Global Yield Gap Atlas – an agronomic

database with local and global relevance

Martin van Ittersum – Plant Production Systems group

Questions of this symposium

Should and could agricultural production be increased at the global scale?

Where should agricultural productivity be increased?

What are the existing limiting factors for increasing agricultural production?

Which intensification pathways could and should be adopted?

These questions require agronomic rigour!

2

3

FAO projection: +60% demand (2007-2050)

Tilman et al.: +100-110% crop yields

Tilman et al., 2011 (PNAS)

5

Five reasons why +60-110% by 2050 must be revisited

FAO projection expressed in monetary value

Baseline (2005-2010) is 10 years old

Projections on drivers of demand (population and economic growth) need continuous update

Demand increases => production increases?

Projections are for the globe, but with huge regional differences

See also: Hunter et al., 2017. Bioscience.

Population increase

6

Continent 2015 2050 2100

World 7.4 9.7 11.2

Asia 4.4 5.3 4.9

Africa 1.2 2.5 4.4

Sub-Saharan Africa 1.0 2.1 3.9

North America 0.4 0.4 0.5

Latin America 0.6 0.8 0.7

Europe 0.7 0.7 0.7

Oceania 0.04 0.06 0.07

United Nations, 2017

Meaning of increased global demand is region-specific!

Two extremes:

Sub-Saharan Africa’s demand will rise fastest because of population growth and dietary change => tripling production

Europe can (should?) play a leading role in developing circular food systems

Questions of this symposium

Should and could agricultural production be increased at the global scale?

Where should agricultural productivity be increased?

What are the existing limiting factors for increasing agricultural production?

Which intensification pathways could and should be adopted?

These questions require agronomic rigour!

8

Motivation to start Global Yield Gap Atlas

1. Estimates of extra crop production potential in existing farmland and with available water resources

2. Support to prioritize investment in agricultural research and development and monitor impact

3. Foundation for narrowing yield gaps, estimate nutrient and water requirements, and for studies on climate change, land use, and environmental footprint

4. Platform to integrate biophysical and socio-economic factors

5. To develop a global database with agronomic rigour!

Global Yield Gap Atlas

Major food crops in the world

Global protocol with local application

Local data and evaluation

Strong agronomic foundation

Co-financed by Bill and Melinda Gates Foundation

www.yieldgap.org

With University of Nebraska, ICRISAT, AfricaRice, CIMMYT and many national partners

62 countries, major food crops, accounting for 70, 84, 45% of rice, maize, and wheat

Yield potential, farm yield, and yield gaps

Modified from: van Ittersum and Rabbinge, Field Crops Research (1997)

* Reaching 75-85% of yield potential is a reasonable target for farmers with access to inputs, markets, and extension services. * Further yield increase is not cost-effective and/or environmentally sound.

Cro

p g

rain

yie

ld (

t/h

a/ye

ar)

Yield Potential Farm yield

Yield gap*

Determined by:

Radiation

Temperature

[CO2]

Cultivar

Rainfall & soil (in rainfed crops)

Limited by:

Poor Fertility

Poor management

Insects, weeds diseases

Global Yield Gap Atlas (www.yieldgap.org)Global Yield Gap Atlas (www.yieldgap.org)

Broad usage in 2017 : 30,000 users of website; 230,000 page-views; 4,500 downloads

Sector Downloads

NGO’s/Foundations 333

Industry 235

Academia 2089

Government 452

Media 12

Individual (producer, consultant, extension)

2000

www.yieldgap.orgSchils et al., 2018

14www.yieldgap.org

www.yieldgap.org

Questions of this symposium

Should and could agricultural production be increased at the global scale?

Where should agricultural productivity be increased?

What are the existing limiting factors for increasing agricultural production?

Which intensification pathways could and should be adopted?

These questions require agronomic rigour!

16

Contribute to food security analysis

17

Van Ittersum et al., 2016. PNAS

Growth in population and cereal demand - 2050

A factor 3.4 increase!

Van Ittersum et al., 2016 (PNAS)

www.yieldgap.org

Can SSA feed itself? - cereals

Van Ittersum et al., 2016. PNAS

Required trend change maize yields

Questions of this symposium

Should and could agricultural production be increased at the global scale?

Where should agricultural productivity be increased?

What are the existing limiting factors for increasing agricultural production?

Which intensification pathways could and should be adopted?

These questions require agronomic rigour!

22

Actual and potential water productivity – rainfed maize

23

www.yieldgap.org

Water productivity gaps (rainfed conditions)

Water or non-water limiting factors?

25Rattalino Edreira, Guilpart, Sadras, Cassman, Van Ittersum, Schils, Grassini,Agricultural and Forest Meteorology, 2018

Estimating nutrient requirements - maize

50% Yw80% Yw

Ten Berge, De Vries, Van Loon, Hijbeek, Rattallino

Edreira and Van Ittersum, 2018 (In review)

www.yieldgap.org

Questions of this symposium

Should and could agricultural production be increased at the global scale?

Where should agricultural productivity be increased?

What are the existing limiting factors for increasing agricultural production?

Which intensification pathways could and should be adopted?

These questions require agronomic rigour!

27

Win

ter

wh

eat

yie

ld (

ton

ha-1

)

Crop inputs (x)

YHFResourceyield gap

YTEx Efficiencyyield gap

Actual yield

Ya

Yp Technologyyield gap

Decomposing yield gaps

Silva et al., 2017. Eur. J. of Agron.

Three contrasting case studies

Mixed farming in

Southern Ethiopia

Rice farming in Central

Luzon, Philippines

Arable farming in

the Netherlands

Sample: 200 farms

Year: 2012

Farm size: < 2.5 ha

Crops: Maize in Hawassa

and wheat in Asella

Sample: 100 farms

Year: 1966-2012

Farm size: 1.7 ha

Crops: Rice (wet season

and dry season)

Sample: 175 farms

Year: 2008 - 2012

Farm size: ~60 ha

Crops: Wheat, barley,

potato, sugar beet, onion

Silva et al., in preparation

The Netherlands

Small yield gap due to efficiency

and technology gaps.

Southern Ethiopia

Large yield gap due to efficiency

and technology yield gaps.

Central Luzon, Philippines

Medium yield gap due to efficiency,

resource and technology yield gaps.

Overview of crop yield gaps

Silva et al., 2017. Eur. J. of Agron.

Silva et al., 2017. Ag. Systems

Interventions to narrow yield gap(s)

31

Technical efficiency yield gap

Yield (tons/ha)

• Suboptimal crop management caused by knowledge, skills and information gaps.

• Knowledge and financial constraints, risk issues and information asymmetries

AllocativeYield gap

EconomicYield gap

TechnologyYield gap

• Transaction and transportation costs

• Agricultural innovation system and broader institutional, technological, economic and social factors

Actual yield

Potential yield

Feasible yield

Economic yield

Technical

efficient yield

Yieldgap

Main causes Policies

• Improve extension services• Stimulate knowledge transfer

from best practice to average farmers

• Credit & insurance• Expand agro-dealer networks• Support market information• Land tenure systems• Smart input subsidies

• Investment in rural roads• Policies to decrease

transaction costs

• Investment in applied agricultural research and development programs

Sliva et al., 2017

Van Dijk et al., 2017

© http://www.riennijboer.nl/

Thank you for your attention!

Future harvest

Merci to MAK!IT

GYGA References van Ittersum MK, Cassman KG, Grassini P, Wolf J, Tittonell P, Hochman Z. 2013. Yield gap analysis with local to global relevance – a review. Field

Crops Res. 143:4-17 van Bussel LGJ, Grassini P, Van Wart J, Wolf J, Claessens L, Yang H, Boogaard H, de Groot H, Saito K, Cassman KG, van Ittersum MK, 2015. From field

to atlas: Upscaling of location-specific yield gap estimates. Field Crops Res. 177, 98-108 Van Wart J, Grassini P, Yang HS, Claessens L, Jarvis A, Cassman KG, 2015. Creating long-term weather data from thin air for crop simulation

modelling. Agric. Forest Meteoro. 208, 49-58 Van Wart J, van Bussel LGJ, Wolf J, Licker R, Grassini P, Nelson A, Boogaard H, Gerber J, Mueller ND, Claessens L, Cassman KG, van Ittersum MK.

2013. Reviewing the use of agro-climatic zones to upscale simulated crop yield potential. Field Crops Res. 143, 44-55 Grassini P, van Bussel LGJ, Van Wart J, Wolf J, Claessens L, Yang H, Boogaard H, de Groot H, van Ittersum MK, Cassman KG, 2015. How good is good

enough? Data requirements for reliable crop yield simulations and yield-gap analysis. Field Crops Res. 177, 49-63 J. Wolf, K. Ouattara, I. Supit, 2015. Sowing rules for estimating rainfed yield potential of sorghum and maize in Burkina Faso. Agricultural and Forest

Meteorology, 214, 208-218 van Oort PAJ, Saito K, Tanaka A, Amovin-Assagba E , Van Bussel LGJ , van Wart J, de Groot H , van Ittersum MK, Cassman KG, Wopereis, MCS. 2014.

Assessment of rice self-sufficiency in 2015 in eight African countries. Global Food Security 5, 39-49. Gobett D, Hochman Z, Horan H, Navarro-Garcia J, Grassini P, Cassman KG, 2016. Yield gap analysis of rainfed wheat demonstrates local to global

relevance. Journal of Agric. Sci. (Cambridge) 1-18. Marin F, Martha G, Cassman KG, Grassini P., 2016. Prospects for increasing sugarcane and bioethanol production on existing crop area in Brazil.

BioScience 66, 307-316 Aramburu Merlos F., Monzon JP, Mercau JL, Taboada, M, Andrade, FH, Hall AJ, Jobbagy E, Cassman KG, Grassini P, 2015. Potential for crop

production increase in Argentina through closure of existing yield gaps. Field Crops Res. 184, 145-154. Van Ittersum MK, van Bussel LGJ, Wolf J, Grassini P., et al. 2016. Can Sub-Saharan Africa feed itself? PNAS 113, 14964-14969 van Oort PAJ, Saito K, Dieng I, Grassini P, Cassman KG, van Ittersum MK. 2016. Can yield gap analysis be used to inform R&D prioritisation? Global

Food Security (In Press). Timsina J, Wolf J, Guilpart N, van Bussel LGJ, Grassini P, van Wart J, Hossain A, Rashid H, Islam S, van Ittersum MK (2016) Can Bangladesh produce

enough cereals to meet future demand? Agric Syst (In Press) Espe MB, Cassman KG, Yang H, Guilpart N, Van Wart J, Grassini P, Anders M, Beighley D, Harrell D, Linscombe S, McKenzie K, Mutters R, Wilson T,

Linquist BA (2016) Yield gap analysis of US rice production systems shows opportunities for improvement. Field Crops Res. 196, 276-283. Schils, R., Olesen, J.E., Kersebaum, K.-C., Rijk, B., Oberforster, M., Kalyada, V., Khitrykau, M., Gobin, A., Kirchev, H., Manolova, V., Manolov, I., Trnka,

M., Hlavinka, P., Paluoso, T., Peltonen-Sainio, P., Jauhiainen, L., Lorgeou, J., Marrou, H., Danalatos, N., Archontoulis, S., Fodor, N., Spink, J., Roggero, P.P., Bassu, S., Pulina, A., Seehusen, T., Uhlen, A.K., Żyłowska, K., Nieróbca, A., Kozyra, J., Silva, J.V., Maçãs, B.M., Coutinho, J., Ion, V., Takáč, J., Mínguez, M.I., Eckersten, H., Levy, L., Herrera, J.M., Hiltbrunner, J., Kryvobok, O., Kryvoshein, O., Sylvester-Bradley, R., Kindred, D., Topp, C.F.E., Boogaard, H., de Groot, H., Lesschen, J.P., van Bussel, L., Wolf, J., Zijlstra, M., van Loon, M.P., van Ittersum, M.K., 2018. Cereal yield gaps across Europe. European Journal of Agronomy 101, 109-120.

Rattalino Edreira, J.I., Guilpart, N., Sadras, V., Cassman, K.G., van Ittersum, M.K., Schils, R.L.M., Grassini, P., 2018. Water productivity of rainfedmaize and wheat: A local to global perspective. Agricultural and Forest Meteorology 259, 364-373.

Rattalino Edreira, J.I., Kenneth G Cassman, Zvi Hochman, Martin K van Ittersum, Lenny G.J. van Bussel, Lieven Claessens, Patricio Grassini. Beyond the plot: accelerating innovation in agronomic science. Environmental Research Letters 13, 10.1088/1748-9326/aac092.

References on understanding yield gaps

• Silva, J.V.; Reidsma, P.; Laborte, A.G; van Ittersum, M.K. 2017a. Explaining rice yields and yield gaps in

Central Luzon, Philippines: An application of stochastic frontier analysis and crop modelling. European

Journal of Agronomy, 82 Part B, 223 – 241.

• Silva, J.V.; Reidsma, P.; Velasco, M.L.; Laborte, A.G.; van Ittersum, M.K. 2018. Intensification of rice-based

farming systems in Central Luzon, Philippines: Constraints at field, farm and regional levels. Agricultural

Systems, 165, 55 – 70.

• Silva, J.V.; Reidsma, P.; van Ittersum, M.K. 2017b. Yield gaps in Dutch arable farming: Analysis at crop and

crop rotation level. Agricultural Systems, 158, 78 – 92.

• Silva, J.V.; Baudron, F.; Reidsma, P.; Giller, K.E. Is labour a major determinant of yield gaps in sub-Saharan

Africa? A study for cereal-based production systems in Southern Ethiopia. Under Review, Agricultural

Systems.

• Wang, N., Reidsma, P., Pronk, A.A., de Wit, A.J.W., van Ittersum, M.K., 2018. Can potato add to China's

food self-sufficiency? The scope for increasing potato production in China. European Journal of Agronomy

101, 20-29.