Improving farm profitability also reduces the carbon footprint of milk production in intensive dairy production systems

Primary beef cattle farming in South Africa is largely extensive, whereas dairy farming is based on both total mixed ration and pasture production systems. Under natural rangeland conditions, decomposition of manure is aerobic, which produces carbon dioxide (CO2), part of which is absorbed by the regrowth of vegetation rather than released into the atmosphere, and water (H2O) as end products. Thus the cow releases methane (CH4) and the manure CO2. This is in contrast to intensive cow-calf systems in large parts of Europe and North America, where large quantities of manure are stockpiled and undergo anaerobic decomposition and produce CH4. Thus both the cow and the manure release CH4, which result in a higher carbon footprint than the extensive cow-calf systems. In dairy farming, increasing cow efficiency through intensive feeding (same kg milk output by fewer animals) can reduce farm CH4 production by up to 15%. In addition, when differences in productivity are accounted for, pasture systems require more resources (land, feed, water, etc.) per unit of milk produced and the carbon footprint is greater than that of intensive systems. This raises the question as to why the carbon footprint of intensive dairy cow production systems is less, but the carbon footprint of intensive beef cow-calf production systems is higher. The explanation lies in the differences in production levels. In the case of beef cows the weight of the intensive cows will be ± 30% higher than that of the extensive cows, and the weaning weight of their calves will also differ by ± 30%. In the case of dairy cows the weight of the intensive cows will be ± 20% higher, but their milk production will be ± 60% higher. The higher increase in production (milk) of intensive dairy cows, compared to the increase in production (calf weight) of intensive beef cows, explains the antagonism in the carbon footprint between different beef and dairy production systems. Unfortunately, carbon sequestration estimates have been neglected and thus the quantitative effects of these differences are not known.Keywords: Cow-calf production, methane, pasture production, production levels, total mixed ration

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The effect of grazing season length on nitrogen utilization efficiency and nitrogen balance in spring-calving dairy production systems

The Journal of Agricultural Science ◽

10.1017/s002185961200010x ◽

2012 ◽

Vol 150 (5) ◽

pp. 630-643 ◽

Cited By ~ 7

Author(s):

W. RYAN ◽

D. HENNESSY ◽

T. M. BOLAND ◽

L. SHALLOO

Keyword(s):

Milk Production ◽

Production Systems ◽

Utilization Efficiency ◽

N Use Efficiency ◽

Dairy Production ◽

N Losses ◽

Grazing Season ◽

Use Efficiency ◽

Milk Solids ◽

N Use

SUMMARYThere is a continual requirement for grass-based production systems to optimize economic and environmental sustainability through increased efficiency in the use of all inputs, especially nitrogen (N). An N balance model was used to assess N use efficiency and N surplus, and to predict N losses from grass-based dairy production systems differing in the length of the grazing season (GS). Data from a 3-year grazing study with a 3×3 factorial design, with three turnout dates (1 February, 21 February and 15 March) and three housing dates (25 October, 10 November and 25 November) were used to generate estimates of N use efficiency and N losses. As the length of the GS increased by a mean of 30 days, milk production, milk solids production and milk N output increased by 3, 6 and 6%, respectively. The increase in milk production as the length of the GS increased resulted in a 2% decline in N surplus and a 5% increase in N use efficiency. Increasing GS length increased the proportion of grazed grass in the diet, which increased N cycling within the system, resulting in an 8% increase in milk solids/ha produced/kg of surplus N. The increased cycling of N reduced the quantity of N partitioned for loss to the environment by 8%. Reducing fertilizer N input by 20% increased N use efficiency by 22% and reduced total N losses by 16%. The environmental and production consequences of increased length of the GS and reduced N loss are favourable as the costs associated with N inputs increase.

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The carbon footprint of dairy production systems through partial life cycle assessment

Journal of Dairy Science ◽

10.3168/jds.2009-2162 ◽

2010 ◽

Vol 93 (3) ◽

pp. 1266-1282 ◽

Cited By ~ 169

Author(s):

C.A. Rotz ◽

F. Montes ◽

D.S. Chianese

Keyword(s):

Life Cycle Assessment ◽

Life Cycle ◽

Carbon Footprint ◽

Production Systems ◽

Dairy Production

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Context Specificity and Time Dependency in Classifying Sub-Saharan Africa Dairy Cattle Farmers for Targeted Extension Farm Advice: The Case of Uganda

Agriculture ◽

10.3390/agriculture11090836 ◽

2021 ◽

Vol 11 (9) ◽

pp. 836

Author(s):

Elizabeth Ahikiriza ◽

Joshua Wesana ◽

Xavier Gellynck ◽

Guido Van Huylenbroeck ◽

Ludwig Lauwers

Keyword(s):

Milk Production ◽

Large Scale ◽

Management Practices ◽

Production Systems ◽

Sub Saharan Africa ◽

Small Scale ◽

Dairy Production ◽

Extension Services ◽

Sub Saharan ◽

Productive Systems

Despite the huge potential for milk production, interventions to improve productivity in sub-Saharan Africa (SSA) are barely based on specified farm classifications. This study aimed to develop robust and context-specific farm typologies to guide content of extension farm advice/services in Uganda. From a sample of 482 dairy farmers, we collected data on farmer socio-demographics, farm management practices, ownership of farm tools and facilities, willingness to pay for extension services, milk production, and marketing. Farm typologies were obtained based on principal component and cluster analyses. Thereby, of the three dairy production systems that emerged, small-scale, largely subsistence yet extensive and low productive farms were more prominent (82.6%). Farms that were classified as large-scale, less commercialized yet extensive with modest productive systems were more than the medium-scale commercial farms with intensive and highly productive systems. However, the later were considered to potentially transform dairy farming in Uganda. It was also predicted that the validity of our farm classification may persist until half of the farms have moved between clusters. The study gives new insights on dairy production systems in Uganda, which can be used to organize more targeted research on farmers’ extension needs for facilitating delivery of relevant and effective extension services and designing appropriate extension policies.

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Information asymmetry among dairy producers in Paraná, Brazil

Semina Ciências Agrárias ◽

10.5433/1679-0359.2020v41n1p295 ◽

2020 ◽

Vol 41 (1) ◽

pp. 293

Author(s):

Marcela Casali ◽

Bruna Sesco de Mendonça ◽

Marcel Moreira de Brito ◽

Marcio Gregório Rojas dos Santos ◽

Pedro Gustavo Loesia Lima ◽

...

Keyword(s):

Information Asymmetry ◽

Milk Production ◽

Production Systems ◽

Common Factor ◽

Milk Quality ◽

Dairy Production ◽

Dairy Farmers ◽

The Past ◽

The Relationship ◽

Production Characteristics

Milk production has great social and economic importance in Paraná, Brazil. However, dairy farmers have abandoned the activity over the past few years because of difficulties in meeting institutional and market demands for increased milk production and quality. Information asymmetry between dairy farmers and market agents may be contributing to this scenario. It occurs when one agent in a transaction has more or better information than another. Information asymmetry can encourage opportunistic behavior and negatively affect the relationship between parties. These problems can be minimized or resolved by horizontal collaboration, such as participation in farmers’ organizations, cooperatives, or associations. The aim of this study was to assess the extent of information asymmetry among dairy farmers and investigate whether participation in farmers’ organizations strengthens buyer–seller relationships and stimulates compliance with milk quality standards. A total of 204 semi-structured questionnaires were applied to head farmers of dairy production systems in Paraná. Two sets of variables were analyzed: variables related to socio-economic and production characteristics and variables related to transactions between farmers and the dairy industry and the head farmer’s knowledge about milk quality regulations. The second set of variables was subjected to common factor analysis, which generated four factors: F1, knowledge about institutional requirements; F2, technical support from the buyer; F3, technical knowledge; and F4, level of trust in the buyer. Dairy farmers who did not participate in farmers’ organizations operated under greater information asymmetry and were disadvantaged with regard to F2, F3, and F4 (P < 0.05). Participation in horizontal collaborations can help farmers survive and thrive in the dairy activity.

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Assessment of the carbon footprint of four commercial dairy production systems in Australia using an integrated farm system model

Carbon Management ◽

10.1080/17583004.2017.1418595 ◽

2018 ◽

Vol 9 (1) ◽

pp. 57-70 ◽

Cited By ~ 5

Author(s):

Veerasamy Sejian ◽

R. Shyaam Prasadh ◽

Angela M. Lees ◽

Jarrod C. Lees ◽

Yaqoub A.S. Al-Hosni ◽

...

Keyword(s):

Carbon Footprint ◽

Production Systems ◽

System Model ◽

Dairy Production ◽

Farm System

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Effect of Nutritional Variation and LCA Methodology on the Carbon Footprint of Milk Production From Holstein Friesian Dairy Cows

Frontiers in Sustainable Food Systems ◽

10.3389/fsufs.2021.588158 ◽

2021 ◽

Vol 5 ◽

Author(s):

Margaret D. March ◽

Paul R. Hargreaves ◽

Alasdair J. Sykes ◽

Robert M. Rees

Keyword(s):

Milk Production ◽

Carbon Footprint ◽

Crude Protein ◽

Production Systems ◽

Climate Change Policy ◽

Ghg Emissions ◽

Economic Allocation ◽

Feed Digestibility ◽

Holstein Friesian ◽

Dairy Systems

The UK livestock industry urgently needs to reduce greenhouse gas (GHG) emissions to contribute to ambitious climate change policy commitments. Achieving this requires an improved understanding of emission sources across a range of production systems to lower the burden associated with livestock products. Life cycle assessment (LCA) methods are used in this study to model milk production from two genetic merits of Holstein Friesian cows managed in two novel and two conventional UK dairy systems. Select merit cows sired by bulls with high predicted transmission for fat plus protein yield are compared with Control merit animals sired from UK average merit bulls. Cows were managed in conventional housed and grazed dairy systems with novel Byproduct and Homegrown feeding regimes. A LCA was used to quantify the effect of allocation and management of feed components on the carbon footprint of milk production. Natural variation in nutritional quality of dairy system rations was investigated to quantify uncertainty in the carbon footprint results. Novel production system data are used to assess the effect of introducing home grown legumes and co-product feeds. Control merit footprints across each of the management regimes were significantly higher (p<0.001) in comparison with a high production Select merit, on average by 15%. Livestock emissions (enteric, manure management and deposition) and embedded emissions (purchased feeds, fertiliser, and pesticides) were also significantly higher from control merit cows (p<0.01). Mass and economic allocation methods, and land use functional units, resulted in differences in performance ranking of the dairy systems, with larger footprints resulting from mass allocation. Pairwise comparisons showed GHG's from the systems to be significantly different in total and source category emissions, with significant differences in mean embedded emissions found between most management systems (p<0.05). Monte Carlo simulated system footprints considering the effect of variation in feed digestibility and crude protein also differed significantly from system footprints using standard methods (p < 0.001). Dairy system carbon footprint results should be expressed using multiple units and where possible calculations should incorporate variation in diet digestibility and crude protein content.

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LIME AND DAIRY PRODUCTION

Proceedings of the New Zealand Grassland Association ◽

10.33584/jnzg.1982.43.1608 ◽

1982 ◽

pp. 93-103

Author(s):

N.A. Thomson

Keyword(s):

Soil Moisture ◽

Dairy Cows ◽

Milk Production ◽

Soil Ph ◽

Dairy Production ◽

Pasture Production ◽

The Third ◽

One Year ◽

Plasma Magnesium

In a four year grazing trial with dairy cows the application of 5000 kg lime/ ha (applied in two applications of 2500 kg/ha in winter of the first two years) significantly increased annual pasture production in two of the four years and dairy production in one year. In three of the four years lime significantly increased pasture growth over summer/autumn with concurrent increases in milk production. In the last year of the trial lime had little effect on pasture growth but a relatively large increase in milkfat production resulted. A higher incidence of grass staggers was recorded on the limed farmlets in spring for each of the four years. In the second spring immediately following the second application of lime significant depressions in both pasture and plasma magnesium levels were recorded. By the third spring differences in plasma magnesium levels were negligible but small depressions in herbage magnesium resulting from lime continued to the end of the trial. Lime significantly raised soil pH, Ca and Mg levels but had no effect on either soil K or P. As pH levels of the unlimed paddocks were low (5.2-5.4) in each autumn and soil moisture levels were increased by liming, these factors may suggest possible causes for the seasonality of the pasture response to lime

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