0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Recent Patterns in Maize Yield and Harvest Area across Africa

      , ,
      Agronomy
      MDPI AG

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Africa’s rapidly growing population is exerting a lot of pressure on agricultural resources including maize yields and harvest area. Across Africa, access to advanced options for increasing maize yields are inadequate. This is daunting as most of the cultivation of maize is in the hands of smallholder farmers who have inadequate access to modern methods of farming. This has resulted in an increase in dependency on harvest area to increase yields. However, it is still unclear how this maize-yield-harvest-area dynamic plays out across different regions of Africa. This study uses crop yield and harvest area time series data from FAOSTAT for the period 1961–2019. The data are analyzed using linear interpolation, the normalization technique, the rate of change, the Pearson correlation coefficient, the coefficient of determination and regression analysis. The results show that maize yields and harvest area have increased by 71.35% and 60.12%, respectively across Africa. Regionally, West, Middle and East Africa witnessed a positive relationship between maize yields and harvest area while in North and Southern Africa, maize yields and harvest area have an inverse relationship. For example, in assessing the relationship between maize yield and harvest area in Africa, this work observes that North Africa has a correlation of −35% and an R2 of 12%, while Southern Africa has a correlation of −36% and R2 of 13%. On the other hand, West Africa has a correlation of 87% and an R2 of 76%, while Middle Africa recorded a correlation of 66% and an R2 of 42%. East Africa recorded a correlation of 76% and R2 of 61%. These results confirm that maize yield and harvest area have a positive relationship in West, Middle and East Africa and a negative relationship in North and Southern Africa. These results underscore the fact that in North and Southern Africa, maize production is less dependent on harvest area as is the case in the other regions of Africa. Such findings have implications for adaptation planning especially in sub-Saharan Africa where food insecurity is closely related to land and forest degradation.

          Related collections

          Most cited references37

          • Record: found
          • Abstract: found
          • Article: not found

          A new look at the statistical model identification

          IEEE Transactions on Automatic Control, 19(6), 716-723
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Food security: the challenge of feeding 9 billion people.

            Continuing population and consumption growth will mean that the global demand for food will increase for at least another 40 years. Growing competition for land, water, and energy, in addition to the overexploitation of fisheries, will affect our ability to produce food, as will the urgent requirement to reduce the impact of the food system on the environment. The effects of climate change are a further threat. But the world can produce more food and can ensure that it is used more efficiently and equitably. A multifaceted and linked global strategy is needed to ensure sustainable and equitable food security, different components of which are explored here.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Global food demand and the sustainable intensification of agriculture.

              Global food demand is increasing rapidly, as are the environmental impacts of agricultural expansion. Here, we project global demand for crop production in 2050 and evaluate the environmental impacts of alternative ways that this demand might be met. We find that per capita demand for crops, when measured as caloric or protein content of all crops combined, has been a similarly increasing function of per capita real income since 1960. This relationship forecasts a 100-110% increase in global crop demand from 2005 to 2050. Quantitative assessments show that the environmental impacts of meeting this demand depend on how global agriculture expands. If current trends of greater agricultural intensification in richer nations and greater land clearing (extensification) in poorer nations were to continue, ~1 billion ha of land would be cleared globally by 2050, with CO(2)-C equivalent greenhouse gas emissions reaching ~3 Gt y(-1) and N use ~250 Mt y(-1) by then. In contrast, if 2050 crop demand was met by moderate intensification focused on existing croplands of underyielding nations, adaptation and transfer of high-yielding technologies to these croplands, and global technological improvements, our analyses forecast land clearing of only ~0.2 billion ha, greenhouse gas emissions of ~1 Gt y(-1), and global N use of ~225 Mt y(-1). Efficient management practices could substantially lower nitrogen use. Attainment of high yields on existing croplands of underyielding nations is of great importance if global crop demand is to be met with minimal environmental impacts.
                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                ABSGGL
                Agronomy
                Agronomy
                MDPI AG
                2073-4395
                February 2022
                February 01 2022
                : 12
                : 2
                : 374
                Article
                10.3390/agronomy12020374
                7e271c92-2b0e-4ed1-96d6-412a3be2c1d4
                © 2022

                https://creativecommons.org/licenses/by/4.0/

                History

                Comments

                Comment on this article