The information contained in this publication is based on knowledge and understanding at the time of writing (June 2017) and may not be accurate, current or complete. The State of New South Wales (including the NSW Department of Industry), the author and the publisher take no responsibility, and will accept no liability, for the accuracy, currency, reliability or correctness of any information included in the document (including material provided by third parties). Readers should make their own inquiries and rely on their own advice when making decisions related to material contained in this publication. The product trade names in this publication are supplied on the understanding that no preference between equivalent products is intended and that the inclusion of a product name does not imply endorsement by the department over any equivalent product from another manufacturer.
Researcher(s) |
Scott Clark Jon Evans Neroli Graham Karl Moore Russell Pumpa Mark Richards |
---|---|
Year(s) | 2016 |
Contributor | Department of Primary Industries NSW |
Trial location(s) |
Lockhart, NSW, NSW
|
Further information | View external link |
To compare growth, development and yield of current commercial faba bean varieties and advanced breeding lines sown on two dates on a brown clay loam at Lockhart southern NSW.
•Across all varieties tested, there was no significant response to sowing time, which validates the current sowing window recommendation. Therefore, the optimum time to sow faba bean at Lockhart in 2016 was late April–mid May.
• PBA Nasma and Fiesta VF were the two highest yielding commercial varieties.
• The advanced breeding lines AF10089 and AF09169, developed by Pulse Breeding Australia (PBA) were significantly higher yielding than all other varieties.
• PBA Samira and Nura yielded significantly higher when sown on 18 May compared to 28 April.
• Crop lodging was significantly less for the 18 May sowing date.
• PBA Nasma flowered 17 and 14 days earlier than PBA Samira and PBA Zahra at 28 April, and eight and six days earlier at 18 May.
Randomised split plot design with sowing date in the main blocks and varieties in the sub-plots; three replications
Lead research organisation | N/A |
---|---|
Host research organisation | N/A |
Related program | N/A |
Acknowledgments |
Thank you to John Stevenson, manager Warrakirri Cropping, Lockhart for the support of pulse research through provision of the experiment site. Thank you to Karl Moore, Russell Pumpa, Scott Clark and Jon Evans for technical assistance and Dr Neroli Graham for biometric support. |
Other trial partners | Not specified |
Crop type | Grain Legume: Faba beans |
---|---|
Treatment type(s) |
|
Trial type | Experimental |
Trial design | Randomised,Replicated,Blocked |
Sow rate or Target density | 30 plants per square meter |
---|---|
Sowing machinery |
Direct drilled using a six-row cone air seeder on 240 mm row spacing using DBS tines and GPS auto-steer |
Sow date | SD1: 28 April SD2: 18 May |
Harvest date | 15 December 2016 |
Plot size | Not specified |
Plot replication | 3 |
Plot randomisation | yes |
Fertiliser |
75 kg/ha grain legume starter (N 0: P 13.8: K 0: S 6.1) placed 50 mm below the seed 150 g/ha sodium molybdate, 16 June |
Herbicide |
Commercial practices were used aiming for weed-free experiments, eliminating both weed competition and weed seed set Fallow weed control: Roundup DST® (470 g/L glyphosate) 743 mL/ha, water 100 L/ha (8 January) |
Fungicide |
Targeting chocolate spot (Botrytis fabae and B. cinerea) and ascochyta blight (Ascochyta fabae) |
Inoculant | Group F peat inoculant was mixed directly into an onboard water tank then pumped through micro tubes into each sowing furrow |
Other trial notes |
This research paper is an extract from the publication Southern NSW Research Results 2017, available at |
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.