Managing Crop Risk Survey Raw Data — Social Science Studies

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Raw data from the Managing Crop Risk survey. This is the data that is transformed into the "formatted" data for analysis.

This datatable is part of the Managing Crop Yield Risk dataset. As farmers adapt to changing climate, they modify practices and technologies to manage evolving risk. Adaptive changes may be as small as adjusting a crop insurance coverage level or as large as investing in an irrigation system. Farmer attitudes toward risk and their subjective perceptions of the evolving probability distributions of crop yields drive adaptation decisions.
To understand climate change adaptation behavior by farmers, we undertook the study “Elicitation and Estimation of Risk Preference and Subjective Probabilities to Understand Farmer Decisions on Climate Change Adaptation.” We interviewed 44 Michigan corn and soybean farmers to elicit mathematical expressions of their risk attitudes. During the interviews, each completed two sets of lottery choices, the first using 25 general risky gambles and the second using 18 risky gambles in a crop farming context that enable econometric estimation of risk attitudes (using variants of Expected Utility Theory). Next, they answered questions about corn yield probability distributions over the past ten years and the next ten years (triangular distributions of minimum, most likely, and maximum values) with no water management, irrigation, tile drainage, and drought-resistant seed. After that, they reported on water management investments that they have made in past and intend to make in future. Finally, they provided background information about themselves and their farms.
This study (MSU Study ID: STUDY00007871) was submitted to the Michigan State University Institutional Review Board (IRB) by principal investigator Scott Swinton. On July 5, 2022, it was determined to be exempt under 45 CFR 46.104(d) 3(i)(B). Data collection took place during September 2022 through March 2023. Farmer respondents completed the survey instrument on Qualtrics with assistance from graduate students in Agricultural, Food, and Resource Economics at Michigan State University at various MSU Extension offices and restaurants around southern Michigan. Respondents received lunch plus $50 for participating and a credit of $40 that could be gained or lost based on the outcome from one of the risky gambles (included to encourage truthful responses [“incentive compatibility”]).

Note

Experiment: Social Science Studies
Data available from: September 2022 to March 2023
Dataset: KBS159
Datatable ID: KBS159-002.67
Repository link:
Related Tables:
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Last Updated 2025-04-16
Variate Description Units
id Farmer identification number
q1 Whether Lottery A selected (1) or Lottery B (2) for Question 1
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q2 Whether Lottery A selected (1) or Lottery B (2) for Question 2
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q3 Whether Lottery A selected (1) or Lottery B (2) for Question 3
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q4 Whether Lottery A selected (1) or Lottery B (2) for Question 4
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q5 Whether Lottery A selected (1) or Lottery B (2) for Question 5
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q6 Whether Lottery A selected (1) or Lottery B (2) for Question 6
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q7 Whether Lottery A selected (1) or Lottery B (2) for Question 7
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q8 Whether Lottery A selected (1) or Lottery B (2) for Question 8
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q9 Whether Lottery A selected (1) or Lottery B (2) for Question 9
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q10 Whether Lottery A selected (1) or Lottery B (2) for Question 10
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q11 Whether Lottery A selected (1) or Lottery B (2) for Question 11
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q12 Whether Lottery A selected (1) or Lottery B (2) for Question 12
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q13 Whether Lottery A selected (1) or Lottery B (2) for Question 13
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q14 Whether Lottery A selected (1) or Lottery B (2) for Question 14
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q15 Whether Lottery A selected (1) or Lottery B (2) for Question 15
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q16 Whether Lottery A selected (1) or Lottery B (2) for Question 16
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q17 Whether Lottery A selected (1) or Lottery B (2) for Question 17
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q18 Whether Lottery A selected (1) or Lottery B (2) for Question 18
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q19 Whether Lottery A selected (1) or Lottery B (2) for Question 19
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q20 Whether Lottery A selected (1) or Lottery B (2) for Question 20
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q21 Whether Lottery A selected (1) or Lottery B (2) for Question 21
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q22 Whether Lottery A selected (1) or Lottery B (2) for Question 22
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q23 Whether Lottery A selected (1) or Lottery B (2) for Question 23
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q24 Whether Lottery A selected (1) or Lottery B (2) for Question 24
  • 1 - lottery A was selected
  • 2 - lottery B was selected
q25 Whether Lottery A selected (1) or Lottery B (2) for Question 25
  • 1 - lottery A was selected
  • 2 - lottery B was selected
drainage 1 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
drainage 2 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
drainage 3 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
drainage 4 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
irrigation 1 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
irrigation 2 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
irrigation 3 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
irrigation 4 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
insurance 1 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
insurance 2 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
insurance 3 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
insurance 4 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
seeds 1 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
seeds 2 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
high irrig 1 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
high irrig 2 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
high irrig 3 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
high irrig 4 Whether Lottery A selected (1) or Lottery B (2)
  • 1 - lottery A was selected
  • 2 - lottery B was selected
past distributions 1 1 Lowest yield past 10 yr w/ no water mgmt bu/ac
past distributions 1 2 Lowest yield past 10 yr w/ irrigation bu/ac
past distributions 1 3 Lowest yield past 10 yr w/ drainage tile bu/ac
past distributions 1 4 Lowest yield past 10 yr w/ drought-tolerant seed bu/ac
past distributions 2 1 Most likely yield past 10 yr w/ no water mgmt bu/ac
past distributions 2 2 Most likely yield past 10 yr w/ irrigation bu/ac
past distributions 2 3 Most likely yield past 10 yr w/ drainage tile bu/ac
past distributions 2 4 Most likely yield past 10 yr w/ drought-tolerant seed bu/ac
past distributions 3 1 Highest yield past 10 yr w/ no water mgmt bu/ac
past distributions 3 2 Highest yield past 10 yr w/ irrigation bu/ac
past distributions 3 3 Highest yield past 10 yr w/ drainage tile bu/ac
past distributions 3 4 Highest yield past 10 yr w/ drought-tolerant seed bu/ac
future distributions 1 1 Lowest yield past 10 yr w/ no water mgmt bu/ac
future distributions 1 2 Lowest yield past 10 yr w/ irrigation bu/ac
future distributions 1 3 Lowest yield past 10 yr w/ drainage tile bu/ac
future distributions 1 4 Lowest yield past 10 yr w/ drought-tolerant seed bu/ac
future distributions 2 1 Most likely yield past 10 yr w/ no water mgmt bu/ac
future distributions 2 2 Most likely yield past 10 yr w/ irrigation bu/ac
future distributions 2 3 Most likely yield past 10 yr w/ drainage tile bu/ac
future distributions 2 4 Most likely yield past 10 yr w/ drought-tolerant seed bu/ac
future distributions 3 1 Highest yield past 10 yr w/ no water mgmt bu/ac
future distributions 3 2 Highest yield past 10 yr w/ irrigation bu/ac
future distributions 3 3 Highest yield past 10 yr w/ drainage tile bu/ac
future distributions 3 4 Highest yield past 10 yr w/ drought-tolerant seed bu/ac
county 1 County’s lowest average yield past 10 years bu/ac
county 2 County’s most likely average yield past 10 years bu/ac
county 3 County’s highest average yield past 10 years bu/ac
future price Average price over the next 10 years bu/ac
p1 1 Whether they are currently implementing drought tolerant seeds
  • 1 - if true
p1 2 Whether they are currently implementing notill
  • 1 - if true
p1 3 Whether they are currently implementing reduced tillage
  • 1 - if true
p1 4 Whether they are currently implementing cover crops
  • 1 - if true
p1 5 Whether they are currently implementing conservation strips
  • 1 - if true
p1 6 Whether they are currently implementing filter strips
  • 1 - if true
p1 7 Whether they are currently implementing soil tests for lime, phosphorus and pottasium
  • 1 - if true
p1 8 Whether they are currently implementing soil test for nitrogen
  • 1 - if true
p1 9 Whether they are currently implementing center pivot irrigation
  • 1 - if true
p1 10 Whether they are currently implementing drip irrigation
  • 1 - if true
p1 11 Whether they are currently implementing tile drainage at 20ft spacing
  • 1 - if true
p1 12 Whether they are currently implementing tile drainage at 30ft spacing
  • 1 - if true
p1 13 Whether they are currently implementing tile drainage at 40ft spacing
  • 1 - if true
p1 14 Whether they are currently implementing tile drainage at 45ft spacing
  • 1 - if true
p1 15 Whether they are currently implementing tile drainage at 50ft spacing
  • 1 - if true
p1 16 Whether they are currently implementing tile drainage at 60ft spacing
  • 1 - if true
p1 17 Whether currently implementing any tile drainage (“current_practices_drain_” = 1)
  • 1 - if true
p1 18 Whether they are currently implementing controlled drainage
  • 1 - if true
w1 1 Prediction of future temperature
  • 1 - will decrease
  • 2 - stay the same
  • 3 - increase
w1 2 Prediction of future total precipitation
  • 1 - will decrease
  • 2 - stay the same
  • 3 - increase
w1 3 Prediction of future intensity of precipitation
  • 1 - will decrease
  • 2 - stay the same
  • 3 - increase
w1 4 Prediction of future frequency of precipitation
  • 1 - will decrease
  • 2 - stay the same
  • 3 - increase
w1 5 Prediction of future spring precipitation
  • 1 - will decrease
  • 2 - stay the same
  • 3 - increase
w2 1 Whether considering cropping change
  • 1 - if true
w2 2 Whether considering cropping change
  • 1 - if true
w2 3 Whether considering cropping change
  • 1 - if true
w2 4 Whether considering cropping change
  • 1 - if true
w2 5 Whether considering cropping change
  • 1 - if true
w2 6 Whether considering cropping change
  • 1 - if true
w2 7 Whether considering cropping change
  • 1 - if true
w2 8 if w2_8 = 1 please specify new crop.
  • 1 - if true
w2 9 Did not consider a cropping change
  • 1 - if true
w2 8 text If crop_change_newcrop = 1, please specify
w3 1 Whether considering production change
  • 1 - if true
w3 2 Whether considering production change
  • 1 - if true
w3 3 Whether considering production change
  • 1 - if true
w3 4 Whether considering production change
  • 1 - if true
w3 5 Whether considering production change
  • 1 - if true
w3 6 Whether considering production change
  • 1 - if true
w3 7 Whether considering production change
  • 1 - if true
d1 New drainage spacing in feet, The survey encouraged the use of numbers but some respondent entered text
d2 Increased drainage spacing in feet. The survey asked for a number but some respondents entered text
e1 1 Concern level for floods
  • 1 - low
  • 2 - medium low
  • 3 - medium
  • 4 - medium high
  • 5 - high
e1 2 Concern level for droughts
  • 1 - low
  • 2 - medium low
  • 3 - medium
  • 4 - medium high
  • 5 - high
e1 3 Concern level for warmer temperatures
  • 1 - low
  • 2 - medium low
  • 3 - medium
  • 4 - medium high
  • 5 - high
e1 4 Concern level for extreme weather events
  • 1 - low
  • 2 - medium low
  • 3 - medium
  • 4 - medium high
  • 5 - high
e1 5 Concern level for soil erosion
  • 1 - low
  • 2 - medium low
  • 3 - medium
  • 4 - medium high
  • 5 - high
e1 6 Concern level for pest impacts
  • 1 - low
  • 2 - medium low
  • 3 - medium
  • 4 - medium high
  • 5 - high
e1 7 Concern level for weed pressure
  • 1 - low
  • 2 - medium low
  • 3 - medium
  • 4 - medium high
  • 5 - high
e2 1 Have you noticed this condition in the past
  • 1 - yes
  • 2 - no
  • 3 - not sure
e2 2 Have you noticed this condition in the past
  • 1 - yes
  • 2 - no
  • 3 - not sure
e2 3 Have you noticed this condition in the past
  • 1 - yes
  • 2 - no
  • 3 - not sure
e2 4 Have you noticed this condition in the past
  • 1 - yes
  • 2 - no
  • 3 - not sure
e2 5 Have you noticed this condition in the past
  • 1 - yes
  • 2 - no
  • 3 - not sure
e2 6 Have you noticed this condition in the past
  • 1 - yes
  • 2 - no
  • 3 - not sure
e2 7 Have you noticed this condition in the past
  • 1 - yes
  • 2 - no
  • 3 - not sure
e2 8 Have you noticed this condition in the past
  • 1 - yes
  • 2 - no
  • 3 - not sure
e2 9 Have you noticed this condition in the past
  • 1 - yes
  • 2 - no
  • 3 - not sure
e2 10 Have you noticed this condition in the past
  • 1 - yes
  • 2 - no
  • 3 - not sure
e2 11 Have you noticed this condition in the past
  • 1 - yes
  • 2 - no
  • 3 - not sure
e2 12 Have you noticed this condition in the past
  • 1 - yes
  • 2 - no
  • 3 - not sure
e3 1 Have you implemented this in response to weather changes
  • 1 - if true
e3 2 Have you implemented this in response to weather changes
  • 1 - if true
e3 3 Have you implemented this in response to weather changes
  • 1 - if true
e3 4 Have you implemented this in response to weather changes
  • 1 - if true
e3 5 Have you implemented this in response to weather changes
  • 1 - if true
e3 6 Have you implemented this in response to weather changes
  • 1 - if true
e3 7 Have you implemented this in response to weather changes
  • 1 - if true
e3 8 Have you implemented this in response to weather changes
  • 1 - if true
e3 9 Have you implemented this in response to weather changes
  • 1 - if true
e3 10 Have you implemented this in response to weather changes
  • 1 - if true
e3 11 Have you implemented this in response to weather changes
  • 1 - if true
e3 12 Have you implemented this in response to weather changes
  • 1 - if true
f1 1 Acres own acre
f1 2 Acres rented acre
f1 3 Acres rented out acre
f1 4 Acres owned + acres rented – acres rented out acre
county What county are most of your acres in?
soil type Most common soil type for fields
f3 1 Acres of this crop planted this year acre
f3 2 Acres of this crop planted this year acre
f3 3 Acres of this crop planted this year acre
f3 4 Acres of this crop planted this year acre
f4 Abandoned more than 5 acres over past 10 years
  • 1 - if true
f5 1 Reason abandoned due to drought
  • 1 - if true
f5 2 Reason abandoned due to flooding
  • 1 - if true
f5 3 Reason abandoned due to soil crusting
  • 1 - if true
f5 4 Reason abandoned due to disease
  • 1 - if true
f5 5 Reason abandoned due to weed problems
  • 1 - if true
f5 6 Reason abandoned due to insect problems
  • 1 - if true
f5 7 Reason abandoned due to hail damage
  • 1 - if true
f5 8 Reason abandoned due to frost
  • 1 - if true
f5 9 Reason abandoned due to wind
  • 1 - if true
f5 10 Reason abandoned due to heat
  • 1 - if true
f5 11 Reason abandoned due to deer
  • 1 - if true
f5 12 Reason abandoned for other reasonse
  • 1 - if true
f5 12 text If reasonabandoned_other = 1 please specify
times abandoned Number of times abandoned
f6 1 Acres operated with practice acre
f6 2 Acres operated with practice acre
f6 3 Acres operated with practice acre
f6 4 Acres operated with practice acre
income level Income level
  • 1 - less than $25,000
  • 2 - $25,000-$50,000
  • 3 - $50,000-$100,000
  • 4 - $100,000-$200,000
  • 5 - $200,000-$500,000
  • 6 - $500,000-$1,000,000
  • 7 - Above $1,000,000
livestock Earnings from livestock more than 5% of farm revenue
  • 1 - if true
section 179 Treated an agricultural investment as a capital expense for tax purposes
  • 1 - if true
section 179 expense type Type of investment
debt asset Debt to asset ratio
  • 9 - 0%-9%
  • 10 - 10%-24%
  • 1 - 25%-32%
  • 2 - 33%-49%
  • 3 - 50%-66%
  • 4 - 67%-74%
  • 5 - 75%-99%
  • 6 - debt equal to asset value
  • 7 - debt greater than asset value
  • 8 - prefer not to say
birth year Birth year
decisionmaker year Year became decision maker
farming years remain Years left in farming
sex Sex
  • 1 - Male
  • 2 - Female
  • 6 - Other
  • 7 - Prefer not to say
education Education level
  • 1 - less than high school
  • 2 - high school diploma
  • 3 - some college
  • 4 - associate degree
  • 5 - bachelor’s degree
  • 6 - master’s degree or higher
ethnicity Ethnicity
  • 1 - Caucasian
  • 2 - African American
  • 3 - Latino or Hispanic
  • 4 - Native American
  • 5 - Other
farm inc perc Household income percentage from farming
  • 1 - less than 25%
  • 2 - 25%-50%
  • 3 - 50%-75%
  • 4 - 75%-100%
Protocols

Data Excerpt

id q1 q2 q3 q4 q5 q6 q7 q8 q9 q10 q11 q12 q13 q14 q15 q16 q17 q18 q19 q20 q21 q22 q23 q24 q25 drainage_1 drainage_2 drainage_3 drainage_4 irrigation_1 irrigation_2 irrigation_3 irrigation_4 insurance_1 insurance_2 insurance_3 insurance_4 seeds_1 seeds_2 high_irrig_1 high_irrig_2 high_irrig_3 high_irrig_4 past_distributions_1_1 past_distributions_1_2 past_distributions_1_3 past_distributions_1_4 past_distributions_2_1 past_distributions_2_2 past_distributions_2_3 past_distributions_2_4 past_distributions_3_1 past_distributions_3_2 past_distributions_3_3 past_distributions_3_4 future_distributions_1_1 future_distributions_1_2 future_distributions_1_3 future_distributions_1_4 future_distributions_2_1 future_distributions_2_2 future_distributions_2_3 future_distributions_2_4 future_distributions_3_1 future_distributions_3_2 future_distributions_3_3 future_distributions_3_4 county_1 county_2 county_3 future_price p1_1 p1_2 p1_3 p1_4 p1_5 p1_6 p1_7 p1_8 p1_9 p1_10 p1_11 p1_12 p1_13 p1_14 p1_15 p1_16 p1_17 p1_18 w1_1 w1_2 w1_3 w1_4 w1_5 w2_1 w2_2 w2_3 w2_4 w2_5 w2_6 w2_7 w2_8 w2_9 w2_8_text w3_1 w3_2 w3_3 w3_4 w3_5 w3_6 w3_7 d1 d2 e1_1 e1_2 e1_3 e1_4 e1_5 e1_6 e1_7 e2_1 e2_2 e2_3 e2_4 e2_5 e2_6 e2_7 e2_8 e2_9 e2_10 e2_11 e2_12 e3_1 e3_2 e3_3 e3_4 e3_5 e3_6 e3_7 e3_8 e3_9 e3_10 e3_11 e3_12 f1_1 f1_2 f1_3 f1_4 county soil_type f3_1 f3_2 f3_3 f3_4 f4 f5_1 f5_2 f5_3 f5_4 f5_5 f5_6 f5_7 f5_8 f5_9 f5_10 f5_11 f5_12 f5_12_text times_abandoned f6_1 f6_2 f6_3 f6_4 income_level livestock section_179 section_179_expense_type debt_asset birth_year decisionmaker_year farming_years_remain sex education ethnicity farm_inc_perc
1 1 2 2 1 1 2 1 1 2 2 1 2 1 2 2 2 2 1 1 1 2 1 2 2 2 1 1 1 1 2 2 1 1 1 2 1 2 1 1 2 2 1 1 90 90 120 90 120 145 155 125 165 220 220 175 95 95 125 95 125 150 160 130 170 225 225 180 120 152 157 4.5 1 1 1 1 1 1 1 2 2 2 2 1 1 1 1 1 1 1 1 1 20 or less split the 40s into 20 4 2 2 3 1 2 4 1 2 3 2 2 2 2 2 2 1 1 1 0 1 0 0 0 0 1 0 1 0 1 1 400 400 0 800 114 capac loam 350 450 0 0 0 800 650 0 0 4 0 1 tile 2 1982 2006 25 1 5 1 4
2 2 2 2 1 2 2 1 1 2 2 2 2 2 1 1 1 2 1 1 1 1 1 2 2 1 1 1 1 1 2 2 2 2 1 1 1 2 1 1 2 1 1 2 90 180 90 110 120 210 120 140 150 240 150 160 100 180 105 120 140 220 140 150 160 260 150 180 142 165 200 5 1 1 1 1 1 3 1 2 1 2 1 1 1 1 1 1 1 1 4 3 1 5 3 2 1 2 1 2 1 1 1 1 2 2 2 1 0 1 1 1 1 1 1 1 0 0 1 0 3000 1700 0 4700 114 sandy 2100 2000 600 0 1 1 4 4350 1000 0 1100 7 1 1 Grain Handling, Equipment, Buildings 9 1998 2021 60 1 2 1 4
3 2 2 1 2 2 2 1 1 2 1 1 2 1 2 2 2 2 2 1 1 1 1 2 1 2 1 2 1 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 70 150 130 80 150 190 170 150 180 220 220 180 70 150 130 80 150 190 170 150 180 220 220 180 125 140 150 5.5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 30 25 4 4 4 4 4 5 5 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 250 1000 0 1250 144 nester kawkalin 750 200 0 300 1 1 1 2 1250 1250 0 250 7 0 1 irrigation 10 1970 2010 30 1 3 5 3
4 1 2 2 1 1 2 1 1 2 2 1 2 2 1 2 2 2 2 1 1 2 1 2 2 2 1 2 1 1 2 2 2 2 1 2 1 2 2 1 2 1 1 1 125 155 175 185 160 170 190 195 175 250 215 205 125 155 175 185 165 178 193 198 165 250 225 215 135 163 174 4.35 1 1 1 1 1 3 2 3 1 3 1 1 1 1 1 25 33 4 4 4 4 2 4 4 2 2 2 2 3 1 2 2 2 1 1 2 0 1 0 1 1 0 1 1 0 0 1 1 450 3050 0 3500 114 parkhill 1200 1850 450 0 1 1 1 3500 3500 3500 0 7 0 1 land and machinery 8 1954 1994 7 1 4 1 4
5 1 1 1 1 1 2 1 2 1 2 1 2 2 1 2 1 1 1 1 2 2 2 1 1 1 1 2 2 1 2 2 2 2 1 2 2 1 1 1 2 2 2 1 85 165 110 120 115 185 145 145 130 215 170 180 125 185 135 135 140 220 170 170 160 260 205 200 148 163 174 6.5 1 1 1 1 1 1 1 3 3 2 2 3 1 1 1 1 1 1 4 5 4 5 5 5 5 1 1 1 2 1 1 1 1 1 1 1 1 0 0 0 0 1 0 1 1 0 0 0 0 2500 2000 0 4600 114 loam 2000 2580 20 0 0 4300 3200 2500 0 7 0 1 tile land clearing 2 1963 1983 20 1 2 1 3
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