Effect of dietary crude protein and energy content on nitrogen utilisation, water intake and urinary output in growing pigs

Selostus: Rehun valkuais- ja energiapitoisuuden vaikutus sikojen typen hyväksikäyttöön, veden kulutukseen ja virtsan eritykseen

Pursuant to Section 1 of House File 466

Pursuant to Section 1 of House File 466 of the 81' General Assembly, the Iowa Department of Transportation (DOT) is required to report to the Legislative Council regarding the progress of the building project for the Motor Vehicle Division and to inform the General Assembly of any significant delays or unanticipated expenditures. The Motor Vehicle Division building project has been completed and $293,753 was reverted. This will serve as the Iowa DOT's final report and will fulfill the requirements of HF 466.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Utilisation of reactive lysine from meat and bone meals of different ash content by growing-finishing pigs

Selostus: Tuhkapitoisuuden vaikutus lihaluujauhon reaktiivisen lysiinin hyväksikäyttöön lihasioilla

Brief DISCERN, six questions for the evaluation of evidence-based content of health-related websites.

OBJECTIVE: To extract and to validate a brief version of the DISCERN which could identify mental health-related websites with good content quality. METHOD: The present study is based on the analysis of data issued from six previous studies which used DISCERN and a standardized tool for the evaluation of content quality (evidence-based health information) of 388 mental health-related websites. After extracting the Brief DISCERN, several psychometric properties (content validity through a Factor analysis, internal consistency by the Cronbach's alpha index, predictive validity through the diagnostic tests, concurrent validity by the strength of association between the Brief DISCERN and the original DISCERN scores) were investigated to ascertain its general applicability. RESULTS: A Brief DISCERN composed of two factors and six items was extracted from the original 16 items version of the DISCERN. Cronbach's alpha coefficients were more than acceptable for the complete questionnaire (alpha=0.74) and for the two distinct domains: treatments information (alpha=0.87) and reliability (alpha=0.83). Sensibility and specificity of the Brief DISCERN cut-off score > or =16 in the detection of good content quality websites were 0.357 and 0.945, respectively. Its predictive positive and negative values were 0.98 and 0.83, respectively. A statistically significant linear correlation was found between the total scores of the Brief DISCERN and those of the original DISCERN (r=0.84 and p<0.0005). CONCLUSION: The Brief DISCERN seems to be a reliable and valid instrument able to discriminate between websites with good and poor content quality. PRACTICE IMPLICATIONS: The Brief DISCERN is a simple tool which could facilitate the identification of good information on the web by patients and general consumers.

Soil spectral library and its use in soil classification

Soil science has sought to develop better techniques for the classification of soils, one of which is the use of remote sensing applications. The use of ground sensors to obtain soil spectral data has enabled the characterization of these data and the advancement of techniques for the quantification of soil attributes. In order to do this, the creation of a soil spectral library is necessary. A spectral library should be representative of the variability of the soils in a region. The objective of this study was to create a spectral library of distinct soils from several agricultural regions of Brazil. Spectral data were collected (using a Fieldspec sensor, 350-2,500 nm) for the horizons of 223 soil profiles from the regions of Matão, Paraguaçu Paulista, Andradina, Ipaussu, Mirandópolis, Piracicaba, São Carlos, Araraquara, Guararapes, Valparaíso (SP); Naviraí, Maracajú, Rio Brilhante, Três Lagoas (MS); Goianésia (GO); and Uberaba and Lagoa da Prata (MG). A Principal Component Analysis (PCA) of the data was then performed and a graphic representation of the spectral curve was created for each profile. The reflectance intensity of the curves was principally influenced by the levels of Fe2O3, clay, organic matter and the presence of opaque minerals. There was no change in the spectral curves in the horizons of the Latossolos, Nitossolos, and Neossolos Quartzarênicos. Argissolos had superficial horizon curves with the greatest intensity of reflection above 2,200 nm. Cambissolos and Neossolos Litólicos had curves with greater reflectance intensity in poorly developed horizons. Gleisols showed a convex curve in the region of 350-400 nm. The PCA was able to separate different data collection areas according to the region of source material. Principal component one (PC1) was correlated with the intensity of reflectance samples and PC2 with the slope between the visible and infrared samples. The use of the Spectral Library as an indicator of possible soil classes proved to be an important tool in profile classification.

Water-dispersible clay in soils treated with sewage sludge

A by-product of Wastewater Treatment Stations is sewage sludge. By treatment and processing, the sludge is made suitable for rational and environmentally safe use in agriculture. The aim of this study was to assess the influence of different doses of limed sewage sludge (50 %) on clay dispersion in soil samples with different textures (clayey and medium). The study was conducted with soil samples collected from native forest, on a Red Latosol (Brazilian classification: Latossolo Vermelho distroférrico) loamy soil in Londrina (PR) and a Red-Yellow Latosol (BC: Latossolo Vermelho-Amarelo distrófico) medium texture soil in Jaguapitã (PR). Pots were filled with 3 kg of air-dried fine earth and kept in greenhouse. The experiment was arranged in a randomized block design with six treatments: T1 control, and treatments with limed sewage sludge (50 %) as follows: T2 (3 t ha-1), T3 (6 t ha-1), T4 (12 t ha-1), T5 (24 t ha-1) and T6 (48 t ha-1) and five replications. The incubation time was 180 days. At the end of this period, the pots were opened and two sub-samples per treatment collected to determine pH-H2O, pH KCl (1 mol L-1), organic matter content, water-dispersible clay, ΔpH (pH KCl - pH-H2O) and estimated PZC (point of zero charge): PZC = 2 pH KCl - pH-H2O, as well as the mineralogy of the clay fraction, determined by X ray diffraction. The results showed no significant difference in the average values for water-dispersible clay between the control and the other treatments for the two soil samples studied and ΔpH was the variable that correlated best with water-dispersible clay in both soils.

Temporal variability of soil water content under different surface conditions in the semiarid region of the Pernambuco state

Rainfall in the semiarid region of Pernambuco is characterized by irregular distribution in time and space, which significantly hinders the rainfed agriculture in the region. This work aims to evaluate the temporal profile of soil moisture in the semiarid region of the Pernambuco State (Brazil) and the effect of different soil surface conditions on soil water content variation and the yield of rainfed beans. To monitor soil water content, five plots 4.5 m wide by 11 m long were installed in a Yellow Argisol (Ultisol). The following treatments were adopted in the experimental plots: natural vegetation, bean intercropped with cactus, beans planted down the slope, beans planted along contour lines with mulch and rock barriers, and bare soil. In each plot, eight PVC access tubes were installed for monitoring the soil water content profile at depths of 0.20 and 0.40 m using a neutron probe device. The surface condition significantly influenced the soil water content variation, both in the dry and rainy seasons. The use of mulch, associated with rock barriers, provided higher soil water content levels than the other treatments and increased the rainfed beans production.

Remaining phosphorus estimated by pedotransfer function

Although the determination of remaining phosphorus (Prem) is simple, accurate values could also be estimated with a pedotransfer function (PTF) aiming at the additional use of soil analysis data and/or Prem replacement by an even simpler determination. The purpose of this paper was to develop a pedotransfer function to estimate Prem values of soils of the State of São Paulo based on properties with easier or routine laboratory determination. A pedotransfer function was developed by artificial neural networks (ANN) from a database of Prem values, pH values measured in 1 mol L-1 NaF solution (pH NaF) and soil chemical and physical properties of samples collected during soil classification activities carried out in the State of São Paulo by the Agronomic Institute of Campinas (IAC). Furthermore, a pedotransfer function was developed by regressing Prem values against the same predictor variables of the ANN-based PTF. Results showed that Prem values can be calculated more accurately with the ANN-based pedotransfer function with the input variables pH NaF values along with the sum of exchangeable bases (SB) and the exchangeable aluminum (Al3+) soil content. In addition, the accuracy of the Prem estimates by ANN-based PTF were more sensitive to increases in the experimental database size. Although the database used in this study was not comprehensive enough for the establishment of a definitive pedotrasnfer function for Prem estimation, results indicated the inclusion of Prem and pH NaF measurements among the soil testing evaluations as promising ind order to provide a greater database for the development of an ANN-based pedotransfer function for accurate Prem estimates from pH NaF, SB, and Al3+ values.

Effect of NPK fertilization on production and leaf nutrient content of eucalyptus minicuttings in nutrient solution

Adequate nutrient levels in plants vary according to the species or clone, age and management practice. Therefore, adjustments of the nutrient solution are often necessary according to the plant material for multiplication. This study aimed to evaluate the influence of NPK fertilization on production and leaf nutrient contents of eucalyptus cuttings in nutrient solution. The study was conducted from November 2008 to January 2009 in a greenhouse. The experimental design was completely randomized fractional factorial (4 x 4 x 4)½, with a total of 32 treatments with three replications. The treatments consisted of four doses of N (50, 100, 200 and 400 mg L-1) as urea, P (7.5, 15, 30 and 60 mg L-1) in the form of phosphoric acid and K (50, 100, 200 and 400 mg L-1) in the form of potassium chloride in the nutrient solution. Only the effect of N alone was significant for the number and dry weight of minicuttings per ministump, with a linear decreasing effect with increasing N levels. The highest number of cuttings was obtained at a dose of 50, 7.5 and 50 mg L-1 of N, P and K, respectively.

Method to estimate soil macroporosity and microporosity based on sand content and bulk density

Macroporosity is often used in the determination of soil compaction. Reduced macroporosity can lead to poor drainage, low root aeration and soil degradation. The aim of this study was to develop and test different models to estimate macro and microporosity efficiently, using multiple regression. Ten soils were selected within a large range of textures: sand (Sa) 0.07-0.84; silt 0.03-0.24; clay 0.13-0.78 kg kg-1 and subjected to three compaction levels (three bulk densities, BD). Two models with similar accuracy were selected, with a mean error of about 0.02 m³ m-3 (2 %). The model y = a + b.BD + c.Sa, named model 2, was selected for its simplicity to estimate Macro (Ma), Micro (Mi) or total porosity (TP): Ma = 0.693 - 0.465 BD + 0.212 Sa; Mi = 0.337 + 0.120 BD - 0.294 Sa; TP = 1.030 - 0.345 BD 0.082 Sa; porosity values were expressed in m³ m-3; BD in kg dm-3; and Sa in kg kg-1. The model was tested with 76 datum set of several other authors. An error of about 0.04 m³ m-3 (4 %) was observed. Simulations of variations in BD as a function of Sa are presented for Ma = 0 and Ma = 0.10 (10 %). The macroporosity equation was remodeled to obtain other compaction indexes: a) to simulate maximum bulk density (MBD) as a function of Sa (Equation 11), in agreement with literature data; b) to simulate relative bulk density (RBD) as a function of BD and Sa (Equation 13); c) another model to simulate RBD as a function of Ma and Sa (Equation 16), confirming the independence of this variable in relation to Sa for a fixed value of macroporosity and, also, proving the hypothesis of Hakansson & Lipiec that RBD = 0.87 corresponds approximately to 10 % macroporosity (Ma = 0.10 m³ m-3).

The Patientʼs Perception of Eosinophilic Esophagitis Related Symptoms: a Qualitative Content Analysis

Background and Aims: The international EEsAI study group is currently developing an activity index for Eosinophilic Esophagitis (EoE). A potential discrepancy between patient and physician reported EoE symptoms has not been assessed yet. Therefore, we aimed to evaluate patient reported items describing their EoE activity and to compare these with the physicianʼs perception. Methods: A questionnaire was sent to 100 EoE patients in Switzerland. EoE-related symptoms dependent and independent of food intake were reported by patients. Results were analyzed using a qualitative content analysis and compared with symptoms reported by international EoE experts in Delphi rounds. Results: The questionnaire response rate was 64/100. The following items were developed by combining categories based on patients answers: food-consistency related dysphagia, frequency and severity of dysphagia, food impaction, strategies to avoid food impaction, food allergy, drinking-related retrosternal pain. The following food categories associated with dysphagia were identified: meat, rice, dry bread, French fries, raw, fibrous foods, others. Sports and psychological stress were identified as triggers for non-food intake related EoE symptoms. A good correlation was found between patient and physicianʼs reported EoE related symptoms. Conclusions: There is a good correlation between patient reported symptoms and the physicianʼs perception of clinical items as reported by international EoE experts. These patient reported outcomes will now be incorporated into the EEsAI questionnaire that measures EoE activity.