Yield Gap Analysis: Implications for Research and Policy

Yield Gap Analysis:
Implications for Research and Policy
Kenneth G. Cassman
Heuermann Professor of Agronomy, and
Director, NE Center for Energy Sciences
University of Nebraska—Lincoln
www.ncesr.unl.edu
Drier savanna
Moist savanna
Humid forest
Midaltitude savanna

What do these have in common?
• Ensuring global food security in face of climate
change
• Land use and indirect land use change
– Impact of climate change on agriculture and
vica versa
• Competition between food and biofuel
• Conservation of natural ecosystems and
biodiversity
EACH DEPENDS ON RATE OF GAIN IN CROP
YIELDS ON EXISTING FARM LAND

• Will business as usual meet projected
global food demand in 2050?
� Global area for cereal crops declining
�48% increase in cereal production
needed by 2050 (40 yr) = 1.2% yr -1 of
current average yield, or…..
�1% annual exponential growth rate
• If business as usual won’t do it, what is
needed to change course?

Grain harvested area (Mha)
800
700
600
500
Global Cereal Area Trends, 1966-2006
Total cereal area
(maize, rice, wheat, sorghum, millet, barley, oats)
1966-1980 1966 1980
+4.6 Mha y-1 1966-1980 1966 1980
+3.9 Mha y-1 400
1960 1970 1980 1990 2000 2010
Year
1981-2006 1981 2006
-1.7 1.7 Mha y-1 maize + rice + wheat area
1981-2006 1981 2006
+0.5 Mha y-1

Urban-industrial expansion onto prime farmland at the periphery
of Kunming (+6 million), the capital of Yunnan Province, China,

Grain Yield (kg ha -1 )
Global Cereal Yield Trends, 1966-2006
5000
4000
3000
2000
1000
+2.8%
Maize Yield
y = 2260 + 62.5x
r 2 = 0.94
Wheat Yield
y = 1373 + 40.1x
r 2 = 0.97
1966 1976 1986 1996 2006
Year
Rice Yield
y = 2097 + 53.5x
r 2 = 0.98
THESE RATES OF INCREASE ARE NOT FAST ENOUGH TO MEET
EXPECTED DEMAND ON EXISTING FARM LAND! source: FAOSTAT
+1.3%

Global Average Maize Yield (kg ha -1 )
7500
7000
6500
6000
5500
5000
4500
Tyranny of constant rate of yield gain:
Decreasing relative rate of gain
Global Maize Grain Yield kg ha -1
Relative Rate of Gain
2010 2020 2030 2040 2050
1.4
1.3
1.2
1.1
1.0
0.9
0.8
Relative Rate of Gain (% average yield)

IRRIGATED AREA (Mha)
Global Irrigated Area and as a % of Total Cultivated
Land Area, 1966-2004
300
250
200
150
100
Irrigated Area
1965 1975 1985 1995 2005
YEAR
% of total
cultivated area
Irrigated systems occupied 18% of
cultivated land area but produced
40% of human food supply
20.0
17.5
15.0
12.5
10.0

Decreasing water supply in all major irrigated areas
Yet, irrigated agriculture produces 40% of global food supply
on just 18% of the cropped area.

Corn grain yield (bu ac -1 )
USA Corn Yield Trends, 1966-2009
(powerful support from science and technology)
180
160
140
120
100
80
linear rate of gain = 1.86 bu ac -1 yr -1
Expansion of irrigated area
double- to
single-cross
hybrids
Improved balance in N,P,K fertilization
Multi-location hybrid testing in
1000s of on-farm strip trials
Increased N fertilizer rates
Conservation tilliage and soil testing
60
1960 1970 1980 1990 2000 2010
Year
Electronic
auto-steer
Precision planters
Transgenic (Bt)
insect resistance
Integrated pest management

From NCGA website, 8 May 2008:
http://www.ncga.com/PDFs/NCGA%20Presentation%20on%20Food%20and%20Fuel%205-7-08.pdf

Bottom Line on Yield Trends
• Expansion of crop area limited by lack of good
quality arable soils and concerns about loss of
wildlife habitat and biodiversity
– USA conservation reserve land
– Rainforests and wetlands in Latin America, SE Asia, SSA
• Current rates of gain in crop yields not adequate to
meet expected demand for food, feed, fiber, and fuel
on existing crop land
• Little scope for increasing irrigated crop area due to
competition for water with other sectors
• Little increase in yield potential of maize or rice for
the last 30-40 years; yield stagnation in some areas
• Little scope for quantum leap in yields from
biotechnology?
• Need for ecological intensification (global sense)

Clearing virgin rain forest in Brazil

Ecological Intensification
• How close can average farm yields
come to the yield potential ceiling
using crop and soil management
practices that conserve natural
resources, protect environmental
quality, give acceptable rate of
economic return?
• Necessary, but not sufficient…..
– food affordability and access, markets,
good governance, policies, etc.

N fertilizer rate (kg N ha -1 )
NUE (kg grain kg -1 N fertilizer)
High yields and high nitrogen use efficiency (NUE) are possible*
•Based on data from 123 fields farmer’s irrigated fields in 2005-2007 seasons, Nebraska, USA.
Grassini et al., submitted, Field Crops Res.
220
200
180
160
140
90
80
70
60
50
12.7 13.3 kg ha -1
Continuous maize Soybean-maize
U.S. maize averages
13.5 13.4
Continuous maize Soybean-maize
Tillage system:
Conservation (NT): strip-,
ridge-, and no-till.
Conventional (CT): disk
• Higher N rates but also higher NUE
compared to U.S. averages,
especially under soybean-corn
rotation due to higher yields and
lower N rate than continuous corn.
• No difference in N fertilizer rate
under continuous corn with NT or
CT; under soybean-corn rotation, N
fertilizer tended to be higher under
NT than CT.
• NUE tended to be higher under
conventional tillage due to (i) higher
yields at the same N rate under
continuous corn and (ii) same yield
with lower N rate under soybeancorn
rotation.

High yields and high water use
efficiency are possible: maize in
south-central NE, 2-y means 2005-06
More crop per drop
Treatment Yield
(t/ha)
Irrigation
(cm)
100% ET 14.9 22.6
Irrigation Efficiency
(t/cm)
0.66
75% ET* 14.7 17.0
0.86
50% ET 12.8 11.4
1.12
Rainfed 5.8 0
--
*75% ET replacement except 10 d before and 7 d after silking

Ecological Intensification
• How close can average farm yields
come to the yield potential ceiling
using crop and soil management
practices that conserve natural
resources, protect environmental
quality, give acceptable rate of
economic return?
• Necessary, but not sufficient…..
– food affordability and access, markets,
good governance, policies, etc.

Yield (Mg ha -1 Yield (t ha ) -1 )
7
6
5
4
3
2
1
0
Evidence that average national yields begin to plateau
when they reach 70-80% of yield potential
Rice
R. Korea
Cassman, 1999. PNAS, 96: 5952-5959
China
Indonesia
India
1960 1970 1980 1990 2000 2010
Year
8
7
6
5
4
3
2
1
0
Wheat
Northwest Europe
China
India
1960 1970 1980 1990 2000 2010
Year
Cassman et al, 2003, ARER 28: 315-358
12
10
8
6
4
2
0
Maize
USA - irrigated
China
USA - rainfed
Brazil
1960 1970 1980 1990 2000 2010
Year
Note yield plateaus in Korea and China for rice, wheat in northwest Europe
and India, and maize in China and……..perhaps for irrigated maize in the USA
?

Crop Sci. 50:1882–1890 (2010)
Genetic Improvement in Winter Wheat Yields in the Great Plains of North
America, 1959–2008
Robert A. Graybosch* and C. James Peterson
Abstract
……Linear regressions of relative grain yields vs. year over the time period 1984 to
2008, however, showed no statistically significant trend in the SRPN. For the same
time period in the NRPN, a statistically significant positive slope of 0.83 was
observed, though the coefficient of determination (R2) was only 0.28. …….. and
further improvement in the genetic potential for grain yield awaits some new
technological or biological advance.
Field Crops Research 119 (2010) 201–212
Why are wheat yields stagnating in Europe? A comprehensive data
analysis for France
Nadine Brissona,∗, Philippe Gateb, David Gouacheb, Gilles Charmetc, Francois-
Xavier Ouryc, Frédéric Huarda
Abstract
The last two decades are witnessing a decline in the growth trend of cereal yields in
many European countries. The present study analyses yield trends in France using
various sources of data: national and regional statistics, scattered trials, results of
agroclimatic models using climatic data.

What are reasons for yield stagnation?
• Secret plot among farmers to limit
production?
• Climate change?
• Unidentified constraints and/or lack of
appropriate crop and soil management
technologies to take full advantage of solar
radiation and water resources?
• Average farm yields are bumping up against
the yield potential (Yp) ceiling (75-85% of Yp)
– Size of exploitable yield gap is too small

Yield
CO 2
Solar radiation
Temperature
Growth period
Plant density
Gap 1
Attainable yield
with available
water supply:
Soil
Rainfall
Irrigation
Yield potential Water-limited
yield potential
Gap 2
Other limiting
factors:
Nutrients
Weeds
Pests
Others
Actual yield
Yield potential and yield gaps
Modified from: van Ittersum and Rabbinge, 1997

When producing crops near the yield potential ceiling, there is a razorthin
margin for error in managing inputs (too much, too little, too early,
too late), and also in managing pests because of dynamic interactions
between nutrient status and pest incidence and severity

Interactions between plant
nutrient status and disease
become more prominent at
high yield levels:
For many crops, there is often
a positive relationship between
leaf N concentration and the
prevalence and severity of
several foliar diseases. In this
case, sheath blight on rice in
Vietnam. Hence, a critical
need to precisely balance N
supply with crop demand
without excess or deficiency.

Yield
75-85% Yp
CO 2
Solar radiation
Temperature
Growth period
Plant density
Gap 1
70-80% Yp-r
Attainable yield
with available
water supply:
Soil
Rainfall
Irrigation
Yield potential Water-limited
yield potential
Gap 2
Other limiting
factors:
Nutrients
Weeds
Pests
Others
Actual yield
Yield potential and yield gaps

Developing a transparent, robust,
reproducible protocol to estimate
crop yield potential (Yp) in a given
field, region, state, or nation
PhD. Project---Justin van Wart

Rainfed Maize area and NOAA weather stations with +20 yr data
(daily Tmax/Tmin, rainfall, dewpoint, wind speed)

Rank of NOAA weather stations by density of harvested rainfed maize area

Select reference weather stations (RWS) with greatest maize area density
within 100-km buffers, with minimum overlap, until >50% of U.S maize area
is covered. Weight Yp estimates for each RWS buffer by maize area
density to estimate national Yp.
Total area within buffers
account for 52% of USA
RF maize production

Appropriate crop simulation model
(validated against yields that approach Yp)

Complicated systems: Maize, rice, wheat in China
Source: Monfreda et al, 2008

NOAA weather stations with +20 yrs data: daily Tmax,
Tmin, precip, dewpoint, wind speed and harvested rice
area density in China

Intensive lowland rice systems in Asia
Central Luzon
Philippines
Mekong Delta
Vietnam
West Java
Indonesia
Cauvery Delta
South India
Southern
China
Indo-Gangetic
Plain & SC China
Red River D.
Vietnam
Central Java
Indonesia
Rice-Rice
Rice-Rice-
Rice
Rice-Rice
Rice-Rice-
Pulses
Rice-Rice
(hybrid)
Rice-Rice-
Maize
DS rice WS rice
DS rice WS rice
WS rice DS rice
Pulses WS rice DS rice
Early-rice Late-rice
Rice-Wheat Wheat
WS rice
Rice-Rice-
Maize
WS rice
Spring-rice Summer-rice Maize
Rice Maize Rice
J F M A M J J A S O N D
Month

Major rice cropping systems in China: 17 provinces, 44 systems (94% of total rice area)
Province Cropping season Crop establish Seeding rate* Hills per m2 Seeding date Transplanting date Flowering date Maturity date Area (ha) Variety match
Hubei Early season Transplanting 25 266,667 IR72
Middle season
Direct seeding
Transplanting
45 (H), 90 (I)
21
266,667
533,333
IR72
2You725
Direct seeding 45 (H), 90 (I) 800,000 2You725
Hunan
Late season
Early season
Transplanting
Transplanting
22.5
25
200,000
1,133,333
IR72
IR72
Direct seeding 30 (H), 60 (I) 466,667 IR72
Middle season
Single late season
Transplanting
Transplanting
22.5
18.4
500,000
366,667
2You725
2You725
Double late season Transplanting 18.4 1,600,000 IR72
Anhui Early season Transplanting 37.5 80,000 IR72
Direct seeding 75 (I) 186,667 IR72
Middle season Transplanting 22.5 1,466,667 2You501
Direct seeding 45 (I) 200,000 2You501
Late season Transplanting 37.5 300,000 IR72
Jiangxi Early season Transplanting 30 1,333,333 IR72
Direct seeding 37.5 (H), 60 (I) 133,333 IR72
Middle season Transplanting 27 333,333 2You501
Late season Transplanting 27 1,400,000 IR72
Guangdong Early season Transplanting 22.5 1,000,000 IR72
Late season Transplanting 22.5 1,000,000 IR72
Sichuan Single season Transplanting 16 2,666,667 2You501
Guangxi Early season Transplanting 30 1,000,000 IR72
Middle season Transplanting 28.5 133,333 2You501
Late season Transplanting 27 1,000,000 IR72
Fujian Early season Transplanting 22.5 233,333 IR72
Middle season Transplanting 18 533,333 IR72
Late season Transplanting 19.5 233,333 IR72
Jiangsu Single season Transplanting 25.5 1,200,000 Wuxiangjing 9
Direct seeding 60 (I) 800,000 Wuxiangjing 9
Jilin Single season Transplanting 22.5 733,333 Jin Dao 305
Heilongjiang
Liaoning
Single season
Single season
Transplanting
Transplanting
24
22.5
2,600,000
666,667
Jin Dao 305
Jin Dao 305
Henan Single season Transplanting 20.5 633,333 XD90247
Zhejiang Early season Transplanting 30 93,333 IR72
Direct seeding 75 (I) 40,000 IR72
Middle season Transplanting 20 333,333 Wuxiangjing 9
Direct seeding 52.5 (I) 333,333 Wuxiangjing 9
Yunan
Late season
Single season (japonica)
Transplanting
Transplanting
22.5
55.5
200,000
600,000
IR72
Jin Dao 305
Single season (indica) Transplanting 55.5 333,333 2You501
Upland rice Direct seeding 75 (I) 100,000 HD297
Guizhou Single season Transplanting 15 733,333 2You725
Hainan Early season Transplanting 33 166,667 IR72
Late season Transplanting 33
*kg/ha, H=hybrid and I=inbred
213,333
29,146,667
IR72
Simulate rice Yp for each of these systems

Selected reference weather stations (RWS) and 100-km buffer
zones over geospatial distribution of harvested rice area.
Selected buffer zones account for 50% of total rice area in
China. Simulation with ORYZA2000,
Once selected, each RWS database undergoes rigorous Q/A vetting and gap
filling for missing data, then used in simulation model to estimate Yp

Wheat area density (green) and reference weather stations with
100 km buffers in Germany covering 74% of total harvested area
Collaboration with:
Kurt Christian Kersebaum
Inst. of Landscape Systems
Analysis, Muncheberg, Germany

Production-weighted yield potential (Yp) estimates based on current
crop management compared to average national yield (Ya), and
coverage of crop area included in Yp estimates.
Country Crop Total
harvested
area, Mha
China
USA
USA
Irrigated
rice
Rainfed
maize
Irrigated
maize
Germany Rainfed
wheat
% of total
area in Yp
estimate
Ya †
(year)
Yp
6.6
29.5 50%
8.8 75%
(2008)
28.7
3.6
3.2
52%
60%
10.1
(2009)
12.4
(2009)
13.2
15.1
8.1
74% 9.5
(2008)
† US data from USDA NASS, 2009; China rice and German wheat data from FAO, 2008.
Ya/Yp
(%)
77%
82%
85%

How high can average farm yields go?
• Best current estimate:
– 75-85% for irrigated crops
– 70-80% for rainfed crops
• Actual threshold depends on:
– Relative prices for outputs versus inputs
– Crop sensitivity to lodging, diseases and
insect pests, other stresses at high yield
levels, and probability of intense storms
• Rice more sensitive than maize (lower ceiling)
• Wheat varies: southern (India) > northern
(northern Europe)

Conclusions
• Crop yield potential (Yp) can be estimated
using methods that are transparent, robust,
and reproducible based on weather data,
geospatial distribution of crop area, current
crop management (plant date and maturity,
plant population) and appropriate crop models
• Average farm yields begin to stagnate when
they reach 70-85% of Yp
• Yield gap analysis depends on accurate
estimate of Yp

Need for Yield Potential--Yield Gap Atlas
• Interpret historical yield trends and yield
plateaus (predict yield plateaus?)
• Prioritize research to ensure global food
security in the face of climate change
– Identify areas with largest unexploited yield gaps,
identify constraints, close yield gaps through
ecological intensification
• Estimate agricultural land requirements and
indirect land use change (and associated
GHG emissions) as influenced by policies
– e.g. competition between food and biofuel