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A von Liebig response function to nitrogen and phosphorus for hay production from irrigated pastures
Author(s) -
PARIS Q.,
PARIS P.
Publication year - 1985
Publication title -
grass and forage science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.716
H-Index - 56
eISSN - 1365-2494
pISSN - 0142-5242
DOI - 10.1111/j.1365-2494.1985.tb01739.x
Subject(s) - dactylis glomerata , lolium perenne , holcus lanatus , trifolium repens , agronomy , pasture , perennial plant , hay , randomized block design , biology , orchard , mathematics , fertilizer , forage , poaceae
Permanent pasture in the Po Valley of Italy was the site of a pluriannual experiment (1975–81) to observe the effects on hay production of N and P fertilizer applications well above those normally recommended. A split‐plot design with a randomized complete block arrangement of the whole‐plot factor with 5 levels of N and the subplot factor with 3 levels of P was chosen for the experiment. The maximum rate of N application was 800 kg ha −1 while the corresponding rate for P was 87.3 kg ha −1 . Principal species in the sward were orchard grass ( Dactylis glomerata L.), perennial ryegrass ( Lolium perenne L.), common velvetgrass ( Holcus lanatus L.) and white clover ( Trifolium repens L.). This field was irrigated according to customary techniques during summer months and cut five limes each year. Yields were analysed by means of a response function of the linear and plateau type which incorporates von Liebig's Law of the Minimum, it was found that this function represents the hay response very well with respect to N. In fact, beyond 390 kg ha −1 applied N the response is negligible up to 800 kg ha −1 , the maximum rate tested in this experiment. The optimal rate of applied N decreased consistently over the years from 390 to 260 kg ha −1 . At these unusually high levels of fertilization hay production increased about 60–80% compared with normal practices. The estimation of the von Liebig response function requires mathematical programming knowledge. The estimates obtained are maximum likelihood estimates. The practical importance of estimating and using this response function lies in its ability to achieve the maximum response with the minimum amount of fertilizers among all other admissible response functions. Hence, its adoption for making fertilizer recommendations would save farmers money and limit chemical pollution to the environment.