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Farming with Organic Fertiliser: Crop-Livestock Integration for Sustainable Resource Management in Ethiopia
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Farming with Organic Fertiliser: Crop-Livestock Integration for Sustainable Resource Management in Ethiopia

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This study was presented during the conference “Production and Carbon Dynamics in Sustainable Agricultural and Forest Systems in Africa” held in September, 2010.

This study was presented during the conference “Production and Carbon Dynamics in Sustainable Agricultural and Forest Systems in Africa” held in September, 2010.

Published in: Technology, Business

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  • 1. Farming with organic fertilizer: crop-livestock integration for sustainable resource management in Ethiopia Hailemariam Teklewold Belayneh, University of Gothenburg, Dpt of Economics. E-mail: hailemariam.teklewold@economics.gu.se Tel: +46-76-262-7814 ABSTRACT In the mixed farming system where low soil organic matter content and soil nutrient depletion stifles crop productivity and livestock feed availability, the emphasis on intensification focusing crop-livestock integration is important for harnessing nutrient recycling. This study suggests an econometric model to estimate the increase of organic fertilizer production due to livestock technology adoption and the crossover effect of crop production, identify the critical factors constrained the taking up of livestock technology and suggest policy recommendations towards the strengthening of crop-livestock synergies aiming to sustainable use of natural resources. Analysis is made on a cross section of 493 farm households in the central highlands of Ethiopia. The result shows that adoption of crossbred-cow technology depends positively on nearness of the farm households to the extension service and access to complementary inputs and negatively on her risk preference. Adopting crossbreeding technology induces an expected increase of farm household’s organic fertilizer production of 3.93 tons. The positive cross over effect of crop technology on organic fertilizer production is significantly higher for crossbred- cow technology adopter than the effect on non-adopter. Hence, crop-livestock integration as explained by the product-product relationship is strong due to joint application of crop and livestock technologies.
  • 2. Motivation Soil fertility depletion is one of the problem causing declining food production in developing countries (Amare etal 2005; Girmay etal, 2008). In Ethiopia: National estimates of input, extraction and balance: • Inorganic: 8.5 N kg/ha and 9.8 P kg/ha • Organic: 29 N kg/ha and 7.2 P kg/ha Extraction: harvested crop, erosion, leaching, etc • Balance: -122 N kg/ha and -13 P kg/ha - negative soil nutrients balance - mining of the soil
  • 3. This is mainly due to constraints: – Inorganic fertilizers (DAP and urea) = 14% area • due to continuous rise of prices (Croppenstedt et al (2003); Amare et al (2005); Teklewold et al 2006). – Organic fertilizers (manure) = 15% area • Allocation problem: source of energy and selling (Mekonnen and Kohlin, 2008; Girmay etal 2008; Amare etal, 2005; Fitsum etal 1999; Erkossa and Teklewold (2009) ). • Availability constraints: the past few decades have witnessed: • Increasing population densities • Decreasing availabilities of arable land • Conversion of grazing land for cultivation • Declining of soil fertility • Traditional production system (limited intensification)
  • 4. • The problem: – Low livestock productivity and dwindling of manure supply – Low agriculture productivity (partly due to little organic fertilizer produced) – Interventions do not take into account crop- livestock interactions.
  • 5. The questions: • How can the system of crop-livestock are further integrated for organic fertilizer in terms of: • technological, • managerial and • institutional considerations?
  • 6. Fig. 1. Farm yard manure under crop-livestock system Farm Yard Manure Farm land (size, productivity) Technology Biomass (Straw) Traction Grazing land Farm inputs Market (cash, off- farm) Livestock Crop (Grain) Household (consumption, labor)
  • 7. Objectives of the study: • suggest an econometric model to estimate the effect of the non-allocable livestock technology adoption and the crossover effect of crop technology on FYM production, • identify the critical factors constrained the taking up of livestock technology and • suggest policy recommendations towards the strengthening of crop-livestock synergies aiming to sustainable use of natural resources in the mixed crop-livestock system
  • 8. • H1: average farm household FYM production is higher for livestock technology adopters (those owned cross-bred cow) than non-adopter farm households: • H2: the cross over effect of crop technology (area covered with modern crop seeds) on FYM production is higher for those farm households who integrate livestock technology in their farming system than the non-adopters • H3: livestock technology adoption influenced + by access to other complementary inputs + by effective communication • the innovation-diffusion model or transfer-of-technology (Roger, 1962) - by risk aversion behavior ( ) ( )u m b m yy Ε>Ε
  • 9. Method of analysis: - endogenous switching regression Livestock Technology Adopters Non-Adopters ( ) ( )( ) u mi b mimi yhyhy α−+α= 1 bibbi b mi uXy +β′= uiuui u mi uXy +β′=
  • 10. The data and study areas • The data for this study originates from a farm household survey conducted by the EIAR in 2006. • conducted in three different zones of the central highlands of Ethiopia. • The total sample consists of 491 farm households. • Multi-stage random sampling technique was employed for selecting districts and households from each area.
  • 11. • The data provides a unique opportunity for the analysis requiring different: – household characteristics, – crop and livestock system components. – Manure production and various utilization • contains information such as: – household and farm characteristics (sex, age, education, labor, etc); – social organization (cooperatives, associations); – resource endowments (land, livestock, credit, off-farm, etc); – agricultural technologies (crops, livestock); – information (extension, training) and – farmer’s risk preference
  • 12. Descriptive statistics Variables Definition Non-binded Binded Location westshoa West shoa zone = 1 0.177 0.123 eastshoa East shoa zone = 1 0.316 0.247 Crop effect improvedarea Modern crop variety grown (ha) 1.049 (0.747) 1.052 (0.764) cultivated Cultivated land area (ha) 2.152 (1.528) 2.538 (1.876) Livestock effect traindairy Training on dairying = 1 0.049 0.300 privatgraz Private grazing land (ha) 0.477 (0.454) 0.656 (0.809) comunalgraz Access to communal grazing land = 1 0.342 0.370 dungprice1 Price of FYM (Birr/100 kg) 64.992 (19.131) 66.471 (21.907) TLU1 Livestock size (Tropical Livestock Unit) 5.823 (3.009) 7.815 (4.864) coopmilk Cooperatives member = 1 0.083 0.207 zerograz Cut and feeding system = 1 0.034 0.097 concentrate concentarte feeding = 1 0.068 0.758 veternairy veterniary service = 1 0.075 0.722
  • 13. . . . continued decriptive statistics Variables Definition Non-binded Binded Location westshoa West shoa zone = 1 0.177 0.123 eastshoa East shoa zone = 1 0.316 0.247 Market/information distanceda Distance to extension agent (hours) 0.515 (0.449) 0.452 (0.431) offarm Off-farm work = 1 0.361 0.471 Household characterstics age Age in years 45.748 (12.937) 46.590 (12.862) sex Male = 1 0.865 0.907 education Years of education 3.297 (3.721) 4.991 (4.353) adultEquvalent Family size (in adult equivalent) 4.565 (1.778) 4.843 (1.810) equib Rotating credit and saving club = 1 0.421 0.467 Risk Farmer’s risk preference (Rank) 1=Neutral to prefering 0.165 0.211 2=Slight to neutral 0.098 0.154 3=Moderate 0.203 0.189 4=Intermediate 0.180 0.185 5=Severe 0.120 0.079 6=Extreme averse 0.233 0.181 N Number of cases 265 226
  • 14. Switching regression: FYM production differentials )()( uiuui u mibibbi b mi uxyuxy +β′=>+β′= - It is found that: - But the difference is due to: - technological - observed characterstics Unconditional Non-binded Binded Conditional on Conditional on Adopter, Non-Adopter, Binding Non-binding Binding Non- Binding 8.98 (0.15) 5.05(0.07) 4.79 (0.11) 5.36 (0.10) 10.37 (0.26) 7.81 (0.14) Average differences in FYM production under different regimes 3.93(0.17) 2.49 (0.18) 2.55 (0.29) 0.57(0.16) 5.58 (0.29) 5.01 (0.27) Table 5. Average FYM production (ton/annum) under different regimes ( )b myE ( )u myE ( )0=hyE u m( )1=hyE u m ( )1=hyE b m ( )0=hyE b m ( ) ( )u m b m yEyE − ( ) ( )00 =−= hyEhyE b m u m ( ) ( )10 =−= hyEhyE u m u m ( ) ( )01 =−= hyEhyE b m b m ( ) ( )11 =−= hyEhyE u m b m ( ) ( )01 =−= hyEhyE u m b m
  • 15. Estimation results - FYM equation Variables FYM equation Binded Non-binded Coef. Robust Std. Err. Coef. Robust Std. Err. Constant 3.495*** 0.559 3.280*** 0.386 Sex -0.251** 0.106 0.014 0.090 Education 0.021** 0.010 -0.018* 0.010 adultEquvalent 0.015 0.022 0.024 0.023 Offarm -0.023 0.076 -0.155** 0.072 Cultivated -0.030 0.019 0.003 0.030 improvedarea 0.118** 0.046 0.014 0.039 Traindairy -0.074 0.092 -0.122 0.146 Privatgraz 0.066* 0.042 0.084 0.073 comunalgraz -0.061 0.087 -0.327*** 0.075 Dungprice 0.007*** 0.002 0.005** 0.002 TLU 0.049*** 0.007 0.029* 0.016 Zerograz 0.420** 0.186 0.222 0.172 E(y
  • 16. Switching regression results – technology adoption Variables Switcher Coef. Robust Std. Err. Constant -4.668*** 1.111 Age 0.086** 0.042 age2/1000 -0.847** 0.406 Offarm 0.482** 0.191 Traindairy 0.635** 0.309 Privatgraz 0.244* 0.146 Dungprice 0.019*** 0.005 TLU 0.083*** 0.028 Risk -0.109** 0.048 Distanceda -0.635*** 0.237 Concentrate 1.834*** 0.261 Veternairy 1.585*** 0.210
  • 17. Conclusions and implications • The major constraint in smallholder farms in many developing countries is the negative soil nutrient balance. • Jointness of crops and livestock production is often considered as an opportunity towards sustainable agricultural production – because of the associated organic matter and nutrient recycling. • In further support of the idea, this study employed an endogenous switching model: – To show joint intensification on technologies for increasing crop-livestock synergies for sustainable soil mgt.
  • 18. • It is clear that a considerable amount of component research, along disciplinary lines has been undertaken. – however, many technological innovations have suffered from limited uptake due to a wide range of cultural, economic and technical reasons; – and a lack of appreciation of the wider impacts of technologies in the other system of components may often be ignored – this might be due to the underestimation by policy makers and planners of the importance of farming system approach that consider each system as an integral and significant component of the mixed farming system, affecting the sustainable management of resources.

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