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The influence of foliar fertilization by water solution of 7hydrate sulphate(VI) iron(II) on yielding and the chemical composition of crops II.The influence of foliar fertilization with the water solution of 7hydrate sulphate(VI) iron(II) on the content.

Krzywy E., Krzywy J., Krzywy-Gawrońska E.

Polish Journal of Chemical Technology

2005

Vol. 7, nr 2

19-21

The research on foliar fertilization with the water solution of the 7 hydrate sulphate (VI) iron (II) applied with and without an addition of urea, was carried out. Three concentrations of the water solution of the waste were used. The results of the research show that because of the waste water solution influence, the content of nitrogen has increased in potato tubers and in spring barley grains. The addition of urea to the water solution of 7 hydrate sulphate (VI) iron (II), has caused an increase of the nitrogen content in the studied plants. Foliar fertilization with the water solution of the 7 hydrate sulphate (VI) iron (II) with and without the addition of urea, did not have a distinct impact on the content of phosphorus, calcium, potassium and magnesium in the studied plants. Foliar fertilization with FeSO4 ź 7H2O water solution with and without the addition of urea as well as the concentration of solutions with the waste in most cases, has increased the content of sulphur and iron in the studied plants.

Próba prognozowania składu chemicznego roślinności na podstawie danych dotyczących cech glebowych

Gruszczyński S., Trafas M.

Inżynieria Środowiska / Akademia Górniczo-Hutnicza im. S. Staszica w Krakowie

2000

T. 5, z. 2

423-432

W pracy omówiono próbę ustalenia powiązań pomiędzy cechami gleb, a zawartością metali ciężkich w roślinach poprzez wykorzystanie sieci neuronowych. Oparto się na wynikach badań gleb i roślin (marchew i inne warzywa, a także trawy) pobranych z różnych rejonów Polski, zarówno "czystych" jak i zanieczyszczonych metalami ciężkimi. Uzyskany przybliżony model pozwala na analizę wpływu zmian występujących w nim parametrów na poziom zawartości metali ciężkich w roślinach.

This work discusses an attempt to make the connection between the qualities of soils and the heavy metal content in plants by using neural networks. To support this results of testing, soil and plants (carrots and other vegetables, as well as grasses) collected in different regions of Poland, both "clear" and contaminated by heavy metals were used. The outcoming estimed model allows the analysis of the effect of the changes taking place in its parameters on the level of heavy metal content in plants.