Successful management of colletotrichum crown and stolon rot in runner production in sub-tropical Australia

Crown, stolon, and petiole rots caused by Colletotrichum gloeosporioides (C.g.) were first identified in runner beds of the Queensland Approved Runner Scheme (QARS) in February 1989. The outbreaks occurred annually from 1990 to 1994. Minor losses in subsequent fruit crops occurred from 1990 to 1993, with 50% post-establishment losses occurring on fruit farms in southeast Queensland in 1994. The objective of this work was to provide a control strategy for the disease that would give stability to the QARS. Runner-bed trials in 1993-1994 showed that Octave® (462 g/kg prochloraz as the MnCl2 complex) was highly effective in reducing the incidence field symptoms and laboratory recovery of C.g. from symptomless petioles. A simple detached petiole laboratory test for measuring fungicide efficacy in runner bed trials and for laboratory screening of fungicides, is described. Scheme protocols were changed to require that only foundation plants from tissue culture were allowed onto QARS sites. These were to be symptomless and to have tested negative for the presence of C.g. The application of Octave® at fortnightly intervals in all QARS nurseries has reduced the level of visible symptoms and the laboratory recovery of C.g. from symptomless petioles to almost zero.

Testing insecticides against Phthorimaea operculella (Zeller) (Lepidoptera: Gelechiidae) using a tomato plant bioassay

A bioassay technique was developed to test the efficacy of insecticides against potato moth (Phthorimaea operculella (Zeller)) on tomatoes. The technique tested efficacy against both larvae in mines and neonate larvae that had not yet penetrated the leaf, and explained the failure of some insecticides to control P. operculella infestations in commercial tomato crops. Neonate larvae placed on leaves of potted plants several days before treatment provided larvae for testing of insecticides against larvae in mines; other neonates were placed on leaves after treatment to test efficacy against larvae yet to penetrate the leaf. The plants were sprayed with the candidate insecticides, held for 5-7 days, and larval mortality assessed. Chlorfenapyr (100, 200 g a.i. ha-1) and abamectin (8.1 g a.i. ha-1) were effective against neonate larvae and larvae in mines. Sulprofos (720 g a.i. ha -1), methomyl (450 g a.i. ha-1) and spinosad (96 g a.i. ha-1) were effective against neonate larvae but not against larvae in mines. Methamidophos (1102 g a.i. ha-1), endosulfan (700 g a.i. ha-1) and Bacillus thuringiensis kurstaki (1000 g ha-1) had some effect against exposed larvae but little against larvae in mines. Thiodicarb (525 g a.i. ha-1), azinphos-ethyl (440 g a.i. ha -1), imidacloprid (59.5 g a.i. ha-1), hexaflumuron (50 g a.i. ha-1), methoxyfenozide (300 g a.i. ha-1) and tebufenozide (200 g a.i. ha-1) were ineffective. A field trial using chlorfenapyr (25, 50, 100, 150 and 200 g a.i. ha-1) and methamidophos (1102 g a.i. ha-1) validated the bioassay technique, with chlorfenapyr effective in reducing the numbers of larvae in mines in leaves.

Cucumber mosaic virus infection of kava (Piper methysticum) and implications for cultural control of kava dieback disease

Cucumber mosaic virus (CMV) was found by reverse transcription polymerase chain reaction (RT-PCR) to be not fully systemic in naturally infected kava (Piper methysticum) plants in Fiji. Twenty-six of 48 samples (54%) from various tissues of three recently infected plants were CMV-positive compared with 7/51 samples (14%) from three long-term infections (plants affected by dieback for more than 1 year). The virus was also found to have a limited ability to move into newly formed stems. CMV was detected in only 2/23 samples taken from re-growth stems arising from known CMV infected/dieback affected plants. Mechanical inoculation experiments conducted in Fiji indicate that the known kava intercrop plants banana (Musa spp.), pineapple (Ananas comosus), peanut (Arachis hypogaea) and the common weed Mikania micrantha are potential hosts for a dieback-causing strain of CMV It was not possible to transmit the virus mechanically to the common kava intercrop plants taro (Colocasia esculenta), Xanthosoma sp., sweet potato (Ipomoea batatas), yam (Dioscorea alata), papaya (Carica papaya) or the weed Momordica charantia. Implications of the results of this research on a possible integrated disease management strategy are discussed.

The development of an improved PCR-based marker system for Sw-5, an important TSWV resistance gene of tomato

Sw-5 is an important disease resistance gene of tomato, providing broad resistance to Tomato spotted wilt virus (TSWV). A cleaved amplified polymorphic sequence (CAPS) marker, closely linked to the gene, has been reported. Although the Sw-5 locus has been characterised, a gene-specific marker has not been developed. This paper presents a PCR-based marker-system that consists of the co-amplification of a dominant marker representing the Sw-5 gene sequence, and the modified CAPS marker as a positive control and indicator of genotype.

Capsicum chlorosis virus infecting Capsicum annuum in the East Kimberley region of Western Australia

Capsicum chlorosis virus (CaCV) was detected in field grown Capsicum annuum from Kununurra in northeast Western Australia. Identification of the Kununurra isolate (WA-99) was confirmed using sap transmission to indicator hosts, positive reactions with tospovirus serogroup IV-specific antibodies and CaCV-specific primers, and amino acid sequence comparisons that showed >97% identity with published CaCV nucleocapsid gene sequences. The reactions of indicator hosts to infection with WA-99 often differed from those of the type isolate from Queensland. The virus multiplied best when test plants were grown at warm temperatures. CaCV was not detected in samples collected in a survey of C. annuum crops planted in the Perth Metropolitan area.

Carrot as a natural host of Watermelon mosaic virus

Carrot was confirmed as a new natural and experimental host of Watermelon mosaic virus by serology, host reactions and sequence comparisons of the coat protein.

Molecular characterisation, pathogenesis and fungicide sensitivity of Pythium spp. from table beet (Beta vulgaris var. vulgaris) grown in the Lockyer Valley, Queensland

Table beet production in the Lockyer Valley of south-eastern Queensland is known to be adversely affected by soilborne root disease from infection by Pythium spp. However, little is known regarding the species or genotypes that are the causal agents of both pre- and post-emergence damping off. Based on RFLP analysis with HhaI, HinfI and MboI of the PCR amplified ITS region DNA from soil and diseased plant samples, the majority of 130 Pythium isolates could be grouped into three genotypes, designated LVP A, LVP B and LVP C. These groups comprised 43, 41 and 7% of all isolates, respectively. Deoxyribonucleic acid sequence analysis of the ITS region indicated that LVP A was a strain of Pythium aphanidermatum, with greater than 99% similarity to the corresponding P. aphanidermatum sequences from the publicly accessible databases. The DNA sequences from LVP B and LVP C were most closely related to P. ultimum and P. dissotocum, respectively. Lower frequencies of other distinct isolates with unique RFLP patterns were also obtained with high levels of similarity (>97%) to P. heterothallicum, P. periplocum and genotypes of P. ultimum other than LVP B. Inoculation trials of 1- and 4-week-old beet seedlings indicated that compared with isolates of the LVP B genotype, a higher frequency of LVP A isolates caused disease. Isolates with the LVP A, LVP B and LVP C genotypes were highly sensitive to the fungicide Ridomil MZ, which suppressed radial growth on V8 agar between approximately four and thirty fold at 5 μg/mL metalaxyl and 40 μg/mL mancozeb, a concentration far lower than the recommended field application rate.

Rickettsia-like-organisms and phytoplasmas associated with diseases in Australian strawberries

Strawberry lethal yellows (SLY) disease in Australia is associated with the phytoplasmas Candidatus Phytoplasma australiense and tomato big bud, and a rickettsia-like-organism (RLO). Ca. P. australiense is also associated with strawberry green petal (SGP) disease. This study investigated the strength of the association of the different agents with SLY disease. We also documented the location of SLY or SGP plants, and measured whether they were RLO or phytoplasma positive. Symptomatic strawberry plants collected from south-east Queensland (Australia) between January 2000 and October 2002 were screened by PCR for both phytoplasmas and the RLO. Two previously unreported disease symptoms termed severe fruit distortion (SFD) and strawberry leaves from fruit (SLF) were observed during this study but there was no clear association between these symptoms and phytoplasmas or the RLO. Only two SGP diseased plants were observed and collected, compared with 363 plants with SLY disease symptoms. Of the 363 SLY samples, 117 tested positive for the RLO, 67 tested positive for Ca. P. australiense AGY strain and 11 plants tested positive for Ca. P. australiense PYL variant strain. On runner production farms at Stanthorpe, Queensland the RLO was detected in SLY diseased plants more frequently than for the phytoplasmas. On fruit production farms on the Sunshine Coast, Queensland, Ca. P. australiense was detected in SLY disease plants more frequently than the RLO.

Incidence and pathogenicity of Phytophthora palmivora and Pythium vexans associated with durian decline in far northern Queensland

In recent years, dieback of durian has become a major problem in mature orchards in the northern Queensland wet tropics region. A survey of 13 durian orchards was conducted during the dry season (July-September 2001) and following wet season (February-April 2002), with roots and soil from the root zone of affected trees being sampled. Phytophthora palmivora was recovered from the roots of affected trees on 12 of the 13 farms in the dry season, and all farms in the wet season. Pythium vexans was recovered from all 13 farms in both seasons. P. palmivora and P. vexans were recovered from diseased roots of 3-month-old durian seedlings cv. Monthong artificially inoculated with these organisms.

A detached leaf bioassay to screen Durian cultivars for susceptibility to Phytophthora palmivora

A detached-leaf bioassay was developed and used to screen five durian (Durio zibethinus) cultivars against Phytophthora palmivora isolates from a trunk canker, root and fruit. The fruit isolate was less aggressive than the canker and root isolates. The bioassay using the canker isolate was later used to determine the variation in resistance of D. macarantha and nineteen cultivars of D. zibethinus. The cultivars displayed a range of responses with Parung and Gob being most tolerant, with Gaan Yaow, Chanee and Penang 88 being susceptible. The remaining germplasm fell between Gaan Yaow and Penang 88 in susceptibility. The leaf bioassay was found to be a rapid and reliable method for assessing the susceptibility of durian cultivars.

Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson’s disease

Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

Pyriproxyfen controls silverleaf whitefly, Bemisia tabaci (Gennadius), biotype B (Homoptera: Aleyrodidae) (SLW) better than buprofezin in bitter melons Momordica charantia L. (Cucurbitaceae)

To improve compatibility between chemical and biological controls, the use of selective insecticides such as insect growth regulators (IGRs) is crucial. In cucurbits, the use of pyriproxyfen (an IGR) has been shown by others to be an effective method of reducing the number of sap-sucking insects, especially silverleaf whitefly, Bemisia tabaci (Gennadius) Biotype B (SLW). Therefore, we compared pyriproxyfen and buprofezin (an IGR) with that of no treatment (control) in a bitter melon crop for the control of populations of SLW and for their effects on fruit production. Pyriproxyfen controlled SLW and tended to have heavier fruits than the control treatment and reduced the abundance of nymphs and exuvia. Buprofezin showed no evidence in controlling SLW compared with the pyriproxyfen and control treatments. Neither pyriproxyfen nor buprofezin had any effect on the number of harvested fruit or overall fruit yield, but the average weight per fruit was higher than the control treatment. Pyriproxyfen was effective in controlling whitefly populations in bitter melons, and both pyriproxyfen and buprofezin may have the potential to increase yield. Their longer-term use may increase predation by natural enemies as they are species-specific and could favour build up of natural enemies of SLW. Thus, the judicious use of pyriproxyfen may provide an effective alternative to broad-spectrum insecticides in small-scale cucurbit production.

Delineating environmental envelopes to improve mapping of species distributions, via a hurdle model with CART &/or MaxEnT

Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.

Scenario analysis of alternative vegetation management options on the greenhouse gas budget of two grazing businesses in north-eastern Australia

The emerging carbon economy will have a major impact on grazing businesses because of significant livestock methane and land-use change emissions. Livestock methane emissions alone account for similar to 11% of Australia's reported greenhouse gas emissions. Grazing businesses need to develop an understanding of their greenhouse gas impact and be able to assess the impact of alternative management options. This paper attempts to generate a greenhouse gas budget for two scenarios using a spread sheet model. The first scenario was based on one land-type '20-year-old brigalow regrowth' in the brigalow bioregion of southern-central Queensland. The 50 year analysis demonstrated the substantially different greenhouse gas outcomes and livestock carrying capacity for three alternative regrowth management options: retain regrowth (sequester 71.5 t carbon dioxide equivalents per hectare, CO2-e/ha), clear all regrowth (emit 42.8 t CO2-e/ha) and clear regrowth strips (emit 5.8 t CO2-e/ha). The second scenario was based on a 'remnant eucalypt savanna-woodland' land type in the Einasleigh Uplands bioregion of north Queensland. The four alternative vegetation management options were: retain current woodland structure (emit 7.4 t CO2-e/ha), allow woodland to thicken increasing tree basal area (sequester 20.7 t CO2-e/ha), thin trees less than 10 cm diameter (emit 8.9 t CO2-e/ha), and thin trees <20 cm diameter (emit 12.4 t CO2-e/ha). Significant assumptions were required to complete the budgets due to gaps in current knowledge on the response of woody vegetation, soil carbon and non-CO2 soil emissions to management options and land-type at the property scale. The analyses indicate that there is scope for grazing businesses to choose alternative management options to influence their greenhouse gas budget. However, a key assumption is that accumulation of carbon or avoidance of emissions somewhere on a grazing business (e.g. in woody vegetation or soil) will be recognised as an offset for emissions elsewhere in the business (e.g. livestock methane). This issue will be a challenge for livestock industries and policy makers to work through in the coming years.

Climate change impacts on northern Australian rangeland livestock carrying capacity: a review of issues

Grazing is a major land use in Australia's rangelands. The 'safe' livestock carrying capacity (LCC) required to maintain resource condition is strongly dependent on climate. We reviewed: the approaches for quantifying LCC; current trends in climate and their effect on components of the grazing system; implications of the 'best estimates' of climate change projections for LCC; the agreement and disagreement between the current trends and projections; and the adequacy of current models of forage production in simulating the impact of climate change. We report the results of a sensitivity study of climate change impacts on forage production across the rangelands, and we discuss the more general issues facing grazing enterprises associated with climate change, such as 'known uncertainties' and adaptation responses (e.g. use of climate risk assessment). We found that the method of quantifying LCC from a combination of estimates (simulations) of long-term (>30 years) forage production and successful grazier experience has been well tested across northern Australian rangelands with different climatic regions. This methodology provides a sound base for the assessment of climate change impacts, even though there are many identified gaps in knowledge. The evaluation of current trends indicated substantial differences in the trends of annual rainfall (and simulated forage production) across Australian rangelands with general increases in most of western Australian rangelands ( including northern regions of the Northern Territory) and decreases in eastern Australian rangelands and south-western Western Australia. Some of the projected changes in rainfall and temperature appear small compared with year-to-year variability. Nevertheless, the impacts on rangeland production systems are expected to be important in terms of required managerial and enterprise adaptations. Some important aspects of climate systems science remain unresolved, and we suggest that a risk-averse approach to rangeland management, based on the 'best estimate' projections, in combination with appropriate responses to short-term (1-5 years) climate variability, would reduce the risk of resource degradation. Climate change projections - including changes in rainfall, temperature, carbon dioxide and other climatic variables - if realised, are likely to affect forage and animal production, and ecosystem functioning. The major known uncertainties in quantifying climate change impacts are: (i) carbon dioxide effects on forage production, quality, nutrient cycling and competition between life forms (e.g. grass, shrubs and trees); and (ii) the future role of woody plants including effects of. re, climatic extremes and management for carbon storage. In a simple example of simulating climate change impacts on forage production, we found that increased temperature (3 degrees C) was likely to result in a decrease in forage production for most rangeland locations (e. g. -21% calculated as an unweighted average across 90 locations). The increase in temperature exacerbated or reduced the effects of a 10% decrease/increase in rainfall respectively (-33% or -9%). Estimates of the beneficial effects of increased CO2 (from 350 to 650 ppm) on forage production and water use efficiency indicated enhanced forage production (+26%). The increase was approximately equivalent to the decline in forage production associated with a 3 degrees C temperature increase. The large magnitude of these opposing effects emphasised the importance of the uncertainties in quantifying the impacts of these components of climate change. We anticipate decreases in LCC given that the 'best estimate' of climate change across the rangelands is for a decline (or little change) in rainfall and an increase in temperature. As a consequence, we suggest that public policy have regard for: the implications for livestock enterprises, regional communities, potential resource damage, animal welfare and human distress. However, the capability to quantify these warnings is yet to be developed and this important task remains as a challenge for rangeland and climate systems science.