The oldest Oldowan tool sites, from around 2.6 million years ago, have previously been confined to Ethiopia’s Afar Triangle. We describe sites at Nyayanga, Kenya, dated to 3.032 to 2.581 million years ago and expand this distribution by over 1300 kilometers. Furthermore, we found two hippopotamid butchery sites associated with mosaic vegetation and a C 4 grazer–dominated fauna. Tool flaking proficiency was comparable with that of younger Oldowan assemblages, but pounding activities were more common. Tool use-wear and bone damage indicate plant and animal tissue processing. Paranthropus sp. teeth, the first from southwestern Kenya, possessed carbon isotopic values indicative of a diet rich in C 4 foods. We argue that the earliest Oldowan was more widespread than previously known, used to process diverse foods including megafauna, and associated with Paranthropus from its onset.

The radiological hazard of naturally occurring radioactive material in Mount Homa in southwestern Kenya was investigated after 210 point measurements and 44 samples were analysed. In situ measured average outdoor absorbed dose rate in air using survey meters was found to vary from 154.8 to 2280.6 nGy h(-1). The mean (range) values of radioactive concentrations measured using an HpGe detection system for (40)K, (226)Ra and (232)Th were 915 ± 3 (64-3017), 195 ± 8 (17-1447) and 409 ± 4 (23-1369) Bq kg(-1), respectively. The calculated range of the annual effective dose for a person living in Homa Mountain area varied from 28.6 to 1681.2, with a mean of 470.4 µSv. All calculated average radiological indices, namely Radium equivalent, Representative level, Gamma activity, External and Internal hazard, were higher than the limits set by various national and international bodies. These results imply that Mount Homa region is a high background radiation area.

Soil quality assessment (SQA) is important for modulating agricultural productivity and thus requires simple and rapid analysis of soil (macro & micro) nutrients (here called soil quality indicators – SQIs). We report proof of concept of a chemometrics‐assisted energy dispersive X‐ray fluorescence and scattering (EDXRFS) spectroscopy technique for direct rapid analysis of SQIs. The EDXRFS method exploits, in addition to fluorescence, the X‐ray scatter peaks obtained non‐invasively from soils to develop a calibration strategy for quantitative analysis of SQIs in model clay soils doped with micronutrients (Fe, Cu, and Zn) and macronutrients (NO3−, SO42−, and H2PO4−). The soil samples and certified reference materials IAEA Soil‐7 and IAEA Soil‐1 (used to build spectral library for soil classification) were irradiated at various live times (to simulate different signal‐to‐noise ratios of analyte signals and analysis speed) in a teflon holder and were analyzed using a 109Cd‐excited XRF spectrometer. Principal components analysis was used for spectral data compression and pattern recognition (including for those SQI spectral signatures without any visibly discernible characteristic X‐ray lines), whereas partial least squares regression and artificial neural networks were used to build a calibration and quantitative analysis strategy. The method furnishes soil micronutrient and macronutrient information simultaneously and rapidly (t = 200 s). To the best of the authors' knowledge, this is the first time that an XRF method has demonstrated spectroanalytical potential for quantitative macronutrients analysis in soils applicable to routine SQA. Coupling EDXRFS with multivariate chemometrics enables rapid and reliable assessment of chemical SQIs. Copyright © 2011 John Wiley & Sons, Ltd.

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Cereals constitute a food staple in the African bread (Ugali) form. Overdependence on maize as a predominant staple is partly blamed on the constricting indigenous cereal phyto-diversity. Strategies rekindling interest in their restoration remain few and disconnected. Thus, the objectives were to: (1) search for micronutrient density information among accessions of sorghum, finger millet, pearl millet and maize on the basis of 'where-they-were-as they-were' (free-call diversity); (2) determine micronutrient densities linked to eco-nutrametric variation for distinguishing differences among accessions. The accessions were collected in 2003/04 from the Bungoma-Maseno-Kibwezi (BMK) phyto-regions and subjected to Energy Dispersive X-ray Fluorescence (XRF) analysis. A nested design was used for sampling in which the cereal species were nested within sites and sites nested within phyto-regions. For each accession with its soil, a gamut of element concentrations was XRF-generated. The data were subjected to a Clustered Bar Graphing (CBG) test for identifying variation-picking element(s). By CBG test, a given element's concentration data range was placed along the X-axis upon which species/accessions' density categories along the Y-axis were graphed as series in rows giving way to density variation comparisons. Where no such density variations were visible, the element was disregarded as non-variation-picking. The CBG test revealed that all accessions were 'imperfect' in that none of them had the gamut elements (density as subject score) inall-top or in-all-low density, i.e. none of the accessions scored high 'As' or low 'Cs' in every elemental density case. This implied that a phenotypic characterization as a whole would have required describing an accession in as different (number of) ways as the number of the variation-picking elements included. A soil-to-plant mineral flow (elemental uptake-ability or EU) was further calculated as a single value [plant ppm]/[soil] x 100. In sorghum the EUs were as follows: 2.4% for Fe (in accession tC74), 211% for Zn (in tC65), 332% for Cu (in tC36) and 408% for K in (tC70). The CBG test among the cereal accessions is invaluable for distinguishing within and between accessions in respect of their single element uptake-ability. A single nutrametric value (NMV) or grade, on the other hand, appears useful in describing a nutrametric phenotypic variant as it bypasses the genotype-environment interaction dilemma. Its robustness is its ability to distinguish various phenotypic mineral micronutrient diversity grading and offers opportunities for mineral micronutrient mapping across phyto-regions.