Yellow Canopy Syndrome (YCS) is a complex that currently only affects commercial sugarcane ( Saccharum sp. hybrids) in Australia. It was first detected in Far North Queensland over a decade ago and has since spread to most cane-growing areas from Far North Queensland down to Southern Queensland. YCS represents a serious challenge to not only the Australian sugarcane industry but also a potential threat to sugarcane industries worldwide. The symptoms and physiological impacts of YCS have been well described. However, despite a decade of research, the underlying causal factor(s) of YCS still need to be fully determined. Multidisciplinary research has focused on several abiotic and biotic factors to determine the symptoms and potential causes of YCS. Although not yet conclusive, the most recent research findings exploring the impact of pesticide application on YCS symptom expression levels indicate that invertebrates may play a role. Furthermore, studies have focused on optimising invertebrate sampling strategies and exploring their population dynamics in relation to YCS expression to determine which invertebrate species may be involved. Other research involves developing effective detection and surveillance approaches for YCS. This report reviews the YCS-related research published to date. It concludes that there are still some fundamental knowledge gaps that need to be addressed before the risk to other sugarcane-producing countries other than Australia can be determined and before effective YCS management strategies can be developed.

Grapevine ( Parthenolecanium persicae (F.)) and frosted ( Parthenolecanium pruinosum (Coq.)) scale insects may cause long‐term physiological damage to grapevines. Although they persist in major grape‐growing regions of Australia, the reproductive and population growth potential of these insect pests is poorly understood. The reproductive output of gravid adult females of grapevine and frosted scales was studied under lab and field conditions on Riesling, Chardonnay and Sauvignon Blanc cultivars of European grapevine Vitis vinifera L. The intrinsic rate of increase of grapevine and frosted scales was also studied on Riesling and Chardonnay cultivars, respectively. Gravid adult females of grapevine scale have a larger body length and body mass and higher fecundity than those of frosted scale. Egg and first instar sizes were smaller for grapevine scale than for frosted scale. Egg incubation period, post‐oviposition by adult females, was affected by grapevine cultivars, being 20 days on Chardonnay and 19 days on Riesling for grapevine scale and 18 days on Chardonnay and Riesling and 22 days on Sauvignon Blanc for frosted scale. Neither fertility nor fecundity was affected by grapevine cultivar. The intrinsic rate of increase ( r m ) was 0.28 per month for grapevine scale on Riesling and 0.29 per month for frosted scale on Chardonnay. The finite rate of increase ( λ ) for grapevine and frosted scales was 1.28 and 1.33 months, respectively, and the population doubling time (DT) was 2.5 and 2.40 months for grapevine and frosted scales, respectively. Based on these observations, the population of grapevine and frosted scales is likely to persist in vineyards and may rise to outbreak levels that require management.

In recent years, the precise identification of an insect pest infestation has become increasingly critical for effective management in agricultural fields. This research addresses the imperative need for an advanced and integrated approach to mapping insect pest infestation in agricultural crops, utilising unmanned aerial vehicles (UAVs), multispectral (MS) imagery, and deep learning (DL). The existing literature reveals a limited number of studies that harness the potential of UAV-based MS imagery in conjunction with DL models for mapping and managing insect pest infestations. The primary aim is to enhance the precision and efficiency of insect pest infestation mapping through the synergistic analysis of spectral bands, vegetation indices (VIs), and textural features using DL techniques. The aerial imagery and ground truth information were collected in crop field for mapping of insect pest infestation. The investigation comprised three specific analyses; first is about establishing correlations between insect pest pupal count versus spectral bands and VIs. Second, the performance comparison of three DL models including U-Net, DeepLabV3+, Fully Convolutional Network (FCN) to segment three classes including insect pest infestation patches, other vegetation (weeds), and crops. Finally, the third analysis evaluated the efficacy of textural features against spectral features in mapping an insect pest infestation using DL techniques. The results indicate that, concerning the correlation between pupal count in the field and spectral bands or VIs, the Simple Ratio Index (SRI), and Red Edge Chlorophyll Index (RECI) demonstrated a positive correlation of 0.7, whereas the Green Chlorophyll Index (GCI) displayed a positive correlation of 0.6. Another key finding shows that spectral features outperformed textural features across all DL models for insect pest infestation segmentation. The research highlights the effectiveness of spectral features, particularly with the FCN model, which demonstrated best performance metrics for insect pest segmentation in the study field. The FCN model achieved scores with a precision (P) of 93%, recall (R) of 97%, F1-score (F1) of 95%, and Intersection over Union (IoU) of 90%, underscoring its excellence in accurately identifying and delineating pest infestations in the field. The proposed methodology and its findings offer implications such as enhanced pest surveillance, timely intervention, precision pest management, and optimised resource allocation that can be extended to optimise insect pest infestation mapping in various crop lands, enabling precise control strategies aimed at enhancing crop yield.

This research is focused on a comparative field-based study of the population dynamics and sampling methods of two mealybug species, Saccharicoccus sacchari (Cockerell, 1895) (Hemiptera: Coccomorpha, Pseudococcidae) and Heliococcus summervillei (Brookes, 1978) (Hemiptera: Coccomorpha, Pseudococcidae), in sugarcane (Saccharum sp. hybrids) (f. Poaceae) over consecutive growing seasons. The research monitored and compared the above- and belowground populations and seasonal abundance of these two mealybug species in sugarcane fields in Far North Queensland, with non-destructive sampling techniques of yellow sticky traps, pan traps, and stem traps, and destructive sampling of the whole leaf and whole plant. The results indicated that S. sacchari (n = 29,137) was more abundant and detected throughout the growing season, with population peaks in the mid-season, while H. summervillei (n = 2706) showed peaks of the early-season activity. S. sacchari is primarily located on sugarcane stems and roots, compared to H. summervillei, which is located on leaves and roots. The whole-leaf collection and stem trap were the most effective sampling techniques for quantification of H. summervillei and S. sacchari, respectively. This study enhanced the understanding of S. sacchari and the first-ever record of H. summervillei on sugarcane in Australia and will contribute to the development of more effective pest management strategies.

Rearing insects in controlled conditions is a prerequisite to supply high‐quality specimens for bioassays. However, while artificial diets and standardized rearing methods have been developed for many phytophagous insects, especially Lepidoptera, there are limited published diets for root‐feeding Coleoptera which are commonly fed either grass roots or pieces of vegetables as a simple alternative to artificial diets during bioassays. These feeding options, while convenient, can be considered suboptimal as they do not maximise the insects' development and health. Additionally, it is also important to develop standardised screening methods designed to test sublethal effects of control agents which may have repellent, antifeedant, antimetabolic and/or delayed mortality effects. The greyback canegrub ( Dermolepida albohirtum , Waterhouse) is the most damaging native pest of Australian sugarcane, but no rearing method or artificial diet has ever been developed for this species. Our objectives were to improve bioassay methodology for D. albohirtum by describing and developing standard rearing and health assessment protocols. We describe a successful rearing method to raise healthy D. albohirtum larvae with a total of 48.8% of first instars successfully moulting to the second instar. We also tested a modified artificial diet which increased the weight, size and food uptake of larvae compared to traditional methods (i.e., pieces of carrots). For example, the average weight increase of larvae fed with the modified diet was 3.4 times higher than for carrot‐fed larvae while modified diet‐fed larvae were 2.1 times wider than if they were fed with carrots. Finally, we developed a method to measure larval activity which can be used to identify sublethal effects of control agents such as effects on activity level. Our methods may also be applied to improve bioassay methodology for other root‐feeding Coleoptera.

Background and Aims. Grape phylloxera in Australia comprises diverse genetic strains that feed on roots and leaves of Vitis spp. The G38 phylloxera strain was detected on roots of Vitis spp., for the first time in North East Victoria in 2015. Prior to 2015, G38 phylloxera was only known to feed on leaves. The aim of this study was to evaluate the survival and development of G38 phylloxera on roots of diverse Vitis spp. under field, controlled laboratory, and greenhouse conditions. Methods and Results. In the field, emergence traps quantified first instars and alates emerging from roots of diverse rootstocks and Vitis vinifera L. High numbers of phylloxera were collected in traps placed at vines of rootstocks 101-14, 3309 Courderc and Schwarzmann. Nodosity were also observed on roots of 101-14, 3309 Courderc and Schwarzmann in the field and in-pot vines experiments. The better performance of G38 phylloxera on these three rootstocks compared to V. vinifera in the field and in potted vines parallelled the excised roots experiments. Conclusions. The relatively high performance of G38 phylloxera on the 101-14, 3309 Courderc and Schwarzmann rootstocks suggest a susceptible response and could be associated with rootstock parentage. Further investigation is warranted to determine implications for rootstocks development. Significance of the Study. These findings are fundamental for decision-making in phylloxera risk assessment and rootstock selection. The study reaffirms the need for triphasic (in vitro, in planta, and in-field) rootstock screening protocols for phylloxera.

The fall armyworm (FAW) Spodoptera frugiperda is thought to have undergone a rapid 'west-to-east' spread since 2016 when it was first identified in western Africa. Between 2018 and 2020, it was recorded from South Asia (SA), Southeast Asia (SEA), East Asia (EA), and Pacific/Australia (PA). Population genomic analyses enabled the understanding of pathways, population sources, and gene flow in this notorious agricultural pest species. Using neutral single nucleotide polymorphic (SNP) DNA markers, we detected genome introgression that suggested most populations in this study were overwhelmingly C- and R-strain hybrids (n = 252/262). SNP and mitochondrial DNA markers identified multiple introductions that were most parsimoniously explained by anthropogenic-assisted spread, i.e., associated with international trade of live/fresh plants and plant products, and involved 'bridgehead populations' in countries to enable successful pest establishment in neighbouring countries. Distinct population genomic signatures between Myanmar and China do not support the 'African origin spread' nor the 'Myanmar source population to China' hypotheses. Significant genetic differentiation between populations from different Australian states supported multiple pathways involving distinct SEA populations. Our study identified Asia as a biosecurity hotspot and a FAW genetic melting pot, and demonstrated the use of genome analysis to disentangle preventable human-assisted pest introductions from unpreventable natural pest spread.

Sugarcane white leaf phytoplasma (white leaf disease) in sugarcane crops is caused by a phytoplasma transmitted by leafhopper vectors. White leaf disease (WLD) occurs predominantly in some Asian countries and is a devastating global threat to sugarcane industries, especially Sri Lanka. Therefore, a feasible and an effective approach to precisely monitoring WLD infection is important, especially at the early pre-visual stage. This work presents the first approach on the preliminary detection of sugarcane WLD by using high-resolution multispectral sensors mounted on small unmanned aerial vehicles (UAVs) and supervised machine learning classifiers. The detection pipeline discussed in this paper was validated in a sugarcane field located in Gal-Oya Plantation, Hingurana, Sri Lanka. The pixelwise segmented samples were classified as ground, shadow, healthy plant, early symptom, and severe symptom. Four ML algorithms, namely XGBoost (XGB), random forest (RF), decision tree (DT), and K-nearest neighbors (KNN), were implemented along with different python libraries, vegetation indices (VIs), and five spectral bands to detect the WLD in the sugarcane field. The accuracy rate of 94% was attained in the XGB, RF, and KNN to detect WLD in the field. The top three vegetation indices (VIs) for separating healthy and infected sugarcane crops are modified soil-adjusted vegetation index (MSAVI), normalized difference vegetation index (NDVI), and excess green (ExG) in XGB, RF, and DT, while the best spectral band is red in XGB and RF and green in DT. The results revealed that this technology provides a dependable, more direct, cost-effective, and quick method for detecting WLD.

Soldier flies are economically damaging pests of sugarcane, particularly in central and southern Queensland. Despite decades of research on soldier fly control, the search for an effective management approach, except for cultural control, remains elusive. Trials were conducted from 2015 to 2017 to identify potential management solutions for soldier flies by assessing insecticide efficacy and varietal tolerance in field conditions. Five field trials were established to determine whether applying insecticide to plant cane would reduce the build-up in soldier fly larvae in subsequent ratoons. Ten products, comprising seven active ingredients, were field-tested at high application rates. Overall, as in most previous studies, none of the insecticides tested reduced the number of larvae in field-trial conditions. The inefficacy of insecticide treatments could be due to products failing to come into contact with soldier fly larvae or simply lacking effective activity. In addition, three field trials, using up to 14 varieties, were conducted, to assess varietal tolerance. Some varieties tended to host fewer larvae than others, suggesting some resistance, in two trials established in southern Queensland. Any future insecticide and varietal screening trials will need to be conducted in both controlled laboratory and field conditions. However, before such trials can be undertaken, a standardised laboratory rearing method and improved field sampling strategy for soldier flies needs to be developed. Soldier fly outbreaks are also unpredictable and developing methods to forecast them (e.g. using climatic data or identifying preferential soil properties) will also be highly beneficial in informing growers of the potential risk of soldier fly establishment in their paddocks and for selecting field-trial sites. Additionally, recent DNA barcoding and morphological studies have revealed that at least six species of soldier flies are found in sugarcane, not two as previously identified. That finding highlights that the distribution of soldier fly species in Australia and the relative damage to sugarcane varieties needs to be resolved to enable the development of targeted species-specific management approaches.

White leaf disease (WLD) is an economically significant disease in the sugarcane industry. This work applied remote sensing techniques based on unmanned aerial vehicles (UAVs) and deep learning (DL) to detect WLD in sugarcane fields at the Gal-Oya Plantation, Sri Lanka. The established methodology to detect WLD consists of UAV red, green, and blue (RGB) image acquisition, the pre-processing of the dataset, labelling, DL model tuning, and prediction. This study evaluated the performance of the existing DL models such as YOLOv5, YOLOR, DETR, and Faster R-CNN to recognize WLD in sugarcane crops. The experimental results indicate that the YOLOv5 network outperformed the other selected models, achieving a precision, recall, mean average precision@0.50 (mAP@0.50), and mean average precision@0.95 (mAP@0.95) metrics of 95%, 92%, 93%, and 79%, respectively. In contrast, DETR exhibited the weakest detection performance, achieving metrics values of 77%, 69%, 77%, and 41% for precision, recall, mAP@0.50, and mAP@0.95, respectively. YOLOv5 is selected as the recommended architecture to detect WLD using the UAV data not only because of its performance, but this was also determined because of its size (14 MB), which was the smallest one among the selected models. The proposed methodology provides technical guidelines to researchers and farmers for conduct the accurate detection and treatment of WLD in the sugarcane fields.

Canegrubs (Coleoptera: Scarabaeidae) are major pests of sugarcane crops in Australia, but despite long-term and intensive research, no commercially viable biological control agents have been identified. We used the RNA-Seq approach to explore the viriomes of three different species of canegrubs from central Queensland, Australia to identify potential candidates for biological control. We identified six novel RNA viruses, characterized their genomes, and inferred their evolutionary relationships with other closely related viruses. These novel viruses showed similarity to other known members from picornaviruses, benyviruses, sobemoviruses, totiviruses, and reoviruses. The abundance of viral reads varied in these libraries; for example, Dermolepida albohirtum picorna-like virus (9696 nt) was built from 83,894 assembled reads while only 1350 reads mapped to Lepidiota negatoria beny-like virus (6371 nt). Future studies are essential to determine their natural incidence in different life stages of the host, biodiversity, geographical distributions, and potential as biological control agents for these important pests of sugarcane.

Recent advancements in the application of unmanned aerial vehicles (UAVs) based remote sensing (RS) in precision agricultural practices have been critical in enhancing crop health and management. UAV-based RS and advanced computational algorithms including Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL), are progressively being applied to make predictions, solve decisions to optimize the production and operation processes in many farming industries such as sugarcane. UAVs with various advanced sensors, including RGB, multispectral, hyperspectral, LIDAR, and thermal cameras, have been used for crop RS applications as they can provide new approaches and research opportunities in precision sugarcane production. This review focuses on the use of UAVs in the sugarcane industry for pest and disease management, yield estimation, phenotypic measurement, soil moisture assessment, and nutritional status evaluation to improve the productivity and environmental sustainability. The goals of this review were to: (1) assemble information on the application of UAVs in the sugarcane industry; and (2) discuss their benefits and limitations in a variety of applications in UAV-based sugarcane cultivation. A literature review was conducted utilizing three bibliographic databases, including Google Scholar, Scopus, Web of Science, and 179 research articles that are relevant to UAV applications in sugarcane and other general information about UAV and sensors collected from the databases mentioned earlier. The study concluded that UAV-based crop RS can be an effective method for sugarcane monitoring and management to improve yield and quality and significantly benefits on social, economic, and environmental aspects. However, UAV-based RS should also consider some of the challenges in sugar industries include technological adaptations, high initial cost, inclement weather, communication failures, policy, and regulations.

Pathogens which need a vector for their transmission can alter the vectors’ behaviour to favour their spread. We used the electrical penetration graph technique to investigate this hypothesis by using the tomato potato psyllid Bactericera cockerelli infected or not with the plant pathogen Candidatus Liberibacter solanacearum (CLso) on African boxthorn and tomato. Probing was not affected by the host type but there was a significant effect on probing due to the infection status of the psyllid. More psyllids carried out probing activities in the sieve elements when infected with CLso, and more probing activities were observed from CLso-infected psyllids by comparison to the non-infected groups. Specifically, significant increases in salivation, phloem ingestion and number of probes, before and after reaching the sieve elements, were noticed in the infected groups. Furthermore, time elapsed to reach the sieve elements was significantly shortened by 2 h in the infected group. Remaining probing activities in xylem tissues were not different between all psyllid groups. The observed changes in feeding behaviour by pathogen-infected psyllids may well ensure further spread of the pathogen as greater salivation has the potential to increase transmission, highlighting at the same time the important role that crop and non-crop hosts play in disease epidemiology.

Pathogens which need a vector for their transmission can alter the vectors' behaviour to favour their spread. We used the electrical penetration graph technique to investigate this hypothesis by using the tomato potato psyllidBactericera cockerelliinfected or not with the plant pathogenCandidatusLiberibacter solanacearum (CLso) on African boxthorn and tomato. Probing was not affected by the host type but there was a significant effect on probing due to the infection status of the psyllid. More psyllids carried out probing activities in the sieve elements when infected with CLso, and more probing activities were observed from CLso-infected psyllids by comparison to the non-infected groups. Specifically, significant increases in salivation, phloem ingestion and number of probes, before and after reaching the sieve elements, were noticed in the infected groups. Furthermore, time elapsed to reach the sieve elements was significantly shortened by 2 h in the infected group. Remaining probing activities in xylem tissues were not different between all psyllid groups. The observed changes in feeding behaviour by pathogen-infected psyllids may well ensure further spread of the pathogen as greater salivation has the potential to increase transmission, highlighting at the same time the important role that crop and non-crop hosts play in disease epidemiology.

Systematic management of plant canopy is an important tool for optimizing economic and environmental outcomes by integrating food crops and cash crops and in tree crop production systems. It can be an effective tool in the attainment of food security through diversification of risk and income by small scale farmers. Many smallholder coffee farmers often face a difficult choice between cash (tree) crops and food crops on their limited landholdings, while an ideal situation would be a capacity to grow both crops concurrently. In their natural ecosystems, these bushy crops grow under large trees, and hence, in commercial farms both coffee and cocoa are grown under shade trees in polyculture farming systems. These systems involve the farmers growing these bushy crops grown under larger shade trees, and then growing mostly seasonal food crops as groundcover. In this short review, we considered how management of the upper (shade tree) and middle (coffee) canopies influence yields of the fruit tree and food crops and hence productivity of the whole farm. We identified several desirable features of shade trees needed to optimise coffee productivity to include minimal management requirements, persistence, short and open canopy, and deciduous phenology, amongst others. We present examples of where growing food crops with coffee in polyculture system generally had minimal impact on the yields of coffee beans, but actually often increased net economic yield by up to 400% over that obtained from farms growing coffee alone.

Lepidopteran stemborers are among the most damaging agricultural pests worldwide, able to reduce crop yields by up to 40%. Sugarcane is the world's most prolific crop, and several stemborer species from the families Noctuidae, Tortricidae, Crambidae and Pyralidae attack sugarcane. Australia is currently free of the most damaging stemborers, but biosecurity efforts are hampered by the difficulty in morphologically distinguishing stemborer species. Here we assess the utility of DNA barcoding in identifying stemborer pest species. We review the current state of the COI barcode sequence library for sugarcane stemborers, assembling a dataset of 1297 sequences from 64 species. Sequences were from specimens collected and identified in this study, downloaded from BOLD or requested from other authors. We performed species delimitation analyses to assess species diversity and the effectiveness of barcoding in this group. Seven species exhibited < 0.03 K2P interspecific diversity, indicating that diagnostic barcoding will work well in most of the studied taxa. We identified 24 instances of identification errors in the online database, which has hampered unambiguous stemborer identification using barcodes. Instances of very high within-species diversity indicate that nuclear markers (e.g. 18S, 28S) and additional morphological data (genitalia dissection of all lineages) are needed to confirm species boundaries.

Entomopathogenic Ascomycetes: Hypocreales fungi occur worldwide in the soil; however, the abundance and distribution of these fungi in a vineyard environment is unknown. A survey of Australian vineyards was carried out in order to isolate and identify entomopathogenic fungi. A total of 240 soil samples were taken from eight vineyards in two states (New South Wales and Victoria). Insect baiting (using Tenebrio molitor) and soil dilution methods were used to isolate Beauveria spp. and Metarhizium spp. from all soil samples. Of the 240 soil samples, 60% contained either Beauveria spp. (26%) or Metarhizium spp. (33%). Species of Beauveria and Metarhizium were identified by sequencing the B locus nuclear intergenic region (Bloc) and elongation factor-1 alpha (EFT1) regions, respectively. Three Beauveria species (B. bassiana, B. australis and B. pseudobassiana) and six Metarhizium species (M. guizhouense, M. robertsii, M. brunneum, M. flavoviride var. pemphigi, M. pingshaense and M. majus) were identified. A new sister clade made up of six isolates was identified within B. australis. Two potentially new phylogenetic species (six isolates each) were found within the B. bassiana clade. This study revealed a diverse community of entomopathogenic fungi in sampled Australian vineyard soils.

Background and Aims Grape phylloxera, Daktulosphaira vitifoliae Fitch, is an important biosecurity pest in Australia. As part of a management strategy, movement of grapevine cuttings, rootlings and propagation material must comply with the National Phylloxera Management Protocols which recommend a hot water treatment. This study validated the effectiveness of the protocol against genetically diverse phylloxera strains and developmental stages. Methods and Results Excised roots of Vitis vinifera L. infested with first instars of phylloxera G1, G4, G7, G19, G20 and G30 genetic strains, and eggs, intermediates and adult stages of G4 were immersed in water for 5 and 30 min at 22, 40, 45, 50 and 54 degrees C. Treatments of 45 degrees C for 30 min and >50 degrees C for a minimum of 5 min resulted in 100% mortality of first instars across all six genetic strains as well as eggs, intermediates and adults of phylloxera G4 strain. Insects survived at 22 and 40 degrees C when immersed for 5 and 30 min and 45 degrees C for 5 min and subsequently developed into egg laying adults. Conclusions Hot water immersion for grapevine root material, as currently recommended in the National Phylloxera Management Protocols is effective for disinfestation of genetically diverse phylloxera and developmental stages. A lower temperature treatment of 45 degrees C for 30 min was 100% effective across diverse strains and developmental stages. Significance of the Study Immersion duration and water temperature are important considerations for effective disinfestation of grapevine material against genetically diverse phylloxera strains and different developmental stages.

Background Grape phylloxera ( Daktulosphaira vitifoliae Fitch) is a major insect pest that negatively impacts commercial grapevine performance worldwide. Consequently, the use of phylloxera resistant rootstocks is an essential component of vineyard management. However, the majority of commercially available rootstocks used in viticulture production provide limited levels of grape phylloxera resistance, in part due to the adaptation of phylloxera biotypes to different Vitis species. Therefore, there is pressing need to develop new rootstocks better adapted to specific grape growing regions with complete resistance to grape phylloxera biotypes. Results Grapevine rootstock breeding material, including an accession of Vitis cinerea and V. aestivalis , DRX55 ([ M. rotundifolia x V. vinifera ] x open pollinated) and MS27-31 ( M. rotundifolia specific hybrid), provided complete resistance to grape phylloxera in potted plant assays. To map the genetic factor(s) of grape phylloxera resistance, a F 1 V. cinerea x V. vinifera Riesling population was screened for resistance. Heritability analysis indicates that the V. cinerea accession contained a single allele referred as RESISTANCE TO DAKTULOSPHAIRA VITIFOLIAE 2 ( RDV2 ) that confers grape phylloxera resistance. Using genetic maps constructed with pseudo-testcross markers for V. cinerea and Riesling, a single phylloxera resistance locus was identified in V. cinerea . After validating SNPs at the RDV2 locus, interval and linkage mapping showed that grape phylloxera resistance mapped to linkage group 14 at position 16.7 cM. Conclusion The mapping of RDV2 and the validation of markers linked to grape phylloxera resistance provides the basis to breed new rootstocks via marker-assisted selection that improve vineyard performance.

This paper describes field trials of Unmanned Aerial Vehicles (UAV) integrated with advanced digital hyperspectral and multispectral sensors to increase the efficiency of existing surveillance practices (human inspectors and insect traps) and application to detect a known endemic biosecurity pest (grape phylloxera) in Victorian vineyards. We evaluated airborne RGB, multi and hyperspectral imagery at two different vineyards with multiple grapevine varieties, in two separate time periods and under different levels of phylloxera infestation. The methods used to incorporate the sensors to the UAV, the flight operations and the processing workflow of the datasets from each imagery type are described. The ultimate aim of this study is to create an integrated methodology for collecting and processing multi and hyperspectral data with the purpose of remote sensing different variables in different applications such as, in this case, plant biosecurity. The development of a methodology for the collection and analysis of airborne multi and hyperspectral imagery would provide scientists with reliable data collection protocols and faster processing techniques to achieve different remote sensing objectives.