Abstract

AbstractThe availability of Mn on 37 low and 20 high organic matter Wisconsin soils was determined by growing oats (Avena sativa L.) and ryegrass (Lolium perenne), respectively, in consecutive greenhouse studies. The Mn uptake values were used to develop prediction equations by means of multiple regression analysis with Mn extracted by various extracting solutions (18 extractants for the low and 13 for the high organic matter soils) plus various functions of soil pH and organic matter as the independent variables.On the low organic matter soils (O.M. < 6%), using only the Mn test, the best prediction values with uptake were obtained with total Mn, and with the 0.1N H3PO4 and 0.01M EDTA in 1N NH4OAc extractants (R2 = 57, 50 and 49%, respectively). Inclusion of soil pH and organic matter with the soil test values resulted in Mn uptake being predicted best by the 0.01M and 0.05M EDTA extractants (R2 = 68% for both). The contribution of the soil test in the prediction equation was strongest when the 0.1N H3PO4, 0.01M EDTA in 1N NH4OAc, 0.05M EDTA or DTPA (pH 7.3) extractants were used.On the high organic matter soils (4.2 to 78.5% OM), a regression equation with soil pH, organic matter and their cross‐product as the independent variables accounted for 70% of the Mn uptake variability. By including test × pH and test × organic matter for the 0.01M EDTA in 0.1M (NH4)2CO3 or DPTA (pH 10.7) extractants, the R2 values were increased to 80%. Soil test Mn or its squared value did not contribute significantly to any of the prediction equations; whereas, soil organic matter and the pH × organic matter cross‐product contributed to all.

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