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Providing food and water security for a population expected to exceed 9 billion by 2050 while conserving natural resources requires achieving high yields on every hectare of currently used arable land suitable for intensification. This is especially relevant for sub-Saharan Africa (SSA), where, u...


Claessens, LievenCassman, Kenneth G.Wart, Justin vanGrassini, PatricioVanlauwe, BernardIttersum, Martin K. vanBussel, Lenny G. J. vanBoogaard, H.Stoorvogel, J.J.Wolf, JoostYang, Haishun[Soil data for yield gap assessment and soil suitability index for sustainable intensification]Soil data for yield gap assessment and soil suitability index for sustainable intensification

Providing food and water security for a population expected to exceed 9 billion by 2050 while conserving natural resources requires achieving high(er) and stable yields on every hectare of currently used arable land suitable for intensification.


Claessens, LievenVanlauwe, BernardCassman, Kenneth G.Wart, Justin vanGrassini, PatricioYang, HaishunIttersum, Martin K. vanBussel, Lenny G. J. vanWolf, JoostBoogaard, H.Groot, Hugo deStoorvogel, J.J.[Soil suitability for sustainable intensification in smallholder systems in Sub-Saharan Africa]Soil suitability for sustainable intensification in smallholder systems in Sub-Saharan Africa

Numerous studies have been published during the past two decades that use simulation models to assess crop yield gaps (quantified as the difference between potential and actual farm yields), impact of climate change on future crop yields, and land-use change. However, there is a wide range in qua...


Grassini, PatricioBussel, Lenny G. J. vanWart, Justin vanWolf, JoostClaessens, LievenYang, HaishunBoogaard, H.Groot, Hugo deIttersum, Martin K. vanCassman, Kenneth G.[How good is good enough? Data requirements for reliable crop yield simulations and yield-gap analysis]How good is good enough? Data requirements for reliable crop yield simulations and yield-gap analysis

Accurate estimation of yield gaps is only possible for locations where high quality local data are available, which are, however, lacking in many regions of the world. The challenge is how yield gap estimates based on location-specific input data can be used to obtain yield gap estimates for larg...


Bussel, Lenny G. J. vanGrassini, PatricioWart, Justin vanWolf, JoostClaessens, LievenYang, HaishunBoogaard, H.Groot, Hugo deSaito, KazukiCassman, Kenneth G.Ittersum, Martin K. van[From field to atlas: Upscaling of location-specific yield gap estimates]From field to atlas: Upscaling of location-specific yield gap estimates

Yield gap analysis, which evaluates magnitude and variability of difference between crop yield potential (Yp) or water limited yield potential (Yw) and actual farm yields, provides a measure of untapped food production capacity. Reliable location-specific estimates of yield gaps, either derived f...


Wart, Justin vanBussel, Lenny G. J. vanWolf, JoostLicker RGrassini, PatricioNelson, A.Boogaard, H.Gerber JMueller NDClaessens, LievenIttersum, Martin K. vanCassman, Kenneth G.[Use of agro-climatic zones to upscale simulated crop yield potential]Use of agro-climatic zones to upscale simulated crop yield potential

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