Benchmarking consumptive water use of bovine milk production systems for 60 geographical regions: An implication for Global Food Security

Sultana, M. N.; Uddin, MT; Ridoutt, Bradley G.; Hemme, Torsten; Peters, Kurt J.

doi:10.1016/j.gfs.2014.08.006

Cited by 18 publications

(9 citation statements)

References 22 publications

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“…In general, this method tends to predict higher water use than diet optimization models likely because additional water requirements are allocated to livestock products. Global average dairy water use has been estimated at 1.83 m 3 /kg with a range of 0.74 to 5.6 m 3 /kg (Sultana et al, 2015). The baseline water use value in the present study was well within this range (1.10 m 3 /kg) but substantially lower than the values of Mekonnen and Hoekstra (2010).…”

Section: Evaluating Baseline Performancesupporting

confidence: 49%

Increasing energy and protein use efficiency improves opportunities to decrease land use, water use, and greenhouse gas emissions from dairy production

White

2016

Agricultural Systems

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The objectives of this study were to construct a farm-scale diet optimization model to identify opportunities to reduce land use, water use, and greenhouse gas (GHG) emissions within dairy production systems and to assess how improved energy and protein use efficiency affect opportunities to reduce these environmental impacts (EI) of dairy production systems. Non-linear programming was used to adjust monthly diets fed to 10 cattle groups to minimize EI associated with an average United States dairy farm. System boundaries extended from the inputs to the cropping system to the dairy farm gate. The effects of improved feed efficiency were modeled as a 15% decrease in maintenance energy or metabolizable protein requirements. Least-cost optimization was used as a baseline. A total of 28 scenarios were simulated which varied in objective, biological efficiency, and allowable cost increase. Objectives included minimizing land, water, or GHG emissions individually or all together. Biological efficiencies reflected either currently achieved efficiencies, improved energy efficiency, improved protein efficiency or improved energy and protein efficiency. Allowable cost increases were adjusted from 1% to 20% above baseline. Baseline land use (1.20 m 2 /kg milk), water use (1.10 m 3 /kg) and GHG emissions (0.70 kg CO 2 e/kg) agreed with established values for U.S. dairies. Within the allowable cost range, EI metrics could be simultaneously reduced by 4.4 to 25.5%. When both energy and protein efficiency were improved, land use, water use, and GHG emission reductions ranged from 23.4 to 35.5%. Diminishing environmental returns to cost increases were apparent. Cost of achieving a 25% reduction in the environmental impacts considered in this study was decreased 78.9% when energy and protein efficiency improved compared with the national average production efficiency scenario. Improving energy-and protein-use efficiency of dairy cattle represents a promising way to reduce land use, water use, and GHG emissions without sacrificing profitability.

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Section: Evaluating Baseline Performancesupporting

confidence: 49%

Increasing energy and protein use efficiency improves opportunities to decrease land use, water use, and greenhouse gas emissions from dairy production

White

2016

Agricultural Systems

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“…There are regional differences in the consumptive water use associated with livestock products (Mekonnen and Hoekstra, 2012;Gerbens-Leenes et al, 2013;Sultana et al, 2015) as a consequence of differences in production systems and their productivity. Sultana et al (2015) reported values for water use per unit of energy-corrected milk in Africa and Asia that were about 3 times greater than in North America, reflecting differences in milk yield and feeding systems. Some of the earlier attempts to approximate water use per product resulted in values that were considerably greater than recent estimates (Thomas, 1987;Pimentel et al, 1997).…”

Section: Comparison Of Ruminant Water Use Estimatesmentioning

confidence: 99%

BOARD-INVITED REVIEW: Quantifying water use in ruminant production1

Legesse

Ominski

Beauchemin

et al. 2017

Journal of Animal Science

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ABSTRACT:The depletion of water resources, in terms of both quantity and quality, has become a major concern both locally and globally. Ruminants, in particular, are under increased public scrutiny due to their relatively high water use per unit of meat or milk produced. Estimating the water footprint of livestock production is a relatively new field of research for which methods are still evolving. This review describes the approaches used to quantify water use in ruminant production systems as well as the methodological and conceptual issues associated with each approach. Water use estimates for the main products from ruminant production systems are also presented, along with possible management strategies to reduce water use. In the past, quantifying water withdrawal in ruminant production focused on the water demand for drinking or operational purposes. Recently, the recognition of water as a scarce resource has led to the development of several methodologies including water footprint assessment, life cycle assessment, and livestock water productivity to assess water use and its environmental impacts. These methods differ with respect to their target outcome (efficiency or environmental impacts), geographic focus (local or global), description of water sources (green, blue, and gray), handling of water quality concerns, the interpretation of environmental impacts, and the metric by which results are communicated (volumetric units or impact equivalents). Ruminant production is a complex activity where animals are often reared at different sites using a range of resources over their lifetime. Additional water use occurs during slaughter, product processing, and packaging. Estimating water use at the various stages of meat and milk production and communicating those estimates will help producers and other stakeholders identify hotspots and implement strategies to improve water use efficiency. Improvements in ruminant productivity (i.e., BW and milk production) and reproductive efficiency can also reduce the water footprint per unit product. However, given that feed production makes up the majority of water use by ruminants, research and development efforts should focus on this area. More research and clarity are needed to examine the validity of assumptions and possible trade-offs between ruminants' water use and other sustainability indicators.

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“…Until today, there is no specific farm type which is established by national authority, the prevailing farm type, hence, varies from the viewpoint of the researchers (Khan et al 2009;Uddin et al, 2010;Uddin et al 2012, Sultana et al 2015Huque 2014;BBS, 2018;Islam et al 2019,). For livestock, more specifically dairy, farm is generally classified based on total livestock per farm which are small, medium and large but the number of the livestock per farm is not same and varies in different study (Khan et al 2009;Datta et al 2018 andIslam et al 2019).…”

Section: Resultsmentioning

confidence: 99%

“…The IFCN is a global network that connects 80 research partners from 120 countries and 110 dairy companies under the auspices of university of Kiel, Germany (IFCN, 2019). This network has strong tools and models for analyzing complete picture of dairy sector, dairy market, dairy farm, production systems, feeding system, market integration, forecasting production, demand, and market outlook (Hagemann et al 2011;Hemme et al 2014;Uddin et al 2017;Sultana et al 2014;Sultana et al 2015). This model clustering on herd structure, dairy farm within herd size class, milk production at global and regional level.…”

Section: )mentioning

confidence: 99%

Reducing dairy data inconsistency through Regional Modeling Approach (RMA): a case from North-Western part of Bangladesh

Uddin

Akter

Tanzin

et al. 2021

Bang. J. Anim. Sci.

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In Bangladesh, the transformation of dairy farming from livelihood-oriented to enterprise-driven farming system might require deeper understanding on the regional differences in terms of regional potential for further dairy development. This, however, entails detailed data on dairy farm at regional level. Since the data are relatively very scarce in one hand and on the other hand, even available, are contradicting among various sources in terms of data accuracy and precision, the application of the regional modeling on the data and extrapolates to the national data and vice-versa is one of the ways to identify the possible options to improve the data availability and quality. Considering this, the current study was undertaken to assess the data inconsistency by comparing the dairy herd structure and its milk production at regional level and propose a validation tool to arrive at the national data by using the regional findings. The International Farm Comparison Network (IFCN) Regional Modeling Approach (RMA) along with the locally developed Integrated Dairy Research Network (IDRN) farm model was used. The primary data was collected from three divisions (9 districts) from the North-Western part of the country. The results revealed that proportion of household farm dominates over family and business farm while considering the total dairy cow as unit for defining the farm type. The share of the cross bred cows to the local cows is 74.6% and 24.4%, respectively. However, the proportion of lactating cows over dry cows and heifer seems to be higher in local cows (48.8%) than cross breed cows (34.2%). The average milk production for all regions is 4.49 lit/day/cow while that for cross breed is 6.23 lit and local 1.71 lit/day/cow. Using regional model and its coefficient on average milk production, herd composition, proportion of lactating cows on total milk production of DLS and IDRN revealed that IDRN new model estimates 36.5% lower milk than the DLS in 2019 and 33.5% lower in 2018. The IDRN version 1.0 and 2.0 model difference was found to 15.4% and 18.3% lower for 2018 and 2019, respectively. The model setup, calibration and validation are time-demanding and challenging tasks for these large set of data, given the scale intensive data requirements, and the need to ensure the reliability data from multiple regions. This study concludes that regional modeling is quite useful for validating the regional share of the milk production and national milk production. However, this study would recommend for using standardized for data collection, validation and thus conducting further study on the other regions and finally including all regions of the country. Bang. J. Anim. Sci. 2020. 49 (2): 128-141

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Benchmarking consumptive water use of bovine milk production systems for 60 geographical regions: An implication for Global Food Security

Cited by 18 publications

References 22 publications

Increasing energy and protein use efficiency improves opportunities to decrease land use, water use, and greenhouse gas emissions from dairy production

Increasing energy and protein use efficiency improves opportunities to decrease land use, water use, and greenhouse gas emissions from dairy production

BOARD-INVITED REVIEW: Quantifying water use in ruminant production1

Reducing dairy data inconsistency through Regional Modeling Approach (RMA): a case from North-Western part of Bangladesh

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