Ethyl Butanoate, Constituent of Cassava Wastewater Volatiloma, a Potential Soil Fumigant Against Meloidogyne Javanica.

As a result of more restrictive legislation regarding the use of pesticides, over the last two decades, the demand for new soil fumigants has increased. These compounds can come from a variety of sources, including organic residues. In this study, we identified in the cassava wastewater volatiloma a molecule with potential to be developed as a new fumigant nematicide. Cassava wastewater (20 mL) releases volatile compounds toxic to Meloidogyne javanica second-stage juveniles (J2), causing J2 mortality up to 89%. Through gas chromatography-mass spectrometry, eight compounds were identified in the cassava wastewater volatiloma, with alcohols being the major class. The compounds ethyl butanoate and butyric acid identified in cassava wastewater volatiloma were selected for in vitro nematicidal activities and substrate fumigation tests. The lethal concentration predicted LC50-48 hr values (effective doses to kill 50% of M. javanica J2 population after 48 h of exposure) were 172.6 µg ∙ mL - 1 and 301.2 µg ∙ mL - 1 for butyric acid and ethyl butanoate, respectively. In a pot assay, the application of butyric acid and ethyl butanoate as a soil fumigant, at a dose of 0.5 mL ∙ kg - 1 substrate, significantly (P < 0.05) decreased M. javanica infectivity and reproduction compared to the negative control (water). However, ethyl butanoate proved to be a more efficient soil fumigant (P < 0.05) than butyric acid, as its application reduced the number of galls and eggs to the level of the commercial fumigant Dazomet. This study is the first to demonstrate the potential of ethyl butanoate as a soil fumigant against M. javanica.

Attraction and toxicity: Ways volatile organic compounds released by Pochonia chlamydosporia affect Meloidogyne incognita.

The production of volatile organic compounds (VOCs) acting against plant-parasitic nematodes has been characterized in different fungi; however, the role of VOCs emitted by Pochonia chlamydosporia in its trophic interaction with Meloidogyne incognita is still unknown. The aim of this study was to determine the effects of VOCs emitted by P. chlamydosporia strain Pc-10 on different stages (eggs, juveniles and female) of the M. incognita life cycle. Exposure of M. incognita eggs to VOCs released by Pc-10 resulted in a reduction up to 88 % in the nematode egg hatching, when compared to the control treatments. The VOCs emitted by Pc-10 also attracted M. incognita second-stage juveniles (J2). Through gas chromatography-mass spectrometry (GC-MS), three molecules were identified from the volatiles of the strain Pc-10, with 1,4-dimethoxybenzene being the major compound. In tests performed in vitro, 1,4-dimethoxybenzene at a concentration of 1050 µg mL-1 inhibited M. incognita egg hatching by up to 78.7 % compared to the control (0 µg mL-1) and attracted M. incognita J2 in all concentrations evaluated (1, 10, 100, 1000, and 10000 µg mL-1). The 1,4-dimethoxybenzene also showed fumigant and non-fumigant nematicidal activity against M. incognita. This compound presented lethal concentration for 50 % (LC50) of M. incognita J2 ranged from 132 to 136 µg mL-1. Fumigation with 1,4-dimethoxybenzene (100 mg) reduced egg hatching by up to 89 % and killed up to 86 % of M. incognita J2 compared to the control (0 µg mL-1). In vivo, the VOCs produced by Pc-10, 1,4-dimethoxybenzene, and the combination of both (Pc-10 + 1,4-dimethoxybenzene) attracted the M. incognita J2, compared to the respective controls. To the best of our knowledge, this is the first report on the attraction of M. incognita J2 and the toxicity to eggs and J2 by VOCs from P. chlamydosporia in which 1,4-dimethoxybenzene is the main toxin and attractant.

Identification of volatile compounds, quantification of glycerol and trace elements in distilled spirits produced in Mozambique.

Distilled spirits, in addition to satisfying the legal requirements with respect to its composition, must possess a sensorial quality capable of satisfying its consumers. The present work describes the analysis of volatile compounds, trace elements and glycerol in thirteen samples of Mozambican spirits collected in different regions of the country. Extraction of volatile components was a accomplished using the headspace SPME technique, the quantification of glycerol was achieved by UV/Vis spectroscopy and the determination of trace elements by atomic absorption spectrometry. Of the 35 volatile compounds identified, 19 were esters, of which ethyl hexanoate, ethyl octanoate, ethyl nonanoate, ethyl decanoate, ethyl laurate, ethyl hexadecanoate, ethyl tetradecanoate, ethyl benzenepropanoate, 3-methylbutyl acetate and isoamyl alcohol were the predominant compounds found in the different samples, contributing to the characteristics and aroma of the beverages. As for glycerol, concentrations below 5 mg L-1 were observed in all the samples studied. The samples were found to be contaminated by metals such as copper, lead and zinc. In addition, the results provided information on the quality of Mozambican spirits regarding some aspects related to the determination of metals and glycerol. This information might stimulate producers to be more attentive to the conditions of production and the risks involved in achieving good quality spirits.

Xanthosoma sagittifolium is resistant to Meloidogyne spp. and controls Meloidogyne enterolobii by soil biofumigation.

Meloidogyne is a relevant plant-parasitic nematode that causes enormous damage. It is very challenging to control, and there are not many chemicals available on the market for that. As an alternative method of nematode control, biofumigation is increasingly gaining space. This research aimed to study the reaction of Xanthosoma sagittifolium to Meloidogyne enterolobii, M. incognita, and M. javanica and soil biofumigation with X. sagittifolium leaves for M. enterolobii control. The reaction test was performed in the populations 0 (control), 333, 999, 3,000, 9,000, 27,000 eggs and eventual juveniles. X. sagittifolium did not host the Meloidogyne species studied, even in a high population. X. sagittifolium leaves incorporated in soil at concentrations 0 (control), 0.45, 0.9, 1.8, 3.6 g were also studied to control M. enterolobii, and they were able to reduce galls and eggs. The number of galls and egg masses was reduced to a concentration of 1.8 g. In the maximum concentration, the number of galls was less than 15 galls, and the eggs were also reduced to less than 200 eggs. As these macerates emitted nematicidal volatile organic compounds (VOCs) against M. enterolobii, it reduced the infectivity and reproduction of nematodes.

Multivariate curve resolution combined with gas chromatography to enhance analytical separation in complex samples: a review.

This review describes the major advantages and pitfalls of iterative and non-iterative multivariate curve resolution (MCR) methods combined with gas chromatography (GC) data using literature published since 2000 and highlighting the most important combinations of GC coupled to mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography with flame ionization detection (GC×GC-FID) and coupled to mass spectrometry (GC×GC-MS). In addition, a brief summary of some pre-processing strategies will be discussed to correct common issues in GC, such as retention time shifts and baseline/background contributions. Additionally, algorithms such as evolving factor analysis (EFA), heuristic evolving latent projection (HELP), subwindow factor analysis (SFA), multivariate curve resolution-alternating least squares (MCR-ALS), positive matrix factorization (PMF), iterative target transformation factor analysis (ITTFA) and orthogonal projection resolution (OPR) will be described in this paper. Even more, examples of applications to food chemistry, lipidomics and medicinal chemistry, as well as in essential oil research, will be shown. Lastly, a brief illustration of the MCR method hierarchy will also be presented.

Quantitative analysis of essential oils in perfume using multivariate curve resolution combined with comprehensive two-dimensional gas chromatography.

The use of multivariate curve resolution (MCR) to build multivariate quantitative models using data obtained from comprehensive two-dimensional gas chromatography with flame ionization detection (GC×GC-FID) is presented and evaluated. The MCR algorithm presents some important features, such as second order advantage and the recovery of the instrumental response for each pure component after optimization by an alternating least squares (ALS) procedure. A model to quantify the essential oil of rosemary was built using a calibration set containing only known concentrations of the essential oil and cereal alcohol as solvent. A calibration curve correlating the concentration of the essential oil of rosemary and the instrumental response obtained from the MCR-ALS algorithm was obtained, and this calibration model was applied to predict the concentration of the oil in complex samples (mixtures of the essential oil, pineapple essence and commercial perfume). The values of the root mean square error of prediction (RMSEP) and of the root mean square error of the percentage deviation (RMSPD) obtained were 0.4% (v/v) and 7.2%, respectively. Additionally, a second model was built and used to evaluate the accuracy of the method. A model to quantify the essential oil of lemon grass was built and its concentration was predicted in the validation set and real perfume samples. The RMSEP and RMSPD obtained were 0.5% (v/v) and 6.9%, respectively, and the concentration of the essential oil of lemon grass in perfume agreed to the value informed by the manufacturer. The result indicates that the MCR algorithm is adequate to resolve the target chromatogram from the complex sample and to build multivariate models of GC×GC-FID data.

Prediction of the physicochemical properties of gasoline by comprehensive two-dimensional gas chromatography and multivariate data processing.

The estimation of physicochemical parameters such as distillation points and relative densities still plays an important role in the quality control of gasoline and similar fuels. Their measurements according to standard ASTM procedures demands specific equipments and are time and work consuming. An alternative method to predict distillation points and relativity density by multivariate analysis of comprehensive two-dimensional gas chromatography with flame ionization detection (GC×GC-FID) data is presented here. Gasoline samples, previously tested according to standard methods, were used to build regression models, which were evaluated by external validation. The models for distillation points were built using variable selection methods, while the model for relativity density was built using the whole chromatograms. The root mean square prediction differences (RMSPD) obtained were 0.85%, 0.48%, 1.07% and 1.71% for 10, 50 and 90% v/v of distillation and for the final point of distillation, respectively. For relative density, the RMSPD was 0.24%. These results suggest that GC×GC-FID combined with multivariate analysis can be used to predict these physicochemical properties of gasoline.

Quantitative analysis by comprehensive two-dimensional gas chromatography using interval Multi-way Partial Least Squares calibration.

A new approach for target quantitative analysis for comprehensive two-dimensional gas chromatography (GC × GC), interval Multi-way Partial Least Square (iNPLS) is presented and evaluated in this paper. In iNPLS, the two-dimensional chromatogram is split in small sections; each of these pieces is treated as an independent new chromatogram. Separated conventional NPLS calibration models for the concentration of the target analyte are built for each of the pieces of the whole chromatogram, and the best model is selected for quantitative analysis. An algorithm for iNPLS running on MatLab platform was written, preliminarily evaluated with using solutions of model compounds with different chemical properties and subsequently applied to quantify some allergens in perfume samples. The results were found to be adequate, and good precision and accuracy was obtained even for poorly resolved peaks.

Identification of gasoline adulteration using comprehensive two-dimensional gas chromatography combined to multivariate data processing.

A method to detect potential adulteration of commercial gasoline (Type C gasoline, available in Brazil and containing 25% (v/v) ethanol) is presented here. Comprehensive two-dimensional gas chromatography with flame ionization detection (GCxGC-FID) data and multivariate calibration (multi-way partial least squares regression, N-PLS) were combined to obtain regression models correlating the concentration of gasoline on samples from chromatographic data. Blends of gasoline and white spirit, kerosene and paint thinner (adopted as model adulterants) were used for calibration; the regression models were evaluated using samples of Type C gasoline spiked with these solvents, as well as with ethanol. The method was also checked with real samples collected from gas stations and analyzed using the official method. The root mean square error of prediction (RMSEP) for gasoline concentrations on test samples calculated using the regression model ranged from 3.3% (v/v) to 8.2% (v/v), depending on the composition of the blends; in addition, the results for the real samples agree with the official method. These observations suggest that GCxGC-FID and N-PLS can be an alternative for routine monitoring of fuel adulteration, as well as to solve several other similar analytical problems where mixtures should be detected and quantified as single species in complex samples.