Department of Primary Industries and Regional Development

A new technology called genomic selection is revolutionizing dairy cattle breeding. Genomic selection refers to selection decisions based on genomic breeding values (GEBV). The GEBV are calculated as the sum of the effects of dense genetic markers, or haplotypes of these markers, across the entire genome, thereby potentially capturing all the quantitative trait loci (QTL) that contribute to variation in a trait. The QTL effects, inferred from either haplotypes or individual single nucleotide polymorphism markers, are first estimated in a large reference population with phenotypic information. In subsequent generations, only marker information is required to calculate GEBV. The reliability of GEBV predicted in this way has already been evaluated in experiments in the United States, New Zealand, Australia, and the Netherlands. These experiments used reference populations of between 650 and 4,500 progeny-tested Holstein-Friesian bulls, genotyped for approximately 50,000 genome-wide markers. Reliabilities of GEBV for young bulls without progeny test results in the reference population were between 20 and 67%. The reliability achieved depended on the heritability of the trait evaluated, the number of bulls in the reference population, the statistical method used to estimate the single nucleotide polymorphism effects in the reference population, and the method used to calculate the reliability. A common finding in 3 countries (United States, New Zealand, and Australia) was that a straightforward BLUP method for estimating the marker effects gave reliabilities of GEBV almost as high as more complex methods. The BLUP method is attractive because the only prior information required is the additive genetic variance of the trait. All countries included a polygenic effect (parent average breeding value) in their GEBV calculation. This inclusion is recommended to capture any genetic variance not associated with the markers, and to put some selection pressure on low-frequency QTL that may not be captured by the markers. The reliabilities of GEBV achieved were significantly greater than the reliability of parental average breeding values, the current criteria for selection of bull calves to enter progeny test teams. The increase in reliability is sufficiently high that at least 2 dairy breeding companies are already marketing bull teams for commercial use based on their GEBV only, at 2 yr of age. This strategy should at least double the rate of genetic gain in the dairy industry. Many challenges with genomic selection and its implementation remain, including increasing the accuracy of GEBV, integrating genomic information into national and international genetic evaluations, and managing long-term genetic gain.

Research on the adoption of rural innovations is reviewed and interpreted through a cross-disciplinary lens to provide practical guidance for research, extension and policy relating to conservation practices. Adoption of innovations by landholders is presented as a dynamic learning process. Adoption depends on a range of personal, social, cultural and economic factors, as well as on characteristics of the innovation itself. Adoption occurs when the landholder perceives that the innovation in question will enhance the achievement of their personal goals. A range of goals is identifiable among landholders, including economic, social and environmental goals. Innovations are more likely to be adopted when they have a high ‘relative advantage’ (perceived superiority to the idea or practice that it supersedes), and when they are readily trialable (easy to test and learn about before adoption). Non-adoption or low adoption of a number of conservation practices is readily explicable in terms of their failure to provide a relative advantage (particularly in economic terms) or a range of difficulties that landholders may have in trialing them.

Flavonoids are a large and diverse group of compounds that, by their presence or absence, contribute greatly to wine quality. While the flavonoid content and composition of a wine reflects the vinification process to some extent, the primary determinant is the composition of the grapes at harvest. Thus, considerable research has been directed toward understanding the nature of flavonoids in grapevines, the factors that influence their biosynthesis, and how this knowledge might be used to manage and manipulate the flavonoid composition of berries at harvest. This review examines the flavonoids as a class of compounds, the role these compounds play in the plant, their contributions to wine quality, and recent research on the impacts of environmental factors and cultural practices on the flavonoid content and composition of grape berries.

Abstract Genetic diversity is key to crop improvement. Owing to pervasive genomic structural variation, a single reference genome assembly cannot capture the full complement of sequence diversity of a crop species (known as the ‘pan-genome’ 1 ). Multiple high-quality sequence assemblies are an indispensable component of a pan-genome infrastructure. Barley ( Hordeum vulgare L.) is an important cereal crop with a long history of cultivation that is adapted to a wide range of agro-climatic conditions 2 . Here we report the construction of chromosome-scale sequence assemblies for the genotypes of 20 varieties of barley—comprising landraces, cultivars and a wild barley—that were selected as representatives of global barley diversity. We catalogued genomic presence/absence variants and explored the use of structural variants for quantitative genetic analysis through whole-genome shotgun sequencing of 300 gene bank accessions. We discovered abundant large inversion polymorphisms and analysed in detail two inversions that are frequently found in current elite barley germplasm; one is probably the product of mutation breeding and the other is tightly linked to a locus that is involved in the expansion of geographical range. This first-generation barley pan-genome makes previously hidden genetic variation accessible to genetic studies and breeding.

BACKGROUND: Two key findings from genomic selection experiments are 1) the reference population used must be very large to subsequently predict accurate genomic estimated breeding values (GEBV), and 2) prediction equations derived in one breed do not predict accurate GEBV when applied to other breeds. Both findings are a problem for breeds where the number of individuals in the reference population is limited. A multi-breed reference population is a potential solution, and here we investigate the accuracies of GEBV in Holstein dairy cattle and Jersey dairy cattle when the reference population is single breed or multi-breed. The accuracies were obtained both as a function of elements of the inverse coefficient matrix and from the realised accuracies of GEBV. METHODS: Best linear unbiased prediction with a multi-breed genomic relationship matrix (GBLUP) and two Bayesian methods (BAYESA and BAYES_SSVS) which estimate individual SNP effects were used to predict GEBV for 400 and 77 young Holstein and Jersey bulls respectively, from a reference population of 781 and 287 Holstein and Jersey bulls, respectively. Genotypes of 39,048 SNP markers were used. Phenotypes in the reference population were de-regressed breeding values for production traits. For the GBLUP method, expected accuracies calculated from the diagonal of the inverse of coefficient matrix were compared to realised accuracies. RESULTS: When GBLUP was used, expected accuracies from a function of elements of the inverse coefficient matrix agreed reasonably well with realised accuracies calculated from the correlation between GEBV and EBV in single breed populations, but not in multi-breed populations. When the Bayesian methods were used, realised accuracies of GEBV were up to 13% higher when the multi-breed reference population was used than when a pure breed reference was used. However no consistent increase in accuracy across traits was obtained. CONCLUSION: Predicting genomic breeding values using a genomic relationship matrix is an attractive approach to implement genomic selection as expected accuracies of GEBV can be readily derived. However in multi-breed populations, Bayesian approaches give higher accuracies for some traits. Finally, multi-breed reference populations will be a valuable resource to fine map QTL.

Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under a given set of conditions. The analysis of the metabolome is particularly challenging due to the diverse chemical nature of metabolites. Metabolites are the result of the interaction of the system's genome with its environment and are not merely the end product of gene expression but also form part of the regulatory system in an integrated manner. Metabolomics has its roots in early metabolite profiling studies but is now a rapidly expanding area of scientific research in its own right. Metabolomics (or metabonomics) has been labeled one of the new "omics", joining genomics, transcriptomics, and proteomics as a science employed toward the understanding of global systems biology. Metabolomics is fast becoming one of the platform sciences of the "omics", with the majority of the papers in this field having been published only in the last two years. In this review metabolomic methodologies are discussed briefly followed by a more detailed review of the use of metabolomics in integrated applications where metabolomics information has been combined with other "omic" data sets (proteomics, transcriptomics) to enable greater understanding of a biological system. The potential of metabolomics for natural product drug discovery and functional food analysis, primarily as incorporated into broader "omic" data sets, is discussed.

A meta-analysis of genome-wide association studies of phenotypic variation for height and body mass index in human populations using 170,000 samples shows that one single nucleotide polymorphism at the FTO locus, which is associated with obesity, is also associated with phenotypic variation. Genome-wide association studies have successfully detected thousands of single nucleotide polymorphisms (SNPs) associated with complex traits in human populations. These studies tested the associations between SNPs and a phenotype — a disease or quantitative trait — expressed as a mean of the trait. This study is different, testing for associations between SNPs and variations of the phenotype, using more than 100,000 samples on height and body mass index in human populations. The authors find that one SNP at the FTO locus, which is known to be associated with obesity, is also associated with phenotypic variability. These results demonstrate that it is possible to find genetic variants that associate with variability and that between-person variability in obesity can partly be explained by genotype at the FTO locus. However, most genetic variants are not associated with phenotypic variance, or their effects on variability are very small. There is evidence across several species for genetic control of phenotypic variation of complex traits1,2,3,4, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)5,6,7, is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation9,10. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

We describe the organization of a nascent international effort, the Functional Annotation of Animal Genomes (FAANG) project, whose aim is to produce comprehensive maps of functional elements in the genomes of domesticated animal species.

Viral diseases provide a major challenge to twenty-first century agriculture worldwide. Climate change and human population pressures are driving rapid alterations in agricultural practices and cropping systems that favor destructive viral disease outbreaks. Such outbreaks are strikingly apparent in subsistence agriculture in food-insecure regions. Agricultural globalization and international trade are spreading viruses and their vectors to new geographical regions with unexpected consequences for food production and natural ecosystems. Due to the varying epidemiological characteristics of diverent viral pathosystems, there is no one-size-fits-all approach toward mitigating negative viral disease impacts on diverse agroecological production systems. Advances in scientific understanding of virus pathosystems, rapid technological innovation, innovative communication strategies, and global scientific networks provide opportunities to build epidemiologic intelligence of virus threats to crop production and global food security. A paradigm shift toward deploying integrated, smart, and eco-friendly strategies is required to advance virus disease management in diverse agricultural cropping systems.

BACKGROUND: The theory of genomic selection is based on the prediction of the effects of genetic markers in linkage disequilibrium with quantitative trait loci. However, genomic selection also relies on relationships between individuals to accurately predict genetic value. This study aimed to examine the importance of information on relatives versus that of unrelated or more distantly related individuals on the estimation of genomic breeding values. METHODS: Simulated and real data were used to examine the effects of various degrees of relationship on the accuracy of genomic selection. Genomic Best Linear Unbiased Prediction (gBLUP) was compared to two pedigree based BLUP methods, one with a shallow one generation pedigree and the other with a deep ten generation pedigree. The accuracy of estimated breeding values for different groups of selection candidates that had varying degrees of relationships to a reference data set of 1750 animals was investigated. RESULTS: The gBLUP method predicted breeding values more accurately than BLUP. The most accurate breeding values were estimated using gBLUP for closely related animals. Similarly, the pedigree based BLUP methods were also accurate for closely related animals, however when the pedigree based BLUP methods were used to predict unrelated animals, the accuracy was close to zero. In contrast, gBLUP breeding values, for animals that had no pedigree relationship with animals in the reference data set, allowed substantial accuracy. CONCLUSIONS: An animal's relationship to the reference data set is an important factor for the accuracy of genomic predictions. Animals that share a close relationship to the reference data set had the highest accuracy from genomic predictions. However a baseline accuracy that is driven by the reference data set size and the overall population effective population size enables gBLUP to estimate a breeding value for unrelated animals within a population (breed), using information previously ignored by pedigree based BLUP methods.

Some 290 species of squids comprise the order Teuthida that belongs to the molluscan Class Cephalopoda.Of these, about 30 40 squid species have substantial commercial importance around the world.Squid fisheries make a rather small contribution to world landings from capture fisheries relative to that of fish, but the proportion has increased steadily over the last decade, with some signs of recent leveling off.The present overview describes all substantial squid fisheries around the globe.The main ecological and biological features of exploited stocks, and key aspects of fisheries management are presented for each commercial species of squid worldwide.The history and fishing methods used in squid fisheries are also described.Special attention has been paid to interactions between squid fisheries and marine ecosystems including the effects of fishing gear, the role of squid in ecosystem change induced by overfishing on groundfish, and ecosystem based fishery management.

Management areas are used in marine spatial planning to conserve biodiversity of marine ecosystems and to protect fish from fishing pressure. To evaluate the effectiveness of these protected areas, observational techniques are used to determine densities, sizes, biomass, habitat types and distribution of fish species in and around management areas. Two types of observational techniques are used in spatial monitoring: (1) fishery-independent techniques, which include underwater visual census (UVC), underwater video, remote sensing, acoustics, and experimental catch and effort data; and (2) fishery-dependent techniques, which include catch, effort and catch per unit effort data from commercial and recreational fisheries. This review summarises the applications, advantages, disadvantages and biases of each of these observational categories and highlights emerging technologies. The main finding from this review was that a combination of observational techniques, rather than a single method, was the most effective approach to marine spatial monitoring. For example, a combination of hydroacoustics for habitat mapping and UVC or video for fish surveys was one of the most cost-effective and efficient means of obtaining fish-habitat linkages and fish assemblage data. There are also emerging technologies that could increase the precision and efficiency of monitoring surveys. There is a need for continued development of non-intrusive technology for marine monitoring studies.

BACKGROUND: Inbreeding reduces the fitness of individuals by increasing the frequency of homozygous deleterious recessive alleles. Some insight into the genetic architecture of fitness, and other complex traits, can be gained by using single nucleotide polymorphism (SNP) data to identify regions of the genome which lead to reduction in performance when identical by descent (IBD). Here, we compared the effect of genome-wide and location-specific homozygosity on fertility and milk production traits in dairy cattle. METHODS: Genotype data from more than 43 000 SNPs were available for 8853 Holstein and 4138 Jersey dairy cows that were part of a much larger dataset that had pedigree records (338 696 Holstein and 64 049 Jersey animals). Measures of inbreeding were based on: (1) pedigree data; (2) genotypes to determine the realised proportion of the genome that is IBD; (3) the proportion of the total genome that is homozygous and (4) runs of homozygosity (ROH) which are stretches of the genome that are homozygous. RESULTS: A 1% increase in inbreeding based either on pedigree or genomic data was associated with a decrease in milk, fat and protein yields of around 0.4 to 0.6% of the phenotypic mean, and an increase in calving interval (i.e. a deterioration in fertility) of 0.02 to 0.05% of the phenotypic mean. A genome-wide association study using ROH of more than 50 SNPs revealed genomic regions that resulted in depression of up to 12.5 d and 260 L for calving interval and milk yield, respectively, when completely homozygous. CONCLUSIONS: Genomic measures can be used instead of pedigree-based inbreeding to estimate inbreeding depression. Both the diagonal elements of the genomic relationship matrix and the proportion of homozygous SNPs can be used to measure inbreeding. Longer ROH (>3 Mb) were found to be associated with a reduction in milk yield and captured recent inbreeding independently and in addition to overall homozygosity. Inbreeding depression can be reduced by minimizing overall inbreeding but maybe also by avoiding the production of offspring that are homozygous for deleterious alleles at specific genomic regions that are associated with inbreeding depression.

BACKGROUND: Bread wheat is an allopolyploid species with a large, highly repetitive genome. To investigate the impact of selection on variants distributed among homoeologous wheat genomes and to build a foundation for understanding genotype-phenotype relationships, we performed population-scale re-sequencing of a diverse panel of wheat lines. RESULTS: A sample of 62 diverse lines was re-sequenced using the whole exome capture and genotyping-by-sequencing approaches. We describe the allele frequency, functional significance, and chromosomal distribution of 1.57 million single nucleotide polymorphisms and 161,719 small indels. Our results suggest that duplicated homoeologous genes are under purifying selection. We find contrasting patterns of variation and inter-variant associations among wheat genomes; this, in addition to demographic factors, could be explained by differences in the effect of directional selection on duplicated homoeologs. Only a small fraction of the homoeologous regions harboring selected variants overlapped among the wheat genomes in any given wheat line. These selected regions are enriched for loci associated with agronomic traits detected in genome-wide association studies. CONCLUSIONS: Evidence suggests that directional selection in allopolyploids rarely acted on multiple parallel advantageous mutations across homoeologous regions, likely indicating that a fitness benefit could be obtained by a mutation at any one of the homoeologs. Additional advantageous variants in other homoelogs probably either contributed little benefit, or were unavailable in populations subjected to directional selection. We hypothesize that allopolyploidy may have increased the likelihood of beneficial allele recovery by broadening the set of possible selection targets.

Ascochyta blight (AB), caused by Ascochyta rabiei is a major disease of chickpea (Cicer arietinum L.), especially in areas where cool, cloudy, and humid weather persists during the crop season. Several epidemics of AB causing complete yield loss have been reported. The fungus mainly survives between seasons through infected seed and in infected crop debris. Despite extensive pathological and molecular studies, the nature and extent of pathogenic variability in A. rabiei have not been clearly established. Accumulation of phenols, phytoalexins (medicarpin and maackiain), and hydrolytic enzymes has been associated with host-plant resistance (HPR). Seed treatment and foliar application of fungicides are commonly recommended for AB management, but further information on biology and survival of A. rabiei is needed to devise more effective management strategies. Recent studies on inheritance of AB resistance indicate that several quantitative trait loci (QTLs) control resistance. In this paper we review the biology of A. rabiei, HPR, and management options, with an emphasis on future research priorities.

The relationships between sensory traits (tenderness, juiciness, flavour and overall liking) and objective measures, such as shear force, intramuscular fat, cooking loss, pH and animal age, were derived for M. longissimus thoracis et lumborum (LL) from 471 lamb and sheep carcasses. Tenderness could be predicted with the most accuracy (R2 = 0.24) and flavour with the highest precision (r.s.d. = 7.5 units) when using the objective measures, which may be in part due to the small variation in the range of shear force values of the samples (all carcasses electrically stimulated and meat aged for 5 days) and the use of consumer panels for the assessment of sensory traits. The ultimate pH of the LL, the rate of decline in pH in the LL or the predicted temperature at pH 6.0 were not significant predictors of the sensory traits when tested on a subsample of the carcasses. The model coefficients indicated that all sensory traits (tenderness, flavour, juiciness and overall liking) declined as shear force and age increased, and as intramuscular fat percentage decreased. This translated into a decline of 16 points on average for tenderness and 13 points for overall liking when LL samples from 68.5-month-old sheep were compared with those from unweaned lambs, when adjusted to the same level of intramuscular fat and shear force. Predictions of the sensory traits at varying levels of shear force were made and show that at 49 Newtons (N), the overall liking score would be 51 and the tenderness score 48. Derived relationships between objective meat quality measures and sensory traits suggest that to achieve a failure rate of no more than 10% for loin meat when eaten, it must have a shear force of about 27 N or less.

Oxidation of meat occurs under postmortem conditions and is inevitable. This oxidation includes the biochemical changes in meat leading to changes in color pigments and lipids. As a consequence, color deteriorates, and undesirable flavors and rancidity develop in meat thereby impacting on consumer appeal and satisfaction. Across carcasses, there is variation in the rate at which muscle undergoes chemical reactions under postmortem conditions that reflect inherent variation at the biochemical level. It is expected that this underlying biochemical variation will be reflected in living muscle through oxidative processes. The oxidative process of muscle tissues will vary according to an animal's immunity status, temperament, and ability to cope with stress, with all these affected by nutrition, genetics, management practices, and environmental conditions (hot and cold seasons). Identification of biomarkers that indicate the oxidative status levels of animals or muscle tissues in vivo could provide insight as to how the muscle will respond to the anoxic conditions that produce undesirable results in meat. This review outlines the potential use of 1 group of biomarkers, the isoprostanes, in the context of complex biochemical reactions relating to oxidative processes that take place in the biological systems of live animals (in vivo) and subsequently in meat (in vitro).

The importance of organic matter produced in seagrass meadows (seagrass and epiphytic algae) to the nutrition of a valuable fisheries species (yellowfin whiting Sillago schomburgkii Peters) occurring over unvegetated mudflats was measured using the isotopic composition (δ 13 C, δ 15 N) of fish, their polychaete prey, and available autotrophic sources at several locations in southern Australia during 2 periods (summer, winter).Values for δ 13 C and δ 15 N for autotrophs and fishes varied little between seasons.Sources could be separated into 3 groups based on δ 13 C: seagrass and epiphytes (mean δ 13 C = -10.5 ‰), benthic microalgae and macroalgae (-19.5 ‰), and saltmarsh and mangroves (-26.5 ‰).Values of δ 15 N for the sources were 2 to 5 ‰.Values of δ 13 C for fish (-13.3 ‰) corresponded with those of their polychaete prey (-12.5 ‰) and ultimately with those of seagrass and epiphytes.Values of δ 15 N were 5 to 6 ‰ more enriched than sources.Modelling of feasible source mixtures showed that seagrass and epiphytes were the most important contributors to the nutrition of fish, but their relative importance varied between seasons.The median contribution by other sources was <10%.Spatial analyses showed that saltmarsh plants contributed significantly to the variability in S. schomburgkii nutrition among locations, while macroalgae contributed in summer.The similarity in δ 13 C values of polychaetes and S. schomburgkii is consistent with source material from a subtidal habitat being incorporated into food webs supporting a fisheries species in adjacent intertidal habitats via a largely sedentary intermediary.

Abstract Bactrocera papayae D rew & H ancock, B actrocera philippinensis D rew & H ancock, B actrocera carambolae D rew & H ancock, and B actrocera invadens D rew, T suruta & W hite are four horticultural pest tephritid fruit fly species that are highly similar, morphologically and genetically, to the destructive pest, the O riental fruit fly, B actrocera dorsalis ( H endel) ( D iptera: T ephritidae). This similarity has rendered the discovery of reliable diagnostic characters problematic, which, in view of the economic importance of these taxa and the international trade implications, has resulted in ongoing difficulties for many areas of plant protection and food security. Consequently, a major international collaborative and integrated multidisciplinary research effort was initiated in 2009 to build upon existing literature with the specific aim of resolving biological species limits among B . papayae , B . philippinensis , B . carambolae , B . invadens and B . dorsalis to overcome constraints to pest management and international trade. Bactrocera philippinensis has recently been synonymized with B . papayae as a result of this initiative and this review corroborates that finding; however, the other names remain in use. While consistent characters have been found to reliably distinguish B . carambolae from B . dorsalis , B . invadens and B . papayae , no such characters have been found to differentiate the latter three putative species. We conclude that B . carambolae is a valid species and that the remaining taxa, B . dorsalis , B . invadens and B . papayae , represent the same species. Thus, we consider B . dorsalis ( H endel) as the senior synonym of B . papayae D rew and H ancock syn.n. and B . invadens D rew, T suruta & W hite syn.n. A redescription of B . dorsalis is provided. Given the agricultural importance of B . dorsalis , this taxonomic decision will have significant global plant biosecurity implications, affecting pest management, quarantine, international trade, postharvest treatment and basic research. Throughout the paper, we emphasize the value of independent and multidisciplinary tools in delimiting species, particularly in complicated cases involving morphologically cryptic taxa.

During application of agrochemicals spray droplets can drift beyond the intended target to non-target receptors, including water, plants and animals. Factors affecting this spray drift include mode of application, droplet size, which can be modified by the nozzle types, formulation adjuvants, wind direction, wind speed, air stability, relative humidity, temperature and height of released spray relative to the crop canopy. The rate of fall of spray droplets depends upon the size of the droplets but is modified by entrainment in a mobile air mass and is also influenced by the rate of evaporation of the liquid constituting the aerosol. The longer the aerosol remains in the air before falling to the ground (or alternatively striking an object above ground) the greater the opportunity for it to be carried away from its intended target. In general, all size classes of droplets are capable of movement off target, but the smallest are likely to move the farthest before depositing on the ground or a non-target receptor. It is not possible to avoid spray drift completely but it can be minimized by using best-management practices. These include using appropriate nozzle types, shields, spray pressure, volumes per area sprayed, tractor speed and only spraying when climatic conditions are suitable. Field layout can also influence spray drift, whilst crop-free and spray-free buffer zones and windbreak crops can also have a mitigating effect. Various models are available to estimate the environmental exposure from spray drift at the time of application.