Abstract:
Animal Production in Australia Vol. 15 A PASTURE UTILIZATION MODEL TO EVALUATE OPTIONS FOR RESEARCH INTO BEEF CATTLE MANAGEMENT J.J.L. MADEN* and L.P. THATCHER* SUMMARY This model was designed to investigate factors affecting level of pasture utilization by beef cattle and to evaluate the suitability of microcomputers for developing simple models of agricultural systems, thus providing an additional tool for examining priorities for research. The model simulates an annual pasture system, set-stocked by cows and calves offered no supplements. It is primarily concerned with pasture-animal interrelationship and not animal production. Variable options include time of calving, stocking rate and pasture growth. It was shown that maximum utilization of pasture was 43% for cows calving in June and run at l-O/ha. Maximum annual intake of cows and calves occurred for cows calving in March, run at 0.6/ha. Preliminary results also suggest that efficiency of utilization was only sensitive to stocking rate, with calving time and variations in pasture growth pattern having little additional effect. It was concluded that research to achieve realistic changes in pasture growth patterns was not of high priority unless accompanied by major improvements in net nutritional value of the pasture. The examination of changes in nutritional value are beyond the scope of the model, requiring additional functions to simulate animal performance. INTRODUCTION When making judgements between research project alternatives most research leaders allot their highest priorities to those options with the greatest potential for producing an economic improvement over existing commercial practices (Anderson 1972). The greatest problem associated with this approach is that of objectively assessing the chances of success. Recent developments in micro-computer technology have placed considerable computing power within the financial reach of most research establishments. The development and use of meaningful models provides a powerful method for identifying those variables in the farming system most sensitive to change, i.e., those variables most likely to provide economic responses and be hence worthy of field experimentation. This model was designed to investigate the factors affecting the utilization of annual pasture by grazing animals. That is, the percentage of total pasture growth actually consumed and thus contributing to animal production. It was intended to discover whether such a model could be successfully installed in a micro-computer. If so, the model would be used to investigate the effect of changing the pattern of pasture growth e.g., by introducing new species or management practices on pasture utilization by beef cows and calves. This report presents some preliminary findings. The Model The model is primarily concerned with pasture utilization, and hence with animal intake, pasture growth and deterioration and pasture availability. It simulates 100 ha of annual pasture environment, typical of S.E. Australia, which is grazed by set stocked beef cows and calves offered no supplements. This was *Department of Agriculture, Rutherglen Research Institute, Rutherglen, Vic. 3685 440 Animal Production in Australia Vol. 15 identified as being the most profitable system from current field experiments at Rutherglen (D. Hamilton pers. comm.). The simulation continues over a number of years, each being nominated as of Pasture growth in each calendar month good 9 average or poor pasture prcduction. is an exogenous variable determined by the operator and is entered for each of the year types. Other management options include three times of calving For reasons (December, March or June), number of cows and calving percentage. of simplicity, the annual liveweight changes of the animals follow a pre-set pattern for each time of calving, derived from experiments at Rutherglen. This liveweight is one determinant of intake. Because the diet of grazing animals in annual pasture environments consists of dry (or dead) herbage in summer, green herbage in spring and a mixture of both at other times, the model maintains a balance of both green and dry herbage at 15 day intervals. Animal intake is determined as a function of animal liveweight and lactation status, and quantity and digestibility of available pasture. Maximum potential intake is derived by applying the relationship found by Church (1974) and Conway (1973) to th e current lactation status, liveweight of animals and digestibility of the pasture. Real intake is usually less than this, due to restrictions in available pasture. In the model, a sinusoidal function is applied to derive real intake from potential intake and available pasture. Disappearance of dry herbage other than that consumed by the animals is determined from the relationship of Bowman et al. (1982). Losses of green pasture not accounted for by animal consumption are assumed to be 15% of that present at each 15 day iteration. The model is written in FORTRAN 77 to run interactively on an APPLE II computer of 64k capacity. Each yearly cycle takes 23 seconds to run. RESULTS Validation Pasture data were validated against data from another experiment at Rutherglen (D. Hamilton pers. comm.) which compared three times of calving (December, March and June) at three stocking rates (0.6, 0.8, 1.0 cows/ha). Since measurements of pasture availability and growth in that experiment were intended only as a guide to relative changes in the system, they did not provide a comprehensive data set for validation. Nevertheless, the curve of predicted green pasture dry matter is in good agreement with the real values (see Fig. l), particularly over the mid-winter period which is critical for annual pasture systems. The main departure of predicted from real values is in early spring. Pasture Utilization and Animal Intake The model has been used to observe the effect on intake and pasture utilization of varying stocking rate, time of calving (Table I> and pattern of pasture growth (Table 2). For a normal pasture growth pattern, mean intake per head is increased by 18% by reducing stocking rate from 1.0 to 0.6 cows per hectare. Animal intake is least for December calving and greatest for June calving, but the difference is only 5%. 441 Animal Production in Australia Vol. 15 Figure 1 Simulation of pasture availability under different stocking intensities (1980) Table 1 Intake and utilization of pasture Table 2 Mean intake and utilization of pasture with pasture growth increased 20% in winter and reduced 20% in spring Animal intake varied with calving time because intake of green herbage is greater than that of dry herbage (Conway 1.973). Intake was also affected by the pattern of pasture growth, though utilization varied little. Results from the model show that maximum utilization of pasture was 43% when cows were stocked at l.O/ha for June calving. The only effective method shown for increasing utilization was to increase stocking rate. Otherwise the utilization of pasture was insensitive to changes in calving time and growth pattern of the pasture. The increased risks associated with higher stocking rates may not make this solution to better utilization a satisfactory economic alternative. 442 Animal Production in Australia Vol. IS DISCUSSION Predicted values for available green pasture were usually greater than those measured in the field. Galbraith, Arnold and Carbon (1980) also reported difficulty in validating predicted growth against that measured in cages, and concluded that such growth measurements may be inflated. Thus we may have used pasture growth values which were artificially high and these have in turn produced a predicted value for available pasture which is too high. If this is so, then the measurement of pasture growth using cages may need closer scrutiny if the absolute values thus produced are to be acceptable. These preliminary results indicate that increasing winter pasture production will not improve level of utilization, although annual intake will increase. If increased winter production is achieved at the expense of spring production, neither utilization nor annual intake will increase. Thus the introduction of such species or practices may not warrant high research priorities. However, should pasture composition changes influence the net nutritional value of the pasture, then animal response functions may need to be considered since animal liveweight influences potential intake. Nonetheless, sensitivity analyses show that in autumn and winter real intake is reduced to less than 20% of potential intake. Thus, extending the model to include all aspects of animal productivity is unlikely to change the conclusion. REFERENCES ANDERSON, J.R. (1972). J.A.I.A.S. 38 (I):70 CI BOWMAN, P.J., WHITE, D.H., CAYLEY, J.W.D. and BIRD, P.R. (1982). Aust. Soc. Anim. Prod. &:36. CHURCH, DC. (197~. In 'Digestive Physiology and Nutrition of Ruminants Vol. 3 p. 33-f, editor D.C. Church. (Church). CONWAY, A.G. (1973). Irish J. Ag. Res. c (2k193. 6:23. GALBRAITH, K.A., ARNOLD, G.W. and CARBON, B.A. (1980). Agric. Systems = 443