Using CERES-maize and ENSO as decision support tools to evaluate climate-sensitive farm management practices for maize production in the northern regions of Ghana

Open Access JournalMaize (Zea mays) has traditionally been a major cereal staple in southern Ghana. Through breeding and other crop improvement efforts, the zone of cultivation of maize has now extended to the northern regions of Ghana which, hitherto, were the home to sorghum and millet as the major cereals. Maize yield in the northern Ghana is hampered by three major biophysical constraints, namely, poor soil fertility, low soil water storage capacity and climate variability. In this study we used the DSSAT crop model to assess integrated water and soil management strategies that combined the pre-season El-Niño-Southern Oscillation (ENSO)-based weather forecasting in selecting optimal planting time, at four locations in the northern regions of Ghana. It could be shown that the optimum planting date for a given year was predictable based on February-to-April (FMA) Sea Surface Temperature (SST) anomaly for the locations with R2 ranging from 0.52 to 0.71. For three out of four locations, the ENSO-predicted optimum planting dates resulted in significantly higher maize yields than the conventional farmer selected planting dates. In Wa for instance, early optimum planting dates were associated with La Nina and El Niño (Julian Days 130-150; early May to late May) whereas late planting (mid June to early July) was associated with the Neutral ENSO phase. It was also observed that the addition of manure and fertilizer improved soil water and nitrogen use efficiency, respectively, and minimized yield variability, especially when combined with weather forecast. The use of ENSO-based targeted planting date choice together with modest fertilizer and manure application has the potential to improve maize yields and also ensure sustainable maize production in parts of northern Ghana

E. coli contamination of mountain springs used for drinking water and drilled well alternatives

Millions of people in developing communities drink water from springs on bedrock mountain slopes. Previous studies show E. coli causing many sampled springs on populated mountain slopes in southwest China to provide unsafe drinking water (Chitwood 2007a). Such studies are rare, but recently a reconnaissance study was initiated in a watershed in the Dominican Republic where more than 25,000 people, spread out across small communities and one town, rely on mountain springs. E. coli testing shows many of these springs to be unsafe. Water users live downslope and distant from the springs and receive spring water via pipelines. Likely, the E. coli originates from sparse livestock grazing up-slope from springs. Small wells drilled using portable rock coring machines and completed using novel continuous seals attached above the water intake zone are proposed to access safe drinking water drawn from permeable fractures tens of meters below ground, avoiding contamination near surface

Location and Land use effects on Soil Carbon Accretion and Productivity in the Coastal Savanna Agro-ecological Zone of Ghana

Land use type, climate and soil properties are major determinants of soil carbon storage and productivity, especially in low-input agriculture. In this study, we investigated the interactions among these factors at four (4) locations, namely Accra Metropolis, Ga West, Ga East and Shai Osudoku, within the Coastal-Savannah agro-ecological zone of Ghana. The land use types were maize-based cropping, cassava-based cropping, woodlot/plantations and natural forests. The impact of these on soil productivity at a given location was assessed in terms of soil carbon stocks and a Soil Productivity Index (SPI). The SPI is a composite value derived from routine soil properties such as: soil texture, available water capacity, pH, cation exchange capacity, soil organic carbon, available P, exchangeable K, potentially mineralizable nitrogen, and basic cations, among others. Principal component analysis was used to select soil properties that were used to estimate SPI. The results showed that the locations differed with respect to rainfall regimes and soil types. Locations with slightly heavier soil texture and relatively higher rainfall regimes (Ga East and Shai Osudoku) had significantly higher soil carbon storage and SPI values than the lighter soil textured locations (Accra Metropolis and Ga West). With regards to land use, forest had significantly higher soil carbon storage and SPI than all the other land use types, irrespective of location. The order of soil carbon storage and SPI were: forest > woodlot/plantation > cassava > maize. It was observed that though the Accra Metropolis location hosted the oldest forest, soil carbon was still low, apparently due to the lighter soil texture. We concluded that the soil productivity restorative ability is an interactive effect of carbon management (land use), soil texture and other properties. This interaction hitherto has not been adequately investigated, especially in low-input agriculture

Wheat EST resources for functional genomics of abiotic stress

BACKGROUND: Wheat is an excellent species to study freezing tolerance and other abiotic stresses. However, the sequence of the wheat genome has not been completely characterized due to its complexity and large size. To circumvent this obstacle and identify genes involved in cold acclimation and associated stresses, a large scale EST sequencing approach was undertaken by the Functional Genomics of Abiotic Stress (FGAS) project. RESULTS: We generated 73,521 quality-filtered ESTs from eleven cDNA libraries constructed from wheat plants exposed to various abiotic stresses and at different developmental stages. In addition, 196,041 ESTs for which tracefiles were available from the National Science Foundation wheat EST sequencing program and DuPont were also quality-filtered and used in the analysis. Clustering of the combined ESTs with d2_cluster and TGICL yielded a few large clusters containing several thousand ESTs that were refractory to routine clustering techniques. To resolve this problem, the sequence proximity and "bridges" were identified by an e-value distance graph to manually break clusters into smaller groups. Assembly of the resolved ESTs generated a 75,488 unique sequence set (31,580 contigs and 43,908 singletons/singlets). Digital expression analyses indicated that the FGAS dataset is enriched in stress-regulated genes compared to the other public datasets. Over 43% of the unique sequence set was annotated and classified into functional categories according to Gene Ontology. CONCLUSION: We have annotated 29,556 different sequences, an almost 5-fold increase in annotated sequences compared to the available wheat public databases. Digital expression analysis combined with gene annotation helped in the identification of several pathways associated with abiotic stress. The genomic resources and knowledge developed by this project will contribute to a better understanding of the different mechanisms that govern stress tolerance in wheat and other cereals