Effect of feeding intensity and milking system on nutritionally relevant milk components in dairy farming systems in the North East of England

There is increasing concern that the intensification of dairy production reduces the concentrations of nutritionally desirable compounds in milk. This study therefore compared important quality parameters (protein and fatty acid profiles; α-tocopherol and carotenoid concentrations) in milk from four dairy systems with contrasting production intensities (in terms of feeding regimens and milking systems). The concentrations of several nutritionally desirable compounds (β-lactoglobulin, omega-3 fatty acids, omega-3/omega-6 ratio, conjugated linoleic acid c9t11, and/or carotenoids) decreased with increasing feeding intensity (organic outdoor ≥ conventional outdoor ≥ conventional indoors). Milking system intensification (use of robotic milking parlors) had a more limited effect on milk composition, but increased mastitis incidence. Multivariate analyses indicated that differences in milk quality were mainly linked to contrasting feeding regimens and that milking system and breed choice also contributed to differences in milk composition between production systems.

A cross-sectional study of reproductive performance of smallholder dairy cows in coastal Tanzania

A retrospective cross-sectional study was conducted on 200 randomly selected smallholder farms from a mixed dairy farming system in Tanga, Tanzania, between January and April 1999. We estimated the frequency and determinants of long calving interval (LCI), retention of fetal membrane (RFM), dystocia, and abortion in smallholder crossbred cattle and explored birth trends. The mean calving interval was 500 days and birth rate was 65 per 100 cow-years. Dystocia was reported to affect 58% of calvings, and 17.2% of animals suffered RFM. Using mixed effect models, the variables associated with LCI, RFM and dystocia were breed, level of exotic blood and condition score. Zebu breeding was associated with LCI (odds ratio (OR) = 2.3, p = 0.041) and Friesian breeding with lower odds for RF (OR = 0.26, p = 0.020). Animals with higher levels of exotic blood had lower odds for evidence of dystocia (OR = 0.45, p = 0.021). Evidence of dystocia was significantly associated with poor condition score (beta = -1.10, p = 0.001). Our observations suggest that LCIs are common in smallholder dairy farms in this region and a likely source of economic loss. Dystocia, RFM, poor condition score and mineral deficiency were common problems and were possibly linked to LCI.

Dairy farmers’ attitudes and intentions towards improving dairy cow foot health

Dairy cow foot health is a subject of concern because it is considered to be the most important welfare problem in dairy farming and causes economic losses for the farmer. In order to improve dairy cow foot health it is important to take into account the attitude and intention of dairy farmers. In our study the objective was to gain insight into the attitude and intention of dairy farmers to take action to improve dairy cow foot health and determine drivers and barriers to take action, using the Theory of Planned Behavior. Five hundred Dutch dairy farmers were selected randomly and were invited by email to fill in an online questionnaire. The questionnaire included questions about respondents’ intentions, attitudes, subjective norms and perceived behavioral control and was extended with questions about personal normative beliefs. With information from such a framework, solution strategies for the improvement of dairy cow foot health can be proposed. The results showed that almost 70% of the dairy farmers had an intention to take action to improve dairy cow foot health. Most important drivers seem to be the achievement of better foot health with cost-effective measures. Possible barriers to taking action were labor efficiency and a long interval between taking action and seeing an improvement in dairy cow foot health. The feed advisor and foot trimmer seemed to have most influence on intentions to take action to improve dairy cow foot health. Most farmers seemed to be satisfied with the foot health status at their farm, which probably weakens the intention for foot health improvement, especially compared to other issues which farmers experience as more urgent. Subclinical foot disorders (where cows are not visibly lame) were not valued as important with respect to animal welfare. Furthermore, 25% of the respondents did not believe cows could suffer pain. Animal welfare, especially the provision of good care for the cows, was valued as important but was not related to intention to improve dairy cow foot health. The cost-effectiveness of measures seemed to be more important. Providing more information on the effects of taking intervention measures might stimulate farmers to take action to achieve improvement in dairy cow foot health.

Farming systems methodology for efficient resource management at the farm level: a review from an Indian perspective

Farming systems research is a multi-disciplinary holistic approach to solve the problems of small farms. Small and marginal farmers are the core of the Indian rural economy Constituting 0.80 of the total farming community but possessing only 0.36 of the total operational land. The declining trend of per capita land availability poses a serious challenge to the sustainability and profitability of farming. Under such conditions, it is appropriate to integrate land-based enterprises such as dairy, fishery, poultry, duckery, apiary, field and horticultural cropping within the farm, with the objective of generating adequate income and employment for these small and marginal farmers Under a set of farm constraints and varying levels of resource availability and Opportunity. The integration of different farm enterprises can be achieved with the help of a linear programming model. For the current review, integrated farming systems models were developed, by Way Of illustration, for the marginal, small, medium and large farms of eastern India using linear programming. Risk analyses were carried out for different levels of income and enterprise combinations. The fishery enterprise was shown to be less risk-prone whereas the crop enterprise involved greater risk. In general, the degree of risk increased with the increasing level of income. With increase in farm income and risk level, the resource use efficiency increased. Medium and large farms proved to be more profitable than small and marginal farms with higher level of resource use efficiency and return per Indian rupee (Rs) invested. Among the different enterprises of integrated farming systems, a chain of interaction and resource flow was observed. In order to make fanning profitable and improve resource use efficiency at the farm level, the synergy among interacting components of farming systems should be exploited. In the process of technology generation, transfer and other developmental efforts at the farm level (contrary to the discipline and commodity-based approaches which have a tendency to be piecemeal and in isolation), it is desirable to place a whole-farm scenario before the farmers to enhance their farm income, thereby motivating them towards more efficient and sustainable fanning.

Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets

Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.

Organic dairy production: A review

Organic farming aims to create an integrated, humane, environmentally and economically sustainable agricultural system. For organic dairy systems, the fulfilment of these aims requires the understanding and integration of a number of systems components including land use (mixed or dairy only) and stocking rate; grassland and forage production, including quantity and quality; potential milk yield and milk quality; animal nutrition (largely farm based) and health; environmental sustainability such as farm nutrient balance; the financial status of the farm, including enterprise performance, fixed costs and labour use, and farm income and profit; and finally the policy environment in which organic dairy systems operate. This review discusses worldwide research undertaken into each of these key components of organic dairy production systems. As converting organic dairy systems are often considerably different to established organic systems, both the converting and developed organic dairy system are discussed in this paper.

Identifying and understanding factors influencing the uptake of new technologies on dairy farms in SW England using the theory of reasoned action

Whilst much is known of new technology adopters, little research has addressed the role of their attitudes in adoption decisions; particularly, for technologies with evident economic potential that have not been taken up by farmers. This paper presents recent research that has used a new approach which examines the role that adopters' attitudes play in identifying the drivers of and barriers to adoption. The study was concerned with technologies for livestock farming systems in SW England, specifically oestrus detection, nitrogen supply management, and, inclusion of white clover. The adoption behaviour is analysed using the social-psychology theory of reasoned action to identify factors that affect the adoption of technologies, which are confirmed using principal components analysis. The results presented here relate to the specific adoption behaviour regarding the Milk Development Council's recommended observation times for heat detection. The factors that affect the adoption of this technology are: cost effectiveness, improved detection and conception rates as the main drivers, whilst the threat to demean the personal knowledge and skills of a farmer in 'knowing' their cows is a barrier. This research shows clearly that promotion of a technology and transfer of knowledge for a farming system need to take account of the beliefs and attitudes of potential adopters. (C) 2006 Elsevier Ltd. All rights reserved.

The inclusion of forage mixtures in the diet of growing dairy heifers: impacts on digestion, energy utilisation, and methane emissions

Intensive farming focusing on monoculture grass species to maximise forage production has led to a reduction in the extent and diversity of species-rich grasslands. However, plant communities with higher species number (richness) are a potential strategy for more sustainable production and mitigation of greenhouse gas (GHG) emissions. Research has indicated the need to understand opportunities that forage mixtures can offer sustainable ruminant production systems. The objective of the two experiments reported here were to evaluate multiple species forage mixtures in comparison to ryegrass-dominant pasture, when conserved or grazed, on digestion, energy utilisation, N excretion, and methane emissions by growing 10–15 month old heifers. Experiment 1 was a 4 × 4 Latin square design with five week periods. Four forage treatments of: (1) ryegrass (control); permanent pasture with perennial ryegrass (Lolium perenne); (2) clover; a ryegrass:red clover (Trifolium pratense) mixture; (3) trefoil; a ryegrass:birdsfoot trefoil (Lotus corniculatus) mixture; and (4) flowers; a ryegrass:wild flower mixture of predominately sorrel (Rumex acetosa), ox-eye daisy (Leucanthemum vulgare), yarrow (Achillea millefolium), knapweed (Centaurea nigra) and ribwort plantain (Plantago lanceolata), were fed as haylages to four dairy heifers. Measurements included digestibility, N excretion, and energy utilisation (including methane emissions measured in respiration chambers). Experiment 2 used 12 different dairy heifers grazing three of the same forage treatments used to make haylage in experiment 1 (ryegrass, clover and flowers) and methane emissions were estimated using the sulphur hexafluoride (SF6) tracer technique. Distribution of ryegrass to other species (dry matter (DM) basis) was approximately 70:30 (clover), 80:20 (trefoil), and 40:60 (flowers) for experiment 1. During the first and second grazing rotations (respectively) in experiment 2, perennial ryegrass accounted for 95 and 98% of DM in ryegrass, and 84 and 52% of DM in clover, with red clover accounting for almost all of the remainder. In the flowers mixture, perennial ryegrass was 52% of the DM in the first grazing rotation and only 30% in the second, with a variety of other flower species occupying the remainder. Across both experiments, compared to the forage mixtures (clover, trefoil and flowers), ryegrass had a higher crude protein (CP) content (P < 0.001, 187 vs. 115 g kg −1 DM) and DM intake (P < 0.05, 9.0 vs. 8.1 kg day −1). Heifers in experiment 1 fed ryegrass, compared to the forage mixtures, had greater total tract digestibility (g kg −1) of DM (DMD; P < 0.008, 713 vs. 641) and CP (CPD, P < 0.001, 699 vs. 475), and used more intake energy (%) for body tissue deposition (P < 0.05, 2.6 vs. −4.9). For both experiments, heifers fed flowers differed the most compared to the ryegrass control for a number of measurements. Compared to ryegrass, flowers had 40% lower CP content (P < 0.001, 113 vs. 187 g kg −1), 18% lower DMD (P < 0.01, 585 vs. 713 g kg −1), 42% lower CPD (P < 0.001, 407 vs. 699 g kg −1), and 10% lower methane yield (P < 0.05, 22.6 vs. 25.1 g kg −1 DM intake). This study has shown inclusion of flowers in forage mixtures resulted in a lower CP concentration, digestibility and intake. These differences were due in part to sward management and maturity at harvest. Further research is needed to determine how best to exploit the potential environmental benefits of forage mixtures in sustainable ruminant production systems.

Did farming arise from a misapplication of social intelligence?

The origins of farming is the defining event of human history-the one turning point that has resulted in modern humans having a quite different type of lifestyle and cognition to all other animals and past types of humans. With the economic basis provided by farming, human individuals and societies have developed types of material culture that greatly augment powers of memory and computation, extending the human mental capacity far beyond that which the brain alone can provide. Archaeologists have long debated and discussed why people began living in settled communities and became dependent on cultivated plants and animals, which soon evolved into domesticated forms. One of the most intriguing explanations was proposed more than 20 years ago not by an archaeologist but by a psychologist: Nicholas Humphrey suggested that farming arose from the 'misapplication of social intelligence'. I explore this idea in relation to recent discoveries and archaeological interpretations in the Near East, arguing that social intelligence has indeed played a key role in the origin of farming and hence the emergence of the modern world.