Management zones definition using soil chemical and physical attributes in a soybean area

Several equipments and methodologies have been developed to make available precision agriculture, especially considering the high cost of its implantation and sampling. An interesting possibility is to define management zones aim at dividing producing areas in smaller management zones that could be treated differently, serving as a source of recommendation and analysis. Thus, this trial used physical and chemical properties of soil and yield aiming at the generation of management zones in order to identify whether they can be used as recommendation and analysis. Management zones were generated by the Fuzzy C-Means algorithm and their evaluation was performed by calculating the reduction of variance and performing means tests. The division of the area into two management zones was considered appropriate for the present distinct averages of most soil properties and yield. The used methodology allowed the generation of management zones that can serve as source of recommendation and soil analysis; despite the relative efficiency has shown a reduced variance for all attributes in divisions in the three sub-regions, the ANOVA did not show significative differences among the management zones.

Redundant variables and the quality of management zones

ABSTRACT Precision agriculture (PA) allows farmers to identify and address variations in an agriculture field. Management zones (MZs) make PA more feasible and economical. The most important method for defining MZs is a fuzzy C-means algorithm, but selecting the variable for use as the input layer in the fuzzy process is problematic. BAZZI et al. (2013) used Moran’s bivariate spatial autocorrelation statistic to identify variables that are spatially correlated with yield while employing spatial autocorrelation. BAZZI et al. (2013) proposed that all redundant variables be eliminated and that the remaining variables would be considered appropriate on the MZ generation process. Thus, the objective of this work, a study case, was to test the hypothesis that redundant variables can harm the MZ delineation process. BAZZI This work was conducted in a 19.6-ha commercial field, and 15 MZ designs were generated by a fuzzy C-means algorithm and divided into two to five classes. Each design used a different composition of variables, including copper, silt, clay, and altitude. Some combinations of these variables produced superior MZs. None of the variable combinations produced statistically better performance that the MZ generated with no redundant variables. Thus, the other redundant variables can be discredited. The design with all variables did not provide a greater separation and organization of data among MZ classes and was not recommended.

Management zones using fuzzy clustering based on spatial-temporal variability of soil and corn yield

Clustering soil and crop data can be used as a basis for the definition of management zones because the data are grouped into clusters based on the similar interaction of these variables. Therefore, the objective of this study was to identify management zones using fuzzy c-means clustering analysis based on the spatial and temporal variability of soil attributes and corn yield. The study site (18 by 250-m in size) was located in Jaboticabal, São Paulo/Brazil. Corn yield was measured in one hundred 4.5 by 10-m cells along four parallel transects (25 observations per transect) over five growing seasons between 2001 and 2010. Soil chemical and physical attributes were measured. SAS procedure MIXED was used to identify which variable(s) most influenced the spatial variability of corn yield over the five study years. Basis saturation (BS) was the variable that better related to corn yield, thus, semivariograms models were fitted for BS and corn yield and then, data values were krigged. Management Zone Analyst software was used to carry out the fuzzy c-means clustering algorithm. The optimum number of management zones can change over time, as well as the degree of agreement between the BS and corn yield management zone maps. Thus, it is very important take into account the temporal variability of crop yield and soil attributes to delineate management zones accurately.

Abordagens semiquantitativa e quantitativa na avaliação da textura do solo por espectroscopia de reflectância bidirecional no VIS-NIR-SWIR

O objetivo deste trabalho foi avaliar o potencial da espectroscopia de reflectância no VIS-NIR-SWIR, para a caracterização granulométrica de amostras de solos de diferentes classes texturais, e obter modelos de predição dos teores de argila, silte e areia no solo. Utilizou-se um conjunto de amostras representativas de Latossolos e Argissolo de cinco locais do Estado do Mato Grosso do Sul. Os espectros do visível e do infravermelho próximo ao infravermelho de ondas curtas (de 350 a 2.500 nm) das amostras foram obtidos e analisados. Empregaram-se a análise de componentes principais (ACP), agrupamento por "fuzzy c-means", regressão logística multinomial (RLM) e regressão por mínimos quadrados parciais. Espectros característicos para as diferentes classes texturais e a segregação de amostras de classes texturais e de locais de coleta com características distintas, por meio da ACP, "fuzzy c-means" e RLM, mostram o potencial semiquantitativo dos dados de reflectância no VIS-NIR-SWIR. Obteve-se quantificação satisfatória quanto à argila (R²=0,92, RPD=3,59), ao silte (R²=0,80, RPD=2,15) e à areia (R²=0,87, RPD=2,62). As técnicas de espectroscopia de reflectância podem auxiliar na determinação da textura e da variabilidade espacial do solo com metodologias semiquantitativas ou quantitativas.

Data mining techniques for identification of spectrally homogeneous areas using NDVI temporal profiles of soybean crop

The aim of this study was to group temporal profiles of 10-day composites NDVI product by similarity, which was obtained by the SPOT Vegetation sensor, for municipalities with high soybean production in the state of Paraná, Brazil, in the 2005/2006 cropping season. Data mining is a valuable tool that allows extracting knowledge from a database, identifying valid, new, potentially useful and understandable patterns. Therefore, it was used the methods for clusters generation by means of the algorithms K-Means, MAXVER and DBSCAN, implemented in the WEKA software package. Clusters were created based on the average temporal profiles of NDVI of the 277 municipalities with high soybean production in the state and the best results were found with the K-Means algorithm, grouping the municipalities into six clusters, considering the period from the beginning of October until the end of March, which is equivalent to the crop vegetative cycle. Half of the generated clusters presented spectro-temporal pattern, a characteristic of soybeans and were mostly under the soybean belt in the state of Paraná, which shows good results that were obtained with the proposed methodology as for identification of homogeneous areas. These results will be useful for the creation of regional soybean "masks" to estimate the planted area for this crop.

Comparison between detailed digital and conventional soil maps of an area with complex geology

Since different pedologists will draw different soil maps of a same area, it is important to compare the differences between mapping by specialists and mapping techniques, as for example currently intensively discussed Digital Soil Mapping. Four detailed soil maps (scale 1:10.000) of a 182-ha sugarcane farm in the county of Rafard, São Paulo State, Brazil, were compared. The area has a large variation of soil formation factors. The maps were drawn independently by four soil scientists and compared with a fifth map obtained by a digital soil mapping technique. All pedologists were given the same set of information. As many field expeditions and soil pits as required by each surveyor were provided to define the mapping units (MUs). For the Digital Soil Map (DSM), spectral data were extracted from Landsat 5 Thematic Mapper (TM) imagery as well as six terrain attributes from the topographic map of the area. These data were summarized by principal component analysis to generate the map designs of groups through Fuzzy K-means clustering. Field observations were made to identify the soils in the MUs and classify them according to the Brazilian Soil Classification System (BSCS). To compare the conventional and digital (DSM) soil maps, they were crossed pairwise to generate confusion matrices that were mapped. The categorical analysis at each classification level of the BSCS showed that the agreement between the maps decreased towards the lower levels of classification and the great influence of the surveyor on both the mapping and definition of MUs in the soil map. The average correspondence between the conventional and DSM maps was similar. Therefore, the method used to obtain the DSM yielded similar results to those obtained by the conventional technique, while providing additional information about the landscape of each soil, useful for applications in future surveys of similar areas.

Fuzzy linguistic model for evaluating the risk of neonatal death

OBJECTIVE: To introduce a fuzzy linguistic model for evaluating the risk of neonatal death. METHODS: The study is based on the fuzziness of the variables newborn birth weight and gestational age at delivery. The inference used was Mamdani's method. Neonatologists were interviewed to estimate the risk of neonatal death under certain conditions and to allow comparing their opinions and the model values. RESULTS: The results were compared with experts' opinions and the Fuzzy model was able to capture the expert knowledge with a strong correlation (r=0.96). CONCLUSIONS: The linguistic model was able to estimate the risk of neonatal death when compared to experts' performance.

Chagas' disease: an algorithm for donor screening and positive donor counseling

Classical serological screening assays for Chagas' disease are time consuming and subjective. The objective of the present work is to evaluate the enzyme immuno-assay (ELISA) methodology and to propose an algorithm for blood banks to be applied to Chagas' disease. Seven thousand, nine hundred and ninety nine blood donor samples were screened by both reverse passive hemagglutination (RPHA) and indirect immunofluorescence assay (IFA). Samples reactive on RPHA and/or IFA were submitted to supplementary RPHA, IFA and complement fixation (CFA) tests. This strategy allowed us to create a panel of 60 samples to evaluate the ELISA methodology from 3 different manufacturers. The sensitivity of the screening by IFA and the 3 different ELISA's was 100%. The specificity was better on ELISA methodology. For Chagas disease, ELISA seems to be the best test for blood donor screening, because it showed high sensitivity and specificity, it is not subjective and can be automated. Therefore, it was possible to propose an algorithm to screen samples and confirm donor results at the blood bank.

Liver fibrosis progression in HIV/hepatitis C virus coinfected patients with normal aminotransferases levels

INTRODUCTION: Approximately 30% of hepatitis C virus (HCV) monoinfected patients present persistently normal alanine aminotransferase (ALT) levels. Most of these patients have a slow progression of liver fibrosis. Studies have demonstrated the rate of liver fibrosis progression in hepatitis C virus-human immunodeficiency virus (HCV-HIV) coinfected patients is faster than in patients infected only by HCV. Few studies have evaluated the histological features of chronic hepatitis C in HIV-infected patients with normal ALT levels. METHODS: HCV-HIV coinfected patients (HCV-RNA and anti-HIV positive) with known time of HCV infection (intravenous drugs users) were selected. Patients with hepatitis B surface antigen (HBsAg) positive or hepatitis C treatment before liver biopsy were excluded. Patients were considered to have a normal ALT levels if they had at least 3 normal determinations in the previous 6 months prior to liver biopsy. All patients were submitted to liver biopsy and METAVIR scale was used. RESULTS: Of 50 studied patients 40 (80%) were males. All patients were treated with antiretroviral therapy. The ALT levels were normal in 13 (26%) patients. HCV-HIV co-infected patients with normal ALT levels had presented means of the liver fibrosis stages (0.77±0.44 versus 1.86±1.38; p<0.001) periportal inflammatory activity (0.62±0.77 versus 2.24±1.35; p<0.001) and liver fibrosis progression rate (0.058±0.043 fibrosis unit/year versus 0.118±0.102 fibrosis unit/year) significantly lower as compared to those with elevated ALT. CONCLUSIONS: HCV-HIV coinfected patients with persistently normal ALTs showed slower progression of liver fibrosis. In these patients the development of liver cirrhosis is improbable.

A Novel Algorithm to Quantify Coronary Remodeling Using Inferred Normal Dimensions

Background:Vascular remodeling, the dynamic dimensional change in face of stress, can assume different directions as well as magnitudes in atherosclerotic disease. Classical measurements rely on reference to segments at a distance, risking inappropriate comparison between dislike vessel portions.Objective:to explore a new method for quantifying vessel remodeling, based on the comparison between a given target segment and its inferred normal dimensions.Methods:Geometric parameters and plaque composition were determined in 67 patients using three-vessel intravascular ultrasound with virtual histology (IVUS-VH). Coronary vessel remodeling at cross-section (n = 27.639) and lesion (n = 618) levels was assessed using classical metrics and a novel analytic algorithm based on the fractional vessel remodeling index (FVRI), which quantifies the total change in arterial wall dimensions related to the estimated normal dimension of the vessel. A prediction model was built to estimate the normal dimension of the vessel for calculation of FVRI.Results:According to the new algorithm, “Ectatic” remodeling pattern was least common, “Complete compensatory” remodeling was present in approximately half of the instances, and “Negative” and “Incomplete compensatory” remodeling types were detected in the remaining. Compared to a traditional diagnostic scheme, FVRI-based classification seemed to better discriminate plaque composition by IVUS-VH.Conclusion:Quantitative assessment of coronary remodeling using target segment dimensions offers a promising approach to evaluate the vessel response to plaque growth/regression.

Increasing the efficiency of utilization of soil and fertilizer phosphorus in the subtropical and tropical agricultural systems C

As a rule, soils of the subtropical and tropical regions, in which rainfall is not limiting, are acidic, and low in phosphorus, and, to a less extent, in other macro and micronutrients as well, such a sulfur, boron and zinc. The establishment of a permanent agricultural prac. tice therefore, demands relatively high usage of liming and phosphatic fertilization, to begin with. Several approaches, not mutually exclusive, could be used in order to increase the efficiency of utilization of soil and fertilizer phosphorus so that, goal of diminishing costs of production is reached. The use of liming materials bringing up pH to 6.0-6.5 causes the conversion of iron and aluminum phosphates to more available calcium phosphates; on the other hand, by raising calcium saturation in the exchange complex, it improves the development and operation if the root system which allows c or a higher utilization of all soil nutrients, including phosphorus, and helps of stand water deficits which may occur. The role of mycorrhizal fungi should be considered as a way of increasing soil and fertilizer P utilization, as well as the limitations thereof. Screening of and breeding for varieties with higher efficiency of uptake and utilization of soil and fertilizer phosphorus leads to a reduction in cost of inputs and to higher benefit/cost ratios. Corrective fertilization using ground rock phosphate helps to saturate the fixation power of the soil thereby reducing, as a consequence, the need for phosphorus in the maintenance fertilization. Maintenance fertilization, in which soluble phos-phatic sources are used, could be improved by several means whose performance has been proved: limimg, granula tion, placement, use of magnesium salts. Last, cost of phosphate fertilization could be further reduced, without impairing yields, through impairing yields, through changes in technology designed to obtain products better adapted to local conditions and to the availability or raw materials and energy sources.

Cloning and characterization of a V-ATPase subunit C from the American visceral leishmaniasis vector Lutzomyia longipalpis modulated during development and blood ingestion

Visceral leishmaniasis (VL) is a serious tropical disease that affects approximately 500 thousand people worldwide every year. In the Americas, VL is caused by the parasite Leishmania (Leishmania) infantum chagasi mainly transmitted by the bite of the sand fly vector Lutzomyia longipalpis. Despite recent advances in the study of interaction between Leishmania and sand flies, very little is known about sand fly protein expression profiles. Understanding how the expression of proteins may be affected by blood feeding and/or presence of parasite in the vector's midgut might allow us to devise new strategies for controlling the spread of leishmaniasis. In this work, we report the characterization of a vacuolar ATPase subunit C from L. longipalpis by screening of a midgut cDNA library with a 220 bp fragment identified by means of differential display reverse transcriptase-polymerase chain reaction analysis. The expression of the gene varies along insect development and is upregulated in males and bloodfed L. longipalpis, compared to unfed flies.

Uso da lógica fuzzy na caracterização do ambiente produtivo para matrizes gestantes

O objetivo desta pesquisa consistiu na avaliação do ambiente de alojamento, estimando as condições favoráveis ao melhor desempenho de matrizes gestantes. O experimento foi realizado no período compreendido entre 4-1 e 11-3-2005, em propriedade de produção industrial de suínos, localizada no município de Elias Fausto - SP. A pesquisa foi desenvolvida no setor de gestação, com 24 matrizes primíparas, 12 fêmeas alojadas em baias individuais (T1) e 12 em baias coletivas (T2). O trabalho foi dividido em duas etapas, em função da forma de avaliação dos dados: análise bioclimática e da qualidade do ar, e estimativa dos padrões de conforto térmico ambiental. As variáveis bioclimáticas T (ºC), UR (%), Tgn (ºC) e fisiológicas, taxa respiratória (mov min-1) e temperatura retal (ºC) apontam o sistema de confinamento em baias coletivas como o que possibilitou melhor condicionamento térmico natural às matrizes em gestação. O uso da teoria dos conjuntos fuzzy permitiu que se fizesse inferência entre os dados resultantes do trabalho experimental com os estabelecidos pela literatura, por intermédio de base de regras, para a determinação do conforto ambiental aplicado a matrizes na fase de gestação.

Sistema fuzzy para estimativa do bem-estar de matrizes pesadas

Entender o comportamento e suas pequenas variações decorrentes das mudanças do ambiente térmico e desenvolver modelos que simulem o bem-estar a partir de respostas das aves ao ambiente constituem o primeiro passo para a criação de um sistema de monitoramento digital de aves em galpões de produção. Neste trabalho, foi desenvolvido um sistema de suporte à decisão com base na teoria dos conjuntos fuzzy para a estimativa do bem-estar de matrizes pesadas em função de frequências e duração dos comportamentos expressos pelas aves. O desenvolvimento do sistema passou por cinco etapas distintas: 1) organização dos dados experimentais; 2) apresentação dos vídeos em entrevista com "especialista"; 3) criação das funções de pertinência com base nas entrevistas e na revisão da literatura; 4) simulação de frequências de ocorrências e tempos médios de expressão dos comportamentos classificados como indicadores de bem-estar utilizando equações de regressão obtidas na literatura, e 5) construção das regras, simulação e validação do sistema. O sistema fuzzy desenvolvido estimou satisfatoriamente o bem-estar de matrizes pesadas, tendo na sua última versão, com maior número de regras, acertado 77,8% dos dados experimentais, comparados com as respostas esperadas por um especialista. O sistema pode ser utilizado como instrumento matemático-computacional para apoiar decisões em galpões de produção de matrizes pesadas.

Use of data mining and spectral profiles to differentiate condition after harvest of coffee plants

This study aimed at identifying different conditions of coffee plants after harvesting period, using data mining and spectral behavior profiles from Hyperion/EO1 sensor. The Hyperion image, with spatial resolution of 30 m, was acquired in August 28th, 2008, at the end of the coffee harvest season in the studied area. For pre-processing imaging, atmospheric and signal/noise effect corrections were carried out using Flaash and MNF (Minimum Noise Fraction Transform) algorithms, respectively. Spectral behavior profiles (38) of different coffee varieties were generated from 150 Hyperion bands. The spectral behavior profiles were analyzed by Expectation-Maximization (EM) algorithm considering 2; 3; 4 and 5 clusters. T-test with 5% of significance was used to verify the similarity among the wavelength cluster means. The results demonstrated that it is possible to separate five different clusters, which were comprised by different coffee crop conditions making possible to improve future intervention actions.