ABSTRACT The use of no-till conservationist agricultural systems as well as intercropping in the Cerrado biome are practices that increase soil organic matter (SOM) due to the deposition of straw. This study aimed to quantify the carbon stock and organic fractions of a latosol under off-season monoculture (Sorghum bicolor and Urochloa ruziziensis) and intercropping (S. bicolor-U. ruziziensis) systems, in Rio Verde, state of Goiás, Brazil. Soil samples were collected from different layers: 0-10, 10-20 and 20-40 cm. The following variables were determined: organic carbon content, carbon stock, dry matter and fractions of organic matter (labile and mineral). The results showed that the organic fractions of the soil are modified according to the adopted management. Intercropping of S. bicolor and U. ruziziensis increased the carbon stock, with the presence of more labile organic fractions on the soil surface, while the use of U. ruziziensis enhances the production of recalcitrant organic fractions, promoting greater preservation of the soil organic matter.
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.
ABSTRACT: 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.
ABSTRACT Mechanized sugarcane harvest is replacing the historic practice of field burning, due to environmental concerns of the particulate and emissions during burning. However, the impact of these practices on soil greenhouse gas (GHG) production potential is not fully known. Thus, the present work quantified the potential production, in 1 g of soil, of greenhouse gases (GHG) in three systems of sugarcane management. The systems were: area with a history of burning sugarcane before harvest (B) and another with two systems of management of “green sugarcane” in two periods of implantation - 5 (G-5) and 10 years (G-10). A laboratory incubation experiment was used to assess the production potentials of carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4) in 1g of soil samples by the different sugarcane management systems. The results of this study demonstrate that the sugarcane management systems had an impact on the potential production of CO2 in the soil. In addition, when the results of gases were divided from convex and concave areas, differences in CO2 patterns between areas B and G-10 were observed, with greater emission in the G-10 area, probably due the residue on the soil surface.
RESUMO O sistema de colheita mecanizado da cana-de-açúcar têm substituido o sistema de queima do canavial devido a preocupações ambientais como a emissão de partículas durante a queima e diversos malefícios ao solo. O impacto dessa prática no potencial de produção de gases do efeito estufa (GEE) no solo ainda demanda estudo. Assim, o presente trabalho quantificou a produção potencial, em 1 g de solo, de gases do efeito estufa em três sistemas de manejo de cana-de-açúcar. As áreas avaliadas foram: uma com histórico de queima do canavial antes da colheita (B) e outras com duas com sistemas de manejo de “cana crua” em dois períodos de implantação - 5 (G-5) e 10 anos (G-10). Um experimento de incubação em laboratório foi montado para avaliar os potenciais de produção de dióxido de carbono (CO2), óxido nitroso (N2O) e metano (CH4) em de 1g de amostras de solo nos diferentes sistemas de manejo de cana-de-açúcar. Os resultados deste estudo demonstram que os sistemas de manejo de cana-de-açúcar apresentaram impacto na produção potencial de CO2 no solo. Além disso, quando dividiu-se os resultados de gases oriundos de áreas convexas e concavas, observou-se diferenças nos padrões de CO2 entre as áreas B e G-10, with greater emission in the G-10 area, possivelmente devido a presença de palhada na superífice do solo.
ABSTRACT 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.
ABSTRACT The sugarcane green harvest system, characterized by mechanized harvesting and the absence of crop burning, affects soil quality by increasing crop residue on the soil surface after harvest; thus, it contributes to improving the physical, chemical, and microbiological properties and influences the soil carbon content and CO2 flux (FCO2). This study aimed to evaluate the spatial and temporal variability of soil FCO2 in sugarcane green harvest systems. The experiment was conducted in two areas of sugarcane in São Paulo, Brazil: the first had a 5-year history of sugarcane green harvest (SG-5) and the second had a longer history of 10 years (SG-10). The temporal FCO2 were evaluated in the dry and rainy periods, and spatial variability in the dry period, and related to soil chemical and physical properties, including organic C porosity, bulk density, soil penetration resistance, mean weight diameter of soil aggregates, clay, P, S, Ca, Mg and Fe. The temporal variability indicated no differences between the dry and rainy periods in SG-10, while in SG-5 soil moisture was increased by 33 % in the rainy period. The spatial variability indicated a different pattern from the temporal one, where FCO2 in SG-10 was correlated with soil temperature, air-filled pore space, total porosity, soil moisture, and the Ca and Mg contents; in the SG-5 area, FCO2 was correlated with soil mean weight diameter of soil aggregates and the sulfur content.
Humic substances result from the degradation of biopolymers of organic residues in the soil due to microbial activity. The objective of this study was to evaluate the influence of three different ecosystems: forest, pasture and maize crop on the formation of soil humic substances relating to their biological and chemical attributes. Microbial biomass carbon (MBC), microbial respiratory activity, nitrification potential, total organic carbon, soluble carbon, humic and fulvic acid fractions and the rate and degree of humification were determined. Organic carbon and soluble carbon contents decreased in the order: forest > pasture > maize; humic and fulvic acids decreased in the order forest > pasture=maize. The MBC and respiratory activity were not influenced by the ecosystems; however, the nitrification potential was higher in the forest than in other soils. The rate and degree of humification were higher in maize soil indicating greater humification of organic matter in this system. All attributes studied decreased significantly with increasing soil depth, with the exception of the rate and degree of humification. Significant and positive correlations were found between humic and fulvic acids contents with MBC, microbial respiration and nitrification potential, suggesting the microbial influence on the differential formation of humic substances of the different ecosystems.