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Record W1994724451 · doi:10.1007/s10460-010-9264-z

Strengthening understanding and perceptions of mineral fertilizer use among smallholder farmers: evidence from collective trials in western Kenya

2010· article· en· W1994724451 on OpenAlexfundno aff
Michael Misiko, Pablo Tittonell, K.E. Giller, Paul Richards

Bibliographic record

VenueAgriculture and Human Values · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Innovations and Practices
Canadian institutionsnot available
FundersWageningen University and ResearchEuropean CommissionInternational Development Research CentreRockefeller Foundation
KeywordsFertilizerStrigaAgricultureSoil fertilityProductivityAgricultural productivityAgroforestryAgronomyBusinessAgricultural economicsEconomicsEnvironmental scienceBiologyEcologySoil waterEconomic growthSorghum

Abstract

fetched live from OpenAlex

It is widely recognized that mineral fertilizers must play an important part in improving agricultural productivity in western Kenyan farming systems. This paper suggests that for this goal to be realized, farmers’ knowledge must be strengthened to improve their understanding of fertilizers and their use. We analyzed smallholder knowledge of fertilizers and nutrient management, and draw practical lessons from empirical collective fertilizer-response experiments. Data were gathered from the collective fertilizer-response trials, through focus group discussions, by participant observation, and via in-depth interviews representing 40 households. The collective trials showed that the application of nitrogen (N) or phosphorous (P) alone was insufficient to enhance yields in the study area. The response to P on the trial plots was mainly influenced by incidences of the parasitic Striga weed, by spatial variability or gradients in soil fertility of the experimental plots, and by interactions with N levels. These results inspired farmer to design and conduct experiments to compare crop performance with and without fertilizer, and between types of fertilizers, or responses on different soils. Participating farmers were able to differentiate types of fertilizer, and understood rates of application and the roles of respective fertilizers in nutrient supply. However, notions were broadly generated by unsteady yield responses when fertilizers were used across different fertility gradients, association with high cost (especially if recommended rates were to be applied), association of fertilizer use with hybrids and certain crops, historical factors, among other main aspects. We identified that strengthening fertilizer knowledge must be tailored within existing, albeit imperfect, systems of crop and animal husbandry. Farmers’ perceptions cannot be changed by promoting more fertilizer use alone, but may require a more basic approach that, for example, encourages farmer experimentation and practices to enhance soil properties such as carbon build-up in impoverished local soils.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.151
GPT teacher head0.319
Teacher spread0.168 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations32
Published2010
Admission routes1
Has abstractyes

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