Maize for food and feed in East Africa—The farmers’ perspective

Field Crops Research 153 (2013) 22–36

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Maize for food and feed in East Africa—The farmers’ perspective Hugo De Groote a,∗ , Getachew Dema b , George B. Sonda c , Zachary M. Gitonga a a

International Maize and Wheat Improvement Center (CIMMYT), PO Box 1041-00621, Nairobi, Kenya Haramaya University, P.O. Box 138, Dire Dawa, Ethiopia c Sokoine University of Agriculture, currently Lake Zone Agricultural Research and Development Institute, P.O. Box 1433, Ukiriguru, Mwanza, Tanzania b

a r t i c l e

i n f o

Article history: Received 9 July 2012 Received in revised form 1 March 2013 Accepted 2 April 2013 Keywords: Maize Mixed cropping system Dual-purpose Participatory evaluation

a b s t r a c t The rapid increase of both human and livestock populations, along with a restricted land base and an increased demand for livestock products, put high pressure on the maize-livestock systems that dominate East and Southern Africa. Dual-purpose maize, i.e. varieties with increased grain and stover yields, are therefore being developed. These varieties show high potential, but it is not clear if they respond to a demand by targeted farmers. Therefore the farmers’ perspective on such varieties was studied in selected districts in Ethiopia (three districts) and Tanzania (two districts), using both informal methods (participatory rural appraisals) and formal methods (farmer evaluation of varieties and household surveys), the latter involving 360 households in Ethiopia and 150 households in Tanzania. Results show that maize stover is an important element of livestock feed in the study areas. Farmers mention a wide variety of criteria they use to evaluate maize varieties. These include field characteristics such as yield and pest resistance, consumer characteristics such as cooking and taste qualities, and feed characteristics including stover quality and quantity. Analysis of adoption patterns shows that varieties that score well on feed characteristics have a higher probability of being adopted. We conclude that there is a demand for varieties with increased stover quantity and quality, as long as they do not compromise field characteristics, in particular yield, and consumer qualities. Such varieties would have the potential to increase the productivity of maize-livestock systems and the income of these farmers, while reducing the pressure on the environment. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Sub-Saharan Africa faces a rapid growth of both human and animal populations, but the land area available for agriculture and livestock is limited (Herrero et al., 2007). A large proportion of arable land is used for growing maize, now by far the most important food crop in East and Southern Africa (with 23% and 34% of crop land, respectively) (FAOSTAT, 2012). The crop is adapted to a wide range of conditions, is more productive than traditional cereals, and its grain is easier to store and transport than root crops, which is important for the increasingly urban population. At the same time, economic growth increases standards of living, and with it the demand for livestock production (Delgado, 2003), leading to increased competition for land between food and feed (Herrero et al., 2007). Unlike other continents, little maize is used directly in Africa for livestock feed, either as grain or as silage (Pingali, 2001). Crop residues, on the other hand, are very commonly fed to livestock (Romney et al., 2003; Herrero et al., 2007).

∗ Corresponding author. Tel.: +254 20 722 4600; fax: +254 20 722 4601. E-mail address: [email protected] (H. De Groote). 0378-4290/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.fcr.2013.04.005

Maize varieties with good yields for both grain and fodder would be of interest to many farmers, yet maize research programs have mainly focused on breeding for improved grain yield and resistance to biotic and abiotic stress (CIMMYT, 2012), ignoring biomass and other fodder characteristics. Recent research has developed several dual-purpose maize varieties that do not compromise grain yield for stover yield and quality (Berhanu et al., 2012). So far, however, the demand for these varieties and the farmers’ perspective on this development has not been investigated. In principle, the potential demand for dual-purpose maize varieties in Africa is great. Not only is maize the most important food crop in East and Southern Africa (Pingali, 2007; FAO, 2011), but also almost all of it is produced in the mixed livestock-crop areas (62% in the extensive and 30% in the intensive mixed zones) (Herrero et al., 2007), with strong interactions between both enterprises. Livestock is increasingly important in the rural economy, and increasing incomes and urbanization drive the increased demand for livestock products (Delgado, 2003). Most agricultural areas of East Africa have been developed into mixed crop–livestock systems, especially the more densely populated areas such as the highlands (Cecchi et al., 2010). In these systems, the interactions between crops and livestock are complex and multi-level. Animals provide elements necessary

H. De Groote et al. / Field Crops Research 153 (2013) 22–36

for agricultural intensification, in particular power and animal traction (Pingali et al., 1987), manure for fertilization (McIntire and Gryseels, 1987), high quality nutrition, cash income, transport of inputs to the fields and outputs to homestead and markets (FAO, 2001). Further, livestock provide a convenient savings, investment and insurance mechanism (FAO, 2001). With increased intensification of semi-subsistence agriculture, land allocated to pasture typically decreases, and feed crops compete with food crops for land (Herrero et al., 2007). Also, current price regimes are not conducive to replacing maize with fodder crops in the small-scale intensive systems (Thornton et al., 2003). Therefore in these systems, crop residues are increasingly important for feeding livestock (Reed et al., 1988; de Leeuw, 1997; Romney et al., 2003). Recent research in Africa and Asia has shown that in areas with high population and high livestock density, demand for food and feed resources is higher, but so is biomass production, and demand for livestock feed can be covered while allowing part of the residues to be used as mulch; in low density areas, on the other hand, farmers largely rely on crop residues to feed livestock during the long dry season, implying substantial opportunity costs to their use as mulch (Valbuena et al., 2012). The complexity of these systems makes research difficult. However, some modeling research has been conducted on crop/livestock interaction (Thornton and Herrero, 2001). Models indicate, for example, that with higher-density planting of maize with thinning to use as livestock feed, reduced maize yield would be compensated with higher milk production (Romney et al., 2003). Some models have also evaluated the potential impact of dualpurpose crops (Thornton et al., 2003). Dual purpose or food–feed varieties are crop varieties, usually of cereals or legumes, that combine good grain yields (for food) with good stover yield and quality (for feed). In Nigeria, dual-purpose cowpea varieties developed in the 1990s showed good adoption rates 4 years after their release (Inaizumi et al., 1999). In India, sorghum and millet varieties with higher stover quality have been developed (Blümmel et al., 2003; Thornton et al., 2003). For maize, however, breeding for higher digestibility might not result in net benefits, as compared to millet and sorghum, because of the high breeding cost and relatively low return (Romney et al., 2003; Thornton et al., 2003). Dual-purpose maize varieties with increased fodder quantity without compromising for grain yield would in principle help to offset the increased need for feed in the intensive mixed maizelivestock systems following a decrease in pasture in combination with an increased demand for livestock products. Research was therefore initiated to develop and test dual-purpose maize. From 2004 to 2006, extensive trials In Ethiopia and Tanzania with 335 experimental hybrids showed a positive correlation between yield and stover quantity, while the link between yield and stover quality was weak (Ertiro et al., 2013). Similar trials with in India, conducted during 2009 and 2010, confirmed the positive correlation between yield and stover quantity but did not find a link between yield and stover quality (Zaidi et al., 2013). Concurrent with the experiments on dual-purpose varieties, research was conducted on the potential impact of these varieties. To better target these varieties, areas with high potential have been identified in Eastern Africa using geographic information systems (GIS) tools (Notenbaert et al., 2013). Based on these results, several districts in Ethiopia and Tanzania were selected for participatory research conducted to provide the farmers’ perspective and their interest in dual-purpose maize varieties, and to determine whether these varieties fit their system and preferences. Both qualitative methods (participatory rural appraisals, group discussions and farmer evaluation of varieties) and quantitative methods (household surveys and individual evaluation of varieties) were used. Because the experimental varieties were not yet ready for screening by farmers, only previously released varieties were

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evaluated, for both food and feed quality. These included the most popular varieties in the study areas, and some promising newly released varieties that produce large biomass quantities. This paper presents the results of this study, undertaken to bring the farmers’ perspective into the discussion on the potential of dual-purpose maize varieties. The specific objectives were: (i) to analyze the socioeconomic characteristics and constraints of mixed maize-livestock farmers; (ii) to identify the major attributes of maize varieties that farmers appreciate; (iii) to document farmers’ evaluation of their maize varieties with respect to these attributes, and (iv) to identify factors that influence farmers’ variety and landallocation choices.

2. Methodology 2.1. Overview A farmer’s decision to adopt a new variety is a complex process that takes into account a large number of factors, including socioeconomic and institutional factors (Feder et al., 1985) and, most important for this research, a large number of attributes that farmers appreciate in their crops (Smale et al., 2001; Doss et al., 2003; Edilegnaw and Asmare, 2007; Edmeades, 2007). New varieties need to offer a clear advantage without compromising other traits farmers find important, including field characteristics such as yield and resistance, and also consumer characteristics such as taste and cooking characteristics (Edmeades, 2007). Moreover, they need to fit the farming system, which includes biophysical aspects such as climate and soils, socioeconomic aspects such as education and assets, and also institutional aspects such as extension services, credit and markets (Byerlee et al., 1982; Sunding and Zilberman, 2001). To develop varieties that respond to farmers’ needs and are adapted to their farming system and institutional environment, it is important to include their perspective and evaluation in the process. There are important differences in selection criteria between farmers and scientists, so breeding programs benefit from an understanding of farmers’ own detailed knowledge about the crop varieties they already cultivate, the trade-off between yield and maturity class and other criteria (Haugerud and Collinson, 1990). Farmer participatory approaches include participatory plant breeding (PPB) and participatory varietal selection (PVS), where the latter is faster and more cost-effective if a suitable choice of cultivars exists (Witcombe et al., 1996). In Nepal, for example, acquisition of local knowledge combined with participatory variety selection (PVS) led to farmers selecting and adopting a variety that had previously escaped identification, while through participatory plant breeding (PPB) farmers participated in developing new varieties with specific adaptation to the target area (Tiwari et al., 2009). To address the complexities of farmers’ needs within a farming systems perspective, a set of research methods was used for this study, including maize variety trials with both farmer and breeder evaluation, and qualitative and quantitative methods to elicit farmers’ perspectives and preferences. The varieties tested in the trials consisted of the major improved varieties released, with a few promising newly released varieties added. These varieties were not specifically bred for dual-purpose, but some are commonly used as such. To estimate their potential as dual-purpose varieties, they were evaluated during trials, including on-station and on-farm trials, by breeders on grain yield and biomass, and by farmers based on their criteria, including production, feed, and consumer characteristics. The qualitative methods consisted of participatory rural appraisals, group discussions and group evaluations of varieties at the trials. Quantitative methods included farmer surveys and individual evaluation of varieties by farmers.

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The research in Ethiopia and Tanzania was conducted by different teams, consisting of local partners and students without field offices, and with limited means to communicate with each other or with the lead scientists based in Nairobi. Common principles were agreed at the initial project meetings, both teams first elicited the criteria farmers use to evaluate different maize varieties for the mixed crop–livestock systems; they both used qualitative methods such as PRAs (Chambers, 1994) and group discussions with ranking and scoring (Coe, 2002), combined with quantitative methods such as farmer surveys; and both analyzed the adoption and use of the different varieties, including multinomial logit models (Green, 2008) to analyze adoption patterns. Both teams had sufficient autonomy to fill in the necessary details as they saw fit during the development of the research. This resulted in slightly different methods of data collection and analysis. In Ethiopia, the PRAs were organized in specially selected villages, while in Tanzania they took place around the trials. The PRAs revealed that in Tanzania, unlike Ethiopia, intensive dairy farming is common and farmers purchase feed for that, so this was reflected in the questionnaire. The two countries also have different maize varieties with different characteristics, and maize is used in very different food preparations, which affected the selection criteria, and the need to evaluate the varieties for the different criteria. Finally, the different data sets collected led to slightly different specifications of the models. 2.2. The study areas The study areas were selected purposely to cover areas with high potential impact of dual-purpose varieties, including high production and consumption of maize, and high livestock densities. Such areas were identified using the GIS analysis (Notenbaert et al., 2013) and district level statistics (Urio and Kategile, 1987; CSA, 2001), and were further narrowed down based on accessibility, good contacts with extension officers and availability of research facilities. In Ethiopia, two districts, Ambo and Hawassa, were thus selected based on these criteria, and complemented with Bako, the center of maize research in the country, where maize is very important but livestock less so. Similarly, in Tanzania, the districts of Hai and Moshi rural, in Kilimanjaro region, Northern Tanzania, were purposively selected based on the same criteria. The study areas reflect the wide range of conditions of the maizebased mixed crop–livestock systems found in East Africa. Most of the study areas are located at medium to high altitudes, with medium to high rainfall. In Ethiopia, Bako and Ambo are situated in the western highlands with high rainfall, with Ambo at high and Bako at medium altitude, while Hawassa is located in the southern Rift Valley, with medium altitude and low rainfall. In Tanzania, both districts cover medium to high altitudes (700 to almost 2000 m), with rainfall directly related to altitude. District statistics show that all study districts have a high livestock density except for Bako. The other two districts in Ethiopia have livestock densities between 88 and 90 animals per km2 (Table 1). The human population density follows the same pattern: low in Bako, with only 54 people per km2 , but over 160 people per km2 in the other districts. In Tanzania, Moshi has the highest population, (294 people per km2 ), with the higher areas of Hai district having about half of this density (165 people per km2 ) but the lower areas having a much lower density (70 people per km2 ). The institutional environments of the two study countries have major differences. In Ethiopia the formal maize-seed system is dominated by the government, and most maize varieties are developed and released by national research organizations such as the Ethiopian Institute of Agricultural Research (EIAR) and research centers such as those in Ambo and Bako. Up to now, the only private sector varieties come from Pioneer, a multinational.

The seed of these varieties is produced primarily by parastatals such as the Ethiopian Seed Enterprise, recently joined by regional seed enterprises. Seed and other agricultural inputs are distributed through the agricultural extension system and the farmer cooperatives. Although the Ethiopian seed sector was recently liberalized, few companies have entered the market and seed sales through the private sector are limited (Spielman et al., 2010). In Tanzania, on the other hand, the formal maize-seed system is increasingly dominated by the private sector, and the most popular varieties in the study zone are developed and distributed by the private sector. 2.3. Selection of trial sites Trials were organized to evaluate existing varieties for both food and feed characteristics, using a mother–baby design (Snapp, 2002), with centrally located, researcher-managed “mother” plots, complemented by decentralized, farmer-managed “baby” plots. In Ethiopia, the mother trials were established at the research centers: the Ambo Plant Protection Research Center, the Bako Agricultural Research Center and the Hawasa Agricultural Research Center. For the first two mother trials, two baby trails were also established in nearby villages on farmers’ fields: Bekenisa and Sheboka (near Bako) and Birbirsa and Babich (near Ambo), selected for convenience and good contacts. In Tanzania, three mother trials, on-farm but researchermanaged and -implemented, were established in Kware and Nshara villages in Hai District, and Kivulini village in Moshi rural District, while baby trials were established at 12 farms in Kware, three farms in Nshara and seven farms at Kivulini villages. These 22 farm households were purposively selected for experimentation, based on their willingness to participate, possession of enough land, ability to conduct the trial, and access to irrigation water during the short rainy season. 2.4. Selection of farmers for the variety evaluation, PRAs and the surveys For the evaluation of varieties at the trials, farmers were invited from the surrounding communities. In Ethiopia, farmers were asked to evaluate the varieties during field days, organized in each of the four baby trials. At each trial, between 9 and 26 farmers attended, with a total of 64 farmers, of which 13 women. In Tanzania, both farmer evaluation and PRAs took place around the mother trial sites. Fifty farmers (16–17 for each trial) were invited to participate in the farmers’ field evaluations and PRAs. In Ethiopia, PRAs and surveys took place in the same Peasant Associations (PAs or Kebeles, the lowest administrative units). In each district, four PAs were randomly selected from a sampling frame provided by the respective District Agricultural Offices. In each PA, male and female farmers were first invited for PRAs, and between 8 and 30 maize and livestock farmers attended, with a total of 179 farmers, of which 40 women. Farmer surveys were organized to obtain quantitative information, using a randomized two-stage sampling, with the lowest administrative unit in the first stage and the household in the second stage. In Ethiopia, in the first stage four PAs were randomly selected in each district. A sampling frame was established for the PA by the agricultural extension officers, and 30 households were randomly selected for each of the 12 PAs: 360 households in total. In Tanzania, in each of the two districts two villages were selected purposively by researchers, assisted by extension officers, based on the same criteria as the district selection: availability of water, high livestock and population densities, the importance of maize as food and feed, and easy accessibility by road. A sampling frame of farm households was obtained from the village extension

H. De Groote et al. / Field Crops Research 153 (2013) 22–36

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Table 1 Characteristics of the different study sites (from PRAs, household surveys and secondary data). Description

Ethiopia

Tanzania

Ambo

Bako

Hawasa

Livestock population (density/km2 )a Human population (density/km2 )

90 162

32 54

88 196

Altitude Rainfall (mm) Soil Stover management and utilization

Higher High Mainly black Poor

Middle High Mainly red Medium

Middle Low Mainly sandy Very good

Maize variety

Mainly local

Improved and local

Recycled IVs (BH-540)

Improved and local varieties

Land size owned (ha) Grass land (ha)*** Crop cultivated land (ha)*** Maize area (ha)*** Major crops

2.64 0.5 2.77 1.16 Wheat, teff

2.67 0.4 3.09 0.38 Maize

1.06 0.05 1.03 0.68 Maize, enset

Maize area (% of cultivated)

42

12

66

1.0 0.2 0.5 0.7 Maize, coffee, beans, horticulture 62

***,b

*** a b

Hai

Moshi rural

70 (lowland), 150–160 (midland) 750–1000 (L); 1000–1600 (M) 325–1560

294 762–1929 400–2000 Volcanic soils; good and very fertile soil Improved and local varieties 0.9 0.2 0.3 0.6 Maize, rice, beans, horticulture 44

Significance level at 1%. Source: Wint and Robinson (2007). Source of the second section: farmer survey.

service offices for each village, from which 133 respondents were selected randomly. From the 50 households participating in the mother and baby trials, another 17 households were purposively selected, bringing the total number of households interviewed to 150. 2.5. Trials The objectives of the trials were to evaluate and compare the grain and biomass yield of improved maize varieties in a controlled environment, and to offer an opportunity to farmers to evaluate the varieties next to each other. All these varieties were dual-purpose to some extent, and were tested for grain and stover yield, and evaluated by farmers for these and other criteria. In Ethiopia, trials were established during the main season of 2007. These trials all contained eight improved maize varieties. One more on-station trial was also established at Hawasa Agricultural Research Center, this time with 15 improved maize varieties. The trails at Ambo and Bako included the varieties BH-670, BHQP542, AMH-800, Kuleni, BH-540, Gibe-1, Hora, BH-660 and Tabor (30H83). The trials used a randomized controlled block design with three replications, with plots of 4 rows of 5.1 m (75 cm apart with 30 cm between plants), two seeds per hill and thinned to one plant after establishment, under recommended fertilizer rates and cultural practices. At harvest, the grain yield, grain moisture content, stover yield and resistance to diseases were measured. Farmers were invited to evaluate the varieties at the baby trials in Ambo and Bako. In Tanzania, the mother and baby trials were established at the end of 2007, and harvested in the beginning of 2008. The mother trials included 12 different improved maize varieties: Situka1; Kilima ST; PAN67; SC627; SC 403; Longe 6H; Lishe H1; Lishe H2; Lishe K1; Situka M1; PAN6549, and DK8031. While these varieties were not specifically bred for dual-purpose, some are used as such, and all were evaluated for their quality by farmers. The varieties were tested under two layouts: (i) optimal conditions with 22.5 kg N/ha of diammonium phosphate (DAP) at planting, and top dressed with 57.5 kg N/ha of urea, and (ii) simulated farmer conditions without basal fertilizer but with a top dressing of 57.5 kg N/ha of urea. The baby trials were farmer-managed and located around the mother trials, with researchers providing seed for a subset of four varieties, providing an incomplete block in the alpha lattice design. Due to water shortages and rodent attacks, one farmer dropped out

at Kware, two at Nshara and five at Kivulini villages, leaving a total of 14 baby trials. 2.6. Data collection Data were collected from the trials, the farmer evaluations, the PRAs and the farm surveys. At the trials, yield, biomass and other biophysical data were collected by the breeders and reported elsewhere. At harvest time, farmers were asked to evaluate the varieties during group exercises at the trials. In Ethiopia, the evaluations in the baby trials in Ambo and Bako took place in October and November 2007. Farmers from the surrounding communities were invited and between 9 and 26 farmers per site attended, 64 in total. During a short group discussion, the major criteria were established and farmers evaluated the varieties as a group (they were all illiterate and this was an easier procedure), on a simple four-point scale (poor, average, good, and very good). A similar group procedure was followed in Tanzania, where about 50 farmers participated in the three mother trials. Participants were asked to rank the varieties pair-wise, and the eight top varieties were then scored on the six criteria they had indicated as important, on a five-point scale (very poor, poor, average, good and very good). The evaluation was conducted at harvest time, assisted by research and extension staff. All participating farmers had a long experience in maize and livestock farming, and also in assessing maize technologies, and could be considered experts. In Tanzania, participating farmers had either grown the varieties on their farms or observed them in trials at neighboring farmers’ fields. Qualitative information on farmers’ perceptions of dualpurpose varieties were obtained from participatory rural appraisals, a popular tool for collecting in-depth qualitative information about a group’s perceptions, feelings, attitudes, and experiences on a particular topic (Chambers, 1994). In Ethiopia, twelve PRAs were organized in different locations in October and November 2007, three in each of the districts. In Tanzania, three PRAs took place, one around each mother trial, in February 2008, and in total 50 farmers participated, of which 11 were women. In both countries, the PRAs followed a checklist, including farmers’ selection criteria, preferences for maize varieties, and their perception of the multiple roles of maize in a crop–livestock farming context. The surveys collected data at the individual, household, farm and institutional levels, and included the factors assumed to

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H. De Groote et al. / Field Crops Research 153 (2013) 22–36

Table 2 Constraints in livestock and maize production in Ethiopia, by district and gender, on four-point scale (0 = not important, 1 = somewhat important, 2 = important, 3 = very important). Group

Constraints

By gender

By district

Overall (n = 360)

Male (n = 297)

Female (n = 63)

Ambo (n = 120)

Bako (n = 120)

Hawasa (n = 120)

Maize production

Untimely supply of seeds High price of seed Lack of quality seeds Untimely supply of fertilizer High price of fertilizer

2.2 1.3 1.5 2.1 2.5

1.7** 1.2 0.9** 1.9 2.3**

2.3 1.1 0.7 0.0 2.1

2.5 0.6 0.9 0.1 2.4

1.4*** 2.2*** 2.0*** 2.0 2.8***

2.08 1.26 1.42 2.08 2.48

Livestock production

Livestock feed shortage Lack of livestock medicine Livestock disease

3.2 3.0 1.3

2.4*** 2.7 1.1

4.4 0.4 2.6

3.8 0.6 4.0

1.1*** 2.5*** 2.2***

2.05 1.64 1.60

Source: Farmer survey. * P < 0.05 (for pair-wise t-test). ** P < 0.01 (for pair-wise t-test). *** P < 0.001 (for pair-wise t-test).

influence the adoption of new varieties (Feder et al., 1985; Doss et al., 2003). Individual characteristics included age, experience, education and gender of the household head, while household characteristics included household size and assets, and farm characteristics included livestock and land use for different crops. Institutional factors included access to inputs such as seed and fertilizer, and access to roads, markets, extension, and credit. Farmers were also asked about their maize varieties, in particular which varieties they had planted the previous year, and over what area. In Ethiopia, farmers were also asked in the survey which attributes they valued in maize and the importance of those attributes on a simple four-point scale (not important, of little importance, important, or very important). Further, farmers were asked to score their varieties on these attributes using the same four-point scale as in the group evaluations. 2.7. Analysis The data from farmer evaluations are categorical variables, which theoretically should be best analyzed using ordinal regression (McCullagh, 1980), as has been done before in participatory research (Coe, 2002; De Groote et al., 2010). This is, however, impractical to apply for many varieties and many criteria, as it would involve running and presenting a large number of regressions, of which the coefficients are hard to interpret. Under the assumption that the difference between the values is meaningful, as we can argue here, ordinal categories can be considered as interval categories. In that case, the categories can be converted into numerical values, and comparison of means with pair-wise t-tests was appropriate (Boone and Boone, 2012). We tried both analyses but did not find a substantial difference; hence we present here only the results of the latter. For this analysis the four- and five-point scales were converted to numerical values, both for the importance of criteria (0 = not important, 1 = of little importance, 2 = important, 3 = very important) and for the evaluation of varieties for these criteria (1 = very poor, 2 = poor, 3 = average, 4 = good, and 5 = very good). To analyze the factors that affect a farmer’s choice of varieties, multinomial logit models were used. This model is indicated because of the categorical nature of the dependent variable, and the ease of estimation and interpretation of the coefficients (Greene, 1991). The independent variables included individual, household and institutional variables, based on previous adoption studies (Doss et al., 2003) and variety-specific attributes, determined during the PRAs. In Ethiopia, the different districts grew different varieties, so the dependent variable was the choice between three maize-variety categories: improved varieties only; both improved and local varieties; and local varieties only, with the latter being

the reference category. In Tanzania, where similar varieties were grown in the different districts, the dependent variable consisted of the actual maize varieties grown by the farmers: PAN67, SC627, Lishe H1, PAN6549 and DK8031, with the latter being the reference category. In Ethiopia, the choice models were followed by an analysis of the area in a particular variety. For farmers who do not grow the variety, the value is truncated at zero, so we used the Tobit model, recommended and common in adoption studies (Adesina and Zinnah, 1993), and used before in Ethiopia (Alene et al., 2000). 3. Results 3.1. Land use in the mixed crop–livestock systems in East Africa The results of the household surveys show that maize was the major crop in all the study areas, but in Ambo wheat and teff were also important. The proportion of land area in Ethiopia allocated to maize cultivation was highest in Hawassa (67%) followed by Ambo (42%) and Bako (12%). The area under maize was higher in Hai (62%) than in Moshi (44%). In Ethiopia many farmers still grew local varieties. Farmers in Ambo and Bako grew both improved and local varieties; those in Hawassa grew improved varieties but including recycled hybrids, in particular BH540. Farmers surveyed in the Ethiopian highlands had generally more land than their counterparts in Tanzania. Farmers in Ambo and Bako had the highest average land size (2.7–2.8 ha) while those in Hawassa and Tanzania had comparatively little land (around 1 ha). The area allocated to grazing is generally small in these systems: in Bako and Ambo 0.4 ha on average per farm; in Hawassa 0.1 ha per farm, and in Hai and Moshi 0.2 ha per farm. In Bako and Ambo the average area cultivated is larger than the land owned, implying that farmers rent land for cultivation. 3.2. Livestock and feeding practices in the mixed system During the PRAs, farmers were asked to assess the constraints they were facing, explain their livestock feeding practices and the sources of feed over the seasons. In Ethiopia, farmers were asked to assess the constraints they faced in both livestock and maize production, on a four-point scale from not important to very important (Table 2). In livestock production, feed shortage was the most important constraint, followed by disease. There were some regional differences: diseases are not so important in Ambo, where the cooler highland climate is healthier for livestock, and lack of veterinary medicine was only serious in Hawassa, where the hot lowland climate is less favorable. In maize production, all major constraints concern inputs, in particular maize seed and fertilizer; untimely supply; high prices; and the lack of quality seed. These

3 Banana leaves Enset leaves Sweet potato leaves

Supplementary feed Improved grass pasture

Stover, legumes

Other crop residues

Feed

Source: Participatory rural appraisals (PRAs), in 12 Peasant Associations (Pas), with 79 farmers participating.

August–February December–February December–February December–February December–February

2 4 5 6 3

August–February December–February December–February December–February December–February

2

3 4

All year, limited June–July, limited

4 5

6 Bean stover

Stover, cereals

All year round All year round

December–February

5

May–September

February–June 4

3

September–February 2 September–January 4 2 3 5 6

April–September

All year round

Maize stover Teff stover Wheat stover Barley stover Sorghum stover Rice

2

Rank

1 February–August April–October

1

April–October

1

April–September 1 Natural grass Pasture

Availability Rank

Hawasa

Availability Availability

1

Moshi

Rank Rank

Availability Hai Bako Ambo

Rank

Tanzania Ethiopia Feed type

In the study areas of both countries, maize is a major food crop, although in Ethiopia maize is less dominant than in Tanzania. In Ethiopia, maize is often mixed with teff and other cereals to make the traditional njera: leavened flat pancakes. Because of its high yield and response to fertilizer, maize has now become the major cereal (CSA, 2012), and it is also the cheapest. In the western highlands, farmers also grow many other cereals such as teff, wheat, and barley. In Ambo in particular, wheat and teff are important crops, and maize is mainly grown for consumption as green or fresh maize, usually roasted or boiled on the cob. In Hawassa, however, maize is the major cereal, with the other major crop being enset, the false banana. Since maize stover is generally larger and stronger than wheat or teff straw, its stalks are also intensively used for construction and fuel purposes, particularly in Hawassa. In Tanzania in contrast, maize is by far the dominant cereal countrywide. The only other cereal grown in the study districts is rice in Moshi, but only by a few farmers. The role of maize in the mixed crop–livestock system was assessed during the PRAs: in both

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Group

3.3. Maize in the mixed system

Table 3 Feed sources and availability in Ethiopia and Tanzania (the numbers represent ranks, as perceived by farmers, blanks mean that the feed type was not mentioned).

constraints were much more strongly felt in Hawassa than in the other two districts. In Tanzania, farmers judged that feed shortages, their major constraint, were caused by the transformation of most of the public and private natural grasslands into crop cultivation. Farmers addressed this problem by reducing herd size, feeding crop residues, purchasing feeds and concentrates, and growing forage. The PRAs also revealed that, in all study areas in both countries, the major source of feed is natural grass, followed by crop residues (Table 3). The most important crop residue is maize stover in the various sites, except for Ambo where it was ranked fourth after teff and wheat straw. In the Ethiopian highlands cereal-residue use prevailed, whereas enset (false banana) and sweet potato were used in the Rift Valley. The use of bean residues was only reported in Tanzania, and banana leaves only in Hai. Complementary feed and improved pastures were only important in Hai. The availability of natural grass pasture and other feed resources differed across time and space. In Hai for example, natural grass pasture was available during the months of February to August, whereas in Moshi rural district it was available all year round. Maize stover was only available during the months of April to September in Hai, and from September to February in Moshi. During the household surveys, farmers were also asked about livestock holdings, marketing, and, in Tanzania, about livestock feeding practices and feeding composition (Table 4). Almost all farmers kept livestock, a nearly universal practice in the Ethiopian highlands (Gryseels and Anderson, 1983). The Tanzanian sites differed in livestock feeding; this being more intensive in Hai where two-thirds of farmers practised zero grazing (or 66% of farmers), compared with Moshi where two-thirds of farmers practised extensive grazing systems (66%). One fifth of farmers in both districts practiced both systems. Similarly, three quarters of farmers in Hai purchased livestock feed, with the most common purchases being cotton-seed cake and maize stover. The proportion of farmers who sold maize grain was higher in Hai (78% of farmers) than in Moshi (58%), with infrequent sales of maize stover in both sites. More farmers sold milk in Hai (65%) than in Moshi (42%). While the questions were not specifically asked in the survey, discussions with farmers in Ethiopia and observations in fields and homesteads revealed that farmers do not practice zero grazing or intensive dairy production. Consequently, farmers rarely purchase animal feed. Many farmers do sell maize grain, in particular in Bako (88%) but less in Ambo (33%), but no maize stover sales were reported. Fewer farmers sell livestock: a quarter in Ambo and a third in Bako.

Availability

H. De Groote et al. / Field Crops Research 153 (2013) 22–36

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H. De Groote et al. / Field Crops Research 153 (2013) 22–36

Table 4 Livestock ownership, feeding practices and feed sources, and marketing practices (in % of farmers). Group

Variables

Livestock owners

Ethiopia

Tanzania

Ambo (N = 120)

Bako (N = 120)

Hawassa (N = 120)

Hai (N = 104)

Moshi (N = 46)

97

98

98

99

96

Livestock feeding management

Zero grazing only Extensive grazing only Both zero and extensive grazing

58 12 17

9 41 13

Feed purchased

Any feed Cotton seed cake Maize stover Maize bran Wheat bran Sunflower cake Stover and grass

65 0 10 9 17 14 12

13 0 0 0 0 2 9

Marketing (% farmers who sell)

Maize Maize stover Cattle Sheep and goats Milk

3 79 18 52 42

2 57 13 37 30

33 0 26 7 0

88 0 35 13 0

72 51 22

Source: Farmer surveys.

districts, grain for food was the most important use of maize. In Hai, grain sales were the second most important use, while in Moshi they were third. Maize for feed was ranked second in Moshi and third in Hai, although this use was mostly as dry stover, or green leaves chopped after the cobs have formed or during thinning. Some maize grain is used for poultry, and maize bran is also used for feed. Other minor uses were maize spindles (leftover cobs) for fuel, crop residues for organic matter for soil, and grain for local brew. In Ethiopia, the difference in climate led to major differences in the adoption of different varieties between the districts (Table 5). Ambo has the longest growing season, so the popular varieties here are late maturing, while in Bako both medium and late varieties are grown, and in Hawassa, which is a dryer area, only mediummaturing varieties are grown. Overall, the most popular variety is the late-maturing hybrid BH660 (BH stands for Bako hybrid, after the research station where it was developed). In Bako, BH660 is grown by 82% of farmers and in Ambo by 36%, but it is not suited to Hawassa. The second most popular variety is BH540, a mediummaturing hybrid that is especially popular in Hawassa (grown by 70% of farmers), and fairly popular in Bako (14%). Local varieties are also still popular, especially Oromia in Ambo (71%) and Burre in Bako (44%), but not in Hawassa, where none of the farmers grew them. The third most popular hybrid is Tabor, grown mostly in Hawassa (by 31% of the farmers) and by a few farmers in Bako (5%). A more recent release for Ambo, the very late-maturing AMH800, (AMH stands for Ambo hybrid), is only found in Ambo, but is not widely used (by only 5% of farmers). Except for one Pioneer variety, all the improved varieties were developed by the public sector. Eight of the Ethiopian varieties, the old improved ones, and three new varieties (Gibe-1, BH670, and Hora) were tested in the on-station and on-farm trials for yield, biomass and other characteristics. The results indicate that BH-660 is the best dual-purpose variety, with a biomass production of 12.6 tons per ha on-station, and 9.9 t/ha on-farm. While the other old, improved varieties provided good biomass on-station, they did not do so well on-farm, except for Kuleni, which is a medium-maturity OPV with lower yield potential. In Tanzania, in contrast to Ethiopia, the four most popular varieties (grown by at least 10% of farmers), were all hybrids from private companies, and farmers from both districts grew similar varieties (Table 6). The top variety, DK8031, is an earlymaturing variety from a multinational, (Monsanto), with good tolerance to insect pests and diseases. Other popular varieties came from regional companies, in particular Pan67 and Pan6549,

medium-maturity varieties from the South African company Pannar, and SC627, also a medium-maturity variety but from SeedCo, a company from Zimbabwe. The national programs have mostly developed OPVs, and their most popular variety, Kilima ST, an early variety, was only ranked fifth and was only popular in Moshi (ST stands for streak-virus resistance). Another popular early variety was SC403, from SeedCo. Four more varieties from Tanzanian public research institutes were grown, but each one by less than 10% of the farmers in the survey. In Tanzania, the trials also provided good indicators of the biomass production of these varieties, ranging from 3.4 to 5.4 tons/ha, substantially lower than in the Ethiopian trials (Table 6). The variety with the highest biomass was SC627 (5.5 tons/ha), which can be considered a dual-purpose variety, and is the third most popular variety. The other varieties among the five most popular all have a biomass in the same medium range, between 3.5 and 3.6 tons/ha. Only one other variety, LisheH1, had a biomass of over 4 tons/ha, and only one variety, SC403, had a biomass of less than 3 tons/ha during the trials. 3.4. Maize attributes valued by farmers Farmers were asked about the attributes they appreciate in maize varieties during group discussions at the trials, as well as during the farmer surveys. In Ethiopia, during the trials, farmers mentioned mostly field characteristics and some biomass characteristics, but no cooking or taste characteristics, probably because of the trial and evaluation setting. The field characteristics included yield and related characteristics (ear filling, cob size and ears per plant), resistance (to wind, diseases and weevils), and others (husk cover, early maturity and plant height). Feed characteristics included biomass, soft stalks, and wetness of leaves and stalks. Because of time constraints, neither the importance of the attribute was assessed at the trials, nor the difference between groups of farmers or districts, but this was done during the survey. During the survey the farmers in Ethiopia mentioned three categories of maize attributes as important: field characteristics, food, and feed, in that order (Table 7). Yield is clearly the most important characteristic, receiving a score of 2.9 (on a scale of 0 = not important, to 3 = very important) in all districts and for both genders. Taste, in particular for green maize and for common dishes, is the second most important attribute, with a score of 2.7, but with differences by gender and region. After taste, farmers mentioned field attributes other than yield, in particular early maturity, cob size,

Table 5 Adoption of improved maize varieties and their characteristics in Ethiopia. Characteristicsb

Farmers adopting (%)a

Variety

Ambo (N = 120)

82 14 0 44 5 0 0 1 1 0 0 0

36 3 71 0 0 5 2 0 0 0 0 0

1 70 0 0 31 0 1 1 0 0 0 0

Only IMV Only local Both IMV and local

55 38 7

28 16 56

100 0 0

a b c d e f

Hawassa (N = 120)

Year of release

Yield (tons)

Variety Type

Maturity (days)

Source

On station

1993 1995

9–12 8–9

Hybrid Hybrid Local OPV Local OPV Hybrid Hybrid Improved OPVe Hybrid Hybrid OPV Hybrid OPV

160 145

Public (Bako) Public (Bako) Local Local Public Public (Ambo) EIAR/CIMMYT Public (Bako) Private Public Public Public/CIMMYT

12.6 8.1

9.9 5.4

9.6 9.0 9.3

5.4 8.6 4.4

7.9 8.7 6.1

10.3 11.4 8.0

2001 2005 1995 2002

7–8 6–7 8–9 8–10 6–7 9–12 6–7

2000 2002 2005

175 150 145 145 165 170

Grain yieldd (t/ha)

On-farm 2.2 2.4 1.4 1.5 2.9 1.4

Source: Household surveys. Source: Ethiopian variety release committee. EIAR/CIMMYT breeders. Farmer survey. Open pollinated variety. Quality protein maize.

Table 6 Adoption of improved maize varieties and their characteristics in Tanzania. Variables

DK8031 Pan 67 SC627 Pan 6549 Kilima ST SC403 Lishe H1 Situka1 Lishe K1 Lishe H2 Longe 6H a b c d e

Adoption (% of farmers)a

Characteristicsb

Trial resultsc

Hai

Moshi

Total

Year of release

Yield (ton/ha)

Type

Maturity (Days)

Texture

Source

Company

Biomass yield (t/ha)

Grain yields (t/ha)

28 18 12 10 4 12 7 3 6 1 11

38 19 14 11 14 3 0 3 0 0 3

33 18 13 10 9 7 3 3 3 1 7

2002 2000 2001 1995 1994 2003 2001 2001 2001 2001 2004

5–8 7 5–10 7.5 4.30 1–6 4–7 4–5 4–6 4–7 9.0–10.1

Hybrid Hybrid Hybrid Hybrid OPVd Hybrid Hybrid OPV OPV Hybrid Hybrid

124–130 135–165 130–140 150–170 100 120.00 130–160 130–150 120–140 130–160 140.00

Dent Dent Flint Semi Flint Dent Semi Flint Hard dent Semi Flint Semi Flint

Multinational Regional Regional Regional Public Regional Public Public Public Public Public

Monsanto Panar (South Africa) Seed Co (Zimbabwe) Panar (South Africa) NMRPe Seed Co (Zimbabwe) ARIe Selian ARI Selian ARI Selian ARI Selian NAROe /CIMMYT

3.78 3.73 5.53 3.47 3.79 2.88 4.27 3.27 2.88 3.44 3.73

4.87 5.92 6.51 5.45 5.92 6.11 5.98 5.29 4.58 5.29 6.11

H. De Groote et al. / Field Crops Research 153 (2013) 22–36

Bako (N = 120) BH660 BH540 Oromia Burre Tabor AMH800 Kuleni BHQP542f Pioneer Gibe-1 BH670 Hora (AMB01Syn1)

Stover yieldc (ton/ha)

Source: Household surveys. Source: Ethiopian variety release committee. EIARO/CIMMYT breeders. OPV = Open pollinated variety. NMRP = National Maize Research Program, ARI = Agricultural Research Institute, NARO = National Agricultural Research Organization (Uganda).

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Table 7 Importance of maize attributes by gender and district in Ethiopia (numbers are average farmer responses on a scale of 0 = not important, 1 = of minor importance, 2 = important, 3 = very important). Category

Attributes

Gender

Study area

Overall (n = 360)

Male (n = 297)

Female (n = 63)

Ambo (n = 120)

Bako (n = 120)

Hawasa (n = 120)

Field

Yield by volume Early maturity Cob size Grain size Grain weight Ear filling Plant height Husk cover Drought tolerance Disease tolerance

2.9 2.6 2.6 2.5 2.5 2.5 2.3 2.3 2.3 2.3

2.9 2.7 2.6 2.6 2.4 2.4 2.5** 2.4 2.5* 2.3

2.9 2.8 2.7 2.5 2.5 2.5 2.4 2.3 2.3 2.3

2.9 2.5 2.5 2.5 2.5 2.4 2.3 2.5 2.3 2.1

2.9 2.6*** 2.5** 2.6 2.5 2.4 2.5** 2.3 2.4 2.5**

2.9 2.6 2.6 2.6 2.5 2.5 2.4 2.3 2.3 2.3

Consumer

Taste of green maize (ishet) Taste of main dishes Market demand Weevil resistance Flour compatibility Nutritional quality Digestibility Local beer (ferso)

2.7 2.7 2.4 2.3 2.4 2.2 2.1 1.8

2.9** 2.9*** 2.5 2.5 2.5 2.4* 2.4*** 2.1*

2.7 2.7 2.5 2.3 2.5 2.0 1.9 2.2

2.8 2.7 2.5 2.3 2.5 2.1 1.9 2.3

2.6*** 2.8 2.4 2.5* 2.4 2.7*** 2.5*** 1.0***

2.7 2.7 2.5 2.4 2.4 2.3 2.1 1.8

Feed

Stover biomass Sweet stalk Wet stalk Green/healthy leaf Thin stalk

2.4 2.4 2.4 2.3 2.1

2.5 2.4 2.3 2.3 2.2

2.5 2.4 2.4 2.3 2.1

2.4 2.3 2.3 2.3 2.0

2.5* 2.5* 2.4 2.3 2.2

2.4 2.4 2.4 2.3 2.1

Source: Farmer survey. * P < 0.05 (for pair-wise t-test). ** P < 0.01 (for pair-wise t-test). *** P < 0.001 (for pair-wise t-test). Table 8 Farmer evaluation of maize varieties at the trials in Ambo and Bako (two sites each, one farmer group per site, on a five-point scale: 1 = very poor, 2 = poor, 3 = average, 4 = good, and 5 = very good). Group

Subgroup

Yield and related

Field characteristics

Resistance

Other

Attributes

BH660

BH670

Gibe-1

BHQP542

Kuleni

BH540

AMH800

Hora

Yield Ear filling Cob size Ear per plant Subtotal Wind resistance Disease tolerant Weevil resistance Subtotal Husk cover Early maturity Plant height Subtotal

5.0 5.0 5.0 4.8 4.9 2.5 4.3 4.3 4.5 5.0 4.0 3.0 4.3 4.3

5.0 4.5 4.8 5.0 4.8 2.3 4.3 4.3 4.4 5.0 4.0 3.0 4.3 4.2

4.0 3.8 4.0 3.8 3.9 4.3 3.5 3.3 3.8 4.5 5.0 5.0 4.1 4.1

4.0 4.3 3.5 3.8 3.9 4.0 3.3 3.3 3.7 4.3 5.0 4.5 3.9 4.0

3.3 3.0 3.3 3.3 3.2 3.8 3.9 3.5 3.4 4.3 5.0 5.0 3.7 3.8

4.0 4.3 4.0 4.0 4.1 4.0 2.8 2.3 3.7 4.0 5.0 4.0 3.8 3.8

3.5 4.3 3.5 3.5 3.7 4.3 3.3 2.8 3.6 4.0 4.0 5.0 3.8 3.8

2.0 2.3 3.0 2.5 2.4 4.3 3.3 3.0 2.8 4.3 4.0 4.5 3.2 3.3

Stover biomass Soft stalk Wet leaf/stalk

5.0 4.0 4.5 4.5

5.0 3.8 4.0 4.3

4.0 4.0 4.3 4.1

4.0 4.3 4.8 4.3

4.8 4.0 4.0 4.3

3.3 3.8 4.5 3.8

4.0 4.0 3.5 3.8

3.3 3.5 3.5 3.4

4.5

4.3

3.9

4.1

3.9

3.8

3.8

3.3

Total

Biomass Total Grand total Source: Farmer evaluation during trials.

grain size, grain weight and good ear filling, all of which received scores of 2.5 to 2.6. Other consumer characteristics are market demand and flour compatibility. The next most important group of attributes consists of characteristics related to animal feeding, especially characteristics such as stover biomass and sweetness and wetness of the stalk, which all received a score of 2.4. For field and feed characteristics, there were few differences between men and women or between zones in importance attributed to these, but for consumer characteristics there were major differences. Early maturity and cob size are more appreciated in Ambo, and women find plant height and drought tolerance somewhat more important. In feeding attributes, there were no differences

by gender, and only slight differences by zone. For consumer characteristics, women placed higher importance on food attributes than men, especially on taste, nutritional quality and the making of local beer. In Ethiopia women are responsible for preparing food and local brews, which might help to explain this difference. There were also major differences in importance of consumer characteristics between zones. Suitability for green maize and quality of local beer are considered more important in Bako, while beer quality is less important in Hawassa area, where most households belong to a protestant religious group that disapproves of alcohol consumption. In Hawassa, on the other hand, nutritional quality is highly appreciated.

Table 9 Farmers’ evaluation of their maize varieties for the major attributes, during surveys in Ethiopia (individual scores, with 1 = very poor, 2 = poor, 3 = average, 4 = good, 5 = very good). Attributes

Ambo

Bako

Hawasa

BH540 (n = 4) Medium hybrid

AMH800 (n = 6) Late hybrid

Orome (n = 85) Local

BH660 (98) Late hybrid

BH540 (n = 17) Medium hybrid

Tabor (n = 6) Medium hybrid

Burre (n = 53) Local

BH540 (n = 85) Medium hybrid

Tabor (n = 38) Medium hybrid

Yield Early maturity Cob size Grain size Grain weight Husk cover Drought tolerance Disease tolerance

5.0 3.6 4.9 4.6 4.3 4.5 3.6 3.8

3.8 4.8 4.0 4.0 4.0 3.0 3.8 4.3

4.1 3.6 3.9 4.1 3.4 3.4 3.3 3.7

2.7*** 4.8*** 3.1*** 3.3*** 4.0 3.6*** 3.6 3.6

4.6 3.3 4.3 4.2 4.1 4.3 4.3 3.4

3.8 4.5 3.6 4.1 3.3 3.5 3.8 3.2

3.7 4.1 3.1 3.0 3.4 3.3 3.3 2.9

2.9*** 3.0*** 3.7*** 3.8*** 4.5*** 3.9*** 3.7* 3.5

3.8 4.3 4.0 4.3 3.9 3.7 3.4 3.3

4.8*** 4.5*** 4.5** 4.4 4.1 3.8 4.5*** 4.4***

Field

4.3

3.9

3.7

3.6

4.1

3.7

3.4

3.6

3.8

4.4

Green maize Food Market price Weevil resistance

4.1 4.8 4.4 3.5

4.3 4.5 4.8 4.0

4.0 4.7 4.4 3.6

4.7*** 3.6*** 3.4*** 3.4

4.4 4.4 4.3 3.5

3.9 4.1 4.1 2.9

3.1 3.1 3.4 2.6

4.6*** 3.9*** 4.0** 3.9***

4.3 4.4 3.9 3.3

4.2 4.7* 4.2 3.5

Consumer

4.2

4.4

4.2

3.8

4.2

3.8

3.1

4.1

4.0

4.1

***

Stover biomass Sweet stalk Wet stalk

4.7 4.3 4.4

4.0 3.0 4.3

4.3 3.9 3.1

3.7 4.5** 4.1**

4.2 4.1 4.2

3.8 3.8 3.6

3.7 3.4 3.3

4.2 4.5*** 4.2*

4.0 3.9 3.7

4.6*** 4.6*** 4.5***

Feed

4.5

3.8

3.8

4.1

4.2

3.7

3.5

4.3

3.8

4.6

Average score

4.3

4.0

3.8

3.7

4.1

3.7

3.3

3.9

3.9

4.3

H. De Groote et al. / Field Crops Research 153 (2013) 22–36

BH660 (n = 43) Late hybrid

Source: Farmer survey. * P < 0.05 (for pair-wise t-test). ** P < 0.01 (for pair-wise t-test). *** P < 0.001 (for pair-wise t-test).

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Table 10 Farmers’ evaluation of maize varieties on key attributes, at trials in Tanzania, (1 = very poor, 2 = poor, 3 = average, 4 = good, 5 = very good). Variety

Lishe H1 SC 627 SC 403 Longe 6H Lishe K1 Situka 1 Situka M1 PAN 67 Kilima ST Lishe H2 DK 8031

Field

Consumer

Feed

Yield

Drought tolerance

Early maturity

Disease

Average

Milling quality

Market

Average

Biomass

5.0 5.0 4.0 5.0 3.5 3.0 4.0 4.0 5.0 4.0 3.7

5.0 4.0 5.0 4.3 4.5 5.0 4.0 4.5 3.0 4.0 4.7

5.0 4.0 5.0 4.3 5.0 5.0 4.0 4.5 5.0 4.3 3.7

5.0 5.0 5.0 4.7 4.5 5.0 5.0 4.0 4.0 4.7 3.7

5.0 4.3 4.7 4.5 4.3 4.3 4.0 4.3 4.3 4.1 4.0

5.0 5.0 5.0 5.0 5.0 5.0 5.0 4.5 5.0 4.0 3.0

5.0 5.0 4.0 4.7 4.5 4.0 5.0 4.0 4.0 4.0 3.3

5.0 5.0 4.5 4.9 4.8 4.5 5.0 4.3 4.5 4.0 3.2

5.0 5.0 5.0 4.0 3.5 3.0 3.0 4.0 3.0 4.0 3.0

Overall

5.0 4.7 4.7 4.6 4.4 4.3 4.3 4.2 4.1 4.1 3.6

Source: Farmer evaluation during trials.

In Tanzania, farmers were also asked about the maize-variety attributes during the farmer evaluations at the trials, and they recognized three categories of attributes: field, consumer and feed characteristics. Field characteristics included yield, resistance to disease, early maturity and drought resistance. Consumer characteristics including milling quality and marketability, while only one feed characteristics, biomass, was mentioned. 3.5. Farmer evaluation of maize varieties In Ethiopia, farmers evaluated the varieties in the trials as well as in the household survey. During the trials, farmers were invited at four sites (two in Ambo and two in Bako) and asked to score, in group, the eight varieties in the trials for the characteristics they had mentioned (Table 8). The results show that the latematuring varieties from the 600 series (such as BH660 and BH670) were more appreciated for yield and related characteristics. The medium-maturing varieties from the 500 series (such as BHQP542 and BH540) were more appreciated for early maturity, but did not do as well for yield-related characteristics and resistance as the 600 series. The extra-late varieties such as AMH800 and Hora (an OPV) were not well appreciated in these trials. Appreciation for biomass is very similar to appreciation for yield, with the 600 series and Kuleni scoring better than the 500 series, indicating that good biomass and grain yield can be combined. Three varieties scored high for wet leaves and stalks: BHQP542, BH660 and BH540. In Ethiopia, farmers were also asked during the survey to evaluate their most important varieties for all their most important attributes (Table 9). In Ethiopia these varieties included the medium-maturing BH540 in all three districts, the late-maturing hybrids BH660 and AMH800 in the highlands in Ambo and Bako, and local varieties Orome in Ambo. Overall, BH660 scored best in Ambo as well as in Bako. In Ambo, BH540 came second, but in Bako the local variety Burre came in second place, followed by BH540. BH660 scored best in yield and in all field characteristics. BH540, as expected, scored well for early maturity, but not as well for yield, which is negatively related to early maturity; neither did it score as well for other field characteristics. In Bako and Ambo, the other varieties did not do as well as these top hybrids for field characteristics. In Hawassa, however, Tabor did much better for yield and other field characteristics, including early maturity In consumer characteristics, large differences were found between districts and varieties. In Bako, BH660 and Burre are generally more appreciated, and Tabor clearly less so. But in Ambo, BH540 is more appreciated. Local varieties are especially appreciated for their taste for green maize, in particular Burre in Bako and Orome in Ambo. In Hawassa, however, there was little difference in consumer characteristics between the two varieties evaluated. For feed characteristics, the late-maturing BH660 is more appreciated

than the early-maturing BH540 in the highlands for biomass, but also for other feed characteristics. Local Burre is also appreciated for its feed quality in Bako, coming second after BH660. In Hawassa, Tabor is much more appreciated for feed qualities than BH540. In Tanzania farmers evaluated the varieties in group at the trials. The varieties that scored best were Lishe H1, SC 403, SC 627, and Longe 6H (Table 10). Apart from Lishe H1, these were all imported varieties; Lishe H1 is late maturing, and does well on all characteristics. SC 403 is early maturing and does not do well for yield, but does well for field and other characteristics. The most widely adopted variety, DK8031, received low scores at the trial, somewhat surprising given its popularity, but this is likely related to its low grain yield results at the trial. Farmers also commented that it sheds leaves quickly at harvest, making it not suitable for feed. The varieties most appreciated for biomass criteria were Lishe H1, and the SeedCo varieties SC 627 and SC403. Apart from the last variety, this corresponded well with the biomass measurement at the trial. Other varieties appreciated for biomass were Longe 6H, Lishe H2 and PAN67, varieties that also did reasonably well in measured biomass at the trials. 3.6. Factors influencing variety choice To analyze the factors that influence adoption of different varieties, choice models were estimated, in particular multinomial regression models. In Ethiopia, the choices were defined as growing only improved varieties, growing both improved and local varieties, or growing only local varieties, the base category in the regression, (Table 11). The results show that a farmer’s likelihood of growing improved varieties increases with age, but reduces with experience. Probably, when farmers are more experienced, they stick to the varieties they know. The probability of growing improved varieties, or both improved and local, also increases with the land area of the farm, a wealth indicator, and decreases with distance to the road, which increases transaction costs. The importance of some attributes also affected the choice of maize varieties. Farmers who found attributes for green maize important in their choice of variety were less likely to grow improved varieties, indicating the quality of local varieties for green maize. On the other hand, farmers who found food quality for traditional dishes an important attribute were more likely to grow improved varieties or both, indicating that improved varieties are not necessarily worse in quality. Factors that increase the probability of growing both improved and local varieties, as compared to only local, are availability of fertilizer, access to credit and access to extension services, indicating the importance of rural services to improve farmers’ access to new technologies. Next, choices were defined as growing high biomass varieties, growing both high and low biomass varieties, or growing only

H. De Groote et al. / Field Crops Research 153 (2013) 22–36

33

Table 11 Factors driving the choice of maize varieties in Ethiopia (multinomial logit model). By improved or local variety type

By high or low biomass variety type

Improved

Local and improved

High biomass

Coef.

Coef.

Coef. Bako Hawassa

4.149

Std. err.

Std. err.

High and low biomass Std. err.

Coef.

Std. err.

0.65***

4.35

0.69***

4.00 0.80

0.59*** 0.74

4.30 −5.21

0.66*** 1.53***

Gender (1 = male, 0 = female) Education (1 = has formal educ; 0 = otherwise) Maize farming experience (years) Age of the respondent (years)

−0.95 0.06 −0.12 0.08

0.73 0.65 0.03*** 0.03***

−0.29 −0.09 −0.09 0.05

0.73 0.67 0.04*** 0.03

0.09 0.12 −0.08 0.04

0.61 0.55 0.03*** 0.02

0.35 0.10 −0.08 0.04

0.71 0.63 0.03** 0.03

Family size Household livestock holding (TLU) Crop land (ha) Off-farm income (10,000 ETB)

−0.10 0.09 0.77 1.71

0.08 0.06 0.21*** 2.45

−0.06 0.09 0.60 3.29

0.09 0.06 0.23*** 2.44

0.01 −0.01 0.49 −0.26

0.08 0.05 0.17*** 1.38

0.02 0.03 0.42 3.40

0.09 0.05 0.19** 1.76**

Fertilizer availability (1 = yes, 0 = no) Seed available (1 = yes, 0 = no) Credit available (1 = yes, 0 = no) Distance to road (h)

0.43 0.01 0.15 −0.68

0.52 0.52 0.49 0.28**

−2.21 0.07 1.06 −0.37

0.71*** 0.67 0.56** 0.29

0.27 0.57 0.63 −0.12

0.48 0.49 0.47 0.26

−1.18 0.11 1.19 0.07

0.62* 0.64 0.54** 0.29

Suitability for making traditional dishes Suitability in making ishet Suitability of biomass Sweetness of stalk Yield rating Market price rating

1.10 −0.31 −0.13 0.04 1.58 0.19

0.45*** 0.53 0.45 0.43 0.85* 0.35

1.03 −1.16 0.60 −0.17 0.97 −0.08

0.47** 0.53** 0.51 0.45 0.81 0.40

0.61 −0.36 0.46 0.08 0.91 0.01

0.40 0.46 0.40 0.38 0.70 0.31

1.18 −0.71 0.77 0.11 0.83 −0.32

0.50** 0.53 0.49 0.43 0.84 0.38

0.70 −12.70

0.98 4.04***

2.70 −7.68

0.98*** 3.94**

0.18 −9.03

0.68 3.32***

Access to extension (1 = yes; 0 = no) Constant Observations LR chi2 (42) Prob > chi2 Log likelihood

240 180.3 0.000 −171

2.77 −10.80

0.80*** 3.98***

273 186.8 0.000 −201.4

TLU = Tropical livestock units, ETB = Ethiopian Birr. * P < 0.05. ** P < 0.01. *** P < 0.001. Table 12 Determinants of area allocation to maize varieties in Ethiopia (Tobit model, dependent variable is area in specific variety). BH660 (ha) Coef.

Burre (ha) Std. err.

Coef.

Std. err.

Coef.

Std. err.

0.13 0.10*** 0.00 0.01

0.31 0.05 0.02 −0.02

0.16* 0.12 0.01** 0.02**

−0.11 −0.04 0.00 0.00

0.07 0.07 0.00 0.01

0.02 0.02 0.13 −0.02 0.08 0.02 0.05

0.01 0.01*** 0.12 0.12 0.08 0.04 0.03*

0.03 0.06 −0.21 −0.25 0.10 −0.03 −0.02

0.01* 0.01*** 0.13 0.16 0.10 0.04 0.05

0.00 0.00 −0.05 0.00 0.03 −0.08 0.04

0.00 0.00 0.05 0.05 0.04 0.05 0.02**

−0.08 0.00 −0.03 −0.02 −0.05 0.10 −0.41

0.07 0.07 0.07 0.05 0.05 0.06* 0.26

0.01 0.00 −0.04 −0.31 0.18 0.19 0.06

0.06 0.14 0.07 0.10*** 0.07*** 0.07*** 0.51

−0.01 −0.02 −0.01 −0.06 0.03 0.00 0.40

0.03 0.06 0.03 0.04* 0.03 0.03 0.16**

0.02

0.26 55 58.84 0.00 −8.03 0.79

0.03

0.17 85 15.67 0.55 28.11 −0.39

Study area (a)

Bako Hawassa

0.59 0.29

0.11*** 0.42

Respondent

Gender (1 = male, 0 = female) Education (1 = Has formal educ; 0 = otherwise) Maize farming experience (year) Age (years)

0.16 0.26 0.00 0.01

Household

Family size Household livestock holding (TLU) Fertilizer availability (1 = available) Seed availability (1 = available) Credit availability (1 = available) Walking time to road (h) Crop land (ha)

Importance of attributes (1 = very important, 0 = otherwise)

Suitability for making traditional dishes Suitability in making ishet Suitability of biomass Sweetness of stalk Yield rating Market price rating Constant Sigma Number of obs LR chi2 (18) Prob > chi2 Log likelihood Pseudo R2

* ** ***

P < 0.05. P < 0.01. P < 0.001.

Orome (ha)

0.39 132 82.77 0.00 −63.63 0.39

34

H. De Groote et al. / Field Crops Research 153 (2013) 22–36

Table 13 Farmers’ choice of varieties in Tanzania, using multinomial logit regression (dependent variable is the choice among five varieties, with DK8031 as the reference choice category). Variablesa

PAN 67

SC 627

PAN6549

LISHE H1

Coefficient

St. err.

Coefficient

St. err.

Coefficient

St. err.

Coefficient

St. err.

Gender (1 = male, 0 = female) Age (years) Education (years) Sells maize (1 = yes; 0 = no) Family size Household livestock holding (TLU) Constant

0.033 0.002 21.108 −1.412 0.647 −0.290 −20.700

0.862 0.002 1.210* 0.870 0.330** 0.150**

−22.00 −0.06 2.11 1.11 −0.03 −0.02 −0.12

0.80 0.04 1.30 1.11 0.36 0.10 2.15

−0.76 −0.01 21.2 −0.99 0.67 −0.09 −20.98

0.85 0.037 1.8* 0.96 0.35** 0.11

−0.41 −0.01 1.12 20.50 0.32 0.07 20.98

1.10 0.02 1.40 2.23* 0.40 0.15

Number of observations Log likelihood Chi-square value Chi-square probability Pseudo R2

76 −96.017 39.89 0.022 0.172

Source: Farmer survey. a Dependent variable is the choice among five varieties expressed as binary variables, with DK8031 as the reference or omitted category, coefficients are estimated using the multinomial logit regression model, and are interpreted as the change in probability of adopting the specific variety in function of the explanatory variable. * P < 0.05. ** P < 0.01. ***P < 0.001.

low biomass varieties, with the last choice as the base category in the regression. The regression results show that high biomass varieties are more popular in Bako, but less popular with more experienced farmers. The probability that farmers grow both high and low biomass varieties also increases with access to fertilizer and credit, but this might just be an indication that these factors increase the opportunities for farmers. The factors that affect the area allocated to different maize varieties was analyzed using a Tobit model, for the major varieties BH660, Orome and Burre (Table 12). The area allocated to BH660 increased with education, livestock ownership and finding marketing characteristics important. The significance of livestock might be attributed to the high appreciation of its stover quality, although this variable is also strongly related to wealth and can therefore also indicate that wealthier farmers may be less averse to taking risk, and are therefore more likely to buy seed of BH660 instead of using local varieties, which are cheaper. The regressions on individual variety also allow the inclusion of farmers’ evaluation of these varieties. The fact that farmers who appreciated the marketability of BH660, for example, planted a larger area with that variety, indicates that its grain is well known and marketable. The factors affecting the use of local varieties were similarly analyzed with a Tobit model, but only in their specific areas: the variety Burre in Ambo and the variety Orome in Bako. The acreage planted in Burre was higher in female-headed households, and increased with experience and livestock, but decreased with age. The area also increased with farmers’ appreciation of the different attributes of the variety, in particular yield and marketability. Similarly, the area planted in Orome decreased with the importance of palatability, indicating a less satisfactory performance of the variety for this characteristic. In the case of Tanzania, a multinomial regression was used to analyze the factors affecting the choice of maize varieties (Table 13). The variety DK 8031 was used as reference choice category for the analysis, and other choices included the other improved varieties PAN 67, SC 627, PAN6549, and Lishe H1. The fitted model explains reasonably well the variation in observed farmers’ choices of particular maize varieties. Several factors were found to affect the choice of variety, although the link with the evaluation of those varieties for different attributes is not very clear. Education has a positive effect on farmers’ choice of PAN67 and PAN 6549. Farmers with a greater number of livestock were more likely to choose DK8031 over PAN67. Increase in farm size increased the probability of a

farmer choosing PAN67 and PAN6549 over DK8031. Farmers who participated in the market were more likely to choose LISHE H1 over DK8031; this choice is probably related to this variety’s higher score for marketability. 4. Conclusion The results of our study confirm that, in the study areas of both countries, the dominating farming systems are maize-based mixed crop–livestock systems. Farmers generally grow improved maize varieties, but in the Ethiopian sites, local varieties are also common. The major use of maize is for food, as grain or as green maize, and little maize grain is used for feed. Stover is, however, a major source of feed in all regions, after natural pasture. The lack of available feed sources is a major constraint in all areas, as has been reported elsewhere for Ethiopia (Tschopp et al., 2010) and Tanzania (Mdoe and Wiggins, 1997). There are, however, major differences between the countries. In Ethiopia, the three districts have distinct agro-ecologies, which affect the choice of crops and varieties and the availability of feed (Kebede et al., 1993). In Tanzania, the two districts are similar in climate, but both districts range from medium to high altitude. We observe a substantial difference in intensification of the maizelivestock systems between the countries. In the Ethiopian study areas, farmers have adopted improved maize varieties, but still grow local landraces, while in the Tanzanian districts farmers only grow improved maize varieties. Furthermore, in Ethiopia, farmers do not purchase feed for their animals, while this is common in Tanzania, especially for dairy farming, leading to the practice of zero grazing and the purchase of feed supplements, a trend that has been observed before (Mdoe and Wiggins, 1997). The choice of maize varieties is complex and many factors were found to play a role. In all study areas, farmers appreciate a wide range of variety attributes, in three main categories: field (including yield), consumer, and feed characteristics, usually in that order. In both countries, field characteristics were the most important attributes, although yield was less important in Tanzania, an outcome probably affected by the methodology. The second most important group of attributes was consumer characteristics, especially taste in Ethiopia (for traditional food and as green maize) and milling qualities in Tanzania, and marketing in both countries. Feed attributes were important, but typically only came third. In this group, biomass came first and was important in both countries, while Ethiopian farmers also found palatability of the stalk, high

H. De Groote et al. / Field Crops Research 153 (2013) 22–36

moisture and stay-green important. The importance of attributes can differ substantially between people and regions. In Ethiopia, for example, consumer characteristics were much more appreciated by women, while the importance of early maturity depended on the region. The importance of different attributes of new varieties has been observed elsewhere, for example in Mexico (Smale et al., 2001; Bellon et al., 2006), but has been missing in the adoption literature in East Africa in general (Doss et al., 2003), and in Ethiopia (Alene et al., 2000) and Tanzania (Nkonya et al., 1997) in particular. Finally, the choice models provide some indication that good stover quality improves the likelihood of adoption. The models also show that many other factors are involved, in particular individual and household characteristics but also the institutional environment. As other studies have shown, an enabling environment is critical in bringing the varieties to the farmers (Tripp, 2003), and there is substantial room for improvement in both Ethiopia (Spielman, 2007) and Tanzania (Kathage et al., 2012). Further research on the acceptability of dual-purpose maize should take into account the lessons of the present study. More attention should be paid to proper randomized selection of the participants, and to harmonizing the procedures for determining the importance of attributes and for evaluating these attributes. In particular, elicitation of the different attributes and their importance should be done independently of the varieties under evaluation, and before the evaluation. Further, to compare farmer evaluation of these and other new varieties across study sites and countries, an effort should be made to standardize the scales. Based on these and other experiences in the evaluation of maize varieties (De Groote and Siambi, 2005), we propose to use standard Likert scales, preferably a 4-point scale to assess importance (0 = not important, 1 = of low importance, 2 = of medium importance, and 3 = very important) and a 5-point scale for the actual evaluation (1 = very poor, 2 = poor, 3 = average, 4 = good, and 5 = very good). These classifications are easy to translate into any language, are simple to administer in questionnaires with people of all educational levels, and are easy to analyze. Finally, an effort should be made to involve the same farmers in the survey as in the evaluation, so that the importance score as well as the evaluation score can be included as explanatory variables in the choice model. We conclude that there is a potentially high demand for dual-purpose maize varieties. Farmers in the maize-based mixed crop–livestock systems of the study areas clearly express an interest in such varieties. The bioeconometric models used earlier, however, indicated that breeding for stover quality might not be profitable (Thornton and Herrero, 2001), and the authors did not explore the options of increasing biomass, because of the low nutritional value of maize stover and its perceived abundance at harvest time. Our research shows, however, that farmers use maize stover extensively, and appreciate its quantity as well as its quality. Unlike the models, which use digestibility, farmers use palatability, water content and stay-green of the stover as indicators for their quality, and use them to evaluate maize varieties. Similarly, the models could be improved to include these indicators, and breeders might want to develop biophysical measurements to evaluate new varieties for these indicators. While farmers do appreciate stover quantity and quality in maize, they would clearly not accept varieties that compromise on field and consumer characteristics. New varieties therefore need to be carefully screened for the range of attributes farmers indicate as important. Fortunately, the related research also indicated that biomass and yield are not necessarily in conflict, but rather that they are positively correlated (Ertiro et al., 2013; Zaidi et al., 2013), as has also been shown for maize elsewhere (Lorenz et al., 2010). The correlation between yield and stover quality is weak at most, and further research is needed to explore the improvement of the stover quality, in particular with the traits that farmers appreciate, such as

35

moisture content and stay-green. This would fit the recent interest in stay-green varieties (Thomas and Howarth, 2000; Barry, 2009). An estimation of the demand for dual-purpose maize varieties is not possible with the current data, in part because of their limited comparability and limited spatial extent over diverse agroecologies. This could be achieved, however, by more rigorously combining GIS analysis to categorize the different systems and agro-ecologies, building on previous work (Notenbaert et al., 2013). This can be expanded with randomly selecting a wider sample of households in the different systems for a survey with a methodology similar yet more harmonized to the one presented here. Finally, the success of these varieties will critically depend on the marketing strategy, and this should take into account the institutional framework of the targeted countries. In particular, a close collaboration with the government institutions in Ethiopia is indicated, in particular the Ethiopian Seed Enterprise and its regional counterparts, although in line with the liberalization (Spielman et al., 2010), the emerging private seed sector should not be ignored. In Tanzania, after the liberalization of the seed sector (Kathage et al., 2012), the varieties of the private sector have become more popular than those from the public sector, at least in the study area. Therefore an effort should be made to involve the private seed companies, in particular the international companies. Acknowledgements The study benefitted from financial assistance provided by the German Federal Ministry for the Economic Cooperation and Development (BMZ) funded project “Improving the value of maize as livestock feed to enhance the livelihoods of maize-livestock farmers in East Africa”. We would like to thank the coordinator of the original larger project, Michael Blümmel, for his help with this study, and Professor Bekabi Fufa, Professor Evelyn Lazaro and David Watson for their advice, and Olaf Erenstein and Liz Lucas for editing. References Adesina, A.A., Zinnah, M.M., 1993. Technology characteristics, farmers’ perceptions and adoption decisions: a Tobit model application in Sierra Leone. Agric. Econ. 9, 297–311. Alene, A.D., Poonyth, D., Hassan, R.M., 2000. Determinants of adoption and intensity of use of improved maize varieties in the central highlands of Ethiopia: a tobit analysis. Agrekon 39, 633–643. Barry, C.S., 2009. The stay-green revolution: recent progress in deciphering the mechanisms of chlorophyll degradation in higher plants. Plant Sci. 176, 325–333. Bellon, M.R., Adato, M., Becerril, J., Mindek, D., 2006. Poor farmers’ perceived benefits from different types of maize germplasm: the case of creolization in lowland tropical Mexico. World Dev. 34, 113–129. Berhanu, T., Habtamu, Z., Twumasi-Afriyie, S., Blümmel, M., Friesen, D., Mosisa, W., Dagne, W., Legesse, W., Girum, A., Tolera, K., Wende, A., 2012. Breeding Maize for Food-Feed Traits in Ethiopia. In: Worku, M., Twumasi-Afriyie, S., Wolde, L., Tadesse, B., Demisie, G., Bogale, G., Wegari, D., Prasanna, B.M. (Eds.), Meeting the Challenges of Global Climate Change and Food Security through Innovative Maize Research. Proceedings of the Third National Maize Workshop of Ethiopia. EIAR/CIMMYT, Addis Ababa, Ethiopia, 18-20 April 2011, pp. 74-80. Blümmel, M., Zerbini, E., Reddy, B.V.S., Hash, C.T., Bidinger, F., Khan, A.A., 2003. Improving the production and utilization of sorghum and pearl millet as livestock feed: progress towards dual-purpose genotypes. Field Crops Res. 84, 143–158. Boone, H.N., Boone, D.A., 2012. Analyzing Likert data. Journal of Extension 50, Article Number 2TOT2 http://www.joe.org/joe/2012april/tt2.php Byerlee, D., Harrington, L., Winkelman, D., 1982. Farming systems research: issues in research strategy and technology design. Am. J. Agric. Econ. 64, 897–904. Cecchi, G., Wint, W., Shaw, A., Marletta, A., Mattioli, R., Robinson, T., 2010. Geographic distribution and environmental characterization of livestock production systems in Eastern Africa. Agric. Ecosyst. Environ. 135, 98–110. Chambers, R., 1994. The origins and practice of participatory rural appraisal. World Dev. 22, 953–969. CIMMYT, 2012. Global Maize Program. http://www.cimmyt.org/en/programs-andunits/global-maize-program (accessed 25.01.13). Coe, R., 2002. Analyzing ranking and rating data from participatory on-farm trials. In: Bellon, M.R., Reeves, J. (Eds.), Quantitative analysis of data from participatory methods in plant breeding. CIMMYT, Mexico, DF, pp. 46–65.

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