Fertile ground? : soil fertility management and the African smallholder
Notice bibliographique
Résumé
Keywords: smallholder farmers, soil fertility, experimentation, "inconvenience", realist.The focus in this thesis is to form a view of how well soil fertility research performs within the ever shifting smallholder contexts. This study examined application of agro-ecological knowledge for soil fertility management by smallholder farmers, with the view to enhancing the utility of research among resource-deprived farmers of westernKenya.A realist methodological approach to the study of soil management was applied. It is shown that soil fertility management operates under the assumption that consequences (soil management) are to be explained not just by contextual states (in this case farmer knowledge) but by "mechanisms" of decision making and soil management that need to be uncovered. Knowledge is nothing unless it engages with real soil management processes.Between 2003 and 2005, participatory experimentation, monitoring and evaluation of technologies and concepts were explored. Those experiments involved: (i) cereal-legume rotations; (ii) screening new soyabean varieties for selection among smallholders; (iii) organic resource quality concepts and biomass transfer; and(iv) mineralfertiliser response. Farmers' practices following these experiments were investigated, with particular focus on their underlying justifications and livelihood objectives.Participating farmers selected experimental plots to ensure that the soils were representative in terms of type, fertility status and history of cultivation. These farms were classified as infertile during the participatory soil characterisation. Farmers deliberately selected the infertile plots to "see if the new technologies worked", and as part of their wider objective. These experimental plots were researcher-designed.Researcher notions of organic resource quality was interpreted and amended by farmers based on existing knowledge, experiences and cultural constructs. For instance, Tithonia was perceived as a "hot resource" that could be added to composts to increase the "speed of cooking". Amendments to this concept, and to new soil fertility management technologies, were based on "ordinary" applications and reflected perceptions of inconvenience; meaning especially labour constraints, land shortage, uncertain yield and economic returns. Alternative (i.e. not-for-soil-fertility-management) uses of the different technologies were prominent. For example, legume varieties with utility beyond soil fertility management were preferred which resulted in readily observable gains when applied under variable local conditions. Those local conditions demanded the use of mineral (P) fertiliser in the successful implementation of the cereal-legume rotation scheme or adoption of newpromiscuoussoyabeanvarieties. Farmers selected varietiesprimarily on the basis of yield, rate of growth and appearance.Poor yields when mineral fertiliser was not applied, or unsteady crop responses after its use, cost - coinciding with priority expenditures and association with particular technologies such as hybrid maize - complicated the use of fertiliser.Limited understanding of fertiliser functionality, soil nutrients or soil fertility mechanisms is clarified in terms of the context-mechanism-outcome paradigm of "realist" explanation. The farmer paradigm refers mainly to context and outcomes, which we interpret as a kind of positivism. On the one hand, scientists' focus on mechanisms (to the apparent exclusion of context and outcome) does not match the highly variable local social, physical and economic contexts made more difficult by poor (implementation of) policy. Both farmers and researchers, it is argued, need to enhance their capacity to modify their knowledge sets by engaging in well-designed joint research drawing on the context-mechanism-outcome configuration. Experimentation is seen as one way to expand farmers' knowledge sets on soil fertility and to make mechanisms (e.g. nutrient availability) more visible, so that farmers can engage in soil fertility improvement activity in ways that are both more effective and more meaningful.This thesis also concludes that to increase the utility of research requires a shiftfrom component research to research at subsystem or whole-farm system level to address broader household objectives. The chances of sustainable application of scientific innovations by smallholders will be greatly enhanced if field research embraces and embeds social science methods of engaging the farmer sustainably as a partner in technology development and not simply as a client.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,005 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».