Literature DB >> 16919932

In situ determination of slurry nutrient content by electrical conductivity.

G Provolo1, L Martínez-Suller.   

Abstract

Land application of animal slurries has both agronomic and environmental implications. It can be supported by the quantification of available nutrients in the field. A prototype device for indirect measurement of the nutrient content of slurry based on electrical conductivity (EC) was calibrated on manure samples collected from farms with different livestock typologies. The resulting correlations between EC and nutrient contents of slurries from laboratory analyses have shown good agreement (r(2) from 0.73 to 0.95) with total and ammoniacal nitrogen and, with some exception, Potassium, but failed to demonstrate any significant relationship with total phosphorous. The mean errors obtained using the device in field conditions for nitrogen content were always lower or equal to 10%, while the standard deviations were 12-13% for pig and calf slurries, and 20-21% for dairy cow slurry. The results obtained suggest that the equipment, provided the regression line used to convert EC readings to nutrient contents is related to the livestock typology under observation, can provide good support to practical slurry spreading, even though it does not reach an accuracy comparable to laboratory methods and does not give reliable information on phosphorus.

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Year:  2006        PMID: 16919932     DOI: 10.1016/j.biortech.2006.07.018

Source DB:  PubMed          Journal:  Bioresour Technol        ISSN: 0960-8524            Impact factor:   9.642


  2 in total

1.  Reflections and Methodological Proposals to Treat the Concept of "Information Precision" in Smart Agriculture Practices.

Authors:  Fabrizio Mazzetto; Raimondo Gallo; Pasqualina Sacco
Journal:  Sensors (Basel)       Date:  2020-05-17       Impact factor: 3.576

2.  Evaluating the Feasibility of a Low-Field Nuclear Magnetic Resonance (NMR) Sensor for Manure Nutrient Prediction.

Authors:  Xiaoyu Feng; Rebecca A Larson; Matthew F Digman
Journal:  Sensors (Basel)       Date:  2022-03-22       Impact factor: 3.576

  2 in total

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