Trade-offs forbiomass uses atfarm level -Livestock vs soilcoverNaudin K, BruelleG, Salgado P, PenotE, Scopel E, Lubbers M,...
The issueTo much biomass      Not enough biomass                     for cattle                         Feed the cows     ...
CONSERVATIONAGRICULTUREIN THE LACALAOTRAREGION OFMADAGASCAR
Alaotra Region 102 000 ha of paddy Fields 7 hours from Antananarivo by car 750 m et 1 100 m ASL Annual rainfall : 850 mm, ...
Alaotra Region-Landscape                      Poor water                      control paddy                      fields Ir...
CA in the Alaotra region                                        2500 First experimentation in 1998          2000          ...
METHODS
Optimization throught Linearprogramming - TheoryGoal : maximize x1+x2With following constraints • x1≥0 • x2 ≥0 • x2-x1≤1 •...
GANESH                  Goals oriented Approach to use No tillfor a better Economic and environmental sustainability for S...
GANESH - Crops     4 kinds of     fields1.     Poor water       control paddy       fields2.     Hillsides3.     Alluvial ...
GANESH- Livestock  LIVESTOCK• 4 kinds of  animals   1. Zebu male   2. Zebu female   3. Dairy cows      improved      breed...
GANESH- FarmFarm structure • Work force • Self   consumption   needsExternal factors • Milk market
GANESH- OptimisationTotal farmincomeConstraints : • Work   availability • Fields • Forage   needs • Soil cover %
GANESH- Biomass export andsoil cover                                                   Adapted from: Naudin et            ...
RESULTSDISCUSSION
Simulation             Alluvial Soil                   Poor water             1 000 m2        Irrigated       control     ...
Simulation What is the impact of an increase in the herd size • in term of % of the area cultivated in CA • in term of eco...
Area with CA, alluvial soilsYear 2
Liverstock economic balance                    Year 2
With a limiting milk market                               12,000                               10,000   Milk -forage bough...
Conclusion  Linear programming can be a useful tool to take into account both negative and positive interactions between C...
Thank you for your attentionMerci de votre attention !
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Trade-offs for biomass uses at farm level, livestock vs soil cover. Krishna Naudin

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Trade-offs for biomass uses at farm level, livestock vs soil cover. Krishna Naudin

  1. 1. Trade-offs forbiomass uses atfarm level -Livestock vs soilcoverNaudin K, BruelleG, Salgado P, PenotE, Scopel E, Lubbers M,de Ridder N, Giller K E
  2. 2. The issueTo much biomass Not enough biomass for cattle Feed the cows or feed the soil ?Not enough biomassto cover the soil
  3. 3. CONSERVATIONAGRICULTUREIN THE LACALAOTRAREGION OFMADAGASCAR
  4. 4. Alaotra Region 102 000 ha of paddy Fields 7 hours from Antananarivo by car 750 m et 1 100 m ASL Annual rainfall : 850 mm, lot of variations, 7 to 10 months whithout rain
  5. 5. Alaotra Region-Landscape Poor water control paddy fields Irrigated paddy fields Hills Alluvials soils
  6. 6. CA in the Alaotra region 2500 First experimentation in 1998 2000 Surface Number of adopting 2010-2011 : 1500 • 2000 farmers 1000 • 1200 ha 500 Strong support from 0 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 developpement project, Source: Penot et al, this congress public funds, NGO EXAMPLE OF PICTUREAnnual rotation: rice/Vicia villosa Bi-annual rotation: maize+dolichos//rice Source : Séguy et al
  7. 7. METHODS
  8. 8. Optimization throught Linearprogramming - TheoryGoal : maximize x1+x2With following constraints • x1≥0 • x2 ≥0 • x2-x1≤1 • x1+6x2 ≤15 • 4x1-x2 ≤10 X1+x2=5 X1+x2=4 X1+x2=2 Matousek & Gartner, 2007
  9. 9. GANESH Goals oriented Approach to use No tillfor a better Economic and environmental sustainability for Smallholders GANESH:• 21 variables• 32 equations
  10. 10. GANESH - Crops 4 kinds of fields1. Poor water control paddy fields2. Hillsides3. Alluvial soils4. Irrigated paddy fields Each crop is characterized by its needs and outputs
  11. 11. GANESH- Livestock LIVESTOCK• 4 kinds of animals 1. Zebu male 2. Zebu female 3. Dairy cows improved breed 4. Dairy cows local breeds• Each animal is characterized by its needs and outputs
  12. 12. GANESH- FarmFarm structure • Work force • Self consumption needsExternal factors • Milk market
  13. 13. GANESH- OptimisationTotal farmincomeConstraints : • Work availability • Fields • Forage needs • Soil cover %
  14. 14. GANESH- Biomass export andsoil cover Adapted from: Naudin et al. Trade-offs between biomass use and soil cover. The case of rice- based cropping systems in the Lake Alaotra region of Madagascar., Exp.Agric. In press Why soil cover ? • Has impact on: weeds pressure, erosion control, water balance. • Not yet possible to link % of soil cover and crop yield impact
  15. 15. RESULTSDISCUSSION
  16. 16. Simulation Alluvial Soil Poor water 1 000 m2 Irrigated control Alluvial Soil Paddy field paddy field 1 000 m2 4 000 m2 2 000 m2 Poor water + 3 children control Hill 1 000 m2 paddy field Hill 1 000 m2 2 000 m2 Hill 1 000 m2 Hill 1 000 m2 EXEMPLE D’IMAGE0 12
  17. 17. Simulation What is the impact of an increase in the herd size • in term of % of the area cultivated in CA • in term of economic balance of livestok activities
  18. 18. Area with CA, alluvial soilsYear 2
  19. 19. Liverstock economic balance Year 2
  20. 20. With a limiting milk market 12,000 10,000 Milk -forage bought (kAr) 8,000 12 10 Nb of cows 6,000 8 6 4,000 4 2,000 2 0 0 -2,000 No 32 limit 16 Milk marketable l/ day -4,000 Constraint: soil cover > 90%
  21. 21. Conclusion Linear programming can be a useful tool to take into account both negative and positive interactions between CA and husbandry at farm level What are the limits in terms of complementarily, or competition for: • Biomass that can be removed from field • Size of the herd • Cropping systems performances (biomass and grain production) • Market demand for animal products To go further: need of more data about relation between soil cover and crop yields • Short term impact of soil cover on: weeds, water balance • Mid term impact of soil cover on : nutrient cycling, soil organic matter
  22. 22. Thank you for your attentionMerci de votre attention !

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