Research

Adaptation strategies strongly reduce the future impacts of climate change on simulated crop yields. Abramoff (2023). Earth’s Future, Vol. 11.
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Diagnosis of the productivity gap using a crop model. Methodology and case study of small-scale maize production in Central Brazil. Affholder (2003). Agronomie, Vol. 23, pp. 305.
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The yield gap of major food crops in family agriculture in the tropics: assessment and analysis through field surveys and modelling. Affholder (2013). Field Crop Res., Vol. 143, pp. 106.
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Comparison of penman-monteith and priestley-Taylor evapotranspiration methods for crop modeling in Oklahoma. Akumaga (2019). Agron. J., Vol. 111, pp. 1171.
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Comparison of methods for estimating ref-et. Amatya (1995). J. Irrig. Drain. Eng., Vol. 121, pp. 427.
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Comparison of hydrological and vegetation remote sensing datasets as proxies for rainfed maize yield in Malawi. Anghileri (2022). Agric. Water Manag., Vol. 262.
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Achieving food security and industrial development in Malawi: are export restrictions the solution?. Aragie (2018). World Dev., Vol. 108, pp. 1.
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Evaluating deficit irrigation management strategies for grain sorghum using AquaCrop. Araya (2016). Irrig. Sci., Vol. 34, pp. 465.
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Effects of farmers’ seed source on maize seed quality and crop productivity. Asiedu (2007). Ghana J. Agricult. Sci., Vol. 40, pp. 105.

Unravelling the variability and causes of smallholder maize yield gaps in Ethiopia. Assefa (2020). Food Secur., Vol. 12, pp. 83.
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The number of subjects per variable required in linear regression analyses. Austin (2015). J. Clin. Epidemiol., Vol. 68, pp. 627.
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The politics of hunger in an sdg era: food policy in Malawi. Banik (2019). Food Ethics, Vol. 4, pp. 189.
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Evaluating AquaCrop model for simulating production of amaranthus (amaranthus cruentus) a leafy vegetable, under irrigation and rainfed conditions. Bello (2017). Agric. For. Meteorol., Vol. 247, pp. 300.
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Thinking beyond agronomic yield gap: smallholder farm efficiency under contrasted livelihood strategies in Malawi. Berre (2017). Field Crop Res., Vol. 214, pp. 113.
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Economic efficiency of mixed crop-livestock production system in the north eastern highlands of Ethiopia: the stochastic frontier approach. Beshir (2012). J. Agricult. Econ. Develop., Vol. 1, pp. 10.

Review of yield gap explaining factors and opportunities for alternative data collection approaches. Beza (2017). Eur. J. Agron., Vol. 82, pp. 206.
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Diversity of sources of income for smallholder farming communities in Malawi: importance for improved livelihood. Bhatti (2021). Sustainability, Vol. 13.
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Modelling climate change impacts on and adaptation strategies for agriculture in Sardinia and Tunisia using AquaCrop and value-at-risk. Bird (2016). Sci. Total Environ., Vol. 543, pp. 1019.
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Satellite-based vegetation health indices as a criteria for insuring against drought-related yield losses. Bokusheva (2016). Agric. For. Meteorol., Vol. 220, pp. 200.
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Potential uses and limitations of crop models. Boote (1996). Agron. J., Vol. 88, pp. 704.
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Putting mechanisms into crop production models. Boote (2013). Plant Cell Environ., Vol. 36, pp. 1658.
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Disparate access to quality land and fertilizers explain Malawi’s gender yield gap. Burke (2021). Food Policy, Vol. 100.
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Social capital typologies and sustainable development: spatial patterns in the central and southern regions of Malawi. Craig (2022). Sustainability, Vol. 14.
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Bonding, bridging and linking social capital combinations for food access; a gendered case study exploring temporal differences in southern Malawi. Craig (2023). J. Rural. Stud., Vol. 101.
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Validation of the CHIRPS satellite rainfall estimates over eastern Africa. Dinku (2018). Q. J. R. Meteorol. Soc., Vol. 144, pp. 292.
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A diagnostic method for assessing regional variations in crop yield. Doré (1997). Agric. Syst., Vol. 54, pp. 169.
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Methodological progress in on-farm regional agronomic diagnosis. a review. Doré (2008). Agron. Sustain. Dev., Vol. 28, pp. 151.
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The Malawi agricultural input subsidy programme: 2005/06 to 2008/09. Dorward (2011). Int. J. Agric. Sustain., Vol. 9, pp. 232.
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Yield gap-based poverty gaps in rural Sub-Saharan Africa. Dzanku (2015). World Dev., Vol. 67, pp. 336.
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Regional overview of food security and nutrition 2021, Africa statistics and trends. FAO, ACA, AUC (2021). .

AquaCrop-OS: an open source version of FAO’s crop water productivity model. Foster (2017). Agric. Water Manag., Vol. 181, pp. 18.
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Calibration of the ceres–maize model for simulating site–specific crop development and yield on claypan soils. Fraisse (2001). Appl. Eng. Agric., Vol. 17.
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Drivers of household food availability in sub-saharan africa based on big data from small farms. Frelat (2016). Proc. Natl. Acad. Sci., Vol. 113, pp. 458.
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The climate hazards infrared precipitation with stations - a new environmental record for monitoring extremes. Funk (2015). Sci. Data, Vol. 2.
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Potential of deficit and supplemental irrigation under climate variability in northern Togo, west africa. Gadédjisso-Tossou (2018). Water, Vol. 10.
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Impact of irrigation strategies on maize (zea mays l.) production in the savannah region of northern Togo (west africa). Gadédjisso-Tossou (2020). WaterSA, Vol. 46.

Evaluation of multiple climate data sources for managing environmental resources in East Africa. Gebrechorkos (2018). Hydrol. Earth Syst. Sci., Vol. 22, pp. 4547.
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How good is good enough? Data requirements for reliable crop yield simulations and yield-gap analysis. Grassini (2015). Field Crop Res., Vol. 177, pp. 49.
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Food insecurity, poverty and the Malawian starter pack: fresh start or false start?. Harrigan (2008). Food Policy, Vol. 33, pp. 237.
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Validating the FAO AquaCrop model for irrigated and water deficient field maize. Heng (2009). Agron. J., Vol. 101, pp. 488.
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SoilGrids250m: global gridded soil information based on machine learning. Hengl (2017). PLoS One, Vol. 12.
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Addressing the Yield Gap in Sub-Saharan Africa. Hillocks (2014). Vol. 43, pp. 85.

Nitrogen management in crop rotations after the break-up of grassland: insights from modelling. Hoffmann (2018). Agric. Ecosyst. Environ., Vol. 259, pp. 28.
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Data for model operation, calibration, and evaluation. Hunt (1998). pp. 9.

Evaluation of the AquaCrop model for winter wheat under different irrigation optimization strategies at the downstream Kabul River basin of Afghanistan. Jalil (2020). Agric. Water Manag., Vol. 240.
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Lessons from the aftermaths of green revolution on food system and health. John (2021). Front. Sustain. Food Syst., Vol. 5.
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Brief history of agricultural systems modeling. Jones (2017). Agric. Syst., Vol. 155, pp. 240.
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Evaluating the impact of improved maize varieties on food security in Rural Tanzania: evidence from a continuous treatment approach. Kassie (2014). Food Secur., Vol. 6, pp. 217.
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Plot size and maize productivity in Zambia: is there an inverse relationship?. Kimhi (2006). Agric. Econ., Vol. 35, pp. 1.
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Effect of changes in population density and crop productivity on farm households in Malawi. Komarek (2019). Agric. Econ., Vol. 50, pp. 615.
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Recent changes in cropland area and productivity indicate unsustainable cropland expansion in Malawi. Li (2021). Environ. Res. Lett., Vol. 16.
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Maize yield estimation in intercropped smallholder fields using satellite data in southern Malawi. Li (2022). Remote Sens., Vol. 14, pp. 2458.
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Limited environmental and yield benefits of intercropping practices in smallholder fields: evidence from multi-source data. Li (2023). Field Crop Res., Vol. 299.
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Modelling climate change impact: a case of bambara groundnut (Vigna subterranea). Mabhaudhi (2018). Phys. Chem. Earth, Parts A/B/C, Vol. 105, pp. 25.
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Mixing process-based and data-driven approaches in yield prediction. Maestrini (2022). Eur. J. Agron., Vol. 139.
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Subsidizing improved legume seeds for increased household dietary diversity: evidence from Malawi’s farm input subsidy programme with implications for addressing malnutrition in all its forms. Matita (2022). Food Policy, Vol. 113, pp. 102309.
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Operational limits to the priestley-Taylor formula. McAneney (1996). Irrig. Sci., Vol. 17, pp. 37.
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Challenges and opportunities for raising agricultural productivity in Malawi. Mthakati (2012). Int. J. Agric. For., Vol. 2, pp. 210.

Closing yield gaps through nutrient and water management. Mueller (2012). Nature, Vol. 490, pp. 254.
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Assessing impacts of seasonal climate variability on maize yield in Kenya. Mumo (2018). Int. J. Plant Prod., Vol. 12, pp. 297.
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Evaluation of spatial and temporal characteristics of rainfall in Malawi: a case of data scarce region. Ngongondo (2011). Theor. Appl. Climatol., Vol. 106, pp. 79.
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Pathway to achieving sustainable food security in sub-saharan africa: the role of agricultural mechanization. Olasehinde-Williams (2020). J. Labor Soc., Vol. 23, pp. 349.
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The impact of agricultural extension on farm production in resettlement areas of Zimbabwe. Owens (2003). Econ. Dev. Cult. Chang., Vol. 51, pp. 337.
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Nitrogen fertilizer rate increases plant uptake and soil availability of essential nutrients in continuous maize production in Kenya and Zimbabwe. Pasley (2019). Nutr. Cycl. Agroecosyst., Vol. 115, pp. 373.
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Challenges and opportunities for raising agricultural productivity in Malawi. Phiri (2012). Int. J. Agricult. Forest., Vol. 2, pp. 210.

Green revolution: impacts, limits, and the path ahead. Pingali (2012). Proc. Natl. Acad. Sci., Vol. 109, pp. 12302.
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Climate change and its impacts on Indian agriculture: an econometric analysis. Praveen (2020). J. Public Aff., Vol. 20.
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AquaCrop—the FAO crop model to simulate yield response to water: II. Main algorithms and software description. Raes (2009). Agron. J., Vol. 101, pp. 438.
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Pushing the envelope? Maize production intensification and the role of cattle manure in recovery of degraded soils in smallholder farming areas of Zimbabwe. Rusinamhodzi (2013). Field Crop Res., Vol. 147, pp. 40.
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Evaluation of fao penman–monteith and alternative methods for estimating reference evapotranspiration with missing data in southern Ontario, Canada. Sentelhas (2010). Agric. Water Manag., Vol. 97, pp. 635.
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Pros and cons of different sampling techniques. Sharma (2017). Int. J. Appl. Res., Vol. 3, pp. 749.

Explaining rice yields and yield gaps in Central Luzon, Philippines: an application of stochastic frontier analysis and crop modelling. Silva (2017). Eur. J. Agron., Vol. 82, pp. 223.
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Is labour a major determinant of yield gaps in sub-saharan africa? A study of cereal-based production systems in southern Ethiopia. Silva (2019). Agric. Syst., Vol. 174, pp. 39.
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Direct assimilation of measured soil water content in root zone water quality model calibration for deficit-irrigated maize. Sima (2020). Agron. J., Vol. 112, pp. 844.
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AquaCrop—the FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Steduto (2009). Agron. J., Vol. 101, pp. 426.
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Assessment of maize yield gap and major determinant factors between smallholder farmers in the Dedza district of Malawi. Tamene (2016). Nutr. Cycl. Agroecosyst., Vol. 105, pp. 291.
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The efficiency of smallholder agriculture in Malawi. Tchale (2009). AFJARE, Vol. 3.

When yield gaps are poverty traps: the paradigm of ecological intensification in African smallholder agriculture. Tittonell (2013). Field Crop Res., Vol. 143, pp. 76.
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Exploring diversity in soil fertility management of smallholder farms in western Kenya: ii. Within-farm variability in resource allocation, nutrient flows and soil fertility status. Tittonell (2005). Agric. Ecosyst. Environ., Vol. 110, pp. 166.
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Comparing penman-monteith and priestley-Taylor approaches as reference-evapotranspiration inputs for modeling maize water-use under mediterranean conditions. Utset (2004). Agric. Water Manag., Vol. 66, pp. 205.
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From field to atlas: upscaling of location-specific yield gap estimates. van Bussel (2015). Field Crop Res., Vol. 177, pp. 98.
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Reducing the maize yield gap in Ethiopia: decomposition and policy simulation. van Dijk (2020). Agric. Syst., Vol. 183.
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Yield gap analysis—rationale, methods and applications—introduction to the special issue. Van Ittersum (2013). Field Crop Res., Vol. 143, pp. 1.
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Yield gap analysis with local to global relevance—a review. Van Ittersum (2013). Field Crop Res., Vol. 143, pp. 4.
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Can yield variability be explained? Integrated assessment of maize yield gaps across smallholders in Ghana. van Loon (2019). Field Crop Res., Vol. 236, pp. 132.
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Participatory research to close the soybean yield gap on smallholder farms in Malawi. Van Vugt (2017). Exp. Agric., Vol. 53, pp. 396.
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AquaCrop: FAO’s crop water productivity and yield response model. Vanuytrecht (2014). Environ. Model. Softw., Vol. 62, pp. 351.
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Agricultural diversification as an important strategy for achieving food security in africa. Waha (2018). Glob. Chang. Biol., Vol. 24, pp. 3390.
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Performance of the priestley-Taylor equation in the semiarid climate of North China. Xiaoying (2005). Agric. Water Manag., Vol. 71, pp. 1.
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Temperature increase reduces global yields of major crops in four independent estimates. Zhao (2017). Proc. Natl. Acad. Sci., Vol. 114, pp. 9326.
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Original language	en
Pages (from-to)	103962
Volume	218
Publication status	Published - 2024

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