180 likes | 294 Views
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
E N D
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 • Modern experimental design should: • provide a measure of experimental error variance • reduce experimental error as much as possible Variation between plots treated alike is always present
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
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
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!