Food insecurity remains a critical challenge across sub-Saharan Africa, particularly in low-income rural areas. Despite Rwanda’s economic progress, rural households continue to face high levels of food insecurity. This study analyzes panel data from 1,100 households in Eastern Rwanda (collected in 2018 and 2022) to identify key socio-economic and environmental factors influencing severe food insecurity, and to assess the potential role of agroforestry in mitigation. Results show persistently high food insecurity, with over 60% of households affected in both years. Households practicing crop diversification were less likely to experience severe food insecurity, while larger households were more vulnerable. Agroforestry-related variables did not show statistically significant effects in reducing food insecurity, suggesting that short-term interventions should prioritize improving socio-economic conditions and market-oriented crop production. Long-term agroforestry strategies should focus on integrating appropriate tree species and be evaluated through time-sensitive and experimental approaches to better understand their impact.
Tag: household surveys
Enhancing food Security through Agroforestry: A Case Study in Petit-Bondoukou, Nawa Region, Côte d’Ivoire
Ensuring food security in tropical regions presents significant challenges due to the competition between cash crop cultivation and food crop production. This study focuses on Petit-Bondoukou, a key cocoa-producing zone in Côte d’Ivoire, investigating food diets and evaluating the potential of agroforestry systems to mitigate food insecurity. All cocoa farmers engage in agroforestry as a national strategy to combat cocoa swollen shoot disease through diversification. Three distinct agroforestry systems, involving various plant associations, were implemented by cocoa farmers. The research compared households practicing agroforestry with those not practicing it. The surveyed households commonly consumed cooked and processed roots, tubers, cereals, vegetables, meat, and pulses. Notably, pounded yam with okra sauce exhibited the highest dry matter content (94.66%), while guava and pounded yam with palm nut sauce displayed acidic pH values (4.13 and 4.61, respectively). Nutritional analyses revealed distinct attributes; rice and eggplant sauce had the lowest lipid content (2.90%), whereas rice with peanut sauce provided the highest protein rate (16.16%). Apart from fruits, all foods exceeded the recommended daily energy intake. Households practicing agroforestry relied on their farms for roots, tubers, and cereals, reducing the need to purchase food. Among households not practicing agroforestry, 80% experienced food shortages, compared to only 35% of households practicing agroforestry. Households practicing agroforestry had a higher intake of meat and pulses, with these pulses primarily sourced from their farms. Additionally, households practicing agroforestry exhibited higher consumption of vegetables. A higher percentage of households practicing agroforestry (78.6%) were identified as food secure compared to households not practicing agroforestry (38.9%). Moreover, households practicing agroforestry exhibited superior food consumption scores. This research provides insights into the role of agroforestry in enhancing food security in tropical regions.
Environmental Income and Rural Livelihoods: A Global-Comparative Analysis
This paper presents results from a comparative analysis of environmental income from approximately 8000 households in 24 developing countries collected by research partners in CIFOR’s Poverty Environment Network (PEN). Environmental income accounts for 28% of total household income, 77% of which comes from natural forests. Environmental income shares are higher for low-income households, but di erences across income quintiles are less pronounced than previously thought. The poor rely more heavily on subsistence products such as wood fuels and wild foods, and on products harvested from natural areas other than forests. In absolute terms environmental income is approximately ve times higher in the highest income quintile, compared to the two lowest quintiles.
Quantifying the economic contribution of wild food harvests to rural livelihoods: A global-comparative analysis
This paper empirically quantifies and analyses (i) the economic contribution of wild foods to rural households, (ii) the household socio-economic, demographic, and geographical correlates of wild food income, and (iii) how wild foods can be better incorporated into integrative food security policies. We used household income data from 7975 households in 24 developing countries across three continents collected by the Poverty Environment Network (PEN). We found 77% of households to be engaged in wild food collection from forest and non-forest environments even though the share of wild food income in total household income was on average only 4%. Poorer households and households experiencing shocks derived higher income shares from wild foods. State land is the main source of forest-derived wild food income while private lands are most important for non-forest wild food income. Considerable regional variation in determinants and the direction of significant relationships indicate there is no one-size-fits-all approach to integrating wild foods into food and forest policies. However, our results reveal potential to increase household food security by integrating wild foods into national food policies in more customized ways.
Spectral Soil Analysis & Household Surveys – A Guidebook for Integration
This Guidebook is intended to be a reference for survey practitioners looking for guidance on integrating soil health testing in household and farm surveys. The role of soil in agrarian societies is nquestionable, yet the complex nature of soil makes it much more challenging to measure than agricultural inputs such as fertilizers or pesticides. Historically, household surveys either include subjective questions of farmer assessment or rely on national-level soil maps to control for land quality, if anything at all. Recent scientific advances in laboratory soil analysis—via spectral soil testing—have opened the door to more rapid, cost-effective objective measurement of soil health in household surveys. This guidebook explores the nascent possibility of integrating plot-level soil testing in household surveys through a presentation of results comparing various soil assessment methods and a step-by-step guide for practical implementation. In partnership with the World Agroforestry Centre (ICRAF), the Living Standards Measurement Study of the World Bank’s Development Data Group set out to validate (1) the feasibility of implementing spectral soil analysis in household surveys, and (2) the value of subjective farmer assessments of soil quality compared with objective measures in order to determinethe need for objective soil analysis, specifically in low-income, smallholder agricultural contexts. These objectives were met by implementing two methodological validation studies, one in Ethiopia and one in Uganda. In both studies, plot-level soil samples were collected following identical international best-practice field protocols and analyzed using wet chemistry and spectral analysis methods at ICRAF’s Soil-Plant Spectral Diagnostics Laboratory. Additionally, plot managers were administereda series of subjective questions that are often used to gauge soil health in national household surveys. These studies resulted in two uniquely rich datasets that allow for comparison of subjective indicators of soil quality against laboratory results. Both laboratory and subjective results can also be compared with publicly available geospatial data, as all plots were georeferenced.
Spectral Soil Analysis & Household Surveys – A Guidebook for Integration
This Guidebook is intended to be a reference for survey practitioners looking for guidance on integrating soil health testing in household and farm surveys. The role of soil in agrarian societies is nquestionable, yet the complex nature of soil makes it much more challenging to measure than agricultural inputs such as fertilizers or pesticides. Historically, household surveys either include subjective questions of farmer assessment or rely on national-level soil maps to control for land quality, if anything at all. Recent scientific advances in laboratory soil analysis—via spectral soil testing—have opened the door to more rapid, cost-effective objective measurement of soil health in household surveys. This guidebook explores the nascent possibility of integrating plot-level soil testing in household surveys through a presentation of results comparing various soil assessment methods and a step-by-step guide for practical implementation. In partnership with the World Agroforestry Centre (ICRAF), the Living Standards Measurement Study of the World Bank’s Development Data Group set out to validate (1) the feasibility of implementing spectral soil analysis in household surveys, and (2) the value of subjective farmer assessments of soil quality compared with objective measures in order to determinethe need for objective soil analysis, specifically in low-income, smallholder agricultural contexts. These objectives were met by implementing two methodological validation studies, one in Ethiopia and one in Uganda. In both studies, plot-level soil samples were collected following identical international best-practice field protocols and analyzed using wet chemistry and spectral analysis methods at ICRAF’s Soil-Plant Spectral Diagnostics Laboratory. Additionally, plot managers were administereda series of subjective questions that are often used to gauge soil health in national household surveys. These studies resulted in two uniquely rich datasets that allow for comparison of subjective indicators of soil quality against laboratory results. Both laboratory and subjective results can also be compared with publicly available geospatial data, as all plots were georeferenced.
Spectral Soil Analysis & Household Surveys – A Guidebook for Integration
This Guidebook is intended to be a reference for survey practitioners looking for guidance on integrating soil health testing in household and farm surveys. The role of soil in agrarian societies is nquestionable, yet the complex nature of soil makes it much more challenging to measure than agricultural inputs such as fertilizers or pesticides. Historically, household surveys either include subjective questions of farmer assessment or rely on national-level soil maps to control for land quality, if anything at all. Recent scientific advances in laboratory soil analysis—via spectral soil testing—have opened the door to more rapid, cost-effective objective measurement of soil health in household surveys. This guidebook explores the nascent possibility of integrating plot-level soil testing in household surveys through a presentation of results comparing various soil assessment methods and a step-by-step guide for practical implementation. In partnership with the World Agroforestry Centre (ICRAF), the Living Standards Measurement Study of the World Bank’s Development Data Group set out to validate (1) the feasibility of implementing spectral soil analysis in household surveys, and (2) the value of subjective farmer assessments of soil quality compared with objective measures in order to determinethe need for objective soil analysis, specifically in low-income, smallholder agricultural contexts. These objectives were met by implementing two methodological validation studies, one in Ethiopia and one in Uganda. In both studies, plot-level soil samples were collected following identical international best-practice field protocols and analyzed using wet chemistry and spectral analysis methods at ICRAF’s Soil-Plant Spectral Diagnostics Laboratory. Additionally, plot managers were administereda series of subjective questions that are often used to gauge soil health in national household surveys. These studies resulted in two uniquely rich datasets that allow for comparison of subjective indicators of soil quality against laboratory results. Both laboratory and subjective results can also be compared with publicly available geospatial data, as all plots were georeferenced.
Spectral Soil Analysis & Household Surveys – A Guidebook for Integration
This Guidebook is intended to be a reference for survey practitioners looking for guidance on integrating soil health testing in household and farm surveys. The role of soil in agrarian societies is nquestionable, yet the complex nature of soil makes it much more challenging to measure than agricultural inputs such as fertilizers or pesticides. Historically, household surveys either include subjective questions of farmer assessment or rely on national-level soil maps to control for land quality, if anything at all. Recent scientific advances in laboratory soil analysis—via spectral soil testing—have opened the door to more rapid, cost-effective objective measurement of soil health in household surveys. This guidebook explores the nascent possibility of integrating plot-level soil testing in household surveys through a presentation of results comparing various soil assessment methods and a step-by-step guide for practical implementation. In partnership with the World Agroforestry Centre (ICRAF), the Living Standards Measurement Study of the World Bank’s Development Data Group set out to validate (1) the feasibility of implementing spectral soil analysis in household surveys, and (2) the value of subjective farmer assessments of soil quality compared with objective measures in order to determinethe need for objective soil analysis, specifically in low-income, smallholder agricultural contexts. These objectives were met by implementing two methodological validation studies, one in Ethiopia and one in Uganda. In both studies, plot-level soil samples were collected following identical international best-practice field protocols and analyzed using wet chemistry and spectral analysis methods at ICRAF’s Soil-Plant Spectral Diagnostics Laboratory. Additionally, plot managers were administereda series of subjective questions that are often used to gauge soil health in national household surveys. These studies resulted in two uniquely rich datasets that allow for comparison of subjective indicators of soil quality against laboratory results. Both laboratory and subjective results can also be compared with publicly available geospatial data, as all plots were georeferenced.
Spectral Soil Analysis & Household Surveys – A Guidebook for Integration
This Guidebook is intended to be a reference for survey practitioners looking for guidance on integrating soil health testing in household and farm surveys. The role of soil in agrarian societies is nquestionable, yet the complex nature of soil makes it much more challenging to measure than agricultural inputs such as fertilizers or pesticides. Historically, household surveys either include subjective questions of farmer assessment or rely on national-level soil maps to control for land quality, if anything at all. Recent scientific advances in laboratory soil analysis—via spectral soil testing—have opened the door to more rapid, cost-effective objective measurement of soil health in household surveys. This guidebook explores the nascent possibility of integrating plot-level soil testing in household surveys through a presentation of results comparing various soil assessment methods and a step-by-step guide for practical implementation. In partnership with the World Agroforestry Centre (ICRAF), the Living Standards Measurement Study of the World Bank’s Development Data Group set out to validate (1) the feasibility of implementing spectral soil analysis in household surveys, and (2) the value of subjective farmer assessments of soil quality compared with objective measures in order to determinethe need for objective soil analysis, specifically in low-income, smallholder agricultural contexts. These objectives were met by implementing two methodological validation studies, one in Ethiopia and one in Uganda. In both studies, plot-level soil samples were collected following identical international best-practice field protocols and analyzed using wet chemistry and spectral analysis methods at ICRAF’s Soil-Plant Spectral Diagnostics Laboratory. Additionally, plot managers were administereda series of subjective questions that are often used to gauge soil health in national household surveys. These studies resulted in two uniquely rich datasets that allow for comparison of subjective indicators of soil quality against laboratory results. Both laboratory and subjective results can also be compared with publicly available geospatial data, as all plots were georeferenced.
Spectral Soil Analysis & Household Surveys – A Guidebook for Integration
This Guidebook is intended to be a reference for survey practitioners looking for guidance on integrating soil health testing in household and farm surveys. The role of soil in agrarian societies is nquestionable, yet the complex nature of soil makes it much more challenging to measure than agricultural inputs such as fertilizers or pesticides. Historically, household surveys either include subjective questions of farmer assessment or rely on national-level soil maps to control for land quality, if anything at all. Recent scientific advances in laboratory soil analysis—via spectral soil testing—have opened the door to more rapid, cost-effective objective measurement of soil health in household surveys. This guidebook explores the nascent possibility of integrating plot-level soil testing in household surveys through a presentation of results comparing various soil assessment methods and a step-by-step guide for practical implementation. In partnership with the World Agroforestry Centre (ICRAF), the Living Standards Measurement Study of the World Bank’s Development Data Group set out to validate (1) the feasibility of implementing spectral soil analysis in household surveys, and (2) the value of subjective farmer assessments of soil quality compared with objective measures in order to determinethe need for objective soil analysis, specifically in low-income, smallholder agricultural contexts. These objectives were met by implementing two methodological validation studies, one in Ethiopia and one in Uganda. In both studies, plot-level soil samples were collected following identical international best-practice field protocols and analyzed using wet chemistry and spectral analysis methods at ICRAF’s Soil-Plant Spectral Diagnostics Laboratory. Additionally, plot managers were administereda series of subjective questions that are often used to gauge soil health in national household surveys. These studies resulted in two uniquely rich datasets that allow for comparison of subjective indicators of soil quality against laboratory results. Both laboratory and subjective results can also be compared with publicly available geospatial data, as all plots were georeferenced.