http://197.159.135.214/jspui/handle/123456789/28 Thu, 23 Apr 2026 15:06:17 GMT 2026-04-23T15:06:17Z http://197.159.135.214/jspui/handle/123456789/441 Spatial and Temporal Variability of Soil Redox Potential, pH and Electrical Conductivity across a Toposequence in the Savanna of West Africa Tano, Bernard F.; Brou, Casimir Y.; Dossou-Yovo, Elliott R.; Saito, Kazuki; Futakuchi, Koichi; Wopereis, Marco. C. S.; Husson, Olivier Soil redox potential is an important factor affecting soil functioning. Yet, very few agronomy studies included soil redox potential in relation to soil processes. The objective of this study was to evaluate the spatial and temporal variation in soil redox potential and to determine the soil parameters affecting its variation. Soil redox potential, soil moisture, soil temperature, pH and bulk electrical conductivity were measured in upland rice fields during two growing seasons at six positions along an upland–lowland continuum, including two positions at the upland, two at the fringe and two at the lowlands in central Côte d’Ivoire (West Africa). The measurements were made at the following soil depths: 3, 8, 20 and 35 cm. Soil redox potential varied between 500 and 700 mV at the upland positions, 400 and 700 mV at the fringe positions and 100 and 750 mV at the lowland positions, and increased with soil depth. Variations in soil redox potential were driven by soil moisture, bulk electrical conductivity and soil organic carbon. We concluded that for proper interpretation of soil redox potential, sampling protocols should systematically include soil pH, moisture and bulk electrical conductivity measurements. Research Article Wed, 01 Jan 2020 00:00:00 GMT http://197.159.135.214/jspui/handle/123456789/441 2020-01-01T00:00:00Z http://197.159.135.214/jspui/handle/123456789/440 Shea (Vitellaria paradoxa Gaertn C. F.) fruit yield assessment and management by farm households in the Atacora district of Benin Aleza, Koutchoukalo; Villamor, Grace B.; Nyarko, Benjamin Kofi; Wala, Kperkouma; Akpagana, Koffi Vitellaria paradoxa (Gaertn C. F.), or shea tree, remains one of the most valuable trees for farmers in the Atacora district of northern Benin, where rural communities depend on shea products for both food and income. To optimize productivity and management of shea agroforestry systems, or "parklands," accurate and up-to-date data are needed. For this purpose, we monitored120 fruiting shea trees for two years under three land-use scenarios and different soil groups in Atacora, coupled with a farm household survey to elicit information on decision making and management practices. To examine the local pattern of shea tree productivity and relationships between morphological factors and yields, we used a randomized branch sampling method and applied a regression analysis to build a shea yield model based on dendrometric, soil and land-use variables. We also compared potential shea yields based on farm household socio-economic characteristics and management practices derived from the survey data. Soil and land-use variables were the most important determinants of shea fruit yield. In terms of land use, shea trees growing on farmland plots exhibited the highest yields (i.e., fruit quantity and mass) while trees growing on Lixisols performed better than those of the other soil group. Contrary to our expectations, dendrometric parameters had weak relationships with fruit yield regardless of land-use and soil group. There is an inter-annual variability in fruit yield in both soil groups and land-use type. In addition to observed inter-annual yield variability, there was a high degree of variability in production among individual shea trees. Furthermore, household socioeconomic characteristics such as road accessibility, landholding size, and gross annual income influence shea fruit yield. The use of fallow areas is an important land management practice in the study area that influences both conservation and shea yield. Research Article Mon, 01 Jan 2018 00:00:00 GMT http://197.159.135.214/jspui/handle/123456789/440 2018-01-01T00:00:00Z http://197.159.135.214/jspui/handle/123456789/439 Predictors of Drought in Inland Valley Landscapes and Enabling Factors for Rice Farmers’ Mitigation Measures in the Sudan-Sahel Zone Dossou-Yovo, Elliott R.; Zwart, Sander J.; Kouyaté, Amadou; Ouédraogo, Ibrahima; Bakare, Oladele Drought is a noteworthy cause of low agricultural profitability and of crop production vulnerability, yet in numerous countries of Africa little to no consideration has been paid to readiness for drought calamity, particularly to spatial evaluation and indicators of drought occurrence. In this study, biophysical and socio-economic data, farmers’ community surveys and secondary data from remote sensing on soil characteristics and water demand were used to evaluate the predictors of drought in inland valley rice-based production systems and the factors affecting farmers’ mitigation measures. The study intervened in three West African countries located in the Sudan-Sahel zone, viz. Burkina Faso, Mali and Nigeria. Significant drying trends occurred at latitudes below 11◦300 whilst significant wetting trends were discerned at latitude above 11◦300 . Droughts were more frequent and had their longest duration in the states of Niger and Kaduna located in Nigeria and in western Burkina Faso during the period 1995–2014. Among 21 candidate predictors, average annual standardized precipitation evapotranspiration index and duration of groundwater availability were the most important predictors of drought occurrence in inland valleys rice based-production systems. Land ownership and gender affected the commitment of rice farmers to use any mitigation measure against drought. Drought studies in inland valleys should include climatic water balance and groundwater data. Securing property rights and focusing on women’s association would improve farmers’ resilience and advance drought mitigation measures. Research Article Mon, 01 Jan 2018 00:00:00 GMT http://197.159.135.214/jspui/handle/123456789/439 2018-01-01T00:00:00Z http://197.159.135.214/jspui/handle/123456789/438 Mapping suitability for rice production in inland valley landscapes in Benin and Togo using environmental niche modeling Akpoti, Komlavi; Kabo-bah, Amos T.; Dossou-Yovo, Elliott R.; Groen, Thomas A.; Zwart, Sander J. Inland valleys (IVs) in Africa are important landscapes for rice cultivation and are targeted by national governments to attain self-sufficiency. Yet, there is limited information on the spatial distribution of IVs suitability at the national scale. In the present study, we developed an ensemble model approach to characterize the IVs suitability for rainfed lowland rice using 4 machine learning algorithms based on environmental niche modeling (ENM) with presence-only data and background sample, namely Boosted Regression Tree (BRT), Generalized Linear Model (GLM), Maximum Entropy (MAXNT) and Random Forest (RF). We used a set of predictors that were grouped under climatic variables, agricultural water productivity and soil water content, soil chemical properties, soil physical properties, vegetation cover, and socio-economic variables. The Area Under the Curves (AUC) evaluation metrics for both training and testing were respectively 0.999 and 0.873 for BRT, 0.866 and 0.816 for GLM, 0.948 and 0.861 for MAXENT and 0.911 and 0.878 for RF. Results showed that proximity of inland valleys to roads and urban centers, elevation, soil water holding capacity, bulk density, vegetation index, gross biomass water productivity, precipitation of the wettest quarter, isothermality, annual precipitation, and total phosphorus among others were major predictors of IVs suitability for rainfed lowland rice. Suitable IVs areas were estimated at 155,000–225,000 Ha in Togo and 351,000–406,000 Ha in Benin. We estimated that 53.8% of the suitable IVs area is needed in Togo to attain self-sufficiency in rice while 60.1% of the suitable IVs area is needed in Benin to attain self-sufficiency in rice. These results demonstrated the effectiveness of an ensemble environmental niche modeling approach that combines the strengths of several models. Research Article Tue, 01 Jan 2019 00:00:00 GMT http://197.159.135.214/jspui/handle/123456789/438 2019-01-01T00:00:00Z