Silverleaf whitefly resistance management

Silverleaf whitefly (SLW) is a major late season pest of cotton due to its potential to contaminate cotton lint with honeydew. To prevent this, management is often reliant on the use of insecticides to control SLW populations. With selection pressure SLW develop resistance to insecticides they are exposed to, resulting in spray failures. Our lab tests resistance levels in SLW populations collected from across the cotton industry. In this presentation I will provide an update of emerging SLW resistance issues the cotton industry is facing.

Growth and development of three key summer grasses in Australian cotton systems

Awnless barnyard grass, feathertop Rhodes grass, and windmill grass are important weeds in Australian cotton systems. In October 2014, an experiment was established to investigate the phenological plasticity of these species. Seed of these species were planted in a glasshouse every four weeks and each cohort grown for 6 months. A developmental response to day length was observed in barnyard grass but not in the other species. Days to maturity increased with each planting for feathertop Rhodes and windmill grass for the first six cohorts. Barnyard grass showed a similar pattern in growth for seeds planted from October to December with an increase in the onset of maturity from 51 to 58 days. However, the onset of maturity for cohorts planted between January and March decreased to between 50 and 52 days. All species had a decrease in the total number of panicles produced from the first four plantings. Feathertop Rhodes grass planted in October produced 41 panicles compared to those planted at the end of December producing 30 panicles, barnyard grass had a decrease from 99 to 47 panicles and windmill grass 37 to 15 panicles on average. By comparing the development of these key weed species over 12 months, detailed information on the phenological plasticity of these species will be obtained. This information will contribute to more informed management decisions by improving our understanding of appropriate weed control timings or herbicide rates depending on weed emergence and development.

Is Australia ready for triple gene herbicide stack technology?

Integration of multiple herbicide-resistant genes (trait stacking) into crop plants would allow over the top application of herbicides that are otherwise fatal to crops. The US has just approved Bollgard II® XtendFlex™ cotton which has dicamba, glyphosate and glufosinate resistance traits stacked. The pace of glyphosate resistance evolution is expected to be slowed by this technology. In addition, over the top application of two more herbicides may help to manage hard to kill weeds in cotton such as flax leaf fleabane and milk thistle. However, there are some issues that need to be considered prior to the adoption of this technology. Wherever herbicide tolerant technology is adopted, volunteer crops can emerge as a weed problem, as can herbicide resistant weeds. For cotton, seed movement is the most likely way for resistant traits to move around. Management of multiple stack volunteers may add additional complexity to volunteer management in cotton fields and along roadsides. This paper attempts to evaluate the pros and cons of trait stacking technology by analysing the available literature in other crop growing regions across the world. The efficacy of dicamba and glufosinate on common weeds of the Australian cotton system, herbicide resistance evolution, synergy and antagonisms due to herbicide mixtures, drift hazards and the evolution of herbicide resistance to glyphosate, glufosinate and dicamba were analysed based on the available literature.

CottonInfo Extending Research

There are many ways in which research messages and findings can be extended to the expansive cotton community. As everyone learns differently it is crucial that information is delivered in a variety of ways to meet the various learning needs of the CottonInfo team’s broad audience. In addition different cotton production areas often require targeted information to address specific challenges. Successful implementation of innovative research outcomes typically relies on a history of cultivated communication between the researcher and the end-user, the grower. The CottonInfo team, supported by a joint venture between Cotton Seed Distributors, Cotton Research Development Corporation, Cotton Australia and other collaborative partners, represents a unique model of extension in Australian agriculture. Industry research is extended via regionally based Regional Development Officers backed by support from Technical Specialists. The 2015 Cotton Irrigation Technology Tour is one example of a successful CottonInfo capacity building activity. This tour took seven CRDC funded irrigation-specific researchers to Emerald, Moree and Nevertire to showcase their research and technologies. These events provided irrigators and consultants with the opportunity to hear first-hand from researchers about their technologies and how they could be applied onfarm. This tour was an example of how the CottonInfo team can connect growers and researchers, not only to provide an avenue for growers to learn about the latest irrigation research, but for researchers to receive feedback about their current and future irrigation research.

New developments in UAV remote sensing for pest management and the implications for cotton

Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.

Response of irrigated cotton to applied nitrogen

Like all high yielding farming systems nitrogen (N) is a key component to their productivity and profitability and Australian irrigated cotton growers are tending to apply more N than is required for the level of lint yield that is being achieved. This suggests either over application of N or inefficient systems limiting the response of cotton to N inputs. To investigate this four replicated trials were established in commercial fields during the 2014/15 season. The trials were aiming to measure the difference in response of irrigated cotton to the application of N under flood and overhead irrigation systems. The application treatments utilized eight upfront rates of applied N, ranging from 0 N kg/ha to a maximum of 410 kg N/ha, with three of the fours trials receiving a growerdetermined in-crop application of N in the irrigation water. The two flood irrigation systems had lower lint yields from similar levels of N input compared to one of the overhead irrigated sites; the result from the second overhead site was impacted by disease. This paper discusses the response of plant N uptake, lint yield and fertilizer N recovery to N application..

The importance of cotton disease surveys in Queensland for monitoring endemic diseases and detecting new pathogens and pests

The cotton industry in Australia funds biannual disease surveys conducted by plant pathologists. The objective of these surveys is to monitor the distribution and importance of key endemic pests and record the presence or absence of new or exotic diseases. Surveys have been conducted in Queensland since 2002/03, with surveillance undertaken by experienced plant pathologists. Monitoring of endemic diseases indicates the impact of farming practices on disease incidence and severity. The information collected gives direction to cotton disease research. Routine diagnostics has provided early detection of new disease problems which include 1) the identification of Nematospora coryli, a pathogenic yeast associated with seed and internal boll rot; and 2) Rotylenchulus reniformis, a plant-parasitic nematode. This finding established the need for an intensive survey of the Theodore district revealing that reniform was prevalent across the district at populations causing up to 30% yield loss. Surveys have identified an exotic defoliating strain (VCG 1A) and non-defoliating strains of Verticillium dahliae, which cause Verticillium wilt. An intensive study of the diversity of V. dahliae and the impact these strains have on cotton are underway. Results demonstrate the necessity of general multi-pest surveillance systems in broad acre agriculture in providing (1) an ongoing evaluation of current integrated disease management practices and (2) early detection for a suite of exotic pests and previously unknown pests.

Composts addition may improve biology in cotton soils

Composts can provide a source of organic carbon and nutrients for soil biota and increase soil fertility as well as provide other biological and structural benefits hence compost addition to cotton soils is seen as a way to improve cotton soil biological health and fertility. In a six month incubation experiment we analysed the changes in microbial populations and activities related to C and N cycling following the application of feedlot, poultry manure and gin trash compost materials. A significant variation in the chemical composition, e.g. major nutrients and trace elements, was found between the three compost products. The feedlot compost generally contained higher levels of dissolved organic carbon, total nitrogen and bicarbonate extractable phosphorus whereas the Gin trash compost had lower carbon and nutrient concentrations. The effect of compost addition @ 5 and 10t/ha generally increased microbial activity but the effect was only evident during the first two weeks of incubation. Composts effects on the abundance of total bacteria (16S), nitrifying (amoA), nitrogen fixing (nifH) and denitrifying bacteria (nosZ) and total fungi (ITS gene) varied between different composts. The addition of feedlot and poultry compost material significantly increased the levels of dissolved organic carbon (DOC) and nitrogen (DON) in soil compared to that in control soils while ‘Gin trash’ compost had no effect. These differences reflected in the microbial catabolic diversity changes in the compost amended soils. Therefore, chemical analysis of the compost material before application is recommended to more fully consider its’ potential benefits.

Can patches of glyphosate-resistant Echinochloa colona be eradicated?

Glyphosate-resistant Echinochloa colona L. (Link) is becoming common in non-irrigated cotton systems. Echinochloa colona is a small seeded species that is not wind-blown and has a relatively short seed bank life. These characteristics make it a potential candidate to attempt to eradicate populations resistant to glyphosate when they are detected. A long term systems experiment was developed to determine the feasibility of attempting to eradicate glyphosate resistant populations in the field. After three seasons, the established Best Management Practice (BMP) strategy of two non-glyphosate actions in crop and fallow have been sufficient to significantly reduce the numbers of plants emerging, and remaining at the end of the season compared to the glyphosate only treatment. Additional eradication treatments showed slight improvement on the BMP strategy, however to date these improvements are not significant. The importance of additional eradication tactics are expected to become more noticeable as the seed bank gets driven down in subsequent seasons.

Effects of silicon treatment and inoculation with Fusarium oxysporum f. sp. vasinfectum on cellular defences in root tissues of two cotton cultivars

BACKGROUND AND AIMS: Silicon has been shown to enhance the resistance of plants to fungal and bacterial pathogens. Here, the effect of potassium silicate was assessed on two cotton (Gossypium hirsutum) cultivars subsequently inoculated with Fusarium oxysporum f. sp. vasinfectum (Fov). Sicot 189 is moderately resistant whilst Sicot F-1 is the second most resistant commercial cultivar presently available in Australia. METHODS: Transmission and light microscopy were used to compare cellular modifications in root cells after these different treatments. The accumulation of phenolic compounds and lignin was measured. KEY RESULTS: Cellular alterations including the deposition of electron-dense material, degradation of fungal hyphae and occlusion of endodermal cells were more rapidly induced and more intense in endodermal and vascular regions of Sicot F-1 plants supplied with potassium silicate followed by inoculation with Fov than in similarly treated Sicot 189 plants or in silicate-treated plants of either cultivar not inoculated with Fov. Significantly more phenolic compounds were present at 7 d post-infection (dpi) in root extracts of Sicot F-1 plants treated with potassium silicate followed by inoculation with Fov compared with plants from all other treatments. The lignin concentration at 3 dpi in root material from Sicot F-1 treated with potassium silicate and inoculated with Fov was significantly higher than that from water-treated and inoculated plants. CONCLUSIONS: This study demonstrates that silicon treatment can affect cellular defence responses in cotton roots subsequently inoculated with Fov, particularly in Sicot F-1, a cultivar with greater inherent resistance to this pathogen. This suggests that silicon may interact with or initiate defence pathways faster in this cultivar than in the less resistant cultivar.

Hyperspectral sensing to detect the impact of herbicide drift on cotton growth and yield

Yield loss in crops is often associated with plant disease or external factors such as environment, water supply and nutrient availability. Improper agricultural practices can also introduce risks into the equation. Herbicide drift can be a combination of improper practices and environmental conditions which can create a potential yield loss. As traditional assessment of plant damage is often imprecise and time consuming, the ability of remote and proximal sensing techniques to monitor various bio-chemical alterations in the plant may offer a faster, non-destructive and reliable approach to predict yield loss caused by herbicide drift. This paper examines the prediction capabilities of partial least squares regression (PLS-R) models for estimating yield. Models were constructed with hyperspectral data of a cotton crop sprayed with three simulated doses of the phenoxy herbicide 2,4-D at three different growth stages. Fibre quality, photosynthesis, conductance, and two main hormones, indole acetic acid (IAA) and abscisic acid (ABA) were also analysed. Except for fibre quality and ABA, Spearman correlations have shown that these variables were highly affected by the chemical. Four PLS-R models for predicting yield were developed according to four timings of data collection: 2, 7, 14 and 28 days after the exposure (DAE). As indicated by the model performance, the analysis revealed that 7 DAE was the best time for data collection purposes (RMSEP = 2.6 and R2 = 0.88), followed by 28 DAE (RMSEP = 3.2 and R2 = 0.84). In summary, the results of this study show that it is possible to accurately predict yield after a simulated herbicide drift of 2,4-D on a cotton crop, through the analysis of hyperspectral data, thereby providing a reliable, effective and non-destructive alternative based on the internal response of the cotton leaves.

Utilization of nitrogen (15N) from urea and green manures by rice as affected by nitrogen fertilizer rate.

The use of green manures (GMs) in combination with nitrogen (N) fertilizer application is a promising practice to improve N fertilizer management in agricultural production systems. The main objective of this study was to evaluate the N use efficiency (NUE) of rice plant, derived from GMs including sunn hemp (Crotalaria juncea L.), millet (Pennisetum glaucum L.) and urea in the greenhouse. The experimental treatments included two GMs (sunn hemp-15N and millet-15N), absence of N organic source (without GM residues in soil) and four N rates, as urea-15N (0, 28.6, 57.2 and 85.8 mg N kg-1). The results showed that both rice grain and straw biomass yields under sunn hemp were greater than that of millet or without the application of GM. The NUE of rice under sunn hemp was greater than that under millet (18.9 and 7.8% under sunn hemp and millet, respectively). The urea N application rates did not affect the fertilizer NUE by rice (53.7%) with or without GMs. The NUE of GMs by rice plants ranged from 14.1% and 16.8% for root and shoot, respectively. The study showed that green manures can play an important role in enhancing soil fertility and N supply to subsequent crops.

Bioecology of Spodoptera frugiperda (Smith, 1757) in different cover crops.

The objective of this work was to evaluate the biological variables of Spodoptera frugiperda on species of cover crops. The experiments were conducted in laboratory and greenhouse using the following species: sunflower (Helianthus annuus), sun hemp (Crotalaria juncea), brachiaria (Urochloa decumbens e Urochloa ruziziensis), millet (Pennisetum americanum), black oat (Avena stringosa), white lupin (Lupinus albus), forage turnip (Rafanus sativus) and maize (Zea mays). In laboratory the S. frugiperda larval survival varied from 57%, on L. albus, to 93% on H. annuus and the survival of the pre-imaginal phase varied from 45% on U. decumbens to 81.6% on Z. mays. On C. juncea the larval biomass was lower and the development period of the young and larval stage was higher. The adaptation index was less on C. juncea in greenhouse and laboratory. In greenhouse the larval survival at 14 days was similar for all plants and at 21 days was the lowest on C. juncea. There was less accumulation of biomass at 14 days on C. juncea and at 21 days on C. juncea and A. stringosa. Regarding damage, C. juncea presented less susceptibility to Spodoptera frugiperda attack, which together with the other evaluated parameters, indicated this plant as the most appropriate for soil cover before cultivation of maize.