Interactions between genotype and environment are becoming increasingly important as cattle genotypes are being managed in a diverse range of environments worldwide. The objective of this study was to investigate if there is an interaction of strain of Holstein-Friesian cows (HF) by grass-based feed system that affects milk production, body weight, and body condition score. Three strains of HF were compared on 3 pasture-based feed systems over 3 consecutive years. The 3 strains of HF were: high production North American, high durability North American, and New Zealand. The 3 grass-based feeding systems (FS) were: a high grass allowance system (MPFS), a high concentrate system (HCFS), and a high stocking rate system (HSFS). There was a separate farmlet for each FS and a total of 99, 117, and 117 animals were used in yr 1, 2, and 3 respectively, divided equally between strains of HF and FS. The high production cows produced the highest yield of milk, the New Zealand the lowest, and the high durability animals were intermediate. Milk fat and protein content were higher for the New Zealand strain than for the high production and high durability strains. The New Zealand strain had the lowest body weight and the highest condition score, whereas the high durability strain had the highest body weight, and the high production strain had the lowest condition score. There was a strain x FS interaction for yield of milk, fat, and protein. The milk production response to increased concentrate supplementation (MPFS vs. HCFS) was greater with both the high production and high durability strains (1.10 kg of milk/kg of concentrate for high production; 1.00 kg of milk/kg of concentrate for high durability) than the New Zealand strain (0.55 kg of milk/kg of concentrate). The results indicate that the optimum strain of HF will vary with feed system.

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The prediction of both food intake and milk production constitutes a major issue in ruminants. This article presents a model predicting voluntary dry matter intake and milk production by lactating cows fed indoors. This model, with an extension to predict herbage intake at grazing presented in a second article, is used in the Grazemore decision support system. The model is largely based on the INRA fill unit system, consisting of predicting separately the intake capacity of the cows and the fill value (ingestibility) of each feed. The intake capacity model considers potential milk production as a key component of voluntary feed intake. This potential milk production represents the energy requirement of the mammary gland, adjusted by protein supply when the protein availability is limiting. Actual milk production is predicted from the potential milk production and from the nutritional status of the cow. The law of response of milk production is a function of the difference between energy demand and actual energy intake, modulated by protein intake level. The simulation of experimental data from different feeding trials illustrates the performance of the model. This new model enables dynamic simulations of intake and milk production sensitive to feeding management during the whole lactation period.

A total of 48 high genetic merit (HM) and 48 medium merit (MM) cows, each given a low (LC), medium (MC), or high (HC) level of concentrate supplementation, were used in a split-plot design experiment, which was run in three consecutive years, to evaluate animal production responses. Individual cow intakes were estimated twice each year while at pasture; measurement period 1 (MP1) was in May/June, and measurement period 2 (MP2) was in early September, corresponding on average to d 110 and 200 of lactation, respectively. In MP1, cows were offered 0 (LC), 3 (MC), and 6 kg (HC), whereas in MP2 the levels were 0 (LC), 0 (MC), and 4 kg (HC) of concentrate daily. Genotype had a significant effect on all milk production parameters in MP1 and MP2. The HM cows had the highest yield of milk, fat, protein, and lactose, whereas the MM cows had the highest milk fat, protein, and lactose concentrations. The HM cows had significantly higher grass dry matter intake (GDMI) estimates. In MP1, the average responses, per kg concentrate dry matter, was +1.10 kg of milk, +0.038 kg of protein, +0.032 kg of fat. The corresponding values in MP2 were +0.94 kg of milk, +0.037 kg of protein, and +0.025 kg of fat. The response to concentrate was linear and independent of preexperimental milk yield. In MP1, the partial regression coefficients relating daily GDMI to an increase in 1 kg of preexperimental milk yield (PMY), preexperimental BW (PBW), and concentrate intake (CI) were 0.123, 0.006, and -0.54, respectively, whereas the corresponding values in MP2 were 0.190,0.007, and-0.444, respectively. This study indicates that with high yielding dairy cows, on gras only GDMI of 17 kg of supporting milk yield of 30-kg/d is achievable. In this scenario, concentrate supplementation will result in lower substitution rates, and higher milk yield response than previously published with lower yielding cows.