Earning his Spurs - Pitchcare

No testing ground can
reproduce the levels and
intensity of wear, timing of
use, exact conditions and all
the other variable inputs that
you, as the turf manager, put
into your turf surfaces.
By Andrew Turnbull
BSc (Hons)
Testing Yourself ...
There is much talk about making sure
that products you use are
independently tested and the results
available for groundsmen/greenkeepers.
Whilst I fully endorse this view point,
there is no greater verification of
whether a product or treatment is
suitable for you than by testing them on
your own turf. No testing ground can
reproduce the levels and intensity of
wear, timing of use, exact conditions and
all the other variable inputs that you, as
the turf manager, put into your turf
surfaces.
This article is written to provide some
guidelines on how you can gain
meaningful results that are relevant to
your playing surfaces. In particular, I
want to show two methods that you can
use to compare treatments of different
products.
First, some guidelines:
1. Before the experiment starts:
Be clear in your mind on why the test is
being conducted in the first place. It is
very important that you start a trial with
clearly defined objectives and purposes.
Decide on how the trial will be run.
You may want to carry out plot trials that
measure many treatments and require
the use of statistics to produce accurate
data. Or, you may just need a simple
comparison between one treatment and
another.
Approach your trials with an open
Fig 1. Plywood test on a fairway
mind. Many experiments are made
invalid because of a bias towards a
certain result, which affects how the data
is collected and interpreted.
2. Materials and Methods
List the materials to be used (products,
sprayer, etc.) and the methods that will
be used to implement the test (sprayer
settings, product rates, evaluation
methods).
Decide what is actually to be measured,
e.g. colour, growth rates, density or
playing characteristics. Bear in mind that
measurements can be subjective, e.g. how
do you measure difference in green if
you are colour blind? Avoid too
ambitious measurements that require
expensive recording data, e.g. infra red
measuring of leaf chlorophyll content.
Keep it to practical levels.
Concentrate on the most important
reason for choosing a particular product
or treatment. The more variables you
introduce the less likely you will be able
to determine the response of your turf.
Keep everything consistent with your
normal turf management, and then
introduce the one change you would like
to make on test areas.
3. Once the experiment has started:
Begin recording observations for each
product or process being tested.
Observations can be descriptions of
visual characteristics (“excellent”, “good”,
“fair” are all visual descriptions),
numerical ratings (weights of clippings,
electrical conductivity readings, etc.) or
relative ratings (subjective performance
estimates of quality, such as a 1-9 turf
quality rating system).
Without good record keeping, the
effort put into a testing programme will
be wasted, because you will have no way
of remembering how and why your
results were obtained.
Use a notebook to record your
Objectives, Materials and Methods,
observations and Discussion, as well as
any other thoughts you have about
product performance, the reaction of
golfers to management practices, or any
difficulty you experience handling or
applying a material. Date each entry, and
take notes carefully and legibly!
Remember - excess information is always
better than insufficient information, so
don’t be stingy with your words. If you
are able to take photos, tape them inside
your experimental log; these can be
invaluable in summarising your results. If
you are a good record keeper, you’ll find
that your notebooks will hold their value
for years to come - in resolving disputes
about which practice or technique is best,
where or how a product was applied, or
the history of a problem area of turf.
4. At the end of the experiment:
Review your notes and write a discussion,
or summary of your findings, why you
Fig 2 - non-randomised plots Fig 3 - randomised plot design