Sustainability: A Farm Manager’s Perspective

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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 - PowerPoint PPT Presentation

Transcript of Sustainability: A Farm Manager’s Perspective

AGRICULTURAL SUSTAINABILITY:A FARM MANAGER’S PERSPECTIVE

Paul D. MitchellAAE 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 outcomes2. Certification and Standards: let someone else

“define” sustainability, you just follow rules3. Self-Assessments, self-certification, self-

regulating 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 SustainabilityYou 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 Studieshttp://www.coolfarmtool.org/CaseStudies

Costco Organic Eggs: GHG Emissions

FieldPrint Calculator 2011 ExampleCorn: Summary of ResultsPer 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 Potatoeshttp://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• Science Based• Cost Effective• Clearly Focused• Educational• Harmonized• Whole-Farm Oriented

• Regionally Appropriate• Flexible• Anonymous• Enhances Communication

• Complementary with Other Programs

NISA Process1. Regional farmer association leads the sustainability self-

assessment program with key stakeholders 2. Regional/local experts develop a self-assessment

survey: set of “good farming practices” for a crop in a region

3. Farmer population completes the survey• < 1 hour to complete, paper or online• Soybean, sweet corn, green beans, cranberry, potato,…

4. Analyze data to create industry report for communications

5. Farmer score cards with specific recommendations to improve

Annual Adaptive Management Cycle

A process to operationalize continuous improvement

Time

Sust

aina

bilit

yMulti-Year Adaptive Management Cycle and

Agricultural Sustainability

Continuous Improvement

A Grand Ideal, but how do we make it Practical?

The Whole-Farm Modular ApproachCornSoybeanCereals

PotatoSweet Corn

Forages

Green BeanCranberry

StrawberryBeefPork

Whole Farm Base-Tier

Assessment

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 practices2. Practices highly correlated with each other3. How do we compare or rank growers over 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

Principal Components

Data Envelope Analysis

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

• 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

0.5 0.53

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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 PCA-DEA 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

• Final PCA Output: For each farmer k: PCik = 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

uvi% Ac

ScoutHiredScout

TimesScout

DistTravel

CultrlPract

SoilTest

TissueTest

WeathrStation

SoilMoistr

Irrg UnifmTest

Nut MgmtPlan

ConsrvPlan Recycle

EmplyInsrnc

EmplyRetrmt

SafetyTrng

PC1 1.014 0 0.001 0 0.025 0 0 0 0.008 0.003 0 0 0 0 0 0PC2 0 0.051 1.012 0 0 0 0.020 0 0 0.002 0 0 0.016 0 0.000 0PC3 0 0 0.009 0.034 0 0 0 0.958 0.339 0 0 0 0 0 0 0PC4 0.001 0 0 0.012 0.035 0 0 0 0.062 1.011 0.007 0.026 0 0 0 0PC5 0 0 0 0 0 0.080 0.605 0 0.091 0 0.822 0.023 0 0 0 0PC6 0 0.078 0 0.431 0 0 0.018 0 0 0 0 0 0.017 0.914 0 0PC7 0 0 0 0 0 0.029 0.003 0 0.069 0 0 0.728 0.708 0 0 0PC8 0 0.008 0 0 0 0 0.011 0.001 0 0 0 0 0.017 0.022 1.014 0.019PC9 0 0.353 0 0 0.496 0.417 0 0 0.050 0 0 0 0 0 0 0.707

X % AcScout

HiredScout

TimesScout

DistTravel

CultrlPract

SoilTest

TissueTest

WeathrStation

SoilMoistr

Irrg UnifmTest

Nut MgmtPlan

ConsrvPlan Recycle

EmplyInsrnc

EmplyRetrmt

SafetyTrng

Farm k=1 75 1 14 324.1 1 1 1 0 1 1 1 1 1 16.7 16.7 1

Cranberry Example: Non-negative PCA: PC4 (irrigation application uniformity testing) vs. PC3 (weather station, soil moisture monitoring) (Dong et al. 2015)

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PC4

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 data1. Many variables and correlations among them both

reduce discriminating power of DEA2. 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)

• 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

1

1

Maximize ( ) ,

subject to 1, 0

Iik ik ik ik

Iij ij iji

PC

PC

S

j

w w

w w

Cranberry Example: Basic DEA (Dong et al. 2015)

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PC3

PC4

Score = 0.90

Score = 0.70

Common-Weight DEA (Despotis 2002)

• Use same weight wi for each PC across all farms (not wik)

• 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

• Common-weight DEA score is

1

1

1Minimize ( , , ) (1 )

subject to , 0, 0 ,

0 , 0

Kk i kk

Ik i ik k k ki

i

h d z t d t zK

S PC d d z d k

i z

w

w

w

1

Ik i iki

S PCw

Recover the endogenous weights Wv for each practice xv

• Solve this program for t = 0 to 1 by 0.01

• Get 101 solutions indexed by t, so average over them

• Use the principal component weights on PCik

• Each practice now has a weight

1

1

1Minimize ( , , ) (1 )

subject to , 0, 0 ,

Kk i kk

Ibk i ik k k ki

h d z t d t zK

S y d d z d k

w

w

1 1 1 1

1 1T T I Ik kt it ik i ikt t i i

S S PC PCT T

w w

1 1 1

V I Vk i vi vk v vkv i v

Z u x W xw

1

1 1/I T

v it vi vTi tW uw

Cranberry Example: Basic DEA (Dong et al. 2015)

0 1 2 3 4 5 6 70

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PC3

PC4

Score = 0.85

Score = 0.50

Common-Weight DEA Frontier (t = t’)

Category 1 Category 2 Category 3 Category 10…

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)

Min0.55

Mean0.83

St. Dev.0.13

Scores for WI Cranberry Growers

Dong et al. (RAFS) Soybean Assessment

Soybean Specific70 practices, N = 410

Whole Farm145 practices, N = 80

Dong et al. (RAFS) Soybean Assessment

• 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

Laggards

Leaders• Leaders at the frontier pulling the group forward

• Laggards in the tail pulling group average down

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)

Category Midwest Sweet Corn

Midwest Green Bean

NY Green Bean

Community 0.930 0.733 0.611Disease Management 0.610 0.663 0.823Ecosystem Restoration 0.330 0.291 0.438Economics 0.870 0.869 0.887Farm Operations 0.761 0.731 0.782Insect Management 0.456 0.555 0.822Nutrient Management 0.840 0.836 -----Production Management 0.882 0.887 0.911Soil & Water Management 0.792 0.709 0.904Weed Management 0.753 0.828 0.725Whole Farm 0.905 0.887 0.945

Histograms of Midwest Green Bean Scores for Select Categories (Mitchell et al. NJAS)

0 0.07 0.14 0.21 0.28 0.35 0.42 0.49 0.56 0.63 0.7 0.77 0.84 0.91 0.980123456789

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0 0.060.120.180.24 0.3 0.360.420.480.54 0.6 0.660.720.780.84 0.9 0.960

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Ecosystem Restoration

0 0.07 0.14 0.21 0.28 0.35 0.42 0.49 0.56 0.63 0.7 0.77 0.84 0.91 0.980

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0 0.060.120.180.24 0.3 0.360.420.480.54 0.6 0.660.720.780.84 0.9 0.960

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Nutrient Management

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Whole Farm Sustainability Score

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Whole Farm Sustainability Score

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Whole Farm Sustainabilty Score

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Histogram of Whole Farm Scores

Midwestern Sweet Corn

Midwestern Green Beans

New York Green Beans

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 engagement2. Role of science3. Consumer access to sustainable food4. How sustainability is measured5. 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