Assessment of PCBs and exposure risk to infants in breast milk of primiparae and multiparae mothers in an electronic waste hot spot and non-hot spot areas in Ghana.

The aim of the study was to assess the levels of PCBs in the breast milk of some Ghanaian women at suspected hotspot and relatively non-hotspot areas and to find out if the levels of these PCBs pose any risk to the breastfed infants. A total of 128 individual human breast milk were sampled from both primiparae and multiparae mothers. The levels of PCBs in the milk samples were compared. Some of these mothers (105 individuals) work or reside in and around Agbogbloshie (hot-spot), the largest electric and electronic waste dump and recycling site in Accra, Ghana. Others (23 donor mothers) also reside in and around Kwabenya (non-hotspot) which is a mainly residential area without any industrial activities. Samples were analyzed using GC-MS/MS. The total mean levels and range of Σ7PCBs were 3.64ng/glipidwt and ˂LOD-29.20ng/glipidwt, respectively. Mean concentrations from Agbogbloshie (hot-spot area) and Kwabenya (non-hotspot areas) were 4.43ng/glipidwt and 0.03ng/glipidwt, respectively. PCB-28 contributed the highest of 29.5% of the total PCBs in the milk samples, and PCB-101 contributed the lowest of 1.74%. The estimated daily intake of PCBs and total PCBs concentrations in this work were found to be lower as compared to similar studies across the world. The estimated hazard quotient using Health Canada's guidelines threshold limit of 1µg/kgbw/day showed no potential health risk to babies. However, considering minimum tolerable value of 0.03µg/kgbw/day defined by the Agency for Toxic Substances and Disease Registry (ATSDR), the values of some mothers were found to be at the threshold limit. This may indicate a potential health risk to their babies. Mothers with values at the threshold levels of the minimum tolerable limits are those who work or reside in and around the Agbogbloshie e-waste site.

Predicting apple (cv. Elshof) postharvest dry matter and soluble solids content with near infrared spectroscopy.

BACKGROUND: Fruit dry matter (DM) and soluble solids content (SSC) are primarily composed of carbohydrate and are standard parameters for assessing quality. Near infrared spectroscopy provides potential for non-destructive fruit quality analysis but the collinearity between DM and SSC is an issue for prediction. Shorter wavelength spectra have been used for the prediction of fruit DM and SSC, but radiation between 1000 and 2500 nm may be suitable for distinguishing between the two forms of carbohydrate. RESULTS: Spectra and DM and SSC samples were taken for a total of 450 'Elshof' apples 30, 58 and 93 days after harvest. Regression models were built using the interval partial least squares method. Prediction models for DM and SSC for each day yielded R² values between 0.63 and 0.86 and residual predictive deviations (RPDs) between 1.7 and 2.7 for DM, and R² = 0.76-0.85 and RPDs = 2.2-2.6 for SSC. CONCLUSION: Model RPD values were not high enough for general quantitative predictions, although they compare well to previous work. Certain factors affected model success, including changes in fruit physiology over time and the range of reference data. The complexity of absorbance spectra for DM and SSC plus their strong correlation suggests that prediction models cannot easily distinguish between soluble and non-soluble forms of carbohydrate.