‘‘moonlighting’’, proteins. By and large, moonlighting proteins are experimentally disclosed by serendipity. Proteomics is becoming one of the very active areas of biomedical research, which permits researchers to identify previously unseen connections among proteins and pathways. In principle, protein–protein interaction (PPI) databases should contain information on moonlighting proteins and could provide suggestions to further analysis in order to prove the multifunctionality. As far as we know, nobody has verified whether PPI databases actually disclose moonlighting proteins. In the present work we check whether well-established moonlighting proteins present in PPI databases connect with their known partners and, therefore, a careful inspection of these databases could help to suggest their different functions. The results of our research suggest that PPI databases could be a valuable tool to suggest multifunctionality.

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This Phase I report describes a preliminary evaluation of a new compaction monitoring system developed by Caterpillar, Inc. (CAT), for use as a quality control and quality assurance (QC/QA) tool during earthwork construction operations. The CAT compaction monitoring system consists of an instrumented roller with sensors to monitor machine power output in response to changes in soil machine interaction and is fitted with a global positioning system (GPS) to monitor roller location in real time. Three pilot tests were conducted using CAT’s compaction monitoring technology. Two of the sites were located in Peoria, Illinois, at the Caterpillar facilities. The third project was an actual earthwork grading project in West Des Moines, Iowa. Typical construction operations for all tests included the following steps: (1) aerate/till existing soil; (2) moisture condition soil with water truck (if too dry); (3) remix; (4) blade to level surface; and (5) compact soil using the CAT CP-533E roller instrumented with the compaction monitoring sensors and display screen. Test strips varied in loose lift thickness, water content, and length. The results of the study show that it is possible to evaluate soil compaction with relatively good accuracy using machine energy as an indicator, with the advantage of 100% coverage with results in real time. Additional field trials are necessary, however, to expand the range of correlations to other soil types, different roller configurations, roller speeds, lift thicknesses, and water contents. Further, with increased use of this technology, new QC/QA guidelines will need to be developed with a framework in statistical analysis. Results from Phase I revealed that the CAT compaction monitoring method has a high level of promise for use as a QC/QA tool but that additional testing is necessary in order to prove its validity under a wide range of field conditions. The Phase II work plan involves establishing a Technical Advisor Committee, developing a better understanding of the algorithms used, performing further testing in a controlled environment, testing on project sites in the Midwest, and developing QC/QA procedures.

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The aim of this work was to evaluate whether terrestrial model ecosystems (TMEs) are a useful tool for the study of the effects of litter quality, soil invertebrates and mineral fertilizer on litter decomposition and plant growth under controlled conditions in the tropics. Forty-eight intact soil cores (17.5-cm diameter, 30-cm length) were taken out from an abandoned rubber plantation on Ferralsol soil (Latossolo Amarelo) in Central Amazonia, Brazil, and kept at 28ºC in the laboratory during four months. Leaf litter of either Hevea pauciflora (rubber tree), Flemingia macrophylla (a shrubby legume) or Brachiaria decumbens (a pasture grass) was put on top of each TME. Five specimens of either Pontoscolex corethrurus or Eisenia fetida (earthworms), Porcellionides pruinosus or Circoniscus ornatus (woodlice), and Trigoniulus corallinus (millipedes) were then added to the TMEs. Leaf litter type significantly affected litter consumption, soil microbial biomass and nitrate concentration in the leachate of all TMEs, but had no measurable effect on the shoot biomass of rice seedlings planted in top soil taken from the TMEs. Feeding rates measured with bait lamina were significantly higher in TMEs with the earthworm P. corethrurus and the woodlouse C. ornatus. TMEs are an appropriate tool to assess trophic interactions in tropical soil ecossistems under controlled laboratory conditions.