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    The file was developed to assess the performance of a novel bamboo-drip irrigation system in laboratory and in field conditions, in South-west Benin. The assessment was conducted in terms of hydraulics, uniformity, yield, water productivity and soil-water management.

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    Using the methodology developed by Graw and Husmann (2014), the map overlays three indicators (high agricultural potential, high poverty mass and high yield gaps) to identify areas with high potential for agricultural development and poverty reduction in Kenya. Data sources and thresholds: Agricultural potential: Suitability of currently available land area for rainfed crops, using maximising crop and technology mix, FGGD map 6.61 (2005), High: top 3 suitability classes (medium high, high and very high) Poverty mass: Number of poor people in Kenya (by district), KIHBS (2005/06), High: >300,000 per district Yield gap: Yield gap for a combination of major crops, FAO/IIASA - GAEZ (2000/05), High: < 0.25 (on a scale from 0-1, with the highest value in Kenya ca. 0.44) District boundaries: Kenya Central Bureau of Statistics (2003)

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    The table includes annual data of yield and production of Maize and Cassava at Regional (Ashanti and Brong-Ahafo) and site specific (Kumasi, Ejura, Dorma Ahenko, Nkoranza, Techiman) level.

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    Agronomic Radiation Use Efficiency (RUE) for maize stover biomass across the Ethiopia has been estimated under unfertilized conditions and under two different fertilizer application rates using crop model LINTUL5 embedded into the modeling framework SIMPLACE (Scientific Impact Assessment and Modelling Platform for Advanced Crop and Ecosystem Management.

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    The yield gap for maize across the Ethiopia has been estimated using crop model LINTUL5 embedded into the modeling framework SIMPLACE (Scientific Impact Assessment and Modelling Platform for Advanced Crop and Ecosystem Management. The yield gap of a crop grown in a certain location and cropping system is defined as the difference between the yield and biomass under optimum management and the average yield achieved by farmers. Yield under optimum management is labeled as potential yield (Yp) under irrigated conditions or water-limited potential yield (Yw) under rain-fed conditions.Yp is location specific because of the climate, and not dependent on soil properties assuming that the required water and nutrients are non-limiting and can be added through management. Thus, in areas without major soil constraints, Yp is the most relevant benchmark for irrigated systems. Whereas, for rain-fed crops, Yw, equivalent to water-limited potential yield, is the most relevant benchmark. Both Yp and Yw are calculated for optimum planting dates, planting density and region-specific crop variety which is critical in determining the feasible growth duration, particularly in tropical climatic conditions where two or even three crops are produced each year on the same field.

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    The table includes annual data of yield and production of cereals and pulses at National and Regional (Amhara and Oromia) level.

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    The yield gap for maize in two regions (Ashanti Region and Brong-Ahafo region) in Ghana has been estimated using crop model LINTUL5 embedded into the modeling framework SIMPLACE (Scientific Impact Assessment and Modelling Platform for Advanced Crop and Ecosystem Management. The yield gap of a crop grown in a certain location and cropping system is defined as the difference between the yield and biomass under optimum management and the average yield achieved by farmers. Yield under optimum management is labeled as potential yield (Yp) under irrigated conditions or water-limited potential yield (Yw) under rain-fed conditions.Yp is location specific because of the climate, and not dependent on soil properties assuming that the required water and nutrients are non-limiting and can be added through management. Thus, in areas without major soil constraints, Yp is the most relevant benchmark for irrigated systems. Whereas, for rain-fed crops, Yw, equivalent to water-limited potential yield, is the most relevant benchmark. Both Yp and Yw are calculated for optimum planting dates, planting density and region-specific crop variety which is critical in determining the feasible growth duration, particularly in tropical climatic conditions where two or even three crops are produced each year on the same field.

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    Overlay of medium, high and very high agricultural potential and yield gaps for Bangladesh. Indicators: Suitability of land area for rainfed crops: FGGD map 6.60, classes: medium to very high Yield Gaps: FAO/IIASA - GAEZ < 0.5 The here presented simple analysis should give insights in potential suitable areas for expecting high yields. Yield gap information for Bangladesh further showed were gaps for production occur. By resampling the statistical data into a raster dataset an overlap with suitability information based on sateliite imagery was possible. The overlay was processed in ArcGIS classifying those areas where yield gaps occur with suitability areas as defined by the dataset cited above. Yield gaps can be found in the southern part of Bangladesh. More intersting are the dark green areas where according to satellite information high potential areas are located but not as many yields are produced. Here, more detailed analysis might be useful.

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    The data was collected for doctoral research on sustainable agricultural sustainability in Ntcheu district of Malawi. The data was collected from 238 farming households and from their 450 plots. Data includes livelihood assets, agronomic practices and productivity. A Land productivity potential was estimated using soil fertility and topography. Soil data was extracted from digital soil map by Mponela P., Snapp S., Villamor G. B., Tamene L. D., Le Q. B., & Borgemeister C. (2020). Digital soil mapping of nitrogen, phosphorus, potassium, organic carbon and their crop response thresholds in smallholder managed escarpments of Malawi. Applied Geography. The topographic layers were extracted the STRM-DEM 30m resolution. The data is used in the thesis to estimate the impact of agricultural subsidy policy on farmer behaviour, productivity and nutrient balances and simulations of alternative subsidy policies are projected for the 20-year period from 2017.

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    Water Use Efficiency (RUE) for maize grain yield across the Ethiopia has been estimated under fertilized conditions using crop model LINTUL5 embedded into the modeling framework SIMPLACE (Scientific Impact Assessment and Modelling Platform for Advanced Crop and Ecosystem Management.