Literature DB >> 24816925

The role of precision agriculture for improved nutrient management on farms.

Carolyn Hedley1.   

Abstract

Precision agriculture uses proximal and remote sensor surveys to delineate and monitor within-field variations in soil and crop attributes, guiding variable rate control of inputs, so that in-season management can be responsive, e.g. matching strategic nitrogen fertiliser application to site-specific field conditions. It has the potential to improve production and nutrient use efficiency, ensuring that nutrients do not leach from or accumulate in excessive concentrations in parts of the field, which creates environmental problems. The discipline emerged in the 1980s with the advent of affordable geographic positioning systems (GPS), and has further developed with access to an array of affordable soil and crop sensors, improved computer power and software, and equipment with precision application control, e.g. variable rate fertiliser and irrigation systems. Precision agriculture focusses on improving nutrient use efficiency at the appropriate scale requiring (1) appropriate decision support systems (e.g. digital prescription maps), and (2) equipment capable of varying application at these different scales, e.g. the footprint of a one-irrigation sprinkler or a fertiliser top-dressing aircraft. This article reviews the rapid development of this discipline, and uses New Zealand as a case study example, as it is a country where agriculture drives economic growth. Here, the high yield potentials on often young, variable soils provide opportunities for effective financial return from investment in these new technologies.
© 2014 Society of Chemical Industry.

Entities:  

Keywords:  GPS; nutrient management; precision agriculture; sensors; variable rate technology

Mesh:

Substances:

Year:  2014        PMID: 24816925     DOI: 10.1002/jsfa.6734

Source DB:  PubMed          Journal:  J Sci Food Agric        ISSN: 0022-5142            Impact factor:   3.638


  7 in total

Review 1.  Priorities for science to overcome hurdles thwarting the full promise of the 'digital agriculture' revolution.

Authors:  Mark Shepherd; James A Turner; Bruce Small; David Wheeler
Journal:  J Sci Food Agric       Date:  2018-10-22       Impact factor: 3.638

Review 2.  A Bibliometric Network Analysis of Recent Publications on Digital Agriculture to Depict Strategic Themes and Evolution Structure.

Authors:  Michele Kremer Sott; Leandro da Silva Nascimento; Cristian Rogério Foguesatto; Leonardo B Furstenau; Kadígia Faccin; Paulo Antônio Zawislak; Bruce Mellado; Jude Dzevela Kong; Nicola Luigi Bragazzi
Journal:  Sensors (Basel)       Date:  2021-11-26       Impact factor: 3.576

3.  CubeSat constellations provide enhanced crop phenology and digital agricultural insights using daily leaf area index retrievals.

Authors:  Kasper Johansen; Matteo G Ziliani; Rasmus Houborg; Trenton E Franz; Matthew F McCabe
Journal:  Sci Rep       Date:  2022-03-28       Impact factor: 4.379

4.  Capability of the TrueColor Sensor Array for Determining the Nitrogen Supply in Winter Barley (Hordeum vulgare L.).

Authors:  Andreas Christ; Oliver Schmittmann; Peter Schulze Lammers
Journal:  Sensors (Basel)       Date:  2022-08-12       Impact factor: 3.847

5.  Optimization of Management Zone Delineation for Precision Crop Management in an Intensive Farming System.

Authors:  Yifan Yuan; Bo Shi; Russell Yost; Xiaojun Liu; Yongchao Tian; Yan Zhu; Weixing Cao; Qiang Cao
Journal:  Plants (Basel)       Date:  2022-10-04

6.  Distributions of emissions intensity for individual beef cattle reared on pasture-based production systems.

Authors:  G A McAuliffe; T Takahashi; R J Orr; P Harris; M R F Lee
Journal:  J Clean Prod       Date:  2018-01-10       Impact factor: 9.297

Review 7.  A New Zealand Perspective on the Application and Regulation of Gene Editing.

Authors:  Steffi Fritsche; Charleson Poovaiah; Elspeth MacRae; Glenn Thorlby
Journal:  Front Plant Sci       Date:  2018-09-12       Impact factor: 5.753

  7 in total

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