Adoption and Impact of the Improved Fallow Technique on Cotton Productivity and Income in Zambia
Notice bibliographique
Résumé
An improved fallow is a soil fertility agroforestry technique that has commonly been used in the staple maize production systems of Zambia and sub-Saharan Africa. Several studies have assessed the adoption and impact of the improved fallow on maize production. Generally, it has been observed that though the improved fallow does increase maize yields, its efficacy on welfare in terms of increased income is low. The use of the technique on cash crops that could significantly contribute to household welfare has rarely been investigated. This study assessed the factors affecting the adoption and impact of improved fallows on a commonly grown cash crop, cotton, in the cotton growing provinces of Zambia. The study used a sub sample (N=1206) of the nationally representative 2014/15 Rural Agricultural Livelihoods Survey (RALS) data which was randomly collected by the Indaba Agricultural Policy Research Institute (IAPRI) and Central Statistical Office (CSO) of Zambia. The determinants of improved fallow adoption among the cotton farmers were examined through the use of the probit model while the impact of the technique on cotton production and income was evaluated by using the propensity score matching and the endogenous switching regression models. Among the socioeconomic factors significantly increasing the probability of improved fallow adoption included: increases in age, education level, and per capita productive assets of the farmer, in addition to the area under cotton production and the distance of the homestead to the market. Institutional factors found to increase the farmer’s likelihood of adopting the improved fallow in the cotton production systems included; farmer membership to a cooperative, receiving improved fallow seedlings from the government projects and having information on agroforestry tree species. On the other hand, an increase in land size per capita was found to negatively affect the likelihood of improved tree fallow adoption. Impact estimates showed significant cotton yield and income increases as a result of adopting the technique. The continuous provision of information on relatively new techniques such as the improved fallows preferably in farmer organized groups, and support towards the provision of the technique’s planting materials are some of the areas requiring government and NGOs attention. In addition, the study recommends that the farmers’ formal education level should be enhanced and that improved tree fallows should also be explicitly promoted on cash crops that have similar agronomic requirements to maize such as cotton.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».