Pesticide residues in food - acute dietary exposure

Consumer risk assessment is a crucial step in the regulatory approval of pesticide use on food crops. Recently, an additional hurdle has been added to the formal consumer risk assessment process with the introduction of short-term intake or exposure assessment and a comparable short-term toxicity reference, the acute reference dose. Exposure to residues during one meal or over one day is important for short-term or acute intake. Exposure in the short term can be substantially higher than average because the consumption of a food on a single occasion can be very large compared with typical long-term or mean consumption and the food may have a much larger residue than average. Furthermore, the residue level in a single unit of a fruit or vegetable may be higher by a factor (defined as the variability factor, which we have shown to be typically ×3 for the 97.5th percentile unit) than the average residue in the lot. Available marketplace data and supervised residue trial data are examined in an investigation of the variability of residues in units of fruit and vegetables. A method is described for estimating the 97.5th percentile value from sets of unit residue data. Variability appears to be generally independent of the pesticide, the crop, crop unit size and the residue level. The deposition of pesticide on the individual unit during application is probably the most significant factor. The diets used in the calculations ideally come from individual and household surveys with enough consumers of each specific food to determine large portion sizes. The diets should distinguish the different forms of a food consumed, eg canned, frozen or fresh, because the residue levels associated with the different forms may be quite different. Dietary intakes may be calculated by a deterministic method or a probabilistic method. In the deterministic method the intake is estimated with the assumptions of large portion consumption of a ‘high residue’ food (high residue in the sense that the pesticide was used at the highest recommended label rate, the crop was harvested at the smallest interval after treatment and the residue in the edible portion was the highest found in any of the supervised trials in line with these use conditions). The deterministic calculation also includes a variability factor for those foods consumed as units (eg apples, carrots) to allow for the elevated residue in some single units which may not be seen in composited samples. In the probabilistic method the distribution of dietary consumption and the distribution of possible residues are combined in repeated probabilistic calculations to yield a distribution of possible residue intakes. Additional information such as percentage commodity treated and combination of residues from multiple commodities may be incorporated into probabilistic calculations. The IUPAC Advisory Committee on Crop Protection Chemistry has made 11 recommendations relating to acute dietary exposure.

Should the 40-year-old practice of releasing virulent myxoma virus to control rabbits (Oryctolagus cuniculus) be continued?

Release of virulent myxoma virus has been a key component of rabbit-control operations in Queensland, Australia, since the 1960s but its use rests on anecdotal reports. During a routine operation to release virulent myxoma virus we found no evidence to support the continued regular use of the technique in south-west Queensland. Radio-tagged rabbits inoculated with virulent myxoma virus contracted the disease but failed to pass enough virus to other rabbits to spread the disease. Rabbits with clinical signs of myxomatosis that were shot were infected with field strain derived from the original laboratory strain released in 1950 rather than the virulent strain that has been released annually. There was no change in rabbit survival or abundance caused by the release. Nevertheless, the release of virulent virus may be useful against isolated pockets of rabbits mainly because field strains are less likely to be present. Such pockets are more common now that rabbit haemorrhagic disease virus is established in Queensland.

Past, current and future approaches to mango genetic improvement in Australia

Improving the genetic base of cultivars that underpin commercial mango production is generally recognized as necessary for long term industry stability. Genetic improvement can take many approaches to improve cultivars, each with their own advantages and disadvantages. This paper will discuss several approaches used in the genetic improvement of mangoes in Australia, including varietal introductions, selection of monoembryonic progeny, selection within polyembryonic populations, assisted open pollination and controlled closed pollination. The current activities of the Australian National Mango Breeding Program will be outlined, and the analysis and use of hybrid phenotype data from the project for selection of next generation parents will be discussed. Some of the important traits that will enhance the competitiveness of future cultivars will be introduced and the challenges in achieving them discussed. The use of a genomics approach and its impact on future mango breeding is examined.

The conservation status of the world’s reptiles

Effective and targeted conservation action requires detailed information about species, their distribution, systematics and ecology as well as the distribution of threat processes which affect them. Knowledge of reptilian diversity remains surprisingly disparate, and innovative means of gaining rapid insight into the status of reptiles are needed in order to highlight urgent conservation cases and inform environmental policy with appropriate biodiversity information in a timely manner. We present the first ever global analysis of extinction risk in reptiles, based on a random representative sample of 1500 species (16% of all currently known species). To our knowledge, our results provide the first analysis of the global conservation status and distribution patterns of reptiles and the threats affecting them, highlighting conservation priorities and knowledge gaps which need to be addressed urgently to ensure the continued survival of the world’s reptiles. Nearly one in five reptilian species are threatened with extinction, with another one in five species classed as Data Deficient. The proportion of threatened reptile species is highest in freshwater environments, tropical regions and on oceanic islands, while data deficiency was highest in tropical areas, such as Central Africa and Southeast Asia, and among fossorial reptiles. Our results emphasise the need for research attention to be focussed on tropical areas which are experiencing the most dramatic rates of habitat loss, on fossorial reptiles for which there is a chronic lack of data, and on certain taxa such as snakes for which extinction risk may currently be underestimated due to lack of population information. Conservation actions specifically need to mitigate the effects of human-induced habitat loss and harvesting, which are the predominant threats to reptiles.

Plant composition modulates arthropod pest and predator abundance: Evidence for culling exotics and planting natives

We investigate the role of plant species in crops, pasture and native vegetation remnants in supporting agronomic pests and their predators. The study was conducted in three Australian States and across 290 sites sampled monthly for two years. Pastures played a key role in harbouring pest species consistent across States, while native vegetation hosted relatively more predators than other habitat types within each State. Furthermore, native plant species supported the lowest pest density and more predators than pests; in contrast, 75 of the exotic weed species surveyed hosted more pests than predators. Despite the role of pasture in harbouring pests, we found in NSW that pasture also supported the highest proportion of juvenile predators, while native vegetation remnants had the lowest. Our results indicate that non-crop habitat (native remnants or pasture) with few exotic weeds supports high predator and low pest arthropod densities, and that weeds are associated with high pest densities. By linking broad response variables such as ‘all pests’ with specific predictors such as ‘plant species’, our study will inform on-farm management actions of which weeds to control and which natives to plant or regenerate. This study shows the importance of knowing the function of habitats and plants species in supporting pests and predators in agricultural landscapes across multiple regions.

Identification of I-7 expands the repertoire of genes for resistance to Fusarium wilt in tomato to three resistance gene classes

The tomato I-3 and I-7 genes confer resistance to Fusarium oxysporum f. sp. lycopersici (Fol) race 3 and were introgressed into the cultivated tomato, Solanum lycopersicum, from the wild relative Solanum pennellii. I-3 has been identified previously on chromosome 7 and encodes an S-receptor-like kinase, but little is known about I-7. Molecular markers have been developed for the marker-assisted breeding of I-3, but none are available for I-7. We used an RNA-seq and single nucleotide polymorphism (SNP) analysis approach to map I-7 to a small introgression of S. pennellii DNA (c. 210 kb) on chromosome 8, and identified I-7 as a gene encoding a leucine-rich repeat receptor-like protein (LRR-RLP), thereby expanding the repertoire of resistance protein classes conferring resistance to Fol. Using an eds1 mutant of tomato, we showed that I-7, like many other LRR-RLPs conferring pathogen resistance in tomato, is EDS1 (Enhanced Disease Susceptibility 1) dependent. Using transgenic tomato plants carrying only the I-7 gene for Fol resistance, we found that I-7 also confers resistance to Fol races 1 and 2. Given that Fol race 1 carries Avr1, resistance to Fol race 1 indicates that I-7-mediated resistance, unlike I-2- or I-3-mediated resistance, is not suppressed by Avr1. This suggests that Avr1 is not a general suppressor of Fol resistance in tomato, leading us to hypothesize that Avr1 may be acting against an EDS1-independent pathway for resistance activation. The identification of I-7 has allowed us to develop molecular markers for marker-assisted breeding of both genes currently known to confer Fol race 3 resistance (I-3 and I-7). Given that I-7-mediated resistance is not suppressed by Avr1, I-7 may be a useful addition to I-3 in the tomato breeder's toolbox.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.