Bortolotto O.C.,State University Londrina |
De Oliveira Menezes Junior A.,UEL CCA |
Sousa-Silva C.R.,Federal University of São Carlos
Semina:Ciencias Agrarias | Year: 2013
This study aimed to record new observations of Sanbornia juniperi Pergarde ex. Barker, 1920 (Hemiptera: Aphididae) in the Neotropical region associated with Juniperus chinensis L. (Cupressaceae). The aphids were found in September 2010 in Londrina city (23 ° 20 -23 "S, 51 ° 12- 32" W, 532m), Parana state (PR), Brazil. This represents only the second report of S.juniperi in the Neotropical region, and the first report was associated with J. chinensis, thereby indicating that in addition to dispersion, the aphid is colonizing new hosts.
Pagliosa E.S.,State University Londrina |
Carpentieri-Pipolo V.,UEL CCA |
Zucareli C.,UEL CCA |
Zago V.S.,State University Londrina
Semina:Ciencias Agrarias | Year: 2015
Genotype x environment interaction greatly influences the selection of genotypes and the crop system should take into account the response of genotype to the employee management. The aim of this experiment was to evaluate the genotype x environment interaction by GGE biplot analysis of four maize varieties (landrace, improved variety and commercial hybrid) in response to fertilization treatments (organic and chemical) under different environments. The experimental was in a 5x4x3 factorial randomized block design with four replications, with the combination of factors: five environments (Imbaú in 2006/2007; Alvorada do Sul in 2008/2009, and Londrina in 2007/2008, 2008/2009 and 2009/2010), four maize genotypes (Caiano, Azteca, DKB 390 and IPR 114) and three types of fertilization (without fertilizer, organic and chemical fertilizer). Considering the yield to Alvorada do Sul hybrid DKB 390 in cultivation with poultry litter is an alternative for small farmers. To Londrina using IPR 114 provides greater productivity for smallholders, however growers should use Azteca for Imbaú. The evaluation of the effects of genotype x environment interaction based on GGE Biplot analysis enabled us to identify behavior through promising and stable genotypic varieties as well as environments that optimize the performance of varieties, being a recommended method to improve the efficiency of the identification of genotypes for specific environments.