scholarly journals Soil‐test biological activity with the flush of CO 2 : VIII. Soil type and management diversity

2020 ◽  
Vol 84 (5) ◽  
pp. 1658-1674
Author(s):  
Alan J. Franzluebbers ◽  
Mary R. Pershing
1985 ◽  
Vol 25 (4) ◽  
pp. 881 ◽  
Author(s):  
DR Kemp ◽  
WJ McDonald ◽  
RD Murison

Soil phosphate (P) values were determined for 49 improved pasture sites on 11 occasions over a 3-year period. Each sample was taken from under an improved pasture on the Central Tablelands of New South Wales and analysed using the Bray No. 1 and Colwell (modified Olsen) tests. Variations in soil P values between samplings over time were significant (P<0.05). For individual sites, the 95% confidence limit, as a percentage of the mean, averaged � 19% for Bray P values and � 13% for Colwell P values. The pattern of variation in P values over time was not significantly (P<0.05) affected by soil P level, soil type or soil test. Variation in P values over time with both tests was significantly (P<0.05) correlated with a general estimate of soil moisture and thermal index for the sampling month. Both Colwell P and Bray P values showed negative correlations with increasing soil moisture or increasing thermal index. The correlation between Colwell P and Bray P values on any one soil type was not reliable enough to allow prediction of one soil-test P value from the other.


2020 ◽  
Vol 71 (2) ◽  
pp. 113
Author(s):  
Mark Conyers ◽  
Richard Bell ◽  
Michael Bell

Critical ranges for soil tests are based on results that inevitably involve some broad variance around the fitted relationship. Some of the variation is related to field-based factors affecting crop response to nutrients in the soil and some to the efficiency of the soil-test extractant itself. Most attempts to improve soil tests focus on the extractant, whereas here, we explore the variation that could be accounted for by field-based factors in the soil-test calibration relationship between Colwell phosphorus (P) and wheat yield, using the Australian Better Fertiliser Decisions for Crops database—the biggest dataset available for this relationship. Calibrations developed from this dataset have been criticised, and so we aimed to explore factors accounting for more of the variation in the relationships for the dryland, winter-dominant rainfall region of southern New South Wales. As reported previously, soil type was shown to influence the critical range and r-value for the Colwell P soil-test calibration for P responses by wheat. We also identified a tendency for dry conditions, at sowing or during the season, to lower relative yields for a given soil-test value, indicating increased reliance on fertiliser P over soil P. A similar trend was evident for later sowing date, again suggesting an increased probability of crop P requirements being met from the fertiliser P. However, additional records need to be generated to establish definitively that early sowing or subsurface P reserves minimise response to fertiliser P. In general, factors that influence crop access to soil P will have an impact on response to fertiliser P. Although this analysis shows that it is possible to ‘tighten’ the response curve for Colwell P and wheat by restricting the data for a given soil type to ideal management and seasonal conditions, the ‘outliers’ that are excluded frequently reflect an important subset of environmental conditions encountered by wheat crops in dryland agriculture.


2018 ◽  
Vol 82 (3) ◽  
pp. 685-695 ◽  
Author(s):  
Alan J. Franzluebbers ◽  
Mary R. Pershing ◽  
Carl Crozier ◽  
Deanna Osmond ◽  
Michelle Schroeder-Moreno

1966 ◽  
Vol 6 (23) ◽  
pp. 409
Author(s):  
ICR Holford

The superphosphate and potassium chloride requirements of sugar cane were studied in relation to soil test levels on 25 different soil types in Fiji. Soil phosphorus was determined by a modified Truog method and soil potassium by extraction with 0.5N acetic acid. Percentage yields of sugar cane in fertilizer field experiments harvested over a five-year period were highly correlated with soil test levels in the control plots. The regressions of percentage yield on soil test level were curvilinear, and a modified Mitscherlich equation gave an excellent fit to the points. Critical soil test levels were found to exist, below which soils gave significant yield responses to applied nutrients. Critical soil test levels ranged over 5 to 20 p.p.m, for phosphorus and 51 to 150 p.p.m. for potassium. Within the deficient range of each nutrient there were only weak relationships between optimum fertilizer requirements and soil test levels. There was some evidence to suggest that soil type may be a useful complementary criterion for predicting fertilizer requirements.


2018 ◽  
Vol 110 (5) ◽  
pp. 2033-2049 ◽  
Author(s):  
Alan J. Franzluebbers ◽  
Smriti Pehim-Limbu ◽  
Matt H. Poore

Sign in / Sign up

Export Citation Format

Share Document