Glyphosate effects on tree species natives from Cerrado and Caatinga Brazilian biome: Assessing sensitivity to two ways of contamination

Glyphosate is applied for dissection in no-till and post-emergence management in transgenic crops in agricultural fields near the Cerrado and Caatinga biomes. These biomes together represent 33.8% of the Brazilian territory, contributing to the maintenance of great world diversity in flora and fauna. Despite actions to protect them, the proximity with agricultural areas and intense use of glyphosate puts at risk the preservation of native vegetation due to the contamination via herbicide transport processes. Our objectives were: i) to determine the sensitivity of native species from the Cerrado and Caatinga to glyphosate contamination via drift and groundwater; ii) evaluate the level of sensitivity to glyphosate among the different organs of plants. The highest intoxications (upper 80%) were observed for Bauhinia cheilantha, Mimosa caesalpiniaefolia, Mimosa tenuiflora and Amburana cearensis due to drift simullation. The species with 90% of total dry matter reduction were Bauhinia cheilantha, Enterolobium contortisiliquum, Mimosa caesalpiniaefolia, Mimosa tenuiflora, Tabebuia aurea. B. cheilantha and M. tenuiflora are most affected by exposure to glyphosate drift, with 50% of total dry matter reduction when exposed to doses below 444,0 g ha-1. Leaf growth is more sensitive to glyphosate for drift exposure for most species. Hymenaea courbaril is an exception, with greater sensitivity to root growth (50% dry matter reduction at doses below 666,0 g ha-1). B. cheilantha is the species most sensitive to drift exposure; however, it showed complete tolerance to contamination in subsurface waters. Other species such as Anadenanthera macrocarpa and M. caesalpiniifolia are also sensitive to drift, but without reach 90% of total dry matter reduction. A. macrocarpa, M. caesalpiniifolia and T. aurea were tolerant to contamination by subsurface water. The differential tolerance of trees confirms glyphosate's potential as a species selection agent in the Cerrado and Caatinga biomes.

Impact of Pyrolysis Temperature on the Properties of Eucalyptus Wood-Derived Biochar

Pyrolysis conditions directly influence biochar properties and, consequently, influence the potential use of biochar. In this study, we evaluated the effects of different pyrolysis temperatures (450, 550, 650, 750, 850, and 950 °C) on the hydrogen potential, electrical conductivity, ash content, yield, volatile matter content, elemental analysis, Fourier-transform infrared spectroscopy results, X-ray diffraction results, scanning electron microscopy results, specific surface area, and micropore volume of eucalyptus wood-derived biochar. The degree of linear association between pyrolysis temperatures and biochar properties was examined using the Pearson correlation coefficient. The results showed a positive correlation of the pyrolysis temperature with the hydrogen potential value, electrical conductivity, and elemental carbon. There was a negative correlation of the pyrolysis temperature with the yield, volatile matter content, elemental oxygen, elemental hydrogen, surface area, aromaticity, hydrophilicity, and polarity indexes. The Fourier-transform infrared spectroscopy data indicated an increase in aromaticity and a decrease in the polarity of high-temperature biochar. The increased pyrolysis temperature caused the loss of cellulose and crystalline mineral components, as indicated by X-ray diffraction analysis and scanning electron microscopy images. These results indicated that changing the pyrolysis temperature enables the production of biochar from the same raw material with a wide range of physicochemical properties, which allows its use in various types of agricultural and environmental activities.

Phytoextraction of diuron, hexazinone, and sulfometuron-methyl from the soil by green manure species

The herbicides diuron, hexazinone, and sulfometuron-methyl present a potential risk of environmental contamination and are widely used for weed control in sugarcane cultivation. Our objectives were to measure the tolerance of Canavalia ensiformes (L.) DC., Stilizobium aterrimum L., Raphanus sativus L., Crotalaria spectabilis Röth, Lupinus albus L., and Pennisetum glaucum (L.) R. Br. To the herbicides diuron, hexazinone, and sulfometuron-methyl to assess the capacity of these species to extract and accumulate the herbicides in their tissues. Before sowing the green manure species, the soils were individually contaminated with the three ¹⁴C-radiolabeled herbicides. ¹⁴C-diuron and ¹⁴C-sulfometuron-methyl showed higher values remaining in the soil (>90%) for all species of green manure compared to hexazinone (<80%). The green manure species analyzed showed greater potential to remedy soils contaminated with hexazinone than the other herbicides. C. ensiformes showed high phytoextraction of hexazinone when compared to the other species, removing 11.2% of the pollutant from the soil, followed by L. albus (8.6%), S. aterrimum (7.3%), R. sativus (4.8%), C. spectabilis (2.5%), and P. glaucum (1.1%). The results indicate that the phytoextraction of diuron, hexazinone and sulfometuron-methyl is dependent on the species of green manure and can be an important tool for the decontamination of areas polluted by these herbicides.

Use of neural networks to estimate the sorption and desorption coefficients of herbicides: A case study of diuron, hexazinone, and sulfometuron-methyl in Brazil

The use of herbicides in Brazil has been carried out based on the manufacturer's recommendation, often disregarding the high variability of soil attributes. The use of statistical methods to predict the herbicide retention processes in the soil can contribute to the improvement of weed control efficiency associated with the lower risk of environmental contamination. This research evaluated the use of Artificial Neural Networks (ANNs) to predict soil sorption and desorption, as well as the environmental contamination potential of diuron, hexazinone and sulfometuron-methyl herbicides in Brazilian soils. The sorption and desorption coefficients of the three herbicides were determined in laboratory tests for 15 soils from different Brazilian states. To predict the sorption and desorption of diuron, hexazinone and sulfometuron-methyl were used a multilayer perceptron ANNs (MLP). The inputs were the characteristics of the herbicides and the physical and chemical attributes of the soils, and the outputs of were the sorption and desorption coefficients (Kfs and Kfd). The risk of leaching of diuron, hexazinone, and sulfometuron-methyl herbicides were evaluated considering the sorption values observed and those estimated by the models. The Artificial Neural Network (ANN) models were efficient for the prediction of sorption and desorption of diuron, hexazinone, and sulfometuron-methyl herbicides. The physicochemical properties of the herbicides were more important for the modeling of multilayer perceptron ANNs than the soil attributes. The herbicides diuron, hexazinone, and sulfometuron-methyl have a high potential risk for contamination of groundwater in different Brazilian states.