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Validation and Application of UPLC-MS/MS Method to Analysis of Glyphosate and its Metabolites in Water.

A method was developed to determine glyphosate and their metabolites in water. The widespread use of this herbicide in agricultural activities worldwide, despite the reported adverse effects on both the environment and health, is a cause for concern and makes it necessary to monitor its presence through a method that guarantees the determination at trace levels. A direct extraction of the analytes with phosphate buffer was performed with subsequent derivatization with 9-fluorenylmethyl chloroformate. The quantification was determined by Ultra Performance Liquid Chromatography-tandem mass spectrometer. The method was validated through the following parameters: selectivity, detection and quantification limits, linearity, accuracy, precision and uncertainty. The average recoveries ranged between 94.08 and 103.31%. Additionally, detection limits from 0.396 to 0.433μg/L, and the quantification limit was 5.0μg/L for all the analytes evaluated. In terms of linearity and precision, the results obtained were in the ranges considered adequate (R2 ≥ 0.99 and CV ≤ 20%), the estimated expanded uncertainty was 12.95, 11.15 and 13.83% for glyphosate, aminomethylphosphonic acid and glufosinate, respectively. This method was successfully applied for the determination of the target analytes in irrigation water samples, detecting concentrations of aminomethylphosphonic acid over limit detection for some sampling sites.

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Validation and Application of Liquid Chromatography Coupled with Tandem Mass Spectrometry Method for the Analysis of Glyphosate, Aminomethylphosphonic Acid (AMPA), and Glufosinate in Soil

A method was developed to determine glyphosate, aminomethylphosphonic acid (AMPA), and glufosinate in soil. The worldwide use of this herbicide in agricultural activities, and its known negative effects on both the environment and health, have generated interest in the establishment of methodologies for its determination in several matrices at trace level. The development of analytical methods for the determination of glyphosate, AMPA, and glufosinate is challenging due to its present amphoteric properties, high solubility in water, low molecular weight, high affinity to the ions presents in the soil, and lack of chromophore groups in its structure, making its quantification difficult. The proposed method exhibits a linear range from 5.0 to 600 µg/kg with limits of detection of 1.37, 0.69 and 1.22 μg/kg, limits of quantification of 4.11, 2.08, and 3.66 μg/kg for glyphosate, AMPA, and glufosinate, respectively, and adequate repeatability and reproducibility (coefficients of variation <8.0% and recovery percentages between 93.56% and 99.10%). The matrix effect was calculated for each analyte, proving to be a good alternative for the determination of these contaminants. The described method was applied to 46 soil samples collected from crop fields in Hidalgo, Mexico, with concentrations varying from not detected to 4.358 μg/kg (for AMPA).

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Open Access
Microencapsulation of Bacillus Strains for Improving Wheat (Triticum turgidum Subsp. durum) Growth and Development.

Bio-formulation technologies have a limited impact on agricultural productivity in developing countries, especially those based on plant growth-promoting rhizobacteria. Thus, calcium alginate microbeads were synthesized and used for the protection and delivery of three beneficial Bacillus strains for agricultural applications. The process of encapsulation had a high yield per gram for all bacteria and the microbeads protected the Bacillus strains, allowing their survival, after 12 months of storage at room temperature. Microbead analysis was carried out by observing the rate of swelling and biodegradation of the beads and the released-establishment of bacteria in the soil. These results showed that there is an increase of around 75% in bead swelling on average, which allows for larger pores, and the effective release and subsequent establishment of the bacteria in the soil. Biodegradation of microbeads in the soil was gradual: in the first week, they increased their weight (75%), which consistently results in the swelling ratio. The co-inoculation of the encapsulated strain TRQ8 with the other two encapsulated strains showed plant growth promotion. TRQ8 + TRQ65 and TRQ8 + TE3T bacteria showed increases in different biometric parameters of wheat plants, such as stem height, root length, dry weight, and chlorophyll content. Thus, here we demonstrated that the application of alginate microbeads containing the studied strains showed a positive effect on wheat plants.

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Proteomic analysis reveals the metabolic versatility of Amycolatopsis sp. BX17: A strain native from milpa agroecosystem soil

Amycolatopsis sp. BX17 is an actinobacterium isolated from milpa soils, which antagonizes the phytopathogenic fungus Fusarium graminearum. Metabolites secreted by the actinobacterium cultured in glucose-free medium inhibited 100% of the mycelial growth of F. graminearum RH1, while the inhibition rate was 65% in medium supplemented with 20 g/L glucose. With the aim of studying how the metabolism of strain BX17 is modulated by glucose as the main carbon source, media with 0 and 20 g/L glucose were selected to analyze the intracellular proteins by quantitative label-free proteomic analysis. Data are available via ProteomeXchange with identifier PXD028644. Proteins identified in bacteria cultured in medium without glucose were involved in glutamate metabolism, the Krebs cycle and the shikimate pathway, suggesting that amino acids are metabolized to synthesize antifungal compounds. In glucose-containing medium, carbon flux was directed mainly toward the synthesis of energy and cell growth. This study shows the metabolic versatility of Amycolatopsis BX17, and strengthens its potential use in designing biotechnological strategies for phytopathogen control. SignificanceAmycolatopsis BX17 is a bacterium isolated from milpa agroecosystems that antagonizes the phytopathogenic fungus Fusarium graminearum. Currently, there is scarce information about the metabolism involved in the biosynthesis of antifungal agents by this genus. We used a label-free proteomic approach to identify the differences in metabolic routes for antifungal biosynthesis in Amycolatopsis BX17 grown in media with 0 and 20 g/L glucose. Taken together the results suggest that the BX17 strain could be synthesizing the antifungal metabolite(s) from the Shikimate pathway through the synthesis and degradation of the amino acid tyrosine, which is a known precursor of glycopeptides with antibiotic and antifungal activity. While the lower antifungal activity of the metabolites secreted by Amycolatopsis BX17 when grown in a medium with glucose as the main carbon source, may be correlated with a lower synthesis of antifungal compounds, due to the directing of carbon flux toward metabolic pathways involved with energy synthesis and cell growth. Likewise, it is possible that the bacteria synthesize other compounds with biological activity, such as glycopeptides with antibiotic activity. These findings are relevant because they represent the first stage to understand the metabolic regulation involved in the biosynthesis of antifungal metabolites by the genus Amycolatopsis. Finally, improving our understanding of the metabolic regulation involved in the biosynthesis of antifungal metabolites is essential to design of strategies in agricultural biotechnology for phytopathogen control.

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SARS-CoV-2 in wastewater from Mexico City used for irrigation in the Mezquital Valley: quantification and modeling of geographic dispersion.

Quantification of SARS-CoV-2 in urban wastewaters has emerged as a cheap, efficient strategy to follow trends of active COVID-19 cases in populations. Moreover, mathematical models have been developed that allow the prediction of active cases following the temporal patterns of viral loads in wastewaters. In Mexico, no systematic efforts have been reported in the use of these strategies. In this work, we quantified SARS-CoV-2 in rivers and irrigation canals in the Mezquital Valley, Hidalgo, an agricultural region where wastewater from Mexico City is distributed and used for irrigation. Using quantitative RT-PCR, we detected the virus in six out of eight water samples from rivers and five out of eight water samples from irrigation canals. Notably, samples showed a general consistent trend of having the highest viral loads in the sites closer to Mexico City, indicating that this is the main source that contributes to detection. Using the data for SARS-CoV-2 concentration in the river samples, we generated a simplified transport model that describes the spatial patterns of dispersion of virus in the river. We suggest that this model can be extrapolated to other wastewater systems where knowledge of spatial patterns of viral dispersion, at a geographic scale, is required. Our work highlights the need for improved practices and policies related to the use of wastewater for irrigation in Mexico and other countries.

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Open Access
SARS-CoV-2 in wastewater from Mexico City used for irrigation in the Mezquital Valley: quantification and modelling of geographic dispersion

AbstractQuantification of SARS-CoV-2 in urban wastewaters has emerged as a cheap, efficient strategy to follow trends of active COVID-19 cases in populations. Moreover, mathematical models have been developed that allow prediction of active cases following the temporal patterns of viral loads in wastewaters. In Mexico, no systematic efforts have been reported in the use of this strategies. In this work, we quantified SARS-CoV-2 in rivers and irrigation canals in the Mezquital Valley, Hidalgo, an agricultural region where wastewater from Mexico City is distributed and used for irrigation. Using quantitative RT-PCR, we detected the virus in 6 out of 8 water samples from rivers, and 5 out of 8 water samples from irrigation canals. Notably, samples showed a general consistent trend of having the highest viral loads in the sites closer to Mexico City, indicating that this is the main source that contributes to detection. Using the data for SARS-CoV-2 concentration in the river samples, we generated a simplified transport model that describes the spatial patterns of dispersion of virus in the river. We suggest that this model can be extrapolated to other wastewater systems that require knowledge of spatial patterns of viral dispersion at a geographic scale. Our work highlights the need for improved practices and policies related to the use of wastewater for irrigation in Mexico and other countries.

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Open Access