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RESEARCH ARTICLE

Superphosphate on perennial pastures. I. Effects of a pasture response on sheep production

ML Curll

Australian Journal of Agricultural Research 28(6) 991 - 1005
Published: 1977

Abstract

From 1973 to 1975 in the Mediterranean environment of southern New South Wales, superphosphate was applied annually at four rates (0, 62, 125 and 250 kg ha-1) to an established perennial pasture with a substantial history of superphosphate use. The pasture was continuously grazed by Border Leicester × Merino ewes (at 10 and 13.3 ha-1), so that plant growth responses to superphosphate could be assessed in sheep production terms and an estimate made of the monetary value of these responses.

Growth rate of unfertilized pastures declined over the experimental period, and depending on the quantity of superphosphate applied and stocking rate, responses of fertilized pastures ranged from 20 to 36% in 1973, 28 to 157% in 1974 and 75 to 233% in 1975. From having similar proportions of perennial ryegrass (Lolium perenne) and subterranean clover (Trifolium subterraneum), pastures tended towards clover dominance with little (62 kg ha-1) or no superphosphate, particularly at high stocking rate, and to grass dominance at higher rates of superphosphate, particularly at low stocking rate.

By increasing the level of available pasture, superphosphate increased wool production and ewe liveweight, lambs reared, their growth rate and the percentage that reached marketable weight (32 kg). These trends were similar at both stocking rates. Significant quadratic response relationships existed between these parameters and rate of superphosphate.

Withholding superphosphate caused a progressive reduction in gross margins of about 37% over the 3 year trial period, while its application increased gross margins, relative to those from unfertilized pastures, by a maximum 10, 42, and 140% for the first, second and third year respectively.

It is suggested that these pasture responses calibrated in animal production terms may be extended to other situations most effectively by using the data to test and improve tentative models used to predict fertilizer requirements.

https://doi.org/10.1071/AR9770991

© CSIRO 1977

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