Use of geoinformation and neurotechnology to assess and to forecast the humus content variations in the steppe soils

This paper reports the results obtained using the systemic basin approach, geoinformation, and neurotechnology for modeling and forecasting of the humus spatial inhomogeneity and content variations in the steppe and dry steppe zones (Kherson oblast, Ukraine). The general trend of such variations has...

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Veröffentlicht in:	Russian agricultural sciences 2017-03, Vol.43 (2), p.157-161
Hauptverfasser:	Lisetskii, F. N., Pichura, V. I., Breus, D. S.
Format:	Artikel
Sprache:	eng
Schlagworte:	Agriculture Agrochemistry. Soil Science Artificial neural networks Biomedical and Life Sciences Decomposing organic matter Dependence Depletion Farming systems Forecasting Humus Inhomogeneity Irrigated lands Life Sciences Mathematical models Modelling Neural networks Plant Biochemistry Polynomials Soils Steppes Variation
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