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problem is due to aluminum toxicity. Additional
laboratory and field studies are needed
to explain the effects and interactions among
phosphorus, lime, and silicate.
Results of the 1969 studies clearly indicated
that local varieties were poorly adapted to
high levels of productivity. This fact was reflected
in a significant increase in the stoner:
grain ratio of the harvest from plots receiving
chicken manure. A systematic collection of
varieties from ecologically similar areas was
made in cooperation with the Graduate School
at Chapingo in early 1970, and these varieties
are being tested at high levels of productivity.
As a part of the study of Andosols, arrangements
are being made for the publication
of a review of the Japanese experience
with this type of soil. Dr. Yoshiaki Ishizuka,
Hokkaido University, Sapporo, Japan,
has agreed to serve as coordinator-editor for
the monograph. Drs. Tomoharu Egawa, Hideo
Okajima and Akira Tanaka of Hokkaido University
and Dr. Shinobu Yamada of Obihiro
University have agreed to contribute chapters
on "Properties of Andosols", "Amelioration of
Andosols", "Maintenance of Fertility and Fertilizer
Use" and "Distribution and Morphology
of Andosols". It is expected that the manuscript
will be prepared and edited by the end
of 1970.
METHODOLOGICAL
RESEARCH
Research is being continued to determine
more efficient procedures for agronomic field
trials and for interpreting experimental results.
Dr. Foster B. Cady, University of Kentucky, is
participating in the methodological studies.
Visual symptoms of plant wilting as an index
of moisture stress
In rainfed agriculture, available soil moisture
is an uncontrolled production factor that
may vary significantly from plot to plot and
contribute to a greatly inflated experimental
error.
To adjust plot yields for random differenences
in the effect of moisture stress, this variable
must be characterized at the plot level
on many dates during the growing season.
Visual symptom of wilting in corn, have been
measured on individual plots and used as a
covariate to adjust for differences in moisture
stress within an experiment. These visual
symptoms of wilting provide a measure of
moisture stress that can be estimated rapidly
and economically where labor costs are low.
The degree of wilting in a plot of corn was
estimated by counting the numbers of slightly
and severely wilted plants. These numbers
were then expressed as fractions of the total,
with the fractions multiplied by empirical factors
and summed to give the drought coefficient.
These daily coefficients for each plot were
transformed to a single value (the drought
index) by multiplying by empirical factors and
summing the products over the entire growing
season. Empirical factors were estimated
from the experiences of many investigators
and reflect the relative importance of stress
on yield at different physiological stages of
growth.
Since several observers of the same plot
at the same time do not provide identical readings
on wilting, an independent estimate was
made of variance due to the observer. A
group of observers was selected and the same
group of observers took readings on the degree
of wilting within each experimental plot.
The daily drought coefficients were calculated
from these readings, and the variance of these
coefficients due to observers was calculated.
This variance was used to calculate the variance
due to observer, or measurement error,
for the drought index.
Before using drought indices as a covariate
in the analysis of yield data, a preliminary test
was made to determine whether the variation
in drought indexes among plots was significantly
greater than the measurement error.
The overall mean squared deviation of the
drought indices for the plots in an experiment
was calculated. As this variance is a measure
of the true variability among drought indices
for the different plots, plus the variance
due to observer, the F value (overall mean
squared deviation) -+- (variance due to measurement)
was calculated. A significant F value
was interpreted to mean that the true variability
in the drought indices among plots was
greater than measurement error, thus the
drought indices could be used as a covariate.
The next step in evaluating drought index
for use as a covariate was to measure the
degree of association between the drought
index and the experimental treatments and
blocks. This association was measured by
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