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To do so, we conducted a characterisation of these agricultural systems in a comparative framework. Smallholder farming systems are diverse and complex. This complexity contributes to system resilience, but may also impede transition of agricultural systems in an area where a high and rapidly increasing population density needs to be fed from a limited amount of land.

Smallholder systems are very diverse due to the large variability in agro-ecological and socio-economic conditions in which they operate. To encompass this complexity, innovations in smallholder systems should be based on a systemic diagnosis of the agro-ecological potential, the socio-economic context and the objectives of the farm households Hall and Clark, and specific attention should be paid to the multi- functionality of agriculture IAASTD, Most of the published results in agronomy are quantitative and collected off-farm Le Gal et al.

They often focus on annual crops cultivated in monoculture and market- oriented systems Scoones and Thompson, To take into account dimensions such as food and income security, diversity and risk avoidance, complementary approaches using additional indicators should be proposed. This will include assessing the multi-functionality of agricultural systems, e. Our approach focuses on the farm level and aims to encompass all dimensions of production in smallholder systems.

From an historical perspective, banana-based systems are at the heart of the adaptation of small scale agricultural systems to environmental and demographic conditions Cochet, The focus of our study is to consider this smallholder system to understand the various dimensions determining farm productivity.

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Three sites in Rwanda were selected along an agro-ecological gradient in terms of altitude, rainfall, soil fertility, pests and disease pressure : Gatore sector in the east, Musenyi in the south and Nzahaha in the west. The two sites in the other countries were Muyange in Burundi and Burhale in DR Congo and take into account diversity of institutional organisation in terms of agricultural policy and extension. The site selection should allow us to better understand the drivers of farm diversity in banana- based systems.

For the sake of homogeneity, we limited the scope of our study to the banana-based cropping system. Indeed, the banana crop is an ideal entry point in the agricultural systems of the Great Lakes region, as banana has a role in food, income and social life of the population.

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It explains why most of smallholders have a banana plantation around their compounds. From to , we conducted regular field surveys in each study site. During this period, the first author conducted six field trips that varied in duration from two weeks to three months. Each visit was an opportunity for contact with farmers. In this chapter, we focus on two survey phases: an individual survey conducted in and a complementary survey undertaken in Given the time consuming constraint of this type of data collection, we sampled 30 farmers six per site with the purpose of capturing maximum diversity.

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Comprehensive interviews were the main tool used to collect the data. We used an interview guide on key topics to tackle during the interview, instead of a questionnaire with fixed question and answer options. Such semi-structured interviews provide an atmosphere of open conversation.

We systematically crosschecked the information provided by the interviewee with a field visit to validate the data. The mode of interaction and the regular personal contacts generated a relationship of trust that guaranteed a high reliability of collected information. The type of information collected was variable but substantial. To analyse the data, we sorted and classified it. Then we transcribed the interviews and compiled summary tables that were combined with key quantitative information e. Finally, we coded the transcription with a set of key words.

This allowed us to analyse the interview data, for example by extracting interviewee statements on specific key words. In this way, the qualitative material can be easily retrieved throughout the research process.


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The aim was to analyse the technical functioning of the farming systems and assess their economic performance. Between nine and 12 farmers were selected in each site, resulting in a total of 53 farms. Among these farmers, there was an equal number who were either low, medium or high in terms of welfare. The socio-economic classification was based on observations of farmers and perceptions by local key informants and interviewed farmers, i. Data were collected on i crop types, e.

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Most of the information was obtained through the interviews. Geo-referenced measurements were used to assess the total size of the farm and the area of each individual plot. Quantitative data were processed with a complex algorithm to compare the performances at both the inter-regional and intra-site level. The first step of this algorithm produced a complete economic balance for each farm by calculating its economic components from the quantitative data collected in the field.

In the second step, any missing information about the production of the different crops was estimated using the average crop yield at the site. Within the initial sample of 53 farmers, we discarded nine farmers for whom more than fifty percent of the production had to be estimated by average values. The final processed sample comprised 43 farmers: ten in Gatore, seven in Musenyi, seven in Nzahaha, ten in Muyange, nine in Burhale. The quantitative and qualitative parts of the method were linked throughout the process of research. The method is intrinsically iterative.

Beer bananas were dominant in Burundi and DR Congo, while the proportion of banana for beer, cooking or dessert was more even in Rwanda sites. Cooking bananas were predominant in the east of Rwanda site. Plantains were only significantly present in the DR Congo site.

Intercropping in banana was widely observed in Burundi sites especially with beans and maize , intermediate in Rwanda sites and uncommon in the DR Congo site. Plant density increased from east to west in line with the gradual increase of rainfall from eastern Rwanda to the Albertine Rift in the west.

The source of fertilization was essentially organic: compost in all sites, cow manure in east and south Rwanda, goat manure in west Rwanda and DR Congo, and no use of manures in Burundi. Mulching sources were various: mulching with grass and self-mulching with residues of banana, crops and weeds. All these mulch types were used in east and in south Rwanda, whereas plantations in the other sites relied heavily on self-mulching and weed residue only. In Burundi, a part of banana wastes was used for the mulching of coffee plantations Fig The length of the black line represents the relative size of the banana plantation.

The distance between the banana plant symbols indicates the density of the plantation. The number of intercropping symbols shows the intensity of intercropping. The mulch symbols in the bubble on the right indicate the source of mulching grass; residues of bananas, crops or weeds; wastes of banana processing. Colours of banana symbols represent: blue: beer banana, green: cooking banana, yellow: dessert banana, red: plantain.

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Farm size ranged from 0. The farms were smallest in DR Congo site, with a median of 0. Burundi and west Rwanda sites had intermediate farm sizes 0. The inter-quartile range of farm sizes was greater in the Rwanda sites than at other sites, particularly in the east.


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  • Individual points are outliers. Productivity USD ha-1 y-1 was related to farm size Figure Even if each site had a specific distribution, the optimum productivity for all sites was reached between 0. In the first category, the farm size from 0. The second category with medium farm sizes from 0. The third category is characterized by larger farms from 1.


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    The mean productivity in the medium size category is almost 1. With a median of 11 crops, Musenyi south Rwanda and Burhale DR Congo recorded the highest number of crops per farm, whereas the Burundi site had the lowest number with a median of seven. But we observed that in Burundi - as with east Rwanda and DR Congo sites - the widest range of crop number per farm was recorded, ranging from five to It is also noteworthy that the intermediate category 2 presents a larger range of crop types compared with the other categories Figure A per site and B per size of farm.

    The median values, i.

    Banana Systems in the Humid Highlands of Sub-Saharan Africa: Enhancing Resilience and Productivity

    They are the first attempt to characterize the diversity and complexity of banana-based systems at the village scale, extrapolation to the country level should be avoided. The qualitative representation of the diversity of farm management practices Figure In Burundi, for example, even if cow manure is available, farmers do not use this source of organic matter because they consider it as the source of disease for banana.

    The high density of plantations in DR Congo compared with east Rwanda was linked to the choice of banana type and to rainfall. In DR Congo, farmers favour beer bananas for which the weight of bunches is less important than the frequency with which they are produced while in east Rwanda, food bananas are predominant and give bigger bunches with a low density of planting. Understanding the perceptions and the mechanism of decision-making is a prerequisite to build and implement more suitable recommendations and innovations Hall and Clark Our results confirm the small-scale characteristic of banana-based farming systems Figure Mussa, Dismas L.

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