The nitrogen sufficiency index underlying estimates of nitrogen fertilization requirements of common bean

Chlorophyll determination with a portable chlorophyll meter can indicate the period of highest N demand of plants and whether sidedressing is required or not. In this sense, defining the optimal timing of N application to common bean is fundamental to increase N use efficiency, increase yields and reduce the cost of fertilization. The objectives of this study were to evaluate the efficiency of N sufficiency index (NSI) calculated based on the relative chlorophyll index (RCI) in leaves, measured with a portable chlorophyll meter, as an indicator of time of N sidedressing fertilization and to verify which NSI (90 and 95 %) value is the most appropriate to indicate the moment of N fertilization of common bean cultivar Perola. The experiment was carried out in the rainy and dry growing seasons of the agricultural year 2009/10 on a dystroferric Red Nitosol, in Botucatu, São Paulo State, Brazil. The experiment was arranged in a randomized complete block design with five treatments, consisting of N managements (M1: 200 kg ha-1 N (40 kg at sowing + 80 kg 15 days after emergence (DAE) + 80 kg 30 DAE); M2: 100 kg ha-1 N (20 kg at sowing + 40 kg 15 DAE + 40 kg 30 DAE); M3: 20 kg ha-1 N at sowing + 30 kg ha-1 when chlorophyll meter readings indicated NSI < 95 %; M4: 20 kg ha-1 N at sowing + 30 kg ha-1 N when chlorophyll meter readings indicated NSI < 90 % and, M5: control (without N application)) and four replications. The variables RCI, aboveground dry matter, total leaf N concentration, production components, grain yield, relative yield, and N use efficiency were evaluated. The RCI correlated with leaf N concentrations. By monitoring the RCI with the chlorophyll meter, the period of N sidedressing of common bean could be defined, improving N use efficiency and avoiding unnecessary N supply to common bean. The NSI 90 % of the reference area was more efficient to define the moment of N sidedressing of common bean, to increase N use efficiency.

Proposal for an index to classify irrigation water quality: a case study in northeastern Brazil

One way of classifying water quality is by means of indices, in which a series of parameters analyzed are joined a single value, facilitating the interpretation of extensive lists of variables or indicators, underlying the classification of water quality. The objective of this study was to develop a statistically based index to classify water according to the Irrigation Water Quality Index (IWQI), to evaluate the ionic composition of water for use in irrigation and classify it by its source. For this purpose, the database generated during the Technology Generation and Adaptation (GAT) program was used, in which, as of 1988, water samples were collected monthly from water sources in the states of Paraíba, Rio Grande do Norte and Ceará. To evaluate water quality, the electrical conductivity (EC) of irrigation water was taken as a reference, with values corresponding to 0.7 dS m-1. The chemical variables used in this study were: pH, EC, Ca, Mg, Na, K, Cl, HCO3, CO3, and SO4. The data of all characteristics evaluated were standardized and data normality was confirmed by Lilliefors test. Then the irrigation water quality index was determined by an equation that relates the standardized value of the variable with the number of characteristics evaluated. Thus, the IWQI was classified based on indices, considering normal distribution. Finally, these indices were subjected to regression analysis. The method proposed for the IWQI allowed a satisfactory classification of the irrigation water quality, being able to estimate it as a function of EC for the three water sources. Variation in the ionic composition was observed among the three sources and within a single source. Although the water quality differed, it was good in most cases, with the classification IWQI II.

Phosphorus accumulation and pollution potential in a hapludult fertilized with pig manure

Successive applications of pig litter to the soil surface can increase the phosphorus (P) content and alter its adsorption, promoting P transfer to surface or subsurface waters. The purpose of this study was to evaluate P accumulation and the pollution potential of a soil after application of pig litter. In March 2010, eight years after the installation of an experiment in Braço do Norte, Santa Catarina, SC, Brazil, on a Typic Hapludult, soil was sampled (layers 0-2.5, 2.5-5, 5-10, 10-15, 15-20 and 20-30 cm) after the following fertilization treatments: no pig litter fertilization, pig slurry application and pig manure application. In this period, 694 and 1,890 kg P2O5 ha-1 were applied in the treatments with pig slurry and pig manure, respectively. The P content was determined, based on Mehlich-1, anion exchange resin (AER), 0.01 mol L-1 CaCl2 and total P in the samples. The adsorption isotherm parameters were also determined by the Langmuir and Koski-Vähälä & Hartikainem models in the layers 0-2.5 and 20-30 cm. The application of 1,890 kg P2O5 ha-1 in the form of pig manure led to P accumulation, as evidenced by Mehlich-1, down to a depth of 15 cm, by AER and 0.01 mol L-1 CaCl2 down to 20 cm and by total P to 30 cm. After application of 1,890 kg P2O5 ha-1 in the form of pig manure, the values of maximum P adsorption capacity were lowest in the deepest layer (20-30 cm), indicating the occupation of part of the adsorption sites of the particles. The application of swine manure to the soil over eight years increased the P quantity in the soil solution of the surface layer, indicating environmental contamination risk for surface and subsurface waters.

Soil infiltration based on bp neural network and grey relational analysis

Soil infiltration is a key link of the natural water cycle process. Studies on soil permeability are conducive for water resources assessment and estimation, runoff regulation and management, soil erosion modeling, nonpoint and point source pollution of farmland, among other aspects. The unequal influence of rainfall duration, rainfall intensity, antecedent soil moisture, vegetation cover, vegetation type, and slope gradient on soil cumulative infiltration was studied under simulated rainfall and different underlying surfaces. We established a six factor-model of soil cumulative infiltration by the improved back propagation (BP)-based artificial neural network algorithm with a momentum term and self-adjusting learning rate. Compared to the multiple nonlinear regression method, the stability and accuracy of the improved BP algorithm was better. Based on the improved BP model, the sensitive index of these six factors on soil cumulative infiltration was investigated. Secondly, the grey relational analysis method was used to individually study grey correlations among these six factors and soil cumulative infiltration. The results of the two methods were very similar. Rainfall duration was the most influential factor, followed by vegetation cover, vegetation type, rainfall intensity and antecedent soil moisture. The effect of slope gradient on soil cumulative infiltration was not significant.

Silicate fertilization of tropical soils: silicon availability and recovery index of sugarcane

Sugarcane is considered a Si-accumulating plant, but in Brazil, where several soil types are used for cultivation, there is little information about silicon (Si) fertilization. The objectives of this study were to evaluate the silicon availability, uptake and recovery index of Si from the applied silicate on tropical soils with and without silicate fertilization, in three crops. The experiments in pots (100 L) were performed with specific Si rates (0, 185, 370 and 555 kg ha-1 Si), three soils (Quartzipsamment-Q, 6 % clay; Rhodic Hapludox-RH, 22 % clay; and Rhodic Acrudox-RA, 68 % clay), with four replications. The silicon source was Ca-Mg silicate. The same Ca and Mg quantities were applied to all pots, with lime and/or MgCl2, when necessary. Sugarcane was harvested in the plant cane and first- and second-ratoon crops. The silicon rates increased soil Si availability and Si uptake by sugarcane and had a strong residual effect. The contents of soluble Si were reduced by harvesting and increased with silicate application in the following decreasing order: Q>RH>RA. The silicate rates promoted an increase in soluble Si-acetic acid at harvest for all crops and in all soils, except RA. The amounts of Si-CaCl2 were not influenced by silicate in the ratoon crops. The plant Si uptake increased according to the Si rates and was highest in RA at all harvests. The recovery index of applied Si (RI) of sugarcane increased over time, and was highest in RA.

Revisiting the S-index for soil physical quality and its use in Brazil

The S-index was introduced in 2004 in a publication by A.R. Dexter. S was proposed as an indicator of soil physical quality. A critical value delimiting soils with rich and poor physical quality was proposed. At present, Brazil is world leader in citations of Dexter's publication. In this publication the S-theory is mathematically revisited and extended. It is shown that S is mathematically correlated to bulk density and total porosity. As an absolute indicator, the value of S alone has proven to be incapable of predicting soil physical quality. The critical value does not always hold under boundary conditions described in the literature. This is to be expected because S is a static parameter, therefore implicitly unable to describe dynamic processes. As a relative indicator of soil physical quality, the S-index has no additional value over bulk density or total porosity. Therefore, in the opinion of the author, the fact that bulk density or total porosity are much more easily determined than the water retention curve for obtaining S disqualifies S as an advantageous indicator of relative soil physical quality. Among the several equations available for the fitting of water retention curves, the Groenevelt-Grant equation is preferable for use with S since one of its parameters and S are linearly correlated. Since efforts in soil physics research have the purpose of describing dynamic processes, it is the author's opinion that these efforts should shift towards mechanistic soil physics as opposed to the search for empirical correlations like S which, at present, represents far more than its reasonable share of soil physics in Brazil.

Index of soil physical quality of hardsetting soils on the brazilian coast

Many soils have a hard-setting behavior, also known as cohesive or "coesos". In such soils, the penetration resistance increases markedly when dry and decreases considerably when moist, creating serious limitations for plant emergence and growth. To evaluate the level of structure degradation in hard-setting soils with different texture classes and to create an index for assessing soil hardness levels in hard-setting soils, six soil representative profiles were selected in the field in various regions of Brazil. The following indices were tested: S, which measures soil physical quality, and H , which analyzes the degree of hardness and the effective stress in the soil during drying. Both indices were calculated using previously described functions based on data from the water-retention curves for the soils. The hard-setting values identified in different soils of the Brazilian Coastal Tablelands have distinct compaction (hardness) levels and can be satisfactorily measured by the H index. The S index was adequate for evaluating the structural characteristics of the hard-setting soils, classifying them as suitable or poor for cultivation, but only when the moisture level of the soil was near the inflection point. The H index showed that increases in density in hard-setting soils result from increases in effective stress and not from the soil texture. Values for Bd > 1.48 kg dm-3 classify the soil as hard-setting, and the structural organization is considered "poor".

Organic Matter Fractions and Quality of the Surface Layer of a Constructed and Vegetated Soil After Coal Mining. II - Physical Compartments and Carbon Management Index

Soils constructed after mining often have low carbon (C) stocks and low quality of organic matter (OM). Cover crops are decisive for the recovery process of these stocks, improving the quality of constructed soils. Therefore, the goal of this study was to evaluate the effect of cover crops on total organic C (TOC) stocks, C distribution in physical fractions of OM and the C management index (CMI) of a soil constructed after coal mining. The experiment was initiated in 2003 with six treatments: Hemarthria altissima (T1), Paspalum notatum (T2), Cynodon dactylon (T3), Urochloa brizantha (T4), bare constructed soil (T5), and natural soil (T6). Soil samples were collected in 2009 from the 0.00-0.03 m layer, and the TOC and C stocks in the physical particle size fractions (carbon in the coarse fraction - CCF, and mineral-associated carbon - MAC) and density fractions (free light fraction - FLF; occluded light fraction - OLF, and heavy fraction - HF) of OM were determined. The CMI components: carbon pool index (CPI), lability (L) and lability index (LI) were estimated by both fractionation methods. No differences were observed between TOC, CCF and MAC stocks. The lowest C stocks in FLF and OLF fractions were presented by T2, 0.86 and 0.61 Mg ha-1, respectively. The values of TOC stock, C stock in physical fractions and CMI were intermediate, greater than T5 and lower than T6 in all treatments, indicating the partial recovery of soil quality. As a result of the better adaptation of the species Hemarthria and Brizantha, resulting in greater accumulation of labile organic material, the CPI, L, LI and CMI values were higher in these treatments, suggesting a greater potential of these species for recovery of constructed soils.

Quantitative Assessment of Soil Physical Quality in Northern China Based on S-theory

ABSTRACT Quantitative assessment of soil physical quality is of great importance for eco-environmental pollution and soil quality studies. In this paper, based on the S-theory, data from 16 collection sites in the Haihe River Basin in northern China were used, and the effects of soil particle size distribution and bulk density on three important indices of theS-theory were investigated on a regional scale. The relationships between unsaturated hydraulic conductivityKi at the inflection point and S values (S/hi) were also studied using two different types of fitting equations. The results showed that the polynomial equation was better than the linear equation for describing the relationships between -log Ki and -logS, and -log Kiand -log (S/hi)2; and clay content was the most important factor affecting the soil physical quality index (S). The variation in the S index according to soil clay content was able to be fitted using a double-linear-line approach, with decrease in the S index being much faster for clay content less than 20 %. In contrast, the bulk density index was found to be less important than clay content. The average S index was 0.077, indicating that soil physical quality in the Haihe River Basin was good.

Biodiversity of Collembola in urban soils and their use as bioindicators for pollution

The objective of this work was to evaluate the effects of pollutants on the abundance and diversity of Collembola in urban soils. The research was carried out in three parks (Cişmigiu, Izvor and Unirea) in downtown Bucharest, where the intense car traffic accounts for 70% of the local air pollution. One site in particular (Cişmigiu park) was highly contaminated with Pb, Cd, Zn and Cu at about ten times the background levels of Pb. Collembola were sampled in 2006 (July, September, November) using the transect method: 2,475 individuals from 34 species of Collembola were collected from 210 samples of soil and litter. Numerical densities differed significantly between the studied sites.The influence of air pollutants on the springtail fauna was visible at the species richness diversity and soil pollution levels. Species richness was lowest in the most contaminated site (Cismigiu, 11 species), which presented an increase in springtails abundances, though. Some species may become resistant to pollution and occur in high numbers of individuals in polluted sites, which makes them a good bioindicator of pollutants.

Towards an ecological index for tropical soil quality based on soil macrofauna

The objective of this work was to construct a simple index based on the presence/absence of different groups of soil macrofauna to determine the ecological quality of soils. The index was tested with data from 20 sites in South and Central Tabasco, Mexico, and a positive relation between the model and the field observations was detected. The index showed that diverse agroforestry systems had the highest soil quality index (1.00), and monocrops without trees, such as pineapple, showed the lowest soil quality index (0.08). Further research is required to improve this model for natural systems that have very low earthworm biomass (<10 g m-2) and a high number of earthworm species (5-7), as it is in the tropical rain forest, whose soil quality index was medium (0.5). The application of this index will require an illustrated guide for its users. Further studies are required in order to test the use of this index by farmers.

Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

Optimization of OSEM parameters in myocardial perfusion imaging reconstruction as a function of body mass index: a clinical approach

AbstractObjective:The present study is aimed at contributing to identify the most appropriate OSEM parameters to generate myocardial perfusion imaging reconstructions with the best diagnostic quality, correlating them with patients' body mass index.Materials and Methods:The present study included 28 adult patients submitted to myocardial perfusion imaging in a public hospital. The OSEM method was utilized in the images reconstruction with six different combinations of iterations and subsets numbers. The images were analyzed by nuclear cardiology specialists taking their diagnostic value into consideration and indicating the most appropriate images in terms of diagnostic quality.Results:An overall scoring analysis demonstrated that the combination of four iterations and four subsets has generated the most appropriate images in terms of diagnostic quality for all the classes of body mass index; however, the role played by the combination of six iterations and four subsets is highlighted in relation to the higher body mass index classes.Conclusion:The use of optimized parameters seems to play a relevant role in the generation of images with better diagnostic quality, ensuring the diagnosis and consequential appropriate and effective treatment for the patient.