Efeitos diretos e indiretos de parâmetros dos semivariogramas referentes aos atributos químicos do solo sobre a produtividade de grãos de soja

In order to add value to soybens crops, and hence the marketing, medium and large producers have been using precision agriculture techniques (PA), as the Remote Sensing, Geographic Information Systems (GIS) and positioning satellite, to assist the management of crops. Thus, given the economic relevance of that culture to the southwest of Paraná State and Brazil, scientific studies to increase their productivity and profitability are of main importance. The objective of this study was to evaluate the correlation between the chemical soil properties and soybean yield for each estimated parameter of semivariogram (range, nugget and level effect), and the deployment of these correlations in direct and indirect effects, aiming to improve the mapping process of spatial variability of soil chemical properties for use in PA. The hypothesis is that not all attributes of soil used to estimate the semivariogram parameters has a direct effect on productivity, and that even in groups of plants within a larger area it is possible to estimate the parameters of the semivariograms. The experiment was conducted in a commercial area of 19.7 ha, located in the city of Pato Branco - PR, central geographic coordinates 26º 11 '35 "South, 52 43' 05" West longitude, and average altitude of 780 m. The area is planted with soybeans for over 30 years, currently being adopted to cultivate Brasmax Target RR - Don Mario 5.9i, with row spacing of 0.50 m and 13 plants m-1, totaling 260,000 plants ha-1. For georeferencing of the area of study and sampling points was used a couple of topographic ProMarkTM3 receptors, making a relative positioning to obtain the georeferenced coordinates. To collect data (chemical analyzes of soil and crop yield) were sampled 10 blocks in the experimental area, each with an area of 20 m2 (20 meters long x 1 meter wide) containing two spaced adjacent rows of 0.5 m. Each block was divided into 20 portions of 1 m2, and from each were collected four subsamples at a distance of 0.5 m in relation to the lines of blocks, making up a sample depth for 0-10 cm a sample to 10-20 cm for each plot, totaling 200 samples for each depth. The soybean crop was performed on the blocks depending on maturity, and in each block was considered a bundle at each meter. In the data analysis, it was performed a diagnosis of multicollinearity, and subsequently a path analysis of the main variables according to the explanatory variables (range of chemical attributes: pH, K, P, Ca, etc.). The results obtained by the path analysis of the parameters of the semivariogram of soil chemical properties, indicated that only the Fe, Mg, Mn, organic matter (OM), P and Saturation by bases (SB) exerted direct and indirect effects on soybean productivity, although they have not presented spatial variability, indicating that the distribution of blocks in the area was unable to identify the spatial dependence of these elements, making it impossible to draw up maps of the chemical attributes for use in PA.

Estudo empírico de antecedentes do sucesso de sistemas de informação: análise de um sistema de apoio à decisão em uma universidade pública

Universities are institutions that generate and manipulate large amounts of data as a result of the multiple functions they perform, of the amount of involved professionals and students they attend. Information gathered from these data is used, for example, for operational activities and to support decision-making by managers. To assist managers in accomplishing their tasks, the Information Systems (IS) are presented as tools that offer features aiming to improve the performance of its users, assist with routine tasks and provide support to decision-making. The purpose of this research is to evaluate the influence of the users features and of the task in the success of IS. The study is of a descriptive-exploratory nature, therefore, the constructs used to define the conceptual model of the research are known and previously validated. However, individual features of users and of the task are IS success antecedents. In order to test the influence of these antecedents, it was developed a decision support IS that uses the Multicriteria Decision Aid Constructivist (MCDA-C) methodology with the participation and involvement of users. The sample consisted of managers and former managers of UTFPR Campus Pato Branco who work or have worked in teaching activities, research, extension and management. For data collection an experiment was conducted in the computer lab of the Campus Pato Branco in order to verify the hypotheses of the research. The experiment consisted of performing a distribution task of teaching positions between the academic departments using the IS developed. The task involved decision-making related to management activities. The data that fed the system used were real, from the Campus itself. A questionnaire was answered by the participants of the experiment in order to obtain data to verify the research hypotheses. The results obtained from the data analysis partially confirmed the influence of the individual features in IS success and fully confirmed the influence of task features. The data collected failed to support significant ratio between the individual features and the individual impact. For many of the participants the first contact with the IS was during the experiment, which indicates the lack of experience with the system. Regarding the success of IS, the data revealed that there is no significance in the relationship between Information Quality (IQ) and Individual Impact (II). It is noteworthy that the IS used in the experiment is to support decision-making and the information provided by this system are strictly quantitative, which may have caused some conflict in the analysis of the criteria involved in the decision-making process. This is because the criteria of teaching, research, extension and management are interconnected such that one reflects on another. Thus, the opinion of the managers does not depend exclusively on quantitative data, but also of knowledge and value judgment that each manager has about the problem to be solved.