Crop yield gaps in Cameroon.

Although food crop yields per hectare have generally been increasing in Cameroon since 1961, the food price crisis of 2008 and the ensuing social unrest and fatalities raised concerns about the country's ability to meet the food needs of its population. This study examines the country's potential for increasing crop yields and food production to meet this food security challenge. Fuzzy set theory is used to develop a biophysical spatial suitability model for different crops, which in turn is employed to ascertain whether crop production is carried out in biophysically suited areas. We use linear regression to examine the trend of yield development over the last half century. On the basis of yield data from experimental stations and farmers' fields we assess the yield gap for major food crops. We find that yields have generally been increasing over the last half century and that agricultural policies can have significant effects on them. To a large extent, food crops are cultivated in areas that are biophysically suited for their cultivation, meaning that the yield gap is not a problem of biophysical suitability. Notwithstanding, there are significantly large yield gaps between actual yields on farmers' farms and maximum attainable yields from research stations. We conclude that agronomy and policies are likely to be the reasons for these large yield gaps. A key challenge to be addressed in closing the yield gaps is that of replenishing and properly managing soil nutrients.

Anthropogenic sources and environmentally relevant concentrations of heavy metals in surface water of a mining district in Ghana: a multivariate statistical approach.

The levels of heavy metals in surface water and their potential origin (natural and anthropogenic) were respectively determined and analysed for the Obuasi mining area in Ghana. Using Hawth's tool an extension in ArcGIS 9.2 software, a total of 48 water sample points in Obuasi and its environs were randomly selected for study. The magnitude of As, Cu, Mn, Fe, Pb, Hg, Zn and Cd in surface water from the sampling sites were measured by flame Atomic Absorption Spectrophotometry (AAS). Water quality parameters including conductivity, pH, total dissolved solids and turbidity were also evaluated. Principal component analysis and cluster analysis, coupled with correlation coefficient analysis, were used to identify possible sources of these heavy metals. Pearson correlation coefficients among total metal concentrations and selected water properties showed a number of strong associations. The results indicate that apart from tap water, surface water in Obuasi has elevated heavy metal concentrations, especially Hg, Pb, As, Cu and Cd, which are above the Ghana Environmental Protection Agency (GEPA) and World Health Organisation (WHO) permissible levels; clearly demonstrating anthropogenic impact. The mean heavy metal concentrations in surface water divided by the corresponding background values of surface water in Obuasi decrease in the order of Cd > Cu > As > Pb > Hg > Zn > Mn > Fe. The results also showed that Cu, Mn, Cd and Fe are largely responsible for the variations in the data, explaining 72% of total variance; while Pb, As and Hg explain only 18.7% of total variance. Three main sources of these heavy metals were identified. As originates from nature (oxidation of sulphide minerals particularly arsenopyrite-FeAsS). Pb derives from water carrying drainage from towns and mine machinery maintenance yards. Cd, Zn, Fe and Mn mainly emanate from industry sources. Hg mainly originates from artisanal small-scale mining. It cannot be said that the difference in concentration of heavy metals might be attributed to difference in proximity to mining-related activities because this is inconsistent with the cluster analysis. Based on cluster analysis SN32, SN42 and SN43 all belong to group one and are spatially similar. But the maximum Cu concentration was found in SN32 while the minimum Cu concentration was found in SN42 and SN43.