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Autor: Jordan Chamberlin
Miet Maertens Oyakhilomen Oyinbo Tahirou Abdoulaye Jordan Chamberlin (2023)
There is growing evidence on the impacts of site-specific nutrient management (SSNM) from Asia. The evidence for Sub-Saharan Africa (SSA), where SSNM developments are more recent and where conditions concerning soil fertility and fertilizer use differ importantly from those in Asia, is extremely scarce. We evaluate a SSNM advisory tool that allows extension agents to generate fertilizer recommendations tailored to the specific situation of an individual farmer’s field, using a three-year randomized controlled trial with 792 smallholder farmers in the maize belt of northern Nigeria. Two treatment arms were implemented: T1 and T2 both provide SSNM information on nutrient use and management, but T2 provides additional information on maize price distributions and the associated variability of expected returns to fertilizer use. We estimate average and heterogenous intent-to-treat effects on agronomic, economic and environmental plot-level outcomes. We find that T1 and T2 lead to substantial increases (up to 116%) in the adoption of good fertilizer management practices and T2 leads to incremental increases (up to 18%) in nutrient application rates, yields and revenues. Both treatments improve low levels of nutrient use efficiency and reduce high levels of greenhouse gas emission intensity, after two years of treatment. Our findings underscore the possibility of a more gradual and sustainable intensification of smallholder agriculture in SSA, as compared with the Asian Green Revolution, through increased fertilizer use accompanied by improved fertilizer management.
Artículo
Randomized Controlled Trial CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA TECHNOLOGY ADOPTION AGRICULTURAL EXTENSION GREEN REVOLUTION FERTILIZERS GREENHOUSE GAS EMISSIONS
TAMASA Nigeria. Agronomy Panel Survey 2016. Crop cut data
Oyakhilomen Oyinbo Jordan Chamberlin Julius Adewopo (2017)
This data covers the crop aspect of the Agronomy Panel Survey (APS) implemented in 99 selected communities across 17 LGAs in 22 randomly selected 10km x 10 km sampling grids from Kano, Kaduna and Katsina States. The XLS file has tabs for Metadata, Variables, Data and Data history.
Dataset
Smallholder maize yield estimation using satellite data and machine learning in Ethiopia
Zhe Guo Jordan Chamberlin Liangzhi You (2023)
The lack of timely, high-resolution data on agricultural production is a major challenge in developing countries where such information can guide the allocation of scarce resources for food security, agricultural investment, and other objectives. While much research has suggested that remote sensing can potentially help address these gaps, few studies have indicated the immediate potential for large-scale estimations over both time and space. In this study we described a machine learning approach to estimate smallholder maize yield in Ethiopia, using well-measured and broadly distributed ground truth data and freely available spatiotemporal covariates from remote sensing. A neural networks model outperformed other algorithms in our study. Importantly, our work indicates that a model developed and calibrated on a previous year's data could be used to reasonably estimate maize yield in the subsequent year. Our study suggests the feasibility of developing national programs for the routine generation of broad-scale and high-resolution estimates of smallholder maize yield, including seasonal forecasts, on the basis of machine learning algorithms, well-measured ground control data, and currently existing time series satellite data.
Artículo
Sentinel-2 Smallholder Agriculture Yield Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA INTENSIFICATION SMALLHOLDERS AGRICULTURE YIELD FORECASTING
Testing innovations for adoption of newer and more adapted maize varieties
Michael Ndegwa Pieter Rutsaert Jason Donovan Jordan Chamberlin (2023)
Objeto de congreso
Changing Production Conditions Genetic Innovations Maize Hybrids CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA TESTING MAIZE VARIETIES YIELDS FARMERS EXPERIMENTATION
Near-real-time welfare and livelihood impacts of an active war: Evidence from Ethiopia
Kibrom Abay Guush Berhane Jordan Chamberlin Mehari Hiluf Abay (2023)
Ethiopia recently experienced a large-scale war that lasted for more than two years. Using unique High-Frequency Phone Survey (HFPS) data, which span several months before and after the outbreak of the war, this paper provides evidence on the immediate impacts of the conflict on households’ food security. We also assess potential mechanisms and evaluate impacts on proximate outcomes, including on livelihood activities and access to food markets. We use difference-in-differences and two-way fixed effects estimation to compare trends across affected and unaffected regions (households) and before and after the outbreak of the war. Seven months into the conflict, we find that the war was associated with a 37 percentage points increase in the probability of moderate to severe food insecurity. Using the Armed Conflict Location and Event Data (ACLED), we show that exposure to an additional battle leads to a 1 percentage point increase in the probability of moderate or severe food insecurity. The conflict was associated with significant reduction in access to food through supply chain disruptions and by curtailing non-farm livelihood activities. Non-farm and wage related activities were affected the most, whereas farming activities were relatively more resilient. Our estimates, which likely underestimate the true average effects on the population, constitute novel evidence on the near-real-time impacts of large-scale conflict. Our work highlights the potential of HFPS to monitor active and large-scale conflicts, especially in contexts where conventional data sources are not immediately available.
Artículo
Phone Surveys CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WAR CONFLICTS FOOD SECURITY LIVELIHOODS
TAMASA Ethiopia. Agronomy Panel Survey 2016. Yield, soil and agronomy data
MESFIN KEBEDE DESTA Jordan Chamberlin Tolera Abera Goshu (2017)
Data from crop-cuts as part of the Agronomy Panel Survey (APS) implemented in Oromia in three Zones (East Wollega, West Showa and Jimma). The APS included 16 peasant associations and 76 communities across the western part of Ethiopia in 56 randomly selected 1 X 1 km areas from eight 10km x 10 km sampling grids. Replicated crop cuts were made on farmers maize fields and yield measured. Soil samples were also collected but have not been analysed yet.
Dataset
TAMASA Ethiopia. Agronomy Panel Survey 2016. Yield, soil and agronomy data
MESFIN KEBEDE DESTA Jordan Chamberlin Tolera Abera Goshu (2017)
Data from crop-cuts as part of the Agronomy Panel Survey (APS) implemented in Oromia in three Zones (East Wollega, West Showa and Jimma). The APS included 16 peasant associations and 76 communities across the western part of Ethiopia in 56 randomly selected 1 X 1 km areas from eight 10km x 10 km sampling grids. Replicated crop cuts were made on farmers maize fields and yield measured. Soil samples were also collected but have not been analysed yet.
Dataset