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Water use in Global Dairy Farming Systems and lessons for breeding policies for dairy production

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This presentation was held by N.Sultana & K.J. Peters at the interntional seminar 'Livestock Resources for Food Security in the Light of Climate Change' co-hosted by SIANI and SLU Global in Uppsala on the 11th of March 2016.

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Water use in Global Dairy Farming Systems and lessons for breeding policies for dairy production

  1. 1. Water use in Global Dairy Farming Systems and lessons for breeding policies for dairy production Results of a research project in collaboration with IFCN-Dairy N.Sultana, K. J.Peters Humboldt Universität zu Berlin k.peters@agrar.hu-berlin.de
  2. 2. Importance of water in animal agriculture Agriculture: uses 85% of the present global freshwater consumption, of which 29% by Livestock (Mekonnen and Hoekstra, 2012) 75% for Irrigation (Shilklomanov, 2000)
  3. 3. 2. Increase food production, agricultural pollution 1. Human population. 65 % increase (3.7 mrd) by 2050 (Wallace, 2000) Future challenges Importance of water in animal agriculture 4. Climate change impact on rainfall distribution pattern • 19 to 35% decrease in water availability for agriculture • Increase water scarcity for human population from 7% to 67% 3. Urbanization and industrial, increase in water use and pollution
  4. 4. WSI = Water Scarcity Index (Pfister et al. 2009. Assessing the environmental impacts of freshwater consumption in LCA. Environ. Sci. Technol. 43 (11), 40984104) Water Stress Index 0 <= 0.2 0.2 <= 0.4 0.6<= 0.7 0.7 <= 0.1 Low Moderate Severe Extreme National Water Scarcity Index (WSI) Water scarcity measured : Total annual freshwater withdrawals / hydrological availability. WSI indicates the portion of CWU depriving other users of freshwater. Holistic view of current water scarcity by region
  5. 5. 1. Around 1.2 mrd people live in areas of physical scarcity and 500 million people are close to it 2. Another 1.6 mrd people face economic water shortage (where countries lack the necessary infrastructure to take water from rivers and aquifers) 3. Though planet water does not change freshwater is distributed unevenly and too much of it is wasted, polluted and unsustainably managed. Sources: Human Development Report 2006. UNDP, 2006 Coping with water scarcity. Challenge of the twenty-first century. UN- Water, FAO, 2007. Effects of current water scarcity
  6. 6. Holistic view of water scarcity problem by regions Source: IWMI = International Water Management Institute, 2007. Economic water scarcity: • <25% of water withdrawn from rivers for human purposes but not enough water infrastructure to make water available for use Physical water scarcity: • >75% of river flows are withdrawn for agriculture, industry and domestic purposes. Water scarcity measures: freshwater available for human requirements implies that dry areas are not Necessarily water scarce).
  7. 7. Water availability and dairying Dairy production highly depenend on water in its various forms Important to know the water demand of a dairy system USA EthiopiaArgentina China Bangladesh India India
  8. 8. Milk production 2011 in mill tons ECM EU-27 153 84 34 30 10 21 42 138 32 11 Milk volumes cows & buffalo milk –standardized to 4% fat and 3,3% protein Status of current milk production Milk production in mill. tonnes Milk production 2011 = IFCN ( International Farm Comparison Network) Milk delivered to processor Milk not delivered to processor
  9. 9. Water footprint definition • A water footprint is measured in terms of the volume of water consumed, evaporated and polluted. • Three corresponding categories (Water Footprint Network) Blue Water Footprint: The amount of surface water and groundwater required (evaporated or used directly) to make a product. Green Water Footprint: The amount of rainwater required (evaporated or used directly) to make a product. Grey Water Footprint: The amount of freshwater required to mix and dilute pollutants enough to maintain water quality according to certain standards as a result of making a product.
  10. 10. Consumptive Water Use • Measures Green and blue water • removed from a local hydrological system • without return to a water system (e.g. water used in manufacturing and agriculture) • Indirectly includes grey water Water footprint methods Is a incomplete Water Foot print
  11. 11. Water footprint methods The Water Footprint Network (WFN) method – accounts for the virtual water and is an indicator of direct and indirect Water Use Volume (green, blue, grey) However – Simple combination of hypothetical pollution volume (grey) with water consumption (blue) is not meaningful – Inclusion of green water in the WF is misleading, since it does not fully affect the water cycle and is rather an indicator of land use Pfister, St. and Ridoutt, B.R. 2013, Environmental Science & Technology 48 (1):4-4
  12. 12. Water footprint methods The LCA - Water use impact (ISO 14046,2010, standard approach) – Accounts for blue water grey water and its water scarcity related impacts of pollutants expressed as water equivalent along the whole LC (H2Oe) Pfister, St. and Ridoutt, B.R. 2013, Environmental Science & Technology 48 (1):4-4
  13. 13. • Types of water consideration (e.g. rainfall, stored water in surface and ground, polluted water) • Concept of water use in farming systems • Defining goals and interpretation problem 2. Lack of consistent approach e.g. Classical or volumetric Impact assessment based approach International Standard Method which is under Development (ISO, 14046, 2013) Methodological challenges in water research Materials and methods
  14. 14. 1. Application of consumptive water use (CWU) and its drivers 2. Application of Water use impact 3. Evaluating differences between Consumptive water use and Water use impact (WF) Application of different WF methods in diverse dairy systems
  15. 15. Steps in our study to measure water use 3. Comparison of Water use assessment method IFCN: International Farm Comparison Network method. TIPI-CAL: Technology Impact and Policy Impact Calculation Represent the most common farming system within the regions Average management & performance & high proportion of milk in the region 1. Selection of typical farm within the IFCN-Dairy Net Typical farm data are collected at farm level 2. System boundary
  16. 16. Drinking and servicing water Concentrate, by-products and roughage Fuel, Electricity Fertilizer, pesticides External inputs Internal farm inputs Total feed and fodder Water for feed mixing Buildings and dairy implements Co- products: beef and manure Heifers Dairy cows Functional unit: 1 kg energy corrected milk (ECM) Farm grown feed (main product and by-products) 2. System boundary (Cradle –to Farm Gate) ECM = Energy Corrected Milk which is standardized by 4% fat and 3.3% protein Materials and methods
  17. 17. Application of Consumptive Water use (CWU) method (as in Hemme et al, 2010) 60 typical farms from 60 dairy regions of 49 countries and 6 selected dairy systems Application and comparison of CWU (WFN, 2010) and LCA-based water use impact (WF) (after Ridoutt and Pfister, 2010) 12 typical farming systems from 12 geographical regions Comparison of Water use assessment methods Materials and methods
  18. 18. 0 1000 2000 3000 4000 5000 6000 NO-20 CH-23 FI-25 AT-22 DE-31S DE-95N DE-85E NL-76 BE-40N LU-51 FR-39MC FR-50W ES-50NW IT-154 UK-146NW IE-48 DK-128 SE-55 PL-15 CZ-425 RS-2 UA-150 BY-1 BY-608 RU-1063 CA-58 US-80WI US-350WI US-66NY AU-275WA NZ-348 MX-15 AR-170 UY-119 PY-45 CL-47 BR-20S BR-120PR PE-7 TN-4 DZ-6 MA-3N EG-2 UG-3 NG-5 CM-35 ZA-422 AM-10A IL-67 JO-75 IR-90 IN-2W IN-13W IN-2S PK-5 BD-2 ID-3NG ID-3JA CN-17BE CN-6IM CWU(L/kgECM) S. America Africa Asia C. and E. Europe Western EuropeRegions *Typical farms N.America Oceania CWU for feed CWU for other inputs Mean (St. Dev.) 1771 (±1035) 62 (±45) Min (Max.) 706 (5400) 31 (304) Application of Consumptive Water use (CWU) method in dairy farms = CWU for feed = CWU for other inputs
  19. 19. Relation between consumptive water use and milk yield (kg ECM/cow/year) y = -0.1168x + 1849.7 R² = 0.68 0 500 1000 1500 2000 0 5000 10000 15000 CWU(LH20/kgECM) Milk yield Europe y = -0.2038x + 3777.1 R² = 0.31 0 1000 2000 3000 4000 5000 6000 0 10000 20000 CWU(LH20/kgECM) Milk yield Asia and Africa y = -0.1601x + 2466.4 R² = 0.65 0 500 1000 1500 2000 2500 3000 0 5000 10000 15000 CWU(LH20/kgECM) Milk yield USA and Oceania Major results
  20. 20. Production system Intensive Grazing Small-scale Variable Unit DE-95N US-350WI NZ-348 BR-20SC EG-2 BD-2 Breed HF HF HF CB EB Local Farm land ha 90 270 130 18 0 0 Grazing hrs./day 0 0 12 12 0 0 Climate Mild with no dry season Humid, severe winter Mild, no dry season Mild with dry winter Desert area Monsoon Rainfall mm/m2 850 860 1250 1300 250 1800 T. (Mean) (°C) 12 15 15 27 32 28 Consumptive water use in selected dairy systems Background information HF = Holstein Friesian; CB = Crossbred; EB: Egyptial Buffaloes
  21. 21. 75% 80% 85% 90% 95% 100% DE-95N US-350WI NZ-348 BR-20SC EG-2 BD-2 Intensive Grazing Small-scale 0 500 1000 1500 2000 2500 3000 3500 4000 DE-95N US-350WI NZ-348 BR-20SC EG-2 BD-2 CWU(LH20/kgECM) Feed production & mixing Drnking Servicing Farm manufacturing inputs Capital goods Intensive Grazing Small-scale Consumptive water use in selected dairy systems CWU = Consumptive water use FEED Pasture based Concentrate, by-product + crop residues Maize + concentrate based Major results Drinking
  22. 22. Conclusion on consumptive water use • The world average CWU 1833 L/kg ECM (range: 739 to 5622), with large inter- and intra-regional differences • Feed is the highest single input to CWU 96-99% water • Lower CWU associated with high productivity and farm based feeding systems • Rather high CWU in pasture based systems • Highest CWU associated with low productivity and higher concentrate feeding
  23. 23. Comparison of CWU and LCA-based water use impact (WF) 1. Volume of water use based on volumetric approach (CWU) 2. Water use impact assessment including water scarcity with Life cycle assessment (LCA) approach
  24. 24. Blue and grey water volumes 0 250 500 750 1000 US-350WI DE-95N CN-17BE JO-75 NZ-348 BR-25SE AR-170 ZA-422 EG-5 IN-2S MX-15 BD-2 LH2O/kgECM Intensive Grazing Small-scale Blue water Grey water Major Results
  25. 25. Major Results H2Oe = Water equivalent; WSI = Water Scarcity Index WF (H2Oe) = Water use impact (WF) based on LCA method a) Blue & grey water volumes considering water scarcity 0 200 400 600 800 1000 1200 1400 1600 US-350WI DE-95N CN-17BE JO-75 NZ-348 BR-25SE AR-170 ZA-422 EG-5 IN-2S MX-15 BD-2 LH2Oe/kgECM Intensive Grazing Small-scale 0,00 0,20 0,40 0,60 0,80 1,00 US-350WI DE-95N CN-17BE JO-75 NZ-348 BR-25SE AR-170 ZA-422 EG-5 IN-2S MX-15 BD-2 m³/m³ National WSI Local WSI Intensive Grazing Small-scale b) Water scarcity of production area
  26. 26. Consumptive water use • The world average CWU 1833 L/kg ECM with huge variability (ranging from 739 to 5622) • Feed is the main contributer more than 96% of total CWU • Lower CWU associated with high productivity and farm based feeding systems Water use impact (WF) • Lower WF associated with pasture based system where water scarcity is low • Higher WF associated with land less system based on external concentrate supply, and where water scarcity is higher Planning of dairy production system should include assessment of water foot print and water returns Home messages
  27. 27. Method perspective • The summation of water volumes is not a comprehensive tool for assessing water productivity • Water use impact assessment considering degradative water use and water scarcity is a more appropriate tool for assessing impact of water use Reasons of WF variation • Due to interaction effects among the regional water scarcity where production occurs, with amount of degraded water, feeding system and feed efficiency Dairying in areas with high concentrate feed input in water scarce region is a hotspot of adding to water problem Home messages (cont.)
  28. 28. Translation of these findings into dairy planning 1. Assessment of water availability and water scarcity 2. Assessment of the appropriate feeding system for a dairy production system pasture, forage, crop-residues, agro-industrial by-products, LCA grain concentrate LCA WF Lower larger 3. Assessment of appropriate performance and production efficiency level 4. Define breeding policy
  29. 29. Thank you so far! and now we need to decide if we can spare time to consider breeding option for smallholders in Ethiopia
  30. 30. The case of Dairying in Ethiopia Diverse dairy production systems: 1. Commercial Peri-urban dairy systems partly with own Value Chain (liquid milk and processed products) 2. Semi-commercial Peri-urban and Rural mixed farming systems with linkage to milk collection systems (liquid milk , but also butter and trad. cheese) 3. Extensive Rural mixed farming systems (Trad. Butter and trad. cheese) 4. 99.2 % of the 27 mill. cows are indigenous breeds with a low milk yield, few selected indigenous dairy breeds 129 thousand are cross (0.61 %) and exotic breeds (0.11%); 32 thousand cows with small holders.
  31. 31. Commercial Peri-urban dairy systems Purebred and grade dairy cows, medium high yield Modern dairy production and processing technics Agro-industrial by-products and concentrates Mais silage, Hay AI service with own technicians
  32. 32. Semi-commercial systems crossbred cows of different grade, medium yield Crop-residues, grazing, hay and agro-industrial by- products AI service only in well organized Dairy coops, otherwise village bull service
  33. 33. Extensive small scale mixed farming systems -Indigenous cows or low grade crossbreds, low yield -Crop-residues, hay, grazing, small amount of by- products -AI service not available, -only NM with available bulls
  34. 34. Agro-ecological breeding policy ,Yilma zelalem,,G.B., Emannuelle aYilmand S., Ameha. 2011. A Review of the Ethiopian Dairy Sector. Ed. Rudolf Fombad, Food and Agriculture Organization of the United Nations, Sub Regional Office for Eastern Africa (FAO/SFE), Addis Ababa, Ethiopia, pp 81. The NEXT STAGE IN DAIRY DEVELOPMENTFOR ETHIOPIA, Dairy Value Chains, End Markets and Food Security, USAID/ Land O+Lakes, 2010 • Absence of effective breeding policies and programs to assure optimum performance levels and efficiencies • AI service has been inefficient for different reasons in rural areas • Bilateral projects through EDDP link up to World Wide Sires, for AI use in commercial peri-urban dairies, through private enterprises (ALPPIS) • Chance of forming Dairy Farmer and Cattle Breeder Associations
  35. 35. Agro-ecological breeding policy Yilma zelalem,,G.B., Emannuelle aYilmand S., Ameha. 2011. A Review of the Ethiopian Dairy Sector. Ed. Rudolf Fombad, Food and Agriculture Organization of the United Nations, Sub Regional Office for Eastern Africa (FAO/SFE), Addis Ababa, Ethiopia, pp 81. The NEXT STAGE IN DAIRY DEVELOPMENTFOR ETHIOPIA, Dairy Value Chains, End Markets and Food Security, USAID/ Land O+Lakes, 2010 Attempts to improve dairy merit of national herd include: • Importation of purebred dairy cows • Production and distribution of Crossbred cows on Government farms • Importation of crossbred cows from Kenya • AI-Center with Purebred, crossbreds and local bulls • Distribution of imported semen form high yielding breeds • Distribution of crossbred bulls
  36. 36. Agro-ecological breeding policy Options: 1. The intensive commercial dairy sector (ICDS) exotic semen through private sector AI services and purchase of breeding bulls from within the ICDS 3. Less intensive semi commercial and rural dairies obtain crossbred bulls of various grade and sources (appropriateness and supply sustainability?) Yilma zelalem,,G.B., Emannuelle aYilmand S., Ameha. 2011.FAO, Sub Regional Office for Eastern Africa (FAO/SFE), Addis Ababa, Ethiopia, pp 81.
  37. 37. Agro-ecological breeding policy Supply of breeding bulls for the rural sector – Link up with existing community actions – Crossbred bulls (?) from commercial dairy farmers in and around Addis Ababa, Asella Livestock Farm, Wolaita Jersey Bull Ranch and DDE – 75 % crossbreed bulls distributed to individual farmers through various agencies – Farmers established breeding bull stations Constraint: Replacement of bulls was and is linked to a functional supply chain (sustainability?)
  38. 38. A new scheme for Breeding bull provision Suggestion of a young sire programme to provide crossbred bulls for rural smallholder dairy farmers 1. Concept for application acrosss the highland dairy shed 2. Action domain Rural administrative Community with established farmer interaction
  39. 39. Evaluation of bulls on the basis of their ancestors’ performances, eg. bull mothers - future option also on maternal / paternal halfsisters A new scheme for Breeding bull provision Definition: Young sire programme Features: - short generation intervals (minimum 3-4 years) - low accuracies → relatively high genetic response per year - simple, least expensive breeding scheme
  40. 40. - comprises about 200 farmers - formation of village service co-operatives (e.g. purchase of agricultural inputs, milk collecting, marketing) - implementation of village bull service A new scheme for Breeding bull provision Rural administrative community e.g. Selale
  41. 41. • Crossbred cow population in a PA –200 small holder - 2 crossbred cows per farm → 400 crossbred cows 4. A new scheme for Breeding bull provision Determination of number of replacement bulls for rural community • Number of replacment bulls needed per year - Mating ratio: 1 : 40 → 10 bulls for service in Useful life of a bull: 3 years → 4 bulls
  42. 42. 5. Model calculation for a Young sire scheme Establishment of local open nuclei based on cow performance - Second step: → start of a farmer based recording system with community verification Identification of superior cows to breed bull calves: - First step (no recording) →farmer identification of best performaning cows (e.g. milk yield history, field day comparison)
  43. 43. 5. Model calculation for a Young sire scheme Establishment of local open nuclei based on cow performance Minimum nucleus size within a PA: - 14-28 superior cows (7-14% of cow population) → no scope for performance selection
  44. 44. 5. Model calculation for a Young sire scheme Establishment of local open nuclei based on cow performance Selection intensities for different nucleus sizes Nucleus size 50 100 150 Expected proportion of bulls selected, % 28-56 14-28 9-19 Selection intensity i 1.16-0.69 1.60-1.16 1.80-1.42
  45. 45. 6. Conclusions • Agro-ecological planning including water conditions essential for securing efficiency • Rural smallholder need increased dairy performance for efficient use of resources/water • Community based breeding scheme best suited to secure operational sustainability • Young Sire program with open nucleus breeding scheme could lead to sutainable performance with best efficiency
  46. 46. 6. Conclusions • It pre-supposes an active participation of the farmers and respective vocational training, • Calls for extended scientific engagement of higher learning institutes interested in R 4 D and aquainted with participartory research methods Excellent field lab for College / University students

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