Spatial variability of noise level in agricultural machines

The knowledge of the spatial variability of noise levels and the build of kriging maps can help the evaluation of the salubrity of environments occupied by agricultural workers. Therefore, the objective of this research was to characterize the spatial variability of the noise level generated by four agricultural machines, using geostatistics, and to verify if the values are within the limits of human comfort. The evaluated machines were: harvester, chainsaw, brushcutter and tractor. The data were collected at the height of the operator's ear and at different distances. Through the results, it was possible to verify that the use of geostatistics, by kriging technique, made it possible to define areas with different levels for the data collected. With exception of the harvester, all of machines presented noise levels above than 85 dB (A) near to the operator, demanding the use of hearing protection.

Comparison of maps of spatial variability of soil resistance to penetration constructed with and without covariables using a spatial linear model

A study about the spatial variability of data of soil resistance to penetration (RSP) was conducted at layers 0.0-0.1 m, 0.1-0.2 m and 0.2-0.3 m depth, using the statistical methods in univariate forms, i.e., using traditional geostatistics, forming thematic maps by ordinary kriging for each layer of the study. It was analyzed the RSP in layer 0.2-0.3 m depth through a spatial linear model (SLM), which considered the layers 0.0-0.1 m and 0.1-0.2 m in depth as covariable, obtaining an estimation model and a thematic map by universal kriging. The thematic maps of the RSP at layer 0.2-0.3 m depth, constructed by both methods, were compared using measures of accuracy obtained from the construction of the matrix of errors and confusion matrix. There are similarities between the thematic maps. All maps showed that the RSP is higher in the north region.

Spatial variability of leaf nutrient contents in a drip irrigated citrus orchard

This study aimed to evaluate the spatial variability of leaf content of macro and micronutrients. The citrus plants orchard with 5 years of age, planted at regular intervals of 8 x 7 m, was managed under drip irrigation. Leaf samples were collected from each plant to be analyzed in the laboratory. Data were analyzed using the software R, version 2.5.1 Copyright (C) 2007, along with geostatistics package GeoR. All contents of macro and micronutrients studied were adjusted to normal distribution and showed spatial dependence.The best-fit models, based on the likelihood, for the macro and micronutrients were the spherical and matern. It is suggest for the macronutrients nitrogen, phosphorus, potassium, calcium, magnesium and sulfur the minimum distances between samples of 37; 58; 29; 63; 46 and 15 m respectively, while for the micronutrients boron, copper, iron, manganese and zinc, the distances suggests are 29; 9; 113; 35 and 14 m, respectively.

Soil sampling intensity and spatial distribution pattern of soils attributes and corn yield in no-tillage system

Taking into account that the sampling intensity of soil attributes is a determining factor for applying of concepts of precision agriculture, this study aims to determine the spatial distribution pattern of soil attributes and corn yield at four soil sampling intensities and verify how sampling intensity affects cause-effect relationship between soil attributes and corn yield. A 100-referenced point sample grid was imposed on the experimental site. Thus, each sampling cell encompassed an area of 45 m² and was composed of five 10-m long crop rows, where referenced points were considered the center of the cell. Samples were taken from at 0 to 0.1 m and 0.1 to 0.2 m depths. Soil chemical attributes and clay content were evaluated. Sampling intensities were established by initial 100-point sampling, resulting data sets of 100; 75; 50 and 25 points. The data were submitted to descriptive statistical and geostatistics analyses. The best sampling intensity to know the spatial distribution pattern was dependent on the soil attribute being studied. The attributes P and K+ content showed higher spatial variability; while the clay content, Ca2+, Mg2+ and base saturation values (V) showed lesser spatial variability. The spatial distribution pattern of clay content and V at the 100-point sampling were the ones which best explained the spatial distribution pattern of corn yield.

Erosion factors and magnetic susceptibility in differet compartments of a slope in Gilbués-PI, Brazil

The erosion is the degradation of soil with effects on crop productivity and pollution of the environment. To understand the spatial variability of this phenomenon, geostatistical techniques and concepts of soil-landscape can be used to identify landscape compartments with different potential of erosion. The aim of this study was to understand the factors of erosion in landscape compartments and the relations with the magnetic susceptibility (MS) of the soils in a slope in Gilbués, state of Piauí (PI), Brazil. Sampling meshes were set in compartments I and II with 121 points and in compartment III with 99 points spaced every 10 meters. There was significant difference to erodibility (K) and risk of erosion (RE); the spatial variability of MS was lower than the factors of soil erosion. The soil losses (A), the natural erosion potential (NEP), the RE and the MS had spatial relation with the topographic factor, indicating dependence of the erosion with the relief. We concluded that losses of soil, natural erosion potential and risk of erosion have spatial relation with the topographic factor, showing the dependence of the erosion factors with the relief. The soil magnetic susceptibility can be used as an auxiliary variable in the indirect quantification of the erodibility factor and the risk of soil erosion.

Spatial variability of air dry bulb temperature and black globe humidity index in a broiler house during the heating phase

The air dry-bulb temperature (t db),as well as the black globe humidity index (BGHI), exert great influence on the development of broiler chickens during their heating phase. Therefore, the aim of this study was to analyze the structure and the magnitude of the t db and BGHI spatial variability, using geostatistics tools such as semivariogram analysis and also producing kriging maps. The experiment was conducted in the west mesoregion of the states of Minas Gerais in 2010, in a commercial broiler house with heating system consisting of two furnaces that heat the air indirectly, in the firsts 14 days of the birds' life. The data were registered at intervals of five minutes in the period from 8 a.m. to 10 a.m. The variables were evaluated by variograms fitted by residual maximum likelihood (REML) testing the Spherical and Exponential models. Kriging maps were generated based on the best model used to fit the variogram. It was possible to characterize the variability of the t db and BGHI, which allowed observing the spatial dependence by using geostatistics techniques. In addition, the use of geostatistics and distribution maps made possible to identify problems in the heating system in regions inside the broiler house that may harm the development of chicks.

Effects of vinasse application under the physical attributes of soil covered with sugarcane straw

Areas under vinasse application have been associated to favorable physical conditions for root development, aeration, infiltration and water movement in soil profile. This study aimed to evaluate changes on physical attributes of soil under sugarcane straw after vinasse application in two sugarcane growing areas (Area 1 and Area 2) under mechanized management in the state of Paraíba, Brazil. In each area, the samples were collected in the 0-0.20, 0.20-0.40 and 0.40-0.60m layers of the soil, in 36 points, distributed in a 10×10m mesh, one day before and 40 days after vinasse application. The data were submitted to multivariate analysis with repeated measures and geostatistics. The vinasse application decreased soil density and increased total porosity in both Areas and increased organic matter in Area 2. In Area 1 occurred pure nugget effect for the fractions of sand, silt and clay, independent of soil layer. In Area 2, this effect was verified mostly at superficial layers, except for the fraction of clay that presented a moderate degree of spatial dependence.

Spatial variability of mechanical resistance to penetration evaluated with mobile unit on haplic vertisol cultivated with mango

Since the advent of mechanized farming and intensive use of agricultural machinery and implements on the properties, the soil began to receive greater load of machinery traffic, which can cause increased soil compaction. The aim of this study was to evaluate the spatial variability of soil mechanical resistance to penetration (RP) in the layers of 0.00-0.10, 0.10-0.20, 0.20-0.30 and 0.30-0.40m, using geostatistics in an area cultivated with mango in Haplic Vertisol of the northeastern semi-arid, with mobile unit equipped with electronic penetrometer. The RP data was collected in 56 points from an area of 3 ha, and random soil samples were collected to determine the soil moisture and texture. For RP data analysis we used descriptive statistics and geostatistics. The soil mechanical resistance to penetration presented increased variability, with adjustment of the spherical and exponential semivariograms in the layers. We found that 42% of the area in the layer of 0.10-0.20m showed RP values above 2.70 MPa. Maximum values of RP were found in the layer of 0.19-0.27m, predominantly in 56% of the area.

Transport of broilers: load microclimate during Brazilian summer

The objective of this study was to characterize the microclimatic profile of broiler transport trucks under commercial conditions, in the summer, by continuous monitoring of environmental variables (temperature and air relative humidity). Three loads were monitored from farm to slaughterhouse, considering factors such as distance and day periods (morning, afternoon, and night). To obtain the profile of the environmental variables during journey, data loggers, that determined the microclimate to which birds were submitted, were installed in the trucks; data loggers also allowed visualization of the Enthalpy Comfort Index (ECI) so that load regions could be classified according to heat comfort limits for 6-week old poultries. Temperature, relative humidity, and ECI in the truck were analyzed, using geostatistics, by the ordinary kriging method. The afternoon was the most critical period, and truck central and rear regions were most problematic for chickens, thus most susceptible to losses.

Methodology for spatialization of intense rainfall equation parameters

The aim of this study was to generate maps of intense rainfall equation parameters using interpolated maximum intense rainfall data. The study area comprised Espírito Santo State, Brazil. A total of 59 intense rainfall equations were used to interpolate maximum intense rainfall, with a 1 x 1 km spatial resolution. Maximum intense rainfall was interpolated considering recurrence of 2; 5; 10; 20; 50 and 100 years, and duration of 10; 20; 30; 40; 50; 60; 120; 240; 360; 420; 660; 720; 900; 1,140; 1,380 and 1,440 minutes, resulting in 96 maps of maximum intense rainfall. The used interpolators were inverse distance weighting and ordinary kriging, for which significance level (p-value) and coefficient of determination (R²) were evaluated for the cross-validation data, choosing the method that presented better R² to generate maps. Finally, maps of maximum intense precipitation were used to estimate, cell by cell, the intense rainfall equation parameters. In comparison with literature data, the mean percentage error of estimated intense rainfall equations was 13.8%. Maps of spatialized parameters, obtained in this study, are of simple use; once they are georeferenced, they may be imported into any geographic information system to be used for a specific area of interest.

Spatial influence of physical and chemical parameters on management zone definition in apple orchards

ABSTRACT Precision agriculture adoption in Brazilian apple orchards is still incipient. This study aimed at evaluating the spatial variability of certain soil properties as soil density, soil penetration resistance, electrical conductivity, yield, and fruit quality in an apple orchard through digital mapping, as well as assessing the correlation between these factors by means of geostatistics, establishing management zones. Forty representative points were set within 2.5 hectares of apple orchard, wherein soil samples were collected and analyzed, besides measurements of fruit quality (Brix degree, size or diameter, pulp firmness and color) to generate an overall index quality. We concluded that the fruit quality indexes, when isolated, did not show strong spatial dependence, unlike the index of fruit quality (FQI), derived from a combination of these parameters, allowing orchard planning according to management zones based on quality.

Weed mapping using a machine vision system

Weed mapping is a useful tool for site-specific herbicide applications. The objectives of this study were (1) to determine the percentage of land area covered by weeds in no-till and conventionally tilled fields of common bean using digital image processing and geostatistics, and (2) to compare two types of cameras. Two digital cameras (color and infrared) and a differential GPS were affixed to a center pivot structure for image acquisition. Sample field images were acquired in a regular grid pattern, and the images were processed to estimate the percentage of weed cover. After calculating the georeferenced weed percentage values, maps were constructed using geostatistical techniques. Based on the results, color images are recommended for mapping the percentage of weed cover in no-till systems, while infrared images are recommended for weed mapping in conventional tillage systems.

Weed mapping using techniques of precision agriculture

The aim of this study was to identify and map the weed population in a no-tillage area. Geostatistical techniques were used in the mapping in order to assess this information as a tool for the localized application of herbicides. The area of study is 58.08 hectares wide and was sampled in a fixed square grid (which point spaced 50 m, 232 points) using a GPS receiver. In each point the weeds species and population were analyzed in a square with a 0.25 m2 fixed area. The species Ipomoea grandifolia, Gnaphalium spicatum, Richardia spp. and Emilia sonchifolia have presented no spatial dependence. However, the species Conyza spp., C. echinatus and E. indica have shown a spatial correlation. Among the models tested, the spherical model has shown had a better fit for Conyza spp. and Eleusine indica and the Gaussian model for Cenchrus echinatus. The three species have a clumped spatial distribution. The mapping of weeds can be a tool for localized control, making herbicide use more rational, effective and economical.

Spatial variability of soil fertility and its relationship with seed physiological potential in a soybean production area

The correlation of soil fertility x seed physiological potential is very important in the area of seed technology but results published with that theme are contradictory. For this reason, this study to evaluate the correlations between soil chemical properties and physiological potential of soybean seeds. On georeferenced points, both soil and seeds were sampled for analysis of soil fertility and seed physiological potential. Data were assessed by the following analyses: descriptive statistics; Pearson's linear correlation; and geostatistics. The adjusted parameters of the semivariograms were used to produce maps of spatial distribution for each variable. Organic matter content, Mn and Cu showed significant effects on seed germination. Most variables studied presented moderate to high spatial dependence. Germination and accelerated aging of seeds, and P, Ca, Mg, Mn, Cu and Zn showed a better fit to spherical semivariogram: organic matter, pH and K had a better fit to Gaussian model; and V% and Fe showed a better fit to the linear model. The values for range of spatial dependence varied from 89.9 m for P until 651.4 m for Fe. These values should be considered when new samples are collected for assessing soil fertility in this production area.

Modélisation de l'utilisation de l'habitat du béluga du Saint-Laurent en fonction de ses proies à l'embouchure de la rivière Saguenay et à la baie Sainte-Marguerite

Le béluga du Saint-Laurent est une espèce menacée au Canada et protégée par la Loi sur les espèces en péril du Canada. La détermination des fonctions biologiques de ses habitats essentiels est nécessaire afin d’assurer le rétablissement de la population. Parcs Canada a entamé en 2009 un suivi des proies du béluga dans deux de ses aires de fréquentation intensive situées dans le Parc marin du Saguenay–Saint-Laurent : l’embouchure de la rivière Saguenay et la baie Sainte-Marguerite. L’étude de l’abondance et de la distribution des proies est réalisée par sondage hydroacoustique le long de transects à l’aide d’un échosondeur multifréquences. Un protocole d’observations systématiques du béluga est mené simultanément aux sondages hydroacoustiques à partir de sites terrestres. Le premier objectif de cette étude est de développer la méthodologie concernant le traitement, la classification et la cartographie des données hydroacoustiques échantillonnées. L’objectif principal consiste à déterminer si l’abondance et la distribution des proies pélagiques ont une influence sur l’utilisation de ces deux habitats par le béluga. La cartographie de la biomasse relative de poissons a été réalisée pour la couche de surface, la couche en profondeur et pour l’ensemble de la colonne d’eau par krigeage ordinaire pour les deux habitats pour les 29 transects. À la baie Sainte-Marguerite, le nombre de bélugas observés augmente avec la biomasse relative des proies en surface et en profondeur. À l’embouchure de la rivière Saguenay, les résultats n’ont pas été concluants. Les résultats suggèrent que l’alimentation pourrait être l’une des fonctions biologiques de la baie Sainte-Marguerite.