To maximise yield of new lentil varieties through the identification of optimum sowing dates and
stubble management strategies to aid in disease management and harvestability.
Early sown lentils were generally highest yielding, and average 12% higher yield than the late
PBA Blitz and CIPAL0501 showed the least sowing date response in the favourable 2010
Retaining barley stubble at 2t/ha was capable of increasing yield and delaying maturity.
Stubble retention improved yields at all sowing dates, while standing stubble was most
important for grain yield at the later sowing date.
Lead research organisation
Department of Primary Industries VIC
Host research organisation
Trial funding source
Trial funding source
Trial funding source
Trial funding source
Southern Pulse Agronomy
Research staff: Jason Brand, Luke Gaynor, Mick Lines, Larn McMurray, Jenny Davidson, Andrew Ware, Trent Potter, Peter Matthews, Jason Ellifson, Justine Ellis, Gerard O’Connor, John Furner, Leigh Davis.
Co-operating staff: Russel Argall, Jenny Briggs, Jan Edwards, Matt Newell.
Industry Collaborators: Michael Materne and Tony Leonforte, Pulse Breeding Australia, DPI – Horsham Victoria; Kristy Hobson, Pulse Breeding Australia, DPI – Tamworth NSW; Jeff Paull, Pulse Breeding Australia, University of Adelaide South Australia; Wayne Hawthorne and Trevor Bray, Pulse Australia.
We are grateful for the support we receive from the numerous commercial agronomists and seed commercialising companies.
Other trial partners
Pulse Breeding Australia, The University of Adelaide, Pulse Australia
Trial source data and summary not available Check the trial report PDF for trial results.
Derived climate information
No observed climate data available for this trial. Derived climate data is determined from trial site location and national weather sources.
SILO weather estimates sourced from https://www.longpaddock.qld.gov.au/silo/
Jeffrey, S.J., Carter, J.O., Moodie, K.B. and Beswick, A.R. (2001). Using spatial interpolation to construct a comprehensive archive of Australian climate data , Environmental Modelling and Software, Vol 16/4, pp 309-330. DOI: 10.1016/S1364-8152(01)00008-1.
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