Crop rotation and succession in a no-tillage system: Implications for CO2 emission and soil attributes.

This study aimed to quantify and characterize the relationship between soil CO2 emission (FCO2) and soil physical, chemical, and microbiological attributes at the end of the agricultural season in an area under a no-tillage system with crop rotation for more than 16 years. Summer crop sequences consisted of corn and soybean monoculture and corn-soybean rotation. Winter crops were corn, millet, pigeon pea, grain sorghum, and crotalaria. Treatments consisted of combinations of three summer crop sequences with five winter crops. Sixteen assessments of FCO2, soil temperature, and soil moisture were carried out under the remaining straw from the combination of summer sequences and winter crops over a 51-day period. Subsequently, soil physical, chemical, and microbiological attributes were assessed at depths of 0-0.10 and 0.10-0.20 m. The experiment was conducted in strips in a randomized block design with three replications. The multivariate analysis showed that the characterization of the pattern of FCO2 and other soil attributes as a function of the management with summer and winter crop residues differed according to the soil layer. In the 0.10-0.20 m layer, no difference was observed between treatments. However, the contents of clay, organic matter, sum of bases, microbial biomass carbon, dehydrogenase and amylase enzyme activity, and humification index of organic matter in the most superficial soil layer (up to 0.10 m) contributed to characterize differences in FCO2. Therefore, FCO2 variation is more influenced by soil microorganisms and the management in the most superficial layer. Soil attributes such as organic matter, enzyme activity, and biomass carbon had a higher influence on FCO2 dynamics in the 0-0.10 m layer, while soil density became a significant factor in FCO2 variation in the subsurface layer (0.10-0.20 m). Strategies such as soil management under no-tillage systems can be considered very efficient because, regardless of the residues generated by different crops, it contributes significantly to reduce FCO2, assisting in mitigating greenhouse gases in agriculture. Further studies on soil metagenomic analyses with quantification of functional genes related to carbon cycle will allow establishing direct relationships between FCO2 and microbiota dynamics and soil management since microbiota is the most sensitive bioindicator to changes in the environment.

Forecasting the spatiotemporal variability of soil CO2 emissions in sugarcane areas in southeastern Brazil using artificial neural networks.

Carbon dioxide (CO2) is considered one of the main greenhouse effect gases and contributes significantly to global climate change. In Brazil, the agricultural areas offer an opportunity to mitigate this effect, especially with the sugarcane crop, since, depending on the management system, sugarcane stores large amounts of carbon, thereby removing it from the atmosphere. The CO2 production in soil and its transport to the atmosphere are the results of biochemical processes such as the decomposition of organic matter and roots and the respiration of soil organisms, a phenomenon called soil CO2 emissions (FCO2). The objective of the study was to investigate the use of neural networks with backpropagation algorithm to predict the spatial patterns of soil CO2 emission during short periods in sugarcane areas. FCO2 values were collected in three commercial crop areas in the São Paulo state, southeastern Brazil, registered through the LI-8100 system during the years 2008 (Motuca), 2010 (Guariba city), and 2012 (Pradópolis), in the period after the mechanical harvesting (green cane). A neural network multilayer perceptron with a backpropagation algorithm was applied to estimate the FCO2 in 2012, using data from 2008 and 2010 as training for the neural network. The neural network initially presented a mean absolute percentage error (MAPE) of 18.3852 and a coefficient of determination (R2) of 0.9188. Data obtained from the observed and estimated values of FCO2 present moderate spatial dependence, and it is observed from the maps of the spatial pattern of the CO2 flow that the results from the neural network show considerable similarity to the observed data. The model results identify the higher and lower characteristics in sample points of CO2 emissions and produce an overestimation of the range of spatial dependence (0.45 m) and an underestimation of the interpolated values in the field (R2 = 0.80; MAPE = 12.0591), when compared to the actual soil CO2 emission values. Therefore, the results indicate that the artificial neural network provides reliable estimates for the evaluation of FCO2 from data of the soil's physical and chemical attributes and describes the spatial variability of FCO2 in sugarcane fields, thereby contributing to the reduction of uncertainties associated with FCO2 accountings in these areas.

Sensibilidade de isolados de fungos entomopatogênicos às radiações solar, ultravioleta e à temperatura / Sensibility of isolates of entomopathogenic fungi to solar radiation, ultraviolet rays and temperature

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.(AU)

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.(AU)