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Accueil du site → Doctorat → Allemagne → 2021 → Benefits and trade-offs of legume-led crop rotations on crop performance and soil erosion at various scales in SW Kenya

Universität Hohenheim (2021)

Benefits and trade-offs of legume-led crop rotations on crop performance and soil erosion at various scales in SW Kenya

Koomson, Eric

Titre : Benefits and trade-offs of legume-led crop rotations on crop performance and soil erosion at various scales in SW Kenya

Vorteile und Kompromisse von durch Hülsenfrüchte geführten Fruchtfolgen in Bezug auf Ernteleistung und Bodenerosion in verschiedenen Größenordnungen im Südwesten Kenyas

Auteur : Koomson, Eric

Université de soutenance : Universität Hohenheim

Grade : “Doktor der Agrarwissenschaften” (Dr. sc. Agr. / Ph.D. in Agricultural Sciences) 2021

Résumé partiel
Soil erosion and land fragmentation threaten agricultural production in large parts of the Western Kenyan Highlands. In Rongo watershed, maize–common bean intercropping systems, which dominate the agricultural landscape, are vulnerable to soil degradation, especially on long slope lengths where ground and canopy cover provision fail to protect the soil from the disruptive impact of raindrops. The inclusion of soil conservation measures like hedgerows, cover crops or mulch can reduce soil erosion, but compete with crops for space and labour. Knowledge of critical slope length can minimise interventions and trade–offs. Hence, we evaluated maize–common bean intercrop (MzBn) regarding runoff, erosion and crop yield in a slope length trial on 20, 60 and 84 m plot lengths, replicated twice on three farms during one rainy season in Rongo, Migori County. Additionally, we investigated systems of MzBn (farmers’ practice), MzBn with 5 Mg ha-1 Calliandra calothyrsus mulch (Mul), Arachis hypogaea (Gnt), Lablab purpureus (Lab) and Mucuna pruriens (Muc), regarding their impact on infiltration, runoff, soil loss, soil C and N loss during three rainy seasons (long and short rains, LR and SR, 2016, and LR 2017). Measured field data on soil, crop, spatial maps and meteorology were used as input datasets to parameterize and calibrate the LUCIA model. The calibrated and validated model was then used to simulate agronomic management scenarios related to planting date (planting with first rain vs baseline) and vegetation cultivar (short duration crop) to mitigate water stress.

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