Avaliação de um sistema de otimização de rações para vacas leiteiras

Abstract

The work was conducted to evaluate a program of optimization of feed for dairy cows based on a Microsoft [marca registrada] Excel [marca registrada] spreadsheet, programmed with equations to calculate the nutritional requirements of dairy cows and the supply of nutrients from food. Data on race day lactation, daily milk yield, average daily consumption observed in fat composition of milk and feed were inserted as input in the program. Information published in 58 scientific articles and has been through the comparison of program results with observed were used. Data on dry matter intake (DMI) and the feed composition were entered as input to the program it was estimated a production of milk by means of the same equations. Subsequently, the estimated milk production was compared with that observed. Subsequently, the estimated milk production was compared with that observed. A second evaluation was performed using as input data to produce milk for the program estimated an intake of dry matter. In this case, the estimates were also compared the program with the actual observed data from CMS. The intake of dry matter was predicted by the program underestimated in most cases. This is due to climatic factors and dietary characteristics, which are not considered in the program. In addition, individual variations can also interfere with the animal consumption. Milk production was estimated on average 11% higher than the observed production. This result is due to some studies reviewed, in which the complete nutritional assessment of foods used in the diets were not available and therefore, tabulated values, which may have interfered in the predictions were used. A comparison between the use of net energy and metabolizable protein to your requirements provided by the program was also held. The diets were 15% and 7% levels of liquid left in the metabolizable energy and protein, respectively. The program proved to be a useful tool for assessing diets for dairy cows in field situations, but their predictions can improve through chemical evaluation of dietary constituents.