Effects of Photoperiod and Temperature on Rate of Node Development in Indeterminate Bean

Abstract

<jats:p>The plastochron index was used to compare the effects by daylength, mean temperature, and diurnal temperature fluctuation, on the rate of node development of five indeterminate common bean <jats:italic>(Phaseolas vulgaris</jats:italic> L.) genotypes grown in eight growth chamber environments. Regression analysis described temporal trends in the plastochron index. Regression curves for the various genotype—environment combinations were compared using canonical variates analysis. At a constant 17C, extending daylength from 12 to 14 or 16 hr had no effect on rate of node development. The rate of node development increased at a constant 23C when daylength was lengthened from 12 to 14 or 16 hr. The increase in rate of node development was more pronounced in genotypes with higher photoperiod sensitivity, as measured by delay of flowering. Temperature rise from 17 to 23 to 29C also increased the rate of node development, with genotypes again exhibiting differential response. Diurnal fluctuation of 6C about a mean of 23C had the same node development rate as a constant 23C.</jats:p>

Surface Color Changes of Tomato and Other Solanaceous Fruit during Chilling

“…In addition, distinct groupings of the time subplots do not exist because, for some experiments, not all treatments could be measured on the same day. To circumvent these limitations, curvilinear regressions can be fitted followed by MANOVA of the regression coefficients (Eskridge and Stevens, 1987;Yourstone and Wallace, 1990). Treatments included various cultivars/lines, varietal characteristics, or different physical manipulations (temperature, RH).…”

“…Further-1 and 3), specific significant differences between treatments more, CV analysis gives a graphic representation of the signif- icant differences between specific treatment means by a plot of the first and sometimes second CV. Data were tested for dimensionality (Tables 1 and 3) (Chatfield and Collins, 1980;Yourstone and Wallace, 1990), and honestly significant intervals (HSI) (Andrews et al, 1980) were calculated for each CV, whose experimental error standard deviation was normalized to 1. HSI = CV ± q× l 2 × (n) l/2 where: q = studentized range statistic (Duncan, 1955) based on the degrees of freedom of the data, selected level of significance ( α = 0.05), and number of treatments being compared and n = number of replicates in the treatment for which the mean is calculated.…”

Effects of Watertable and Fertilizer Management on Susceptibility of Tomato Fruit to Chilling Injury

“…Multiple analysis of variance (MANOVA) of the resulting regression coefficients was followed by canonical variates (CV) analysis as described in detail in Yourstone and Wallace (1990) and Dodds et al (1991). Honestly significant intervals (α = 0.05) were calculated for each CV (Andrews et al, 1980), whose experimental error standard deviation was normalized to 1, according to the equation HSI = CV ± q•1/2√n where q = studentized range statistic (Duncan, 1955) based on the degrees of freedom of the data, selected level of significance,and number of treatments being compared, and n= number of replicates in the treatment for which the mean is calculated.…”

Applications of Canonical Discriminant Analysis in Horticultural Research

“…While the original derivations of most of these techniques occurred about 50 years ago, the comparatively recent advances in computer power and capacity have revolutionized multivariate statistical analysis and it is now applied in many disciplines. In the early 1980s, there was little enthusiasm for using these techniques to analyze horticultural experiments (Swallow, 1981), but recently they have been used to interpret responses to treatments (Lawes et al, 1990;Perez-Gonzales, 1992;Yourstone and Wallace, 1990).…”