NEW UPDATE: Completed trials may now upload and register supplementary documents (e.g. null results reports, populated pre-analysis plans, or post-trial results reports) in the Post Trial section under Reports, Papers, & Other Materials.
Alleviating Constraints to Adoption of Improved Soil Fertility Management
Last registered on April 29, 2016


Trial Information
General Information
Alleviating Constraints to Adoption of Improved Soil Fertility Management
Initial registration date
April 22, 2016
Last updated
April 29, 2016 12:34 AM EDT
Primary Investigator
Other Primary Investigator(s)
PI Affiliation
UC Berkeley
Additional Trial Information
In development
Start date
End date
Secondary IDs
Smallholder farmers in low income countries often invest a large proportion of their production costs in fertilizer, however returns on this investment can be highly variable and maximum potential productivity gains are very rarely achieved (Beaman et al. 2013; Duflo et al. 2008; Suri 2011). Experimental evidence points to the need for balanced nutrient application in order to maximize the efficiency of each synthetic compound (Das et al. 2009). However in order to effectively optimize fertilizer use efficiency, targeted advice needs to be generated at the individual level based on current soil fertility status as well as the nutrient demands of the cropping system (Das et al. 2009). At present, most farmers rely on blanket fertilizer recommendations which fails to account for this variability. The emphasis on nitrogen based fertilizers also implies that the supply chains for other nutrients have not been well established. As a result even if farmers had the knowledge allowing them to adopt more effective fertilizer application practices, appropriate and timely supply of fertilizer may still remain a major constraint. Here we will investigate the constraints to adoption of a new affordable automated system for delivering balanced fertilizer recommendations as compared to government soil testing laboratories.
External Link(s)
Registration Citation
Butler, A and Aprajit Mahajan. 2016. "Alleviating Constraints to Adoption of Improved Soil Fertility Management." AEA RCT Registry. April 29. https://doi.org/10.1257/rct.1200-2.0.
Former Citation
Butler, A, A Butler and Aprajit Mahajan. 2016. "Alleviating Constraints to Adoption of Improved Soil Fertility Management." AEA RCT Registry. April 29. http://www.socialscienceregistry.org/trials/1200/history/8004.
Experimental Details
The intervention to be piloted is the provision of fertilizer recommendations using both the automated NE system and a soil testing laboratory facility with and without time bound procurement of fertilizer to smallholder farmers in the state of Madhya Pradesh India. We will conduct the intervention during the winter (Rabi) growing season, as 80% of farmers cultivate wheat as the dominant crop and would therefore benefit from NE recommendations.
There are costs and benefits to these two alternative recommendation systems which need to be better understood. The automated NE system, is cheap and easily deployed in the field and can therefore reach a lot more clients in a shorter period of time. However the system focuses on the dynamic requirements of macro nutrients (N:P:K) throughout the growing season, while neglecting potential deficiencies in micro nutrients. In contrast, the soil testing laboratories are able to provide extremely accurate nutrient requirement, including micro nutrients. However, farmers must incur the cost of getting their soil tested. A comparison of these two alternative solution will provide us with valuable information on potential adoption rates, as well as the relative benefits to productivity.
Farmers in Madhya Pradesh commonly take out a loan from government cooperatives and purchase fertilizer within the same transaction. However, their choice of fertilizer is limited to those supplied at the cooperative outlet, which is in turn driven by coarse government recommendations. At the time of delivering our recommendations we will give the farmers a service through which we would source and deliver the precise recommended fertilizers in a timely manner. This should ease any existing market inefficiencies that may be restricting adoption.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Following the intervention we will conduct a short household survey. The household questionnaire will collect information on agricultural production decisions (crop choices, labour allocation, input purchases, and fertilizer use), yield, income, consumption and expenditure. A comparison of differences in take-up rates between different treatment households will provide information on the extent to which both information and market inefficiencies are a constraint to adopt of improved soil fertility management.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
This pilot study has two principle treatment arms. The first will be given NE fertilizer recommendations, while the other will be given recommendations from a soil testing laboratory. Within each of the two treatment groups a random half the farmers will be offered a guarantee of time bound fertilizer procurement.
Experimental Design Details
Randomization Method
Randomization will be done in the office by a computer.
Randomization Unit
Randomization will be done at the village level
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
20 villages
Sample size: planned number of observations
500 farmers
Sample size (or number of clusters) by treatment arms
We will target 20 randomly selected villages for the pilot, of which 8 (200 farmers) will be given NE fertilizer recommendations, 8 (200 farmers) will be given recommendations from a soil testing laboratory, and 4 (100 farmers) will be given no recommendations. Within each of the two treatment groups half the villages will be offered a guarantee of time bound fertilizer procurement.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
The Committee for Protection of Human Subjects (CPHS)
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)