03531nam a2200337 a 450000100080000000500110000800800410001910000200006024501240008026000160020430000100022050000650023052026450029565000210294065000130296165000110297465000150298565000190300065000160301965000170303565000160305265000160306865000150308465000120309965000090311165300150312065300150313565300150315065300190316565300090318415648982002-05-28       1977    bl uuuu  m   00u1 u    #d1 aTEIXEIRA, M. G.  aEffect of day length on associations between seed yield and developmental traits in soybeans (Glycine max (L.) Merril).  a1977.c1977  a63 f.  aThesis (Master of Science) - University of Florida, [S. l.].  aThe purpose of this study was to determine associations between various morphological and developmental characters and yield of 12 soybean genotypes when planted on june 1 and also to determine the extent to which these same charaters could be used to predict the yield of soybeans planted July 26. The July 26 planting date was chosen to simulate June 1 day lengths at about 200  N latitude. The same 12 genotypes, chosen to represent a wide renge in latitude adaptation, were replicated three in four-or six-row plots in three Planting Treatments (PT) designated A, B, and C. PT A was planted 1 in 90-cm rows; PTS B and C were planted July 26 in 90-and 60-cm rows, respectively. Characters on which data were collectyed were seven time sequence variables, eight stem development variables, and nine miscellaneous variables. Analyses of variance showed significant differences among cultivars for nearly all characters measured in each planting treatment. All time sequence variables were negatively correlated with yield in PT .This suggests that the growing season for many of the 12 genotypes was longer than was needed for maximum yield. In a stepwise regression model, days to beginning flower, days to beginning seed enlargement, days to maturity, and number of days flowering were assaciated wich 86 of the yield variability in PT ª However, data on these variables, measured in PT A were  associated with 34 of the yield varialility in PT B. Adding more variables did not significantly increase R2 values. In Pt C, planted in 60 cm rows on July 26, 64% of the yield variability was associated with the following PT A variables: days to first pods 4 cm long. In stewise regression models dealing wich stem variables measured in PT A, three variables were associated wich 87 % of the yield  variability of PT A, three were associated with 72% of the yield variability in PT C. Adding additional variables in PT B and incresed R2 values very little. Three miscellaneous variables measured in PT A were associated with 90% of the yield variability in PT  A, five were associated with 72% of the yield variability in PT B and three were associated with 65% of the yield variability in PT C. Some variables were negatively associated with yield PT A, but positively associated in PT B or C. The row with differences in PT B and C significantly influenced the extent to which some variables in PT A were associated with yield in B or C. The results indicate that measurements made on early planted soybeans may be used effectively in selecting for yield in later plantings or in selecting for a higher yield potential at lower latitudes.  aplant physiology  asoybeans  ayields  aFisiologia  aFotoperiodismo  aGlycine Max  aIluminação  aInsolação  aMaturação  aRendimento  aSemente  aSoja  aInsolation  aLightining  aMaturation  aPhotoperiocity  aSeed