Eduardo Godoy de Souza

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.

Variabilidade espacial dos atributos físicos do solo e da produtividade em um Latossolo Bruno distrófico da região de Cascavel, PR

Through geostatistics techniques, contour maps, were produced by interpolation using ordinary kriging, representing the spatial variability of the physical attributes; soil density [kg dm-3], soil water [g g-1] and penetration resistance [MPa] in the 0-10, 10-20 and 20-30 cm of depth, besides the soy bean productivity [t ha-1]. Soil attributes and yield data, derived from an unaligned stratified systematic sampling scheme, subdivided in portions with localized management (CML) and without localized management (SML) for the agricultural year 1998/99. The productivity maps in general presented a similar variability standard for the distribution in the non responding area as well as in the area with different chemical treatments applied in the CML plots. Where as the physical attributes presented a similar behavior for the two methods of management. Amongst the physical attributes studied, the penetration resistance in the 0-10 cm of depth was the variable which was best correlated with the productivity.

Software para estimativa do custo operacional de máquinas agrícolas - MAQCONTROL

The rational mechanization has as main objectives the selection and optimization of mechanized systems. An adequate purchase of agricultural machinery is not sufficient if its use is not controlled in operational and financial aspects. This work describes the development of software to estimate operational costs of agricultural machinery (MAQCONTROL), using Borland Delphis development environment and Firebird database. The operational costs were divided in fixed and variable. In fixed costs, the expenses with depreciation, interest, storage and insurance were estimated. In variable costs, the emphasis was given to the expenses on maintenance, lubricating oils, filters, tires, grease, fuel, small repairs, and parts replacement. Results have shown the software efficiency for the proposed objectives. Therefore, the MAQCONTROL software proved to be an important tool in the rural management process, because it reduces information costs and accelerate the precise determination of operational costs of farm machinery.

PRAPRAG: software para planejamento racional de máquinas agrícolas

The software PRAPRAG is a tool used for choosing agricultural machines and implements that present the lowest cost per area or produced amount, as well as, to it makes the machines acquisition planning for the agricultural property, from both technical and economical points of view. It was used the programming language Borland Delphi 3.0. From the machine and implement handouts, it was created a database where the user can register and modify their characteristics of use. The software showed to be a useful and friendly tool. The software provides high speed, safety and reliability for the productive and economical process of the properties, at the selection and acquisition of agricultural systems, as well as for the determination of costs with the used labor.

Anisotropia no estudo da variabilidade espacial de algumas variáveis químicas do solo

Studies on soil fertility mapping based on geostatistics should consider some spatial variability characteristics such as spatial continuity and absence of anisotropy. The present study reports an anisotropic analysis of the spatial variability of the following soil chemical variables: iron (Fe), potential acidity (H + Al), organic matter (OM) and manganese (Mn) of a data set of 128 plots without local chemical management, spatially referenced, studied between 1998 and 2002 in a dystrophic Red Latosol (Oxisol), in Cascavel, Parana, Brazil. Anisotropy was identified through the construction of directional semivariograms with adjusted models and corrected through linear transformations and by combined models. Thereafter a model was used adjusted to the omnidirectional semivariogram for the construction of thematic variability maps of the studied variables. The existence of geometric anisotropy was observed for the variable H + Al. The variables MO, Mn and Fe evidenced the presence of combined anisotropy. The geometric anisotropy was first corrected and then the zonal anisotropy was adjusted. Based on anisotropy it was possible to eliminate the biased directions, enhancing the semivariogram fitting and precision of the thematic maps of chemical variables.

Optimization of management zone delineation by using spatial principal components

Variable selection techniques were evaluated jointly with the Fuzzy C-means algorithm.A new variable selection approach, for defining management zones, was proposed.The new approach, named MPCA-SC, provided the best performance for the Fuzzy C-means.MPCA-SC provided management zones more viable from the viewpoint of field operations. Definition of management zones is the delimitation of sub-areas with similar topographic, soil and crop characteristics within a field. Among the many variables that can be used for this definition, those that are stable and spatially correlated with yield are more often recommended for use. Clustering algorithms such as Fuzzy C-means are also frequently applied to define management zones. Three variable selection techniques that can be applied with Fuzzy C-means are spatial correlation analysis, principal component analysis (PCA), and multivariate spatial analysis based on Morans index PCA (MULTISPATI-PCA). In this study, the efficiency of each of these three techniques used in conjunction with the clustering method was assessed. Furthermore, a new variable selection approach, named MPCA-SC, based on the combined use of Morans bivariate spatial autocorrelation statistic and MULTISPATI-PCA, was proposed and tested. The evaluation was performed by using data collected from 2010 to 2014 from three agricultural areas in Parana State, Brazil, with corn and soybean crops, generating two, three, and four classes. The delineated management zones were different according to the method used, and MPCA-SC provided the best performance for the Fuzzy C-means algorithm and the best variance reduction values of the data after the delimitation of the sub-areas. Furthermore, MPCA-SC provided management zones with greater internal homogeneity, making them more viable for implementation from the viewpoint of field operations.

Model to estimate the sampling density for establishment of yield mapping

Yield mapping represents the spatial variability concerning the features of a productive area and allows intervening on the next year production, for example, on a site-specific input application. The trial aimed at verifying the influence of a sampling density and the type of interpolator on yield mapping precision to be produced by a manual sampling of grains. This solution is usually adopted when a combine with yield monitor can not be used. An yield map was developed using data obtained from a combine equipped with yield monitor during corn harvesting. From this map, 84 sample grids were established and through three interpolators: inverse of square distance, inverse of distance and ordinary kriging, 252 yield maps were created. Then they were compared with the original one using the coefficient of relative deviation (CRD) and the kappa index. The loss regarding yield mapping information increased as the sampling density decreased. Besides, it was also dependent on the interpolation method used. A multiple regression model was adjusted to the variable CRD, according to the following variables: spatial variability index and sampling density. This model aimed at aiding the farmer to define the sampling density, thus, allowing to obtain the manual yield mapping, during eventual problems in the yield monitor.

Unidades de manejo a partir de mapas de produtividade normalizada e padronizada equivalente

Through the site-specific management, the precision agriculture brings new techniques for the agricultural sector, as well as a larger detailing of the used methods and increase of the global efficiency of the system. The objective of this work was to analyze two techniques for definition of management zones using soybean yield maps, in a productive area handled with localized fertilization and other with conventional fertilization. The sampling area has 1.74 ha, with 128 plots with site-specific fertilization and 128 plots with conventional fertilization. The productivity data were normalized by two techniques (normalized and standardized equivalent productivity), being later classified in management zones. It can be concluded that the two methods of management zones definition had revealed to be efficient, presenting similarities in the data disposal. Due to the fact that the equivalent standardized productivity uses standard score, it contemplates a better statistics justification.

Influência da direção de semeadura do milho nas variáveis reflectância e índice de vegetação verde normalizado

The objective of this work was to study the influence of the row direction of corn (Zea mays) on its spectral properties measured in the field, including the green normalized difference vegetation index (Green NDVI). Spectral properties of corn are known to be related to the nitrogen (N) status of the corn and may form the basis for real-time site-specific rates of N application. Row direction effects on spectral properties may be substantial before canopy closure. If so, it will be necessary to account for these effects in order to accurately predict the N need of corn from spectral measurements. Corn was planted directly, with no tillage, in North-South (NS) and East-West (EW) oriented rows. Nitrogen was applied as ammonium nitrate at a rate of 160 kg N ha-1. Reflectance was measured with spectral radiometers placed 30 cm above individual plants. Reflectance and green NDVI were bly dependent on time of day for corn in NS rows, and much less so for corn in EW rows. Reflectance and green NDVI were lower for corn in EW rows than corn in NS rows, but lack of replication makes it difficult to be certain that this was due to row direction. Green NDVI was less sensitive than reflectance to row direction and therefore may be more appropriate for use in a real-time variable-rate nitrogen application system.

Vegetation indices in the maize as a function of hour of the day and the applied rate of nitrogen

Metodos tem sido propostos visando a melhoraria da administracao de nitrogenio (N) e, simultaneamente, ao aumento de produtividade com a protecao do meio ambiente, diminuindo a concentracao de nitratos no solo e na agua, em que um deles, a agricultura de precisao, consiste na aplicacao localizada dos insumos agricolas em funcao da necessidade especifica local. Neste contexto, a medicao da reflectância espectral foliar da planta se apresenta como metodo promissor para o sensoriamento instantâneo da deficiencia de N em milho, atraves do calculo de indices de vegetacao; entretanto, nao sao bem conhecidas as caracteristicas da interacao das plantas com a radiacao solar. Avaliou-se, neste trabalho, o comportamento dos indices de vegetacao em relacao a hora do dia e da taxa de nitrogenio aplicada. Seis indices diferentes foram estudados: relacao infravermelho proximo/vermelho (IVP/V), relacao infravermelho proximo/verde (IVP/Verde), indice de vegetacao de diferenca normalizada (IVDN), indice verde de vegetacao da diferenca normalizada (IVVDN), indice de vegetacao ajustado ao solo (IVAS) e indice aperfeicoado de vegetacao ajustado ao solo (IAVAS). Quando analisados apenas os dados coletados em torno do meio dia solar, os indices que apresentaram a menor dispersao dos resultados foram o IVDN e o IAVAS, enquanto para dados tomados durante todo o dia os indices que indicaram melhor explicacao da variabilidade foram o IVAS e o IAVAS.