Agronomic survey to assess crop yield, controlling factors and management implications: a casestudy of Babati in northern Tanzania
cg.contributor.center | International Center for Tropical Agriculture - CIAT | en_US |
cg.contributor.center | Selian Agricultural Research Institute - SARI Tanzania | en_US |
cg.contributor.center | International Institute of Tropical Agriculture - IITA | en_US |
cg.contributor.crp | CRP on Dryland Systems - DS | en_US |
cg.contributor.funder | Not Applicable | en_US |
cg.coverage.country | TZ | en_US |
cg.coverage.region | Eastern Africa | en_US |
cg.creator.id | Kihara, Job Maguta: 0000-0002-4394-9553 | en_US |
cg.creator.id | Tamene, Lulseged: 0000-0002-3806-8890 | en_US |
cg.creator.id | Mateete, Bekunda: 0000-0001-7297-9383 | en_US |
cg.date.embargo-end-date | 2016-12-31 | en_US |
cg.identifier.doi | https://dx.doi.org/10.1007/s10705-014-9648-3 | en_US |
cg.isijournal | ISI Journal | en_US |
cg.issn | 1385-1314 | en_US |
cg.journal | Nutrient Cycling in Agroecosystems | en_US |
cg.subject.agrovoc | agriculture | en_US |
cg.subject.agrovoc | yield gap | en_US |
cg.subject.agrovoc | plant density | en_US |
cg.volume | 102 | en_US |
dc.contributor | Tamene, Lulseged | en_US |
dc.contributor | Massawe, P. | en_US |
dc.contributor | Mateete, Bekunda | en_US |
dc.creator | Kihara, Job Maguta | en_US |
dc.date.accessioned | 2017-01-10T17:05:42Z | |
dc.date.available | 2017-01-10T17:05:42Z | |
dc.description.abstract | Improved agronomic management is important to reduce yield gaps and enhance food security in subSaharan Africa. This study was undertaken to understand contributing factors to observed yield gaps for maize in farmer fields and to demonstrate appropriate agronomic survey methods. The study aimed to (1) demonstrate an approach for farmlevel agronomic survey, (2) identify key crop production constraints and (3) define the nutrient input and output balances of different fields. Agronomic survey was conducted in 117 farmer fields randomly distributed in a 10 km by 10 km block in Babati, northern Tanzania. A semistructured questionnaire and production measurements were used to collect data which were analyzed with regression classification and mixed effect models. The exploitable maize yield gap at farmlevel reaches up to 7.4 t ha , and only <5 % of fields achieve maize grain yield of 5 t ha . Slope, plant density, distance from homestead, crop variety, timing of planting and period since conversion significantly influenced maize yields. For example, fields on flat land had up to 1.6 t ha more maize grain yield than those on steep slopes while fields with plant density >24,000 plants ha had 900 kg ha more yield than those with less density. At least 52 % of the fields had negative nutrient balances. We conclude that cropping systems used in Babati should be preferentially supplemented with mineral fertilizers while optimizing plant density, increasing manure application and appropriate varietal choice in order to reduce the yield gaps | en_US |
dc.format | en_US | |
dc.identifier | https://mel.cgiar.org/reporting/downloadmelspace/hash/24OLHeYF/v/61218dfee36faf465c1d32b149a426f4 | en_US |
dc.identifier.citation | Job Maguta Kihara, Lulseged Tamene, P. Massawe, Bekunda Mateete. (31/5/2015). Agronomic survey to assess crop yield, controlling factors and management implications: a casestudy of Babati in northern Tanzania. Nutrient Cycling in Agroecosystems, 102, pp. 5-16. | en_US |
dc.identifier.status | Limited access | en_US |
dc.identifier.uri | https://hdl.handle.net/20.500.11766/5459 | |
dc.language | en | en_US |
dc.publisher | Springer Verlag (Germany) | en_US |
dc.rights | CC-BY-NC-4.0 | en_US |
dc.source | Nutrient Cycling in Agroecosystems;102,(2015) Pagination 5,16 | en_US |
dc.subject | agronomic survey | en_US |
dc.subject | nutrient balances | en_US |
dc.subject | regression tree | en_US |
dc.title | Agronomic survey to assess crop yield, controlling factors and management implications: a casestudy of Babati in northern Tanzania | en_US |
dc.type | Journal Article | en_US |
dcterms.available | 2015-05-31 | en_US |
dcterms.extent | 5-16 | en_US |
mel.impact-factor | 1.416 | en_US |