Jandricic OMAFRA Testing New Products How Do Y ou Know it REALLY worked Let you be SURE about new products techniques for YOUR farm Research Trials Require PLANNING and ID: 810827
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Slide1
Drs. Chevonne Carlow and Sarah Jandricic, OMAFRA
Testing New Products: How Do You Know it REALLY worked???
Slide2Let you be SURE about new products / techniques for YOUR farm
Research Trials…
Require
PLANNING
and
COMITTMENT to not waste your efforts Extra time, labour, money
Slide3Why Trial
Biostimulants
?
Biostimulants
/ Fertilizers
Biopesticides / Chemical pesticidesRegistered byCFIAHealth CanadaData neededCompositionProduct safetyQuality control proceduresCompositionProduct safety
Quality control procedures
Environmental
t
oxicity
Efficacy against specific pests
Data generated
In house
Often
independent
Time to market
Relatively quick
Very slow
Slide410 Basic Steps in a Research ProjectIdentify your research question and objective.Develop a research hypothesis.Decide what you will measure and what data you will collect
.Develop an experimental design.Choose the location and map out your field plots.
Implement
the project.
Make observations and keep records throughout the season.Collect research data.Analyze the data.Interpret the data and draw conclusions.
Outline
Source: SARE Grant Learning Centre
Slide510 Basic Steps in a Research ProjectIdentify your research question and objective.Develop a research hypothesis.Decide what you will measure and what data you will collect
.Develop an experimental design.Choose the location and map out
your field plots.
Implement
the project.Make observations and keep records throughout the season.Collect research data.Analyze the data.Interpret the data and draw conclusions.
Outline
Source: SARE Grant Learning Centre
Slide6Identifying your QuestionThe most important part of any experiment!Don’t expect one project to answer all of your questions
BUTDo expect one project to lead to many more questions!
Slide7Identifying your QuestionI would like to see if ________ will help to ________ in ________.
Slide8Identifying your QuestionI would like to see if ________ will help to ________ in ________.BioStimulants
Crop XVariety YField Z
Propagation
Improve profits
Slide9Identifying your GoalsExample Hypotheses:“Biostimulant X will increase yields by an average of at least 5% compared to my current production practices.“Biostimulant Y will
increase the percentage of fruit given top grade over my current methods”“Biostimulant Z will increase biomass of my cover crop and improve soil N levels, reducing the amount of fertilizer needed
.”
I would like to see if ________ will
help to ______ __ in ________.Improve ProfitsGeneral Question:Narrow Down SPECIFIC Hypothesis– more measurable
Biostimulants
Crop X
Slide1010 Basic Steps in a Research ProjectIdentify your research question and objective.Develop a research hypothesis.Decide what you will measure and what data you will collect
.Develop an experimental design.Choose the location and map out your field plots.
Implement
the project.
Make observations and keep records throughout the season.Collect research data.Analyze the data.Interpret the data and draw conclusions.
Outline
Source: SARE Grant Learning Centre
Slide11Getting Started: Data CollectionDecide what data to collect BEFORE you set up your experiment
Does it answer your QUESTION?How many samples will you need to collect to SEE A DIFFERENCE
Informs
layout, size of plots, labour, TIME
Slide12Getting Started: Data Collection
Research Question:Examples of Measurements:
Quantitative
Quantitative
Qualitative
QualitativeBiostimulant X improves crop YPlant biomassYieldRating ScalePhoto analysisDecide what data to collect BEFORE you set up your experimentDoes it answer your QUESTION?How many samples will you need to collect to SEE A DIFFERENCEInforms layout, size of plots, labour, TIMEMost InformativeMost time consuming
Least Informative
Least time consuming
Slide13Collecting Data: A Note on Bias Do you see what you expected? Does it influence how you take data? Or how you interpret the results?
Too much focus on what you expect to see,
can cause you to miss interesting results!
Slide14Identify your research question and objective.Develop a research hypothesis.Decide what you will measure and what data you will collect.Develop an experimental design
.Define treatmentsVariables
Replication
Blocking
RandomizationChoose the location and map out your field plots.Implement the project.Make observations and keep records throughout the season.Collect research data.
Analyze the data.Interpret the data and draw conclusions.Outline
Are your results
REAL
or just due to
CHANCE
???
Slide15Experimental Design –Treatments
Treatment
=
What you’re applying to the crop;
COMPARISONS
of interestDifferent Biostimulant productsDifferent rates of BiostimulantsDifferent Biostimulant regimes
Slide16Selecting Treatments: Keep the Trial ManageablePaired comparison (2 TREATMENTS only) E.g. Something NEW vs a CONTROL
Experimental Design -
Treatments
Paired comparison
Biostimulant
XControlPlots/Rows
Slide17Selecting Treatments: Keep the Trial ManageablePaired comparison (TWO TREATMENTS) E.g. Something NEW vs a CONTROL
Experimental Designs -
Treatments
Paired comparison
Biostimulant
XControlWhat you’re already doing!Keep ALL other management practices (VARIABLES) the same
:
- Tillage
Irrigation
Pesticide applications
Plots/Rows
Slide18Why re-invent the wheel?Use other sources to narrow it downData on a SIMILAR crop? Region?Independent studies?Neighbours?Talk to company reps – want to ensure your success!
Choosing a Product
Slide19Remember, these are LIVE organisms!Quality control is importantFRESH product (check expiry date!)Proper STORAGEProper APPLICATION
A BIG Variable –
Product Quality
Slide20Remember, these are LIVE organisms!Quality control is importantTesting?????
A BIG Variable –
Product Quality
Slide21Identify your research question and objective.Develop a research hypothesis.Decide what you will measure and what data you will collect.Develop an experimental design
.Define treatmentsVariables
Replication
Blocking
RandomizationChoose the location and map out your field plots.Implement the project.Make observations and keep records throughout the season.Collect research data.
Analyze the data.Interpret the data and draw conclusions.Outline
Are your results
REAL
or just due to
CHANCE
???
Slide22WHY Replicate?
lets you figure out if what you see is caused by:
NATURAL VARIATION
or your TREATMENT
= Number of times the treatment is in the fieldExperimental Design: Replication
Slide23HOW MANY TIMES SHOULD YOU REPLICATE?MORE IS BETTER IDEAL: 3-5 replicates per treatment
Experimental Design:
Replication
SIZE MATTERS
E.g. Corn:
Each plot needs to yield 1000 lbs of harvested material- Will depend on equipment sizeBLOCK 1BLOCK 2
BLOCK 3
Slide24Assigning treatments to plots WITHOUT BIAS- Also helps reduce variation (noise)
Experimental Design:
Randomization
BLOCK 1
BLOCK 2
BLOCK 3
Slide25BlockingIs your Field perfectly uniform? No? Then you need to blockHelps reduce “noise” (variability)Field conditions should be uniform WITHIN each block
Experimental Design:
Blocking
BLOCK 1
BLOCK 2
BLOCK 3
Wet part of field
All in shade
Slide26Experimental Design:
Blocking
BLOCK 1
BLOCK 2
BLOCK 3
Examples of variation to block against:
Shade
Slope
Soil texture
Wetness
Ajacent
crops/wildlands
Blocking
Is your Field perfectly uniform? No? Then you need to block
Helps reduce “noise” (variability)
Field conditions should
be uniform WITHIN each block
Slide27Helps Eliminate Sources of Variation:Requires pre-mapping of fieldTrick: lay out blocks 90 degrees to source of “noise”
Experimental Design:
Blocking
Slope = variation
Block position
Slide2810 Basic Steps in a Research ProjectIdentify your research question and objective.Develop a research hypothesis.Decide what you will measure and what data you will collect.
Develop an experimental design.Choose the location and map out your field plots.
Implement
the project.
Make observations and keep records throughout the season.Collect research data.Analyze the data.Interpret the data and draw conclusions.
Outline
Source: SARE Grant Learning Centre
Slide29Interpreting your Data
Data “analysis” does NOT have to be overly complicated
Slide30Interpreting your Data: GRAPH ITPhoto: U. FloridaSTEPS 1& 2
- Calculate AVERAGE within each treatment and STANDARD ERRORGRAPH (need to make a graph in Excel with separate SE bars for each treatment)
Slide31Photo: U. FloridaSTEPS 1& 2- Calculate AVERAGE within each treatment and STANDARD ERRORGRAPH (need to make a graph in Excel with separate SE bars for each treatment)
Standard Error
The bigger the standard error, the
more variation
(noise)
around your treatment mean
Interpreting your Data:
GRAPH IT
Slide32Photo: U. FloridaSTEPS 1& 2- Calculate AVERAGE within each treatment and STANDARD ERRORGRAPH (need to make a graph in Excel with separate SE bars for each treatment)
The bigger the standard error, the
more variation
(noise) in your treatment
Mean
is less representative of what’s likely to happen
Interpreting your Data:
GRAPH IT
Slide33Photo: U. Florida
Interpreting your Data:
GRAPH IT
Slide34Photo: U. FloridaResources:Ready-made spreadsheets for mean + SEswroc.cfans.umn.edu/farm-trials-worksheet YouTube tutorials for graph with separate standard error bars:Excel 2010:
youtube.com/watch?v=N1xwu8eSk7kExcel 2013+:
youtube.com/
watch?v
=AfAG61UWsWA
Interpreting your Data: GRAPH IT
Slide35Interpreting your Data: ComparePhoto: U. FloridaSTEP 3:
COMPARE your dataA) Simple methods
Likely NOT significantly different:
i.e. NO treatment differences
Likely significantly different:
i.e. one treatment was better“Significant Difference" = results seen are most likely NOT due to chance or natural variation
Slide36Photo: U. FloridaSTEP 3: COMPARE your data
A) Simple methods (but may conclude differences are there when they are notB) More Involved, i.e.
use
statistical tests
(can be more sure that results mean something)Time to run a t-test!
Takes into account means, degree of overlap Calculates how certain we can be that there is a significant difference
Interpreting your Data:
Compare
Slide37T-test: WHY WE HAVE GOOD BEER
Statistics: not just for dorks
William Sealy
Gosset
– inventor of the t-test and why Guinness is successful
Slide3810 Basic Steps in a Research ProjectIdentify your research question and objective.Develop a research hypothesis.Decide what you will measure and what data you will collect.
Develop an experimental design.Choose the location and map out your field plots.
Implement
the project.
Make observations and keep records throughout the season.Collect research data.Analyze the data.Interpret the data and draw conclusions.
Outline
Source: SARE Grant Learning Centre
Slide39Photo: U. FloridaSTEP 4: Do an ECONOMIC analysis
Interpreting your Data:
The Big Picture
Biostimulant
Trial
GoalEffectsBenefitsConsiderationsReduce crop susceptibility to stress
Quantifiable
Fewer losses
($)
Lower IPM costs
($)
Market expansion
($)
Cost
of Product
($)
Cost of Application
($)
Non- Quantifiable:
Greater piece
of mind
Sustainability
Cost
p
er
crop
? Per row?
P
er
b
ushel? Cost of being wrong???
Slide40Crop
Week
1
10 20 30 40 50
Crop 1
1,289,741 (
incl
, 2", 4" and 6" and 8")
Crop 2
58,104 (4” - 26,588) (6” – 31,516)
Crop 3
32,025
Crop 4
27,967 (
incl
4” and 6”)
Crop 5
15,329
Crop 6
7,757 (incl. 8” and 10”)
Crop 7
22,151
Crop 8
72,440 (incl. 4” and 6”)
Crop 9
29,782
Greenhouse Example
Slide41Biocontrol costs by crop
Slide42Crop 2
Slide43So you didn’t see much difference…..Effects of most Biostimulants are likely more subtle than things like changing pesticides or varying NPKLikely require MULTI-YEAR trials; pool data
Managing Expectations
Slide44When Good Research Goes BadWelcome to research!Can you still reach a conclusion? The take away:Did you try to do too much?Does it give you guidelines for what “not to do”?
Slide45YOUR OMAFRA crop specialistIan MacDonald, OMFRA Applied Research Coordinatorian.mcdonald@ontario.cahttps://www.sare.org/Learning-Center/Bulletins/How-to-Conduct-Research-on-Your-Farm-or-Ranch/Text-VersionVideo Series, Conducting on Farm Research, Univ. of Nebraska CropWatch:https://www.youtube.com/playlist?list=PLdssrgg38jJ2Qaf3heqE_ne6ecce-j7ud
Resources