AGRICULTURAL
SUSTAINABILITY:
A FARM MANAGER’S
PERSPECTIVE
Paul D. Mitchell
AAE 320: Farming Systems Management
Learning Goals
• To develop a basic understanding of company
efforts and consumer comprehension of ag and
food sustainability
• How sustainability is typically defined
• Terminology and concepts
• What farm mangers can expect
• Cool Farm Tool, Fieldprint Calculator
• Sustainability Assessments and Frontiers of
Sustainability
Corporate Agricultural Sustainability
• Agriculture and Food are part of the
corporate push for sustainability
• Most major food companies have announced
sustainability programs
• McDonald’s, Cargill, Unilever, WalMart,
FritoLay, Sysco, Del Monte, Kettle Chips, etc.
Corporate Agricultural Sustainability in WI
• Focus on energy and waste reduction
• FritoLay’s Beloit Plant
• 1st food manufacturing plant to achieve LEED gold
• Reduced natural gas 35%, electricity 20% and water
50% per pound of product since 2000
• Kettle Chips Beloit Plant (LEED gold plant)
• 100% waste oil for biodiesel: saves 8 tons CO2
emissions/year
• Reduces gas and electricity by 20%, uses wind power
• Reuses 3.4 million gallons of water per year
• Removing paper layer in bag reduced material use 20%
Commodity Groups
• Most major commodity groups have sustainability
programs
• Innovation Center for U.S. Dairy
• National Corn Growers Association
• United Soybean Board
• National Potato Council
• Wisconsin State Cranberry Growers Association
Sustainability and WI Farms
• Russet Potato Exchange/Wysocki Farms
• Responsible Farming: list of “Earth Actions”
• Windmill on logo to sell potatoes
• Crave Brothers Farmstead Cheese
• Sustainable Story: Anaerobic manure digester, text
story, news video, press release
• “From cow pies to clear skies”
Main Point
• Sustainability is a big deal & becoming more so!
• Ag Sustainability used to be “Alternative Ag”
• More mainstream now and becoming even more so
• It is now and will continue to impact farm operations
• Look at how sustainability is defined and its
drivers
• What can farm mangers can expect?
What is Sustainable Agriculture?
U.S. Code Title 7, Section 3103 defines sustainable agriculture:
• An integrated system of plant and animal production
practices having a site-specific application that will over
the long-term:
• Satisfy human food and fiber needs
• Enhance environmental quality and the natural resource
base upon which the agriculture economy depends
• Make the most efficient use of nonrenewable resources
and on-farm resources and integrate, where
appropriate, natural biological cycles and controls
• Sustain the economic viability of farm operations
• Enhance the quality of life for farmers and society as a
whole
Agricultural Sustainability
• Sustainable agriculture integrates three main
goals – environmental health, economic
profitability, and social equity – to meet the needs
of the present without compromising the ability of
future generations to meet their needs.
• Stewardship of both natural and human resources
• Systems-based, interdisciplinary research and
education
• Responsibility of all participants in the system
• Strategy for dealing with the future, not something
you accomplish
• Tied to personal values—which leads to conflicts
People, Profits
and Planet
Triple Bottom
Line
Practical Issues
• “People, Profits and Planet” is a grand ideal, but
issues remain to make it practical
• Have to measure to manage: What do you measure?
1. Life Cycle Analysis (LCA) and Models to
estimate environmental impacts or outcomes
2. Certification and Standards: let someone else
“define” sustainability, you just follow rules
3. Self-Assessments, self-certification, selfregulating organization (SRO)
Industrial Sustainability
• Industrial Sustainability: Changes are relatively
easy to measure in industrial production
processes
• Production concentrated in a highly controlled and
metered facilities, even for food processing
• Companies can make statements about gallons
of this or tons of that saved
• Frito-Lay: Saved 570 million gallons H2O by recycling
in plants, Eliminated 150 square miles of packaging by
reducing material use by 10%, Saved 5 million trees by
reusing 97% of delivery cartons,
• Kettle: Convert 100% waste oil to biodiesel, saving 8
tons CO2 emissions per year
Measuring Industrial Sustainability
You have to “Measure to Manage”
• Industrial sustainability focuses on outcomes
because they can be measured in these facilities
• Sustainability becomes efficiency oriented
• Companies already have economic incentives to
pursue efficiency as sustainability
• Collect data to measure input use and cost savings, in
pursuit of enhanced profitability
• Can also claim changes as sustainability improvements
• Measurements like these difficult in Ag: random,
expensive, distributed over landscape
• 1) Models to predict or 2) Practice-based approach
#1 Life Cycle Analysis/Assessment (LCA)
• Framework to estimate environmental effects of products
for sustainability assessment and measure progress—
Have you improved?
• Examine inputs and activities used to produce the
product, then quantify impacts
• Examine the outputs created by making, using and
disposing of the product, then quantify impacts
• Commonly focus on energy consumption, water use
waste generated, greenhouse gases/CO2, etc.
• Gallons of water or tons of CO2 per pound of cheese
• Data to measure or models estimate these values
• Never much on Economics/Profit and
Society/Community
General LCA Graphic
Source: http://www.ched-ccce.org/confchem/2010/Spring2010/P3-Haack_et_al.html
Agricultural LCAs
• Ag Production (http://pubs.acs.org/doi/abs/10.1021/es702969f)
• 83% of average U.S. household carbon footprint per year
for food consumption is ag production
• Food production & distribution = 17% of U.S. energy use
• Shifting less than one day per week’s worth of calories
from red meat and dairy products to chicken, fish, eggs,
or a vegetable-based diet achieves more GHG reduction
than buying all locally sourced food
• UW “Green Cheese” Project: Cheese LCA
http://fyi.uwex.edu/greencheese/
• Potato & vegetable LCAs for processed vegetables from WI
• Many more need to be completed
Green Cheese LCA Graphic
Source: http://fyi.uwex.edu/greencheese/files/2011/04/10_Passos-Fonseca_GreenCheeseLCA-EnergyGHGIntegratedDairyBiofuelsWisconsin_ASABE.pdf
Operationalizing Sustainability
• Companies push suppliers (farmers) for
sustainable products so company can make
claims to consumers to aid their marketing
• Companies using sustainability as a way to compete,
differentiate themselves, reputation, …
• Different companies have different methods and
ways to ensure sustainability
• Currently a “free for all” with little structure to
systems in place, but lots of demands
• Farmers at ground zero in the middle of debate
• To sell in certain markets, need to be “certified”
Ag Sustainability LCA Examples
• Cool Farm Tool
• Unilever, Pepsico/FritoLay, Sysco, McCain, etc.
• GHG (CO2, N20, CH3) emissions (Farm-Level
LCA)
• Field to Market/Keystone Alliance Fieldprint
Calculator for Soybeans/Corn/Wheat/Cotton
• Seven part radar plot: Land Use, Soil Loss,
Water Use, Energy Use, and GHG,
Conservation, Water Quality (Farm-Level LCA)
Cool Farm Tool: Case Studies
http://www.coolfarmtool.org/CaseStudies
Costco Organic
Eggs: GHG
Emissions
FieldPrint Calculator 2011 Example
Corn: Summary of Results
Per bushel findings:
• Productivity (yield per
acre) increased 41%
• Land use decreased 37%
• Soil loss decreased 69%
• Irrigation water use has
been variable, with an
average 27% decrease
• Energy use decreased
37%
• Greenhouse gas
emissions decreased 30%
http://fieldtomarket.org/files/Field_to_Market_Background_December_2011.pptx
Issues with LCA/Models
• Models predict outcomes, they do not measure them
• Prediction, not documentation: Many people forget this
• Lots of room to improve absolute prediction of outcomes,
models often make substantial prediction errors
• Modeling approach better for making relative comparisons
among policies or changes to estimate effectiveness
• Expensive to develop, calibrate, validate and implement:
long-term data collection & model calibration
• Work at large scales (watershed/region) and long-term
averages, not at farm level and for specific years
#2 Sustainability Certification (Eco-Labels)
• Create standards and certification system
• Someone else defines sustainability, you just have to
meet the standard
• Way to “prove” sustainability for marketing
• Fair Trade, Organic, Healthy Grown
• Sustainability standards: no consensus among companies
and consumers, multiple systems exist with lots of
overlap, too many labels for consumers to care
• Many companies currently have individual systems
• Comparable to GAP/GHP a few years ago
Wisconsin Healthy Grown Potatoes
http://www.healthygrown.com/
• Farmers and stakeholders defined a standard for
themselves in an attempt to capture a market
• 3rd party-verified practice-based standards, kind
of like Fair Trade, but an “Eco-Potato”
• Primarily Pest Management, plus some Soil & Water
Quality and Ecosystem Restoration
• Had hoped for a market price premiums, but so
far none has emerged
• Other Examples: Lodi Rules for Wine, Salmon
Safe
#3 National Initiative for Sustainable
Agriculture (NISA): Self Assessment
• Many sustainability initiatives seemed to exclude
conventional farmers from dialogue and program
development
• UW faculty and leaders from several farmer
organizations started meeting and planning
• Farmer response to ag sustainability programs
• Create consortium of ag/farmer groups
• http://wisa.cals.wisc.edu/nisa
NISA Key: Producer Engagement
• Farmers bear most of the economic, social &
environmental consequences of their practices
• Why don’t they help define sustainability?
• Work with grower associations & regional experts
• How do you want to assess yourselves?
• Focus on adoption of science-based practices
with proven positive outcomes in their region
Desirable Qualities for a Practical
Agricultural Sustainability Program
• Engages Farmers
• Regionally Appropriate
• Science Based
• Flexible
• Cost Effective
• Anonymous
• Clearly Focused
• Enhances
• Educational
Communication
• Complementary with
Other Programs
• Harmonized
• Whole-Farm Oriented
NISA Process
1. Regional farmer association leads the sustainability
2.
3.
•
•
4.
5.
self-assessment program with key stakeholders
Regional/local experts develop a self-assessment
survey: set of “good farming practices” for a crop in a
region
Farmer population completes the survey
< 1 hour to complete, paper or online
Soybean, sweet corn, green beans, cranberry, potato,…
Analyze data to create industry report for
communications
Farmer score cards with specific recommendations to
improve
Annual Adaptive Management Cycle
A process to operationalize
continuous improvement
Sustainability
Multi-Year Adaptive Management Cycle and
Agricultural Sustainability
Continuous Improvement
A Grand Ideal, but how do
we make it Practical?
Time
The Whole-Farm Modular Approach
Corn
Whole Farm
Base-Tier
Assessment
Soybean
Cereals
Forages
Potato
Sweet Corn
Green Bean
Cranberry
Strawberry
Beef
Pork
Making it Practical: The Sustainability
Data Analysis Problem
• Farmers willing to do an anonymous, short,
practice-based survey for their farm that they help
to develop and about practices they believe in
• Many variables for practice adoption: Green Bean
& Sweet Corn with Whole Farm has about 170
• Many questions are yes/no answers or
categorical variables (discrete variables)
• Many practices closely related: pest, disease and
weed scouting or soil tests and tissue tests for
nutrient management (correlated variables)
Example Practices from a Soybean
Sustainability Assessment
Resistance management, Pesticide & fertilizer handling & worker
safety, Ecosystem restoration, Production & management,
Community, Crop scouting, Learning and research, …
http://www.aae.wisc.edu/pdmitchell/RAFS/SoybeanAssessment.pdf
Sustainability Measurement Problem:
Data Envelope Analysis with Principal Components
• First Principal Component Analysis (PCA) to reduce the
number of variables, to remove correlation among
variables, and to convert discrete variables to continuous
• Next Data Envelope Analysis (DEA) to calculate a
composite index to measure how intensely each farmer
adopts sustainable practices relative to his/her peer group
• Final Output:
• Score between 0 and 1 for each farmer measuring
intensity of sustainable practice adoption relative to peers
with endogenous weights for each practice
• Document adoption intensity of farmer population and
identify practices to most improve each farmer’s score
Frontiers of Sustainability
• Key problems analyzing and summarizing results of
sustainability assessments
1. Too many questions and practices
Principal
2. Practices highly correlated with each other Components
3. How do we compare or rank growers over Data Envelope
Analysis
the wide range of possible practices?
• Principal Components (PC): Reduces number of
variables, makes them continuous and removes
correlation
• Data Envelope Analysis (DEA): Gives single number
measuring intensity of grower practice adoption
Measuring Sustainability
• Lots of math to analyze the practice adoption data from
the self assessment to score each farmer: 0 to 1
• Score measures intensity of best management practice
adoption compared to peers
The Power of Frontiers of Sustainability
25
Number of Farms
20
15
10
5
0
0.50
0.55
0.60
0.65
0.70
0.75
Score
0.80
0.85
0.90
0.95
• Show growers how they compare to each other
• Prioritize practices that would provide the greatest
advancement toward the frontier
• Identify research & outreach priorities at industry level
1.00
Individual
Grower
Scorecard:
Sustainability
“Dashboard”
Midwestern
Green Beans
Individual
Grower
Scorecard:
Recommended
Practices
Midwestern
Green Beans
Papers by Dong, Mitchell, et al.
• Measuring Farm Sustainability using Data Envelope
•
•
•
•
Analysis with Principal Components: The Case of
Wisconsin Cranberry (JEM 2015)
Assessing Sustainability and Improvements in U.S.
Midwestern Soybean Production Systems Using a PCADEA Approach (RAFS 2015)
Quantifying Adoption Intensity for Weed Resistance
Management Practices and Its Determinants among U.S.
Soybean, Corn, and Cotton Farmers (JARE 2016)
Conceptual Framework & Empirical Results for a Practical
Agricultural Sustainability Program in the United States
(NJAS 1st review)
Endogenizing Sustainability in U.S. Corn Production: A
Cost Function Analysis (AAEA poster)
Non-negative, Polychoric PCA
• Use polychoric correlation for PCA because many
of the variables are discrete
• Use non-negative (sparse) PCA
• a controls coordinate overlap
• b controls sparseness (non-zero PCA weights)
• We used b = 0, as not an issue for our data
• Frobenius norm of A = sqrt of trace of A*A
Cranberry Non-Negative Sparse PCA Weights
uvi
PC1
PC2
PC3
PC4
PC5
PC6
PC7
PC8
PC9
% Ac
Scout
1.014
0
0
0.001
0
0
0
0
0
Hired
Scout
0
0.051
0
0
0
0.078
0
0.008
0.353
Times
Scout
0.001
1.012
0.009
0
0
0
0
0
0
Dist
Travel
0
0
0.034
0.012
0
0.431
0
0
0
Cultrl Soil Tissue Weathr
Pract Test
Test Station
0.025
0
0
0
0
0 0.020
0
0
0
0 0.958
0.035
0
0
0
0 0.080 0.605
0
0
0 0.018
0
0 0.029 0.003
0
0
0 0.011 0.001
0.496 0.417
0
0
% Ac Hired Times Dist Cultrl
Scout Scout Scout Travel Pract
X
Farm k=1
75
1
14 324.1
1
Soil Irrg Unifm Nut Mgmt Consrv
Emply Emply Safety
Moistr
Test
Plan Plan Recycle Insrnc Retrmt Trng
0.008
0.003
0
0
0
0
0
0
0
0.002
0
0 0.016
0 0.000
0
0.339
0
0
0
0
0
0
0
0.062
1.011
0.007 0.026
0
0
0
0
0.091
0
0.822 0.023
0
0
0
0
0
0
0
0 0.017 0.914
0
0
0.069
0
0 0.728 0.708
0
0
0
0
0
0
0 0.017 0.022 1.014 0.019
0.050
0
0
0
0
0
0 0.707
Soil Tissue Weathr
Soil Irrg Unifm Nut Mgmt Consrv
Emply Emply Safety
Test
Test Station Moistr
Test
Plan Plan Recycle Insrnc Retrmt Trng
1
1
0
1
1
• Final PCA Output: For each farmer k: PCik =
1
1
1
16.7
16.7
SvuviXvk
• PC1k = 1.014*0.75 + 0*1 + 0.001*14 + 0*324.1 …
• Each PCik is a weighted average of the Xvk for each farmer
• Converts V variables into I PCs that are continuous, non-
negative and have no correlation between them
1
Cranberry Example: Non-negative PCA: PC4 (irrigation
application uniformity testing) vs. PC3 (weather station,
soil moisture monitoring) (Dong et al. 2015)
7
6
PC4
5
4
3
2
1
0
0
1
2
3
4
PC3
5
6
7
Data Envelope Analysis (DEA)
• Widely used to benchmark performance of individual
decision making units (DMUs) against a “best practices”
frontier and to create composite indices
• Two problems emerge when applying traditional DEA to
BMP adoption data
1. Many variables and correlations among them both
reduce discriminating power of DEA
2. Uninterpretable convex combinations of
categorical/discrete practices
• That’s why we used PCA: reduce variables, remove
correlation, convert discrete to continuous variables
• Needed non-negativity to make sense
Basic DEA
• Find finds DMU-specific weights
wik for the ith principal
component (PC) for the kth farmer to maximize each
farmer’s adoption intensity score (efficiency)
I
Maximize Sk (wik )  i1wik PCik ,
I
subject to i1wij PCij 1, wij  0 j
• Mathematically equivalent to an input-oriented constant
returns to scale DEA model with I inputs and a single
dummy output of 1 for all farms k
Cranberry Example: Basic DEA (Dong et al. 2015)
7
6
Score = 0.90
PC4
5
4
3
2
Score = 0.70
1
0
0
1
2
3
4
PC3
5
6
7
Common-Weight DEA (Despotis 2002)
wi for each PC across all farms (not wik)
• Use same weight
1
Minimize h(d k , wi , z )  t
K

K
k 1
d k  (1  t ) z
subject to S k   i 1 wi PCik  d k , d k  0, z  d k  0 k ,
I
wi  0 i, z  0
• Sk is conventional DEA score, dk is deviation of the
common-weight DEA score from conventional DEA score,
and z is the maximum deviation over all farms
• Math program finds common weights wi and deviations dk
to minimize weighted sum of average DEA score and
maximum deviation, parametrically varying weight 0≤ t ≤1
I
• Common-weight DEA score is S k   i 1 wi PCik
Recover the endogenous weights Wv for
each practice xv
• Solve this program for t = 0 to 1 by 0.01
1
Minimize h(d k , wi , z )  t
K

K
k 1
d k  (1  t ) z
subject to S   i 1 wi yik  d k , d k  0, z  d k  0 k ,
I
b
k
• Get 101 solutions indexed by t, so average over them
1 T
1 T
I
I
Sk   t 1 S kt   t 1  i 1 wit PCik   i 1 wi PCik
T
T
• Use the principal component weights on PCik
Z k   v 1  i 1 wi uvi xvk   v 1Wv xvk
V
I
V
• Each practice now has a weight
Wv  
I
1
i 1 T

T
t 1
wit uvi /  v
Cranberry Example: Basic DEA (Dong et al. 2015)
7
6
Score = 0.85
5
PC4
Common-Weight DEA
Frontier (t = t’)
4
3
2
Score = 0.50
1
0
0
1
2
3
4
PC3
5
6
7
Category 3 … Category 10
Category 1
Category 2
PCA
PCA
PCA
…
PCA
Category
DEA
Category
DEA
Category
DEA
…
Category
DEA
Whole Farm
DEA
• To deal with PCA computational intensity: group practices
into categories (nutrient, pest, labor, energy, etc.)
• Calculate category DEA score, then do DEA on these
scores to get the grand DEA score
Dong, Mitchell, and Colquhoun (2015) JEM
• Final practice weights
were highest for
1. Basing fertilizer
applications on soil
tests
2. Using cultural controls
for pest management
3. Providing safety
training for employes
Dong, Mitchell, and Colquhoun (2015) (JEM)
Scores for WI Cranberry Growers
Min Mean St. Dev.
0.55
0.83
0.13
Dong et al. (RAFS) Soybean Assessment
Soybean Specific
70 practices, N = 410
Dong et al. (RAFS) Soybean Assessment
Whole Farm
145 practices, N = 80
• Leaders at
the frontier
pulling the
group forward
• Laggards in
the tail pulling
group average
down
Leaders
Laggards
• How do we help the Leaders to keep getting better?
• How do we help the Laggards to improve?
• Identify practices that would most improve farmer scores for
the group as a whole or at individual farmer level
• Help set Research and Outreach priorities for group
Impact of the lowest 10% adopting the 10
highest weighted practices
Weed Resistance Management (JARE)
Weed Resistance Management (JARE)
Increase
weed BMP
adoption
• Educated
• Smaller
• Above avg
yields
• RR user
• Cotton, not
corn or soy
• Concern for
safety and
efficacy
Average Category Scores by Crop and
Region (Mitchell et al. NJAS)
Midwest
Midwest NY Green
Category
Sweet Corn Green Bean Bean
Community
0.930
0.733
0.611
Disease Management
0.610
0.663
0.823
Ecosystem Restoration
0.330
0.291
0.438
Economics
0.870
0.869
0.887
Farm Operations
0.761
0.731
0.782
Insect Management
0.456
0.555
0.822
Nutrient Management
0.840
0.836
----Production Management
0.882
0.887
0.911
Soil & Water Management
0.792
0.709
0.904
Weed Management
0.753
0.828
0.725
Whole Farm
0.905
0.887
0.945
10
9
8
7
6
5
4
3
2
1
0
5
4
1
0
0
0.04
0.08
0.12
0.16
0.2
0.24
0.28
0.32
0.36
0.4
0.44
0.48
0.52
0.56
0.6
0.64
0.68
0.72
0.76
0.8
0.84
0.88
0.92
0.96
1
0
0.04
0.08
0.12
0.16
0.2
0.24
0.28
0.32
0.36
0.4
0.44
0.48
0.52
0.56
0.6
0.64
0.68
0.72
0.76
0.8
0.84
0.88
0.92
0.96
1
Disease Management
Insect Management
3
20
2
15
0
0.04
0.08
0.12
0.16
0.2
0.24
0.28
0.32
0.36
0.4
0.44
0.48
0.52
0.56
0.6
0.64
0.68
0.72
0.76
0.8
0.84
0.88
0.92
0.96
1
0
0.04
0.08
0.12
0.16
0.2
0.24
0.28
0.32
0.36
0.4
0.44
0.48
0.52
0.56
0.6
0.64
0.68
0.72
0.76
0.8
0.84
0.88
0.92
0.96
1
Histograms of Midwest Green Bean Scores for
Select Categories (Mitchell et al. NJAS)
Ecosystem Restoration
12
10
8
6
4
2
0
Nutrient Management
35
30
25
10
5
0
Number of Farmers
Number of Farmers
8
Midwestern Sweet Corn
7
6
5
4
3
2
1
0
0.70
0.75
0.80
0.85
0.90
0.95
Whole Farm Sustainability Score
6
5
Number of Farmers
5
1.00
Midwestern Green Beans
4
3
2
1
0
0.70
6
Histogram of Whole
Farm Scores
0.75
New York Green Beans
4
3
2
1
0
0.70
0.75
0.80
0.85
0.90
0.95
Whole Farm Sustainabilty Score
1.00
0.80
0.85
0.90
0.95
Whole Farm Sustainability Score
1.00
Individual
Grower
Scorecard:
Sustainability
“Dashboard”
Midwestern
Green Beans
Individual
Grower
Scorecard:
Recommended
Practices
Midwestern
Green Beans
NISA  FieldRise
• NISA a great concept, lots of traction among
farmers
• Grant funded
• Hard to get traction among companies
• Spinoff in a Research Park approach with help
from UW’s Law and Entrepreneurship Clinic
• FOIA protection for data
• Credibility among businesses
• Research on campus, business off campus
FieldRise.com
FieldRise.com
What can farmers expect?
• To complete paperwork and maintain records for
sustainability certification
• Focus on practice adoption: environment, economics
and social aspects
• Data to support metrics (LCAs), on-farm audits
• Find a way to make money while doing so
• Agriculture has been through this before
• Dairy Sanitation
• Pesticides
• Food Safety
Consumer Survey: Preliminary Results
• Dr. Chengyan Yue, U of MN, Applied Econ & Hort
• Online survey of 10,000 people
• Wiliness to buy a can of “Sustainable” Sweet Corn
• Varied Sustainability Program along 5 qualities
(Conjoint Analysis)
1. Farmer engagement
2. Role of science
3. Consumer access to sustainable food
4. How sustainability is measured
5. How program communicates along supply chain
What do consumers care about?
• Price: dominates willingness to pay
• Measurement of Sustainability
• Farmers in program must demonstrate use of sustainable practices
• Measures of on-farm practices and consumer buying decisions are
used to measure sustainability
• Role of Science
• Program communicates scientific information to farmers
• Program funds science that will increase the sustainability of
farmer practices
• Farmers’ active participation
• Farmers advise program managers on program requirements and
activities
• Farmers participate to learn what is required to meet consumer
demands
Sustainability and Farmers
• How can farmers take advantage of these
trends/demands for sustainability?
• Consider it an Opportunity, not a Threat
• Innovation to develop new strategies, new alliances,
new practices and technologies
• Find a way to use sustainably to make money
• How do farmers participate in the creation and
implementation of sustainability standards?
• Get involved with grower organizations at local, state
and national level and with ag universities
• NISA: Grower Led, Science Based