Yield sensing technologies for horticultural crops: a short review

In: Precision agriculture '19
Authors:
L. Longchamps .Agriculture and Agri-Food Canada, 430 Gouin blvd., St-Jean-sur-Richelieu, QC, J3B 3E6, Canada.

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B. Panneton .Agriculture and Agri-Food Canada, 430 Gouin blvd., St-Jean-sur-Richelieu, QC, J3B 3E6, Canada.

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S. Fountas Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece.

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R. Khosla Colorado State University, 307 University Ave, Fort Collins, CO 80521, USA.

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Type:
Chapter
Pages:
589–595
DOI:
https://doi.org/10.3920/978-90-8686-888-9_73

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Few yield monitoring systems exist for horticultural crops. Yield maps can play an important role in the advent of big data in agriculture. The majority of horticultural crops are hand harvested and are diverse, which complicates the development of yield monitoring systems for such crops. Commercial systems for real time yield monitoring of horticultural crops involve use of load cells, which require further improvement to provide information on crop quality and noise filtration. Other technologies covered in this short literature review include machine vision, capacitance, RFID, ultra-wide radar systems and LIDAR for the purpose of yield monitoring of horticultural crops.

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Cover Precision agriculture '19
E-Book ISBN:
9789086868889
Publisher:
Wageningen Academic
Print Publication Date:
08 Jul 2019
Front Matter
Section 1 – Precision agriculture
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Section 2 – Precision horticulture
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Section 3 – Precision viticulture
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Section 4 – Precision crop protection
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Section 5 – Proximal and remote sensing of soil and crop
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Section 6 – Applications of unmanned aerial systems
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Section 7 – Satellite-based applications for precision agriculture
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Section 8 – Site-specific nutrient, lime and seed management
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Section 9 – Site-specific canopy and harvest quality
Section 10 – Precision pasture management
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Section 11 – Drainage optimization and variable rate irrigation
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Section 12 – Geostatistics, mapping and spatial data analysis
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Section 13 – Robotics, guidance and automation
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Section 14 – Economics of precision agriculture
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Section 15 – Adoption of precision agriculture
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Section 16 – Small farms/small holders and precision agriculture
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Section 17 – On farm experimentation with site-specific technologies
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Section 18 – Software and mobile apps for precision agriculture
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Section 19 – Decision support for precision agriculture
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Section 20 – Data mining for precision agriculture
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Back Matter

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