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The construction of the hydroelectric power plant of Ilha Solteira, in state of São Paulo, was initiated in the 1960s, when an average, 8.60 m of soil depth was removed, resulting in a degraded area. A plan for the recovery of the area started in 2005 in Selvíria /MS with the use of plant species adapted to the Cerrado biome. This study aimed to evaluate the soil macrofauna of an area under recovery by using different types of soil cover (1- bare soil (control); 2- native Cerrado vegetation; 3- specie Astronium fraxinifolium; 4- Astronium fraxinifolium + Canavalia ensiformis; 5- Astronium fraxinifolium + Raphanus sativus; 6- Astronium fraxinifolium + Brachiaria decumbens + sewage sludge). Soil macrofauna was evaluated in 2005, 2006 and 2007 using the direct collection method and manual counting. Number of species, diversity and uniformity index were determined. Principal component analysis (PCA) and cluster analysis were used for data interpretation. Results showed that treatment 6 (Astronium fraxinifolium+ Brachiaria decumbens+ sewage sludge) increased the soil macrofauna population by approximately 4 to 6 times more than the other types of cover after three years of evaluation. And the PCA and cluster analysis showed the approximation of the data between treatment 6 and Cerrado, which represents the most appropriate treatment for the recovery of the degraded soil.(AU)

A construção da usina hidrelétrica de Ilha Solteira, no interior de São Paulo, foi iniciada nos anos 1960, quando foi retirado, em média, 8,60 m de solo em profundidade, dando origem a uma área degradada. Com isso, iniciou-se em 2005 um plano de recuperação da área no município de Selvíria/MS com plantio de espécies vegetais adaptadas ao bioma Cerrado. Assim, este trabalho teve como objetivo avaliar a macrofauna do solo de uma área em processo de recuperação com plantio de diferentes tipos de cobertura vegetal (1- solo nu (testemunha); 2- vegetação nativa de Cerrado; 3- espécie arbórea Astronium fraxinifolium; 4- Astronium fraxinifolium + Canavalia ensiformis; 5- Astronium fraxinifolium + Raphanus sativus; 6- Astronium fraxinifolium + Brachiaria decumbens + lodo de esgoto). A macrofauna de solo foi avaliada em 2005, 2006 e 2007 utilizando o método de coleta direta e contagem manual. Foram determinados: quantidade de espécies e índices de diversidade e uniformidade. As análises de componentes principals (PCA) e de cluster foram utilizadas para interpretação de dados. Os resultados mostraram que o tratamento 6 (Astronium fraxinifolium + Brachiaria decumbens + lodo de esgoto) aumentou a população de macrofauna do solo em aproximadamente 4 a 6 vezes mais que os demais tipos de cobertura vegetal após três anos de avaliação. As análises de PCA e de cluster mostraram aproximação dos dados do tratamento 6 às condições ambientais naturais de Cerrado, indicando ser o tratamento mais adequado para a recuperação do solo degradado.(AU)

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ABSTRACT: The construction of the hydroelectric power plant of Ilha Solteira, in state of São Paulo, was initiated in the 1960s, when an average, 8.60 m of soil depth was removed, resulting in a degraded area. A plan for the recovery of the area started in 2005 in Selvíria /MS with the use of plant species adapted to the Cerrado biome. This study aimed to evaluate the soil macrofauna of an area under recovery by using different types of soil cover (1- bare soil (control); 2- native Cerrado vegetation; 3- specie Astronium fraxinifolium; 4- Astronium fraxinifolium + Canavalia ensiformis; 5- Astronium fraxinifolium + Raphanus sativus; 6- Astronium fraxinifolium + Brachiaria decumbens + sewage sludge). Soil macrofauna was evaluated in 2005, 2006 and 2007 using the direct collection method and manual counting. Number of species, diversity and uniformity index were determined. Principal component analysis (PCA) and cluster analysis were used for data interpretation. Results showed that treatment 6 (Astronium fraxinifolium+ Brachiaria decumbens+ sewage sludge) increased the soil macrofauna population by approximately 4 to 6 times more than the other types of cover after three years of evaluation. And the PCA and cluster analysis showed the approximation of the data between treatment 6 and Cerrado, which represents the most appropriate treatment for the recovery of the degraded soil.

RESUMO: A construção da usina hidrelétrica de Ilha Solteira, no interior de São Paulo, foi iniciada nos anos 1960, quando foi retirado, em média, 8,60 m de solo em profundidade, dando origem a uma área degradada. Com isso, iniciou-se em 2005 um plano de recuperação da área no município de Selvíria/MS com plantio de espécies vegetais adaptadas ao bioma Cerrado. Assim, este trabalho teve como objetivo avaliar a macrofauna do solo de uma área em processo de recuperação com plantio de diferentes tipos de cobertura vegetal (1- solo nu (testemunha); 2- vegetação nativa de Cerrado; 3- espécie arbórea Astronium fraxinifolium; 4- Astronium fraxinifolium + Canavalia ensiformis; 5- Astronium fraxinifolium + Raphanus sativus; 6- Astronium fraxinifolium + Brachiaria decumbens + lodo de esgoto). A macrofauna de solo foi avaliada em 2005, 2006 e 2007 utilizando o método de coleta direta e contagem manual. Foram determinados: quantidade de espécies e índices de diversidade e uniformidade. As análises de componentes principals (PCA) e de cluster foram utilizadas para interpretação de dados. Os resultados mostraram que o tratamento 6 (Astronium fraxinifolium + Brachiaria decumbens + lodo de esgoto) aumentou a população de macrofauna do solo em aproximadamente 4 a 6 vezes mais que os demais tipos de cobertura vegetal após três anos de avaliação. As análises de PCA e de cluster mostraram aproximação dos dados do tratamento 6 às condições ambientais naturais de Cerrado, indicando ser o tratamento mais adequado para a recuperação do solo degradado.

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The Random Forest algorithm is a data mining technique used for classifying attributes in order of importance to explain the variation in an attribute-target, as soil CO2 flux. This study aimed to identify prediction of soil CO2 flux variables in management systems of sugarcane through the machine-learning algorithm called Random Forest. Two different management areas of sugarcane in the state of São Paulo, Brazil, were selected: burned and green. In each area, we assembled a sampling grid with 81 georeferenced points to assess soil CO2 flux through automated portable soil gas chamber with measuring spectroscopy in the infrared during the dry season of 2011 and the rainy season of 2012. In addition, we sampled the soil to evaluate physical, chemical, and microbiological attributes. For data interpretation, we used the Random Forest algorithm, based on the combination of predicted decision trees (machine learning algorithms) in which every tree depends on the values of a random vector sampled independently with the same distribution to all the trees of the forest. The results indicated that clay content in the soil was the most important attribute to explain the CO2 flux in the areas studied during the evaluated period. The use of the Random Forest algorithm originated a model with a good fit (R2 = 0.80) for predicted and observed values.(AU)

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The use of data mining is a promising alternative to predict soil respiration from correlated variables. Our objective was to build a model using variable selection and decision tree induction to predict different levels of soil respiration, taking into account physical, chemical and microbiological variables of soil as well as precipitation in renewal of sugarcane areas. The original dataset was composed of 19 variables (18 independent variables and one dependent (or response) variable). The variable-target refers to soil respiration as the target classification. Due to a large number of variables, a procedure for variable selection was conducted to remove those with low correlation with the variable-target. For that purpose, four approaches of variable selection were evaluated: no variable selection, correlation-based feature selection (CFS), chisquare method (χ2) and Wrapper. To classify soil respiration, we used the decision tree induction technique available in the Weka software package. Our results showed that data mining techniques allow the development of a model for soil respiration classification with accuracy of 81 %, resulting in a knowledge base composed of 27 rules for prediction of soil respiration. In particular, the wrapper method for variable selection identified a subset of only five variables out of 18 available in the original dataset, and they had the following order of influence in determining soil respiration: soil temperature > precipitation > macroporosity > soilmoisture > potential acidity.

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The use of data mining is a promising alternative to predict soil respiration from correlated variables. Our objective was to build a model using variable selection and decision tree induction to predict different levels of soil respiration, taking into account physical, chemical and microbiological variables of soil as well as precipitation in renewal of sugarcane areas. The original dataset was composed of 19 variables (18 independent variables and one dependent (or response) variable). The variable-target refers to soil respiration as the target classification. Due to a large number of variables, a procedure for variable selection was conducted to remove those with low correlation with the variable-target. For that purpose, four approaches of variable selection were evaluated: no variable selection, correlation-based feature selection (CFS), chisquare method (χ2) and Wrapper. To classify soil respiration, we used the decision tree induction technique available in the Weka software package. Our results showed that data mining techniques allow the development of a model for soil respiration classification with accuracy of 81 %, resulting in a knowledge base composed of 27 rules for prediction of soil respiration. In particular, the wrapper method for variable selection identified a subset of only five variables out of 18 available in the original dataset, and they had the following order of influence in determining soil respiration: soil temperature > precipitation > macroporosity > soilmoisture > potential acidity.(AU)

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Soil CO2 emissions are regarded as one of the largest flows of the global carbon cycle and small changes in their magnitude can have a large effect on the CO2 concentration in the atmosphere. Thus, a better understanding of this attribute would enable the identification of promoters and the development of strategies to mitigate the risks of climate change. Therefore, our study aimed at using data mining techniques to predict the soil CO2 emission induced by crop management in sugarcane areas in Brazil. To do so, we used different variable selection methods (correlation, chi-square, wrapper) and classification (Decision tree, Bayesian models, neural networks, support vector machine, bagging with logistic regression), and finally we tested the efficiency of different approaches through the Receiver Operating Characteristic (ROC) curve. The original dataset consisted of 19 variables (18 independent variables and one dependent (or response) variable). The association between cover crop and minimum tillage are effective strategies to promote the mitigation of soil CO2 emissions, in which the average CO2 emissions are 63 kg ha-1 day-1. The variables soil moisture, soil temperature (Ts), rainfall, pH, and organic carbon were most frequently selected for soil CO2 emission classification using different methods for attribute selection. According to the results of the ROC curve, the best approaches for soil CO2 emission classification were the following: (I)-the Multilayer Perceptron classifier with attribute selection through the wrapper method, that presented rate of false positive of 13,50%, true positive of 94,20% area under the curve (AUC) of 89,90% (II)-the Bagging classifier with logistic regression with attribute selection through the Chi-square method, that presented rate of false positive of 13,50%, true positive of 94,20% AUC of 89,90%. However, the (I) approach stands out in relation to (II) for its higher positive class accuracy (high CO2 emission) and lower computational cost.

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Ventilation systems are incorporated at intensive poultry farms to control environment conditions and thermal comfort of broilers. The ventilation system operates based on environmental data, particularly measured by sensors of temperature and relative humidity. Sensors are placed at different positions of the facility. Quality, number and positioning of the sensors are critical factors to achieve an efficient performance of the system. For this reason, a strategic positioning of the sensors associated to controllers could support the maintenance and management of the microclimate inside the facility. This research aims to identify the three most representative points for the positioning of sensors in order to support the ventilation system during the critical period from 12h00 to 15h00 on summer days. Temperature, relative humidity and wind speed were measured in four different tunnel ventilated barns at the final stage of the production cycle. The descriptive analysis was performed on these data. The Temperature and Humidity Index (THI) was also calculated. Then, the geostatistical analysis of THI was performed by GS+ and the position of sensors was determined by ordinary kriging. The methodology was able to detect the most representative points for the positioning of sensors in a case study (southeastern Brazil). The results suggested that this strategic positioning would help controllers to obtain a better inference of the microclimate during the studied period (the hottest microclimate), considered critical in Brazil. In addition, these results allow developing a future road map for a decision support system based on 24 h monitoring of the ventilation systems in broiler houses.

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Ventilation systems are incorporated at intensive poultry farms to control environment conditions and thermal comfort of broilers. The ventilation system operates based on environmental data, particularly measured by sensors of temperature and relative humidity. Sensors are placed at different positions of the facility. Quality, number and positioning of the sensors are critical factors to achieve an efficient performance of the system. For this reason, a strategic positioning of the sensors associated to controllers could support the maintenance and management of the microclimate inside the facility. This research aims to identify the three most representative points for the positioning of sensors in order to support the ventilation system during the critical period from 12h00 to 15h00 on summer days. Temperature, relative humidity and wind speed were measured in four different tunnel ventilated barns at the final stage of the production cycle. The descriptive analysis was performed on these data. The Temperature and Humidity Index (THI) was also calculated. Then, the geostatistical analysis of THI was performed by GS+ and the position of sensors was determined by ordinary kriging. The methodology was able to detect the most representative points for the positioning of sensors in a case study (southeastern Brazil). The results suggested that this strategic positioning would help controllers to obtain a better inference of the microclimate during the studied period (the hottest microclimate), considered critical in Brazil. In addition, these results allow developing a future road map for a decision support system based on 24 h monitoring of the ventilation systems in broiler houses.(AU)

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The harvesting system of green sugarcane, characterized by mechanized harvesting and no crop burning, affects soil quality by increasing the remaining straw left on the soil surface after harvesting, thus, contributing to the improvement of physical, chemical, and microbiological soil attributes, influencing CO2 fluxes. This study aimed to evaluate CO2 fluxes and their relation to soil properties in sugarcane crops under different harvesting managements: burned (B), Green harvesting for 5 years (G-5) and Green harvesting for ten years (G-10). For this, a 1 ha sampling grid with 30 points was installed in each area, all located in the Northeast of São Paulo State, Brazil. In each point, CO2 fluxes were measured and the soil was sampled to analyze the microbial biomass, physical (soil moisture and temperature, mean weight diameter, bulk density, clay, macroporosity and microporosity) and chemical characterization (pH, organic C, base saturation and P). The CO2 fluxes were divided into four quantitative criteria: high, moderate, low and very low from the Statistical Division (mean, first quartile, median and third quartile) and the other data were classified according this criterion. The Principal Component Analysis (PCA) was used to identify the main soil attributes that influence CO2 fluxes. The results showed that G-10 CO2 fluxes were 28 and 41 % higher than those in the G-5 and B treatments, respectively. The PCA analysis showed that macroporosity was the main soil attribute that influenced the high CO2 fluxes.

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The harvesting system of green sugarcane, characterized by mechanized harvesting and no crop burning, affects soil quality by increasing the remaining straw left on the soil surface after harvesting, thus, contributing to the improvement of physical, chemical, and microbiological soil attributes, influencing CO2 fluxes. This study aimed to evaluate CO2 fluxes and their relation to soil properties in sugarcane crops under different harvesting managements: burned (B), Green harvesting for 5 years (G-5) and Green harvesting for ten years (G-10). For this, a 1 ha sampling grid with 30 points was installed in each area, all located in the Northeast of São Paulo State, Brazil. In each point, CO2 fluxes were measured and the soil was sampled to analyze the microbial biomass, physical (soil moisture and temperature, mean weight diameter, bulk density, clay, macroporosity and microporosity) and chemical characterization (pH, organic C, base saturation and P). The CO2 fluxes were divided into four quantitative criteria: high, moderate, low and very low from the Statistical Division (mean, first quartile, median and third quartile) and the other data were classified according this criterion. The Principal Component Analysis (PCA) was used to identify the main soil attributes that influence CO2 fluxes. The results showed that G-10 CO2 fluxes were 28 and 41 % higher than those in the G-5 and B treatments, respectively. The PCA analysis showed that macroporosity was the main soil attribute that influenced the high CO2 fluxes.(AU)

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Machinery traffic in sugarcane (Saccharumsp.) plantations reduces soil physical quality, and hinders both root development and crop yield. We evaluated the physical quality of an Oxisol and the development of sugarcane roots under controlled traffic. The treatments assessed were: without controlled machinery traffic (WCT), controlled traffic by adjusting the tractor and infield wagons to a 3.0 m track width with the operator guiding the machinery (CT1) and the previous treatment using real time kinematic / global positioning system (RTK / GPS) precision auto steer (CT2). Soil samples were collected from the planting rows, seedbed and inter-row center to determine the least limiting water range (LLWR) and soil porosity from scanned 2-D images. The root dry mass was sampled from monoliths, separated from the soil by washing through a 2-mm sieve and dried in an oven. A higher LLWR was observed in the planting row under CT1 and CT2 than under WCT. The planting row had a predominance of complex pores with a diameter > 500 µm in the 0.15-0.27 m depth layer under CT1 and CT2. In the planting rows under WCT, the root dry mass was only 44 % of that measured under CT2. Benefits regarding soil physical quality and growth roots were observed when the tractor-wagon track width was adjusted based on the sugarcane spacing using either precision auto steering or manual operation of the machinery.(AU)

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Machinery traffic in sugarcane (Saccharumsp.) plantations reduces soil physical quality, and hinders both root development and crop yield. We evaluated the physical quality of an Oxisol and the development of sugarcane roots under controlled traffic. The treatments assessed were: without controlled machinery traffic (WCT), controlled traffic by adjusting the tractor and infield wagons to a 3.0 m track width with the operator guiding the machinery (CT1) and the previous treatment using real time kinematic / global positioning system (RTK / GPS) precision auto steer (CT2). Soil samples were collected from the planting rows, seedbed and inter-row center to determine the least limiting water range (LLWR) and soil porosity from scanned 2-D images. The root dry mass was sampled from monoliths, separated from the soil by washing through a 2-mm sieve and dried in an oven. A higher LLWR was observed in the planting row under CT1 and CT2 than under WCT. The planting row had a predominance of complex pores with a diameter > 500 µm in the 0.15-0.27 m depth layer under CT1 and CT2. In the planting rows under WCT, the root dry mass was only 44 % of that measured under CT2. Benefits regarding soil physical quality and growth roots were observed when the tractor-wagon track width was adjusted based on the sugarcane spacing using either precision auto steering or manual operation of the machinery.

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O objetivo deste trabalho foi analisar diferentes intensidades de amostragem do solo com relação à precisão na análise geoestatística e interpolação de mapas, para fins de agricultura de precisão em área de cana-de-açúcar. O solo foi coletado em duas grades regulares na profundidade de 0,00-0,20m para análise granulométrica (área 1) e da fertilidade do solo (área 2). Foram comparadas intensidades de amostragem do solo: 208, 105, 58 e 24 pontos na área 1 e 206, 102 e 53 pontos na área 2. Os dados foram submetidos à análise descritiva e geoestatística. Os variogramas construídos com 105 pontos não diferem dos variogramas com 208 pontos, fato que não ocorre para 58 e 24 pontos. O aumento do intervalo de amostragem e a redução do número de pontos promovem o maior erro na estimativa por krigagem. As amostragens com mais de 100 pontos por área não resultaram em melhorias significativas no erro da estimativa por krigagem, nem diferiram na quantidade de insumos aplicados em campo.

The objective of this study was to analyze different intensities of soil sampling for accuracy in geostatistical analysis and interpolation maps for precision agriculture in the sugarcane area. Soil samples were collected at two regular grids at a depth of 0.00 to 0.20m for granulometric analysis (area 1) and soil fertility (area 2). We compared soil sampling intensities: 208, 105, 58 and 24 points in Area 1 and 206, 102 and 53 points in Area 2. The data were submitted to descriptive analysis and geostatistics. The variograms constructed with 105 points didn't differ from variograms with 208 points, which doesn't occur for 58 and 24 points. The increase of sampling interval and reducing the number of points promote greater error in kriging. Samples with more than 100 points per area did not result in significant improvements in the error of kriging, or differed in the amount of fertilizer applied to the field.

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O objetivo deste trabalho foi analisar diferentes intensidades de amostragem do solo com relação à precisão na análise geoestatística e interpolação de mapas, para fins de agricultura de precisão em área de cana-de-açúcar. O solo foi coletado em duas grades regulares na profundidade de 0,00-0,20m para análise granulométrica (área 1) e da fertilidade do solo (área 2). Foram comparadas intensidades de amostragem do solo: 208, 105, 58 e 24 pontos na área 1 e 206, 102 e 53 pontos na área 2. Os dados foram submetidos à análise descritiva e geoestatística. Os variogramas construídos com 105 pontos não diferem dos variogramas com 208 pontos, fato que não ocorre para 58 e 24 pontos. O aumento do intervalo de amostragem e a redução do número de pontos promovem o maior erro na estimativa por krigagem. As amostragens com mais de 100 pontos por área não resultaram em melhorias significativas no erro da estimativa por krigagem, nem diferiram na quantidade de insumos aplicados em campo.(AU)

The objective of this study was to analyze different intensities of soil sampling for accuracy in geostatistical analysis and interpolation maps for precision agriculture in the sugarcane area. Soil samples were collected at two regular grids at a depth of 0.00 to 0.20m for granulometric analysis (area 1) and soil fertility (area 2). We compared soil sampling intensities: 208, 105, 58 and 24 points in Area 1 and 206, 102 and 53 points in Area 2. The data were submitted to descriptive analysis and geostatistics. The variograms constructed with 105 points didn't differ from variograms with 208 points, which doesn't occur for 58 and 24 points. The increase of sampling interval and reducing the number of points promote greater error in kriging. Samples with more than 100 points per area did not result in significant improvements in the error of kriging, or differed in the amount of fertilizer applied to the field.(AU)

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Os solos cultivados intensivamente e inadequadamente são degradados, assim como a construção de obras civis no meio rural executada sem atender à legislação. O trabalho objetivou definir a interferência do lodo de esgoto na recuperação de atributos de um Latossolo Vermelho. O experimento foi implantado em 2004, em Selviria (MS). Os tratamentos utilizados foram: T1-vegetação de cerrado; T2-solo exposto sem tratamento para recuperação; T3-solo cultivado com eucalipto e braquiária sem o uso do lodo de esgoto e adubação mineral; T4-solo cultivado com eucalipto e braquiária com adubação mineral; T5-solo cultivado com eucalipto e braquiária com uso de 30Mg ha-1 de lodo de esgoto e; T6-solo cultivado com eucalipto e braquiária com uso de 60Mg ha-1 de lodo de esgoto. Nas camadas do solo de 0,00-0,05; 0,05-0,10; 0,10-0,20 e de 0,20-0,30m, foram avaliados os atributos físico-hídricos e teor de matéria orgânica. Os tratamentos com adubação mineral e orgânica estão agindo de forma semelhante para a recuperação dos atributos físico-hídricos e do teor de matéria orgânica. Em solos degradados pela construção de obras civis a aplicação de 30 a 60mg de lodo de esgoto ha-1 recupera as suas propriedades físico-hídricas.

Intensively and inadequately managed soils and the civil construction industry in the rural area that are unconcerned with specific legislation, result in several problems in the environment. The objective of the present study was to evaluate the influence of sewage sludge on the recovery of hydro-physical properties of an Oxisol. The experiment was implanted in 2004, in Selvíria, Mato Grosso do Sul, Brazil. The six experimental treatments were arranged according to a randomized complete-block design with four replications. The experimental treatments were: 1 - Native Cerrado vegetation; 2 - degraded soil without treatment for soil recovery; 3 - Eucalyptus citriodora planting and Brachiaria decumbens sowing and no sewage sludge or mineral fertilization use; 4 - Eucalyptus citriodora planting and Brachiaria decumbens sowing in soil enriched with mineral fertilizer; 5 - Eucalyptus citriodora planting and Brachiaria decumbens sowing in soil enriched with 30Mg ha-1 sewage sludge, and 6- Eucalyptus citriodora planting and Brachiaria decumbens sowing in soil enriched with 60Mg ha-1 sewage sludge. Hydro-physical properties and the soil organic matter content were characterized at 0.00-to-0.05; 0.05-to-0.10; 0.10-to-0.20 and 0.20-to-0.30m layers in the soil. Mineral and organic fertilization treatments showed similar effects on the recovery of the hydro-physical properties and organic matter content of the degraded soil. The hydro-physical properties and organic matter content of Cerrado soils degraded due to civil construction activities can be recovered by the use of 30 to 60Mg sewage sludge ha-1.

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Um dos desafios da agricultura de precisão é oferecer subsídios para a definição de unidades de manejo para posteriores intervenções. Portanto, o objetivo deste trabalho foi avaliar os atributos químicos do solo e a produtividade da cultura de cana-de-açúcar por meio da geoestatística e mineração de dados pela indução da árvore de decisão. A produtividade da cana-de-açúcar foi mapeada em uma área de aproximadamente 23ha, utilizando-se o critério de célula, por meio de um monitor de produtividade que permitiu a elaboração de um mapa digital que representa a superfície de produção para a área em estudo. Para determinar os atributos de um Argissolo Vermelho-Amarelo, foram coletadas as amostras no início da safra 2006/2007, utilizando-se uma grade regular de 50 x 50m, nas profundidades de 0,0-0,2m e 0,2-0,4m. Os dados dos atributos do solo e da produtividade foram analisados por meio da técnica de goestatística e classificados em três níveis de produção para indução de árvore de decisão. A árvore de decisão foi induzida no programa SAS Enterprise Miner, sendo utilizado algoritmo baseado na redução de entropia. As variáveis altitude e potássio apresentaram os maiores valores de correlação com a produtividade de cana-de-açúcar. A indução de árvores de decisão permitiu verificar que a altitude é a variável com maior potencial para interpretar os mapas de produtividade de cana-de-açúcar, auxiliando na agricultura de precisão e mostrando-se uma ferramenta adequada para o estudo de definição de zonas de manejo em área cultivada com essa cultura.

One of the challenges of precision agriculture is to offer subsidies for the definition of management units for posterior interventions. Therefore, the objective of this work was to evaluate soil chemical attributes and sugarcane yield with the use of geostatistics and data mining by decision tree induction. Sugarcane yield was mapped in a 23ha field, applying the cell criterion, by using a yield monitor that allowed the elaboration of a digital map representing the surface of production of the studied area. To determine the soil attributes, soil samples were collected at the beginning of the harvest in 2006/2007 using a regular grid of 50 x 50m, in the depths of 0.0-0.2m and 0.2-0.4m. Soil attributes and sugarcane yield data were analyzed by using geostatistics techniques and were classified into three yield levels for the elaboration of the decision tree. The decision tree was induced in the software SAS Enterprise Miner, using an algorithm based on entropy reduction. Altitude and potassium presented the highest values of correlation with sugarcane yield. The induction of decision trees showed that the altitude is the variable with the greatest potential to interpret the sugarcane yield maps, then assisting in precision agriculture and, revealing an adjusted tool for the study of management definition zones in area cropped with sugarcane.

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Em solos sob cultivo de cana-de-açúcar, o tráfego intenso de máquinas agrícolas pode provocar estado de compactação ao solo. Portanto, o objetivo deste trabalho foi caracterizar a variabilidade espacial de atributos físicos e teor de matéria orgânica de um Latossolo Vermelho eutroférrico gibbsítico (sob Basalto) e Latossolo Vermelho distroférrico caulinítico (sob Arenito) nas profundidades de 0,0-0,2m e 0,2-0,4m, em áreas sob cultivo de cana-de-açúcar. Os solos foram amostrados nos pontos de cruzamento de uma malha, com intervalos regulares de 10m, nas profundidades de 0,0-0,2m e 0,2-0,4m, totalizando 100 pontos para cada área de estudo. Em cada ponto da malha, foram determinados a densidade do solo, a macroporosidade, o teor de matéria orgânica e a resistência do solo à penetração. Os atributos físicos mostram valores de resistência do solo à penetração, da densidade do solo e da macroporosidade acima da média para esses solos. As variáveis em estudo apresentaram um maior alcance e menor coeficiente de variação no LVef em comparação com o LVd, nas profundidades em estudo. Recomenda-se maior número de amostragem para os atributos em estudo no Latossolo Vermelho distrófico e na profundidade de 0,2-0,4m.

The intense traffic of agricultural machines in soils cultivated with sugar cane can cause soil compaction. Therefore, the objective of this research was to characterize the spatial variability of soil physical attributes and content organic matter of a eutroferric Red Latosol gibbisitic (under Basalt) and dystroferric Red Latosol caulinitic (under Sandstone) in the depths of 0.0-0.2m and 0.2-0.4m in areas cultivated with sugar cane. Soils were sampled at the crossing points of a grid at regular intervals of 10m and at depths of 0.0-0.2m and 0.2-0.4m. Bulk density, macroporosity, organic matter content and soil penetration resistance were measured for all sampling points. The physical attributes show values of soil penetration resistance, bulk density and macroporosity above average for these soils. The studied variable presented a larger range and minor variation coefficient in the eutroferric Red Latosol (Oxisol Eutrustox) when compared with the dystroferric Red Latosol (Oxisol Haplustox), in the studied depths. It is recommended a bigger number of samples to study the eutroferric Red Latosol attributes and the depth of 0.2-0.4m.

RESUMO

O relevo influencia a variabilidade da textura, uma vez que condiciona o tempo de exposição dos materiais à ação do intemperismo. Neste trabalho, desenvolvido no município de Gavião Peixoto (SP), objetivou-se caracterizar a variabilidade espacial da textura de um Latossolo Vermelho distrófico sob cultivo de citros. A encosta foi dividida em três segmentos: topo, meia encosta e encosta inferior. O solo foi amostrado em malha, com intervalos regulares de 50 m, perfazendo o total de 332 pontos em uma área de 83,5 ha, nas profundidades de 0,0-0,2 m e 0,6-0,8 m. Os dados foram submetidos à análise estatística descritiva e geoestatística (modelagem de semivariogramas e mapas de krigagem). O comportamento espacial da textura de latossolos está diretamente relacionado com as formas do relevo neste estudo, que controla o sentido dos fluxos de água superficial e subsuperficial. O conceito de homogeneidade da distribuição de argila no perfil dos latossolos é uma informação que pode ser ajustada pelo conhecimento do padrão espacial dessa distribuição em diferentes formas do relevo.

Relief influences soil texture variability, since it contributes to the time of exposition of the materials to weathering factors. Our work was carried out in the city of Gavião Peixoto (SP), with the objective of characterizing the spatial variability of texture of a dystrophic Red Latosol cultivated with citrus. The hillside was divided into three segments: top, stocking lean and inferior lean. Soil samples were collected in a grid with regular intervals of 50 m, at the depths of 0.0-0.2 m and 0.6-0.8 m, comprising a total of 332 points in an area of 83.5 ha. The data were submitted to descriptive and geostatistics analyses (semivariogram modeling and kriging maps). The spatial behavior of the texture of oxisols is directly related to the relief forms in this study, which controls the direction of surface and subsurface water flows. The concept of homogeneity of clay distribution in the Oxisol profile is a piece of information that can be adjusted by knowing the spatial pattern of this distribution in different relief forms.

RESUMO

A compactação do solo pode ser considerada uma das principais causas de degradação de pastagens. Entre várias técnicas de mobilização do solo para rompimento de camadas compactadas, a escarificação apresenta aspectos positivos para um manejo conservacionista. Objetivou-se, neste trabalho, avaliar as alterações ocorridas na resistência do solo à penetração, porosidade do solo e densidade do solo de um Latossolo Vermelho-Amarelo, sob pastagem mediante sua escarificação. Implementou-se um experimento em uma área de Brachiaria decumbens Stapf. em Nova Odessa (SP), utilizando um escarificador com discos de corte e ponteiras aladas. A resistência do solo à penetração foi avaliada utilizando um penetrógrafo hidráulico eletrônico e a densidade do solo e porosidade do solo, a partir de amostras indeformadas. As camadas de solo identificadas por análise multivariada da resistência do solo à penetração foram alteradas pela escarificação. A escarificação do solo reduziu significativamente os valores de resistência do solo à penetração. A escarificação do solo promoveu maiores alterações nos atributos físicos na profundidade de 0,0-0,1 m, na entrelinha da passagem das hastes do escarificador.

Soil compaction is considered one of the main causes of pasture degradation. Several techniques can be applied to reduce compacted soil layers. Chisel plowing is one of the farming expedients that present the most positive aspects regarding the soil conservation management. The aim of this study was to evaluate the changes in soil penetration resistance, soil porosity and bulk density in an oxisol soil of a pasture field after chisel plowing. The experiment was set up in Nova Odessa (SP) on a Brachiaria decumbens Stapf. field, using a chisel plow with cutting discs and winged tips. The soil penetration resistance was evaluated with an electronic hydraulic penetrographer, and the porosity and bulk density with undeformed samples. The soil layers identified by multivariate data analysis of the soil penetration resistance were changed by soil scarification. The soil scarification procedure decreased the soil penetration resistance. The soil scarification showed the highest changes in physical attributes in the layer of 0.0-0.1 m, between the lines of the chisel plow shanks.

RESUMO

A pecuária é uma das atividades econômicas mais importantes da região do cerrado, sendo que o sucesso dessa atividade é dependente do sistema de manejo e de gramíneas forrageiras adaptadas às condições edafoclimáticas da região. Objetivou-se, neste tabalho, avaliar os atributos do solo em áreas sob pastagens com capim-Tanzânia (Panicum maximum Jacq. cv. Tanzânia) e braquiarão [Brachiaria brizantha (Hochst ex A. Rich.) Stapf. cv. Marandu], em sistema de sequeiro e irrigado no município de Rio Verde, GO. O experimento foi instalado no Centro Tecnológico Comigo, em um Latossolo Vermelho-Amarelo Distrófico típico, em 16 parcelas com 450m² cada. Adotou-se o delineamento em blocos completamente casualisados, referindo-se aos quatro tratamentos: capim-Tanzânia e braquiarão com e sem irrigação, com quatro repetições. Foram realizadas análises de atributos físicos (estabilidade de agregados) e químicas (pH, cálcio, magnésio, potássio, fósforo, acidez potencial, capacidade de troca catiônica, saturação por bases e conteúdo de matéria orgânica). Os atributos químicos variaram em ambas as profundidades, decorrentes principalmente da ação da calagem e adubação do solo independente da ausência ou presença de irrigação. Os tratamentos com capim-Tanzânia e braquiarão sem irrigação apresentaram os maiores teores de matéria orgânica e tiveram os maiores valores do diâmetro médio geométrico (DMG). A maior porcentagem dos agregados ficou retida na peneira de > 2,0mm de malha. A irrigação não afetou a produção de massa seca do capim-Tanzânia e braquiarão.

The livestock production is one of the most important economic activities in the Brazilian savanna and its success depends on the management system used as well as the use of grasses adapted to the edaphoclimatic conditions of the region. Therefore, the aim of this work was to evaluate the soil attributes under pasture with Tanzania grass (Panicum maximum Jacq. cv. Tanzania) and bread grass [Brachiaria brizantha (Hochst ex A. Rich.) Stapf. cv. Marandu], with and without irrigation, in the municipality of Rio Verde, Goiás State, Brazil. The experiment was carried out on an oxisol soil at the Comigo Technological Center, in 16 plots of 450m² each. The experimental design used was the completely randomized blocks with four replications. The treatments consisted of two grass species, Tanzania grass (Panicum maximum) and bread grass (Brachiaria brizantha) and two irrigation treatments, with and without irrigation. The following attributes were determined: aggregate stability, pH, calcium, magnesium, potassium, phosphorus, potential acidity, cation exchange capacity, base saturation, and organic matter content. The chemical attributes varied in both layers mainly due to the liming and fertilization of the soil, independently of the irrigation system. The treatments with Tanzania grass and bread grass without irrigation presented the highest organic matter content and the highest values of DMG. Most of the aggregates had a diameter larger than 2.0 mm. The irrigation management did not affect the dry mass of the grasses studied.