Improvement of a testing apparatus for dynamometry: procedures for penetrometry and influence of strain rate to quantify the tensile strength of soil aggregates

Soil penetration resistance (PR) and the tensile strength of aggregates (TS) are commonly used to characterize the physical and structural conditions of agricultural soils. This study aimed to assess the functionality of a dynamometry apparatus by linear speed and position control automation of its mobile base to measure PR and TS. The proposed equipment was used for PR measurement in undisturbed samples of a clayey "Nitossolo Vermelho eutroférrico" (Kandiudalfic Eutrudox) under rubber trees sampled in two positions (within and between rows). These samples were also used to measure the volumetric soil water content and bulk density, and determine the soil resistance to penetration curve (SRPC). The TS was measured in a sandy loam "Latossolo Vermelho distrófico" (LVd) - Typic Haplustox - and in a very clayey "Nitossolo Vermelho distroférrico" (NVdf) - Typic Paleudalf - under different uses: LVd under "annual crops" and "native forest", NVdf under "annual crops" and "eucalyptus plantation" (> 30 years old). To measure TS, different strain rates were applied using two dynamometry testing devices: a reference machine (0.03 mm s-1), which has been widely used in other studies, and the proposed equipment (1.55 mm s-1). The determination coefficient values of the SRPC were high (R² > 0.9), regardless of the sampling position. Mean TS values in LVd and NVdf obtained with the proposed equipment did not differ (p > 0.05) from those of the reference testing apparatus, regardless of land use and soil type. Results indicate that PR and TS can be measured faster and accurately by the proposed procedure.

Implications of the variability in soil penetration resistance for statistical analysis

Soil penetration resistance (PR) is a measure of soil compaction closely related to soil structure and plant growth. However, the variability in PR hampers the statistical analyses. This study aimed to evaluate the variability of soil PR on the efficiency of parametric and nonparametric analyses in indentifying significant effects of soil compaction and to classify the coefficient of variation of PR into low, medium, high and very high. On six dates, the PR of a typical dystrophic Red Ultisol under continuous no-tillage for 16 years was measured. Three tillage and/or traffic conditions were established with the application of: (i) no chiseling or additional traffic, (ii) additional compaction, and (iii) chiseling. On each date, the nineteen PR data (measured at every 1.5 cm to a depth of 28.5 cm) were grouped in layers with different thickness. In each layer, the treatment effects were evaluated by variance (ANOVA) and Kruskal-Wallis analyses in a completely randomized design, and the coefficients of variation of all analyses were classified (low, intermediate, high and very high). The ANOVA performed better in discriminating the compaction effects, but the rejection rate of null hypothesis decreased from 100 to 80 % when the coefficient of variation increased from 15 to 26 %. The values of 15 and 26 % were the thresholds separating the low/intermediate and the high/very high coefficient variation classes of PR in this Ultisol.

Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

Critical values of nitrogen indices in tomato plants grown in soil and nutrient solution determined by different statistical procedures

The objective of this study was to establish critical values of the N indices, namely soil-plant analysis development (SPAD), petiole sap N-NO3 and organic N in the tomato leaf adjacent to the first cluster (LAC), under soil and nutrient solution conditions, determined by different statistical approaches. Two experiments were conducted in randomized complete block design with four repli-cations. Tomato plants were grown in soil, in 3 L pot, with five N rates (0, 100, 200, 400 and 800 mg kg-1) and in solution at N rates of 0, 4, 8, 12 and 16 mmol L-1. Experiments in nutrient solution and soil were finished at thirty seven and forty two days after transplanting, respectively. At those times, SPAD index and petiole sap N-NO3 were evaluated in the LAC. Then, plants were harvested, separated in leaves and stem, dried at 70ºC, ground and weighted. The organic N was determined in LAC dry matter. Three statistical procedures were used to calculate critical N values. There were accentuated discrepancies for critical values of N indices obtained with plants grown in soil and nutrient solution as well as for different statistical procedures. Critical values of nitrogen indices at all situations are presented.

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.

Prediction of soil shear strength in agricultural and natural environments of the Brazilian Cerrado

The objective of this work was to develop uni- and multivariate models to predict maximum soil shear strength (τmax) under different normal stresses (σn), water contents (U), and soil managements. The study was carried out in a Rhodic Haplustox under Cerrado (control area) and under no-tillage and conventional tillage systems. Undisturbed soil samples were taken in the 0.00-0.05 m layer and subjected to increasing U and σn, in shear strength tests. The uni- and multivariate models - respectively τmax=10(a+bU) and τmax=10(a+bU+cσn) - were significant in all three soil management systems evaluated and they satisfactorily explain the relationship between U, σn, and τmax. The soil under Cerrado has the highest shear strength (τ) estimated with the univariate model, regardless of the soil water content, whereas the soil under conventional tillage shows the highest values with the multivariate model, which were associated to the lowest water contents at the soil consistency limits in this management system.

Validation and statistical analysis of two high performance liquid chromatography methods for the determination of indinavir sulfate raw material and capsules

Two high performance liquid chromatography (HPLC) methods for the quantitative determination of indinavir sulfate were tested, validated and statistically compared. Assays were carried out using as mobile phases mixtures of dibutylammonium phosphate buffer pH 6.5 and acetonitrile (55:45) at 1 mL/min or citrate buffer pH 5 and acetonitrile (60:40) at 1 mL/min, an octylsilane column (RP-8) and a UV spectrophotometric detector at 260 nm. Both methods showed good sensitivity, linearity, precision and accuracy. The statistical analysis using the t-student test for the determination of indinavir sulfate raw material and capsules indicated no statistically significant difference between the two methods.

Visual demonstration of the ionic strength effect in the classroom: the Debye-Hückel limiting law

The effects of ionic strength on ions in aqueous solutions are quite relevant, especially for biochemical systems, in which proteins and amino acids are involved. The teaching of this topic and more specifically, the Debye-Hückel limiting law, is central in chemistry undergraduate courses. In this work, we present a description of an experimental procedure based on the color change of aqueous solutions of bromocresol green (BCG), driven by addition of electrolyte. The contribution of charge product (z+|z-|) to the Debye-Hückel limiting law is demonstrated when the effects of NaCl and Na2SO4 on the color of BCG solutions are compared.

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.

Statistical Model to DNA Melting

We explore a DNA statistical model to obtain information about the behavior of the thermodynamics quantities. Special attention is given to the thermal denaturation of this macromolecule.