Mycotoxin contamination of Maize and Guinea corn from markets in Plateau State, Nigeria

Maize (Zea mays) and guinea corn (Sorghum bicolor) are major food items in Plateau state, Nigeria. A multistage sampling technique was used to select the markets and store/warehouses used for this study; sample collection employed a simple random sampling method from different sampling points within designated areas. A total of 18 representative samples were collected and analyzed for the following mycotoxins: aflatoxins (Aflatoxin B1 - AFB1, Aflatoxin B2 - AFB2, Aflatoxin G1 - AFG1 and Aflatoxin G2 - AFG2), fumonisins (Fumonisin B1 - FB1 and Fumonisin B2 - FB2 ) and cyclopiazonic acid (CPA). Out of 12 samples analyzed for Aflatoxins, AFB1 was detected in 5, AFB2 in 1, AFG1 in 1 and AFG2 in 6 samples respectively. The highest concentration of AFB1 and AFG2 were found in maize samples from Pankshin market. Only maize samples from Mangu market were contaminated with AFB2 and also harboured the lowest concentration of AFG2. AFG1 contamination occurred in only guinea corn from Shendam market. and FB1 was detected in all 18 samples analyzed. The mycotoxin CPA was not detected in any of the samples. Aflatoxins levels in analyzed samples were regarded as safe based on Nigerian and European Union maximum permissible levels of 4g/kg. With the exception of two samples, FB1 levels in analyzed maize samples were within European Union maximum permissible levels of 1,000 to 3000g/kg. The health and food safety implications of these results for the human and animal population are further discussed.

A modular traffic sampling architecture for flexible network measurements

Dissertação de Mestrado (Programa Doutoral em Informática)

Random walk forecast of urban water in Iran under uncertainty

There are two significant reasons for the uncertainties of water demand. On one hand, an evolving technological world is plagued with accelerated change in lifestyles and consumption patterns; and on the other hand, intensifying climate change. Therefore, with an uncertain future, what enables policymakers to define the state of water resources, which are affected by withdrawals and demands? Through a case study based on thirteen years of observation data in the Zayandeh Rud River basin in Isfahan province located in Iran, this paper forecasts a wide range of urban water demand possibilities in order to create a portfolio of plans which could be utilized by different water managers. A comparison and contrast of two existing methods are discussed, demonstrating the Random Walk Methodology, which will be referred to as the â On uncertainty pathâ , because it takes the uncertainties into account and can be recommended to managers. This On Uncertainty Path is composed of both dynamic forecasting method and system simulation. The outcomes show the advantage of such methods particularly for places that climate change will aggravate their water scarcity, such as Iran.