regression model of the sweet corn yields depending on the agrotechnology under the irrigated conditions of the dry steppe zone of ukraine

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ID: 221234
2016
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Ranked #7 of 9 articles by views in international geoscience and remote sensing symposium (igarss)

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Abstract
The article presents the model of the commodity sweet corn cobs without husks yields depending on the depth of the moldboard primary tillage, mineral fertilizers and crops density, obtained on the basis of the regression analysis of yielding data of the field experiment. It is found that increasing of the moldboard plowing depth on 1 cm leads to lowering of the yields of sweet corn commodity cobs without husks, in average, on 97.2 kg/ha; increasing of the mineral fertilizers application rate on 1 kg/ha of active substance leads to increase of yields, in average, on 43,6 kg/ha; increasing of the crops density on 1 ths/ha – to increase of yields, in average, on 26,5 kg/ha. It is defined, that mineral fertilizers have the maximum influence on the sweet corn yields (coefficient of determination – 0,833), and depth of the primary tillage – the minimum (coefficient of determination – 0,028). Use of the regression model should contribute to high-precision prediction of the sweet corn yields under the different crop cultivation technologies on drip irrigation in conditions of the Dry Steppe Zone of Ukraine
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o2016regression Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Ushkarenko V. O;Likhovid P. V.
Journal international geoscience and remote sensing symposium (igarss)
Year 2016
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