Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

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    We will mail you new results for this query: keywords==Yield potential
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Can yield variability be explained? Integrated assessment of maize yield gaps across smallholders in Ghana
Loon, Marloes P. van; Adjei-Nsiah, Samuel ; Descheemaeker, Katrien ; Akotsen-Mensah, Clement ; Dijk, Michiel van; Morley, Tom ; Ittersum, Martin K. van; Reidsma, Pytrik - \ 2019
Field Crops Research 236 (2019). - ISSN 0378-4290 - p. 132 - 144.
Crop experiments - Crop modelling - Farm household survey - Integrated assessment - Smallholder farms - Yield gaps - Yield potential

Agricultural production in Ghana should more than double to fulfil the estimated food demand in 2050, but this is a challenge as the productivity of food crops has been low, extremely variable and prone to stagnation. Yield gap estimations and explanations can help to identify the potential for intensification on existing agricultural land. However, to date most yield gap analyses had a disciplinary focus. The objective of this paper is to assess the impact of crop management, soil and household factors on maize (Zea mays) yields in two major maize growing regions in Ghana through an integrated approach. We applied a variety of complementary methods to study sites in the Brong Ahafo and Northern region. Farm household surveys, yield measurements and soil sampling were undertaken in 2015 and 2016. Water-limited potential yield (Y w ) was estimated with a crop growth simulation model, and two different on-farm demonstration experiments were carried out in 2016 and 2017. There is great potential to increase maize yields across the study sites. Estimated yield gaps ranged between 3.8 Mg ha −1 (67% of Y w ) and 13.6 Mg ha −1 (84% of Y w ). However, there was no consistency in factors affecting maize yield and yield gaps when using complementary methods. Demonstration experiments showed the potential of improved varieties, fertilizers and improved planting densities, with yields up to 9 Mg ha −1 . This was not confirmed in the analysis of the household surveys, as the large yield variation across years on the same farms impeded the disclosure of effects of management, soil and household factors. The low-input nature of the farming system and the incidence of fall armyworm led to relatively uniform and low yields across the entire population. So, farmers’ yields were determined by interacting, and strongly varying, household, soil and management factors. We found that for highly variable and complex smallholder farming systems there is a danger in drawing oversimplified conclusions based on results from a single methodological approach. Integrating household surveys, crop growth simulation modelling and demonstration experiments can add value to yield gap analysis. However, the challenge remains to improve upon this type of integrated assessment to be able to satisfactorily disentangle the interacting factors that can be managed by farmers in order to increase crop yields.

Cereal yield gaps across Europe
Schils, René ; Olesen, Jørgen E. ; Kersebaum, Kurt Christian ; Rijk, Bert ; Oberforster, Michael ; Kalyada, Valery ; Khitrykau, Maksim ; Gobin, Anne ; Kirchev, Hristofor ; Manolova, Vanya ; Manolov, Ivan ; Trnka, Mirek ; Hlavinka, Petr ; Paluoso, Taru ; Peltonen-Sainio, Pirjo ; Jauhiainen, Lauri ; Lorgeou, Josiane ; Marrou, Hélène ; Danalatos, Nikos ; Archontoulis, Sotirios ; Fodor, Nándor ; Spink, John ; Roggero, Pier Paolo ; Bassu, Simona ; Pulina, Antonio ; Seehusen, Till ; Uhlen, Anne Kjersti ; Żyłowska, Katarzyna ; Nieróbca, Anna ; Kozyra, Jerzy ; Silva, João Vasco ; Maçãs, Benvindo Martins ; Coutinho, José ; Ion, Viorel ; Takáč, Jozef ; Mínguez, M.I. ; Eckersten, Henrik ; Levy, Lilia ; Herrera, Juan Manuel ; Hiltbrunner, Jürg ; Kryvobok, Oleksii ; Kryvoshein, Oleksandr ; Boogaard, Hendrik ; Groot, Hugo de; Lesschen, Jan Peter ; Bussel, Lenny van; Wolf, Joost ; Zijlstra, Mink ; Loon, Marloes P. van; Ittersum, Martin K. van - \ 2018
European Journal of Agronomy 101 (2018). - ISSN 1161-0301 - p. 109 - 120.
Barley - Crop modelling - Grain maize - Nitrogen - Wheat - Yield potential

Europe accounts for around 20% of the global cereal production and is a net exporter of ca. 15% of that production. Increasing global demand for cereals justifies questions as to where and by how much Europe's production can be increased to meet future global market demands, and how much additional nitrogen (N) crops would require. The latter is important as environmental concern and legislation are equally important as production aims in Europe. Here, we used a country-by-country, bottom-up approach to establish statistical estimates of actual grain yield, and compare these to modelled estimates of potential yields for either irrigated or rainfed conditions. In this way, we identified the yield gaps and the opportunities for increased cereal production for wheat, barley and maize, which represent 90% of the cereals grown in Europe. The combined mean annual yield gap of wheat, barley, maize was 239 Mt, or 42% of the yield potential. The national yield gaps ranged between 10 and 70%, with small gaps in many north-western European countries, and large gaps in eastern and south-western Europe. Yield gaps for rainfed and irrigated maize were consistently lower than those of wheat and barley. If the yield gaps of maize, wheat and barley would be reduced from 42% to 20% of potential yields, this would increase annual cereal production by 128 Mt (39%). Potential for higher cereal production exists predominantly in Eastern Europe, and half of Europe's potential increase is located in Ukraine, Romania and Poland. Unlocking the identified potential for production growth requires a substantial increase of the crop N uptake of 4.8 Mt. Across Europe, the average N uptake gaps, to achieve 80% of the yield potential, were 87, 77 and 43 kg N ha−1 for wheat, barley and maize, respectively. Emphasis on increasing the N use efficiency is necessary to minimize the need for additional N inputs. Whether yield gap reduction is desirable and feasible is a matter of balancing Europe's role in global food security, farm economic objectives and environmental targets.

Prospect for increasing grain legume crop production in East Africa
Loon, Marloes P. van; Deng, Nanyan ; Grassini, Patricio ; Rattalino Edreira, Juan I. ; Wolde-meskel, Endalkachew ; Baijukya, Frederick ; Marrou, Hélène ; Ittersum, Martin K. van - \ 2018
European Journal of Agronomy 101 (2018). - ISSN 1161-0301 - p. 140 - 148.
Chickpea - Common bean - Cowpea - Food self-sufficiency - Groundnut - Legumes - Pigeonpea - Sub-Saharan Africa - Yield gap - Yield potential

Agricultural production in East Africa (E-Afr) has to increase drastically to meet future food demand. Yield gap assessment provides important information on the degree to which production can be increased on existing cropland. Most research on yield gap analysis has focussed on cereal crops, while legumes have received less attention despite of their relatively large area, and their importance as source of protein in smallholder farming systems in E-Afr. The objectives of this study were to (i) estimate water-limited yield potential (Yw) and yield gaps (Yg) for major grain legume crops in E-Afr, and (ii) estimate how narrowing the current legume Yg can contribute to food self-sufficiency by the year 2050. We focussed on Ethiopia, Kenya, and Tanzania, and five legumes crops including chickpea, common bean, cowpea, groundnut, and pigeonpea. A bottom-up approach which entails that local weather, soil and agronomic data was used as input for crop modelling (SSM-legumes) in a spatial framework, to estimate Yw, actual on-farm yield (Ya), and Yg from local to regional scale. Future legume self-sufficiency was assessed for 2050 demand assuming different Yg closure scenarios. On average, Ya was 25% of Yw across all legume-county combinations, being 15% for Kenya, 23% for Tanzania and 41% for Ethiopia. On average, common bean had the largest Yg of 2.6 Mg ha−1and chickpea the smallest (1.4 Mg ha−1). Closure of the exploitable Yg (i.e., 80% of Yw) can help to meet future legume demand in both Kenya and Tanzania, while it seems not to be sufficient in Ethiopia.

Can Bangladesh produce enough cereals to meet future demand?
Timsina, J. ; Wolf, J. ; Guilpart, N. ; Bussel, L.G.J. van; Grassini, P. ; Wart, J. van; Hossain, A. ; Rashid, H. ; Islam, S. ; Ittersum, M.K. van - \ 2018
Agricultural Systems 163 (2018). - ISSN 0308-521X - p. 36 - 44.
Cropland area - Food security - Land use change scenarios - Self-sufficiency ratio - Yield gap - Yield potential
Bangladesh faces huge challenges in achieving food security due to its high population, diet changes, and limited room for expanding cropland and cropping intensity. The objective of this study is to assess the degree to which Bangladesh can be self-sufficient in terms of domestic maize, rice and wheat production by the years 2030 and 2050 by closing the existing gap (Yg) between yield potential (Yp) and actual farm yield (Ya), accounting for possible changes in cropland area. Yield potential and yield gaps were calculated for the three crops using well-validated crop models and site-specific weather, management and soil data, and upscaled to the whole country. We assessed potential grain production in the years 2030 and 2050 for six land use change scenarios (general decrease in arable land; declining ground water tables in the north; cropping of fallow areas in the south; effect of sea level rise; increased cropping intensity; and larger share of cash crops) and three levels of Yg closure (1: no yield increase; 2: Yg closure at a level equivalent to 50% (50% Yg closure); 3: Yg closure to a level of 85% of Yp (irrigated crops) and 80% of water-limited yield potential or Yw (rainfed crops) (full Yg closure)). In addition, changes in demand with low and high population growth rates, and substitution of rice by maize in future diets were also examined. Total aggregated demand of the three cereals (in milled rice equivalents) in 2030 and 2050, based on the UN median population variant, is projected to be 21 and 24% higher than in 2010. Current Yg represent 50% (irrigated rice), 48-63% (rainfed rice), 49% (irrigated wheat), 40% (rainfed wheat), 46% (irrigated maize), and 44% (rainfed maize) of their Yp or Yw. With 50% Yg closure and for various land use changes, self-sufficiency ratio will be >. 1 for rice in 2030 and about one in 2050 but well below one for maize and wheat in both 2030 and 2050. With full Yg closure, self-sufficiency ratios will be well above one for rice and all three cereals jointly but below one for maize and wheat for all scenarios, except for the scenario with drastic decrease in boro rice area to allow for area expansion for cash crops. Full Yg closure of all cereals is needed to compensate for area decreases and demand increases, and then even some maize and large amounts of wheat imports will be required to satisfy demand in future. The results of this analysis have important implications for Bangladesh and other countries with high population growth rate, shrinking arable land due to rapid urbanization, and highly vulnerable to climate change.
Can increased leaf photosynthesis be converted into higher crop mass production? A simulation study for rice using the crop model GECROS
Yin, Xinyou ; Struik, Paul C. - \ 2017
Journal of Experimental Botany 68 (2017)9. - ISSN 0022-0957 - p. 2345 - 2360.
Crop modelling - Crop productivity - GECROS - Genetic transformation - Photosynthesis - Radiation use efficiency - Simulation - Water use efficiency - Yield potential

Various genetic engineering routes to enhance C3 leaf photosynthesis have been proposed to improve crop productivity. However, their potential contribution to crop productivity needs to be assessed under realistic field conditions. Using 31 year weather data, we ran the crop model GECROS for rice in tropical, subtropical, and temperate environments, to evaluate the following routes: (1) improving mesophyll conductance (gm); (2) improving Rubisco specificity (Sc/o); (3) improving both gm and Sc/o; (4) introducing C4 biochemistry; (5) introducing C4 Kranz anatomy that effectively minimizes CO2 leakage; (6) engineering the complete C4 mechanism; (7) engineering cyanobacterial bicarbonate transporters; (8) engineering a more elaborate cyanobacterial CO2-concentrating mechanism (CCM) with the carboxysome in the chloroplast; and (9) a mechanism that combines the low ATP cost of the cyanobacterial CCM and the high photosynthetic capacity per unit leaf nitrogen. All routes improved crop mass production, but benefits from Routes 1, 2, and 7 were ≤10%. Benefits were higher in the presence than in the absence of drought, and under the present climate than for the climate predicted for 2050. Simulated crop mass differences resulted not only from the increased canopy photosynthesis competence but also from changes in traits such as light interception and crop senescence. The route combinations gave larger effects than the sum of the effects of the single routes, but only Route 9 could bring an advantage of ≥50% under any environmental conditions. To supercharge crop productivity, exploring a combination of routes in improving the CCM, photosynthetic capacity, and quantum efficiency is required.

Resource use efficiencies as indicators of ecological sustainability in potato production : A South African case study
Steyn, J.M. ; Franke, A.C. ; Waals, J.E. van der; Haverkort, A.J. - \ 2016
Field Crops Research 199 (2016). - ISSN 0378-4290 - p. 136 - 149.
Agricultural input - Agro-ecological zones - Carbon footprint - Competitiveness - Crop model - Yield gap analysis - Yield potential

Potato, the most important vegetable crop in South Africa, is produced in many distinct geographical regions differing in climate, soils, production seasons and management practices and access to markets. These differences affect the amount of input resources required to produce potatoes as well as yields and crop value, and therefore the use efficiencies of land, water, nutrients, seed and energy. Resource use efficiencies affect the ecological and financial sustainability of potato production in this region, which has in general less favourable potato growing conditions than north-western Europe and the U.S.A., where high resource use efficiencies are usually recorded. This study aimed to assess and benchmark South African potato production regions, representing a wide range of growing conditions, regarding their use of input resources and to identify resource-intensive practices, which may suggest inefficient use of inputs. Surveys were conducted in 2013 and 2014 by interviewing growers in all production regions, to provide data on resource use efficiencies. Quantitative modelling approaches were applied to calculate carbon footprints as a proxy of energy use efficiency, potential crop yields and irrigation needs for each region. Variability in the gap between potential and actual yield was used to identify yield limiting factors. Actual yields achieved were on average 60% of the potential yield, suggesting fairly efficient use of available production factors. Water, seed and nutrient use efficiencies differed widely between and within regions and were not directly proportional to water requirements and yields achieved. Fertilizers (34%) and irrigation (30%) were the greatest contributors to energy use in potato crop production. Energy required to pump water was strongly related to the amount of irrigation applied, pumping depth and distance. Long distance travel of produce to retail points contributed substantially to energy use. Significant improvements in efficiencies are possible by improving management practices. Analysis of the variability in resource use efficiencies between farms and regions provided production sustainability indicators that can assist growers in identifying inefficient practices and yield limiting factors. These can be addressed through the use of decision support systems, such as irrigation scheduling tools, to improve resource use efficiencies and the sustainability of production, not only for the production efficiency of the specific study area, but also for the economic efficiency of potato production anywhere else.

Geostatistical interpolation and aggregation of crop growth model outputs
Steinbuch, Luc ; Brus, Dick J. ; Bussel, Lenny G.J. van; Heuvelink, Gerard B.M. - \ 2016
European Journal of Agronomy 77 (2016). - ISSN 1161-0301 - p. 111 - 121.
Geostatistics - Spatial aggregation - Spatial prediction - Uncertainty - Yield gap - Yield potential

Many crop growth models require daily meteorological data. Consequently, model simulations can be obtained only at a limited number of locations, i.e. at weather stations with long-term records of daily data. To estimate the potential crop production at country level, we present in this study a geostatistical approach for spatial interpolation and aggregation of crop growth model outputs. As case study, we interpolated, simulated and aggregated crop growth model outputs of sorghum and millet in West-Africa. We used crop growth model outputs to calibrate a linear regression model using environmental covariates as predictors. The spatial regression residuals were investigated for spatial correlation. The linear regression model and the spatial correlation of residuals together were used to predict theoretical crop yield at all locations using kriging with external drift. A spatial standard deviation comes along with this prediction, indicating the uncertainty of the prediction. In combination with land use data and country borders, we summed the crop yield predictions to determine an area total. With spatial stochastic simulation, we estimated the uncertainty of that total production potential as well as the spatial cumulative distribution function. We compared our results with the prevailing agro-ecological Climate Zones approach used for spatial aggregation. Linear regression could explain up to 70% of the spatial variation of the yield. In three out of four cases the regression residuals showed spatial correlation. The potential crop production per country according to the Climate Zones approach was in all countries and cases except one within the 95% prediction interval as obtained after yield aggregation. We concluded that the geostatistical approach can estimate a country's crop production, including a quantification of uncertainty. In addition, we stress the importance of the use of geostatistics to create tools for crop modelling scientists to explore relationships between yields and spatial environmental variables and to assist policy makers with tangible results on yield gaps at multiple levels of spatial aggregation.

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