W. J. Fulkerson

Opportunities for future Australian dairy systems: a review

During the last decade, Australian dairy farmers have been challenged to increase total factor productivity (the ratio between the rate of increase in total output and the rate of increase in the use of all inputs) in order to attenuate the negative effects of a steady decline in the terms of trade over the same period of time. Overall, the increase in total factor productivity has been low (1.5%) and farmers are questioning the most appropriate production system for the future. In an attempt to address this central question, we first identified the nature of the key pressures dairy farmers in Australia are likely to face in the future, namely labour and feed related issues. We then discuss major opportunities for developing new dairy production systems based on increased efficiency in the use of land and cows and on increasing the efficiency of labour management and lifestyle. We do not attempt to provide the best futuristic option for dairy systems in Australia. Instead, this review discusses key areas of the production system with potential to impact positively on any or all the physical, economic and labour-related aspects of modern dairy farming. By so doing, this review highlights the research questions that need to be addressed now in order to provide Australian dairy farmers with improved tools to manage their production systems in the future.

Effect of diet, energy balance and milk production on oxidative stress in early-lactating dairy cows grazing pasture.

The aim of this study was to determine the effect of diet, energy balance and milk production on oxidative stress in early-lactating, Holstein-Friesian dairy cows fed to produce either low or high levels of milk. Indicators of energy balance (non-esterified fatty acids, β-hydroxybutyrate, glucose and insulin-like growth factor-1) and indicators of oxidative stress (reactive oxygen metabolites and biological antioxidants) were measured in the first 5 weeks of lactation. Energy balance indicators showed that high producing animals had a lower degree of negative energy balance. Diet was found to have an indirect effect on the level of oxidative stress. Factors associated with a high level of oxidative stress were severe negative energy balance (mean -71 ± 6.85 27 MJ/cow/day, P < 0.05) and lower levels of milk production (mean 26.4 ± 0.07 28 L/cow/day, P < 0 .05). Further studies will be required to more precisely determine the specific effects of diet, energy balance and milk production on such stress in dairy cows and to establish normal ranges for these biomarkers.

Holstein-Friesian Dairy Cows Under a Predominantly Grazing System: Interaction Between Genotype and Environment

A 5 yr whole-system study, beginning in June 1994, compared the productivity of high [HGM; Australian Breeding Value (ABV) of 49.1 kg of fat plus protein] and low [LGM; ABV of 2.3 kg of fat plus protein] genetic merit cows. Cows from both groups were fed at 3 levels of concentrate (C): 0.34 (low C), 0.84 (medium C), and 1.71 (high C) t of DM/cow per lactation. Thus, there were 6 treatments (farmlets) composed of 18 cows each. The 30 blocks of pasture on each farmlet were matched between farmlets for pasture growth before the study (and soil characteristics and aspect). Cows were culled, and pasture and feed use were managed so as not to bias any one treatment. Genetic merit, level of feeding, and their interaction were significant effects for protein content, protein/cow, and milk and protein/ha. For fat and milk yield/cow, genetic merit and level of feeding were significant, whereas there was no significant effect of genetic merit on fat content. The difference of 46.8 kg of fat plus protein yield between the ABV of HGM and LGM cows and the actual difference in production between the 2 groups was not significantly different except for low C (27 kg) cows. This was due to a 3-fold lower protein yield difference (6 kg/cow) compared with an ABV difference for protein yield of 17.9 kg/cow. The dramatic effect of treatment on protein is in line with differences in the mean protein content (2.89% for the HGM - low C cows compared with a mean of 3.02% for the remaining groups) and mean body condition score [4.3 for HGM - low C cows compared with 4.8 for the mean of the remaining groups (scale 1 to 8)], both indicators reflecting a higher negative energy balance in the HGM - low C cows. When individual cow production was plotted against ABV for production of milk or protein yield all relationships were quadratic, but the slope was relatively flat (low response to ABV) for the low C cows, steeper for the medium C cows and steepest (but not linear) for the high C cows. The relationship between ABV for fat yield and actual fat yield was linear for all levels of concentrate. The mean milk yield/ha from pasture for the 6 farmlets over the 5 yr was 11,868 L, 11,417 L, or 7,761 L for the HGM cows fed at low C, medium C, or high C, respectively, and 10,579 L, 9,800 L, or 5,812 L for LGM cows, fed at low C, medium C, or high C, respectively. The response to concentrates fed was very high for the HGM - medium C cows at 0.115 kg fat plus protein or 1.75 L milk/kg of concentrate fed, with comparable figures of 0.083 kg and 1.0 L, 0.86 kg and 1.47 L and 0.066 and 0.92 L/kg of concentrate fed for the HGM - high C, LGM - medium C, and LGM - high C, respectively. The results show a significant genetic merit by environment (level of feeding) interaction for reproduction and most production parameters when considered in terms of the individual cow and the whole farm system.

Energy Balance and Reproduction on Dairy Cows Fed to Achieve Low or High Milk Production on a Pasture-Based System

This study investigated the energy balance, metabolic changes, reproduction, and health in Australian Holstein-Friesian cows of average genetic merit fed to produce 6,000 L of milk/cow per lactation (restricted production; Rp) on a predominantly grazed pasture diet, or 9,000 L of milk/cow per lactation (high production: Hp) on a more intensive feeding regimen by using a partial mixed ration to supplement pasture. The mean 4% fat-corrected milk (FCM) and standard deviation achieved was 8,466 +/- 1,162 L/cow per lactation for the Hp herd and 6,748 +/- 787 L/cow per lactation for the Rp herd. During early lactation, the degree of estimated negative energy balance was less in the Hp cows than in the Rp cows (-16.1 vs. -29.1 MJ/cow per day, respectively). Consequently, the mobilization of body reserves was also lower in the Hp cows, and this was reflected in lower concentrations of nonesterified fatty acids (0.70 vs. 0.84 mmol/L) and beta-hydroxybutyrate (0.51 vs. 0.69 mmol/L) and greater concentrations of glucose (3.51 vs. 3.34 mmol/L) and insulin-like growth factor-I (78.9 vs. 58.7 ng/mL) for Hp and Rp cows, respectively. After calving, body condition score and body weight decreased to a similar extent in both herds and did not reflect the differences in mobilization of body reserves between the 2 herds. Reproductive performance was not significantly related to level of milk yield. The mean interval from calving to first active corpus luteum was 33 (SD = 20) d postpartum, and there were 1.4 (SD = 0.8) estrus cycles before the beginning of the breeding period (>50 d postpartum). The interval from calving to pregnancy was 114 d, and the pregnancy rate after 12 wk of mating was 74%. The number of cows with ovarian abnormalities was also similar between the 2 herds. Cows with a long postpartum anestrus had the lowest concentration of insulin-like growth factor-I. The number of health-related disorders was also similar between the herds, with the exception of mastitis, for which the incidence was significantly greater in the Hp cows. The results indicate that the production per cow could be increased from 6,748 L of FCM/cow per lactation for cows grazing pasture and supplemented with concentrates only at milking to 8,466 L of FCM/ cow per lactation, in one lactation, by supplementing pasture with a partial mixed ration. Despite the fact that production per cow increased substantially, the degree of estimated negative energy balance and the metabolic changes in early lactation were lower and reproductive performance was maintained.

Difference in yield and persistence among perennial forages used by the dairy industry under optimum and deficit irrigation

Perennial ryegrass (Lolium perenne L.) is the dominant forage grazed by dairy cows in Australia; however, poor persistence has led to an increasing interest in alternative forages. This study was conducted to identify more productive and/or persistent perennial forage species than perennial ryegrass. We evaluated 15 perennial forages under optimum irrigation (I1) and 2 nominated deficit irrigation (I2, 66% of irrigation water applied to I1; I3, 33% of irrigation water applied to I1) regimes, over 3 years at Camden, NSW (34°3′S, 150°39′E), on a brown Dermosol in a warm temperate climate. The forages were: perennial ryegrass, cocksfoot (Dactylis glomerata L.), phalaris (Phalaris aquatica L.), prairie grass (Bromus catharticus M. Vahl), tall fescue (Schedonorus phoenix (Scop.) Holub), kikuyu (Pennisetum clandestinum Hochst. ex. chiov.), paspalum (Paspalum dilatatum Poir.), birdsfoot trefoil (Lotus corniculatus L.), lucerne (Medicago sativa L.), red clover (Trifolium pratense L.), strawberry clover (Trifolium fragiferum L.), sulla (Hedysarum coronarium L.), white clover (Trifolium repens L.), chicory (Cichorium intybus L.), and plantain (Plantago lanceolata L.). Under non-limiting conditions of water and fertility, tall fescue, kikuyu, and prairie grass had the highest mean annual yield over the 3 years of this experiment (24.8–25.5 t dry matter (DM)/ha), which was significantly greater (P < 0.05) than perennial ryegrass (21.1 t DM/ha). Kikuyu was significantly higher than all forages under the extreme I3 deficit irrigation treatment, with mean annual yields of 17.0 t DM/ha. In contrast, the mean yield of white clover was significantly lower (P < 0.05) than of any other forage at only 5.0 t DM/ha, a 70% decline in yield compared with I1. Lucerne was the most tolerant species to deficit irrigation, with a mean annual yield decline (P < 0.05) between the I1 and I3 treatment of only 22%. This study has shown that there are large differences in the relative yield potential of forages and, importantly, indicates the possibility of increasing yield of perennial forages by at least 2-fold on commercial farms, by improving water, and fertiliser management. However, while yield is an important criterion for choosing dairy forages, it is only one factor in a complex system, and choice of forages must be considered on a whole-farm basis and include water-use efficiency, nutritive value, costs of production, and risk.

Grazing preferences by dairy cows for 14 forage species.

The objective of this study was to quantify the grazing preference of dairy cows for eight grass, four legume and two herb species in eight seasons over 2 years. All species were grown at the same site, under the same climatic conditions, and with soil moisture and nutrient availability being non-limiting to plant growth. The forage species evaluated were cocksfoot (Dactylis glomerata cv. Kara H0265), perennial ryegrass (Lolium perenne cv. Bronsyn), short rotation ryegrass (Lolium multiflorum cv. Concord), fescue (Festuca arundinacea cv. Advance Maxp.), phalaris (Phalaris tuberose cv. Holdfast), paspalum (Paspalum dilatatum cv. Poir. Common), kikuyu (Pennisetum clandestinum cv. Whittet), prairie grass (Bromus willdenowii cv. Matua), lucerne (Medicago sativa cv. Sceptre), persian clover (Trifolium resupinatum cv. Maral), red clover (Trifolium pretense cv. Astred), white clover (Trifolium repens cv. Kopu II), chicory (Cichorium intybus cv. Grouse) and plantain (Plantago lanceolata cv. Tonic). The 14 forage species treatment plots were laid out in a completely randomised block design with three replicate blocks. The treatment plots were around the circumference of a circle so that the three cows used in each test had unbiased access to all forage species within the blocks. The tests comprised observing the forage being grazed at 10-s intervals for 1 h. The cow preference was recorded as time (min) spent grazing on each forage species. Three Holstein Friesian dairy cows of similar dominance were selected and had grazed all 14 forage species before tests. Cows were fed to requirements before each test so that they would be selective in choice of forages. The most preferred species over the whole year was prairie grass followed by kikuyu and then white clover, despite the fact that kikuyu was not available in winter. Fescue was the least preferred grass species. The mean grazing times for prairie grass and kikuyu during the 1-h test periods of grazing was 11.6 and 10.5 min, respectively. White clover and lucerne were the most preferred legumes (9.6 and 9.0 min, respectively), whereas chicory and plantain were little consumed (3.5 and 3.2 min, respectively). A prediction equation comprising water soluble carbohydrates (WSC%) and nitrate-nitrogen [NO3-N (g/kg DM)] over all seasons and forage species accounted for more variation in cow preference than any other single or combination of variables measured: cow preference [time (min) on plots] = 1.86 + 0.67 WSC% – 1.9 NO3-N (g/kg DM) (r2 = 0.76; s.e. = 2.22; n = 109). The results indicate that the relative palatability of forages can be reasonably well predicted from WSC% and NO3-N concentration, having a positive and negative effect on cow preference, respectively. The prediction equation was improved for groups of species if neutral detergent fibre (NDF%) was included: grasses, cow preference [time (min) on plots] = 24.5 + 0.42 WSC% – 1.31 NO3-N (g/kg DM) – 0.39 NDF% (r2 = 0.87; s.e. = 1.62; n = 57); legumes, cow preference [time (min) on plots] = 3.02 + 0.98 WSC% – 2.15 NO3-N (g/kg DM) – 0.08 NDF% (r2 = 0.92; s.e. = 1.38; n = 36); and herbs, cow preference [time (min) on plots] = 19.41 + 0.22 WSC% – 1.74 NO3-N (g/kg DM) – 0.69 NDF% (r2 = 0.53; s.e. = 1.81; n = 19).

FutureDairy: a national, multidisciplinary project to assist dairy farmers to manage future challenges – methods and early findings

FutureDairy is a national, multidisciplinary project designed to assist Australian dairy farmers to manage future challenges. FutureDairy is exploring technical, economic and social aspects of technology adoption through an innovative approach that combines methodologies of social research (‘People’), extension (‘System’) and technical research (‘Science’). The technologies being investigated revolve around increasing forage production per unit of land through a complementary forage rotation; evaluating the most efficient use of brought-in feed to increase milk production per ha; and, the incorporation of automatic milking and other technological innovations that would either reduce labour input or allow more precise agriculture. The central strategy of FutureDairy is to utilise ‘knowledge partnerships’ to co-develop knowledge around each of the key areas of investigation; thus a key feature of the project is its linkage with commercial ‘partner’ farmers that explore similar questions to those being investigated at Elizabeth Macarthur Agricultural Institute (NSW Department of Primary Industries), where the technical research is being undertaken. This paper focuses on early findings from the forages module. Work thus far has shown that forage yields in excess of 40 t DM/ha.year are achievable. However, the practicalities of implementing this technology on-farm have already identified new and diverse issues that, unless understood, will jeopardise its effective adaptation by farmers.

Benefits of accurately allocating feed on a daily basis to dairy cows grazing pasture

Two experiments were conducted, each over several months, when cows grazed either ryegrass (September–November 2001) or kikuyu (February–March 2002) pastures, to assess the effects of accurately allocating feed on a daily basis to lactating Holstein–Friesian dairy cows. In each case, 28 cows were randomly stratified into 2 equal groups on the basis of milk and milk component yield, liveweight, age and days in lactation. The metabolisable energy requirements of the animals were estimated from standard established requirements. In each experiment, both groups of cows received the same amount of supplement over a period that was equivalent to a pasture regrowth cycle of 12–16 days. The control group received a set amount of supplements each day, while supplements fed to the adjusted group varied, dependent on pasture available. Available pasture was varied from 7 to 21 kg DM/cow.day (above a stubble height of 5 cm), to mimic the variation found on well-managed dairy farms. When pasture available was above the predicted requirement for cows in the adjusted group, pasture availability was restricted to predicted requirements and the extra milk that could be produced from the spared pasture was estimated. However, cows in the control group had the opportunity to eat more pasture if allocated more than required. This could result in more milk being produced, a gain in liveweight, and/or a higher post-grazing pasture residue (and hence potentially improve pasture regrowth). If less pasture than required was allocated to the control group, production could reduce or the cows might graze harder. Thus, in the control group the proportion of forage to supplement remained relatively constant, but intake varied in relation to pasture allocated, while for the adjusted group the total intake was kept relatively constant. In experiment 1 (ryegrass), the milk yield, percentage of milk fat and liveweight change of cows in the control and adjusted groups was not significantly different. However, the cows in the adjusted group produced 0.016 kg/cow.day more milk protein. As the control group ate 0.35 kg DM/cow.day more ryegrass pasture (P = 0.008) it is assumed that accurate daily allocation of feed improved feed efficiency. In experiment 2, the milk yield and percentage of milk protein of cows grazing kikuyu pastures was not significantly different between groups but the percentage of milk fat and covariate-corrected liveweight at the end of the experiment was higher in the control group than in the adjusted group. The pasture spared by cows in the adjusted group was predicted to produce 8.9% more milk when grazing ryegrass pasture and 12.3% when grazing kikuyu pasture. Linear regression analysis of pasture on offer on post-grazing pasture residue was not significant for the cows in the adjusted group but was significant for the control group cows when grazing either pasture, indicating success in accurately allocating supplementary feed to maintain a constant grazing pressure. The results of this study should assist dairy farmers in deciding whether the effort required to allocate feed accurately to dairy cows on a daily basis, is worthwhile.

Effects of age and liveweight at first calving on first lactation milk, protein and fat yield of Friesian heifers

This paper reports on both the individual and combined effects of age (AFC) and liveweight (LWFC) at first calving for Australian Holstein–Friesian heifers on first lactation production. One hundred and thirty-five Australian Holstein–Friesian heifers were allocated to 1 of 3 AFC treatments. Within each AFC treatment, heifers were randomly assigned to 1 of 3 LWFC treatments. Heifers in all groups grazed pasture and were supplemented when the quantity and quality of pasture was inadequate to meet growth requirements. Mean AFC and LWFC achieved were 25.1, 29.9 and 33.9 months and 498, 549 and 595 kg, respectively. Mean liveweight gains from 16 weeks of age to calving ranged from 0.45 to 0.71 kg/day, depending on treatment. The heifers calving at 33.9 months of age produced 6.6 and 12.3% more milk, 6.3 and 11.9% more protein and 5.4 and 12.2% more fat than those calving at 29.9 and 25.1 months of age at the end of their first 300 day lactation, respectively. The lower production of the younger cows was associated with decreased daily output rather than by shorter lactation length. Heifers averaging 595 kg at first calving produced 5.5% more milk, 8.4% more protein and 11.4% more fat than those averaging 498 kg in first lactation, respectively. The heifers averaging 621 kg LWFC and 34 months AFC had the highest production of the 9 treatment groups. Production was increased by 5.35 L milk, 0.19 kg protein and 0.23 kg fat for an additional 1 kg LWFC, respectively. For each month delay in AFC, production was increased by 66.7 L milk, 1.87 kg protein and 2.36 kg fat, respectively. The combined effects of AFC and LWFC showed that to offset the negative effects of a 1 month reduction in AFC on milk, protein and fat yields in first lactation, LWFC would have to be increased by 8.1, 4.0 and 4.5 kg, respectively. Under the conditions of this experiment, maximum milk, protein and fat were estimated to be achieved at 559, 563 and 568 kg liveweight at first calving, respectively.

Evaluation of rumen probe for continuous monitoring of rumen pH, temperature and pressure

The primary objective of this study was to evaluate the accuracy of a commercially available wireless rumen probe by Kahne Limited (New Zealand) for continuous pH, temperature and pressure measurements under different ruminal conditions. In a 4 by 4 latin square design, rumen-fistulated sheep were fed diets comprising 0, 30 or 60% concentrate, with the rest of the diet being balanced for metabolisable energy and protein with maize silage and lucerne hay. Each experimental period was 10 days with the first 8 days for adaptation and the last 2 days for collection of rumen fluid samples. In the first experimental period, probes were left in the rumen of sheep for 10 days to observe drift in pH. In the other three periods, probes were repeatedly cleaned and recalibrated before each sampling period. Probes were set to read every 20 min while the samples of rumen fluid were withdrawn manually at 4-h intervals and pH recorded immediately. There was an upward drift in pH observed after 48 h of insertion of probes into the rumen. This study resulted in a minor level of agreement between the two methods as indicated by higher root mean prediction error (0.43 pH units), lower Pearson’s correlation coefficient (r = 0.46) and concordance correlation coefficient (0.46). In conclusion, these rumen probes need further advancement to be potentially used for continuous rumen pH measurements for research purposes.