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Farmers’ uptake of improved feed practices and reasons for
adoption/ non adoption
Gregory Ndwandwa Sikumba
CLEANED Project East Africa Stakeholder Consultation on Dairy and Environment
Nairobi, Kenya, 18 September 2013
IntroductionIntroduction
 In Kenya, feed availability often affects livestock productivity and
continues to be a major challenge on smallholder farms.
 Small scale farmers often feed dairy cattle herds at maintenance levels
only which leads to low herd productivity.
 The potential for increasing dairy productivity in Kenya and especially
the smallholder dairy remains great because an average yield per cow
in smallholder farms is as low as 1,300 liters per year as compared to
the global best practice of 4000-6000 liters (Karanja 2003).
 It has been shown that farmers who adopt new technologies can
increase the financial benefits through increased biophysical productivity
or through reduced input costs (Franzel, 2003)
 Feeds and feeding contributes 60 – 70% of the total cost of milk
production in East Africa (EADD, 2010)
Feed technologies Promoted
Tube silage making
Hay making
Silage tubes
Above ground silage making
Mixing home made rations
Chopping fodder maizeSource ILRI, 2012
Plastic tank silage
Mucuna spp.
Lucerne Calliandar spp.
Established pastures Desmodium Napier grass
Fodder maizeLab lab spp.Fodder oats
Source ILRI, 2012
• Low expenditure on research (Developing countries spend about 0.7% while
developed countries spend about 3% from their GDP (Karugia et al. 2009))
• The poor targeting of technologies because of the traditional top down
approach of developing innovations (One size fits all approach).
• Lack of knowledge of all available technologies (extension ration of 1:800)
• Lack of basket of options for farmers to choose among the available
technologies.
• Lack of screening of available technologies in relation to local conditions
• Lack of Gender mainstreaming
Reasons for Poor adoption/non adoption
ILRI, 2012
Current Status
Percentage of households to practice any feed conservation practices in the last 12
months
  Final
Indicator Catchment/E Catchment/NE Control
Kenya        
% of HHs to practice feed conservation 56.5% 39.6% 46.1%
n 405 182 297
Conservation practices (of farmers to practice any conservation practice)
Final
Indicator Catchment/E Catchment/NE Control
Kenya %
# of 
responses %
# of 
responses %
# of 
responses
Box bailing 5.7 13 1.4 1 4.4 6
Tube Silage 9.6 22 6.9 5 5.8 8
Above-Ground Silage 4.3 10 8.3 6 4.4 6
Pit Silage 3.5 8 6.9 5 1.5 2
Standing Hay 9.1 21 9.7 7 10.9 15
Traditional Stacking Under Shade 6.5 15 11.1 8 7.3 10
Stacking In Store 83.0 191 75.0 54 86.9 119
Loose Hay 13.9 32 15.3 11 13.9 19
Other 2.6 6 2.8 2 0.0 0
n= farmers to practice any conservation practice 229   72   137  
ILRI, 2012
1) Productivity of the selected feed technologies in the three
agro ecological zones in Kenyan Highlands
2) Costs of feed technologies being promoted for dairy cattle
feeding
3) Profitability of each promoted feed technology for dairy cattle
feeding
4) Socio-economic characteristics that influence profitability of
feed
Areas of Interest
Rationale
• The study aimed at developing a decision support tool for dairy farmers.
• Knowledge of the profitability of feed technologies being promoted by EADD in
Kenya, will assist farmers to make informed decisions when adopting.
• Knowledge of enterprise’s profitability will enhance the promotion of feeds and
various technologies in the sites and guide the dissemination strategy of the
EADD project and Extension officers
Cows feeding on improved grass
Study Site
The study was carried out in Rift Valley province in the Kenyan highlands. The counties sampled fall under
three agro ecological zones namely Upper Midlands (Kabiyet and Siongiroi), Upper Highlands (Olkalou) and
Lower Highlands (Longisa, Liten and Metkei) see figure below:
source own construct
Results (Fodder Productivity in the AEZ’s)
• Napier grass flourished well in lower highlands while fodder legumes did
better in Upper and lower highlands
Overall Annual cost of fodder production
per acre in USD
Gross margin=Revenues (fodder yields) X market price - Costs (planting
materials, fertilizer/manure, pesticides, herbicides, fungicides, labor, any
other cost).
Results Area 1
 One way ANOVA of yield between Lower highlands, Upper midlands and Upper
highlands for the adopted fodder
Source F Prob>F Bonferroni
Napier Grass 3.58 0.035** Upper highlands different from
lower highlands (P=0.046)
Fodder Maize 0.64 0.053*
Fodder Oats 2.80 0.123
Fodder Trees 4.48 0.019** lower highlands different from
Upper midlands (P=0.016)
Fodder Legumes 0.06 0.810
***, **, and * indicates significance at 1%, 5% and 10%, respectively
Results Area 2
 One way analysis of variance for cost between Lower highlands, Upper midlands
and Upper highlands for the adopted fodder
Source F Prob>F Bonferroni
Napier Grass 3.00 0.058*
Fodder Maize 0.17 0.84
Fodder Oats 4.39 0.056*
Fodder Trees 4.48 0.006** Lower highlands different from
Upper midlands (P=0.004).
Fodder Legumes 0.01 0.927
***, **, and * indicates significance at 1%, 5% and 10%, respectively
 One way ANOVA of Profit (USD /acre) between Lower highlands, Upper
midlands and Upper highlands for the adopted fodder
Results Area 3
Source F Prob>F Bonferroni
Napier Grass 2.85 0.0856* Upper highlands different from
lower highlands (P=0.10)
Fodder Maize 3.11 0.1182
Fodder Oats 0.01 0.9326
Fodder Trees 3.11 0.1182
Fodder Legumes 3.11 0.3266
***, **, and * indicates significance at 1%, 5% and 10%, respectively
 Social Economic Determinant of Profitability and Inefficiency
Determinants of Profitability
Coefficient Std-error P>|z|
Linear terms Constant
-58.85 16.57 0.000***
Resources Log cost of Labour/acre (Inlab)
46.69 12.33 0.000***
Log other costs/acre (In Other)
9.18 3.75 0.015**
Log Land under fodder cost/acre (In Land)
26.77 5.23 0.000
Square terms
Log Other costs/acre2
-9.04 2.42 0.000***
Log labor cost/acre2
-1.31 0.35 0.000***
Log land under fodder cost/acre2
3.07 1.34 0.022**
Cross terms In Labor # log InLand
-8.13 1.61
0.000
In fodderland #In other costs
0.30 0.76 0.697
In other inputs # In labor
12.41 1.30 0.064*
Determinants of Inefficiency
Social economic
Factors
Gender of Farmer (0=Male, 1=otherwise)
-2.58 o.77 0.001***
Years of experience in Fodder production
0.096 0.035 0.006**
Other Occupation of Farmer
1.799 0.659 0.006**
Size of farm in acres
-0.47 0.13 0.000***
Scale of Farming (Small, Large)
2.098 0.76 0.006**
AEZ
Upper Midlands
4.60 1.35 0.001***
Lower Highlands
6.572 1.796 0.000***
Sigma-squared
-1.45*** 1.03
Gamma
Profit Efficiency Summary Statistics
AEZ Average Profit
Efficiency
Min Max Median Standard
Deviation
Upper
Highlands
32% 7% 68% 29% 0.26
Upper Midlands 37% 2% 75% 40% 0.22
Lower
Highlands
33% 0.9% 82% 39% 0.21
Overall 34% 0.99% 82% 40% 0.22
 On average, the overall profit efficiency score was very low (34%).
 This means that on average Kenyan farms producing dairy cattle feed could increase their profits by
66% by improving their technical and allocative efficiency.
Important implications
• Need to train farmers in profitable feed production
• Need to focus on areas that increase cost of feed in
the given areas e.g. fodder costs were mainly
increased by labor, therefore ways to reduce labor
costs such as mechanization need to be adopted.
• Overall improved extension focusing on feed cost
benefit analysis on the fodder crops grown in the
areas can increase gross margins and find innovative
ways of making forage seed available cheaply etc.
References
 Ali, M., and Flinn, J. (1989), Profit efficiency among Basmati rice producers in Pakistan Punjab. American
Journal of Agricultural Economics, 71(2), 303-310.
 Franzel, S. (2004). Financial analysis of agroforestry practices. In: Alavalapati, J.R.R., Mercer, D.E.
(Eds.). Valuing Agroforestry Systems. Kluwer Academic Publishers, Netherlands, pp. 9–37.
 EADD (2010). East African Dairy Development Project Baseline Survey Report 3 Feeds and Feeding
Practices. ILRI, Nairobi Kenya.
 Roothaert, R., Karanja, G.M., Kariuki, I.W. Paterson, R., Tuwei, P., Kiruiro, E., Mugwe, J. and Franzel, S.
(1998) ‘Calliandra for livestock’, Technical Bulletin No. 1, Embu, Kenya: Regional Research Centre,
Embu.
 Roothaert, R.L. and Paterson, R.T. (1997). Recent work on the production and utilization of tree fodder in
East Africa. Animal Feed Science and Technology, 69: 39–51.
 Staal, S.J., Chege, L., Kenyanjui, M., Kimari, A., Lukuyu, B., Njubi, M., Owango, M., Tanner, J. Thorpe,
W. and Wambugu, M. (1997). Characterisation of Dairy Systems Supplying the Nairobi Milk Market: A
Pilot Survey in Kiambu District for The Identification of Target Groups of Producers. KARI/MoA/ILRI
Collaborative Research Project Report.
Thank you

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Farmers’ uptake of improved feed practices and reasons for adoption/ non adoption

  • 1. Farmers’ uptake of improved feed practices and reasons for adoption/ non adoption Gregory Ndwandwa Sikumba CLEANED Project East Africa Stakeholder Consultation on Dairy and Environment Nairobi, Kenya, 18 September 2013
  • 2. IntroductionIntroduction  In Kenya, feed availability often affects livestock productivity and continues to be a major challenge on smallholder farms.  Small scale farmers often feed dairy cattle herds at maintenance levels only which leads to low herd productivity.  The potential for increasing dairy productivity in Kenya and especially the smallholder dairy remains great because an average yield per cow in smallholder farms is as low as 1,300 liters per year as compared to the global best practice of 4000-6000 liters (Karanja 2003).  It has been shown that farmers who adopt new technologies can increase the financial benefits through increased biophysical productivity or through reduced input costs (Franzel, 2003)  Feeds and feeding contributes 60 – 70% of the total cost of milk production in East Africa (EADD, 2010)
  • 3. Feed technologies Promoted Tube silage making Hay making Silage tubes Above ground silage making Mixing home made rations Chopping fodder maizeSource ILRI, 2012 Plastic tank silage
  • 4. Mucuna spp. Lucerne Calliandar spp. Established pastures Desmodium Napier grass Fodder maizeLab lab spp.Fodder oats Source ILRI, 2012
  • 5. • Low expenditure on research (Developing countries spend about 0.7% while developed countries spend about 3% from their GDP (Karugia et al. 2009)) • The poor targeting of technologies because of the traditional top down approach of developing innovations (One size fits all approach). • Lack of knowledge of all available technologies (extension ration of 1:800) • Lack of basket of options for farmers to choose among the available technologies. • Lack of screening of available technologies in relation to local conditions • Lack of Gender mainstreaming Reasons for Poor adoption/non adoption
  • 6. ILRI, 2012 Current Status Percentage of households to practice any feed conservation practices in the last 12 months   Final Indicator Catchment/E Catchment/NE Control Kenya         % of HHs to practice feed conservation 56.5% 39.6% 46.1% n 405 182 297
  • 7. Conservation practices (of farmers to practice any conservation practice) Final Indicator Catchment/E Catchment/NE Control Kenya % # of  responses % # of  responses % # of  responses Box bailing 5.7 13 1.4 1 4.4 6 Tube Silage 9.6 22 6.9 5 5.8 8 Above-Ground Silage 4.3 10 8.3 6 4.4 6 Pit Silage 3.5 8 6.9 5 1.5 2 Standing Hay 9.1 21 9.7 7 10.9 15 Traditional Stacking Under Shade 6.5 15 11.1 8 7.3 10 Stacking In Store 83.0 191 75.0 54 86.9 119 Loose Hay 13.9 32 15.3 11 13.9 19 Other 2.6 6 2.8 2 0.0 0 n= farmers to practice any conservation practice 229   72   137  
  • 8. ILRI, 2012 1) Productivity of the selected feed technologies in the three agro ecological zones in Kenyan Highlands 2) Costs of feed technologies being promoted for dairy cattle feeding 3) Profitability of each promoted feed technology for dairy cattle feeding 4) Socio-economic characteristics that influence profitability of feed Areas of Interest
  • 9. Rationale • The study aimed at developing a decision support tool for dairy farmers. • Knowledge of the profitability of feed technologies being promoted by EADD in Kenya, will assist farmers to make informed decisions when adopting. • Knowledge of enterprise’s profitability will enhance the promotion of feeds and various technologies in the sites and guide the dissemination strategy of the EADD project and Extension officers Cows feeding on improved grass
  • 10. Study Site The study was carried out in Rift Valley province in the Kenyan highlands. The counties sampled fall under three agro ecological zones namely Upper Midlands (Kabiyet and Siongiroi), Upper Highlands (Olkalou) and Lower Highlands (Longisa, Liten and Metkei) see figure below: source own construct
  • 11. Results (Fodder Productivity in the AEZ’s) • Napier grass flourished well in lower highlands while fodder legumes did better in Upper and lower highlands
  • 12. Overall Annual cost of fodder production per acre in USD Gross margin=Revenues (fodder yields) X market price - Costs (planting materials, fertilizer/manure, pesticides, herbicides, fungicides, labor, any other cost).
  • 13. Results Area 1  One way ANOVA of yield between Lower highlands, Upper midlands and Upper highlands for the adopted fodder Source F Prob>F Bonferroni Napier Grass 3.58 0.035** Upper highlands different from lower highlands (P=0.046) Fodder Maize 0.64 0.053* Fodder Oats 2.80 0.123 Fodder Trees 4.48 0.019** lower highlands different from Upper midlands (P=0.016) Fodder Legumes 0.06 0.810 ***, **, and * indicates significance at 1%, 5% and 10%, respectively
  • 14. Results Area 2  One way analysis of variance for cost between Lower highlands, Upper midlands and Upper highlands for the adopted fodder Source F Prob>F Bonferroni Napier Grass 3.00 0.058* Fodder Maize 0.17 0.84 Fodder Oats 4.39 0.056* Fodder Trees 4.48 0.006** Lower highlands different from Upper midlands (P=0.004). Fodder Legumes 0.01 0.927 ***, **, and * indicates significance at 1%, 5% and 10%, respectively
  • 15.  One way ANOVA of Profit (USD /acre) between Lower highlands, Upper midlands and Upper highlands for the adopted fodder Results Area 3 Source F Prob>F Bonferroni Napier Grass 2.85 0.0856* Upper highlands different from lower highlands (P=0.10) Fodder Maize 3.11 0.1182 Fodder Oats 0.01 0.9326 Fodder Trees 3.11 0.1182 Fodder Legumes 3.11 0.3266 ***, **, and * indicates significance at 1%, 5% and 10%, respectively
  • 16.  Social Economic Determinant of Profitability and Inefficiency Determinants of Profitability Coefficient Std-error P>|z| Linear terms Constant -58.85 16.57 0.000*** Resources Log cost of Labour/acre (Inlab) 46.69 12.33 0.000*** Log other costs/acre (In Other) 9.18 3.75 0.015** Log Land under fodder cost/acre (In Land) 26.77 5.23 0.000 Square terms Log Other costs/acre2 -9.04 2.42 0.000*** Log labor cost/acre2 -1.31 0.35 0.000*** Log land under fodder cost/acre2 3.07 1.34 0.022** Cross terms In Labor # log InLand -8.13 1.61 0.000 In fodderland #In other costs 0.30 0.76 0.697 In other inputs # In labor 12.41 1.30 0.064* Determinants of Inefficiency Social economic Factors Gender of Farmer (0=Male, 1=otherwise) -2.58 o.77 0.001*** Years of experience in Fodder production 0.096 0.035 0.006** Other Occupation of Farmer 1.799 0.659 0.006** Size of farm in acres -0.47 0.13 0.000*** Scale of Farming (Small, Large) 2.098 0.76 0.006** AEZ Upper Midlands 4.60 1.35 0.001*** Lower Highlands 6.572 1.796 0.000*** Sigma-squared -1.45*** 1.03 Gamma
  • 17. Profit Efficiency Summary Statistics AEZ Average Profit Efficiency Min Max Median Standard Deviation Upper Highlands 32% 7% 68% 29% 0.26 Upper Midlands 37% 2% 75% 40% 0.22 Lower Highlands 33% 0.9% 82% 39% 0.21 Overall 34% 0.99% 82% 40% 0.22  On average, the overall profit efficiency score was very low (34%).  This means that on average Kenyan farms producing dairy cattle feed could increase their profits by 66% by improving their technical and allocative efficiency.
  • 18. Important implications • Need to train farmers in profitable feed production • Need to focus on areas that increase cost of feed in the given areas e.g. fodder costs were mainly increased by labor, therefore ways to reduce labor costs such as mechanization need to be adopted. • Overall improved extension focusing on feed cost benefit analysis on the fodder crops grown in the areas can increase gross margins and find innovative ways of making forage seed available cheaply etc.
  • 19. References  Ali, M., and Flinn, J. (1989), Profit efficiency among Basmati rice producers in Pakistan Punjab. American Journal of Agricultural Economics, 71(2), 303-310.  Franzel, S. (2004). Financial analysis of agroforestry practices. In: Alavalapati, J.R.R., Mercer, D.E. (Eds.). Valuing Agroforestry Systems. Kluwer Academic Publishers, Netherlands, pp. 9–37.  EADD (2010). East African Dairy Development Project Baseline Survey Report 3 Feeds and Feeding Practices. ILRI, Nairobi Kenya.  Roothaert, R., Karanja, G.M., Kariuki, I.W. Paterson, R., Tuwei, P., Kiruiro, E., Mugwe, J. and Franzel, S. (1998) ‘Calliandra for livestock’, Technical Bulletin No. 1, Embu, Kenya: Regional Research Centre, Embu.  Roothaert, R.L. and Paterson, R.T. (1997). Recent work on the production and utilization of tree fodder in East Africa. Animal Feed Science and Technology, 69: 39–51.  Staal, S.J., Chege, L., Kenyanjui, M., Kimari, A., Lukuyu, B., Njubi, M., Owango, M., Tanner, J. Thorpe, W. and Wambugu, M. (1997). Characterisation of Dairy Systems Supplying the Nairobi Milk Market: A Pilot Survey in Kiambu District for The Identification of Target Groups of Producers. KARI/MoA/ILRI Collaborative Research Project Report.

Hinweis der Redaktion

  1. IB comments 24/11: I edited the box on gross margins by adding ‘X market price’ The 3 graphs are not completely similar (full line in Kenya & Rw versus ‘dashes’ in Uganda). Also add # on the x-axis In his email Greg wrote that he made changes for calliandra and hay- were these graphs adjusted? I suggest if we can’t get more realistic data for Calliandra Kenya, we don’t include it. This would also allow us to do the graphs with the same y-axis (max of $4,000) for the 3 countries, as the comparison between countries with different y axis is difficult. Greg writes that ‘ Napier [..] yield per acre is the highest (15.9). The total cost of Napier is actually the second lowest ($ 685.1). Because of the scale, we can’t see that on the graph. We need to make this clear as it explains the high adoption rate of Napier in EA The last bullet point about fodder adoption is not backed up by data. I don’t think we can conclude from this survey that fodder adoption is slow since we only surveyed feed farmers. Constraints to fodder adoption e.g. lack of planting materials, are very valid but we would need to show %. Previous comments, inclunding Greg below Compare costs across fodder types- check f Napier is among the cheapest fodder type to grow Why has Napier low gross margins yet it’s the most common fodder type? GNS: The table below shows that Napier has the lowest price per ton ($53) hence the low gross margins as compared to the rest of the fodder types even if its yield per acre is the highest (15.9). The total cost of Napier is actually the second lowest ($ 685.1). I think the very low cost of Napier is the reason why it has a very low gross margin. GNS: The calliandara data was checked but still there is no problem with the yield computations because they are within range with other fodder types though from the data the costs. It also has the highest variable cost but still there are profits. Suggest we leave it the way it is.