| Researcher(s) |
Sean Bithell (NSW DPI) Steven Harden (NSW DPI) Kristy Hobson (NSW DPI) Willy Martin (QLD DAF) Alan McKay (SARDI) Kevin Moore (NSW DPI) |
|---|---|
| Year(s) | 2015 |
| Contributor | Department of Primary Industries NSW |
| Trial location(s) |
Warwick, QLD
|
| Further information | View external link |
To predict the risk of PRR disease and potential yield losses in chickpea, and detect P. med inoculum in soil from commercial paddocks.
Key findings:
Summary
P.med inoculum level, PRR disease and yield
Can the P.med DNA soil test predict the risk of Phytophthora root rot? Based on the results of this trial with Yorker (MR) and the 2014 Tamworth trial with Sonali (S), the answer is YES. For Yorker significant yield loss can be expected with starting (pre-sow sampling) inoculum levels above ca 3000 P.med DNA sequences/g soil (ca 130 oospores/plant). However, these values may need to be interpreted with some caution as seasonal conditions will modify outcomes, for instance in a dry season less disease may develop from the same amount of inoculum.
As Phytophthora can reproduce rapidly and cause new infections over a relatively short period there was concern that under PRR conducive conditions (a wet season), that low initial levels of inoculum could catch up to high initial levels as cause similar disease severity and yield loss. The 2015 season was wet but not very wet, under these conditions there was separation in the disease and yields of the low and high inoculum treatments.
P.med DNA detection in commercial in paddocks and disease risk determination
These second season of detection capability results for the soil P.med DNA test were again generally promising, with most samples with positive and negative P.med DNA results corresponding to expected P.med isolation results. However, results for some samples indicate that further work is required to a) identify what factors may contribute to false negative results and b) determine if false positives are due to the presence of dead or inactive P.med DNA
The DNA result for a soil sample from a paddock can only provide an indication of inoculum concentration and disease risk for the areas of the paddock which were sampled. Therefore, the spread and locations of sampling across a paddock will affect how representative DNA results are for a paddock. Because of the risk of rapid PRR disease buildup following wet conditions it may be appropriate to treat a negative Predicta B® test result as indicating a low risk rather than a nil risk, as the pathogen could still be in areas of the paddock that were not sampled and so still cause PRR and reduce yield.
Work in 2016 will evaluate maximising the probability of detecting P. med by targeting those areas of the paddock where P.med is more likely to occur. The pathogen thrives in high soil moisture contents and so often occurs in low lying regions of paddocks where pooling following rain may occur. The pathogen also carries over from season to season on infected chickpea volunteers, lucerne and, native medics. Including low lying areas and weedy areas of paddocks during PreDicta B® soil sampling may provide the best strategy to detecting P. med and so identifying a paddocks disease risk of PRR in chickpea.
| Lead research organisation |
Department of Primary Industries NSW |
|---|---|
| Host research organisation | N/A |
| Trial funding source | GRDC DAN00172,DAS00137 |
| Trial funding source | DPI NSW |
| Related program |
National improved molecular diagnostics for disease management, and Managing Crop Disease – Improving chickpea pathogen resistance |
| Acknowledgments |
This research was co-funded by NSW DPI and GRDC under projects DAN00172: Managing Crop Disease – Improving chickpea pathogen resistance (PRR) and DAS00137: National improved molecular diagnostics for disease management. Thanks to Gail Chiplin (NSW DPI) and Kris King (QDAF) for technical support. The co-operation of growers and advisers in facilitating soil sample collection from their paddocks is also greatly appreciated. |
| Other trial partners | Not specified |
| Crop type | Grain Legume: Chickpeas |
|---|---|
| Treatment type(s) |
|
| Trial type | Experimental |
| Trial design | Replicated |
| Sow date | 10 June 2015 |
|---|---|
| Harvest date | Not specified |
| Plot size | 5m x 2.1m |
| Plot replication | 5 |
| Other trial notes |
Treatments Disease development and yield loss prediction Inoculum treatments: 0, 40, 130 and 660 P. med oospores per plant applied at sowing Irrigation treatments: in-crop supplementary irrigation, dryland Inoculum detection: Soil samples from 43 paddocks and one P. med control sample RESULTS: • Post sowing soil P.med DNA results differed significantly among the oospore treatments but also indicated that some P.med was already present at the site . • On 13 Oct (end of flowering), the irrigated 130 and 660 oospores/plant treatments had significantly more PRR than the dryland 130 and 660 oospores/plant treatments . By 12 Nov (dryland treatments senescing), the irrigated 40, 130 and 660 oospores/plant treatments had significantly more PRR than the dryland 40, 130 and 660 oospores/plant treatments. • The interaction of irrigation (to simulate a PRR conducive season) and oospore treatments on grain yield was complex as indicated by :
These interactions suggest that at low PRR levels, the primary effect of irrigation is on yield, but at high PRR levels the primary effect is on disease. However, the shape of these relationships are likely to vary from season to season due to differences in seasonal rainfall P.med DNA detection in soil from commercial paddocks • Ten of the 43 paddock soil treatments produced PRR like cankers on plants, P.med like cultures were isolated from eight samples from growers paddocks; P.med like cultures were also isolated from the control soil, giving a total of nine P.med isolates. One of the samples produced cankers that were not caused by P.med. • Of the 43 paddock soil treatments (including the control soil), nine had positive P.med DNA results. Comparing the DNA results to the isolation results showed that most (8/9, 89%) samples which had positive DNA results also yielded P.med cultures and that most (33/34, 97%) samples which had negative DNA results also did not yield P.med cultures . • Notably, one sample (LOU2) which yielded a P.med culture was negative for P.med DNA. • One sample (A) was positive for P.med DNA but seedlings in all 5 cups remained healthy. This sample had a lower P.med DNA value (1,234 P.med copies/g soil) than other samples (range 2,443-813,436 P.med copies/g soil). Possible explanations for this result is: (i) more time may be required for symptoms to develop, or (ii) that the pathogen had died but some DNA had been detected. |
| # |
Treatment 1
|
Grain yield (t/ha) | Phytophthora concentration (DNA/g soil) |
|---|---|---|---|
| 1 | █ Dryland - 1 | 3198 | 342 |
| 2 | █ Dryland - 40 | 2961 | 1986 |
| 3 | █ Dryland - 130 | 3038 | 3051 |
| 4 | █ Dryland - 660 | 2402 | 5357 |
| 5 | █ Irrigation - 0 | 3914 | 169 |
| 6 | █ Irrigation - 40 | 3631 | 1765 |
| 7 | █ Irrigation - 130 | 2966 | 2996 |
| 8 | █ Irrigation - 660 | 1764 | 5925 |
| Rainfall trial gsr (mm) | 160mm |
|---|
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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