ArticleRSC advances2024
Low-cost precision agriculture for sustainable farming using paper-based analytical devices.
Article in RSC advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Embodied Intelligence for Soil Health toward Sustainable Smart Agriculture: Sensing the Soil with Flexible Geotextiles Sensors.Global challenges (Hoboken, NJ) · 2026Review
- Dataset of near-infrared (NIR) spectral data for prediction of organic matter and total carbon in agricultural soil using homemade NIR spectrometer.Data in brief · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The United Nations estimates that by 2030, agricultural production must increase by 70% to meet food demand. Precision agriculture (PA) optimizes production through efficient resource use, with soil fertility being crucial for nutrient supply. Traditional nutrient quantification methods are costly and time-consuming. This study introduces a rapid (15 min), user-friendly, paper-based platform for determining four essential macronutrients-nitrate, magnesium, calcium, and ammonium-using colorimetric methods and a smartphone for data reading and storage. The sensor effectively detects typical soil nutrient concentrations, showing strong linearity and adequate detection limits. For nitrate, the RGB method resulted in an
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.