Resumo -O objetivo deste trabalho foi avaliar a eficiência de diferentes métodos de estratificação ambiental, a representatividade dos locais de avaliação, e a adaptabilidade e estabilidade de genótipos de soja, por meio de ensaios de produtividade de grãos, nos estados do Paraná e Santa Catarina, nos anos agrícolas de 2000 a 2003, em um total de 15 ambientes. Foram utilizados, para estratificação ambiental, o método tradicional de Lin e a análise de fatores aliada ao porcentual de parte simples (PS%) da interação genótipo vs. ambiente (GxA). Na determinação da adaptabilidade e estabilidade dos genótipos, foram utilizados modelos baseados em regressão linear única e bissegmentada. Foram testados 21 genótipos de soja em delineamento de blocos ao acaso com três repetições, na avaliação da produtividade de grãos. O genótipo RB 605 apresenta ampla faixa de adaptação com elevada produtividade média de grãos. De acordo com ambos os métodos, as localidades de Palotina e Brasilândia do Sul podem ser reduzidas a somente um local de ensaio.A análise de fatores associada ao PS% da interação GxA é mais seletiva para estratificação ambiental, em relação ao método tradicional de Lin.Termos para indexação: Glycine max, interação genótipo x ambiente, previsibilidade. Factor analysis and environmental stratification in the assessment of soybean adaptability and stabilityAbstract -The objective of this work was to assess the efficiency of different methods of environmental stratification, the representation level of the evaluation places, and the adaptability and stability of soybean genotypes, through yield trials in the Paraná and Santa Catarina States, Brazil, in the agricultural years of 2000 to 2003, totaling 15 environments. For environmental stratification, the Lin's traditional method and factor analysis, allied to percentage of the simple portion (SP%) of genotype vs. environment interaction (GxE), were utilized. Adaptability and stability of the genotypes were determined by linear and bisegmented regression models. Twenty one soybean genotypes were evaluated on randomized complete blocks design, comprising three replications, and the analyzed variable was grain yield. RB 605 genotype is highly adapted and presents high yield. According to both methods, Palotina and Brasilândia do Sul localities can be reduced to one trial location. The factor analysis allied to SP% of GxE interaction is more selective to environmental stratification in relation to the Lin's traditional method.

Since the US president decided to turn off the selective availability (SA) one of the biggest error in the GPS system has been the ionosphere refraction. The refraction effect on GPS signals are: delay for the code and an advance for the phase. In the equatorial region, where Brazil is, the refraction presents the biggest variations that are caused by the solar cycle, the time of the day, the season, the geomagnetic field and many others phenomena. In this case, the ionosphere refraction is a limitation because it increases the degradation of the position, specially if the user is using a single frequency receiver. To evaluate the ionospheric effects in Brazil, between January 1997 and December 2001, data from the Brazilian Continuous GPS Monitoring Network were used, provided by double frequency GPS receivers. All data were prepared and used by a scientific software to process the GPS observations. The volume of data was so big that it was necessary to write a software to manage the data integrity, to transform the precise ephemeris and the observations to scientific program format and to create batch files. Also, the program was used to process the data and to compute the total electron content automatically. At the end of the process, the software shows the TEC parameters. These parameters were used to create a historical series of the ionosphere refraction in Brazil. This series represents a period of minimal solar cycle, 1997, and a maximum period of the solar cycle, 2000 / 2001 in one of the most active regions of the planet. This series will improve the knowledge on the ionosphere and will allow to improve models or create new ones.

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