The Profitability of Precision Ag in Times of Increased Financial Vulnerability

Terry Griffin, PhD, CCACropping Systems Economist

Department of Agricultural Economics

@SpacePlowboy#PrecisionAg #farmData

#EOCC17

Eastern Ontario Crop ConferenceKemptville, ON February 14, 2017

Farmer’s Use of Precision Ag

0

25

50

75

100

1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Per

cent of

Far

ms

Automated Guidance Lightbar Automated Section Control Precision Soil Sampling

Yield Monitor Yield Monitor with GPS Variable Rate Fert. Variable Rate Seed

N=348

Proportion of Farms' Adoption of Precision

Probability of Adopting…

Given…

Soil

Sampling

VR

Fertility VR Seed

GPS Yield

Monitor

Automated

Guidance

Soil Sampling - 59% 30% 65% 87%

VR Fertility 92% - 37% 68% 92%

VR Seed 75% 60% - 86% 98%

GPS Yield Monitor 69% 46% 36% - 97%

Automated Guidance 55% 37% 24% 58% -

N=358

Adopting, upgrading, and abandoning

Number of Farms

%

abandonedTechnology adopt abandon upgrading

abandon

(adjusted)**

Yield Monitor 147 60 54 6 4

Lightbar 202 57 45 12 6

Precision Soil

Sampling149 6 NA 6 4

Variable Rate

Fertility94 3 NA 3 3

Yield Monitor

w/GPS142 2 NA 2 1

N=358

Tale of Two Technologies

Information-intensive

• Field level data to

make decisions

• Requires additional

data and skill

• IPM

Embodied-knowledge

• Information purchased

in the form of an input

• Requires minimal

additional data/skill

• Round-up Ready or Bt

Two Faces of Precision Agriculture

Information-intensive

• Yield monitors

• Traditional variable

rate applications

• *Data

Embodied-knowledge

• Automated guidance

• On-the-go sensors

applying variable rates

• *Automated

Precision ag bundles

0%

20%

40%

60%

80%

100%

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

% o

f U

sers

YM, PSS, & VR PSS & VR

YM & VR YM & PSS

Variable Rate (VR) Precision Soil Sampling (PSS)

Yield Monitor (YM) None

Probability of transitioning

none PSS

PSS

VR VR YM

YM

PSS

YM

PSS

VR

YM

VR

none 0.94 0.01 0.01 0.01 0.04 0.01 0.01 0.01

PSS 0.01 0.82 0.04 0 0 0.12 0.01 0

PSS VR 0.01 0 0.94 0 0 0 0.05 0

VR 0 0 0 0.53 0 0 0 0.47

YM 0.01 0 0 0 0.90 0.04 0.03 0.03

YM PSS 0 0 0.01 0 0.01 0.89 0.11 0

YM PSS VR 0 0 0 0 0 0.01 0.99 0.01

YM VR 0.12 0 0 0 0.01 0 0.10 0.77

YM = Yield monitor

VR = Variable rate

PSS = Precision soil sampling

Fro

m

To

Current precision ag utilization

• 20% use telematics in 2015

– Up from 15% in 2013

• Most common (72%) soil grid size = 2.5 ac

– Smaller grid sizes used only 13% of time

• 16% of service providers use UAVs

Erickson & Widmar, 2015

Profitability over time

34%

42%42%

40%36%

44% 44% 45%

44%

62%

35% 33% 39%

42%

34%

47% 50%

51%

60%

74%

41%

33%

43% 44% 45%

49%51%

58%63%

75%

26%27%

20%

30%

25% 25%22%

20%21%

20%18%

22%13%

21%19%

15%19%

26%

11%

14%

31%

37% 39%

38%

44%43% 43% 42%

51%

60%

0%

10%

20%

30%

40%

50%

60%

70%

80%

2003 2004 2005 2006 2007 2008 2009 2011 2013 2015

% o

f re

spondents

off

eri

ng p

recis

ion s

erv

ices

makin

g

a p

rofi

t

Soil Sampling

Single Variable Rate Application

Multi Variable Rate Application

Satellite Imagery

Yield Monitor Data Analysis

Total Precision Package

2015 Base: 261

Erickson & Widmar, 2015

Farm Data Quality & Value

• Yield monitor data is great, but…

– Sensor calibration crucial

– Yield cleaning necessary

– Data ≠ truth

USDA ARS Yield Editor

Raw data from combine yield monitor

Default cleaning algorithm

Advanced data cleaning algorithm

Unprocessed yield data

Filtered yield data

Farm Data Quality Litmus Test #1

Flow delay set correctly: not jagged edges. “field in focus”

Summary

• UAVs and drones

• Automated equipment

• Data and information technologies

Terry Griffin

Cropping Systems Economist

twgriffin@ksu.edu

501.249.6360

@SpacePlowboy

Would love to hear from

you about your thoughts!