CamDairy : a computer program for performance prediction, ration analysis and ration formulation to maximise profit from dairy cows.

Abstract

214 Proc. Aust. Soc. Anim. Prod. Vol. 17 CAMDAIRY - A COMPUTER PROGRAM FOR PERFORMANCE PREDICTION, RATION ANALYSIS AND RATION FORMULATION TO MAXIMISE PROFIT FROM DAIRY COWS R.C. KELLAWAY* SUMMARY Applications of a computer model CAMDAIRY are described. An example is given of how it can be used to predict the performance of lactating cows, identify limiting nutrients and formulate maximum-profit rations. Examples are also given of how it can be used to simulate management options in order to determine their effects on profitability. Key words: computer model, lactating cows, feeding management INTRODUCTION CAMDAIRY is a computer model containing a package of programs designed to help advisers, farmers, students and research workers who are involved in the feeding of dairy cows. Details of the model are given by Hulme et al. (1986). The core program incorporates functions to predict nutrient requirements, feed intake, substitution effects when feeding concentrates, tissue mobilisation and Nutrient partition of nutrient utilisation between milk production and growth. partitioning is described by a series of asymptotic curves relating energy intake to milk production, such that energy requirements per litre increase progressively with level of milk production. When the user specifies feed intake and composition and information on cow liveweight and condition score, potential peak milk production and stage of lactation, cow performance is predicted and limiting nutrients identified. Alternatively, when feed intake is not specified, the model predicts intake from plant and animal factors and uses linear programing to formulate rations for up to two groups of cows in a herd in a way which maximises income above feed costs, whilst meeting nutrient requirements and satisfying constraints on feed supply and milk production requirements. PREDICTION OF PERFORMANCE Prediction of performance is often appropriate as the first step in determining factors which are limiting the productivity of dairy cows. When predicted performance is similar to actual performance, it may be assumed that factors which are not considered by the model, such as trace elements, or stress due to disease or environment factors, are unlikely to be limiting performance. However, when predicted performance does differ from current performance, the accuracy of inputs relating to animal and plant factors should be checked. If correct, it may be assumed that performance could be limited by one or more of the factors above Inputs required for this prediction are which are not considered by the model. Information on the amount of pasture eaten may be estimated given in Table 1. Information on the nutrient using a meter, e.g. the Ellinbank plate meter. content of pasture feeds, is contained in the 'feed library', a data file in the program which may be edited to conform with local information. Pasture meter readings, taken before and after grazing, may be used to predict the nutrient Performance is content of pasture eaten, following calibration of the meter. predicted on the basis of these inputs, as shown in Table 2. 2 M.C. Franklin Laboratory, Department of Animal Husbandry, University of Sydney, Camden, N.S.W. 2570 Proc. Aust. Soc. Anim. Prod. Vol. 17 OPTIMISATION OF RESOURCES TO INCREASE PROFITABILITY Daily feeding practice 215 Following the prediction of performance, the next step towards increasing profitability is to consider alternative feeding strategies. As an example of this, consider a dairy farm on the Central Coast of NSW in summer. There` are 100 Holstein Friesian cows calving year round, grazing kikuyu grass ($17/t as fed), The farm has a quota of 1000 with a commercial concentrate available ($150/t>. L/ day ; milk prices are 36 cents/L for quota milk and 14 cents/L for milk produced It is assumed that 30 of the cows in herd 1 are in early above the quota. Animal inputs lactation and the remainder in herd 2 are in mid-late lactation. are the same as 'those in Table 1, and nutrient information on the feeds is taken from the feed data file. CAMDAIRY is then used to formulate a maximum-profit ration. A summary of predictions and recommendations is given in Table 3. . TABLE 1. Inputs required for performance prediction . Detai,led information is also produced on the nutrient composition of the rat ion in relation to nutrient requirements. Information in Table 3 shows that, with the resources available, profit is maximised when concentrates are fed at rates of 6.7 and 5.0 kg/day to cows in herds 1 and 2 respectively, It is predicted that it is profitable to produce 967 litres/day in excess of the quota of 1000 litres/day. 216 TABLE 3. Proc. Aust. Soc. Anim. Prod. Vol. 17 Predicted milk yields, milk income, amounts of roughage and concentrate, feed costs and predicted liveweight change Feed management strategies CAMDAIRY can be used to simulate various management options in order to determine their effects on profitability. The effect of potential peak milk yield (genetic merit) on requirements for concentrates and gross profit is illustrated in Table 4. Apart from potential peak milk yield, all other assumptions are the same as those in the previous example. TABLE 4. Effects of potential peak milk yield on concentrate requirements for maximum profit, and gross profit* On the basis of the information presented in Table 4, the cost of improving the genetic merit of the cows may be compared with the potential returns. With a better quality pasture, the potential intake of nutrients would be higher, so that incremental changes in gross profit would be greater. At the present time there is much interest in the role of white clover in pastures for dairy cows in Victoria. A unique characteristic of clover is its high edibility relative to that of ryegrass of similar digestibility. A simulation study of farms in the Gippsland area of Victoria was made, to determine the effect of increasing the proportion of white clover in the pasture. Assumptions on the main resources and returns were as follows:- cows: 100 Proc. Aust. Soc. Anim. mod. Vol. 17 217 Holstein Friesian x Jersey, 450 kg liveweight; pastures: perennial ryegrass, late vegetative, costing $30/t DM; white clover costing $30, $36 or $48/t DM, assumed edibility 26% higher than that of ryegrass (Rogers et al., 1982); milk: no quota; 14 cents/L. Higher costs of clover are based on the assumption that clover yields are usually lower than those of perennial ryegrass in the same environment. TABLE 5. Effects of pasture costs and stage of lactation on gross profit* ($/day) from 100 cow herd with seasonal calving * Milk returns less pasture costs. Output from the model (Table 5) indicates that, on the basis of the assumptions made, gross' profit decreases with increases in the amount of white clover in the pasture, when clover costs 60% or more than ryegrass, and cows are To the feed costs must be added animal health 20 weeks or later in lactation. costs associated with, grazing clover, such .as drugs used in bloat prevention and losses associated with cows succumbing to bloat. Without considering these costs, it appears that it8 would be useful to increase the percentage of white clover in the . pasture, provided that costs of production (.$/t DM) are no more than 20040% higher than 'those of producing perennial ryegrass. CONCLUSION \ The model integrates what 'is thought to be the most accurate informat ion available relating to the feeding of dairy COWS, and applies this, to maximising Currently it is being used by advisers, profit from feed and animal resources. There is scope to research workers .and students feed manufticturers, farmers, improve the model by increasing the accuracy of prediction of feed intake,. yield of absorbed nutrients from different feeds and partition of absorbed nutrients into milk and body tissue. l REFERENCES HULME, D.J., KELLAWAY, R.C., BOOTH, P.J. and BENNETT, L. (1986). Agr'ic. Systems 22:. 81: ROGERT G.L., PORTER, R.H.D. and ROBINSON, I. (1982). In: Dairy Production from ,Pasture. Eds. K.L. Macmillan and V.K. Taufa, N.Z. Soc; Anim. Prod.