Growth: Growth Medium for Plant Tissue

Description Usage Format Source References See Also Examples

Description

This research concerned growth medium for cloning plants (Stieve, Stimart and Yandell 1992). Plant tissue (a small part of a leaf) was placed in a Petri dish which had a ‘food preparation’ on it. The dish was sealed and placed in a controlled chamber with adequate light and proper temperature. The ‘food preparation’, or medium, was designed to encourage growth of new plant shoots from the tissue. The response of interest here was the number of ‘adventitious shoots’ (advplt), or new plants growing out of the tissue. Basically, the more adventitious shoots produced, the better the growing media. The adventitious plants can be separated and grown into numerous individuals for greenhouse cultivation, saving tremendous space and cost for nurseries and florists. The key question is: what is the best growing condition for the shoots?

There were 12 factor combinations (trt) of interest, coming from a two-factor layout with added control (BHTA, trt = 20). One factor combination was missing; the plant material seemed to be burned by high levels of both chemicals together.

Usage

1

Format

Growth data frame with 183 observations on 5 variables.

[,1] trt factor treatment identifier
[,2] BA factor BA level
[,3] TDZ factor TDZ level
[,4] code factor plot code
[,5] advplt numeric number of adventitious plants

Source

Sue Stieve \& Dennis Stimart

References

Stieve SM, Stimart DP and Yandell BS (1992) 'Heritable tissue culture induced variation in Zinnia Marylandica', Euphytica 64, 81-89.

See Also

GrowthCount.

Examples

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data( Growth )

#Growth <- Growth[,c("trt","advplt")]
# drop the added BHTA control ( trt = 20 )
Growth <- Growth[ Growth$trt != 20, ]
Growth$logadvplt <- log10(1+Growth$advplt)
 
Growth$trt <- factor(Growth$trt)
Growth$BA <- ordered(Growth$BA)
Growth$TDZ <- ordered(Growth$TDZ)
Growth <- Growth[!is.na(Growth$advplt),]

sample.size( Growth$BA, Growth$TDZ )

Growth.zero <- Growth[Growth$advplt>0,]

Growth.fit <- lm(logadvplt~trt,Growth)
Growth.zero.fit <- lm(logadvplt~trt,Growth.zero)

Growth.full <- aov( logadvplt ~ BA * TDZ, Growth )
Growth.add <- aov( logadvplt ~ BA + TDZ, Growth )

# D:11.1 Growth interaction plots with a missing cell

int.plot( Growth.full, xpos = 2.5, ypos = .425,
  xaxt = "n", xlab = "(a) BA by TDZ", ylab = "",
  main = "Figure D:11.1",
  more = TRUE, split = c(1,1,2,1) )
int.plot( Growth.full, fac = c("TDZ","BA"),
  xpos = 3.25, ypos = .425, xaxt = "n",
  xlab = "log(1 + advplt)", ylab = "(b) TDZ by BA",
  main = "Growth Interaction",
  split = c(2,1,2,1) )

# E:13.2 Growth residual plots with zeros
tmpdata = data.frame( x = jitter( predict( Growth.fit )),
  y = jitter( resid( Growth.fit )), group = Growth$code )
print( xyplot( y ~ x, tmpdata, groups = group,
  panel = function(...) {
    panel.superpose(...)
    panel.abline( h = 0, lty = 2 )
    panel.abline( h = c(-1,1) * std.dev( Growth.fit ), lty = 3 )
    panel.abline( 0, -1 )
  },
  xlab = "(a) mean with zeroes", ylab = "residuals",
  main = "Figure E:13.2" ),
  more = TRUE, split = c(1,1,2,1) )

tmpdata = data.frame( x = jitter( predict( Growth.zero.fit )),
  y = jitter( resid( Growth.zero.fit )), group = Growth.zero$code )
print( xyplot( y ~ x, tmpdata, groups = group,
  panel = function(...) {
    panel.superpose(...)
    panel.abline( h = 0, lty = 2 )
    panel.abline( h = c(-1,1) * std.dev( Growth.zero.fit ), lty = 3 )
    panel.abline( 0, -1 )
  },
  xlab = "(b) mean without zeroes", ylab = "",
  main = "Growth Residuals" ), 
  split = c(2,1,2,1) )

byandell/pda documentation built on May 13, 2019, 9:27 a.m.