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3. Agronomic and socio-economic drivers of fertilizer use and crop productivity in smallholder wheat production systems in Ethiopia

Author

Ebrahim Mohammed, Mesfin Tewodros, Tamene Lulseged, Liben Feyera, Abera Wuletawu, and Tilaye Amsalu

Subjects
Soil fertility, Agro-advisories, Food security, Site-specific fertilizer recommendations, Environmental sciences, GE1-350
Abstract

Abstract Wheat (Triticum aestivum L.) is crucial for global food security and a staple crop in Ethiopia, yet farmer yields remain low, averaging 2.7 t ha⁻1 compared to over 5 t ha⁻1 at research stations. This study investigates the impact of socio-economic factors, local agronomic practices, and site-specific fertilizer management on wheat production in Goba, Lemu, Siyadebr, and Basona districts of Ethiopia. A survey of 228 households analyzed the influence of these factors on wheat productivity and fertilizer use, employing descriptive statistics, t-tests, and regression models. Results indicated that crop residue retention, improved wheat varieties, and organic fertilizers significantly increased yields, while row fertilizer application at planting had a negative effect. Fertilizer application rates varied significantly among farmers and were influenced by practices like top-dressing, monocropping, and participation in agricultural training. District-level differences in yield and fertilizer response highlighted the need for site-specific management. Multiple regression analysis revealed that key predictors of fertilizer use included cultivated land area, household income, education, small ruminant ownership, and extension contact, with larger land ownership, higher income, organic fertilizer use, and extension access being the most significant. Average yield increases due to site-specific fertilizer applications varied across districts. Overall, significant yield gains were achieved through site-specific fertilizer application across the four districts, with an average yield of 5.3 Mg ha⁻1, compared to approximately 4 Mg ha⁻1 using the local farmers' fertilizer application rates. This study underscores the importance of considering local agroecological conditions in fertilizer management to boost wheat productivity and support food security and economic development in Ethiopia.

Published
2024
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18. Scientific Misconduct and Partisan Research on the Stability of the Grand Ethiopian Renaissance Dam: A Critical Review of a Contribution to Environmental Remote Sensing in Egypt (Springer, 2020)

Author

Abera, Wuletawu, Haregeweyn, Nigussie, Dile, Yihun, Fenta, Ayele A., Berihun, Mulatu L., Demissie, Biadgilgn, Mulatu, Chalachew A., Nigussie, Tewodros A., Billi, Paolo, Meaza, Hailemariam, Woldearegay, Kifle, Melesse, Assefa M., Moges, Semu A., Tamene, Lulseged, Brilly, Mitja, Advisory Editor, Davis, Richard A., Advisory Editor, Hoalst-Pullen, Nancy, Advisory Editor, Leitner, Michael, Advisory Editor, Patterson, Mark W., Advisory Editor, Veress, Márton, Advisory Editor, Melesse, Assefa M., editor, Abtew, Wossenu, editor, and Moges, Semu A., editor

Published
2021
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25. Reference soil groups map of Ethiopia based on legacy data and machine learning-technique: EthioSoilGrids 1.0

Author

Ali, Ashenafi, primary, Erkossa, Teklu, additional, Gudeta, Kiflu, additional, Abera, Wuletawu, additional, Mesfin, Ephrem, additional, Mekete, Terefe, additional, Haile, Mitiku, additional, Haile, Wondwosen, additional, Abegaz, Assefa, additional, Tafesse, Demeke, additional, Belay, Gebeyhu, additional, Getahun, Mekonen, additional, Beyene, Sheleme, additional, Assen, Mohamed, additional, Regassa, Alemayehu, additional, Selassie, Yihenew G., additional, Tadesse, Solomon, additional, Abebe, Dawit, additional, Wolde, Yitbarek, additional, Hussien, Nesru, additional, Yirdaw, Abebe, additional, Mera, Addisu, additional, Admas, Tesema, additional, Wakoya, Feyera, additional, Legesse, Awgachew, additional, Tessema, Nigat, additional, Abebe, Ayele, additional, Gebremariam, Simret, additional, Aregaw, Yismaw, additional, Abebaw, Bizuayehu, additional, Bekele, Damtew, additional, Zewdie, Eylachew, additional, Schulz, Steffen, additional, Tamene, Lulseged, additional, and Elias, Eyasu, additional

Published
2024
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29. The role of climate smart agricultural practices on household income and food security: A propensity score matching approach

Author

Tesfaye, Abonesh, primary, Hammod, James, additional, Radeny, Maren, additional, Recha, John Walker, additional, Nigussie, Abebe, additional, Ambaw, Gebermedihin, additional, van Wijk, Mark T., additional, Tamene, Lulseged, additional, Abera, Wuletawu, additional, Demeke, Getamesay, additional, and Solomon, Dawit, additional

Published
2023
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32. Assessing the application of gender perspectives in land restoration studies in Ethiopia using text mining

Author

Abera, Wuletawu; Tamene, Lulseged; Mekonnen, Dawit; Carmona, Natalia Estrada; Elias, Marlene; Joshi, Deepa; Aynekulu, Ermias, http://orcid.org/0000-0003-3642-3497 Mekonnen, Dawit, Abera, Wuletawu; Tamene, Lulseged; Mekonnen, Dawit; Carmona, Natalia Estrada; Elias, Marlene; Joshi, Deepa; Aynekulu, Ermias, and http://orcid.org/0000-0003-3642-3497 Mekonnen, Dawit

Abstract

PR, IFPRI3; ISI; CRP5; G Cross-cutting gender theme, Natural Resources and Resilience Strategies (NRRS); Transformation Strategies, CGIAR Research Program on Water, Land and Ecosystems (WLE), Restoration of degraded land is key to enhancing land productivity and farmers' wellbeing in sub-Saharan Africa. Evidence shows that the benefits of land restoration are tremendous, ranging from biophysical benefits in soil health, agricultural productivity, ecosystem services, to socio-economic dimensions such as improving farmers’ income and livelihoods. Yet one issue that is rarely considered is how the outcomes of restoration initiatives affect different social groups, specifically women, men, and the marginalized. Our study aims to understand the extent of gender and social inclusion in land restoration studies in Ethiopia. Through analyzing 314 peer-reviewed scientific articles on land restoration initiatives and studies for Ethiopia published between 1985 and 2020, we aimed to: i) develop a novel approach that would allow for the semi-automatization of analyzing gender aspects in a large set of scientific documents using machine learning techniques, ii) assessed the current evidence on gender integration in peer-reviewed studies related to RDL, and iii) identified what gender issues are discussed in RDL literature. We employed text mining techniques to analyze the literature for keywords and to classify articles into three main classes: gender blind, gender sensitive, and gender transformative, based on the extent to which gender and social inclusion keywords appeared in the studies. Our analysis showed that gender and social inclusion are rarely considered in landscape restoration studies in Ethiopia, as most studies and interventions are heavily focused on the biophysical and environmental aspects of restoration. Despite an exponential increase in the use of gender and social inclusion keywords after 2005, most of the research (58 percent of articles) remains gender blind. The most frequently used related terms remained generic, e.g. community, access, participatory, and tenure. Only 38% of the studies could be classified as gender sensitive to a certain de

Published
2023

34. Time-series ARIMA modelling of the Labeobarbus spp (Cyprinidae) fishery in water hyacinth-infested and non-infested sites in Lake Tana, Ethiopia.

Author

Mohammed Yesuf, Brehan, Getahun, Abebe, Mengistou, Seyoum, Wilson, Glenn, Anteneh, Wassie, and Abera, Wuletawu

Subjects
WATER hyacinth, BOX-Jenkins forecasting, CYPRINIDAE, ENDEMIC fishes, CLARIAS gariepinus, FISH declines, FISH productivity
Abstract

Ethiopia's largest freshwater lake, Lake Tana, is home to 21 endemic fish species, the majority of which are cyprinids in the genus Labeobarbus. The lake is undergoing numerous ecological changes, including an invasion of water hyacinth (Eichhornia crassipes (Mart.) Solms (WH). The aim of this study was to predict the future fish productivity in Lake Tana by considering the increasing water hyacinth infestation. This was accomplished by analyzing a 12-year fishery-independent time-series data set of Labeobarbus, collected from sites infested and not infested by water hyacinth. The stationarity of the data was investigated using the Augmented Dickey-Fuller (ADF) unit root test. First-order data differencing was applied to solve the non-stationarity data to stationarity. With the same standardized fishing gillnet and the same sites, the CPUE during the dry season decreased from 3,502 grams (3.5 kg/day) in 2010 to 360 grams (0.36 kg) in 2020 at the water hyacinth-infested sites, demonstrating a 90% decrease in the daily catch. A reduction in catch per unit effort (CPUE) is evident at the WH sites in all seasons, and the rate of fall in there was faster than at the non-infested site. Box Jenkin's auto-regressive integrated moving average models (ARIMA) modelling predicted that Labeobarbus CPUE will decline by a threefold % by 2032 compared to the current catch. Based on these results, the most suitable model for all the seasons and areas was confirmed to be ARIMA (0, 1, 0) using the lowest value of Akaike Information Criteria (AIC's). The fish production declines with expanding WH infestation will necessitate integrated water hyacinth reduction strategies, closed area and closed spawning seasons, and mesh size regulations to conserve and utilize the resource sustainably. As Labeobarbus is the only examined species in this study, forecasts should be made for other commercially significant fish species in the Lake, such as Oreochromis niloticus and Clarias gariepinus. [ABSTRACT FROM AUTHOR]

Published
2023
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39. A data-mining approach for developing site-specific fertilizer response functions across the wheat-growing environments in Ethiopia

Author

Abera, Wuletawu, Tamene, Lulseged, Tesfaye, Kindie, Jiménez, Daniel, Dorado, Hugo, Erkossa, Teklu, Kihara, Job, Ahmed, Jemal Seid, Amede, Tilahun, Ramirez-Villegas, Julian, Abera, Wuletawu, Tamene, Lulseged, Tesfaye, Kindie, Jiménez, Daniel, Dorado, Hugo, Erkossa, Teklu, Kihara, Job, Ahmed, Jemal Seid, Amede, Tilahun, and Ramirez-Villegas, Julian

Abstract

The use of chemical fertilizers is among the main innovations brought by the 1960s Green Revolution. In Ethiopia, fertilizer application during the last four decades has led to significant yield gains, yet yield remains below its potential across much of the country. One of the main challenges responsible for low yield response to fertilizer application has been the use of 'blanket' recommendations, whereby no tailoring of fertilizer amount and frequency is done based on soil requirements. As a result, the amount of fertilizer applied ranges widely, and can be either sub- or supra-optimal. There is thus an increasing need for site-specific fertilizer recommendations which take into account site characteristics such as climate variables (temperature, rainfall, and solar radiation); soil factors (soil organic carbon, moisture, pH, texture, cation exchange capacity, and level of macro- and micronutrients); and topographic position indices. This article reports on a data-mining approach we developed on a large dataset of 6585 wheat (Triticum aestivum) field trials. The dataset includes detailed, site-specific biophysical variables to create nutrient response functions that can guide optimal site-specific fertilizer application. The approach used a machine-learning model (random forest) to capture the relationship between nutrients - nitrogen (N), phosphorous (P), potassium (K), and sulfur (S) - and wheat yield. The model explained about 83, 82, 47, and 69% of variances of yield for N, P, K, and S omission, respectively, with consistent performance across training and testing datasets. Expectedly, for N and P omission data, the most important explanatory variables are nutrient rate, followed by soil organic carbon and soil pH. For K and S, however, climatic variables played an important role alongside nutrient rates. The site-specific yield-fertilizer response curves derived from our model are highly variable from location to location, as they are affected by the climati

Published
2022

40. Reference Soil Groups Map of Ethiopia Based on Legacy Data and Machine Learning Technique: EthioSoilGrids 1.0

Author

Ali, Ashenafi, primary, Erkossa, Teklu, additional, Gudeta, Kiflu, additional, Abera, Wuletawu, additional, Mesfin, Ephrem, additional, Mekete, Terefe, additional, Haile, Mitiku, additional, Haile, Wondwosen, additional, Abegaz, Assefa, additional, Tafesse, Demeke, additional, Belay, Gebeyhu, additional, Getahun, Mekonen, additional, Beyene, Sheleme, additional, Assen, Mohamed, additional, Regassa, Alemayehu, additional, Selassie, Yihenew G., additional, Tadesse, Solomon, additional, Abebe, Dawit, additional, Walde, Yitbarek, additional, Hussien, Nesru, additional, Yirdaw, Abebe, additional, Mera, Addisu, additional, Admas, Tesema, additional, Wakoya, Feyera, additional, Legesse, Awgachew, additional, Tessema, Nigat, additional, A. Abebe, Ayele, additional, Gebremariam, Simret, additional, Aregaw, Yismaw, additional, Abebaw, Bizuayehu, additional, Bekele, Damtew, additional, Zewdie, Eylachew, additional, Schulz, Steffen, additional, Tamene, Lulseged, additional, and Elias, Eyasu, additional

Published
2022
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44. Balanced fertilization increases wheat yield response on different soils and agroecological zones in Ethiopia

Author

Dargie, Sofonyas, primary, Girma, Tsegaye, additional, Chibsa, Tilahun, additional, Kassa, Sofia, additional, Boke, Shiferaw, additional, Abera, Abate, additional, Haileselassie, Bereket, additional, Addisie, Samuel, additional, Amsalu, Sosina, additional, Haileselassie, Mehretab, additional, Soboka, Shure, additional, Abera, Wuletawu, additional, and Weldesemayat, Sileshi G., additional

Published
2022
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45. Yield response of tef (Eragrostis tef) to nitrogen, phosphorus, potassium and sulphur under balanced fertilization on Vertisols in different agroecological zones of Ethiopia

Author

Chala, Girma, primary, Kassa, Sofia, additional, Tadele, Tsadik, additional, Assefa, Kefyalew, additional, Teshome, Habtemariam, additional, Agegnehu, Getachew, additional, Abera, Wuletawu, additional, Tibebe, Degife, additional, Sileshi, Gudeta W., additional, and Erkossa, Teklu, additional

Published
2022
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