ABSTRACT: 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 > soil moisture > potential acidity.

RESUMO: Este trabalho teve por objetivo avaliar a sensibilidade de isolados dos fungos Metarhizium anisopliae (Metsch.) Sorok. e Beauveria bassiana (Bals). Vuill. ao efeito das radiações solar e ultravioleta e da temperatura. Conídios dos isolados foram expostos, por vários períodos, aos raios de um simulador solar em diversas irradiâncias e a uma lâmpada de raios ultravioleta germicida. Os conídios do isolado de M. anisopliae foram também expostos às temperaturas de 19,5; 24,2 e 31,0ºC, e os do isolado de B. bassiana a 19,4; 20,8 e 28,3ºC, e 18,7; 23,8 e 30,9ºC. Avaliou-se a germinação de conídios pelo teste de viabilidade. Os isolados dos fungos se mostraram bastantes sensíveis aos raios do simulador solar e aos raios ultravioleta. A germinação de ambos sofreu significativa redução a partir de 30 minutos de exposição à radiação do simulador solar. O efeito mais severo foi evidenciado pelo isolado de B. bassiana, com grande redução da germinação dos conídios em todas as irradiâncias testadas. A sensibilidade à radiação ultravioleta também foi grande, pois ocorreu acentuada redução da germinação dos conídios do isolado de M. anisopliae (38,2%) e de B. bassiana (65%) já aos 30 segundos de exposição. A temperatura afetou a viabilidade de ambos os fungos. Temperaturas entre 23,8 e 31ºC favoreceram a germinação dos conídios, enquanto temperaturas próximas de 20ºC dificultaram a germinação.

ABSTRACT: This study aimed to access the sensibility of isolates of the fungus Metarhizium anisopliae (Metsch.) Sorok. and Beauveria bassiana (Bals.) Vuill. to the effect of solar and ultraviolet radiation and temperature. Conidia were exposed for various periods to the rays from a solar simulator at various irradiances, and to light germicidal ultraviolet rays. Conidia of the isolate of M. anisopliae were also exposed to temperatures of 19.5, 24.2 and 31.0ºC and the isolate of B. bassiana to 19.4, 20.8 and 28.3ºC, and also to 18.7, 23.8 and 30.9ºC. The germination of conidia was evaluated by the viability test. The fungal isolates showed to be very sensitive to the solar simulator and ultraviolet rays. Germination of both was significantly decreased starting from 30 minutes of exposure to the rays of the solar simulator. The most severe effect was evidenced by the isolate of B. bassiana with great reduction in conidia germination in all the tested irradiances. Sensitivity to ultraviolet radiation was also great, showing a marked reduction in the germination of M. anisopliae (38.2%) and B. bassiana (65%) conidia after 30 seconds of exposure. The temperature affected the viability of both fungi. Temperatures ranging of 23.8 to 31ºC favor the germination of conidia while temperatures around 20ºC constrained germination.

ABSTRACTSoil CO2 emissions (fCO2) in agricultural areas have been widely studied in global climate change research, but its characterization and quantification are restricted to small areas. Because spatial and time variability affect emissions, tools need to be developed to predict fCO2 for large areas. This study aimed to investigate soil magnetic susceptibility (MS) and its correlation with fCO2 in an agricultural environment. The experiment was carried out on a Typic Eutrudox located in Guariba-SP, Brazil. Results showed that there was negative spatial correlation between fCO2 and the magnetic susceptibility of Air Dried Soil (MSADS) up to 34.3 m distant. However, the fCO2 had no significant correlation with MSADS, magnetic susceptibility of sand (MSSAND) nor clay (MSCLAY). However, MSADS could be a supplemental mean of identifying regions of high fCO2 potential over large areas.

Soil CO2 emission (FCO2) is one of the main sources of carbon release into the atmosphere. Moreover, FCO2 is related to soil attributes governing the transfer of gases from soil to the atmosphere. This study aimed firstly to describe the spatial variability of hematite (Hm), goethite (Gt), iron extracted with sodium dithionite-citrate-bicarbonate (Fed) contents, soil CO2 emission (FCO2) and free-water porosity (FWP) and secondly, to develop statistical models to predict the above mentioned factors in an Oxisol cultivated under manual harvesting of sugarcane (Saccharumspp.) in southeastern Brazil. The study was conducted on an irregular 50 m × 50 m grid containing 89 points, each 0.5-10 m apart. The 0-0.1 m soil layer at each sampling point was used to assess soil FCO2, moisture and total pore volume. The results were subjected to descriptive statistical and geostatistical analyses using auto- and cross-semivariograms. All soil attributes exhibited a spatial dependence structure and the experimental semivariograms fitted spherical and exponential models. The Gt content was the individual attribute that exhibited the highest linear and spatial correlation, especially with FCO2. We were able to use diffuse reflectance spectroscopy to map large areas, which allows for easy identification and estimation of soil attributes such as FCO2 and FWP. Geostatistical techniques faciltate the interpretation of spatial relationships between soil respiration and the examined properties.

Soil CO2 emission (FCO2) is governed by the inherent properties of the soil, such as bulk density (BD). Mapping of FCO2 allows the evaluation and identification of areas with different accumulation potential of carbon. However, FCO2 mapping over larger areas is not feasible due to the period required for evaluation. This study aimed to assess the quality of FCO2 spatial estimates using values of BD as secondary information. FCO2 and BD were evaluated on a regular sampling grid of 60 m × 60 m comprising 141 points, which was established on a sugarcane area. Four scenarios were defined according to the proportion of the number of sampling points of FCO2 to those of BD. For these scenarios, 67 (F67), 87 (F87), 107 (F107) and 127 (F127) FCO2 sampling points were used in addition to 127 BD sampling points used as supplementary information. The use of additional information from the BD provided an increase in the accuracy of the estimates only in the F107, F67 and F87 scenarios, respectively. The F87 scenario, with the approximate ratio between the FCO2 and BD of 1.00:1.50, presented the best relative improvement in the quality of estimates, thereby indicating that the BD should be sampled at a density 1.5 time greater than that applied for the FCO2. This procedure avoided problems related to the high temporal variability associated with FCO2, which enabled the mapping of this variable to be elaborated in large areas.