Analysis of variance of primary data on plant growth analysis

Plant growth analysis presents difficulties related to statistical comparison of growth rates, and the analysis of variance of primary data could guide the interpretation of results. The objective of this work was to evaluate the analysis of variance of data from distinct harvests of an experiment, focusing especially on the homogeneity of variances and the choice of an adequate ANOVA model. Data from five experiments covering different crops and growth conditions were used. From the total number of variables, 19% were originally homoscedastic, 60% became homoscedastic after logarithmic transformation, and 21% remained heteroscedastic after transformation. Data transformation did not affect the F test in one experiment, whereas in the other experiments transformation modified the F test usually reducing the number of significant effects. Even when transformation has not altered the F test, mean comparisons led to divergent interpretations. The mixed ANOVA model, considering harvest as a random effect, reduced the number of significant effects of every factor which had the F test modified by this model. Examples illustrated that analysis of variance of primary variables provides a tool for identifying significant differences in growth rates. The analysis of variance imposes restrictions to experimental design thereby eliminating some advantages of the functional growth analysis.

Spatial statistical analysis and selection of genotypes in plant breeding

The objective of this study was to evaluate the efficiency of spatial statistical analysis in the selection of genotypes in a plant breeding program and, particularly, to demonstrate the benefits of the approach when experimental observations are not spatially independent. The basic material of this study was a yield trial of soybean lines, with five check varieties (of fixed effect) and 110 test lines (of random effects), in an augmented block design. The spatial analysis used a random field linear model (RFML), with a covariance function estimated from the residuals of the analysis considering independent errors. Results showed a residual autocorrelation of significant magnitude and extension (range), which allowed a better discrimination among genotypes (increase of the power of statistical tests, reduction in the standard errors of estimates and predictors, and a greater amplitude of predictor values) when the spatial analysis was applied. Furthermore, the spatial analysis led to a different ranking of the genetic materials, in comparison with the non-spatial analysis, and a selection less influenced by local variation effects was obtained.

Química orgânica experimental: integração de teoria, experimento e análise

A new approach for teaching in basic experimental organic chemistry is presented. Experimental work goes on parallel to theoretical lectures leading to an immediate application of theoretical concepts transmitted therein. One day/week is dedicated exclusively to the organic laboratory. Reactions are proposed as problems to be solved; the student has to deduce the structure of the product on the basis of his observations, the analytical data and his mechanistical knowledge. 70 different experiments, divided in 7 thematical chapters, are presented. All experiments require the analysis and discussion of 1H and 13C NMR, IR and UV spectra. Additional questions about each reaction have to be answered by the student in his written report. Laboratory safety is garanteed by the exclusion or substitution of hazardous and toxic reagents. Microscale preparations are adopted in most cases to lower the cost of materials and the amount of waste. Recycling of many reaction products as starting materials in other experiments reduces the need for commercial reagents and allows the execution of longer reaction sequences. Only unexpensive standard laboratory equipment and simple glassware are required. All experiments include instructions for the save treatment or disposal of chemical waste.

Introdução a modelagem molecular de fármacos no curso experimental de química farmacêutica

Molecular Modeling is an important tool in drug design and it is very useful to predict biological activity from a library of compounds. A wide variety of computer programs and methods have been developed to visualize the tridimensional geometry and calculate physical properties of drugs. In this work, we describe a practical approach of molecular modeling as a powerful tool to study structure-activity relationships of drugs, including some antibacterials, hormones, cholinergic and adrenergic agents. At first, the students learn how to draw 3D structures and use them to perform conformational and molecular analysis. Thus, they compare drugs with similar pharmacological activity by superimposing one structure on the top of another and evaluate the geometry and physical properties.

Estudo experimental e teórico da redução de bases de Schiff derivadas da 3,3-difenilpropilamina

A series of seven Schiff bases have been synthesized from 3,3-diphenylpropilamine and substituted benzaldehydes. These imines were treated with NaBH4 in ethanol affording the corresponding amines in 98-55% yields. A molecular modeling study was performed with the Schiff bases in order to compare the theoretical parameters with the experimental results. The theoretical parameters were obtained by AM1 and PM3 semi-empirical methods. The analysis of charge, electron densities and LUMO coefficients suggested that the most favorable interactions should occur with Schiff bases containing electron-donating groups, in accordance with experimental yields, showing that the higher reactivity is due to higher electrophilic character of imine carbons.

Atualizando a química orgânica experimental da licenciatura

The present contribution describes three different modern experiments for possible adoption in undergraduate organic chemistry laboratories. These are: 1. electrocatalytic hydrogenation of benzaldehyde to benzyl alcohol; 2. identification of three volatile components, obtained from pineapple fruit, by mass spectrometry and 3. microwave mediated fast synthesis of N-(p-chlorophenyl)phthalamic acid from phthalic anhydride and p-chloroaniline under solvent-free conditions. The experiments can be executed in a short period of time, putting the undergraduate student in contact with a variety of topics in organic chemistry and several techniques of analysis, showing multidisciplinarity in organic chemistry.

Quantitative structure-retention relationships analysis of retention index of essential oils

Genetic algorithm and multiple linear regression (GA-MLR), partial least square (GA-PLS), kernel PLS (GA-KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between retention index (RI) and descriptors for 116 diverse compounds in essential oils of six Stachys species. The correlation coefficient LGO-CV (Q²) between experimental and predicted RI for test set by GA-MLR, GA-PLS, GA-KPLS and L-M ANN was 0.886, 0.912, 0.937 and 0.964, respectively. This is the first research on the QSRR of the essential oil compounds against the RI using the GA-KPLS and L-M ANN.

Planejamento experimental na otimização da extração dos frutos de Syzygium cumini (L.) skeels

The aim of this study was to standardize the extractive solution of Syzygium cumini. The extractive solution was selected through a full factorial design, considering the extraction method (maceration-5-days, turbo extraction, percolation), extractor solvent (ethanol 50, 70, 96%) and plant material particle size 0.302 mm into a plant:solvent ratio (1:10), using the dried residue and antimicrobial activity determination as evaluation criteria. The tests were performed in triplicate. It appeared that the percolation is the best procedure extractive, and ethanol mixture: water (50:50) the best solvent. ANOVA analysis showed the importance of these parameters.

Resolução do ibuprofeno: um projeto para disciplina de química orgânica experimental

A practical and didactic sequence of experiments was proposed to illustrate the stereochemistry concept, optically active compounds, resolution of racemates, and use of the NMR technique, including 2D-COSY for identification of organic compounds, on a laboratory course for undergraduate students. The sequence was: extractions of racemic ibuprofen and chiral naproxen from commercial tablets; syntheses of diastereoisomeric amides reacting chiral (S)-(-)-α-methylbenzylamine with (±)-ibuprofen; separation and determination of absolute configuration of amides by ¹H NMR spectroscopy and GC analysis, and hydrolysis of amides to obtain (+)- and (-)-ibuprofen.

Combined experimental powder X-ray diffraction and DFT data to obtain the lowest energy molecular conformation of friedelin

Friedelin molecular conformers were obtained by Density Functional Theory (DFT) and by ab initio structure determination from powder X-ray diffraction. Their conformers with the five rings in chair-chair-chair-boat-boat, and with all rings in chair, are energy degenerated in gas-phase according to DFT results. The powder diffraction data reveals that rings A, B and C of friedelin are in chair, and rings D and E in boat-boat, conformation. The high correlation values among powder diffraction data, DFT and reported single-crystal data indicate that the use of conventional X-ray diffractometer can be applied in routine laboratory analysis in the absence of a single-crystal diffractometer.

Methane combustion kinetic rate constants determination: an ill-posed inverse problem analysis

Methane combustion was studied by the Westbrook and Dryer model. This well-established simplified mechanism is very useful in combustion science, for computational effort can be notably reduced. In the inversion procedure to be studied, rate constants are obtained from [CO] concentration data. However, when inherent experimental errors in chemical concentrations are considered, an ill-conditioned inverse problem must be solved for which appropriate mathematical algorithms are needed. A recurrent neural network was chosen due to its numerical stability and robustness. The proposed methodology was compared against Simplex and Levenberg-Marquardt, the most used methods for optimization problems.

Extração de bifenilas policloradas de amostras de leite materno: otimização univariada versus planejamento experimental

The convenience of the multivariate optimization of SPME procedures through ANOVA calculated using Doehlert designs has been demonstrated for twelve PCBs in the complex matrix of milk. For this study, the main parameters of the extraction were selected and valued through univariate and multivariate optimization. In addition, the analysis of variance allowed identification of the statistically significant variables in this model: high temperature (95 ºC) and ionic strength (36% m/v) proved significant for all the PCBs while intermediate time (70 min) and low methanol concentration (5% v/v) also contributed to the extraction of the majority of these PCBs.

Optimization of solvent mixtures for extraction from bark of Schinus terebinthifolius by a statistical mixture-design technique and development of a UV-Vis spectrophotometric method for analysis of total polyphenols in the extract

A statistical mixture-design technique was used to study the effects of different solvents and their mixtures on the yield, total polyphenol content, and antioxidant capacity of the crude extracts from the bark of Schinus terebinthifolius Raddi (Anacardiaceae). The experimental results and their response-surface models showed that ternary mixtures with equal portions of all the three solvents (water, ethanol and acetone) were better than the binary mixtures in generating crude extracts with the highest yield (22.04 ± 0.48%), total polyphenol content (29.39 ± 0.39%), and antioxidant capacity (6.38 ± 0.21). An analytical method was developed and validated for the determination of total polyphenols in the extracts. Optimal conditions for the various parameters in this analytical method, namely, the time for the chromophoric reaction to stabilize, wavelength of the absorption maxima to be monitored, the reference standard and the concentration of sodium carbonate were determined to be 5 min, 780 nm, pyrogallol, and 14.06% w v-1, respectively. UV-Vis spectrophotometric monitoring of the reaction under these conditions proved the method to be linear, specific, precise, accurate, reproducible, robust, and easy to perform.

Automatic evaluation and data generation for analytical chemistry instrumental analysis exercises

In general, laboratory activities are costly in terms of time, space, and money. As such, the ability to provide realistically simulated laboratory data that enables students to practice data analysis techniques as a complementary activity would be expected to reduce these costs while opening up very interesting possibilities. In the present work, a novel methodology is presented for design of analytical chemistry instrumental analysis exercises that can be automatically personalized for each student and the results evaluated immediately. The proposed system provides each student with a different set of experimental data generated randomly while satisfying a set of constraints, rather than using data obtained from actual laboratory work. This allows the instructor to provide students with a set of practical problems to complement their regular laboratory work along with the corresponding feedback provided by the system's automatic evaluation process. To this end, the Goodle Grading Management System (GMS), an innovative web-based educational tool for automating the collection and assessment of practical exercises for engineering and scientific courses, was developed. The proposed methodology takes full advantage of the Goodle GMS fusion code architecture. The design of a particular exercise is provided ad hoc by the instructor and requires basic Matlab knowledge. The system has been employed with satisfactory results in several university courses. To demonstrate the automatic evaluation process, three exercises are presented in detail. The first exercise involves a linear regression analysis of data and the calculation of the quality parameters of an instrumental analysis method. The second and third exercises address two different comparison tests, a comparison test of the mean and a t-paired test.

PROPOSTA EXPERIMENTAL DIDÁTICA PARA O ENSINO DE ANÁLISE DE COMPONENTES PRINCIPAIS

Principal component analysis (PCA) is a chemometric method that allows for the extraction of chemical information that would otherwise be impossible to determine. Teaching chemometrics to undergraduates can contribute to the overall professional development and training of new teachers, whose profiles have been gaining attention due to the current demand for data interpretation. In this study, a didactic experiment involving PCA is proposed. Spectrophotometry was used in the ultraviolet-visible (UV-Vis) region to assess the behavior of anthocyanins extracted from red cabbage at different pH values. The results suggest the possible separation of anthocyanin structures into three distinct groups, according to their chemical characteristics displayed in acid, neutral, and basic media. The objective is to develop educational materials targeted to undergraduate courses, which encompass a larger number of concepts and introduce instrumental techniques currently being employed in both academic research and the industrial sector. Specifically, the proposed experiment introduces concepts related to spectrophotometry in the UV-Vis range and the PCA chemometric method. The materials used are easily accessible, and UV-Vis spectroscopy equipment is less expensive in comparison with other spectroscopy methods.