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Yield gap analysis of field crops. Methods and case studies













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    Improving water productivity in the field with farmers: Farmers Field Schools on water in Jordan 2022
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    The North Jordan Valley (NJV) is located in the northwest of Jordan and it has a subtropical climate with warm winters and hot summers, with a mean annual rainfall of about 350 mm. The warm climate made the area an important agricultural area that mainly produces citrus. Vegetables (e.g., hot peppers, eggplants, okra and others) and other fruit trees (e.g., banana, grapes and date palm) are cultivated in the area as well. Water deficiency is evident in this area and the Jordan Valley Authority (JVA) adopted reduced water allocations (quotas) for farmers in NJV. For the local community in NJV, agriculture is the main employment sector and the main source of income. In addition to scarce water, the major challenges faced by farmers are the high prices of agricultural inputs and low yield prices. Producing more benefits with less water (increased water productivity) is one of the most strategic response to such challenges. Benefits can be either biophysical (yield, expressed in mass unit – kg), economical (returns, expressed in monetary terms – $) or even social when considering job created or dietary value. The analysis of local crop production showed that there is a significant gap between the actual yields and the attainable yields. the reader will know more about FAO's farmer field schools (FFS), its methodology and implementation. in addition to Farming practices implemented through FFSs including the objective of the FFS for each practice, the method applied by the FFS in the demonstration field and the method applied by traditional farmers.
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    Adaptation to Climate Risk and Food Security: Evidence from Smallholder Farmers in Ethiopia 2015
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    This paper explores the impact of climate risk on the adoption of risk decreasing practices and other input choices and evaluates their impact on subjective and objective measures of household welfare (namely net crop income and a food insecurity indicator). The analysis is conducted primarily using a novel data set that combines data from the large-scale and representative Ethiopia Socioeconomic Survey (ERSS), 2011/12 with historical climate and biophysical data. We employ a multivariate probit model on plot level observations to model simultaneous and interdependent adoption decisions and utilize a conditional mixed process estimator (CMP) and instrumental variable (IV) method for the impact estimates. Findings show that there is interdependency between the adoption decisions of different farm management practices which may be attributed to complementarities or substitutability between the practices. Greater riskiness, reflected in the coefficients of variation and higher temperature , increases use of risk reducing inputs such as climate-smart agriculture (CSA) inputs, but decrease use of modern inputs such as chemical fertilizer. Even if higher climate risk does generate higher incentive to adopt, results also confirm the importance of other conventional constraints to adoption that need to be addressed. Yield enhancing inputs such as chemical fertilizer and improved seed are mainly adopted by wealthier households and households having access to credit and extension servic es whereas risk reducing inputs are frequently used by households with lower level of wealth and limited access to credit and households with stable land tenure. Moreover, the CMP and IV estimations showed that the adoption of CSA and modern inputs have positive and statistically significant impacts on the objective measure of food security (net crop income) but no impact is observed for the subjective food security indicator.
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    A strategic reassessment of fish farming potential in Africa 1998
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    The present study is an update of an earlier assessment of warm-water fish farming potential in Africa, by Kapetsky (1994). The objective of this study was to assess locations and areal expanses that have potential for warm-water and temperate-water fish farming in continental Africa. The study was based on previous estimates for Africa by the above author, and on estimates of potential for warm-water and temperate-water fish farming in Latin America by Kapetsky and Nath (1997). However, a nu mber of refinements have been made. The most important refinement was that new data allowed a sevenfold increase in resolution over that used in the previous Africa study, and a twofold increase over that of Latin America (i.e. to 3 arc minutes, equivalent to 5 km x 5 km grids at the equator), making the present results more usable in order to assess fish farming potential at the national level. A geographical information system (GIS) was used to evaluate each grid cell on the basis of severa l land-quality factors important for fish-farm development and operation regardless of the fish species used. Protected areas, large inland water bodies and major cities were identified as constraint areas, and were excluded from any fish farming development altogether. Small-scale fish farming potential was assessed on the basis of four factors: water requirement from ponds due to evaporation and seepage, soil and terrain suitability for pond construction based on a variety of soil attributes a nd slopes, availability of livestock wastes and agricultural by-products as feed inputs based on manure and crop potential, and farm-gate sales as a function of population density. For commercial farming, an urban market potential criterion was added based on population size of urban centres and travel time proximity. Both small-scale and commercial models were developed by weighting the above factors using a multi-criteria decision-making procedure. A bioenergetics model was incorporated int o the GIS to predict, for the first time, fish yields across Africa. A gridded water temperature data set was used as input to a bioenergetics model to predict number of crops per year for the following three species: Nile tilapia (Oreochromis niloticus), African catfish (Clarias gariepinus) and Common carp (Cyprinus carpio). Similar analytical approaches to those by Kapetsky and Nath (1997) were followed in the yield estimation. However, different specifications were used for small-scale and co mmercial farming scenarios in order to reflect the types of culture practices found in Africa. Moreover, the fish growth simulation model, documented in Kapetsky and Nath (1997), was refined to enable consideration of feed quality and high fish biomass in ponds. The small-scale and commercial models derived from the land-quality evaluation were combined with the yield potential of each grid cell for each of the three fish species to show the coincidence of each land-quality suitability class with a range of yield potentials. Finally, the land quality-fish yield potential combinations were put together to show where the fish farming potential coincided for the three fish species. The results are generally positive. Estimates of the quality of land show that about 23% of continental Africa scored very suitable for both small-scale and commercial fish farming. For the three fish species, 50-76% of Africa's land has the highest yield range potential, and the spatial distribution of th is yield is quite similar among the species and farming systems. However, the spatial distribution of carp culture potential was greater than for Nile tilapia and African catfish. Combining the two farming system models with the favourable yields of the three fish species suggest that over 15% of the continent has land areas with high suitability for pond aquaculture.

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