EpuleDhibaEtongoEtAl2021
Référence
Epule, T.E., Dhiba, D., Etongo, D., Peng, C., Lepage, L. (2021) Identifying maize yield and precipitation gaps in Uganda. SN Applied Sciences, 3(5). (Scopus )
Résumé
In sub-Saharan Africa (SSA), precipitation is an important driver of agricultural production. In Uganda, maize production is essentially rain-fed. However, due to changes in climate, projected maize yield targets have not often been met as actual observed maize yields are often below simulated/projected yields. This outcome has often been attributed to parallel gaps in precipitation. This study aims at identifying maize yield and precipitation gaps in Uganda for the period 1998–2017. Time series historical actual observed maize yield data (hg/ha/year) for the period 1998–2017 were collected from FAOSTAT. Actual observed maize growing season precipitation data were also collected from the climate portal of World Bank Group for the period 1998–2017. The simulated or projected maize yield data and the simulated or projected growing season precipitation data were simulated using a simple linear regression approach. The actual maize yield and actual growing season precipitation data were now compared with the simulated maize yield data and simulated growing season precipitation to establish the yield gaps. The results show that three key periods of maize yield gaps were observed (period one: 1998, period two: 2004–2007 and period three: 2015–2017) with parallel precipitation gaps. However, in the entire series (1998–2017), the years 2008–2009 had no yield gaps yet, precipitation gaps were observed. This implies that precipitation is not the only driver of maize yields in Uganda. In fact, this is supported by a low correlation between precipitation gaps and maize yield gaps of about 6.3%. For a better understanding of cropping systems in SSA, other potential drivers of maize yield gaps in Uganda such as soils, farm inputs, crop pests and diseases, high yielding varieties, literacy, and poverty levels should be considered. © 2021, The Author(s).
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@ARTICLE { EpuleDhibaEtongoEtAl2021,
AUTHOR = { Epule, T.E. and Dhiba, D. and Etongo, D. and Peng, C. and Lepage, L. },
JOURNAL = { SN Applied Sciences },
TITLE = { Identifying maize yield and precipitation gaps in Uganda },
YEAR = { 2021 },
NOTE = { cited By 0 },
NUMBER = { 5 },
VOLUME = { 3 },
ABSTRACT = { In sub-Saharan Africa (SSA), precipitation is an important driver of agricultural production. In Uganda, maize production is essentially rain-fed. However, due to changes in climate, projected maize yield targets have not often been met as actual observed maize yields are often below simulated/projected yields. This outcome has often been attributed to parallel gaps in precipitation. This study aims at identifying maize yield and precipitation gaps in Uganda for the period 1998–2017. Time series historical actual observed maize yield data (hg/ha/year) for the period 1998–2017 were collected from FAOSTAT. Actual observed maize growing season precipitation data were also collected from the climate portal of World Bank Group for the period 1998–2017. The simulated or projected maize yield data and the simulated or projected growing season precipitation data were simulated using a simple linear regression approach. The actual maize yield and actual growing season precipitation data were now compared with the simulated maize yield data and simulated growing season precipitation to establish the yield gaps. The results show that three key periods of maize yield gaps were observed (period one: 1998, period two: 2004–2007 and period three: 2015–2017) with parallel precipitation gaps. However, in the entire series (1998–2017), the years 2008–2009 had no yield gaps yet, precipitation gaps were observed. This implies that precipitation is not the only driver of maize yields in Uganda. In fact, this is supported by a low correlation between precipitation gaps and maize yield gaps of about 6.3%. For a better understanding of cropping systems in SSA, other potential drivers of maize yield gaps in Uganda such as soils, farm inputs, crop pests and diseases, high yielding varieties, literacy, and poverty levels should be considered. © 2021, The Author(s). },
AFFILIATION = { International Water Research Institute, Mohammed VI University Polytechnic, Lot 660, Hay Moulay Rachid, Ben Guerir, 43150, Morocco; Department of Geography, McGill University, 805 Sherbrooke St. West. Burnside Hall 416, 4, Montreal, QC H3A 0B9, Canada; Department of Environmental Sciences, University of Seychelles, Anse Royale, Seychelles; University of Quebec at Montreal (UQAM), Succ Centre-Ville, Case postale 8888, Montreal, QC H3C 3P8, Canada },
ART_NUMBER = { 537 },
AUTHOR_KEYWORDS = { Crop pests and diseases; Farm inputs; High yielding varieties; Literacy rates; Maize; Poverty rates; Precipitation gaps; Uganda; Yield gaps },
DOCUMENT_TYPE = { Article },
DOI = { 10.1007/s42452-021-04532-5 },
SOURCE = { Scopus },
URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104077534&doi=10.1007%2fs42452-021-04532-5&partnerID=40&md5=be537011bceff6fffcd862c4c9164c3c },
}