<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "Adding Value to Field-Based Agronomic\r\nResearch through Climate Risk Assessment:\r\nA Case Study of Maize Production\r\nin Kitale, Kenya\r\n"^^ . "In sub-Saharan Africa (SSA), rainfed agriculture is the dominant source of food production. Over the past\r\n50 years much agronomic crop research has been undertaken, and the results of such work are used in\r\nformulating recommendations for farmers. However, since rainfall is highly variable across seasons the\r\noutcomes of such research will depend upon the rainfall characteristics of the seasons during which the\r\nwork was undertaken. A major constraint that is faced by such research is the length of time for which\r\nstudies could be continued, typically ranging between three and five years. This begs the question as to\r\nwhat extent the research was able to ‘sample’ the natural longer-term season-to-season rainfall variability.\r\nWithout knowledge of the full implications of weather variability on the performance of innovations being\r\nrecommended, farmers cannot be properly advised about the possible weather-induced risks that they\r\nmay face over time. To overcome this constraint, crop growth simulation models such as the Agricultural\r\nProduction Systems Simulator (APSIM) can be used as an integral part of field-based agronomic studies.\r\nWhen driven by long-term daily weather data (30+ years), such models can provide weather-induced risk\r\nestimates for a wide range of crop, soil and water management innovations for the major rainfed crops of\r\nSSA.Where access to long-term weather data is not possible, weather generators such as MarkSim can be\r\nused. This study demonstrates the value of such tools in climate risk analyses and assesses the value of the\r\noutputs in the context of a high potential maize production area in Kenya. MarkSim generated weather\r\ndata is shown to provide a satisfactory approximation of recorded weather data at hand, and the output of\r\n50 years of APSIM simulations demonstrate maize yield responses to plant population, weed control and\r\nnitrogen (N) fertilizer use that correspond well with results reported in the literature.Weather-induced risk\r\nis shown to have important effects on the rates of return ($ per $ invested) to N-fertilizer use which, across\r\nseasons and rates of N-application, ranged from 1.1 to 6.2. Similarly, rates of return to weed control and\r\nto planting at contrasting populations were also affected by seasonal variations in weather, but were always\r\nso high as to not constitute a risk for small-scale farmers. An analysis investigating the relative importance\r\nof temperature, radiation and water availability in contributing to weather-induced risk at different maize\r\ngrowth stages corresponded well with crop physiological studies reported in the literature."^^ . "2011" . . "47" . "2" . . "Cambridge University Press"^^ . . . "Experimental Agriculture"^^ . . . . . . . . . . . . . . . . . "P J M"^^ . "Cooper"^^ . "P J M Cooper"^^ . . "J"^^ . "Dimes"^^ . "J Dimes"^^ . . "K P C"^^ . "Rao"^^ . "K P C Rao"^^ . . "P N"^^ . "Dixit"^^ . "P N Dixit"^^ . . "Kenya"^^ . . . "Zimbabwe"^^ . . . . . . . "Adding Value to Field-Based Agronomic\r\nResearch through Climate Risk Assessment:\r\nA Case Study of Maize Production\r\nin Kitale, Kenya\r\n (PDF)"^^ . . . . . . . . "Adding Value to Field-Based Agronomic\r\nResearch through Climate Risk Assessment:\r\nA Case Study of Maize Production\r\nin Kitale, Kenya\r\n (Indexer Terms)"^^ . . . . . . "Adding Value to Field-Based Agronomic\r\nResearch through Climate Risk Assessment:\r\nA Case Study of Maize Production\r\nin Kitale, Kenya\r\n (Image (JPEG))"^^ . . . . . "HTML Summary of #43 \n\nAdding Value to Field-Based Agronomic \nResearch through Climate Risk Assessment: \nA Case Study of Maize Production \nin Kitale, Kenya \n\n\n" . "text/html" . . . "Maize"@en . . . "Climate Change"@en . .