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Precision Agriculture using ICT
Last registered on October 03, 2016


Trial Information
General Information
Precision Agriculture using ICT
Initial registration date
October 03, 2016
Last updated
October 03, 2016 10:55 AM EDT
Primary Investigator
Other Primary Investigator(s)
Additional Trial Information
Start date
End date
Secondary IDs
This is a randomized-controlled trial that I am currently running with One Acre Fund. This study seeks to understand if heterogeneity in underlying agronomic conditions is a barrier to adoption of agricultural inputs that are widely understood to have high returns. Suri and Tjernström find evidence for this heterogeneity in both fertilizer and seeds, respectively. To address this heterogeneity, a mobile phone information system will disseminate location-specific agricultural advice to farmers based on statistically interpolated soil chemistry content. This intervention leverages technological scale in two ways: (1) using geospatial statistics and modern machine learning techniques to turn a relatively small number of expensive soil tests into a predictive map of continuous soil characteristics, and (2) scaling the dissemination of this precise information over the mobile phone in a way that would be cost prohibitive for human extension agents. Previous research by Casaburi and Cole have found mobile phones to be an effective medium to disseminate agricultural advice to positively affect farmer behavior.
One Acre Fund has been doing soil tests in all areas of operation to better understand what inputs would be most appropriate for their farmers. Several thousand soil tests are performed using soil spectroscopy (<$1 per sample) which are calibrated using Random Forests with a 10% percent sample of wet chemistry tests ($10-$50 per sample). These soil chemistry results can then be interpolated using Kriging to create a continuous field of soil chemistry predictions. Some of these soil properties interpolate better than others. We can reliably spatially interpolate nitrogen and potassium but have a difficult time explaining variation in phosphorus spatially. This is evident in the semi-variograms produced when estimating the parameters for the Kriging procedure.
Soil acidity (pH) is one characteristic that is spatially well-interpolated and happens to be a major issue for farmers in western Kenya. Under a critical threshold (pH < 5.5), the maize plant will suffer from aluminum photo-toxicity. High acidity also inhibits the absorption of other beneficial nutrients that affect plant growth. This can be remedied by the application of agricultural lime (ground limestone) to the soil and was the key to ending rural poverty and unlocking the green revolution in rural Brazil with similar soils. Agricultural trials run by One Acre Fund sees yield increases of up to 40% by microdosing agricultural lime. Despite this high return and the low cost of agricultural lime, there is very low uptake of agricultural lime (<2%). Our interpolated soil maps show a fairly high degree of variation in soil pH which makes agricultural lime hugely profitable in some areas but less so in others.
This trial seeks to provide this information at scale, targeting poor farmers with specific lime application recommendations over the mobile phone. There is a group of ~4000 One Acre Fund farmers who will be randomly assigned into treatment or control. The control group will receive no messaging and the treatment group will receive messages with location-specific recommendations for the application of agricultural lime or a general recommendation to use lime. These messages will be sent this month (August 2016). In September, farmers will choose which agricultural products they will purchase from One Acre Fund, including the uptake of lime. We will compare the appropriate uptake of agricultural lime in the treatment group with the control group controlling for information spillovers and group leader effects.
External Link(s)
Registration Citation
On, Robert. 2016. "Precision Agriculture using ICT." AEA RCT Registry. October 03. https://doi.org/10.1257/rct.1574-1.0.
Former Citation
On, Robert. 2016. "Precision Agriculture using ICT." AEA RCT Registry. October 03. http://www.socialscienceregistry.org/trials/1574/history/10977.
Experimental Details
SMS providing targeted lime recommendations to farmers in Nambale District in Busia County. One SMS is geo-targeted at the farmer, the other is a general nudge to use lime.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Adoption of agricultural lime offered by One Acre Fund.
Primary Outcomes (explanation)
One Acre Fund takes orders for agricultural inputs every year in Kenya. This is the outcome variable.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
RCT randomizing SMS messages to farmers. 1/3 will be control, 1/3 will receive a general SMS recommendation to adopt lime, 1/3 will receive a geo-targeted SMS recommendation to adopt lime.
Experimental Design Details
Randomization Method
Randomization Unit
Individual farmer.
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
Control: 1578
T1: 1697
T2: 1655
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Power=0.8, alpha=0.05 Control vs T1+T2: 7.58953% difference in adoption Control vs T1: 8.75019% difference in adoption Control vs T2: 8.697624% difference in adoption T1 vs T2: 9.679689% difference in adoption
IRB Name
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)