Factors influencing the soil test calibration for Colwell P and wheat under winter-dominant rainfall

Abstract 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. While most attempts to improve soil tests focus on the extractant, here we explore the variation that could be accounted for by field based factors in the soil test calibration relationship between Colwell P and wheat yield. The Australian Better Fertiliser Decisions for Crops (BFDC) database was used as it is the biggest data set available for the relationship between the Colwell P soil test and wheat yield. The calibrations developed from this data set have been the subject of criticism, hence our objective of exploring the factors that account for more of the variation in the relationships for the dryland, winter dominant rainfall region of southern New South Wales (NSW). As reported in previous studies, soil type was shown to influence the Critical Range and r value for the Colwell P soil test calibration for P responses by wheat. In addition, in this study we identify that there was 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 there was an increased probability of crop P requirements being met from the fertiliser P. However, additional records need to be generated to establish more 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. While 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. The visual variation in these calibrations is therefore not simply due to random error associated with numerous workers over 60 years with different cultivars and agricultural systems. Factors such as soil type, sowing date and growing season rainfall influence the relative importance of the soil versus fertiliser pools of P for plant acquisition and hence cause much of the visual scatter, or mathematical variance, in the calibration curve. Understanding the mechanisms underlying the dependence of crops on fertiliser versus soil P can improve decision making for the application of fertiliser P