A study of the effect of inputs on level of production of dairy farms in Queensland - a comparative analysis of survey data

Abstract

Multiple linear regression models able to estimate total farm milk production from nutritional inputs were developed from farm survey data provided by dairy farmers in Queensland, Australia. These models were specifically developed for inclusion in a decision support system that could provide dairy farmers with an annual milk production estimate, thus enabling them to compare their production with an average farm using the same inputs in their region. Separate models were developed for each of 4 regions in Queensland and an additional model was developed for farms producing greater than 750 kL of milk per farm per year. The models were tested on dairy farms in Queensland by using the decision support system on farms that were not involved with initial model development. The partial regression coefficients for the models were biologically sensible and, apart from some minor interactions between independent variables in 2 regions, were additive. These interactions were not included in the final model in the interests of parsimony, ease of explanation and a need to provide transparent models within the decision support system. The coefficients of determination (R2) for the models varied from 79.9 to 88.3%. Forward-feed artificial neural network models were also used to confirm the relative accuracy of the multiple linear regression models and to allow for any interactions or non-linear functions in the data and to show that the simple equations are more appropriate for a farmer-orientated decision support system.