Lincoln Agritech Limited

 

Lincoln Agritech is a leading edge research and development company with a track record in applying new and innovative engineering and science technologies in the primary, industrial and environmental sectors.

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Recent Submissions

  • A review of the effects of droplet size and flow rate on the chargeability of spray droplets in electrostatic agricultural sprays 

    Post, Scott; Roten, R. L. (American Society of Agricultural and Biological Engineers, 2018)
    The chargeability of liquid sprays is an important factor in determining the deposition efficiency of electrostatic pesticide sprays. The Rayleigh limit provides information on the maximum amount of charge a spray droplet ...

  • Flat-fan spray atomization model 

    Post, Scott; Hewitt, A. J. (American Society of Agricultural and Biological Engineers, 2018)
    In pesticide application, the lack of a suitable theoretical atomization model for flat-fan spray nozzles forces a reliance on empirical data and correlations, even for computational simulations. There is considerable ...

  • Export of nitrogen and phosphorus from artificially drained dairy pastures in the Hauraki Plains 

    Barkle, G.; Stenger, Roland; Moorhead, B.; McKelvey, T. (FLRC, 2017-02)
    This work forms part of the MBIE-funded Transfer Pathways Programme, which targets quantification of the pathway-specific transfers of nitrogen (N) and phosphorus (P) from the land to receiving waters, taking lag times and ...

  • A framework for understanding the linkages between land and water quality impacts 

    Tanner, C.; Muirhead, R.; Burger, D.; Carrick, S.; Close, M.; Monaghan, R.; Singh, S.; Srinivasan, M. S.; Stenger, Roland; Tipa, G. (Fertilizer and Lime Research Centre, 2017)
    Different soils, landscapes and water pathways vary at a range of spatial and temporal scales in their propensity to yield, transport and attenuate contaminants. This affects a land's suitability t various types and ...

  • Assessment of mixed sward using context sensitive convolutional neural networks 

    Bateman, Christopher; Fourie, Jaco; Hsiao, Jeffrey; Irie, Kenji; Heslop, A.; Hilditch, A.; Hagedorn, Michael; Jessep, B.; Gebbie, S.; Ghamkhar, K. (Frontiers Media S.A., 2020-02-27)
    Breeding higher yielding forage species is limited by current manual harvesting and visual scoring techniques used for measuring or estimation of biomass. Automation and remote sensing for high throughput phenotyping has ...

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