Optimizing Fertilizer Use in
Results of a Baseline Survey of Fertileer ft1 Adoption in Arsi Zone 5- ? • \ /■'% o-%.\ / i t ' - Z ' ■''\s : / a - ? v 4 -
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^ 4a Setotaw Ferede, Hugo Verkuijl,Douglas G. Tanner and Takele Gebre
Study sponsored and implemented by
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Ministry of Agriculture Optimizing Fertilizer Use in Ethiopia
Results of a Baseline Survey of Fertilizer Adoption in Arsi Zone
Setotaw Ferede, Hugo Verkuijl, Douglas G. Tanner, and Takele Gebre
Study sponsored and implemented by
Ethiopian Agricultural Research Organization
International Maize and Wheat Improvement Center
Sasakawa-Globa! 2000
Ministry of Agriculture
CIMMYT® 2000
Sasakawa-Global 2000, Addis Ababa 2000 Published by
Sasakawa-Global 2000, c/o Ministry of Agriculture, Agriculture Extension Department, P.O. Box 12771, Addis Ababa, Ethiopia.
Correct citation: Setotaw Ferede, H. Verkuijl, D. G. Tanner, and Takele Gebre. 2000. Optimizing fertilizer use in Ethiopia: Results of a baseline survey of fertilizer adoption in Arsi Zone. Addis Ababa: Sasakawa-Global 2000. CONTENTS
List of Tables...... iv Foreword...... vii Acknowledgments...... viii Executive Summary...... ix 1. Introduction...... 1 2. Methodology...... 4 3. Socio-economic characteristics of the study area...... 5 4. Fertilizer use and sources of financing...... 10 5. Cropping patterns and fertilizer adoption ...... 14 6. Farmers' perceptions of soil fertility management practices...... ,...31 7. Relationships among farmers' reported crop yields and measured soil parameters...... 36 8. Conclusions and recommendations...... 45 References...... - ...... 48 Appendices...... 49 LIST OF TABLES
3.1. Family composition and activities of average households...... 5 3.2. Family age distribution of average households...... 5 3.3. Education of average households...... 6 3.4. Average land holding...... 6 3.5. Reasons for sharing or renting-out land...... :...... 6 3.6. Type of livestock owned...... 7 3.7. Purpose of owning livestock...... ;...... 7 3.8. Land allocation to different crops by wo red a ...... 8 3.9. Priorities in the disposal of crops produced...... — 8 3.10. Assets owned by surveyed farmers...... 9 4.1. Fertilizer prices and annual fertilizer consumption per farmer...... 10 4.2. Farmers' sources of fertilizer...... 11 4.3. Month of fertilizer purchase...... ,...... 12 4.4. Average distance of fertilizer distribution centers from farm ...... 12 4.5. Preferences for alternative fertilizer package sizes...... 13 4.6. Reasons for preferences for alternative package sizes..;...... 13 4.7. Sources of finance for fertilizer purchase...... 13 5.1. Adoption of wheat varieties ...... ■■ 14 5.2. Average area (per adopter) sown to individual wheat varieties...... 14 5.3. Adoption of barley varieties...... 15 5.4. Average area (per adopter) sown to individual barley varieties...... 15 5.5. Soil types in relation to crop grown...... 16 5.6. Rotation crops...... 16 5.7. Farmers' perceptions of the advantages of crop rotation...... 16 5.8. Reasons for not using crop rotation...... — ...... 17 5.9. Frequency of ploughing with a mares ha ...... 18 5.10. Fertilizer rates adopted on major crops...... 18 5.11. Method of applying DAP and urea...... 18 5.12. Average hand weeding frequency in major crops...... 19 5.13. Time of first and second hand weedings in wheat, barley, tef, and maize...... 20 5.14. Herbicide rate by crop...... 20 5.15. Time of herbicide application...... 21 5.16. Methods of harvesting and handling crops...... 21 5.17. Yields of major crops...... 21 5.18. Wheat yield by variety...... 22 5.19. Barley yield by variety...... 22 5.20. Farmers' experience with fertilizer for wheat after break crops...... 23 5.21. Fertilizer rates used on wheat after a break crop ...... 23 5.22. History of fertilizer adoption...... 23 5.23. Farmers' experience with fertilizer rates after legume break crops...... 24 5.24. Reasons for reducing fertilizer rates after legume break crops...... 24 5.25. Duration of reduced fertilizer rates after legume break crops...... 24 5.26. Average duration of continuous production of wheat or barley...... 24 5.27. Farmers' experience with wheat production without fertilizer...... 25 5.28. Reasons for producing wheat without fertilizer...... 25 5.29. Farmers' perceptions of the rate of fertilizer used on all wheat fields...... 25 5.30. Factors affecting the rate of fertilizer applied on wheat fields...... 26 5.31. Farmers' perceptions of yield difference due to changed fertilizer rates...... 26 5.32. Reasons for fertilizer application in alternate years...... 26 5.33. Timeliness of fertilizer delivery...... 27 5.34. Reasons for late delivery of fertilizer...... 27 5.35. Recent timeliness of fertilizer delivery compared with 1991...... 27 5.36. Farmers' perceptions of demand for and actual procurement of fertilizer...... 27 5.37. Reasons for low demand and procurement of fertilizer...... 28 5.38. Average fertilizer requirement per farmer...... 28 5.39. Motivation for annual fertilizer purchase...... -...... 28 5.40. Farmers' perceptions of the specific benefits of DAP and urea...... 29 5.41. Reasons for farmers' preference for DAP...... 29 5.42. Awareness and adoption of recommended fertilizer rates for wheat...... 29 5.43. Sources of information for fertilizer recommendations...... 29 5.44. Reasons for not adopting recommended fertilizer rates...... 30 5.45. Farmers' perceptions of yield due to fertilizer relative to fertilizer loan...... 30 5.46. Constraints to fertilizer utilization...... 30 6.1. Yields of major crops on best and poorest fields with and without fertilizer ...... 32 6.2. Soil-related yield limiting factors...... 32 6.3. Non-soil-related yield limiting factors...... 32 6.4. Farmers' experience in fallowing land...... 33 6.5. Reasons for leaving land fallow ...... 33 6.6. Fertilizer application on major crops after fallowing...... 33 6.7. Average duration of fallow ...... 34 6.8. Farmers' reported yields for major crops on fallowed land using fertilizer...... 34 6.9. Soil fertility management practices...... 34 6.10. Crops receiving application of farmyard manure...... 35 6.11. Reasons for use of farmyard manure...... 35 6.12. Reasons for removing crop residues from fields...... 35
v 7.1. Correlations among yields of the four principal crop species with fertilizer...... 36 7.2. Comparisons of crop yields with and without fertilizer...... 36 7.3. Wheat: Summary of yield increment due to fertilizer on the poorest and best fields...... 38 7.4. Barley: Summary of yield increment due to fertilizer on the poorest and best fields...... 38 7.5. Faba bean: Summary of yield increment due to fertilizer on the poorest and best fields....38 7.6. Tef: Summary of yield increment due to fertilizer on the poorest and best fields...... 38 7.7. Summary of soil pH levels in the poorest and best fields ...... 39 7.8. Summary of soil organic matter levels in the poorest and best fields...... 39 7.9. Summary of Olsen P levels in the poorest and best fields...... 40 7.10. Summary of Bray and Kurtz P levels in the poorest and best fields...... 40 7.11. Correlations among soil parameters across all five woredas and for Asasa woreda...... 41 7.12. Correlations among soil parameters for Bekoji and Etheya woredas...... 41 7.13. Correlations among soil parameters for Lole and Robe woredas...... 41 7.14. Correlations among crop yields and soil parameters across the sampled woredas...... 42 7.15. Cumulative amounts of DAP and urea purchased from 1995 to 1998 per farmer...... 43 7.16. Correlations between yields and cumulative amounts of DAP and urea purchased...... 43 7.17. Correlations between DAP purchased and soil P levels and crop yield increments...... 44 7.18. Correlations of urea purchased with soil organic matter, pH level, and yield increments... 44 Appendix 1. Varietal adoption for various crops...... 49 Appendix 2. Correlations among crop yields and measured soil parameters for Asasa...... 49 Appendix 3. Correlations among crop yields and measured soil parameters for Bekoji...... 49 Appendix 4. Correlations among crop yields and measured soil parameters for Etheya...... 50 Appendix 5. Correlations among crop yields and measured soil parameters for Lole...... 50 Appendix 6. Correlations among crop yields and measured soil parameters for Robe...... 50 FOREWORD
Agriculture is the mainstay of the majority of up and recycle nutrients from lower depthsin the soil Ethiopians. With an estimated 80 percent of the labor profile, is no longer a common practice owing to the force engaged in this sector, agriculture is not only the increased population pressure on the land. Thus, in backbone of the national economy, but any future order to restore plant nutrients to depleted soils, economic growth hinges upon the development of the farmers must resort to the use of mineral fertilizers agricultural sector. This is clearly articulated in the coupled with other agronomic practices to enhance national economic policy "Agricultural Development crop yields and restore the fertility of the soil. Led Industrialization" that the Government has Many farmers and, surprisingly, educated people vigorously embarked upon. have the misconception that the use of mineral Over the last 30 years, the population of the fertilizers is wrong and leads to severe soil degradation country has increased at about 3 percent annually, and environmental problems. This misconception can, while food production during the same period had a however, be easily dispelled by the research data, mixed performance. From 1970 to 1980, food which show that, when lost nutrients are replaced, production declined 0.7 percent a year, and from 1980- intensive agricultural systems can be sustained 92, the decline was 0.4 percent a year. However, from indefinitely. One of the oldest continuous fertilizer 1995 through 1999 food production has increased experiments in the world is carried out in the UK at dramatically. This change has resulted from a Rothamsted. In some treatments within that trial, combination of factors, among which favorable mineral fertilizers have been continuously applied for weather and strong support by the government for more than 150 years, and the soils are currently more agricultural development are worth mentioning. productive than at any time in the past. Such an Approximately 40 percent of the Ethiopian experiment clearly shows that if plant nutrient deficits landmass is situated in the highlands, with altitudes are not corrected, no agricultural system can be of 1500 meters above sea level or more. Owing to sustained in the long term. However, research has also relatively favorable environmental conditions, these demonstrated that continuous unbalanced application highlands have 90 percent of Ethiopia's people and of nutrients inevitably leads to declining crop yields. cattle. At present the estimated human population is Thus, it is imperative to match the nutrients applied 60.5 million and the cattle population is 60 million. in mineral fertilizers with the requirements of both the The very high human and cattle density has had a soils and the crops grown therein. disastrous impact on the environment. In particular Despite nearly four decades of fertilizer the soil resource base has been degraded and nearly popularization efforts, Ethiopia exhibits one of the all forests have disappeared from the highlands. world's lowest rates of per capita fertilizer Crop cultivation in Ethiopia is predominantly in consumption. Therefore, optimizing fertilizer use in the peasant subsector and has hardly advanced Ethiopia is not only appropriate as an economic beyond the subsistence level. The use of agricultural imperative, but, also, because the sustainability of our practices based on science and modern technology is agriculture system is at stake. Our future development still at a very low leveL As a result, the adoption of / must be based on a more productive, sustainable, and new agricultural technologies has not taken root environment-friendly agricultural system that throughout the country. considers improvement in soil productivity a matter of utmost concern. The traditional land use systems rely on the exploitation of the soil, extracting all plant nutrients The collaborative work represented by Optimizing with basically no replenishment. When the process Fertilizer Use in Ethiopia is only the beginning of a long continues over several crop generations, land becomes term initiative. I personally welcome all the degraded as a result of nutrient mining, mainly as institutions that are involved in this undertaking, and harvest removals. This situation, in turn, leads to a I suggest that others join in. low-yielding subsistence agricultural system in which soil nutrient levels critically limit food and agricultural D r. M engistu H uluka productivity. Traditional land fallowing, used to build Minister of Agriculture ACKNOWLEDGMENTS
Many people have been directly involved in conducting this study and their contribution is greatly appreciated. A number of EARO scientists are continuing to participate in the process leading to the establishment of on-farm verification trials, which it is hoped will lead to the development of specific fertilizer recommendations for Arsi Zone. Among these, Dr. Paulos Dubaie (Director, Soil and Water Management Research), Dr. Tekaligne Mamo (soil scientist, Debre Zeit Agricultural Research Center), Dr. Sahelemedhin Sertsu (Head, National Soil Laboratory), Dr. Taye Bekele (soil scientist, Holeta Research Center), Dr. Amanuel Gorfu (agronomist, Kulumsa Research Center), Dr. Bedada Girma (National Wheat Research Coordinator, Kulumsa Research Center), and Ato Duga Debele (Center Manger, Kulumsa Research Center) deserve special mention. Dr. Thomas Payne and Dr. Wilfred Mwangi of CIMMYT-Ethiopia provided valuable input during the planning of this work. Dr. Tesfaye Tesema (durum wheat breeder and consultant to SG 2000/Ethiopia), Ato Bisrat Retu (senior expert, SG 2000/Ethiopia), and Ato Tamene Terfa (soils expert, Ministry of Agriculture) have actively participated in the committee commissioned to undertake this study. Ato Cheru Batu and Ato Alemu Kebede of the Arsi Bureau of Agriculture ably coordinated the field work associated with the collection of socio-economic and soil data. The questionnaire used to collect the socio-economic data was adapted from a questionnaire develop by Ato Regassa Ensermu (agricultural economist, Kulumsa Research Center) to study the effects of market liberalization on the supply and consumption of fertilizer in southeastern Ethiopia. The 300 farmers in the five woredas in Arsi and the Development Agents (DAs) who assisted in completing questionnaires and collecting soil samples must be thanked for their invaluable contributions. Ato Tesfaye Zegeye, head of the Socio-economic Department of EARO, kindly provided access to computers and data typists during data entery, while Miss Aklilewerk Bekele (CIMMYT-Ethiopia Secretary) provided a great deal of assistance in typing and retyping the draft document, and both deserve our appreciation. Finally, special thanks are due to Dr. Marco A. Quinones, Country Director of the SG 2000 Agriculture Program in Ethiopia, who originated the idea of this study and who subsequently facilitated the necessary funding through the Sasakawa Africa Association. EXECUTIVE SUMMARY
During 1995-99, Ethiopia's food production situation The specific objectives of this fertilizer adoption improved markedly, as a result of favorable weather survey were conditions combined with government support for • to collect baseline information on fertilizer usage agricultural development. Evidence of the high by peasant farmers in key woredas of Arsi Zone priority given to agricultural development in recent • to identify problems and constraints associated years is increased availability of mineral fertilizers, with fertilizer use as perceived by peasant farmers the relative ease with which small-scale farmers can access credit for input procurement, and • to identify the major soil types used for bread improvements in technical backstopping by the wheat production in Arsi Zone research and extension services. Annual sales of The survey Was conducted in the five major chemical fertilizer have grown from 32,000 tonnes in wheat-producing woredas of Arsi Zone: Asasa, Bekoji, 1982 to 280,000 tonnes during 1998. Etheya, Lole, and Robe. Within these five woredas, In subsistence agricultural systems, most farmers peasant associations were selected on the basis of cannot easily get the sums of money required to recorded levels of fertilizer consumption, and farmers purchase even moderate amounts of fertilizers. Thus, were randomly selected from within each peasant it is extremely important to determine the correct association. A sample of 60 farmers was taken from nutrient mix to optimize crop response and economic each woreda. Thus, a total of 300 farmers were return. Moreover, it has been generally observed that surveyed during May 1999. A total of 600 soil samples crop response to fertilizer declines if unbalanced crop were collected from the best and poorest fields nutrients are repeatedly applied. identified by each surveyed farmer. These samples were analyzed to facilitate planning of subsequent To identify the correct nutrient mix, and, thus, to field experiments. balance the application of fertilizers, a joint study is being conducted by the Ethiopian Agricultural The survey result revealed that the average family Research Organization, the Eastern Africa Cereals consisted of seven persons with a large proportion of Program of the International Maize and Wheat children-four per household. Off-farm employment Improvement Center (CIMMYT), the Ministry of opportunities were very limited: less than 8% of Agriculture (MOA), and Sasakawa-Global 2000 (SG households reported family members engaged in off- 2000). This study selected the ArSi Zone of Oromiya farm activities. The mean age of a representative Region as its initial focus for a socio-economic and household head was 47 years. Female-headed soil survey to determine the types and rates of households made up 17% of the sample. About 54% commercial fertilizers adopted by farmers, to estimate of the sampled farmers were illiterate. the benefits realized and the problems encountered The average land holding in the study area was in fertilizer use, and to generate soil data from samples p 10.7 timad (1 timad = 0.25 ha), varying from 7.48 timad collected in surveyed farmers' fields. Such information in Etheya to 14.27 timad in Bekoji. Twenty-two percent should facilitate the identification of relationships of the farmers rented-in an average area of 4.86 timad among soil chemical characteristics and the productive for crop production with a mean contractual period potential of the farmland. Arsi*Zone is an area of 1.55 years and a mean rent of about Birr 664/ha; characterized by a cereal-dominated farming system, 21% of the farmers rented-in grazing land for an and it has hosted long-term comprehensive average duration of 2.4 years with a mean rent of Birr development projects since 1967. 343/ha. Sharecropping was also common in the study area. About 99% of the farmers reported livestock farmers in 1998. The adoption rates for other improved ownership with a mean of about 8 TLUs (tropical wheat varieties were Pa von, 25%;Wabe, 15%; and ET- livestock units) per household. However, only 89% of 13,11%. In terms of area planted to each variety, Kubsa the surveyed farmers owned oxen with a mean (34.5%) and Pavon (26%) accounted for 60.5% of the number of 2.39 per owner household. Peasant farmers total wheat area. This indicates that there is a high did not have a significant asset base: less than 1% of level of awareness among farmers in Arsi Zone that the farmers owned a tractor and only 5% had a chemical fertilizer and improved high-yielding crop commercial grain store. Similarly only 19% owned varieties are important yield-enhancing agricultural radios and 6% had tape recorders. technologies. The results of the socio-economic survey revealed The increments in crop yields due to fertilizer that during 1998 mean fertilizer procurement by application, as estimated from farmers' reported yields farmers in Arsi Zone was roughly 150 kg of DAP and with and without fertilizer, were highly significant for 15 kg of urea per capita. Farmers' usage of urea is very the major crops in Arsi on both the best and poorest limited primarily due to their perceptions and fields. The estimated yield increments due to fertilizer preferences. For instance, only 23% of the surveyed application were more pronounced on the best than farmers procured urea during the 1998 cropping on the poorest fields. It is also interesting that a small season vs. 93% who procured DAP. During the period minority of farmers in Arsi Zone perceived that the 1995-98, the cumulative amount of urea procurement application of commercial fertilizer has negative or was only 5.1% of mean DAP procurement. However, nil effects on the yield of some of their crops. it is encouraging to note from the survey results that Estimates of fertilizer profitability in wheat were the proportion of farmers using urea in 1998 increased highly positive in both categories of fields. The by more than seven-fold relative to the 1995 season. estimated high profitability of wheat yield response Farmers acquired their fertilizer from Agricultural to fertilizer was consistent with the farmers' Inputs Supply Enterprise, Ethiopia Amalgamated, assessment of fertilizer profitability: 82.9% indicated Dinsho, Fertiline, and retailers in local markets. It was that incremental crop yields due to applied fertilizer found that fertilizer distribution centers were located sufficed to repay input loans. on average 6 km from the farm. About 82% of the Although a number of socio-economic variables, farmers had access to input credit, but 63% of the such as age, gender, literacy, family size, farm size, farmers reported a constraint to timely delivery of access to information, credit, and proximity to market, fertilizer. influence farmers' decisions on the use of fertilizer, Although 71% of the farmers were aware of multivariate regression models were not used to recommended fertilizer rates, only 16% of the wheat estimate the significance of these variables. An growers actually adopted the recommendations. The econometric analysis of factors affecting the adoption sources of information on fertilizer recommendations of fertilizer will be reported separately. included extension personnel, research institutes, Soil samples taken from fields identified by each relatives, friends, and SG 2000. of the surveyed farmers as best and poorest in terms Wheat and barley are the dominant crops and of crop production levels were analyzed for soil pH, cover 78% of the total cultivated land area in Arsi. organic matter, and available phosphorus (P) levels. Largely as a result of the heavy investment in wheat Subsequently, the soil data were statistically analyzed breeding by the former CADU/ARDU project and the to identify relationships among the soil chemical national wheat research program, 92% of the farmers characteristics and the productive potential of the in Arsi used improved wheat varieties in 1998— fields as perceived by the surveyed farmers. Analysis similar to the proportion of farmers adopting chemical of the soil data revealed clear differences among the fertilizers on wheat. Kubsa, the most widely adopted woredas for all measured soil parameters. However, wheat variety in the region, was grown by 39% of the no apparent difference in the pH levels in the best and poorest fields, was found. Analysis of farmers' reported crop yields and and 5.5 kg urea for barley, and 40 kg DAP and 7.0 kg measured soil parameters revealed statistically urea for tef. Thus, the current study revealed that significant relationships. Fields identified by farmers farmers in Arsi use 83% of the amount of DAP as high in productive potential exhibited higher soil recommended by MOA for wheat for Arsi, while the organic matter and P levels. This explains why many mean rate of application of urea on wheat is only 14% farmers in Ethiopia deliberately adjust the amount of of the recommendation. fertilizer applied on specific areas within a field and Farmers in Arsi perceive that there is a suggests that they may often be correct in doing so. considerable yield increment due to fertilizer Mean soil P contents (Olsen method) across Arsi Zone application on their major crops, in general, and on were 5.61 ppm for the poorest fields and 8.61 ppm for wheat and barley, in particular. They also believe that the best fields. Soil organic matter and available P this increment is substantially higher on their best contents were positively correlated across the five fields than on their poorest fields. This finding may woredas, suggesting that a significant fraction of the justify the need to establish fertilizer trials on both the available P content of Arsi soils is derived from soil best and the poorest fields as identified by farmers. organic matter. The current findings may also lead to the Soil P test values and crop yields were positively establishment of different recommendation rates for and significantly correlated both with and without fields characterized by variable levels of soil fertility fertilizer for Arsi Zone, suggesting that crop yields as identified by farmers. are enhanced by the levels of available soil P and that There were marked differences in the estimated the yield enhancement effect is independent of applied cereal crop yields across the five woredas surveyed, fertilizer. Overall, soil P levels and farmers' basal indicating variations in crop yield potential among application of DAP appear to have an additive and the five agro-ecologies. The establishment of fertilizer individually positive effect on crop yields. trials in each woreda will facilitate the development The cumulative farmer procurement levels of of fertilizer recommendations to increase productivity DAP and urea during the period 1995-98 were in the lower potential woredas. generally not significantly correlated with reported In agreement with earlier findings, this survey crop yields: the correlation between cumulative DAP confirmed the relationship between soil organic matter procurement and crop yield was only significant for levels and wheat response to fertilizer N. The study wheat yield with fertilizer on the best fields and the also showed that soils in the five woredas distinctly poorest fields. The cumulative DAP procurement level differ in soil organic matter content. Contrasting soil was also not significantly correlated with soil P test organic matter levels in the best and poorest fields values, either across Arsi Zone or within individual also revealed significant differences. Across the entire woredas, indicating that the current study failed to Arsi soil data set, there were also significant and capture any residual effect of the farmers' DAP positive correlations between soil organic matter level application history on the levels of available soil P. and yield increment due to fertilizer. Similarly, the correlations between cumulative urea One of the most important findings of this joint procurement levels and soil organic matter, soil pH, socio-economic and soil survey is that, although the and the indices of crop yield response to applied sampled farmers in Arsi purchased and applied, on fertilizer were predominantly nonsignificant. average, a cumulative total of 532 kg of DAP per farm However, given the extremely low level of urea during 1995-1998, cumulative DAP levels were not procurement throughout Arsi Zone, the absence of significantly correlated with either soil P test values significant correlations was logical. or crop yields across Arsi or within individual According to the current survey, the mean per woredas. This implies that the current study failed to hectare fertilizer application by farmers in Arsi Zone capture any residual effect of the farmers' DAP is 83 kg DAP and 18 kg urea for wheat, 59 kg DAP application history on the levels of available soil P, presumably because the amount of P added annually recommendations for Arsi Zone by woreda and soil in the form of DAP is too small to have any cumulative type. This suggests that fertilizer trials should be effect. Thus, there is clearly scope to increase the rate established in the major crop-producing woredas of of DAP application to enhance crop yields and Arsi and in fields identified by farmers as contrasting accumulate soil P capital. Similar surveys will be in terms of soil fertility The trial program should also conducted in other parts of Ethiopia characterized by encompass the themes of P rate calibration based on a long history of adoption of chemical fertilizer by soil test values, and a study of the residual effects of small-scale farmers. continuous P application. As far as practical, the Thus, considering (1) that fertilizer selection of fertilizer trial sites should take into recommendations do not exist for each of the major consideration the range of existing soil pH, organic crops within the specific agro-ecologies of Arsi Zone, matter, and P values, and not only mean values. Since (2) that marked variations were observed in the rates it may be important to consider other nutrients in of fertilizer application by farmers across the different addition to N and P, the fertilizer trials to be woredas within Arsi, and (3) that fertilizer rates established, particularly on red soils, should also adopted by farmers do not reflect the recommended include secondary treatments with potassium, sulfur, amounts, there is an urgent need to study and and micronutrients. The fertilizer trials should also subsequently refine crop-specific fertilizer incorporate treatments to study the timing of N fertilizer application. Introduction
1.1 Background backstopping by the research and extension services. Economic statistics on the distribution of output, Annual sales of chemical fertilizer in the peasant employment, and foreign exchange earnings clearly sector increased from 32,000 tonnes in 1982 to reveal that agriculture is the mainstay of the 280,000 tonnes in 1998 (NBE 1999). Ethiopian economy. Agricultural production The agricultural sector in Ethiopia is dominated accounts for 53% of GDP and nearly 90% of export by peasant production systems, which are earnings, and more than 70% of the labor force is characterized by rainfed production of food crops engaged in the agricultural sector (NBE 1999; ADB at or near the subsistence level. Agricultural 1996). Moreover, although agriculture provides raw production is highly dependent on traditional materials and markets for domestic industries, the farming practices. The use of modern agricultural role of agriculture in securing the food needs of the technologies, such as chemical fertilizer, high- population is of paramount importance. As a result, yielding varieties, herbicides, pesticides, and agriculture has been given the highest priority in irrigation, is at a relatively low level. Despite efforts the national economic policy—Agricultural to popularize and facilitate the transfer of new Development Led Industrialization. agricultural technologies, their adoption throughout Since the early 1970s, the performance of the the country has been uneven. In 1994/95, improved agricultural sector in Ethiopia has not met crop cultivars were used on only 0.9% of total expectations. The annual growth of agricultural cultivated land and fertilizer on only 28% of the production declined from 0.7% in the 1970-80 period cultivated land (CSA1995). \ to 0.4% in the 1980-92 period (World Bank 1994). One characteristic of subsistence farming is the 1 And at the same time, there was an unprecedented very low level of inputs invested in farm land to population growth, exceeding 3% a year, with an replenish soil fertility. This low level of input use, attendant increase in the demand for food and when continued over several generations, leads to natural resources. As a consequence, Ethiopia has nutrient mining—mainly as harvest removals. A become one of the food-deficit countries of Africa. low-yielding agriculture results, in which reduced Food self-sufficiency fell to 58% in 1991/92 (Mulat soil nutrient levels critically limit agricultural 1995). production. From 1995 to 1999, however, food production Ethiopia is one of the sub-Saharan African in Ethiopia improved substantially, partly as a result countries where severe soil nutrient depletion of favorable weather conditions and partly due to restrains agricultural production and economic government support for agricultural development. growth. The annual per-hectare net loss of nutrients The high priority given to agricultural development is estimated to be at least 40 kg N, 6.6 kg P, and 33.2 in recent years is demonstrated by increased kg K (Scoones and Toulmin 1999). Continuous availability of mineral fertilizers, the relative ease cropping, the high proportion of cereals in the with which small-scale farmers access credit for cropping system, and the application of suboptimal input procurement, and improvements in technical levels of mineral fertilizer aggravate the soil fertility decline (Hailu, Mwangi, and Workneh 1991; reviewed in light of the market liberalization Workneh and Mwangi 1992; Tanner, Amanuel, and implemented during the early 1990s (Hassena, Kassahun 1991). Tanner, and Amanuel 1995). Reflecting the genotype- In agriculture-based economies, agricultural specific nature of nutrient responses among intensification is a prerequisite for economic Ethiopian breadwheat cultivars (Asefa et al. 1999), development. However, agricultural intensification tables of zone- and cultivar-specific, price-dynamic has to be built upon a foundation of improved soil nutrient rate recommendations have been developed fertility management. Use of mineral fertilizers for use by extension staff (Tanner, Asefa, and should form the core of the soil fertility management Kefyalew 1999). These tables incorporate a range of regime, with complementary measures such as anticipated prices for N and P inputs and grain incorporation of crop residues or green manures output. used to enhance soil organic matter content. A series of on-farm trials are planned for the Improved soil fertility should lead to sustainable major wheat-growing areas of Arsi Zone in crop production and allow the efficient production southeastern Ethiopia with the aim of verifying the of high yielding crop cultivars with appropriate economically optimal nutrient mix, particularly husbandry practices. focusing on residual effects of applied P. However, In countries such as Ethiopia, where cash- prior to conducting on-farm experiments, it was constrained farmers are often unable to purchase the considered essential to conduct a survey to obtain recommended quantities of fertilizer/it is extremely information on current fertilizer use by peasant important to determine economically optimal farmers and to characterize the cropping systems of nutrient rates (Amanuel et al. 1991; Tanner, Asefa, the area. and Kefyalew 1999). The identification of the proper fertilizer mix is also beneficial at the macroeconomic 1.2 Objectives of the Survey level by improving the efficiency of fertilizer The survey was initiated to generate baseline procurement and resource allocation. It is generally information for the subsequent improvement of understood that crop response to fertilizer inevitably fertilizer rate recommendations. The survey covered declines if nutrient applications are continually the types and rates of fertilizer that Arsi fanners have unbalanced. However, if harvested nutrients are adopted and identified the benefits and problems replaced, intensive agricultural systems can be of fertilizer use. The specific objectives of the study sustained indefinitely, provided that measures are were to taken to halt soil erosion and to minimize detrimental changes in soil pH. • collect and evaluate baseline information on fertilizer use by peasant farmers in key woredas; The national breadwheat research program of of Arsi Zone Ethiopia has studied various aspects of the crop's response to applied nitrogen and phosphorus under • identify problems and constraints associated farmers' conditions throughout the Ethiopian with fertilizer use as perceived by peasant highlands. In contrast to the earlier nationwide farmers recommendations for N and P, the wheat research • identify the major soil types used for breadwheat team developed zone-specific nutrient production in Arsi Zone recommendations, focusing on the highest priority • facilitate the development of subsequent soil agroecological zones for breadwheat production fertility-related research themes and activities in (Amanuel et al. 1991). Optimal nutrient rates were Arsi Zone
2 1.3 The Study Area benefiting local farmers through the dissemination The surveyed areas in Arsi Zone are located in of improved agricultural technologies. Farmers' crop southeastern Ethiopia with elevations ranging from management practices (the use of seeds of improved 1,980 to 3,760 meters above sea level. The five cultivars, fertilizer, pesticides, etc.) are relatively surveyed woredas are dominated by cereal farming advanced in Arsi as compared with other regions of systems in which bread wheat and barley are the the nation: Arsi has 57% of Ethiopia's wheat major crops. In the 1994/95 cropping season, cereals production area that uses improved seeds and 37% accounted for 80% of the total cultivated land in Arsi of the wheat area on which fertilizer is applied (CSA Zone (CSA 1995). Wheat and barley occupied half 1995). The relatively well-established institutions and of the total cropped area (wheat covered 28% and infrastructure facilities in Arsi enhance farmers' barley 22%). access to improved agricultural technologies. In 1991, an adoption study conducted in Arsi Zone found that Beginning in 1967, Arsi Zone hosted a long-term 87% of surveyed farmers used fertilizer for wheat comprehensive integrated package project (CADU/ production, although 50% of the farmers applied 50 ARDU). Since then, other agricultural development kg/ha or less. But virtually all farmers planted seed projects have been implemented in the region, of improved wheat varieties (Mulugeta 1996). Methodology
2.1 Sampling Method 2.3 Soil Analysis The survey was conducted in the five major wheat- All soil analyses were conducted by the National Soil producing woredas of Arsi Zone—Asasa, Bekoji, Research Laboratory following standard laboratory Etheya, Lole, and Robe—during May 1999. Within procedures. these five woredas, peasant associations were The soil samples were air-dried at room selected on the basis of the longest recorded temperature by spreading the soil on plastic trays. experience of fertilizer consumption, and farmers Subsequent to drying, the samples were ground and were randomly selected from within the peasant passed through a 2-mm sieve. associations. A sample of 60 farmers was taken from Soil pH was determined in 1:2.5 soil:water each woreda; thus, a total of 300 smallholder farmers suspension. The soil suspension, after stirring for 30 were surveyed. Data were collected using a minutes using a mechanical stirrer; was subjected structured questionnaire. to pH determination using combined electrodes. Data on area, yield, and application rates are To determine available phosphorus, soil samples based on farmers' responses to enumerators' were analyzed by two procedures—Olsen (Olsen et questions (they were not measured directly). al. 1954) and Bray and Kurtz No. 2 (Bray and Kurtz Farmers in Ethiopia measure area in timad (1 timad 1945). The aim was to compare the procedures to = 0.25 ha) and weights in metric units. Farmers learn which one is most appropriate for Arsi soils. express yield as quintals per timad. For the Olsen method, 5 g of air-dried soil were Composite surface soil samples were collected shaken in 100 ml sodium bicarbonate solution at a from the plow layer of the best and poorest fields as pH of 8.5. The phosphate in the extractant was identified by each surveyed farmer. These samples determined colorimetrically using the blue were analyzed to facilitate site selection for ammonium molybdate method with ascorbic acid subsequent field experiments. as a reducing agent. For the Bray and Kurtz No. 2 method, 2 g of soil in 20 ml extraction solution were 2.2 Data Analysis shaken by hand for 1 minute. After extraction, available phosphorus content was determined Data were initially analyzed using descriptive colorimetrically with the addition of a mixed reagent. } statistics such as ratios, percentages, and means. Where appropriate, data were subjected to analysis Soil organic matter contents were determined of variance (ANOVA), paired T-tests, and using the colorimetric procedure of Walkley and correlations. All data analyses were conducted using Black (1947). SPSS Version 9.0 software.
4 Socio-Economic Characteristics of the Study Area
3.1 Household Characteristics school and 8% had completed secondary school. The The characteristics of the average family in the study remaining 22% of the farmers possessed basic area are shown in Tables 3.1,3.2, and 3.3. The typical literacy skills. family has about seven members, including many children—about four per household. Three family 3.2 Land Holding Characteristics members were working full-time on the farm, while Land holdings in the study area are very small, nearly three family members contribute labor to the mainly due to the high population density (Table farm on a part-time basis. Seventeen percent of 3.4). The mean farm size was 10.7 timad (2.7 ha), households were headed by females. The survey varying from 7.5 timad (1.9 ha) in Etheya woreda to revealed that about three family members attend 14.3 timad (3.6 ha) in Bekoji (1 timad = 0.25 ha). As a school. Few households have family members result, farmers allocate very limited areas to grazing engaged in off-farm activities such as daily labor (8% and fallowing. For farmers reporting such land uses, of households), civil service (8%), or trading the mean area of grazing land was 3.1 timad while activities (4%). The large size of households in Arsi Zone helps ensure adequate labor for various agricultural Table 3.2. Family age distribution of average households in Arsi Zone. activities. However, the large family size also creates j a heavy demand for food and natural resources Age group (no.) Age of 14 yrs or 15-60 Over 60 household despite the generally low level of agricultural Woreda less yrs yrs head (yrs) productivity, making food security at the household Asasa 4.9 (39) 3.4 (46) 2.0 (2) 44.6 level precarious. Bekoji 4.8 (48) 3.9 (44) 2.0 (3) 47.3 The mean age of a representative household Etheya 4.1 (37) 3.0 (44) 2.0 (6) 49.9 Lole 4.2 (44) 3.5 (55) - 47.3 t head was 47 years. Nearly 54% of the farmers were Robe 4.2 (46) 3.4 (57) 1.8 (4) 45.6 illiterate. Seventeen percent had completed primary Mean 4.5 (214) 3.4 (246) 1.9 (15) 46.9
Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999.
Table 3.1. Family composition and activities of average households
Work full Work part- Family members working off-farm (no.) Family size Household head (%) time on the time on the Daily Civil Woreda (no.) Male Female farm (no.) farm (no.) laborer servant Trader
Asasa 7.1 (60) 73.3 (44) 26.7 (16) 3.3 (60) 2.9 (36) 2.0 (1) 1.0 (3) 2.0 (2) Bekoji 7.4 (59) 81.7 (49) 18.3 (11) 2.8 (44) 2.7 (44) - 4.2 (6) 1.0 (4) Etheya 5.9 (58) 80.0 (48) 20.0 (12)'-' 2.3 (42) 2.4 (51) 1.4 (9) 1.9 (13) 1.5 (2) Lole 7.3 (59) 91.7 (55) 8.3 (5) 3.3 (56) 3.0 (45) 2.4 (11). 2.0 (1) 1.0 (1) Robe 7.0 (60) 88.3 (53) 11.7 (7) 3.8 (57) 2.0 (29) 1.0 (2) 20 (1) 2.0 (4) Mean 6.9 (296) 83.0 (249) 17.0 (51) 3.1 (259) 2.6 (205) 1.9 (23) 2.4 (24) 1.5 (13)
Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999.
5 Table 3.3. Education of average households.
Read and Primary Secondary Family members Woreda Illiterate (%) write (%) school (%) school(%) attending school (no.)
Asasa 57.9 (33) 10.5 (6) 21.1 (12) 10.5 (6) 3.0 (34) Bekoji 53.4 (31) 27.6 (16) 15.5 (9) 3.4 (2) 4.9 (44) Etheya 55.9 (33) 23.7 (14) 15.3 (9) 5.1 (3) 2.3 (47) Lole 50.8 (30) 20.3 (12) 16.9 (10) 11.9 (7) 2.8 (51) Robe 51.7 (31) 25.0 (15) 16.7 (10) 6.7 (4) 2.1 (28) Mean 53.9 (158) 21.5 (63) 17.1 (50) 7.5 (22) 3,1 (204)
Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999. fallow land was around 2.6 timad. However, only Sharecropping arrangements are also common 58% of the surveyed farmers reported having in the study area. About 12% of the farmers reported grazing and only 36% reported having fallow land. that they shared-in land for crop production to The problem of land scarcity was particularly mitigate land scarcity and to ensure adequate food apparent in Etheya and Robe woredas where there production for their households. is a shortage of grazing land and fallowing is About 22% of the farmers reported sharing-out virtually nonexistent. or renting-out arrangements for land. Such farmers To alleviate land shortage, 22% and 21% of the usually are resource-poor: 52% of the respondents farmers rented-in land for crop production and reporting sharing out of land did so due to a lack of grazing, respectively (Table 3.4). For these farmers, ox draught power (Table 3.5), and 32% did so the mean area rented-in for crop production was 4.9 timad (1.2 ha), with a contractual arrangement for Table 3.5. Reasons for sharing or renting-out land in Arsi 1.6 years and a rent of about Birr 664/-ha. By Zone, 1998 (% of respondents). comparison, rented grazing lands have a longer Shared-out Rented-out mean contractual term, 2.4 years, and lower mean Reasons (n =35) (n = 37) rent, Birr 343/ha, which is about half of the rent paid Can't afford seed and fertilizer 32 19.4 for cropping land. The low rental value of grazing Shortage of ox draught power 52 _ Problem of guarding 8 - lands was attributed to their low soil fertility and Family problem 8 41.7 sloping topography, which are not suitable for crop To pay land tax - 13.9 production. For consumption and credit payment - 16.7 To buy seed and oxen - 11.1
Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999.
Table 3.4. Average land holding in Arsi Zone, 1998.
Shared- Rented- Rented-in/crop production Rented-in/grazing Owned Fallow Grazing out out/cash Amt Duration Rent Amt Duration Rent Shared-in Woreda (timad) (timad) (timad) (timad) (timad) (timad) (yr) (Birr/ha) (timad) (yr) (Birr/ha) (timad)
Asasa 11.8 (60) 3.0 (34) 3.8 (30) 3.7 (3) 4.9 (9) 4.0 (16) 1.8 (16) 490 (16) 3.7 (18) 3.6 (17) 350 (17) 2.6 (11) Bekoji 14,3 (60) 2.9 (32) 5.3 (40) 3.0 (9) 2.3 (3) 4.1 (17) 1.1 (17) 306 (17) 4.4 (20) 1.1 (20) 200 (20) 2.6 (7) Etheya 7.5 (60) 0.6 (2) 1.2 (37) 3.0 (2) 1.9 (13) 5.2 (15) 1.0 (15) 1,249 (15) 1.5 (8) 1.1 (7) 200 (8) 1.7 (6) Lole 10.1 (60) 2.4 (38) 2.2 (17) 3.5 (6) 2.8 (9) 9.2 (10) 1.0 (10) 581 (10) 3.0 (8) 1.0 (6) 537 (8) 3.0 (2) Robe 10.0 (60) 1.0 (2) 2.8 (50) 2.0 (9) 1.9 (4) 2.1 (8) 3.8 (8) 541 (8) 2.2 (9) 5.0 (9) 803 (9) 2.0 (11) Mean 10.7(300) 2.6(108) 3.1 (174) 2.9 (29) 2.9 (38) 4.9 (66) 1.6 (66) 664 (66) 3.3 (63) 2.4 (59) 343 (62) 2.3 (37) i
Notes: Figures in parentheses are numbers of respondents; 1 timad = 0.25 ha. Source: Survey data, 1999, because they could not afford seed and fertilizer. 3.3 Livestock Ownership Similarly, 19% of those who rented out their lands Arsi Zone is characterized by mixed farming systems did so because they could not afford seed and in which both crop and livestock production provide fertilizer. Farmers also rented out farm land to obtain income to the peasant household. Virtually all cash for household consumption or to settle other farmers reported ownership of livestock with a mean obligations such as payment of credit and land tax. of 8 TLU (tropical livestock units) per household In contrast, fanners who had adequate resources, i.e., (Table 3.6). The total number of livestock kept on oxen, seeds, and fertilizer, rented additional land to the farm ranged from 5.2 TLU in Etheya to 9.8 TLU increase their total crop production. Such farmers in Asasa. The relatively low livestock population in are generally believed to be more progressive, i.e., Etheya can perhaps be attributed to shortage of land "risk takers/' in adopting improved agricultural in the area. Eighty-nine percent of farmers reported technology. owning oxen, on average 2.4 oxen per household. Livestock are raised for various economic and social reasons (Table 3.7). The livestock provide draught power, transport, and food (milk, meat,
Table 3.6. Type of livestock owned (no.).
Livestock Asasa Bekoji Etheya Lole Robe Mean
TLU3 9.8 (60) 8.9 (60) 5.2 (57) 8.9 (59) 7.1 (60) 8.0 (296) Cows 3.4 (50) 3.3 (51) 1.4 (40) 3.0 (50) 2.2 (56) 2.7 (250) Calves 2.5 (50) 2.8 (39) 1.4 (35) 2.6 (40) 2.2 (50) 2.3 (214) Heifers 2.5 (37) 3.1 (28) 1.5 (26) 2,5 (32) 1.8 (34) 2.3 (157) Bulls 2.2 (13) 1.0 (1) 1,0 (6) 1.5 (10) 1.6 (11) 1.7 (41) Oxen 2,4 (51) 2.5 (52) 2.2 (55) 2.5 (55) 2.3 (54) 2.4 (267) Steers 1.0 (1) 2.0 (3) - - 1.0 (1) 1.5 (6) Sheep 6.6 (44) 5.6 (37) 3.3 (18) 4.8 (40) 3.8 (21) 5.2 060) Goats 4.0 (7) 3.1 (11) ' 3.4 (7) 2,8 (6) 5.8 (5) 3.7 (36) Donkeys 1.7 (30) 1.8 (24) 1.7 (44) 1.5 (48) 1.3 (37) 1.6 (183) Horses 1.8 (35) 2.4 (37) 1.0 (4) 1.5 (38) 1.1 (17) 1.8 (131) Mules 1.0 (7) 1:0 (2) 1.0 (D 1.2 (5) 1.0 (4) 1.1 (19) Poultry 5.5 (13) - 3.3 (6) 8.0 (2) 7.0 (6) 5.5 (27)
a/ Tropical livestock units. Notes: Figures in parentheses are numbers of respondents. Source: Survey data, 1999.
Table 3.7. Purpose of owning livestock, Arsi Zone, 1998 (% of respondents).
Livestock Consumption Cash income Draught power Transport Threshing
Cows (n = 248) 91.1 26.6 - - Calves (n = 165) 52.7 61.8 9.1 - - Heifers (n = 133) 54.1 60.2 -- 0.8 Bulls (n = 46) 30.4 50.0 45.7 - 2.2 Oxen (n = 259) 2.3 8.5 94.6 - - Steers (n = 3) - 66.7 33.3 -- Sheep (n = 149) 38.3 92.6 - - - Goats (n = 37) 40.5 86.5 - -- Donkeys (n = 179) - 5.6 20.1 86.6 0.6 Horses (n = 129) - 5.4 6.2 , 95.3 0.8 Mules (n = 20) - .. .10.0 15.0 85.0 - Poultry (n = 26) 73.1 ' 61.5 - -
Notes: n = number of respondents. Total of percentages exceeds 100 if respondents gave multiple answers. Source: Survey data, 1999. eggs), and are a source of cash income for the farm The proportion of non-cereal crops is slight in household. Farmers keep small ruminants (sheep the current cropping systems. In terms of the and goats) primarily for market sales to generate proportion of total cropped area, wheat (55%) is cash income. Pack animals (donkeys, horses, and ranked first followed by barley (24%), tef (10%), mules) provide transport. Poultry production is maize (4%), and faba bean (3%). This dominance of destined both for household consumption and sales. cereal crops has an important implication for soil Cows supplement household food consumption fertility management because cereals are heavy through milk production. Calves and heifers provide consumers of soil nutrients, particularly soil both food and cash income for the farm household.
Table 3.9. Priorities in the disposal of crops produced, Arsi 3.4 Cultivated Crops Zone, 1998 (% of respondents).
Farmers grow multiple crops to satisfy family food Majority Majority Consumption and cash requirements. Cereals, particularly wheat for for and marketing Crop consumption marketing equal and barley, predominate in Arsi Zone (Table 3.8), mainly due to the high proportion of favorable Wheat (n= 301) 45.8 11.0 43.2 Barley (n = 210) 92.4 1.9 5.7 highland environments for the production of these Tef (n = 104) 75.0 7.7 17.3 crops. Tef, maize, faba bean, and linseed production Sorghum (n = 17) 76.5 - 23.5 follow wheat and barley in terms of importance. Maize (n = 85) 94.1 2.4 3.5 Faba bean (n = 80) 83.8 8.8 7.6 Other crops such as sorghum, field pea, potato, and Field pea (n = 17) 53.0 23.5 23.5 lentil are produced to a lesser extent. Chickpea (n = 2) 50.0 50.0 - Lentil (n = 4) 25.0 75.0 - The survey revealed that there are variations in Niger seed (n = 10) 10.0 80.0 10.0 the distribution of crops across the woredas. Wheat Linseed (n = 42) 7.1 92.9 - is the dominant crop in all woredas except Bekoji Rapeseed (n - 5) - 100 - where barley is dominant. In Robe woreda, almost Potato (n = 13) 53.8 23.1 23.1 Peas (n = 1) 100 - _ all farmers produce tef, but in Lole none reported Rye (n = 2) 100 - - tef production. Sorghum is produced exclusively in Chat (n = 1) 100 - - Etheya and Robe, while lentil production was Sugarcane (n = 2) 50.0 50.0 - Onion (n = 6) - 100 - restricted to Asasa and Robe. Field pea production Note: Figures in parentheses are numbers of respondents. was not reported in Asasa. Source: Survey data, 1999.
Table 3.8. Land allocation to different crops by woreda, Arsi Zone, 1998.
Land area (timad) Share of total Crops Asasa Bekoji Etheya Lole Robe Mean cultivated area (%)
Wheat 5.6 (58) 3.1 (56) 5.1 (57) 7.3 (58) 3.0 (57) 4.8 (286) 54.9 Barley 3.1 (49) 4.9 (51) 1.3 (47) 2.3 (47) 1.4 (14) 2.8 (208) 23.5 ; Tef 1.2 (13) 4.2 00) 1.0 (31) - 2.6 (54) 2.3 (108) 10.0 Sorghum - - 0.8 (12) - 2.10 (6) 1.3 (18) 0.9 Maize 0.1 (D 0.8 (2) 0.8 (36) 1.0 (6) 1.3 (42) 1.0 (87) 3.5 Faba bean 0.8 (9) 1.3 09) 0.7 (33) 0.8 (4) 1.4 (15) 1.0 (80) 3.2 Field pea - 1.2 (6) 0.5 (6) 0.5 (1) 1.0 (5) 0.9 (18) 0.6 Lentil 0.6 (2) - - - 1.5 (3) 1.2 (5) 0.2 Linseed 2.2 (9) 1.9 (18) 1.0 (1) 2.0 (1) 1.0 (15) 1.7 (44) 2.9 Potato 0.2 (5) 0.8 (3) 0.6 (5) - - 0.5 (13) 0.3
Notes: Figures in parentheses are numbers of respondents; 1 timad = 0.25 ha. Source: Survey data, 1999. nitrogen; leading to nutrient mining when cereals 3.5 Asset Ownership are continuously cultivated on a given land unit. Farmers seldom reveal their wealth status to Although farmers are often reluctant to disclose outsiders, however, asset ownership could serve as how they dispose of their harvested produce, an a proxy indicator of the socio-economic status of the overview of their priorities for specific crops is surveyed farmers. The survey showed that the presented in Table 3.9. Barley, tef, maize, sorghum, peasant farmers in Arsi Zone do not have a and faba bean are the major crops that are produced significant asset base (Table 3.10), For instance, less primarily to meet household food needs, although than 1% of the farmers had a tractor and only 5% to a limited extent these crops are also used for cash had a commercial grain store. Even small assets were purposes. However, wheat was reported to be the rare. Only 19% of the farmers had a radio, and only most important crop, satisfying both the cash and 6% owned a tape recorder. Based on asset ownership, food needs of the peasant household. This fact is also farmers in Etheya and Lole are relatively better off apparent from the large proportion of the cropped than farmers in the other woredas. It is plausible to land area allocated to wheat. Minor crops such as infer that the low level of asset ownership reflects lentil, linseed, onion, Niger seed, and rapeseed were the low economic status and subsistence nature of produced mainly as cash crops. the farming community.
Table 3.10. Assets owned by surveyed farmers (% of respondents).
Asset Asasa Bekoji Etheya Lole Robe Mean
Radio 20.0 20.0 23.3 15.0 16.7 19.0 Tape recorder 3.3 3.3 6.7 6.7 8.3 5.7 Knapsack sprayer -- 5.0 3.3 - 1.7 Commercial grain store 1.7 3.3 1.7 20.0 5.3 Tractor 1.7 - 1.7 . - 0.7 Broad-bed maker -- 3.3 - ■ 0.7 Bicycle -- 1.7 - - 0.3 Car - - 1.7 -- 0.3
Source: Survey data, 1999. Fertilizer Use and Sources of Financing
4.1 Fertilizer Consumption and Prices input supply, and credit programs. As a result, Arsi A number of development initiatives aimed at is one of ^ dominant zones in terms of fertilizer attaining food self-sufficiency have promoted the consumption in the peasant sector, consumption of fertilizer in the peasant farming The current survey revealed that for farmers in sector in Ethiopia. The policy measures have Arsi Zone who reported applying fertilizer between included price mechanisms (i.e., price control and 1995 and 1998, mean annual per capita consumption input subsidies) and non-price mechanisms (i.e., was roughly 150 kg of DAP (diammonium sulfate) research, extension, and credit). Arsi was among the and 60 kg of urea (Table 4.1). But farmers' use of first zones in which comprehensive package projects urea is still very limited. In 1998, only 23% of the were implemented. The Arsi Rural Development surveyed farmers used urea, procuring an average Unit (ARDU) invested heavily in research, extension, of about 60 kg, as compared with 93% of the farmer^
Table 4.1. Fertilizer prices and average annual fertilizer consumption per farmer, Arsi Zone, 1995-98/
DAP Carryover Urea Woreda Farmers (no.) Amt (kg) Price* (Birr/q) Farmers (no.) Amt (kg) Farmers (no.) Amt (kg) Price6 (Birr/q) 1995 Asasa 55 134 178 3 37 -- 168 Bekoji 49 163 178 1 50 2 50 168 Etheya 48 134 178 -- 6 67 168 Lole 58 202 178 - --- 168 Robe 40 79 178 1 134 1 50 168 Mean 250 146 178 5 59 9 61 168 1996
Asasa 56 130 200 - - 4 50 190 Bekoji 52 156 200 -- 190 _ Etheya 48 144 200 - - 9 56 190 Lole 60 207 200 -- 3 50 190 Robe 50 80 200 - - 4 62 190 Mean 266 146 200 -- 20 55 190 1997 Asasa 59 115 . 244 - - • 10 50 230 Bekoji 54 185 248 -- 3 67 186 Etheya 51 157 242 -- 19 54 229 Lole 60 218 242 -- 5 70 227 Robe 47 87 248 - - 7 50 235 Mean 271 155 245 -- 44 55 221 1998 Asasa 59 126 215 -- 13 65 166 Bekoji 53 186 225 2 38 4 56 171 Etheya 56 149 214 3 69 27 61 162 Lole 60 206 221 -- 10 60 167 Robe 51 88 228 5 75 14. 54 174 Mean 279 152 220 10 66 68 60 168 a/ Reported by fertilizer users, bI Pan-territorial prices were in effect until 1997. Source: Survey data, 1999. q = quintal {100 kg) who used DAP, procuring an average of 152 kg of As a result, a few private and semi-autonomous DAP. However, the proportion of fanners using urea enterprises, such as Ethiopian Amalgamated in 1998 had grown more than seven-fold compared Limited, Dinsho, Fertiline, and Ambassel, are with 1995. Urea was used primarily in Etheya (45% currently engaged in the procurement and of the farmers applied urea in 1998) where the wheat distribution of fertilizer. Both wholesale and retail yield response to N has been shown to be highly functions are undertaken by the networks of these profitable (Amanuel et al. 1991; Tanner, Asefa, and enterprises. In 1996, the private sector accounted for Kefyalew 1999). 35% of total fertilizer imports (Mulat 1996). At The price of fertilizer has varied markedly. The present, AISCO and Ethiopian Amalgamated are the price of DAP increased from Birr 178/q in 1995 to dominant agents in the fertilizer market. Birr 220/q in 1998; the price of urea rose from Birr Farmers in Arsi Zone reported that they obtain 168/q in 1995 to Birr 221/q in 1997, but fell to Birr fertilizer from AISCO, Amalgamated, Dinsho, 168/q in 1998. Price changes can be attributed Fertiline, and retailers in local markets. In 1998, about primarily to three factors: the devaluation of the local 46% of the farmers reported that they procured currency, market liberalization, and international fertilizer from AISCO through Ministry of fertilizer prices. Before 1997 the government Agriculture (MOA) offices in their areas (Table 4.2). subsidized fertilizer to facilitate consumption in the Twenty percent of the respondents indicated that smallholder sector. The government budgeted Birr they obtained their supplies from Amalgamated, 50 million annually for fertilizer subsidies from 1994 11% obtained supplies from Dinsho, and 17% used to 1996 (Mulat 1996). In 1996, there was a 22% subsidy Fertiline. Since retailers sell fertilizer solely on a cash on the price of DAP and a 23% subsidy on urea. basis, only about 19% of respondents bought The price of fertilizer in Arsi Zone, as in other fertilizer in the local market. This is most likely regions of the country, has been directly affected by because farmers are usually short of cash and they the national fertilizer pricing policy. Until the subsidy have limited access to credit for fertilizer purchases. program was abolished in 1997, a pan-territorial One hallmark of fertilizer marketing in Ethiopia fertilizer pricing policy was implemented by the is that the timing of sales is closely related to the government. That is, fertilizer cost the same cropping calendar. This is due mainly to the irrespective of the location of the distribution centers. predominant single cropping season and the The uniform fertilizer prices were set by the subsistence nature of farming. Fertilizer purchases government each year based on cost structures are, thus, not evenly spread over the year. Farmers submitted by importers. The subsidy element was in Arsi purchase fertilizers primarily between May also reviewed annually by the government. and July. In 1998, about 82% of the farmers reported
Table 4.2. Fanners' sources of fertilizer, Arsi Zone, 1998 (% of 4.2 Farmers'Sources of respondents).
Fertilizer and Time of Purchase 1995 1996 1997 1998 It is important to understand the fertilizer marketing Source (n = 194) (n = 219) (n = 227) (n = 297) system before examining the specific sources of AISCO 86.6 72.9 70.3 45.6 fertilizer in the study areas. Prior to 1991, the Amalgamated Limited 2.1 12.1 10.5 20.3 Dinsho 0.5 1.9 8.2 11.1 Agricultural Inputs Supply Corporation (AISCO) Retailers and local markets 8.2 12.2 11.9 19.1 was the sole agent responsible for the procurement Fertiline 2.6 3.3 2.7 16.9 and distribution of fertilizer in Ethiopia. In 1992, the Service coop/ farmers' association -- 0.8 fertilizer market was liberalized to promote the Note: Figures in parentheses are numbers of respondents. participation of the private sector in fertilizer trading. Source: Survey data, 1999.
11 procuring fertilizer in June while 18% did so in July cannot find buyers in the market once the planting (Table 4.3). During the peak planting season, farmers season is finished. They have thus to wait until the spend time waiting at distribution centers to buy next cropping season if they have carryover fertilizer fertilizer, which lowers their potential crop yields stock, increasing their capital and handling costs. by forcing them to delay planting beyond the Fertilizer distribution centers are often located optimal period. near the development centers of the MOA and The marketing of fertilizer within a limited service cooperatives (where these are functional). period also has a negative effect on traders: they The location of distribution centers has an impact on farm resources in terms of time and transport Table 4.3. Month of fertilizer purchase (% of respondents). costs. Fortunately, in Arsi, farms are relatively near
Woreda January March May June July the fertilizer distribution centers—6 km away on 1995 average (Table 4.4). The distances range from 14 km Asasa (n = 49) 6.1 93.6 in Asasa to 3 km in Etheya and Robe. The relatively Bekoji (n = 36) 83.3 16.7 well-established distribution networks are primarily Etheya (n = 50) 84.0 16.0 Lole (n = 58) 1.7 98.3 the result of the rural development projects Robe (n = 35) 2.9 2.9 17.1 77.1 conducted in Arsi Zone over the last three decades. Mean (n = 228) 0.4 0.4 1.8 79.4 18.0 1996 Asasa (n - 51) 3,9 96.1 4.3 Fertilizer Package Size Preferences Bekoji (n = 46) 82.6 17.4 Etheya (n = 52) 80.8 19.2 DAP fertilizer has been sold only in 50 kg bags. Lole {n = 59) 1.7 98.3 Consequently, buyers of DAP must purchase 50 kg Robe (n = 47) 29.8 70.2 Mean (n = 255) 1.2 78.8 20.0 even if they require less. For urea, however, 25 kg 1997 bags have become available in recent years in Asasa (n = 54) 3.7 96.3 Bekoji (n = 46) 100 addition to 50 kg bags. Etheya (n = 54) 75.9 24.1 Farmers were asked to state their preferences Lole (n = 59) 100 Robe (n = 46) 37.0 63.0 among fertilizer package sizes of 10 kg, 25 kg, and Mean (n = 259) 0.8 83.0 16.2 50 kg. Their preferences were different for DAP and 1998 urea. About 94% of the respondents preferred the Asasa (n = 53) 100 Bekoji (n = 51) 100 50 kg bag for DAP; only 5% opted for the 25 kg bag. Etheya (n = 58) 75.9 24.1 However, for urea, 60% of the farmers preferred the Lole (n = 59) 1.7 98.3 25 kg bag (Table 4.5). About 90% of the respondents Robe (n = 50) 32.0 68.0 Mean (n = 271) 0.4 81.9 17.7 said they preferred the 50 kg bag for DAP because
Note: Figures in parentheses are numbers of respondents. the package size is sufficient for their plots or because Source: Survey data, 1999.
Table 4.4. Average distance of fertilizer distribution centers from farm (km).
1995 1996 1997 1998 Distance Farmers Distance Farmers Distance Farmers Distance Farmers Woreda (km) (no.) (km) (no.) (km) (no.) (km) (no.)
Asasa 12.9 48 15.9 49 14.2 51 13.9 59 Bekoji 5.3 37 4.9 38 5.8 39 6.9 48 Etheya 3.9 50 3.9 48 3.3 49 3.3 53 Lole 4.0 57 4.0 58 4.0 58 4.0 59 Robe 3.7 37 3.2 49 3.2 46 3.1 50 Mean 6.0 229 6.4 242 6.2 243 6.2 262
Source: Survey data, 1999. it is a quantity of fertilizer they can afford. For the service cooperatives or farmers' groups. Normally, same reasons, 58% of the farmers preferred the 25 fertilizer credit is given without any collateral kg bag for urea (Table 4.6). requirements; instead, local administrators assume the responsibility for loan guarantees. The credit is extended with a 12% interest charge on the principal 4.4 Sources of Finance for of the loan. Farmers are required to pay down 25% Purchasing Fertilizer of the principal value upon negotiating the loan, and Farmers can purchase fertilizer with their own cash the remaining 75% is to be repaid after harvest. or on a credit basis. Since farmers often have limited Moreover, to be eligible for a fertilizer credit, a farmer cash especially between the planting and harvesting must have settled his previous debt within the seasons, the availability of credit to buy fertilizer is specified term. vitally important for them. The survey revealed that Although the fertilizer credit is available without during the 1998 cropping season 76% of the farmers collateral, the credit terms require repayment of the used credit to buy fertilizer while 6% used a loan right after harvest. In the immediate post combination of their own cash and credit (Table 4.7). harvest period, however, crop prices are low as a The present input credit system involves banks, rule, so that the productivity gains from fertilizer regional governments, and the farmers themselves. use are limited. Extending the time for repayment Under an agreement between the banks and regional of fertilizer loans for several months until crop prices governments on the provision of fertilizer loans, the rise would enhance the benefit farmers obtain from governments are responsible for ensuring credit using fertiliser. collection. Fertilizer credit is made available through
Table 4.5. Preferences for alternative fertilizer package sizes Table 4.6. Reasons for preferences for alternative package (% of respondents). sizes (% of respondents).
Woreda 10 kg 25 kg 50 kg Reason 10 kg 25 kg 50 kg DAP DAP (n = 218) Asasa (n = 53) - - 100 Can afford 0.9 3.7 59.2 Bekoji (n = 14) 7.1 - 92.9 Enough for my plot - . 1.4 31.2 Etheya (n = 50) 2.0 8.0 90.0 Not manageable for transport - - 0.4 Loie (n = 49) - 6,1 93.9 Manageable for transport - - 2.8 Robe (n = 55) - 7.3 92.7 Own experience - - 0.4 Mean(n = 221) 0.9 5.0 94.1 Urea (n = 160) Urea Can afford 1.9 33.8 23.8 Asasa (n = 9) - 88.9 11.1 Enough for my plot - 23.8 13.7 Bekoji (n = 10) - 70.0 30.0 Not manageable for transport - 0.6 0.6 Etheya (n = 37) 37.8 62.2 Manageable for transport i - 0.6 0.6 Lole (n = 50) 96.0 4.0 Own experience - 0.6 - Robe (n = 55) 5.5 36.4 58.2 Note: Figures in parentheses are numbers of respondents. Mean (n = 161) 1.9 60.2 37.9 Source: Survey data, 1999. Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999.
Table 4.7. Sources of finance for fertilizer purchase, 1998 (% of respondents).
Source Asasa (n = 59) Bekoji (n = 50) Etheya (n = 60) Lole (n = 59) Robe (n = 47) Mean (n = 302)
Own cash 32.2 22 10.0 10.2 23.4 17.5 Credit 62.7 72 96.7 93.2 95.7 76.5 Both 13.6 16 - 3.4 - 6.0
Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999.
13 CROPPING PATTERNS AND FERTILIZER ADOPTION
5.1 Crops Produced (8%), and Batu (7%) (Table 5.2). Comparing the A number of improved crop varieties have been distribution of varieties among the woredas revealed released and disseminated in Arsi Zone over the past that Kubsa was dominant in two of the five woredas. decades. As a result, farmers grow an array of Pavon and Batu were not planted in Bekoji, and improved varieties of wheat, barley, maize, tef, faba Wabe was not planted in Robe. Survey results also bean, linseed, and other crops. revealed that adopters of Pavon planted an average of 4.8 timad of that variety, adopters of Kubsa Only 8% of the farmers in Arsi grew local wheat planted 4.0 timad, adopters of Batu planted 3.5 varieties (Table 5.1). Of the improved wheat varieties, timad, and adopters of Dashen planted 3.3 timad Kubsa was the most widely adopted: 39% of the (Table 5.2). farmers grew it in 1998. Farmers also reported high adoption rates for Pavon (25%), Wabe (15%), ET-13 The predominance of improved varieties of (11%), and Dashen (11%), all of which are improved breadwheat in Arsi Zone is directly attributable to varieties. Two varieties, Kubsa and Pavon, accounted the heavy investment in wheat breeding by the for 60% of the total wheat area in 1998. Individually, CADU/ARDU project and the national wheat in terms of area covered, the major varieties were research program. The grain yield potential of Kubsa (34%), Pavon (26%), Wabe (11%), Dashen breadwheat cultivars released in Arsi Zone between 1957 and 1987 has grown by 2.2%, or 77 kg/ha, a year (Amsal, Tanner, and Getinet 1995). Furthermore, Table 5.1. Adoption of wheat varieties, Arsi Zone, 1998 (% of in a series of on-farm trials conducted across Ethiopia respondents). in the mid-1990s, the recently released semi-dwarf Asasa Bekoji Etheya Lole Robe Mean varieties Kubsa and Galama significantly outyieided Variety (n = 59) (n = 51) (n = 57) (n = 59) (n = 57) (n = 283) the taller check varieties Enkoy and ET-13 (Asmare Kubsa et al. 1997), (HAR1685) 44.1 13.7 71.9 42.4 21.1 39.2 Pavon-76 28.8 22.8 61.0 8.8 25.1 Batu 3.4 _ 35.1 5.1 3.5 9.5 Table 5.2. Average area (per adopter) sown to individual Enkoy - 3.9 - - 1.8 1.1 wheat varieties, Arsi Zone, 1998 (timad). Dashen 15.3 37.3 3.5 - - 10.6 Variety Asasa Bekoji Etheya Lole Robe Mean Local - 2.0 - _ 38.6 .8.1 Wabe Kubsa 4.6 2.1 3.9 4.8 2.3 4.0 (111) (HAR710) 33.9 9.8 8.8 22.0 - 15.2 Pavon-76 3.7 - 2.2 6.5 2.9 4.8 (71) K6290-Bulk ---- 21.1 4.2 Batu 3.5 - 3.8 3.0 1.5 3.5 (27) Galama Enkoy - 2.0 - - 3.0 2.3 (3) (HAR604) 1.7 17.6 1.8 - - 3.9 Dashen 4.8 2.7 2.5 -- 3.3 (30) Mitike Local - 1.0 -- 3.0 2.9 (23) (HAR1709) 1.7 - 1.8 - 3.5 1.4 Wabe 4.1 1.8 2.2 3.9 - 3.5 (43) ET-13 1.7 35.3 -- 22.8 11.3 Galama 3.0 1.8 2.0 - - 1.9 (11) K6295-4A - 2.0 --- 0.4 Mitike 3.0 - 2.0 - 1.5 2.0 (4) Israel - 2.0 --- 0.4 ET-13 2.0 2.3 -- 2.4 2.3 (32)
Notes: n = number of respondents. Total of percentages exceeds 100 if Notes: Figures in parentheses are numbers of respondents; respondents gave multiple answers. 1 timad = 0.25 ha. Source: Survey data, 1999. Source: Survey data, 1999.
14 Similarly, most farmers in Arsi have adopted concentrated in Etheya and Robe woredas. improved varieties of barley; only 11% of the sampled Moreover, the average area devoted to maize farmers used local barley varieties (Table 5.3). Thirty production is much smaller than that of wheat or percent of the farmers planted the variety Aruso and barley. 11% planted Semareta. Other varieties adopted by many farmers were Holker and Sheneka. The rates 5.2 Soil Types of adoption varied across the study areas. Although 49% of the farmers in Lole grew Semareta, the variety Soil type strongly influences the production was not reported in any other woreda. Similarly, decisions of a farm household. It is an important Holker was virtually restricted to Bekoji, where it was technical factor determining the crop species or grown by 42% of the farmers. In 1998, Aruso and variety the farmer plants or the alternative uses for Sheneka covered 41% of the total barley area in Arsi a field. To provide an overview of the array of soil in (Aruso 25% and Sheneka 16%). Semareta and Holker, the study areas, soil types were surveyed. respectively, accounted for 9% and 14% of the total In general, the survey results revealed that grey barley area, while local varieties occupied 9% of the loam is the dominant soil type for cereal crops, area. The average adopter had 2.2 timad of Aruso, followed by Vertisols. In 1998, the majority of the 3.9 timad of Sheneka, 3.4 timad of Holker, and 2.2 sampled farmers (75%) produced wheat on grey timad of Semareta (Table 5.4). loam soil, 35% planted wheat on black clay (Vertisol), In contrast to wheat and barley growers, nearly and 21% planted on red clay (Nitosol) soil types 66% of the farmers growing maize in Arsi Zone use (Table 5.5). Nearly 55% of the farmers planted barley local varieties (Appendix 1). Mize and Katumani, the on grey loam, 32% planted on Nitosols, and 28% most important improved maize varieties, were planted on Vertisols. Tef was planted primarily on grown by only 16% and 10% of the respondents, grey loam (45%) and Vertisols (42%). Of the farmers respectively. Within Arsi Zone, maize production is growing maize, about 58% located their maize fields on grey loams and 26% planted on Vertisols.
Table 5.3. Adoption of barley varieties, Arsi Zone, 1998 {% of Table 5.4. Average area (per adopter) sown to individual respondents). barley varieties, Arsi Zone, 1998 (timad).
Asasa Bekoji Etheya Lole Robe Mean Variety Asasa Bekoji Etheya Lole Robe Mean Variety (n = 51) (n = 50) (n = 46) Semareta ' - - ■ - 48.9 - 11.1 Holker 3.0 3.4 __ - 3.4 (22) - Holker 2.0 42.0 ■ - 10.6 Bre 0.9 1.8 - 2.2 - 1.6 (11) _ Bre 13.7 10.0 6.4 ; - 7.2 HB42 - 2.8 - - - 2.8 (8) - - HB42 18.0 -- 4.3 Venka 3.0 2.0 -- - 2.7 (3) Venka 3.9 2.0 --- 1.4 Werkiye 2.7 --- 1.0 2.2 (4) Werkiye 5.9 -- - 7.1 1.9 Sheneka 3.2 10.8 - - - 3.9 (17) _ Sheneka 25.5 8.0 -- 8.2 Atlas - 2.0 - - 4.0 - 2.5 (4) Atlas - 6.0 - 2.1 - 1.9 Tikur Gebse - 2.7 - 4.0 - 3.0 (4) Tikur Gebse - 8.0 - 2.1 - 2.4 Nechi Gebse - 2.4 --- 2.4 (8) Nechi Gebse - 16.0 - - - 3.8 Abado - 5.0 — - - 5.0 (2) Abado - 4.0 - - - 1.0 Asheles - 2.7 - -- 2.7 (3) - --- Asheles 6.0 1.4 Bahirseded - 2.0 -- — 2,0 (2) Bahirseded - 4.0 -- _ 1.0 Notes: Figures in parentheses are numbers of respondents; Notes: n = number of respondents. Total of percentages exceeds 100 if 1 timad = 0.25 ha. respondents gave multiple answers. Source: Survey data, 1999. Source: Survey data, 1999. 15 5.3 Crop Rotations been planted with barley in 1997 and 1996, Farmers often alternate crops from year to year and respectively; 10% and 12% of the farmers planted field to field. However, cereals dominate the crop barley where tef had been in 1997 and 1996, production systems in the study areas. Thus, in 1998, respectively; 40% and 26% of the farmers planted 67% of the farmers planted wheat on fields that had barley following wheat in 1997 and 1996, been sown to barley in 1997, and 39% planted wheat respectively. The proportion of pulses in the crop on fields that had been sown to barley in 1996 (Table rotation system is minimal. For instance, 3% of the 5.6). In the same year, 59% and 70% of the farmers farmers planted barley on fields that had been sown planted wheat on fields that had been sown to wheat to faba beans in 1997 and 5% planted barley on field in 1997 and 1996, respectively. Only 5% and 8% of that had been in faba beans in 1996. the farmers planted wheat on fields that had been This cereal-dominated crop rotation system has left fallow in 1997 and 1996, respectively (data not an important implication for soil fertility shown). management. Cereals are heavy users of soil Barley, similarly, was sown primarily on fields nutrients, particularly nitrogen, emphasizing the that had previously been in cereals. In 1998,18% and importance of applying optimal levels of mineral 51% of the fanners planted barley on fields that had fertilizers to minimize soil fertility decline. Table 5.5. Soil types in relation to crop grown, Arsi Zone, 1998 Table 5.6. Rotation crops, Arsi Zone (% of respondents). (% of crop fields). 1998 crop Black Red Grey Dark Precursor crop Wheat Barley Tef Linseed Maize Faba bean Woreda ciay clay loam grey Intermediate Wheat Wheat 1996 (n = 278) 69.9 26.2 8.2 8.6 3.6 2.9 Asasa (n = 76) 39.5 23.7 36.8 1997 (n = 277) 59.2 39.7 8.7 8.7 5.1 3.2 Bekoji (n = 76) 43.4 39.5 17.1 -- Barley Etheya {n = 85) 17.6 10.6 65.9 5.9 - 1996 (n = 198) 38.9 50.5 4.5 6.6 1.0 5.1 Lole (n = 78) 2.6 - 97.4 _ 1997 (n = 196) 67.3 17.9 4.1 5.6 2.0 3.1 Robe (n = 71) 28.2 4.2 57.7 5.6 4.2 Tef Mean (n = 386) 25.9 15.5 55.4 2.3 0.8 1996 (n = 98) 36.7 12.2 26.5 5.1 3.1 2.0 Barley 1997 (n = 99) 42.4 10.1 17.2 16.2 3.0 1.0 Asasa (n = 53) 52.8 17.0 30.2 Maize Bekoji (n = 72) 19.4 72.2 8.3 -- 1996 (n = 77) 22.1 11.7 1.3 1.3 62.3 2.6 Etheya {n = 48) 22.9 8.3 64.6 4.2 1997 (n = 76) 30.3 5.3 1.3 - 53.9 9.2 Lole (n = 51) 3,9 96.1 ■ - Robe (n = 14) 7.1 - 71.4 - 21.4 Notes: n = number of respondents. Total of percentages exceeds 100 if respondents gave multiple answers. Mean (n = 238) 23.5 27.3 47.1 0.8 1.3 Source: Survey data, 1999. Tef Asasa (n = 9) 55.6 22.2 22.2 - Bekoji (n = 7) 85.7 14.3 - Table 5.7. Farmers' perceptions of the advantages of crop Etheya (n = 28) 32.1 50.0 10.7 - 7.1 rotation (% of respondents). Lole (n = 0) - - . - -- Robe (n = 56) 37.5 1.8 50.0 5.4 5.4 Asasa Bekoji Etheya Lole Robe Mean Mean (n = 100) 41.0 6.0 44.0 6.0 3.0 Advantage (n = 59) (n = 54) (n = 51) (n = 60) (n = 57) (n = 281) Maize Bekoji (n = 1) 100 ■_ _/ Soil fertility 96.6 100 100 100 96.5 98 i Etheya (n = 36) 13.9 5.6 69.4 11.1 - Disease Lole {n = 3) 33.3 - 66.7 - - control 23.7 35.2 21.6 31.7 21.1 26.7 Robe {n = 39) 33.3 2.6 46.2 7.7 10.3 Weed Mean (n = 79) 25.3 3.8 57.0 8.9 5.1 suppression 54.2 37.0 33.3 36.7 35.1 39.5 Increase yield 15.3 1.9 -- 1.8 3.9 Notes: n * number of fields sown to each crop. Total number of fields exceeds number of surveyed farmers in each woreda if respondents Notes: n = number of respondents. Total of percentages exceeds 100 if gave multiple responses (i.e., sowed multiple fields of a specific crop). respondents gave multiple answers. Source: Survey data, 1999. Source: Survey data, 1999.. 16 Among the reasons given for using crop Although farmers express awareness of the rotations, almost every farmer mentioned soil advantages of crop rotation, some technical and fertility (Table 5.7). Since crops differ in their capacity socio-economic considerations hinder their use of for nutrient uptake, the rotation of crops along with rotations. The widespread land shortages., along with associated management practices helps to maintain the perceived low yields of pulse crops, force farmers soil fertility or reduces the rate of nutrient mining. to practice continuous production of higher yielding Among the other advantages of crop rotation were cereal crops. Moreover, pulses are relatively more disease control, reported by 27% of the farmers, and susceptible to pests and diseases than cereals. As weed suppression, reported by 40%. reasons for not rotating crops, 73% of the sampled Long-term crop rotation studies conducted at farmers reported land shortage, and 44% cited low two sites in Arsi Zone have shown that when wheat yield of the alternative crops (Table 5.8). Low market followed a faba bean precursor crop, wheat yields prices for alternative crops were also reported as a were significantly increased in two consecutive major constraint to adopting crop rotation. Farmers seasons. In comparison with a continuous wheat often opt for the crops that attract a favorable market crop, yield increments ranged from 50% to 121% for price. the first wheat crop and from 6% to 69% for the second wheat crop (Tanner et al. 1999). Crop 5.4 Land Preparation rotations significantly affected weed populations. Land is commonly prepared with the maresha, the For example, the density of the problematic grass local ox plough. The frequency of ploughing varies weed species Bromus -pectinatus is significantly among crops. Wheat, barley, and maize fields are reduced when wheat follows faba bean or rapeseed ploughed an average of four times, while tef fields (Asefa and Tanner 1998; Kefyalew et al. 1996). are ploughed nearly five times (Table 5.9), clearly Economic analysis of the same trial data sets showing that tef requires more labor for land showed that faba bean production is less profitable preparation than other cereals. than continuous cereal production (Tanner et al. About 14% of the sampled farmers in Arsi 1999). However, due to the yield increments in the ploughed their wheat fields twice using tractors. two successive crops of wheat following faba bean, Tractor ploughing is more frequent in Lole (30%) and the economically optimal rotation consisted of one Etheya (23%) than in Asasa (13%) and Bekoji (5%), crop of faba bean followed by two crops of wheat. and no farmer in Robe reported tractor ploughing. Furthermore, the faba bean precursor enhanced the Tractors are frequently hired for the first ploughing, wheat crop's response to fertilizer P and reduced especially for wheat fields. the response to fertilizer N. These phenomena were apparent in both the agronomic and economic analyses. Table 5.8. Reasons for not using crop rotation (% of respondents). Reasons Asasa (n = 23) Bekoji (n = 4) Etheya (n = 16) Loie (n = 49) Robe (n = 54) Mean (n = 146) Shortage of land 60.9 75.0 62.5 87.8 68.5 72.6 Low yield of alternate crops 60.9 25.0 12.5 20.4 68.5 43.8 Low prices for alternative crops 52.2 25.0 56.3 - 5.6 17.1 Lack of money 4.3 -- 2.0 - 1.4 Shortage of seed - - - - 3.7 1.4 Good yield of sole crop, especially. cereals - - 2.0 - 0.7 Susceptibility of pulses to pests -- 6.3 - - 0.7 Notes: n = number of respondents. Total of percentages exceeds 100 if respondents gave multiple answers. Source: Survey data, 1999. 5.5 Fertilizer Adoption barley Both the adoption and mean application rates Chemical fertilizer is an important yield-enhancing showed significant variation across the different technology without which agricultural productivity crops and the five woredas. Average fertilizer could not be maintained. In particular, the improved adopters in Arsi applied 90 kg/ha of DAP on wheat, high yielding crop varieties cannot express their full 76 kg/ha on barley, and 55 kg/ha on tef. Maize yield potential without the application of inorganic received on average 63 kg/ha. By woreda, the mean fertilizer. As a result of Ethiopia's national goal of rates of DAP that adopters used on wheat were 108 attaining food self-sufficiency, considerable efforts kg/ha in Etheya, 99 kg/ha in Lole, 93 kg/ha in have been made to encourage smallholders to adopt Bekoji, 79 kg/ha in Asasa, and 70 kg/ha in Robe. chemical fertilizers. Since the advent of Application of urea is less common in Arsi, and comprehensive package projects in the 1960s, Arsi it is only used on the major cereal crops - wheat, Zone has benefited from agricultural technology barley, tef, and maize. The highest rate of adoption development and dissemination. of urea for wheat production was observed in Etheya The survey revealed that 88% of the sampled (58%), followed by Asasa (22%) and Robe (22%) farmers in Arsi applied DAP on wheat and 54% on woredas. barley (Table 5.10). The rates of adoption of DAP on Few farmers apply fertilizer to pulses. Only tef and maize are much lower than on wheat and about 3% of the farmers applied DAP on beans, at average rate of 61 kg/ha, and only 6% of the farmers Table 5.9. Frequency of ploughing with a maresha. applied DAP on faba beans, at an average rate of 75 Crop Asasa Bekoji Etheya Lole Robe Mean kg/ha. Wheat 3.5 3.8 4.2 3:9 5.5 4.2 (277) Methods of applying DAP and urea differ. Barley 3.2 3.8 3,9 3.1 4.8 3.6 (206) Almost all respondents in the region correctly used Tef 3.8 4.7 4.4 - 5.2 4.8 (101) Maize - 4.0 3.6 3.0 4.1 3.8 (79) DAP as a basal application at planting (Table 5.11). Linseed 1.7 1.5 - 2.0 3.1 2.1 (35) Sixty-eight percent of the farmers applied urea at Oilseed 3.0 _ 4.0 - 3.3 3.3 (15) planting while 32% applied it as topdressing. Field pea 4.0 - - 3.0 2.0 2.7 (4) Faba bean 3.7 4.2 3.0 3.0 4.4 4.0 (36) Experimental results on Vertisols in central Ethiopia Sorghum -- 2.9 - 4.2 3.3 (17) have shown that split application of the urea N Bean - 4.0 3.3 - 4.0 3.4 (35) source, with one-third applied at planting and two- Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999. thirds top-dressed at the mid-tillering stage of the crop, is agronomicaily beneficial (TUahun etal. 1996). Table 5.10. Fertilizer rates adopted on major crops (kg/ha). Split application of N enhanced grain yield, grain N Crop Asasa Bekoji Etheya lole Robe Mean content and uptake, and apparent N recovery and DAP Wheat 79.2 93.1 107.7 98.7 70.0 90.3 (264) Table 5.11. Method of applying DAP and urea, Arsi Zone Barley 49.0 103.0 71.0 84.9 100.0 76.4 (161) (% of respondents). Tef 21.3 73.3 72.4 - 45.0 55.0 (78) Basal at planting Topdressing Maize - 100.0 60.0 100.0 55.0 63.0 (22) Woreda DAP Urea DAP Urea Bean -- 56.3 - 100.0 61.0 (9) Potato 18.3 150.0 70.8 -- 70.9 (10) Asasa 100 100 __ Faba bean 7.0 97.9 31.8 - 100.0 74.5 (19) Bekoji 100 7.7 - 92.4 Urea Etheya 100 92.6 - 7.4 Wheat 62.5 75.0 70.8 79.5 49.7 67.2 (75) Lole 98.0 95.8 2.0 4.2 Barley 50.0 103.8 44.7 85.0 - 62.6 08) Robe 100 - 100 ! Tef - 62.5 48.0 - 26.0 43.5 (18) Mean 99.5 68.1 0.5 31.9 Maize - 48.3 - 10.0 42.9 (7) Number of respondents (DAP/Urea): Asasa, 46/28; Bekoji, 48/13; Etheya, : Note: Figures in parentheses are numbers of respondents. 38/27; Lole, 51/24; Robe. 34/21; Mean, 217/113. j Source:.Survey data, 1999. Source: Survey data, 1999. j 18 agronomic efficiency. As a result, some farmers have Weeding of most crops begins in July, but for been advised to split application of urea in recent crops such as maize and sorghum, which are planted years. The survey results indicate that wheat farmers in the short rains, weeding begins in May and June are responding to this message. (Table 5.13). About 39% of the Arsi farmers carried out the first hand weeding for wheat in July and 51% began in August. About 10% oft farmers who carried 5.6 Weed Control out a second weeding of wheat did it in July and Previous research has demonstrated that weeds are 57% did it in August. Most farmers (67%) began the a major crop production constraint in Arsi. An earlier first weeding of barley in August. Weeding of tef is survey in wheat fields in Arsi found a weed mainly done in August and September: 59% of the population of 743 weeds/m2 in comparison with a farmers did the first weeding of tef in August and stand of 149 crop plants/m2 (Tanner and Giref 1991). 27% did it in September. Among those doing a Hailu, Mwangi, and Workneh (1991) estimated that second weeding, 61% carried it out in September. weed competition reduces grain yield in wheat and Early hand weeding, i.e., during the first 15 to barley by 36% in Ethiopia. Agronomic trials found 30 days after emergence of the crop, significantly that hand weeding increased wheat yield by 17% to increases the yield of wheat under conditions of 94% as compared with the unweeded treatments moderate to high weed infestation (Tanner and Giref (Tanner, Amanuel, and Kassahun 1991). 1991). Farmers in the current survey appear to weed In Arsi, weed control is mostly done by hand. later than the recommended time. About 60% of the About 84% of the wheat growers hand-weeded their farmers in Arsi began the first hand weeding of wheat fields at least once, while 22% weeded twice wheat in August or later (Table 5.13), suggesting that (Table 5.12). Hand weeding twice was most common a labor bottleneck exists during the peak weeding in Asasa (85% of wheat farmers) and Etheya (93%). period and that farmers are suffering a yield loss This may indicate a severe weed problem in these due to suboptimal weeding. The small share of woredas that would cause a significant yield loss if farmers who did a second hand weeding indicates farmers omitted the second hand weeding. There a shortage of labor for weeding. was also marked variation in hand weeding frequency among various crops. In the major crops, farmers reported the highest frequency of two hand 5.7 Herbicide Application weedings in maize (i.e., 69% of maize fields were Among the sampled farmers, 63% of wheat growers, hand weeded twice), followed by tef (30%), wheat 29% of barley growers, and 33% of tef growers (22%), faba bean (11%), and barley (8%). reported adopting herbicides for weed control. The rates of herbicide application varied among these Table 5.12. Average hand weeding frequency in major crops. crops. Wheat receives the highest rate, 0.74 1/ha, Crop Asasa Bekoji Etheya Lole Robe Mean followed by barley, 0.721/ha, and tef, 0.511/ha (Table Wheat 1.6 1.2 1.7 1.2 1.0 1.4 (240) 5.14). Farmers did not use chemical weed control in Barley 1.2 1.2 1.0 1.0 1.0 1.0 053) other crops, reflecting the importance of wheat, Tef 2.0 1.0 1.6 - 1.3 1.5 (90) barley, and tef as both food and cash sources for the Maize - 1.0 2.6 2.0 2.0 2.3 (78) Linseed 1,0 1,0 - - 1.5 1.0 (7) farm household. Oilseed -- 1.0 - 1.0 1.0 (3) Because 2,4-D is the only herbicide applied by Faba bean 1.6 1.0 1.6 - 1.3 1.3 (34) Sorghum - - 1.9 - 1.6 1.8 (14) farmers in the surveyed areas, continuous use has Bean -- 1.2 - 1.0 1.2 (31) caused a dramatic shift of the weed population to Potato 2.8 1.0 2.0 -- 2.1 (11) species that are tolerant to 2,4-D (Tanner and Giref Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999. 19 Table 5.13. Time of firs! and second hand weedings in wheat, barley, tefr and maize, Arsi Zone (% of respondents).3 May June Ju ly August September October Woreda 1st 2nd 1st 2nd 1st 2nd 1st 2nd 1st 2nd 1st 2nd Wheat Asasa' 58.0 20.8 36.0 66.7 2.0 8.3 Bekoji ---- 44.7 - 50.0 50.0 2.6 25.0 - - ■ Etheya ---- 10.9 - 89.1 51,6 - 48.4 -- Lole - ■ - - 69.8 25.0 28.3 75.0 -- Robe ---- 13.0 52.2 28.6 23.9 42.9 10.9 14.3 Mean ---- 38.9 9.5 50.8 56.8 5.3 28.4 2.0 1.4 Barley Asasa 55.0 18.2 45,0 81.8 Bekoji ---- 40.0 52.0 50.0 8.0 50.0 - _ Etheya ---- 6.5 - 935 - 100 - Lole - - ■ - - ; 11,9 - 88.1 - 100 -- Robe ---- 40.0 - ■ 40.0 - 20.0 - Mean -- - 26.7 9.5 67.1 52.4 2.7 38.1 0.7 - Tef Asasa 60,0 33.3 40.0 44.4 22.2 Bekoji ------66.7 - 33.3 100 - Etheya --- 6.9 - 65.5 18.8 27.6 81.3 -- Robe --- 2.0 - 58.8 28.6 31.4 57.1 7.8 - Mean - -- 9.7 9.1 59.1 27.3 26.9 60.6 4.3 - Maize Bekoji .100 _ . __ _ _„__ _ . Etheya 28.6 - 62.9 13.3 5.7 56.7 2.9 23.3 - ' - - 3.3 Lole 100 - - 100 . - - ■■ - -- - - Robe 88.6 8.3 8.6 66.7 ' - 8.3 2.9 11.1 - 2.8 -- Mean 59.7 4.5 34.7 43.3 2.8 29.9 2.8 16.4 1.5 - 1,5 a/ Number of respondents (1st planting/2nd planting). Wheat: Asasa, 50/24; Bekoji, 38/4; Etheya, 55/31; Lole, 53/8; Robe, 46/7; Mean, 242/74. Barley: Asasa, 40/11; Bekoji, 25/4; Etheya, 31/5; Lole, 42/1; Robe, 5/0; Mean, 143/21. Tef: Asasa, 10/9; Bekoji, 3/1; Etheya, 29/16; Robe, 50/7; Mean, 93/33. Maize: Bekoji, 1/0; Etheya, 35/30; Lole, 1/0; Robe, 36/36; Mean, 73/66. Source: Survey data, 1999. 1991). Alternating the use of different herbicides 5.8 Harvesting and Threshing should be recommended to minimize this problem. Traditional methods of harvesting and threshing Herbicide is mainly applied in July and August. depend he:avily on manual labor. In the current About 92% of the herbicide adopters for wheat and survey, farmers reported harvesting wheat and; 95% of those for barley applied herbicide in this barley both manually and with combine harvesters: period (Table 5.15). This peak period for herbicide 38% of the farmers in Arsi rented combine harvesters application is presumably associated with the labor to harvest wheat and 1% rented combines to harvest shortage for critical activities in other crops. The use barley (Table 5.16). All other cereal crops are; of chemical weed control eases the labor constraint harvested entirely by hand and are threshed using; in the farm household. animals. Vegetables, i.e., shallots and potatoes, are. also harvested manually. In the local grain-threshing; system, the harvested material is spread on a: Table 5.14. Herbicide rate by crop, Arsi Zone, 1998 (l/ha). threshing floor and animals then tread upon it. The; use of combine harvesters for wheat harvesting; Crop Asasa Bekoji Etheya Lole Robe Mean underscores the importance of the wheat crop in Arsi; Wheat 0.74 0.62 0.68 0.91 0.55 0.74 (179) as well as at the farm household level. Asasa ranks; Barley 0.49 0.66 0.35 0.97 0.43 0.72 (60) Tef 0.33 0.63 0.57 - 0.48 0.51 (36) first with 81% of the farmers using combine; Note: Figures in parentheses are numbers of respondents. harvesters for wheat, followed by Lole (79%). Bekoji^ Source: Survey data, 1999. 20 reported the lowest usage of harvesting machines, yields farmers reported were unexpectedly low. presumably reflecting the limitation imposed by the Probably yields were depressed by high incidence topography in this woreda. of wheat stem rust (caused by Puccinia graminis) and stripe rust (caused by P. striiformis), coupled with terminal moisture stress during the 1998 cropping 5.9 Crop Yields season. Of all the crops reported by farmers in Arsi, wheat Although barley is grown in all the woredas, it was the highest yielding (15.9 q/ha) (Table 5.17). ranked fourth in terms of yield at 10.5 q/ha. Maize However, considering the high production potential yield (12.9 q/ha) was second to wheat. for wheat in the selected woredas of Arsi Zone, the Crop yields showed marked variation across the five woredas. Lole reported the highest wheat yield Table 5.15. Time of herbicide application, Arsi Zone, 1998 (% (20.3 q/ha), followed by Etheya (18.1 q/ha) and of respondents). Asasa (15.4 q/ha). The lowest yield was reported in August Sept October Woreda June July Robe (12.2 q/ha). Etheya had the highest barley yield Wheat in Arsi Zone, 16.1 q/ha. Overall, farmers in Etheya Asasa {n = 38) 2.6 42.1 52,6 2.6 Bekoji (n = 17) 5.9 17.6 64.7 . 5.9 5.9 reported the highest yields in Arsi Zone for every Etheya (n = 44) - 4.5 95.5 -- crop except wheat. This may be attributed to the 67.9 30.2 ■ - - Lole (n = 53) 1.9 favorable agroecological conditions in this woreda. Robe (n = 22) - 4.5 63.6 22.7 9.1 Mean (n = 174) 1.7 33.3 59.2 4.0 1.7 Barley Table 5.17. Yields of major crops, Arsi Zone, 1998 (q/ha). Asasa (n = 14) . 28.6 64.3 7.1 _ Crop Asasa Bekoji Etheya Lole Robe Mean Bekoji (n = 14) - 14.3 78.6 ■ - 7.1 Etheya (n = 7) - - 100 - - Wheat 15.4 12.7 18.1 20.3 12.2 15.9 (267) - Lole (n = 27) - - 100 ■ - Barley 8.9 9.2 16.1 9.0 9.5 10.5 (193) Robe (n = 3) - ' - 66.7 33.3 - Tef 3.9 5.6 8.7 - 7.2 7.1 (97) Mean (n = 65) - 9.2 86.2 3.1 1.5 Maize - 10 15.4 15.0 10.7 12.9 (71) Tef Linseed 4.9 4.5 - 4.0 3.6 4.3 (29) Asasa (n = 3) 33.3 33.3 33.3 Bekoji (n = 3) - - 100 - - Faba bean 4.0 6.4 12.8 - 5.8 6.8 (28) Etheya (n = 11) - _ 90.9 - 9.1 Sorghum - - 14.9 - 7.2 12.3 (15) - Robe (n = 19) - 5.3 47.4 ‘ 47.4 - • Bean 11.3 1.5 10.6 (29) Mean (n = 36) - 5.6 63.9 27.8 2.8 Field pea 2.5 10.0 - . - 7.9 (7) Notes: n = number of respondents. Total of percentages exceeds 100 if Note: Figures in parentheses are numbers of respondents. respondents gave multiple answers. Source: Survey data, 1999. Source: Survey data, 1999. Table 5.16. Methods of harvesting and handling crops (% of respondents). Crop and harvest method Asasa Bekoji Etheya Lole Robe Mean Wheat Manual sickling/ox threshing 19.0 96.1 85.5 21.1 92.9 61.7 (171) Combine harvester 81.0 3.9 14.5 78.9 7.1 38.3 (106) Barley Manual sickling/ox threshing 97.8 100 100 95.6 100 98.5 (192) Combine harvester 2.2 - - 2.2 - 1.0 (2) Tef Manual sickling/ox threshing 100 100 100 - 100 100 (97) Maize Cut by hand and shelling 100 100 100 - 100 100 (71) Faba bean Manual sickling/ox threshing 100 100 100 - 100 100 (30) Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999 21 Since the yields reported are gross averages, it 10 q/ha. In terms of distribution, Aruso was grown may be worthwhile to examine the performance of in all surveyed woredas. The production of many of individual varieties. The yields of varieties of the two the less common barley varieties was concentrated major crops, wheat and barley, are presented in in Bekoji. This may be attributed to the favorable Tables 5.18 and 5.19. high altitude environment for barley production in The highest reported wheat yield in Arsi was that woreda. for Pavon (19.2 q/ha), followed by Dashen (17.0 q/ ha), Batu (16.8 q/ha), and Kubsa (16.8 q/ha). The 5.10 Fertilizer Rates in reported yield for Wabe, another widely adopted Relation to Crop Rotations variety in the region, was 15.4 q/ha. ET-13 and Israel In general, farmers rotate crops to maintain the had the lowest reported yields, less than 10 q/ha. fertility of their cropland. This suggests that farmers Variations were observed across the woredas. Kubsa may vary the amount of fertilizer they apply to a had the highest yield (20 q/ha) in Lole while the specific field depending on the precursor crop. The lowest yield was reported in Robe (13.3 q/ha). Pavon survey revealed that 56% of the farmers changed the also gave the highest yield (21.7 q/ha) in Lole while rate or type of fertilizer used after different rotation the highest yield of Batu (18.3 q/ha) was reported crops; 44% of the farmers changed neither the rate; in Asasa. Only farmers in Bekoji reported production nor the type of fertilizer, irrespective of the break of K6290-Bulk, Israel, K6295-4A, and Enkoy. Of the crop (Table 5.20). Robe was the only woreda in which 13 wheat varieties reported in Arsi, Bekoji grew 10 more than half of the sampled farmers do not change and Asasa grew 8. Farmers in Etheya and Robe their fertilizer practice as a result of the break crop woredas reported only six wheat varieties each, used. This may be associated with the generally poor while farmers in Lole reported only four varieties, crop yields in this woreda due to declining soil Among barley varieties, farmers reported that fertility and a high incidence of waterlogging. Aruso gave the highest mean yield (11.8 q/ha) in Farmers were asked about the rate of fertilizer Arsi, followed by HB42 (11.6 q/ha) and Holker (10.8 they applied to wheat grown after different crops. q/ha). The other varieties had mean yields below Farmers used higher rates on wheat following cereal Table 5.18. Wheat yield by variety, Arsi Zone, 1998 (q/ha). Table 5.19. Barley yield by variety, Arsi Zone, 1998 (q/ha). Variety Asasa Bekoji Etheya Lole Robe Mean Variety Asasa Bekoji Etheya Lole Robe Mean Kubsa (HAR 1685) 14.4 11.9 18.6 20.0 13.3 16.8 (106) Local _ 16.0 14.5 _ 12.0 13.5 (22) Pavon-76 16.1 - 16.7 21.7 16.6 19.2 (68) Aruso 8.2 10.0 17.7 8.6 4.0 11.8 (53) Batu 22.5 - 18.3 10.0 5.5 16.8 (23) Beka 8.0 7.7 - 13.0 3.5 7.4 (8) Enkoy - 14.0 --- 14.0 (2) Semareta - -- 9.3 - 9.3 (21)J Dashen 18.0 17.1 12.0 - - 17.0 (23) Holker 6.0 10.9 --- 10.8 (22) | Local - 10.0 - - 11.7 11.6 (21) Bre 9.7 7.8 - 12.0 9.2 (11)! Wabe HB42 - 11.6 -- - 11.6 (8); (HAR 710) 12.9 17.0 13.2 20.3 - 15.4 (37) Venka 8.0 2.0 --- 5.0 (2); K6290-Bu!k - 12.9 --- 12.9 (10) Werkiye 9.5 --- 4.0 7.7 (3)> Galama Sheneka 9.6 16.0 --- 10.1 (14) (HAR 604) 20.0 12.1 16.0 -- 13.1 (12) Atlas - 8.7 - 12.0 - 9.5 (4) Mitike Tikur Gebse - 9.8 - 8.0 - 9.4 (5): (HAR 1709) 14.0 --- 9.0 10.7 (3) Nechi Gebse - 8.2 - -- 8.2 (8) ET-13 13.0 10.2 -- 8.1 9.6 (23) Abado - 2.5 -- - 2.5 (2) CD r-- K6295-4A - 12.0 - -- 12.0 (1) Asheles - 6.7 - - _ (3) Israel - 8.0 - - - 8.0 (1) Bahirseded - 3.5 --- 3.5 (2)' Note: Figures in parentheses are numbers of respondents. Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999. Source: Survey data, 1999. Table 5.20. Farmers' experience with fertilizer for wheat after break crops (% of respondents). Experience Asasa (n = 54) Bekoji (n - 56) Etheya (n = 59) Lole (n = 56) Robe (n = 58) Mean (n : No change in rate/type of fertilizer 31.5 48,2 45.8 33.9 58.6 43.8 Change in rate/type fertilizer 68.5 51.8 54.2 66.1 41.4 56.2 Note: n = number of respondents. Source: Survey data, 1999. precursor crops, i.e., barley, tef, or wheat. The survey There was variation in the rates of fertilizer found that farmers practicing differential fertilizer reported across the five woredas. For wheat following application reported applying DAP at 85 kg/ha on a barley break crop, the highest fertilizer rate, nearly wheat grown after wheat, at 73 kg/ha on wheat 89 kg/ha of DAP, was reported in Lole, whereas the following barley, and at 60 kg/ha on wheat following lowest rate, 62 kg/ha of DAP, was reported in Asasa tef (Table 5.21). The rates of DAP applied on wheat and Robe. For wheat following wheat or tef precursor following sorghum, maize, and linseed precursor crop, a rate of about 100 kg/ha of DAP was reported crops were 73, 72, and 101 kg/ha, respectively By in Bekoji, Etheya, and Lole woredas. contrast, only 62 kg/ha of DAP was used on wheat planted after legume break crops. For urea, the 5.11 Trends Related to Fertilizer Adoption lowest rate, 30 kg/ha, was also reported on wheat grown after legumes. Therefore, it is plausible to Arsi Zone began using fertilizer before any other area conclude that farmers are aware of the beneficial of Ethiopia. The introduction of fertilizer in Arsi was effect of leguminous crops in enhancing soil nitrogen enhanced when the CADU/ARDU comprehensive levels, as well as the high soil nutrient consumption package project was implemented during the 1960s. of cereal crops. Farmers' long experience with fertilizer»has important implications for planning soil research in the region. A strong fertilizer adoption trend was Table 5.21. Fertilizer rates used on wheat after a break crop identified in the current survey. Only 3% of the (kg/ha). respondents reported starting fertilizer use during Break crop Asasa Bekoji Etheya Lole Robe Mean the 1950s (Table 5.22). A decade later, however, half DAP the farmers were using fertilizer, undoubtedly Legume 50.3 74.0 70.0 80.0 46.5 62.5 (185) Barley 61.5 87.0 64.3 88.6 61.8 73.4 (188) reflecting the impact of the CADU/ARDU project. Noug - 100.0 100.0 - 51.5 59.6 (12) The high proportion of farmers, 30%, adopting Wheat 78.2 101.5 101.4 99.3 65.7 85.3 163) fertilizer during 1966-70 corroborates this Tef 54.3 100.0 69.2 ■ - 56.6 59.9 (82) Sorghum - - 69.7 - 100.0 72.7 (10) relationship. About 21% of the farmers in the region Maize - - - 76.8 100.0 (24) 58.8 71.8 first adopted fertilizer in the 1971-80 period. Linseed 110.3 90.4 - 75.0 85.0 100.7 (36) Rapeseed 25.0 95.0 - - - 83.3 (6) Potato 20.0 95.0 52.5 - - 55.0 (8) Urea Table 5.22. History of fertilizer adoption, Arsi Zone. Legume 27.2 N 20.3 37.3 26.0 29.8 (56) Year of adoption Frequency Cumulative percent Barley 37.5 - 37.8 41.0 37.5 39.3 (53) Noug - - 50.0 - 25.0 30.0 (5) 1951-55 1 0.4 Wheat 45.0 75 66.3 50.0 40.4 51.7 (64) 1956-60 7 2.9 Tef 25.0 100 43.9 - 109.6 75.1 (28) 1961-65 47 19.9 Sorghum ------1966-70 84 50.2 Maize - - 44.0 - 25.0 42.3 (11) 1971-75 26 59.6 Linseed 37.5 65 --- 46.7 (6) 1976-80 33 71.5 Rapeseed 10.0 100 -- - 55.0 (2) 1981-85 42 86.6 Potato ------1986-90 34 98.9 — TO796T™T j 3 100 Note: Figures in parentheses are numbers of res| Ethiopia V i'c-h * ------Source: Survey data, 1999. Source: Survey da|a, 1999. 23 Farmers often attach a high value to cropland The duration of the fertilizer rate reduction that has been in leguminous crops. This is, of course, following legumes varied markedly. The majority closely related to the perceived fertility of the soil. of the farmers, nearly 67%, reduced the rate of About 62% of the farmers reported that they used a fertilizer applied for a single cropping season, while lower rate of fertilizer on fields that had previously 24% applied less fertilizer for two consecutive years grown legumes (Table 5.23). The only woredas where (Table 5,25). About 6% of the farmers maintained the the majority of the farmers did not reduce the rate reduction in fertilizer application rates for 3 years; of fertilizer applied on wheat following leguminous less than 4% of farmers reduced fertilizer rates for 4 break crops were Bekoji and Robe, probably because to 8 years following legumes. of low soil fertility. Nearly all surveyed farmers reported producing By far the most common reason given for using wheat or barley, or both, in consecutive cropping less fertilizer after leguminous break crops was seasons on the same piece of land (Table 5.26). In adequate soil fertility (94%) (Table 5.24). A Bekoji, Lole, and Robe, farmers grow wheat or barley, nonsignificant yield response to fertilizer prompted or both, continuously for almost 3 years. This may some farmers (6%) to reduce the rate of fertilizer reflect land shortage in these woredas and the applied on wheat following legumes. There were importance of these crops to the farm household as also some reported socio-economic factors: about 3% food and cash crops. of the farmers applied less fertilizer because they Although farmers frequently apply fertilizer for could not afford the input price, while 2% did so wheat production, sometimes they omit fertilizer: because fertilizer was not available. in Arsi 31% of the farmers had at least one experience Table 5.23. Fanners' experience with fertilizer rates after Table 5.25. Duration of reduced fertilizer rates after legume legume break crops (% of respondents). break crops (% of respondents). Asasa Bekoji Etheya Lole Robe Mean Asasa Bekoji Etheya Lole Robe Mean Experience (n = 59) (n = 57) (n = 59) (n = 60) (n = 59) (n = 294) Year (n = 51) (n = 23) (n = 39) (n = 44) (n = 33) (n = 190) No reduction 1 64.7 100 74.4 - - 66.9 in rate 28.8 54.4 28.8 21.7 55.9 37,8 2 21.6 - 25.6 11.4 12.1 23.6 Reduction 3 9.8 - - 2.3 3.0 5.5 in rate 71.2 45.6 71.2 78.3 44.1 62.2 4 2.0 _ - - 3.0 1.6 5 2.0 -- - 0.8 Notes: n = number of respondents. Source: Survey data, 1999. 6 - -- 3.0 0.8 / 8 --- - 3.0 0.8 Table 5.24. Reasons for reducing fertilizer rates after legume break crops (% of respondents). Notes: n = number of respondents. Total of percentages exceeds 100 if respondents gave multiple answers. Asasa Bekoji Etheya Lole Robe Mean Source: Survey data, 1999. Reason (n = 43) (n = 29) (n = 42) (n = 46) (n = 25) (n = 185) Table 5.26. Average duration of continuous production of Adequate wheat or barley on the same piece of land, Arsi Zone (years). | soil fertility 95.3 82.8 95.2 97.8 96.0 94.1 No significant yield Woreda Duration difference 27.6 4.8 2.2 - - 5.9 Asasa (n = 59) 2.1 Cannotafford - 6.9 - 2.4 2.2 4.0 2.7 Bekoji (n = 49) 2.5 Fertilizer not Etheya (n = 59) 2.2 available 7.0 --- - 1.6 Lole (n = 54) 2.5 Notes: n = number of respondents. Total of percentages exceeds 100 if Robe (n = 55) 2.5 respondents gave multiple answers. Mean (n = 276) 2.3 ' Source: Survey data, 1999. Note: n = number of respondents. Source: Survey data, 1999. ■ in the past four decades in producing wheat without Some farmers (19%) planted wheat without fertilizer (Table 5.27). Among the woredas, the fertilizer mainly because they considered the fertility highest incidence of experience with wheat of their land high enough to obtain a good yield production without fertilizer was found in Robe without fertilizer. Adequate soil fertility may have (58%), while the lowest (18%) was reported in Lole. been attained through crop rotation or fallowing. Farmers reported various socio-economic and Specifically, 11% of the farmers reported crop technical reasons for growing wheat without rotation with legumes as the main reason for fertilizer. About 42% of the farmers in the group who growing wheat without applying fertilizer, and 10% had grown wheat without fertilizer reported that the said fallowing was the main reason. A few farmers input was unaffordable (Table 5.28). Also, lack of (7%) also reported preferring organic manure to credit for input purchase caused many farmers (37%) commercial fertilizers. to plant wheat without fertilizer. This, in turn, reflects Since most farmers in Arsi have many years of the weak cash position of the peasant farmers. Other experience with fertilizer, they recognize its potential important reasons were non-availability of fertilizer, to enhance crop productivity. The farmers expressed reported by 29% of the respondents, and late awareness that they could not supply their family's delivery, reported by 18%. food needs without commercial fertilizer. As a result, almost all farmers (96%) in the region reported that Table 5.27. Farmers' experience with wheat production they planned to continue using chemical fertilizer without fertilizer (% of respondents). on wheat in the future. However, a few farmers in Woreda With fertilizer Without fertilizer Bekoji (14%), Etheya (2%), and Robe (5%) indicated that they might not use fertilizer in the future. This, Asasa (n = 60) 71.7 28.3 Bekoji (n = 57) 61.4 38.6 however, does not mean that these farmers intend Etheya (n = 60) 81.7 18.3 to stop using fertilizer, rather, they will continue to Lole (n = 60) 86.7 13.3 use fertilizer unless some constraint prevents them Robe (n = 59) 42.4 57.6 Mean {n = 296) 68.9 31.1 from doing so. Note: n = number of respondents. ~ Farmers have differing perceptions about Source: Survey data, 1999. varying the rates of fertilizer applied on different fields (Table 5.29). A minority of farmers (28%) use a Table 5.28. Reasons for producing wheat without fertilizer (% of respondents). uniform rate on all wheat fields irrespective of soil type, while the rest (72%) adjust the rate to fit the Asasa Bekoji Etheya Lole Robe Mean Reason (n = 17) (n = 22) (n = 10) (n = 10) (n = 32) (n = 91) soil type. Among reasons farmers gave for varying the rates of fertilizer applied on wheat fields: 66% Can’t afford 17.7 27.3 60.0 71.9 41.8 Not available 58.8 36.4 10.0 - 21.9 28.6 mentioned soil type (Table 5.30). Specific break crops Late delivery 5.9 27.3 30.0 20.0 12.5 17.6 Adequate soil fertility 5.9 18.2 50.0 10.0 18.8 18.7 Table 5.29. Farmers' perceptions of the rate of fertilizer used Prefer organic on all wheat fields (% of respondents). manure - 9.1 - 10.0 9.4 6.6 Woreda Different Uniform Weather not good -- 10.0 - 9.4 4.4 Asasa (n = 59) 64.4 35.6 Lack of credit 64.7 63.6 - 20,0 21,9 37.4 Bekoji (n = 58) 72.4 ' 27.6 Crop rotation/ Etheya (n = 60) 68.3 31.7 legumes - 9.1 20.0 40.0 6.3 11.0 Lole (n = 58) 79.3 20.7 Fallow 11.8 18.2 - 30.0 - 9.9 Robe (n = 59) 74.6 25.4 Mean (n = 294) 71.8 28.2 . Notes: n = number of respondents. Total of percentages exceeds 100 if respondents gave multiple answers. Notes: n = number of respondents. Source: Survey data, 1999. Source: Survey data, 1999. 25 also affected the rate of fertilizer used. Farmers often Recurrent fertilizer application on a given field applied less fertilizer on fields that had leguminous has important implications for soil analysis and the precursor crops. About 6% of the farmers reported development of appropriate fertilizer fallowing as a reason for the variation of fertilizer recommendations. About 69% of the farmers in Arsi rates. The cost of fertilizer prompted some farmers applied fertilizer on all their fields every year, while (7%) to minimize the rate of fertilizer application in 31% did not. Only in Lole did all farmers apply order to cover all cropped fields. A few farmers (3%) fertilizer on all their fields every year. By contrast, indicated that the non-availability of the input many farmers in Robe (75%), Bekoji (42%), Asasa determines the rate of fertilizer used on wheat. The (25%), and Etheya (13%) did not apply fertilizer on soil fertility of a given field also determined the rate all fields every year. of fertilizer used by some farmers (4%). The survey results revealed that some farmers The surveyed farmers clearly perceived that applied fertilizer in alternate years. Twenty-nine crops respond differentially to fertilizer depending percent of the responding farmers in this category on the rate, type of fertilizer, and timing of applied fertilizer in alternate years because they application. About 90% of the fanners reported that could not afford the input price (Table 5.32). The use they observed yield differences due to changes in of crop rotation (18%) and the crop type (18%) were the rate of fertilizer applied. Only 10% did not reasons for alternate-year application. Moreover, perceive any yield difference (Table 5.31). some fanners (12%) reported that the soil type of a given field affected their decisions to apply fertilizer in alternate years. A few farmers (1.7%) applied Table 5.30. Factors affecting the rate of fertilizer applied on wheat fields (% of respondents). fertilizer in alternate years due to limitations in the Asasa Bekoji Etheya Lole Robe Mean amount of fertilizer available to cover their Factor (n = 57) (n = 42) (n = 43) (n = 47) (n = 49) (n = 238) important crops. ^ Expected yield 12.3 2.3 25.5 2.0 9,2 Soil type 43.9 81.0 74.4 57.4 79.6 66.0 5.12 Fertilizer Procurement Break crops/ and Preferences rotation 15.8 11.9 11.6 2.1 8.2 10.1 Fallow 12.3 11.9 4.7 . - ■ 5.8 Prompt delivery is an important feature of an Costof efficient fertilizer marketing system. Timeliness of fertilizer 12.3 2.4 4.7 14.2 7.1 delivery has an impact on crop productivity by Lack of fertilizer 12.3 2.0 3.4 Table 5.32. Reasons for fertilizer application in alternate Soil fertility 5.3 - 12.8 - 3.8 years (% of respondents). Notes: n = number of respondents. Total of percentages exceeds 100 if respondents gave multiple'answers. Asasa Bekoji Etheya Lole Robe Mean Source: Survey data, 1999. Reason (n = 30) (n = 32) (n = 8) > = 2) (n = 47) (n = 119) Can't afford/ \ Table 5.31. Fanners' perceptions of yield difference due to expensive 3.3 15.6 12.5 - 57.4 28.6 5 changed fertilizer rates (% of respondents). Crop rotation 43.3 9.4 12.5 . - 8.5 17.6 ; Crop type 23.3 21.9 25.0 100 8.5 18.5 ■; Woreda No Yes Experience 10.0 - 12.5 - -- 3.4 Asasa (n = 58) 3.4 96.6 Late fertilizer Bekoji (n = 57) 12.3 87.7 arrival - 3.1 - 2.1 1.7 i Etheya (n = 60) 8.3 91.7 Soil type : 20.0 12.5 37.5 - 2.1 11.8 . Lole (n = 57) 5.3 94.7 Low yield 31.3 21.3 16.8 Robe (n = 55) 20.0 80.0 Shortage of i Mean (n = 287) 9.8 90.2 fertilizer - 6.3 - 1.7 : Notes: n ». number of respondents. Notes: n = number of respondents. Source: Survey data* 1999. Source: Survey data, 1999. affecting planting time. The survey showed that Farmers were questioned about the trends in the about 63% of the farmers in the region did not obtain timeliness of input delivery since 1991, i.e., since the fertilizer on time (Table 5.33). The incidence of late Ethiopia's fertilizer market was liberalized. A slight delivery of fertilizer varied across the five woredas. majority of the farmers reported the timeliness of Ninety-eight percent of the farmers in Asasa and input supply has improved since 1991 (Table 5.35). Bekoji reported that they could not get fertilizer on However, most farmers in Asasa (94%) and Bekoji time. In contrast, most farmers in Etheya (70%) (74%) reported that no improvement had occurred. obtained fertilizer on time, probably because this In addition to the timeliness of availability of woreda is near input suppliers. the fertilizer supply, assessment of the farmers' Several reasons for the late delivery of fertilizer actual demand for fertilizer will indicate inefficient in Arsi Zone were identified (Table 5.34). About 66% shortfalls or gluts in fertilizer supply. Because many of the farmers attributed late input delivery to late farmers depend on receiving a loan for fertilizer, they loan settlement. Many farmers (33%) reported that often cannot procure as much as they want for a the limited participation of service cooperatives in particular cropping season. In such instances, to meet the provision of fertilizer credit contributed to late their needs, they are forced either to purchase input delivery. A few farmers (4%) claimed that late fertilizer for cash or to allocate a limited supply of fertilizer demand assessment contributed to the fertilizer among the different crops. The survey problem. revealed that 36% of the farmers obtain less fertilizer than they heed while about 64% of the farmers obtain enough (Table 5.36). Variation was observed among Table 5.33. Timeliness of fertilizer delivery (% of respondents). the woredas. Most farmers in Asasa (86%) and Bekoji Fertilizer received on time Woreda No Yes Table 5.35. Recent timeliness of fertilizer delivery compared Asasa (n = 60) 98.3 1.7 with 1991 (% of respondents). Bekoji (n = 59) 98.3 1.7 Etheya (n = 59) 30.5 69.5 Woreda Not improved improved Lole (n = 58) 39.7 60.3 Asasa (n = 55) 94.5 5.5 Robe (n = 58) 46.6 53.4 Bekoji (n = 57) 73.7 26.3 Mean (n = 294) 62.9 37.1 Etheya {n = 56) 21.4 78.6 Notes: n = number of respondents. Lole (n = 58) 29.3 70.7 Source: Survey data, 1999. Robe (n = 58) 19.0 81.0 Mean (n = 284) 47.2 52.8 Table 5.34. Reasons for late delivery of fertilizer (% of Notes: n = number of respondents. Source: Survey data, 1999. respondents). Asasa Bekoji Etheya Lole Robe Mean Table 5.36. Farmers' perceptions of demand for and actual Reason (n = 58) (n = 51) (n = 11) (n = 4) (n = 7) (n = 131) procurement of fertilizer {% of respondents). Farmers do not Farmers who obtain settle loans less than more than the amount on time 31.0 92.2 100 100 100 66.4 Woreda required required required Late demand assessment 6.9 2.0 3.8 Asasa (n = 59) 86.2 _ 15.5 Late auction Bekoji {n = 56) 53.6 1.8 44.6 for fertilizer 6.9 _ - — 3.1 Etheya (n = 59) 29.3 - 72.4 No credit from Lole (n = 59) -- 100 service Robe (n = 57) 12.3 1.8 86.0 cooperatives 69.0 5.9 - - _ 32.8 Mean (n = 290) 36.1 0.7 63.9 Notes: n = number of respondents. Total of percentages exceeds 100 if Notes: n = number of respondents. Total of percentages exceeds 100 if respondents gave multiple answers, respondents gave multiple answers. Source: Survey data, 1999. Source: Survey data, 1999. (54%) reported fertilizer purchases below their 36% of the farmers. Annual fertilizer purchases were demand level, whereas all farmers in Lole were able also affected by the cash position of the farmers. to procure enough fertilizer. The survey results revealed that almost all An important reason many farmers (31%) gave farmers (99%) in Arsi Zone are aware of the specific for buying less fertilizer than they needed for a benefits of the fertilizer they use. For DAP, high yield particular season was the increasing cost of fertilizer was cited by 87% of the farmers as a benefit; 51% of (Table 5.37). Since most input suppliers lack reliable the farmers thought high yield was a benefit of urea data on the actual demand for fertilizer, shortfalls in (Table 5.40). About 30% of the farmers perceive that supply were frequently observed in the market. Thirty percent of the surveyed farmers indicated that Table 5.38. Average fertilizer requirement per fanner the fertilizer supply in the market was insufficient in 1998 (kg). to meet the actual demand. The limited capacity of Woreda DAP Urea the service cooperatives to handle fertilizer Asasa 205.9 70.0 marketing also contributed to the undersupply of Bekoji 196.6 73.0 fertilizer. Moreover, the lack of credit and the need Etheya 149.4 67.6 Lole 202.0 for a downpayment kept some farmers (9%) from 51.1 Robe 98.6 55.0 procuring their actual input requirement. Mean 171.9 65.3 In 1998, the average farmer required 172 kg of Source: Survey data, 1999. DAP and 65 kg of urea (Table 5.38), while mean Table 5.39. Motivation for annual fertilizer purchase (% of actual purchases were 152 kg of DAP and 60 kg of respondents). urea (Table 4.1). Thus, farmers obtained 88% of their Basis Asasa Bekoji Etheya Lole Robe Mean DAP needs and 92% of their urea needs. The highest (n = 59) (n = 55) (n = 59) (n = 59) (n = 59) (n = 291) per capita demand for DAP fertilizer was reported Past in Asasa (206 kg), Lole (202 kg), and Bekoji (197 kg). experience 69.5 78.2 64.4 69.5 22.0 60.5 Farmers' annual fertilizer requirements are Current fertilizer price 27.1 30.9 16.9 8.5 16.5 based on multiple factors. Most farmers (60%) Advice from decided their annual fertilizer purchases from their extension services 57.6 43.6 30.5 71.2 84.7 57.7 experience in the preceding cropping seasons (Table Observation of 5.39). The extension service also influenced demand neighbors 40.7 40.0 37.3 5.1 30.5 30.6 by disseminating improved varieties along with Fertilizer supply condition - - 1.7 - 0.3 information on recommended practices: 58% of the Cash position 1.7 3.6 3.4 1.7 - 2.1 farmers based the types and quantities of their Availability of annual fertilizer purchases on extension service credit 50.8 49.1 61.0 13.6 5.1 35.7 advice. The availability of credit to purchase fertilizer Notes: n = number of respondents. Total of percentages exceeds 100 if respondents gave multiple answers. had a significant effect on the purchase decision of Source: Survey data, 1999. Table 5.37. Reasons for low demand and procurement of fertilizer, Arsi Zone, 1998 (% of respondents). Asasa (n = 55) Bekoji (n = 27) Etheya (n = 19) Lole (n = 1) Robe (n = 10) Mean (n = 112) Can't afford/cost of fertilizer 16.4 29.6 68.4 100 40.0 31.3 Lack of fertilizer/inadequate supply 29.1 51.8 5.3 100 20.0 30.3 Problem of service cooperatives 50.9 3.7 5.3 - 20.0 28.6 Lack of credit/down payment problem 14.5 - 10.5 - - 8.9 Notes: n = number of respondents. Total of percentages exceeds 100 if respondents gave multiple answers. Source: Survey data, 1999. DAP increases soil fertility but only 2% of the fanners Farmers receive information regarding fertilizer believe that urea does. Some farmers indicated that recommendations from sources such as the extension urea has an advantage of promoting good vegetative service (MOA), research institutes, NGOs, and SG growth as compared with DAP. 2000. The farmers' main source (84%) of information Most farmers in Arsi Zone expressed a on fertilizer recommendations is the extension preference for DAP over urea. Sixty-six percent service provided by the Regional Bureau of believe that crops produce higher yields when DAP Agriculture, while 3% of the farmers obtained is applied (Table 5.41). They also indicated a belief recommendations from research institutes in the area that DAP improves soil fertility more than urea does. (Table 5.43). Another important source of ■ Twenty-three percent of the farmers said that they Table 5.41. Reasons for farmers' preference for DAP (% of preferred DAP to urea based on their experience with respondents). applying both fertilizers over several years. Asasa Bekoji Etheya Lole Robe Mean Reason (n = 58) (n = 56) (n = 57) (n = 60) (n = 59) (n = 290) 5.13 Awareness and Adoption of High yield 67.3 69.7 72,0 45.0 74.6 65.5 Increase soil Fertilizer Recommendations fertility 27.6 14,3 24.6 5.0 16.9 17.6 Reflecting the fact that most farmers in Arsi Zone Experience 24.1 17.9 17.5 55,0 1.7 23.4 Observation have many years of experience with fertilizer, 71% from others - 1.8 - 0.3 of the farmers reported being aware of the Sandy soil 5.4 1.8 -- 1.4 Protect against recommended fertilizer rates for wheat (Table 5.42). pests/diseases - - - 1.7 - 0.3 The highest awareness rate, 88%, was reported in Notes: n = number of respondents. Total of percentages exceeds 100 if Lole, while the lowest rate, 59%, was in Robe. In spite respondents gave multiple answers. of the high level of awareness, adoption of the Source: Survey data, 1999. recommended rates was markedly lower (Table Table 5.42. Awareness and adoption of recommended 5.42). Only 20% of farmers who were aware of the fertilizer rates for wheat (%). recommended rates actually adopted those rates for Woreda Awareness8 Adoption6 wheat production. Adoption ranged from 56% in Asasa 64.4 . 7.9 Etheya to 5% in Bekoji. Bekoji 76.8 4.7 Etheya 67.2 56.4 Table 5.40. Farmers' perceptions of the specific benefits of Lole 88.1 19.2 DAP and urea (% of respondents). Robe 59.3 14.3 Mean 71.1 20.3 Benefit Asasa Bekoji Etheya Lole Robe Mean a I Percent of respondents, DAP bI Percent of those aware of recommendations. High yield 90.0 84.7 84.2 91.7 82.8 86.7 Source: Survey data, 1999. Increase soil Table 5.43. Sources of information for fertilizer fertility 40'0 20.3 36.8 15.0 37.9 29.9 recommendations (% of respondents). Resist diseases - - 7.0 -- 1.4 Urea Sources of Asasa Bekoji Etheya Lole Robe Mean 66.7 High yield 25.0 30,0 100 33.3 51.1 information (n = 46) (n = 55) (n = 39) (n = 53) (n = 41) (n = 234) Waterlogging tolerance 31.3 32.5 - 86.1 36.8 Extension Good for (MOA) 76.1 90.9 69.2 96.2 82.9 84.2 leaves/stems 6.3 33.3 35.0 - 13.9 15.9 Research Early crop 43.8 - 17.5 - 2.8 11.3 institutes 2.2 3.6 7.7 3.8 - 3.4 Increase soil Other farmers 37.0 34.5 71.8 5.7 43.9 36.3 fertility -- 7.5 -- 2.3 No information 2.2 --- 2.4 0.9 SG2000 - -- 1.9 - 0.4 a/ Number of respondents (DAP/urea): Asasa, 60/16; Bekoji, 59/3; Etheya, 57/40; Lole, 60/38; Robe, 58/36; Mean, 294/133. Notes: n = number of respondents. Source: Survey data, 1999. Source: Survey data, 1999. 29 information is the sharing of experience among the of the respondents (83%) reported that the fanners themselves: 36% received information on incremental yield from fertilizer use was sufficient fertilizer recommendations from early adopters. to repay their loans (Table 5.45). Farmers not adopting the recommended Among the constraints farmers identified as fertilizer rates gave several reasons. Most of the non hindering their capacity to procure the required adopters (80%) reported high fertilizer prices amount of fertilizer for their crops, the rising price prevented them from adopting the recommended of fertilizer was cited by 91% of respondents (Table rates (Table 5.44). In addition, the lack of credit forced 5.46). Both the devaluation of the local currency and some to use less than the recommended rate on the abolition of fertilizer subsidies have raised wheat in order to allocate fertilizer among their fertilizer prices. In addition, some farmers (40%) various crops. Some non-adopters (14%) did not claimed that the price of their produce is too low follow the recommended rates because they relative to the input price. In addition, since considered their fields to be highly fertile and felt fertilizers are often procured on credit, farmers might that they could obtain an acceptable yield with a not be able to secure a loan because of the limited application of fertilizer. Only a few non downpayment required or because they were late adopters (3%) used manure to supplement their low in settling the previous loan. About 45% of the levels of fertilizer application. A significant farmers also indicated that late delivery of fertilizer proportion of the non-adopters (28%) reported that is one of the major problems constraining the use of they lacked knowledge of the recommended rates. commercial fertilizer. Instead they devised their own fertilizer rates through experience. Table 5.45. Farmers' perceptions of incremental yield due to Farmers will adopt a new agricultural fertilizer relative to fertilizer loan (% of respondents). technology or practice only if they believe that it is Woreda Not sufficient Sufficient to repay loan profitable. The high demand for fertilizer credit in Asasa (n = 60) 31.7 68.3 Arsi suggests that farmers are able to settle their Bekoji (n = 47) 4.3 95.7 loans using the yield increment realized from the Etheya (n = 57) 19.3 80.7 application of fertilizer. The overwhelming majority Lole (n = 59) - 100 Robe (n = 58) 27.6 72.4 Mean (n = 281) 17.1 82.9 Table 5.44. Reasons for not adopting recommended fertilizer Notes: n = number of respondents. Source: Survey data, 1999. rates (% of non-adopters). Asasa Bekoji Etheya Lole Robe Mean Table 5.46. Constraints to fertilizer utilization (% of Reason (n = 45) (n = 39) (n = 42) (n = 53) (n = 51) (n = 232) respondents). Lack of Asasa Bekoji Etheya Lole Robe Mean knowledge 34.0 28.2 28.6 1.9 47.1 27.6 Constraint (n = 59) (n = 57) (n = 59) n = 59) (n = 57) (n = 291) High fertilizer price 87.3 66.7 78.6 71.7 92.2 79.7 Unavailability 47.5 29.8 8.5 - 19.3 2 i.o ; Manure High input price 98.3 96.5 94.9 69.5 94.7 90.7 ! supplement 2.1 - 7.1 - 3.9 2.6 Late delivery 55.9 63.2 10.2 50.8 43.9 44.7 Fertile soil 12.8 10.3 23.8 17.0 7.8 14.2 Lack of credit 83.1 59.6 6.8 42.4 45.6 47.4 = Poor soil 6.4 2.6 -- 2.0 2.2 Low price for Lack of credit 19.1 - 7.1 - - 5.2 produce 59.3 28.1 32.2 49.2 31.6 40.2 Own experience - - - 11.3 - 2.6 Inadequate supply 6.8 -- 1.7 - 1.7; Notes: n = number of respondents. Total of percentages exceeds 100 if respondents gave multiple answers. Notes: n = number of respondents. Source: Survey data, 1999. Source: Survey data, 1999. 30 Farmers' Perceptions of Soil Fertility Management Practices 6.1 Crop Yields on Best reported wheat yield on poor fields without fertilizer and Poorest Fields was 4.8 q/ha, or 61% less than the yield on poor In research, the fertility of a particular soil can be fields with fertilizer. assessed by detailed laboratory analysis. However, For barley with fertilizer the average yields farmers use their own methods to determine the reported were 17.3 q/ha for the best fields and 9.7 quality of soil in a field. The survey revealed that q/ha for the poorest fields. The average barley yield for 95% of the sampled farmers in Arsi previous crop with fertilizer for the best fields ranged from 22.3 yields are an important indicator of soil fertility. This q/ha in Bekoji to 10.6 q/ha in Lole. A marked yield is quite plausible since crop yields are closely difference was reported for the best fields with and associated with the level of soil nutrients available without fertilizer. The average yield without to them. Only a few farmers (2%) reported that they fertilizer was 8.3 q/ha, a 52% reduction in yield. This identified poor or fertile soils based on physical again emphasizes the contribution of mineral observation of the field. fertilizers to the productivity of crops in Arsi Zone. Given that crop yield is a common indicator of Without fertilizer, farmers estimated the average soil quality for farmers, the reported yields of the yield of barley on the poorest fields at 4.4 q/ha on major crops with and without fertilizer on the the poorest fields, 47% yield less than the yield of farmers' best and poorest fields could provide some the best fields. indication of the soil fertility status in the five Crop yields are affected by several other soil- sampled woredas. With the application of fertilizer, related factors. Waterlogging was reported by 51% farmers reported that 23.6 q/ha of wheat could be of the sampled farmers in Arsi Zone (Table 6.2), but obtained on their best fields while the yield reported the severity of waterlogging varied across the five on the poorest fields was 12.4 q/ha, a 47% difference woredas. It was most frequently reported in Robe (Table 6.1). Across the five woredas, the highest yield (90%) and Bekoji (64%), which is attributable to thei of wheat with fertilizer on the best field was reported characteristic heavy clay soils in these woredas. Soil! in Etheya (27.6 q/ha) while the lowest yield (20.0 erosion was the second-ranked (44%) yield-limiting; q/ha) was in Robe. The low wheat yield reported in factor in Arsi. the majority of the farmers in Etheya Robe could reflect the relatively low soil fertility and (66%) and Asasa (56%) reported soil erosion as a; high incidence of waterlogging in this woreda. major problem limiting crop productivity. = On the best fields without fertilizer, the farmers Another important yield-limiting factor was: reported a mean wheat yield of 10 q/ha, or 58% less moisture deficit, reported by 34% of the farmers.; than the yield with fertilizer. This clearly indicates Moisture deficit was mentioned by 77% of the; the contribution of fertilizers to increasing peasant farmers in Lole and by 37% in Asasa. This constraint yield lev.els. Without fertilizer, the highest yield for is usually associated with a low water-holding the best field was reported in Etheya (13.6 q/ha) capacity of the soil. In Asasa, for example, soil whereas the lowest was in Lole (6.9 q/ha). The mean contains a relatively low proportion of clay. The survey also revealed that soil-borne diseases are one of the yield constraints in Arsi: 57% of the farmers Farmers also reported various natural factors in Bekoji and 32% of the farmers in Asasa reported (i.e., insect pests, disease, bad weather, weeds) and this problem. socio-economic factors (i.e., low produce prices, high input prices, lack of credit, land scarcity, late input Table 6.1. Yields of major crops on best and poorest fields delivery) that limit the yield of their crops (Table 6.3). with and without fertilizer (qfta). Most farmers (85%) reported bad weather as the With fertilizer Without fertilizer most important factor limiting yields in Arsi Zone. Crop Best field Poorest field Best field Poorest field In most of Ethiopia, erratic rainfall, particularly Wheat terminal moisture stress, is a major problem affecting Asasa 23,7 11.3 9.8 5.3 crop production. Yields are often affected by insect Bekoji 22.5 10.2 7.2 2.8 Etheya 27.6 16.6 13.6 6.8 pests and diseases, which in the worst cases can Lole 23.7 12.5 6,9 3.0 cause total crop failure. Nearly 60% of the farmers Robe 20.0 10.9 10.2 4.5 in Arsi Zone identified disease and pest problems Mean3 23.6 12.4 10.0 4.8 Barley as contributing to yield reductions. Asasa 15.3 8.1 7.0 3.4 Bekoji 22.3 9,9 4.8 2.0 Etheya 21.1 15.9 13.0 7.0 Table 6.2. Soil-related yield limiting factors Lole 10.6 4.9 4.0 3.5 (% of respondents). Robe 19.5 10.7 11.0 6.0 Asasa Bekoji Etheya Lole Robe Mean Meanb 17.3 9.7 8.3 4.4 Factor (n = 57) (n = 55) (n = 55) (n = 60) (n = 60) (n = 288) Faba bean Asasa 12.0 7.0 9.0 4.4 Waterlogging 47.4 64.3 41.8 10.0 90.0 50.7 Bekoji 12.4 4,5 6.8 4.2 Shallow/ Etheya 14.5 9.8 10.6 5.6 stony soil 52.6 42.9 36.4 21.7 21,7 34.7 Lole 10.5 3.8 9.5 4.3 Soil erosion 56.1 42.9 65.5 16.7 43.3 44.4 Robe 15.9 7.6 9.5 3.4 Moisture deficit 36.8 8.9 21.8 76.7 23.3 34.0 Meanc 14.0 8,0 9.7 4.6 Soil-borne Tef disease 31.6 57.1 14.5 18.3. 25.0 29.2 Asasa 7.3 4.6 4,0 2.3 Note: Figures in parentheses are numbers of respondents. Bekoji 9.9 5.0 3.0 3.0 Source: Survey data, 1999. Etheya 11.8 7.0 5,8 3.6 Robe 10.9 7.3 7.6 4.0 Meand 10.6 6.7 6.2 3.6 Table 6.3. Non-soil-related yield limiting factors Sorghum ( % of respondents). Bekoji _ 9.0 5.0 Etheya 23.5 18.8 12.6 8.0 Asasa Bekoji Etheya Lole Robe Mean Robe 16.0 10,0 13.4 9.0 Factor (n = 60) (n = 58) n = 60) (n = 60) (n = 60) (n = 298) Mean* 23.0 15.0 12.6 8.0 Insect pests 63.3 56.9 31.7 68.3 70.0 58.1 . Maize Disease 53.3 72.4 28.3 66.7 75.0 59.1 . Etheya 28.6 18.0 17.3 8.0 Bad weather 70.0 72.4 86.7 96.7 100 8 5.2; Lole 20.0 8.0 -- Low produce Robe 15.2 7.9 12.2 5.5 prices 50.0 17.2 30.0 71.7 33.3 40.6 j Meanf 22.9 13.7 14.4 6.7 High input prices 81.7 69.0 63.3 78.3 70.0 72.5 j a/ Number of respondents: With fertilizer, best field, 286; poorest field, Lack of credit 60.0 53.4 11.7 58.3 58.3 48.3 281. Without fertilizer, best field, 198; poorest field, 182. b/ Number of Unavailability of respondents: With fertilizer, best field, 212; poorest field, 208. Without chemicals 1.7 - 1.7 - 0.7 ■; fertilizer, best field, 156; poorest field, 144. c/ Number of respondents: Shortage of With fertilizer, best field, 65; poorest field, 63. Without fertilizer, best - ■ field, 71; poorest field, 69. d/ Number of respondents: With fertilizer, farmland - 1.7 -- ' 0.3 ; best field, 105; poorest field, 106. Without fertilizer, best field, 104; Weeds - -- 5.0 - 1.0 poorest field, 95. el Number of respondents: With fertilizer, best field, Late input 17; poorest field, 16. Without fertilizer, best field, 22; poorest field, 19. f/ delivery - 1.7 - -- 0.3 Number of respondents: With fertilizer, best field, 48; poorest field, 40. Without fertilizer, best field, 60; poorest field, 48. Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999. Source: Survey data, 1999. 32 High input prices, particularly fertilizer, caused land is allowed to lie fallow, the farmer returns it to many farmers to apply fertilizer at suboptimal rates, crop production to obtain higher yields. However, which obviously reduces the productivity of crops. many farmers (51%) use fallow land for grazing to Nearly 73% of farmers indicated this constraint as ease their feed shortage problem. Farmers leave land one of the most important yield-limiting factors. fallow for grazing only if they have enough land for Moreover, as discussed earlier, late delivery of crop production to feed their families. Some farmers fertilizer reduces yield by delaying crop planting. (6%) reported that they are forced to leave their land Since the cash position of the subsistence farmers is idle due to natural factors such as the late arrival of very weak, they depend heavily on loans to buy crop the rainy season. A few farmers (1%) reported a belief inputs. The lack of access to credit prevents some that fallowing minimizes pest and disease problems. farmers from procuring as much fertilizer as they The survey revealed that most farmers apply need. moderate to high rates of fertilizer on crops planted on previously fallowed soils (Table 6.6). About 75% 6.2 Fallowing and Use of Fertilizer of the sampled farmers in Arsi applied DAP on wheat planted on fallow lands, at a mean rate of 73 In addition to crop rotation, many farmers use kg/ha, and 20% applied urea, at a rate of 35 kg/ha. fallowing, particularly in woredas where land The relatively high rates of fertilizer application on scarcity is not acute. Overall, 52% of the farmers wheat indicates the high priority given to this crop. sampled in Arsi Region practice land fallowing Among the five woredas, the highest rate of DAP (Table 6.4). Fallowing is widely used in Lole (95%), use on wheat, 86 kg/ha, was reported in Lole, while Bekoji (81%), and Asasa (66%) woredas. In Etheya, the lowest rate, 57 kg/ha, was reported in Robe. however, few farmers (3%) reported fallowing, indicating land scarcity. But, the high level of fertilizer application also suggests that fallowing did not have a major impact Almost all sampled farmers (94%) left their land on soil fertility replenishment. In other words, fallow to replenish soil fertility (Table 6.5). After the farmers could not obtain a satisfactory yield without Table 6.4. Fanners' experience in fallowing iand (% of respondents). Table 6.6. Fertilizer application on major crops after fallowing Land ever Asasa Bekoji Etheya Lole Robe Mean (kg/ha). left fallow (n = 59) (n = 59) (n = 58) (n = 57) (n = 54) (n = 287) Crop Asasa Bekoji Etheya Lole Robe Mean No 33.9 18.6 96.6 5.3 87.0 47.7 DAP Yes 66.1 81.4. 3.4 94.7 13.0 52.3 Barley 42.5 77.7 62.5 53.4 51.3 56.0 (173) Note: Figures in parentheses are numbers of respondents. Faba bean 36.3 62.5 67.5 - 38.6 50,3 (32) Source: Survey data, 1999. Field pea - 100 63.3 - - 72.5 (4) Maize - - 90.0 - 50.0 72.2 (9) Table 6.5. Reasons for leaving land fallow (% of respondents). Tef 27.5 85.7 75.0 - 48.6 51.4 (64) Wheat 66.9 76.2 81.8 86.4 57.3 72.6 (225) Reason Asasa Bekoji Etheya Lole Robe Mean Sorghum - - - - . -- Replenish soil Urea fertility 89.4 95.8 100 98.2 66.7 93.7 (149) Barley . 33.3 39.0 _ 50.0 39.5 (10) Adequate land 12.8 4.2 3.6 - 6.3 (10) Faba bean - 70.0 50.0 - 40.0 57.5 (4) Grazing purpose 61.7 47.9 46.4 33.3 50.6 (80) Field pea ------Late rainy season 4.3 14.6 1.8 - 6.3 (10) Maize - - 62.5 - 50.0 58.3 (6) Rent land 2.1 4.2 - - 1.9 (3) Tef -- 33.3 - 33.3 33.3 (9) Protect against Wheat 40.6 50.0 42.9 30.9 32.2 34.7 (61) pests/diseases 4.3 _ _ - 1.3 (2) Sorghum 25.0 - 35.0 -- 33.6 (7) Note: Figures in parentheses are numbers of respondents. Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999. Source: Survey data, 1999. 33 fertilizer. This is perhaps because the fallow period yields. Only 25% of the farmers reported applying is too brief. The survey revealed that the average farmyard manure (Table 6.9). These farmers applied duration of fallowing was about 1 year (Table 6.7)— a mean rate of only 175 kg of farmyard manure per too short a time to restore soil fertility The longest hectare. The highest application rates were reported duration of fallowing, 5.6 years, was reported by 12% in Bekoji (491 kg/ha), Etheya (291 kg/ha), and Robe of the farmers in Robe woreda. In Robe, most farmers (130 kg/ha), while the lowest rates were in Lole (15 used fallow land for grazing. kg/ha) and Asasa (20 kg/ha). The level of To estimate the perceived effects of fallowing on application is affected by the availability of manure, the productivity of subsequent crops, farmers were which is closely related to the number of livestock asked to estimate the yield of the major crops planted the farm household has. However, there are other on fallowed land with fertilizer. Wheat was found constraining factors such as transport and perceived to be the highest yielding crop (24.6 q/ha) in Arsi weed problems. The mean application rates of (Table 6.8). Maize yielded 23.5 q/ha and sorghum farmyard manure reported by farmers are extremely yielded 22.2 q/ha. Barley also gave a higher yield low. They would be ineffective in replenishing soil (18.4 q/ha) than on non-fallowed lands. In general, organic matter and nutrient levels. However, the the survey indicated that all crops exhibited good manure applications were reported in gross amounts yields on fallowed lands with fertilizer application. per farm and were not disaggregated by crop or field, Thus, it is not possible to calculate the actual rates 6.3 Other Soil Fertility of farmyard manure applied to specifically targeted crops or fields. Management Practices Although hardly any farmers (1%) used green Among other soil fertility management practices, manures as a soil fertility amendment, 33% of the some farmers in Arsi Zone use organic fertilizers as farmers left part of the plant biomass on the field supplements to chemical fertilizer to enhance crop during harvesting as a contribution to soil fertility. Compost is not widely used (reported by only 4% Table 6.7. Average duration of fallow (years). of farmers). And few farmers (2%) practiced soil burning. This practice, which some farmers believe Woreda Duration improves soil fertility, was reported only in Asasa Asasa (n = 50) 1.0 and Bekoji woredas. Bekoji (n = 48) 1.2 Etheya (n = 0) - The survey revealed that the practice of applying Lole (n = 56) 1.0 farmyard manure varies among the different crops. Robe (n = 7) 5.6 Mean (n = 161) 1.3 The majority of the farmers who applied farmyard Source: Survey data, 1999. Table 6.8. Farmers' reported yields for major crops on Table 6.9. Soil fertility management practices (% of fallowed land using fertilizer (q/ha). respondents). Crop Asasa Bekoji Etheya Lole Robe Mean Asasa Bekoji Etheya Lole Robe M ean; Practice (n= 60) (n= 60) (n= 60) (n= 60) (n= 60) (n= 300) Barley 16.0 23.6 33.3 12.7 19.5 18.4 (185) Faba bean 9.0 9.2 18.3 - 22.0 16.7 (39) Farmyard Field pea ' - 28.0 17.0 - 8.7 15.4 (9) manure 25.0 16.7 15.0 21.7 48.3 25.3 Maize -- 34.0 - 12.9 23.5 (14) Green manure 1.7 3.3 1.7 -- 1.3 Sorghum -- 28.2 - 10.3 22.2 (9) Compost - 1.7 5.0 13.3 1.7 4.3 Tef 7.9 9.0 12.5 - 13.3 11.7 (67) Crop residues 55.0 1.7 30.0 - 80.0 33.3 Wheat 26.4 23.9 41.0 25.0 18.5 24.6 (218) Soil burning 8.3 3.3 - -- 2.3 Note: Figures in parentheses are numbers of respondents. Source: Survey data. 1999. 34 manure used it on wheat (54%), while 46% used it farmyard manure to the structure of the soil, a few on maize (Table 6.10). Significant proportions of adopters (2%) were aware of the benefits of organic farmers also applied farmyard manure on barley manure to soil structure. (34%) and faba bean (23%). The large proportion of Although many farmers reported the retention farmers who apply manure on cereal crops (i.e., of crop residues in the field as an alternative soil wheat, maize, and barley) suggests that fanners are fertility management practice (Table 6.9), most aware of the high nutrient uptake by cereal crops. farmers remove crop residues. About 81% feed crop Also, the cereal crops are important sources of both residues to livestock, while 71% use the residues as food and cash for the farm household. cooking fuel (Table 6.12), reflecting the severe Very few farmers used green manuring for shortage of grazing land and firewood. Farmers also wheat (1%) and barley (0.67%) in addition to use crop residues for house construction and in farmyard manure. Only 3% of the farmers in the market sales. Moreover, some farmers reported that region practiced soil burning as a soil fertility the removing of crop residues helps to control pest, management practice for wheat production, disease, and weed problems and facilitates land although no justification was given for its role in preparation. replenishing soil fertility. The surveyed farmers reported various reasons Table 6.11. Reasons for use of farmyard manure for the use of alternative soil fertility management (% of adopters). practices, particularly the application of farmyard Asasa Bekoji Etheya Lole Robe Mean manure. About 59% of the farmers who applied Reason (n = 56) (n = 26) (n = 18) (n = 14) (n = 55) (n = 169) farmyard manure indicated that the its use improves High price 5,5 soil fertility, while 12% reported increased yields as offertilizer 3.6 7.6 44.4 50.0 13.0 Increase soil a major reason (Table 6.11). The high price of fertilizer fertility 58.9 15,4 66.7 28.6 85.5 59.2 forced some manure adopters (13%) to attempt to Increase yield 3.6 19.2 33,3 21.4 9.1 12.4 minimize their fertilizer expense through Pest/disease control 3.6 - - - - 1.2 supplementation with organic inputs. Although Good for soil 1.8 3.8 - 7.1 - 1.8 farmers could not explain the contribution of Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999. Table 6.10. Crops receiving application of farmyard manure Table 6.12. Reasons for removing crop residues from fields (% of adopters). (% of respondents). Asasa Bekoji Etheya Lole Robe Mean Asasa Bekoji Etheya Lole Robe Mean Crop (n = 15) (n = 10) Maize _ 10.0 26.7 57.1 86.2 45.8 Animal feed 80.4 44.0 85.2 100 - 81,3 Wheat 66.7 40.0 80.0 64.3 34.5 54.2 Fire wood/fuel 60,9 32.0 66.7 100 - 70.6 Barley 66.7 10.0 40.0 64.3 6.9 33.7 Pest/disease/ Linseed 20.0 ---- 3.6 weed control 8.7 16.0 11.1 - 33.3 7.6 Faba bean * 26.7 70.0 6.7 42.9 3.4 22.9 House Tef 13.3 - - - - 2.4 construction 60.9 68.0 40.7 30.5 66.7 47.5 Sorghum - - -- 3.4 1.2 Ease of land Potato 20.0 -- ' -- 3.6 preparation 10.9 4.0 7.4 5,0 For sale 3.7 0.6 Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999. Note: Figures in parentheses are numbers of respondents. Source: Survey data, 1999. 35 Relationships among Farmers' Reported Crop Yields and Measured Soil Parameters 7.1 Crop Yields Reported by Farmers the farmers surveyed within each woreda. However, The 300 surveyed farmers estimated the crop yields since r values ranged roughly between 0.4 to 0.6 (i.e., they attained on their best and poorest fields both r 2 values <40%), the yield correlations are relatively with and without their customary level of fertilizer low in predictive value. application (Table 6.1). Analysis of variance of the Similarly, estimated yields with and without yield estimates across vs. within woredas for wheat, fertilizer for each of the four principal crops exhibited barley, tef, and faba beans revealed more variation significant correlations in the best fields (P <0.01 or across woredas for cereal crop yields than for faba P <0.001) and in the poorest fields (P <0.001) of the bean yield. For wheat and barley, the yields reported surveyed farmers (Table 7.2). Of even greater interest, within each field-fertilizer class combination differed the estimated increments in crop yield (q/ha) due markedly across woredas (P <0.001), presumably to fertilizer application (i.e., AY in Table 7.2) were reflecting differences in crop yield potentials among highly significant (P <0.001) for all four crop species the five agroecologies. For tef, yields varied most on both the best and the poorest fields. The yield across woredas (P <0.001) in farmers' best fields increments due to fertilizer, as calculated from the regardless of fertilizer application; the yield differences across woredas were less significant for Table 7.1. Correlations among yields of the four principal crop farmers' poorest fields either with fertilizer (P <0.01) species with fertilizer. or without (P <0.05) fertilizer. For faba bean, reported Wheat Barley Faba bean Tef yields varied across woredas (P <0.01) only for the W h eat 0.52*** 0.24T 0.36*** combination of fertilizer applied on the poorest (n = 208) (n = 64) (n = 104) fields. Barley 0.57*** 0.36** 0.59*** (n= 203) (n = 52) (n = 61) The data exhibited significant correlations Faba bean 0.42*** 0.55*** 0.26 NS among the yields reported with fertilizer application (n = 62) (n = 49) (n = 38) Tef 0.55*** 0.63*** 0.44** for virtually all pair-wise comparisons among the (n = 105) (n = 60) (n = 37) four principal crop species (Table 7.1). This high t, **, *** Significant at the 0.1,0.01, and 0.001 probability levels, across-species correlation indicates that the yield respectively. levels of the four principal crop species tend to vary Notes: Yields were estimated by surveyed farmers. Correlations above and below the diagonal represent yields reported for the best and the j in parallel across woredas and across the fields of poorest fields, respectively, n = number of respondents. Table 7.2. Comparisons of crop yields with and without fertilizer. Best fields Poorest fields______n Correlation A Y (q/ha) n Correlation A Y (q/ha) Wheat with vs. without fertilizer 192 0.45*** 14.0*** 175 0.45*** 7.7*** Barley with vs. without fertilizer 138 0.23** 10.7*** 127 0.39*** 7.0*** Faba bean with vs. without fertilizer 53 0.39** 4.8*** 52 0.60*** 4.3*** Tef with vs. without fertilizer 97 0.38*** 4.5*** 91 0.72*** 3.1*** *’ ,*** Significant at the 0.01 and 0.001 probability levels, respectively. Notes: Yields were estimated by surveyed farmers, n = number of respondents. AY = increment in crop yield due to fertilizer. 36 yields estimated by the surveyed farmers, revealed an index of fertilizer response for each of the four two major trends: principal crop species (Tables 7.3 to 7.6). Except for • Yields of wheat and barley increased much more tef response on the poorest fields (Table 7.6), all of in response to applied fertilizer than yields of the crop fertilizer response indices varied faba bean or tef. significantly across woredas. Considering the mean responses across all five woredas sampled within • The favorable fertilizer response of wheat and Arsi Zone, it was again apparent that farmers get a barley is even more pronounced on the best vs. much greater response to applied fertilizer in their the poorest fields. wheat and barley crops than in their tef or faba bean The profitability of wheat response to fertilizer was crops. In response to the fertilizer rates farmers used, estimated using the following information: wheat yield increased by 235% on the best fields and • Wheat yield increments in response to fertilizer, by 282% on the worst fields; the corresponding rates based on farmers' reported yields, were 14 q/ for barley were 309% and 303%, for tef 157% and ha on the best fields and 7,7 q/ha on the poorest 121%, and for faba bean 85% and 140%. The fields (Table 7.2). surveyed farmers in Bekoji woreda had the greatest response to fertilizer for all four crop species. Mean • Fertilizer prices were Birr 2.20/kg for DAP and yield increments due to fertilizer were calculated for Birr 1.68/kg for urea, in 1998 (Table 4.1). wheat as 620% on the best fields and 745% for the • The mean rates of fertilizer application on wheat worst fields; the corresponding rates for barley were during 1998 by fertilizer adopters were 839% and 672%, for tef 1,086% and 200%, and for calculated as 90.3 kg/ha for DAP and 19.1 kg/ faba bean 267% and 322%. In agreement with the ha for urea (Table 5.10). farmers' perceptions, the results of long-term trials • The mean wheat grain price received by farmers conducted in Etheya and Asasa woredas have clearly in the wheat-growing woredas of Arsi Zone from shown that faba bean is less responsive to applied December 1998 to April 1999 was reported to be fertilizer than wheat or barley (Tanner et al. 1999). Birr 1.46/kg (Mohammed Hassena, Kulumsa It is notable that, although in all woredas all four Research Center, personal communication). crops had high mean indexes of response to fertilizer, Assuming that the mean rate of fertilizer applied for a small minority of the farmers in each woreda to wheat was constant across all fields, the marginal the effects of applied fertilizer on the yield of at least rates of return (MRR), calculated on a cash cost basis, one of the principal crops were negative or nil. For were extremely favorable: MRRs ranged from a 385% example, based on the yields estimated by the on the poorest fields to 782% on the best fields. This surveyed farmers, negative indices of fertilizer high estimated profitability of wheat yield response response were encountered for wheat in Asasa, to applied fertilizer is consistent with the farmers' Bekoji, and Etheya (Table 7.3), for barley in Bekoji, positive assessment of fertilizer profitability: 83% of Etheya, and Lole (Table 7.4), for faba bean in Bekoji, respondents indicated that incremental crop yields Etheya, Lole, and Robe (Table 7.5), and for tef in due to applied fertilizer were sufficient to repay input Etheya and Robe (Table 7.6). In previous on-farm loans (Table 5.45). studies in the Ethiopian highlands (Asmare et al. Crop yield increments due to fertilizer 1997), farmers occasionally registered negative application were converted to a percentage of the impressions of the effects of fertilizer on their wheat respective yields without fertilizer in order to derive crops. Table 7.3. W heat: Summary of the percent yield increm ent due to applied fertilizer on the poorest and best fields. Poorest fields Best fields Woreda n Mean (%) Min. (%) Max. (%) n Mean{%) Min. (%) Max. (%) Asasa 52 138 -33 400 53 170 -33 900 Bekoji 28 745 -50 4,900 32 620 -33 3,900 Etheya 39 225 17 700 45 149 -5 800 Lole 7 580 60 1,400 8 521 100 1,233 Robe 49 173 33 1,100 54 99 14 275 Combined 175 282 -50 4,900 192 235 -33 3,900 ANOVA: ■' *** *** Between vs, within *** Significant at the 0.001 probability level. Notes: Yields were estimated by surveyed farmers, n = number of respondents. Table 7.4. Barley: Summary of the percent yield increment due to applied fertilizer on the poorest and best fields. Poorest fields Best fields Woreda n Mean (%) Min. (%) Max. (%) n Mean (%) Min. (%) Max. (%) Asasa 49 163 14 733 50 126 20 400 Bekoji 28 672 -67 4,900 35 839 -28 4,900 Etheya 38 262 11 2,567 38 111 -90 500 Lole 4 136 -38 500 6 327 100 800 Robe 8 149 0 400 9 86 0 250 Combined 127 303 -67 4,900 138 309 -90 4,900 ANOVA: Between vs. within *** *** *** Significant at the 0.001 probability level. Notes: Yields were estimated by surveyed farmers, n = number of respondents... Table 7.5. Faba bean: Summary of the percent yield increm ent due to applied fertilizer on the poorest and best fields. Poorest fields Best fields Woreda n Mean (%) Min. (% ) Max. (% ) n Mean(%) Min. (%) Max.(%) Asasa 5 75 0 125 5 14 0 25 Bekoji 6 322 -67 900 6 267 -67 700 Etheya 27 109 o 300 28 63 -43 200 Lole 2 25 -50 100 1 114 114 114 Robe 12 165 40 400 13 74 -13 233 Combined 52 140 -67 900 53 85 -67 700 ANOVA: Between vs. within * ** V * Significant at the 0.05 and 0.01 probability levels, respectively. Notes: Yields were estimated by surveyed farmers, n = number of respondents. Table 7.6. Tef: Summary of the percent yield increment due to applied fertilizer on the poorest and best fields. Poorest fields ______Best fields Woreda n Mean (% ) Min. {% ) Max. {% ) n Mean (%) Min. (%) Max. (%) Asasa 14 110 25 200 14 ■ 87 33 200 Bekoji 2 200 100 300 7 1,086 200 3,900 Etheya 26 137 0 300 28 136 -50 500 Lole ------Robe 49 111 0 900 48 . 54 -33 200 Combined 91 121 0 900 97 157 -50 3,900 ANOVA: Between vs. within NS *** *** Significant at the 0.001 probability level. Notes: Yields were estimated by surveyed farmers, n = number of respondents. 38 7.2 Chemical Analyses of Soil Sampled a maximum of 8.34 (in Etheya). However, comparing from Farmers' Fields the best and poorest fields revealed no apparent Soil samples were collected from the fields that each difference in pH between the two classes of fields; surveyed farmer identified as his or her best and the T-test was nonsignificant for each woreda and poorest fields for crop production. These soil for the combined data set for all of Arsi Zone (P >0.10, samples were chemically analyzed for pH, organic n = 292). matter, and available phosphorus contents. For soil organic matter (Table 7.8), the analysis Subsequently, the soil data were statistically of variance also detected significant differences analyzed to identify any relationships among the soil among the woredas (P <0.001). Soil organic matter chemistry parameters and the productive potential ranged from a mean of 3.84% in Robe to 5.17% in of the fields as perceived by the surveyed farmers. Bekoji woreda. High soil organic matter levels have For soil pH (Table 7.7), the analysis of variance been reported previously for Bekoji on-farm sites revealed clear differences among the woredas (P (Amanuel et al. 1991). They are related to the high <0.001). Soil pH ranged from a mean of 5.61 in Bekoji altitude of this agroecological zone. On an individual to 6.87 in Etheya woreda. Earlier soil analyses field basis, soil organic matter ranged from a conducted in conjunction with on-farm fertilizer minimum of 1.17% (in Robe) to a maximum of 9.59% trials in Arsi Zone (Amanuel et al. 1991; Tanner (in Bekoji). Contrasting the levels in the best and Asefa, and Kefyalew 1999) showed, similarly, that poorest fields revealed apparent differences in the Nitosols of Bekoji woreda are relatively low in organic matter level between the two field classes in pH. On an individual field basis, measured soil pH Robe woreda (P <0.01, n = 60) and across Arsi Zone levels ranged from a minimum of 4.17 (in Bekoji) to (P <0.05, n = 292). In Robe, mean soil organic matter Table 7.7. Summary of soil pH levels in the poorest and best fields as identified by surveyed farmers. Poorest fields Best fields Woreda n Mean pH Min. pH Max. pH n Mean pH Min. pH Max. pH Prob. T-test Asasa 60 6.11 5.12 7.82 59 6,05 5.08 7.43 NS Bekoji 56 5.57 4.43 7.76 53 5.66 4.17 7.96 NS Etheya 60 6.90 6.06 8.14 60 6.84 5.89 8.34 NS Lole 60 6.20 5.70 6.79 60 6.26 5,76 7.82 NS Robe 60 5.93 5.20 8.10 60 5.80 4.74 7.92 NS Combined 296 6.15 4.43 8.14 292 6.13 4.17 8.34 NS ANOVA: *** ■ ... Between vs, within *** Significant at the 0.001 probability level. Note: n = number of respondents. Table 7.8. Summary of soil organic matter levels in the poorest and best fields as identified by surveyed farmers. Poorest fields Best fields Woreda n Mean (% ) Min. (% ) Max. (%) n Mean (% ) Min. (% ) Max. (% ) Prob. T-test Asasa 60 3.96 2.31 6.66 59 3.90 1.55 7.18 NS Bekoji 56 5.15 2.31 9.59 53 5.19 2.75 7.94 NS Etheya 60 4.04 1.69 6.07 60 4.20 2.75 5.66 NS Lole 60 4.72 3.45 6.33 60 4.98 3.58 7.98 NS Robe 60 3.39 1.17 8.90 60 4.28 1.17 8.56 ** Combined 296 4.24 1.17 9.59 292 4.50 1.17 8.56 * ANOVA: Between vs. within ...... \ ” , *'*’ Significant at the 0.05,0.01, and 0.001 probability levels, respectively. Note: n = number of respondents. 39 levels were 3.39% for the poorest fields and 4.28% <0.001, n = 292). Across Arsi Zone, the mean soil P for the best fields; across Arsi Zone, mean soil organic contents were 5.61 ppm for the poorest fields matter levels were 4.24% for the poorest fields and identified by farmers and 8.61 ppm for best fields. 4.50% for the best fields. Amanuel et al. (1991) Wheat is highly responsive to fertilizer P in Bekoji reported a significant relationship between soil and Asasa woredas (Amanuel et al. 1991; Tanner organic matter levels and wheat response to fertilizer Asefa, and Kefyalew 1999), however the current N in the Ethiopian highlands, however the r2 value analysis does not facilitate the differentiation of the they found was too low to be of predictive value for farmers' field classes in these two woredas on the estimating N response in individual farmers' fields. basis of Olsen P values. The available P contents of Soil available P content, as measured by the the sampled soils as determined via the procedure Olsen analytical procedure (Table 7.9), varied across of Bray & Kurtz (Table 7.10) paralleled the P values woredas for the best fields (P <0.001) and the poorest measured using the Olsen procedure. Soil available fields (P <0.05). Mean soil P content varied from a P content varied across woredas for the best (P <0.01) minimum of 4.98 ppm for Asasa to a maximum of and the poorest (P <0.05) fields. Mean soil P content 9.16 ppm for Bekoji woreda. In individual fields, P varied from a minimum of 9.66 ppm for Asasa to a content varied from a minimum of 0.20 ppm (in maximum of 24.5 ppm for Etheya woreda. Across Etheya) to a maximum of 74.8 ppm (in Robe). The the individual fields sampled, P content ranged from T-test indicated a significantly higher P content in a minimum of 0.72 ppm (in Bekoji) to a maximum of the best vs. the poorest fields for Etheya (P <0.01, n 267 ppm (in Bekoji). Contrasting available soil P = 60), Robe (P <0.001, n = 60), and for Arsi Zone (P levels in the best and poorest fields revealed apparent Table 7.9. Summary of Olsen P levels in the poorest and best fields as identified by surveyed farmers. Poorest fields Best fields Woreda n Mean (ppm) Min. (ppm) Max. (ppm) n Mean (ppm) Min. (ppm) Max. (ppm) Prob. T-test Asasa 60 4.74 1.48 41.7 59 5.29 1.26 35.2 NS Bekoji 56 7.49 1.46 50.5 53 10.9 2.06 68,8 NS Etheya 60 6.46 0.20 34.7 60 10.4 0.44 47.4 «* Lole 60 5.21 2.10 27,4 60 4.74 1.70 17.6 NS Robe 60 4.27 1.46 16.1 60 11.90 1.74 74.8 *** Combined 296 5.61 0.20 50.5 292 8.61 0.44 74.8 ... ANOVA: Between vs. within * .... *, **, *** Significant at the 0.05,0.01, and 0.001 probability levels, respectively. Notes: n = number of respondents. Table 7.10. Summary of Bray and Kurtz P levels in the poorest and best fields as identified by surveyed farmers. Poorest fields Best fields Woreda n Mean (ppm) Min. (ppm) Max. (ppm) n Mean (ppm) Min. (ppm) Max. (ppm) Prob. T-test Asasa 60 8.84 1.50 74.4 59 10.5 1.41 68.2 NS ! Bekoji 56 15.1 0.72 191 53 21.7 1.29 267 NS ; ■ ** ; Etheya 60 16.0 2.34 130 60 32.9 3.50 196 Lole 60 9.28 2.39 96.1 60 10.2 2.15 101 NS ; Robe 60 6.18 1.21 38.1 60 29.8 2.66 264 ** i Combined 296 11.0 0.72 191 292 21.0 1.29 267 *** ; ANOVA: Between vs. within * .. *, **, Significant at the 0.05,0.01, and 0.001 probability levels, respectively. Notes: n = number of respondents. differences in available P content between the two values, the correlations were significant for Robe (P field classes in Etheya (P <0.01, n = 60), in Robe (P <0.001), Bekoji (P <0.05), and Etheya (P <0.01). These <0.01, n = 60), and for Arsi Zone (P <0.001, n = 292). positive correlations suggest that a significant Across Arsi Zone, the mean P contents were 11.0 ppm fraction of the available P content determined for for the poorest fields, as identified by the surveyed Arsi soils is derived from soil organic matter. In farmers, and 21.0 for the best fields. Thus, there were general, the mineralization of soil organic matter no obvious differences between the two P analytical represents a major source of N and P in subsistence- procedures in terms of their capacity to differentiate oriented farming systems. However, we are not between the two classes of farmers' fields. aware of any detailed studies of the chemistry of soils Correlations among the four measured soil in Arsi Zone that provide corroborating evidence for parameters were calculated using the data within this relationship. each woreda and across the five woredas surveyed in Arsi Zone (Tables 7.11 to 7.13). Table 7.11. Correlations among soil parameters across all five woredas and for Asasa woreda. Available soil P levels estimated by the Olsen Organic P P and the Bray & Kurtz procedures were highly pH matter (Olsen) (Bray & Kurtz) correlated whether the data were analyzed across pH -0.30*** 0.04 0.13** woredas (r = 0.90, P <0.001, n = 588) or within the organic matter -0.35*** 0.23*** 0.21*** five individual woredas (0.83 < r < 0.92, P <0.001). P (Olsen) 0.11 0.09 0.90*** This corroborates the earlier observation that the two P (Bray & Kurtz) 0.23* 0.13 0.86*** P analytical procedures were essentially equal in * ,", *” Significant at the 0.05,0.01, and 0.001 probability levels, respectively. their capacity to differentiate the sampled soils in Notes: Correlations above diagonal for data across woredas (n = 588); the current study. below diagonal for data from Asasa woreda (n = 119). Soil organic matter and pH levels were negatively correlated across woredas {r = -0.30, P Table 7.12. Correlations among soil parameters for Bekoji and Etheya woredas. <0.001, n = 588) and within the five individual Organic P P woredas (-0.20 < r < -0.42, P <0.001). This negative pH matter (Olsen) (Bray & Kurtz) relationship forms the basis of one of the general -0.20* 0.06 0.14 principles of soil chemistry: disturbance of soils for PH organic matter -0.36*** 0.23* 0.24* agricultural purposes stimulates the microbial P (Oisen) 0.09 0.22* 0.92*** conversion of soil organic matter to nitrate, releasing P (Bray & Kurtz) 0.10 0.28** 0.86*** protons in the process. Hence, as a consequence, soils * ** *** Significant at the 0.05,0.01, and 0.001 probability levels, respectively. with high organic matter content can be expected to Notes: Correlations above diagonal for data from Bekoji woreda (n = 109); exhibit higher nitrate levels and lower pH levels. below diagonal for data from Etheya woreda (n = 120). Soil organic matter and available P contents were positively correlated across the five woredas for both Table 7.13. Correlations among soil parameters for Lole and Robe woredas. the Olsen method (r = 0.23, P <0.001, n = 588) and the Bray & Kurtz method (r = 0.21, P <0.001, n = Organic P P PH matter (Olsen) (Bray & Kurtz) 588) (Table 7.11). Within individual woredas, significant positive correlations were also observed pH -0.36*** -0.02 0.09 organic matter -0.42*** 0.16t 0.09 between soil organic matter and available P as P (Olsen) 0.03 0.33*** 0.83*** follows: for Olsen P values, the correlations were P (Bray & Kurtz) 0.07 0.30*** 0.92*** significant for Lole (P <0.10), Robe (P <0.001), Bekoji t, *** Significant at the 0.1 and 0.001 probability levels/respectively.. (P <0.05), and Etheya (P <0.05); for Bray & Kurtz P Notes: Correlations above diagonal for data from Lole woreda (n = 120); below diagonal for data from Robe woreda (n «120). 7.3 Relationships among Soil to crop plants, so fertilizer P partially compensates Parameters and Crop Yields for the effects of soil acidity. Correlations between the four measured soil The correlations between soil pH and the indices parameters and crop yields, with and without of yield response to applied fertilizer were negative fertilizer, and the yield increment due to fertilizer and highly significant for the four major crop species (expressed as a percentage of the yield without (Table 7.14), suggesting two trends: fertilizer) were calculated for the combined data set • The yield response to farmers' fertilizer (Table 7.14) and separately for each of the five applications, dominated by basal application of surveyed woredas (Appendices 2 to 6). DAP, is greater on low pH soils and diminishes Considering the data set across Arsi Zone (Table at higher pH levels. 7.14), soil pH was positively correlated with yield • Yields without applied fertilizer on low pH soils without fertilizer for wheat (r = 0.26, P <0.001, n = are relatively low, resulting in very high indices 374), barley (r = 0.37, P <0.001, n = 293), and faba of yield increment when expressed as a bean (r = 0.24, P <0.01, n = 139). The correlation percentage of the yield without fertilizer. between soil pH and yield with applied fertilizer was For individual woredas, the associations less pronounced, being significant only for wheat (r between soil pH and crop yields were most = 0.15, P <0.001, n = 556) and faba bean (r = 0.16, P pronounced in Bekoji (Appendix 3), the woreda <0.1, n = 125). These results suggest that crop yields characterized by the lowest mean soil pH level (Table increase in response to higher soil pH, but that 7.7). fertilizer application weakens this association. These conclusions are logical because the surveyed fanners Surprisingly, the correlations between soil pH apply more fertilizer P than N to their crops. Acid and crop yields were reversed in sign for wheat and soils are characterized by low availability of soil P tef in Robe (Appendix 6), suggesting that wheat and tef yields diminished as soil pH increased. For the Table 7.14. Correlations among crop yields3 and measured Robe data set, the farmers' poorest fields exhibited soil parameters across the five sampled woredas. a higher mean pH level than the best fields, 5.93 vs. Soil parameter 5.80 (Table 7.7), although this apparent difference ~~ Organic P P (Bray was not significant. There is no obvious explanation Crop n pH matter (Olsen) & Kurtz) for this reverse relationship between soil pH and Yield with fertilizer crop yields in Robe relative to the other surveyed Wheat 0.15*** 0.06 0.07 0 .12 556** Barley 0.00 -0.06 0.14** 0 .11 409* woredas. Faba bean 0.16t 0.03 0.20* 0.20 125* Soil organic matter content had low and Tef 0.04 0.00 0.13t 0.11 211 generally nonsignificant correlations with crop Yield without fertilizer Wheat 0.26*** 0.02 0.13* 0.19* 374 yields, either with or without applied fertilizer, Barley 0.37*** -0.18** 0.12* 0.13" 293 except for Etheya woreda (Appendix 4). For the Faba bean 0.24** 0.04 0.33*** 0.37* 139 Etheya data set, soil organic matter level was Tef -0.09 0.06 0.12 0.08 197 positively correlated with yield without fertilizer for Yield increment due to fertilizer (%) wheat, barley, and faba bean and with yield with Wheat 362 -0.29*** 0.21*** -0.03 -0.07 Barley 258 -0.38*** 0.26*** 0.00 -0.07 applied fertilizer for wheat and faba bean. Etheya Faba bean 104 -0.37*** 0.10 -0.14 -0.181 exhibited a low soil organic matter level (Table 7.8) Tef 188 -0.22** 0.15* -0.03 -0.05 relative to the mean across Arsi Zone. The positive t, *, **, *** Significant at the 0.1,0.05,0.01, and 0.001 probability levels, correlations obtained from the Etheya data set respectively. Notes: Yields were estimated by surveyed farmers, n = number of indicate that higher soil organic matter levels respondents. enhance crop yields with or without applied buying no urea during 1995-98, but a minority of fertilizer, presumably by supplying more nitrate the farmers, in only three of the five woredas, (and other nutrients) to the crops as a result of the reported nil procurement of DAP. mineralization and nitrification processes in the soil. In general, farmers' cumulative procurement of This postulation is supported by the significant and DAP and urea during 1995-98 was not significantly positive correlations between soil organic matter correlated with crop yields. The correlations between level and yield increments due to fertilizer observed cumulative DAP procurement and crop yields (Table in the entire Arsi data set (Table 7.14): at higher soil 7.16) were only significant for wheat yields with organic matter levels, crop response to applied fertilizer on the best fields (r - 0.14, P <0.05) and the fertilizer is enhanced (i.e., N derived from the soil poorest fields (r = 0.12, P <0.05) and for faba bean organic matter interacts synergistically with P yields with fertilizer on the best fields (r = -0.26, P supplied by the applied DAP). <0.05). Cumulative urea procurement was The correlations between the available soil P test significantly correlated only with tef yield with values, generated by both analytical procedures, and fertilizer on the poorest fields (r = 0.21, P <0.05). crop yields were generally positive and significant both with and without fertilizer for the Arsi data set Table 7.15. Cumulative amounts of DAP and urea purchased (Table 7.14). This suggests that crop yields are from 1995 to 1998 per farmer.3 enhanced by higher levels of available soil P and that DAP (kg) Urea (kg) the yield enhancement effect is independent of Woreda Mean Min. Max. Mean Min. Max. applied fertilizer. That observation is supported by Asasa 480 0 1,400 26 0 250 the absence of a significant correlation between the Bekoji 599 0 1,750 9 0 250 Etheya index of yield response to fertilizer and available soil 495 0 2,400 60 0 400 Lole 825 125 2,050 18 0 200 P. For individual woredas, the relationship between Robe 262 183 900 23 0 150 available soil P and crop yields was most apparent Combined 532 0 2,400 27 0 400 in Asasa (Appendix 2) and Etheya (Appendix 4). ANOVA: Between vs. within * ** * * * Considered together with the marked positive *** Significant at the 0.001 probability level. response to fertilizer shown in Table 7.2, it is a/As reported by 60 surveyed farmers in each woreda. apparent that soil P levels and farmers' applications of basal DAP have an additive and individually Table 7.16. Correlations between crop yields with fertilizer positive effect on crop yields. and cumulative amounts of DAP and urea purchased, 1995-98.3 Fertilizer purchased 7.4 Cumulative Amounts of DAP Urea n‘ DAP and Urea Purchased Wheat on best field 0.14* 0.22 286 The 300 surveyed farmers reported the cumulative on poorest field 0.12* 0.10 281 amounts of DAP and urea fertilizer they purchased Barley from 1995 to 1998 (Table 7.15). Totals for both types on best field -0.04 0.06 212 on poorest field -0.06 0.13 208 of fertilizer differed significantly (P <0.001) among Faba bean the woredas. Farmers in Lole and Bekoji reported on best field -0.26* -0.11 65 the highest mean procurement levels of DAP, while on poorest field -0.18 0.11 63 Tef farmers in Etheya reported the highest levels of urea on best field -0.01 0.11 105 procurement. It is worth noting that the mean urea on poorest field -0.11 0.21* 106 procurement reported was only 5% of the mean DAP * Significant at the 0.05 probability level. aI Crops yields and fertilizer purchases as reported by surveyed farmers, procurement. Also, a majority of farmers reported bI Number of respondents. 43 Cumulative DAP procurement was not Similarly, the correlations between cumulative significantly correlated with soil P test values (Table urea procurement and soil organic matter, soil pH, 7.17) either across Arsi Zone or within individual and the indices of crop yield response to applied woredas, indicating that the current study failed to fertilizer were predominantly nonsignificant (Table capture any residual effect of DAP application 7.18). However, given the extremely low level of urea history on levels of available soil P. Significant bought and applied throughout Arsi Zone (Table positive correlations of cumulative DAP 7.15), the absence of significant correlations is not procurement to the index of crop yield response to unexpected, fertilizer in only 4 of the 24 crop x district correlations (Table 7.17). Table 7.17. Correlations between cumulative amount of DAP purchased and soil P levels and crop yield increments, 1995-98. DAP purchased Combined Asasa Bekoji Etheya Lole Robe P (Olsen) -0.07 -0,06 0,22 -0.07 -0.11 -0.18 P (Bray & Kurtz) -0.07 0.05 0.14 -005 -0.04 -0.15 Wheat AY 0.29*** 0.18 0.16 0.07 -0.10 0.27* Barley AY 0.14 0.12 -0,03 -0.09 0.66 0.38 Faba bean AY 0.08 0.19 -0.03 -0.25 ■ - : -0.05 Tef AY 0.26* O CO -0.45 -0.02 0.22 VV** Significant at the 0.05,0.01, and 0.001 probability levels, respectively. Notes: Crop yield and fertilizer purchases as reported by 60 surveyed farmers in each woreda. AY = Yield increment with fertilizer application on best fields. Table 7.18. Correlations of cumulative amount of urea purchased with soil organic matter content, pH level, and crop yield increments, 1995-98. Urea purchased Combined Asasa Bekoji Etheya Lole Robe Organic matter -0.09 0.08 -0.01 -0.04 -0.24t -0.01 PH 0.14* 0.03 0.00 -0,05 0.14 . -0.18 Wheat AY -0.08 -0.02 -0.01 -0.05 0.29 0.17 Barley AY -0.12 0.31* -0.05 0.10 . -0.66 -0.07 Faba bean AY -0.15 0.62 • -0.50 -0.01 -0.14 Tef AY -0.08 -0.29 -0.30 -0.06 - -003 t, * Significant at the 0.1 and 0.05 probability levels, respectively. Notes: Crop yield and fertilizer purchases as reported by 60 surveyed farmers in each woreda. AY = Yield increment with fertilizer application on best fields. 44 Conclusions and Recommendations Although the mean fertilizer application rate in 74 kg P2Os (about 150 kg DAP and 50 kg urea) for Ethiopia has historically been very low (about 15 kg/ barley, and 78 kg N and 20 kg P2Os (about 50 kg DAP ha of nutrients annually), the use of inorganic and 150 kg urea) for tef. fertilizer by small-scale farmers in Ethiopia is Farmers in Arsi Zone have substantially currently increasing. Furthermore, there are regions benefited from the presence of the CADU/ARDU in Ethiopia with a lengthy history of use of Comprehensive Project, which was instrumental in commercial fertilizers. In high potential agricultural stimulating agricultural research and the areas such as Arsi, Eastern Gojam, and Eastern dissemination of improved technologies for almost Showa, farmers began applying commercial 20 years beginning in the late 1960s. However, the fertilizers during the late 1960s. results of the socio-economic and soil survey Studies aimed at identifying and recommending conducted in Arsi Zone revealed that mean rates of proper fertilizer types and rates for different crops application of DAP and urea fertilizers by farmers and agroecologies have been conducted in the past in Arsi were not consistent with any of the by several agricultural research centers of EARO recommended rates. The survey found that the mean (and its predecessor institution IAR), higher learning rate of fertilizer application per hectare (i.e., institutes and some projects in the Ministry of weighted mean rate of fertilizer use by adopters and Agriculture. In the 1970s, there was one "blanket" non-adopters) is 83 kg DAP and 18 kg urea for wheat, recommendation rate—100 kg/ha of DAP and 50 59 kg DAP and 5.5 kg urea for barley, and 40 kg DAP kg/ha of urea—for all cereals throughout Ethiopia. and 7 kg urea for tef. Thus, the current study revealed However, research centers and higher learning that on wheat, farmers in Arsi use 83% of the NFIU institutes had recommended location-specific recommendation for DAP and only 14% of the fertilizer rates in their mandated zones. In the early recommended amount of urea. 1990s, the National Extension Campaign Program Analysis of yield data reported by farmers and. promoted a new blanket recommendation—100 kg/ soil data from sampled fields showed that farmers ha of DAP and 100 kg/ha of urea for all cereals in logically relate crop yields to soil fertility status. the high rainfall zones of Ethiopia. This Fields identified by farmers as high producing were recommendation was later adjusted to suit specific generally higher in soil organic matter and P. That crop and rainfall regimes. By the mid-1990s, the explains why many farmers in Ethiopia deliberately National Fertilizer and Inputs Unit (NFIU) of the adjust the amount of fertilizer applied on specific Ministry of Agriculture compiled its long-term areas within a field, and suggests that they may often fertilizer study results and developed be correct in doing so. recommendations that were specific to area, crop, Farmers in Arsi perceive that there is a and soil type. For Arsi, the NFIU recommended rate considerable yield increment due to fertilizer per hectare was 79 kg N and 44 kg P2Os (about 100 application on their major crops, in general, and on kg DAP and 125 kg urea) for wheat, 42 kg N and wheat and barley, in particular. They also believe that this increment is substantially higher on their best with the marked positive yield response of wheat fields than on their poorest fields. This finding may and barley to applied fertilizer, it is apparent that justify the need to establish fertilizer trials on both soil P levels and the basal application of DAP have the best and the poorest fields as identified by the an additive and individually positive effect on crop farmers. The current findings may also lead to the yields. establishment of different recommendation rates for One of the most important findings of this joint fields characterized by different levels of soil fertility socio-economic and soil survey is that, although the as identified by farmers. sampled farmers in Arsi purchased and applied, on Estimates of fertilizer profitability in wheat were average, a cumulative total of 532 kg of DAP on their highly positive in both categories of fields. The farms from 1995 to 1998, cumulative DAP levels estimated high profitability of wheat yield response were not significantly correlated with either soil P to fertilizer was consistent with the farmers' test values or crop yields across Arsi or within assessment of fertilizer profitability: 83% indicated individual woredas. This implies that the current that incremental crop yields due to applied fertilizer study failed to capture any residual effect of the were sufficient to repay input loans. farmers' DAP application history on the levels of There were considerable differences in available soil P. Presumably the amount of P added measured soil pH levels across the five woredas. For annually in the form of DAP is too small to have the entire Arsi data set, soil pH was positively any cumulative effect. Thus, there is clearly scope correlated with yield without fertilizer, particularly to increase the rate of DAP application in order to for wheat and barley. These results indicate that crop enhance crop yields and accumulate soil P capital, yield levels are enhanced with increasing soil pH, In general, there were marked variations in the but that fertilizer application weakens this estimated cereal crop yields across the five woredas association. surveyed, indicating differences in crop yield In agreement with previous studies, the survey potential among the five agroecologies. The confirmed the positive relationship between soil establishment of fertilizer trials in each woreda will organic matter levels and wheat response to fertilizer facilitate the development of fertilizer N. The study also revealed that soils in the five recommendations aimed at increasing productivity woredas differ distinctly in soil organic matter in the lower potential woredas. content. Soil organic matter levels differed The results of the socio-economic and soil significantly in the best and poorest fields. Across survey reported in this document will facilitate the the entire Arsi soil data set, there were also development of on-farm fertilizer trials to be significant and positive correlations between soil conducted in the surveyed woredas starting in 2000. organic matter level and yield increments due to It is anticipated that these studies will lead to the applied fertilizer. establishment of more focused and accurate Positive correlations were observed between soil fertilizer recommendations in the five woredas ojf P levels and crop yields, both with and without Arsi Zone based on soil test values derived from fertilizer, suggesting that crop yields are enhanced sampled farmers' fields. Furthermore, fertilizer by higher levels of available soil P. This yield recommendations must be dynamic, reflecting enhancement effect is not dependent on applied changing economic scenarios. Also, lessons learned fertilizer, particularly considering that farmers apply in undertaking this exercise should guide similar suboptimal nutrient levels. Considered together studies in other parts of Ethiopia in the future. 46 Thus, considering (1) that fertilizer terms of soil fertility. As far as practical, the selection recommendations do not exist for each of the major of fertilizer trial sites should take into consideration crops within the specific agroecologies of Arsi Zone, the range of values for soil pH, organic matter and (2) that marked variations were observed in the rates P, and not only mean values. of fertilizer application by farmers across the Since it may be important to consider other different woredas within Arsi, and (3) that fertilizer nutrients in addition to N and P, the fertilizer trials rates adopted by farmers do not reflect the to be established, particularly on red soils, should recommendations, there is an urgent need to also include secondary treatments with potassium, properly study and refine crop-specific fertilizer sulfur, and micronutrients where detailed soil recommendations for Arsi Zone by woreda and soil analyses indicate potential deficiency. The fertilizer type. This suggests a need to establish fertilizer trials trials should also incorporate treatments to study the in all of the major crop-producing woredas of Arsi application timing of N fertilizer. and in fields identified by farmers as contrasting in 47 REFERENCES ADB (African Development Bank). 1996. African development Conference of the Agricultural Economics Society of Ethiopia, report 1996. Washington, D.C. 3-4 October, 1996, ed. Mulat Demeke, Wolday Amha, Amanuel Gorfu, Asefa Taa, D. G. Tanner, and W. Mwangi. Tesfaye Zegeye, Solomon Belete, and S. Ehui, 242-266. 1991. On-farm research to derive fertilizer recommendations Addis Ababa: Agricultural Economics Society of Ethiopia. for small-scale bread wheat production: Methodological issues Mulugeta Mekuria. 1995. Technology development and and technical results. Research Report No. 14. Addis transfer in Ethiopian agriculture: An empirical evidence. Ababa: 1AR. 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Payne, and O. S. Abdalla, Seventh Regional Wheat Workshop for Eastern, Central, and 96-103. Addis Ababa: CIMMYT. Southern Africa, ed. D. G Tanner and W. Mwangi, 239- Mulat Demeke. 1996. Constraints to efficient and sustainable 253. Nakuru, Kenya: CIMMYT use of fertilizer in Ethiopia. In Sustainable intensification World Bank. 1994. World development report 1994. New York: of agriculture in Ethiopia: Proceedings of the Second Oxford University Press. APPENDIXES Appendix 1. Varietal adoption for various crops, Arsi Zone, Appendix 2. Correlations among crop yields and measured 1998 (% of respondents). soil parameters for Asasa. Asasa Bekoji Etheya Lole Robe Mean ______Soil parameter______Organic P P (Bray Tef Crop n pH matter (Olsen) & Kurtz) Red 70 100 4 19 25 (25) Local 20 - 96 - 70 68 (69) Yield with fertilizer White 10 -- - 4 3 (3) Wheat 117 -0.11 -0.09 0.05 0.07 DZ-01-354 -- - - 7 4 (4) Barley 111 -0.09 -0.13 0,06 0.03 Maize Faba bean 10 0.28 0.43 0.24 0.19 Mesimeru 2 1 (1) Tef 28 -0.08 0.03 -0,06 -0.06 Local -- 31 100 91 65 (48) Yield without fertilizer Merde - - - - - 5 3 (2) Wheat 104 0.00 -0.12 0.22* 0.19f Mize _ - 38 - _ 16 (12) Barley 100 0.00 -0.15 0,25* 0.22* Katumani - _ 22 - 10 (7) Faba bean 30 0.05 -0.24 0.351" 0.21 Kulnie -- 6 - 2 4 (3) Tef 32 0.10 -0.11 0.16 0.15 Alemaya - - 3 - - 1 (1) Linseed Yield increment due to fertilizer (%) _ _ I English 57 8 100 20 (6) Wheat 104 -0.20* 0,09 O CO -0.10 Local 43 92 - - 100 80 (24) Barley 98 -0.04 0.04 -0.09 -0.11 Field pea Faba bean 10 0.34 0.23 0.44 0.50 Ferenge 50 _ _ 100 57 (4) Tef 28 -0,24 0.10 -0.39* -0.331 Local 50 - 100 - - 43 (3) T, * Significant at the 10 and 5% levels, respectively. Faba bean Notes: Yields were estimated by surveyed farmers, n = number of _ Local 100 90 100 100 96 (24) samples. Ferenge - 10 - - - 4 (1) Bean Local . 96 . 100 97 (31) Appendix 3. Correlations among crop yields and measured Debelek - - 4 - - 3 (1) soil parameters for Bekoji. Potato ______Soil parameter______Local 75 100 100 90 (9) Organic P P (Bray Red 25 - - ' -- 10 (1) Crop n pH matter (Olsen) & Kurtz) Onion Local 50 . 50 (2) Yield with fertilizer Gojam - - 50 - - 50 (2) Wheat 0.18t 0.00 -0.02 0.02 91 -0.16 0.06 0.05 0.03 Note: Figures in parentheses are numbers of respondents. Barley 86 Source: Survey data, 1999. Faba bean -0.26 0.01 -0.20 -0.27 18 Tef -0.14 -0.22 0.08 0.06 17 Yield without fertilizer Wheat 68 0.31** 0.01 0.01 0.05 Barley 74 0.38*** -0.211 0.08 0.10 Faba bean 18 0.50* -0.30 0.37 0.24 1 Tef 12 0.20 O CO CO -0.12 -0.12 Yield increment due to fertilizer (%) Wheat 56 -0.45*** 0.29* -0.08 -0.12 Barley 57 -0.44*** 0.24t -0.07 -0.12 Faba bean 11 -0.59t 0.12 -0.31 -0.33 Tef 9 -0,46 -0.03 -0.17 -0.25 t, *, **, *** Significant at the 10,5,1 and 0.1% levels, respectively. Notes: Yields were estimated by surveyed farmers, n = number of samples. 49 Appendix 4. Correlations among crop yields and measured Appendix 5. Correlations among crop yields and measured soil parameters for Etheya. soil parameters for Lole. Soil parameter Soil parameter Organic P P (Bray Organic P P (Bray Crop n pH matter (Olsen) & Kurtz) Crop n PH matter (Olsen) & Kurtz) Yield with fertilizer Yield with fertilizer Wheat 114 0.09 0.30*** 0.19* 0.24* Wheat 120 0.09 0.13 -0.04 0.03 Barley 95 0.01 0.09 0.21* 0.11 Barley 97 0.13 0.03 -0.04 0.09 Faba bean 66 0.15 0.24T 0.43*** 0.39*** Faba bean 4 0.80 0.92T 0.95* 0.72 Tef 66 0.27* -0.09 0.07 0.08 Yield without fertilizer Yield without fertilizer Wheat 15 0.69** -0.46t 0.22 0.03 Wheat 84 0.13 0.31’ * 0.211 0.35*** Barley 10 0.10 -0.18 0.18 0.04 Barley 81 0.09 0.20T 0.13 0.10 Faba bean 5 0.97** 0.01 0.52 0.61 Faba bean 57 0.17 0.27* 0,31* 0.40** Yield increment due to fertilizer (%) Tef 54 0.24| 0.05 -0.10 -0.07 Wheat 15 -0.52* 0.67** -0.15 0.13 Yield increment due to fertilizer (%) Barley 10 -0.21 0.42 0.09 0.20 Wheat 84 -0.19t -0.07 -0.06 -0.17 Faba bean 3 0.28 0.68 0.58 0.55 Barley 76 -0.19 -0.07 0.05 -0.07 T, *, ** Significant at the 10,5, and 1% levels, respectively. Faba bean 55 -0.06 -0.08 -0.11 -0.14 Notes: Yields were estimated by surveyed farmers, n = number of Tef 54 -0.13 -0.05 0.12 0.09 samples. t, *, * * , Significant at the 10,5,1 and 0.1% levels, respectively. Notes: Yields were estimated by surveyed farmers. n.= number of samples. Appendix 6. Correlations among crop yields and measured soil parameters for Robe. Soil parameter Organic P P (B ra y Crop n pH matter (Olsen) & Kurtz) Yield with fertilizer Wheat 114 -0.29** 0.11 0.15 0.11 Barley 20 -0.16 -0.36 -0.16 -0.15 Faba bean 27 -0.17 0.10 0.14 0.09 Tef 100 -0.36*** 0.13 0.12 0.08 Yield without fertilizer Wheat 103 -0.30’ * 0.20* 0.16t 0.11 Barley 28 -0.05 -0.13 -0.06 -0.08 Faba bean 29 -0.18 0.18 0.37* 0.41* Tef 99 -0.32*** 0.23* 0.16 0.10 Yield increment due to fertilizer (%) Wheat 103 0.09 -0.14 -0.07 -0.06 Barley 17 -0.17 -0.23 -0.27 -0.26 Faba bean 25 -0.10 -0.19 -0.28 -0.37T Tef 97 -0.07 -0.07 -0.13 -0.10 t, *, *'* Significant at the 10,5,1 and 0.1% levels, respectively. Notes: Yields were estimated by surveyed farmers, n = number of samples.