Why conduct experiments?... To explore new technologies, new crops, and
new areas of production
To develop a basic understanding of the factors that control production
To develop new technologies that are superior to existing technologies
To study the effect of changes in the factors of production and to identify optimal levels
To demonstrate new knowledge to growers and get feedback from end-users about the acceptability of new technologies
What is a designed experiment? Treatments are imposed (manipulated) by
investigator using standard protocols
May infer that the response was due to the treatments
Potential pitfalls As we artificially manipulate nature, results may not
generalize to real life situations
As we increase the spatial and temporal scale of experiments (to make them more realistic), it becomes more difficult to adhere to principles of good experimental design
What is an observational study? Treatments are defined on the basis of existing
groups or circumstances Uses
– Early stages of study – developing hypotheses– Scale of study is too large to artificially apply treatments
(e.g. ecosystems)– Application of treatments of interest is not ethical
May determine associations between treatments and responses, but cannot assume that there is a cause and effect relationship between them
Testing predictions in new settings may further support our model, but inference will never be as strong as for a designed (manipulative) experiment
Some Types of Field Experiments(Oriented toward Applied Research)
Agronomy Trials– Fertilizer studies
– Time, rate and density of planting
– Tillage studies
– Factors are often interactive so it is good to include combinations of multiple levels of two or more factors
– Plot size is larger due to machinery and border effects
Integrated Pest Management– Weeds, diseases, insects, nematodes, slugs
– Complex interactions betweens pests and host plants
– Mobility and short generation time of pests often create challenges in measuring treatment response
Types of Field Experiments (Continued)
Plant Breeding Trials– Often include a large number of treatments (genotypes)
– Initial assessments may be subjective or qualitative using small plots
– Replicated yield trials with check varieties including a long term check to measure progress
Pasture Experiments– Initially you can use clipping to simulate grazing
– Ultimately, response measured by grazing animals so plots must be large
– The pasture, not the animal, is the experimental unit
Types of Field Experiments (Continued)
Experiments with Perennial Crops– Same crop on same plot for two or more years– Effects of treatments may accumulate– Treatments cannot be randomly assigned each year so it is not
possible to use years as a replication– Large plots will permit the introduction of new treatments
Intercropping Experiments– Two or more crops are grown together for a significant part of the
growing season to increase total yield and/or yield stability– Treatments must include crops by themselves as well as several
intercrop combinations– Several ratios and planting configurations are used so number of
treatments may be large– Must be conducted for several years to assess stability of system
Types of Field Experiments (Continued)
Rotation Experiments– Determine effects of cropping sequence on target crop, pest or
pathogen, or environmental quality– Treatments are applied over multiple cropping seasons or years,
but impact is determined in the final season
Farming Systems Research– To move new agricultural technologies to the farm– A number of farms in the target area are identified– Often two large plots are laid out - old versus new– Should be located close enough for side by side comparisons– May include “best bet” combinations of several new technologies– Recent emphasis on farmer participation in both development
and assessment of new technologies
Choice of Experimental Site Site should be representative
Grower fields may be better suited to applied research
Suit the experiment to the characteristics of the site– make a sketch map of the site including differences in
topography– minimize the effect of the site sources of variability– consider previous crop history– if the site will be used for several years and if resources
are available, a uniformity test may be useful
Greenhouse effects Greenhouse and growth chambers are highly
controlled, but in practice may be quite variable
Not representative of field conditions– light– growth media– unique insect pests and diseases
Experiments can be conducted in the off-season
Experimental Error
Variation between plots treated alike is always present
Modern experimental design should: provide a measure of experimental error variance reduce experimental error as much as possible
Natural sources of error in field experiments
Plant variability– type of plant, larger variation among larger plants– competition, variation among closely spaced plants is smaller– plot to plot variation because of plot location (border effects)
Seasonal variability– climatic differences from year to year– rodent, insect, and disease damage varies– conduct tests for several years before drawing firm conclusions
Soil variability– differences in texture, depth, moisture-holding capacity, drainage,
available nutrients– since these differences persist from year to year, the pattern of
variability can be mapped with a uniformity trial
Uniformity Trials
The area is planted uniformly to a single crop
The trial is partitioned into small units and harvested individually
Adjustments are made to distinguish patterns in the data from random noise
Areas of equal yield are delineated
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Interpretation
Determine suitability of the site for the experiment– uniformity critical for fertility trials
Make decisions concerning management of site over time– cover crops
Group plots into blocks to reduce error variance within blocks– blocks do not have to be
rectangular
Determine size, shape and orientation of the plots
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Uniformity trials? costs
time constraints
land limitations
pressure to publish or perish
may already have knowledge of field characteristics, previous cropping history
new technological tools may achieve the same or better result
Precision Agriculture
Techniques, technologies, and management strategies that address within-field variability of parameters that affect crop growth.
soil type
soil organic matter
plant nutrient levels
topography
water availability
weeds
insects
Tools of Precision Agriculture
GPS and GIS – constant reference to geographic coordinates
Remote Sensing – infrared maps
Equipment such as combines that can continuously monitor yield at harvest
Crop Modeling
Spatial analyses
Example: central Missouri farm
Aerial photograph, soil pH and 3-year average grain yields
Source: http://muextension.missouri.edu/explore/envqual/wq0450.htm
Spatial Analyses
Utilize patterns in the data to adjust for heterogeneity in an experiment
Example: ASReml
http://www.vsni.co.uk/software/asreml
Not a substitute for good experimental design and technique!
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