S. C. Garcia

Simulating pasture growth rates in Australian and New Zealand grazing systems

DairyMod, EcoMod, and the SGS Pasture Model are mechanistic biophysical models developed to explore scenarios in grazing systems. The aim of this manuscript was to test the ability of the models to simulate net herbage accumulation rates of ryegrass-based pastures across a range of environments and pasture management systems in Australia and New Zealand. Measured monthly net herbage accumulation rate and accumulated yield data were collated from ten grazing system experiments at eight sites ranging from cool temperate to subtropical environments. The local climate, soil, pasture species, and management (N fertiliser, irrigation, and grazing or cutting pattern) were described in the model for each site, and net herbage accumulation rates modelled. The model adequately simulated the monthly net herbage accumulation rates across the range of environments, based on the summary statistics and observed patterns of seasonal growth, particularly when the variability in measured herbage accumulation rates was taken into account. Agreement between modelled and observed growth rates was more accurate and precise in temperate than in subtropical environments, and in winter and summer than in autumn and spring. Similarly, agreement between predicted and observed accumulated yields was more accurate than monthly net herbage accumulation. Different temperature parameters were used to describe the growth of perennial ryegrass cultivars and annual ryegrass; these differences were in line with observed growth patterns and breeding objectives. Results are discussed in the context of the difficulties in measuring pasture growth rates and model limitations.

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.

Description and evaluation of the Farmax Dairy Pro decision support model

Abstract Decision support models have been developed to assist management in dairy systems. This paper describes Farmax Dairy Pro (a pastoral grazing model of a dairy farm) and presents an evaluation of it using two independent farmlet studies carried out in Hamilton and Palmerston North, New Zealand with spring-calving dairy cows. Farmax Dairy Pro predicted, to a high degree of accuracy, mean annual yields (per cow and per hectare) for milk, fat, protein and milksolids (MS; fat + protein) and mean annual concentrations of MS. Monthly predictions were predicted with less accuracy than whole lactation values, but still with moderate degrees of accuracy compared with other comparable models. The general trajectory over time of yield and MS concentration was predicted well for all datasets, but in some instances the model over or under predicted the degree of variation between months. The trajectory of body condition score over time was reliably simulated in early lactation but with some discrepancies in late lactation. The model was then used to determine if it was possible to achieve 1750 kg MS/cow per ha using forages grown within the milking area for the Hamilton study. Managerial changes represented in the model, which included earlier calving dates, use of a chicory crop and additional intakes of pasture in summer, predicted increases in performance of 50–190 kg MS/ha, still at least 81 kg MS/ha short of the target level of production. Farmax Dairy Pro can be used to predict animal, farm and financial performance for different management scenarios.

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.

Invited review: An evaluation of the likely effects of individualized feeding of concentrate supplements to pasture-based dairy cows

In pasture-based dairy systems, supplementary feeds are used to increase dry matter intake and milk production. Historically, supplementation involved the provision of the same amount of feed (usually a grain-based concentrate feed) to each cow in the herd during milking (i.e., flat-rate feeding). The increasing availability of computerized feeding and milk monitoring technology in milking parlors, however, has led to increased interest in the potential benefits of feeding individual cows (i.e., individualized or differential feeding) different amounts and types of supplements according to one or more parameters (e.g., breeding value for milk yield, current milk yield, days in milk, body condition score, reproduction status, parity). In this review, we consider the likely benefits of individualized supplementary feeding strategies for pasture-based dairy cows fed supplements in the bail during milking. A unique feature of our review compared with earlier publications is the focus on individualized feeding strategies under practical grazing management. Previous reviews focused primarily on research undertaken in situations where cows were offered ad libitum forage, whereas we consider the likely benefits of individualized supplementary feeding strategies under rotational grazing management, wherein pasture is often restricted to all or part of a herd. The review provides compelling evidence that between-cow differences in response to concentrate supplements support the concept of individualized supplementary feeding.

Lactation curves of autumn- and spring-calved cows in pasture-based dairy systems

A linear-based and a non-linear-based method for the analysis of lactation curves were evaluated in this study to investigate the effects of calving season on the shape and length of the lactation curve, total milk yield, milk composition and somatic cell counts of autumn- and spring-calved cows. Lactation records from a 3-year systems study in which cows calved either in the autumn or in the spring, were analysed by either split-plot analysis of test-day data, or by fitting the diphasic equation of Grossman and Koops [J. Dairy Sci., 71 (1988) 1598–1608] prior to analysis by linear models. Average lactation curves produced by both methods were similar. Lactation curves of spring-calved cows were ‘normal’, with a peak followed by a steady decline. However, lactation curves of autumn-calved cows were different in shape, with lower yields at peak of lactation but higher yields in mid and late lactation, which resulted in a significant interaction (P<0.01) between calving season and stage of lactation. The greater yields in mid and late lactation by the autumn-calved cows, together with their longer lactations (despite the fact that the same guidelines were applied for deciding the drying-off of all cows), resulted in greater total milk yields for these cows. Somatic cell counts were greater (P<0.05) in mid and late lactation for the spring-calved cows than for the autumn-calved cows, due probably to a dilution effect. A conceptual model is presented, in which the observed differences in the shapes of the lactation curves of autumn- and spring-calved cows are referred to the cows’ potential yield.

Seasonality of calving in pasture-based dairy systems: its effects on herbage production, utilisation and dry matter intake

The objectives of the present work were to evaluate the influence of season of calving on (i) pasture productivity, (ii) total dry matter intake by cows, and (iii) the relationship between intake and milk yield of individual cows. Three systems in which the cows calved either in autumn, in spring or half in autumn, half in spring, were managed according to a set of common guidelines during 3 consecutive years. Herbage accumulation rate (HAR) was estimated by the difference between 2 successive grazings (pre- and post-grazing herbage mass). Average HAR in each month was similar between systems. However, small differences in HAR were observed between calving systems in spring and summer, and appeared to be related to the proportion of the farmlet closed for silage. Herbage dry matter intakes varied seasonally (P 0.05). Cows from different calving systems, offered 8.9 or 2.5 kg maize silage dry matter per cow daily in the paddocks, consumed an average of 6.0 and 1.4 kg, respectively. A large variation in intake was observed between individual cows with ranges from 2 to 10 kg and 0.2 to 2.9 kg, respectively. In conclusion, applying the same grazing management decisions to systems with contrasting calving dates resulted in only small seasonal, but not annual, differences in pasture HAR. The results also indicated that when maize silage is fed in the paddock, wastage can be high and variation in intake between individual cows can also be large.

Complementary forages – integration at a whole-farm level

A high proportion of the Australian and New Zealand dairy industry is based on a relatively simple, low input and low cost pasture feedbase. These factors enable this type of production system to remain internationally competitive. However, a key limitation of pasture-based dairy systems is periodic imbalances between herd intake requirements and pasture DM production, caused by strong seasonality and high inter-annual variation in feed supply. This disparity can be moderated to a certain degree through the strategic management of the herd through altering calving dates and stocking rates, and the feedbase by conserving excess forage and irrigating to flatten seasonal forage availability. Australasian dairy systems are experiencing emerging market and environmental challenges, which includes increased competition for land and water resources, decreasing terms of trade, a changing and variable climate, an increasing environmental focus that requires improved nutrient and water-use efficiency and lower greenhouse gas emissions. The integration of complementary forages has long been viewed as a means to manipulate the home-grown feed supply, to improve the nutritive value and DM intake of the diet, and to increase the efficiency of inputs utilised. Only recently has integrating complementary forages at the whole-farm system level received the significant attention and investment required to examine their potential benefit. Recent whole-of-farm research undertaken in both Australia and New Zealand has highlighted the importance of understanding the challenges of the current feedbase and the level of complementarity between forage types required to improve profit, manage risk and/or alleviate/mitigate against adverse outcomes. This paper reviews the most recent systems-level research into complementary forages, discusses approaches to modelling their integration at the whole-farm level and highlights the potential of complementary forages to address the major challenges currently facing pasture-based dairy systems.