In this paper we describe an experiment of detecting ammonia pollution in water and food samples. The novelty of our work is that we used an electronic nose to measure the smell of the samples, and applied henceforth an algorithmic procedure called decision trees to the measurements, in order to determine if ammonia was present in the samples. The results we get suggest that an appropriate extension of that method should allow not only for qualitative, but also for quantitative analysis of ammonia pollution in food.
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