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Methods Used in Evaluating the Productivity of Some Illinois Soils
Author(s) -
Rust R. H.,
Odell R. T.
Publication year - 1957
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj1957.03615995002100020011x
Subject(s) - productivity , yield (engineering) , soil water , regression analysis , statistics , environmental science , crop , mathematics , crop yield , regression , sampling (signal processing) , hydrology (agriculture) , agronomy , soil science , computer science , materials science , geotechnical engineering , biology , metallurgy , filter (signal processing) , computer vision , economics , macroeconomics , engineering
Abstract Multiple curvilinear regression analyses of crop yields on major Illinois soil types and associations under different weather conditions and systems of management were made with the aid of an electronic digital computer. The independent variables studied in relation to corn yield were: rainfall and the mean of daily maximum temperatures for the period July 1 to August 31; nitrogen applied in the current year and in the previous year; pounds of P 2 O 5 and K 2 O applied in the current year plus an estimate of carry‐over; an index of the kind and frequency with which legume and legume‐grass mixtures were grown preceding the crop; and year. Yield estimates for a 10‐year period ending in 1955 on 7 representative soil types and associations are presented, together with measures of the reliability of the yield estimates. The amount of yield variation explained by the regression equations varied from about 18 to 56% in the examples presented. The primary objective of this study is to determine the relative productivity of major Illinois soils. The results presented are more satisfactory for this purpose than for predicting the net effect of individual management factors on crop yields. For the kind of sampling and analysis employed in this study, data are needed for approximately 100 to 200 fields in order to make reasonably accurate estimates of crop yields for a soil type or an association of two closely related soils under various climatic conditions and management practices.