Modeling population growth and site specific control of the invasive Lantana camara L. (Verbenaceae) under differing fire regimes

It is at the population level that an invasion either fails or succeeds. Lantana camara L. (Verbenaceae) is a weed of great significance in Queensland Australia and globally but its whole life-history ecology is poorly known. Here we used 3 years of field data across four land use types (farm, hoop pine plantation and two open eucalyptus forests, including one with a triennial fire regime) to parameterise the weed’s vital rates and develop size-structured matrix models. Lantana camara in its re-colonization phase, as observed in the recently cleared hoop pine plantation, was projected to increase more rapidly (annual growth rate, λ = 3.80) than at the other three sites (λ 1.88–2.71). Elasticity analyses indicated that growth contributed more (64.6 %) to λ than fecundity (18.5 %) or survival (15.5 %), while across size groups, the contribution was of the order: juvenile (19–27 %) ≥ seed (17–28 %) ≥ seedling (16–25 %) > small adult (4–26 %) ≥ medium adult (7–20 %) > large adult (0–20 %). From a control perspective it is difficult to determine a single weak point in the life cycle of lantana that might be exploited to reduce growth below a sustaining rate. The triennial fire regime applied did not alter the population elasticity structure nor resulted in local control of the weed. However, simulations showed that, except for the farm population, periodic burning could work within 4–10 years for control of the weed, but fire frequency should increase to at least once every 2 years. For the farm, site-specific control may be achieved by 15 years if the biennial fire frequency is tempered with increased burning intensity.

Spectral and thermal sensing for nitrogen and water status in rainfed and irrigated wheat environments

Variable-rate technologies and site-specific crop nutrient management require real-time spatial information about the potential for response to in-season crop management interventions. Thermal and spectral properties of canopies can provide relevant information for non-destructive measurement of crop water and nitrogen stresses. In previous studies, foliage temperature was successfully estimated from canopy-scale (mixed foliage and soil) temperatures and the multispectral Canopy Chlorophyll Content Index (CCCI) was effective in measuring canopy-scale N status in rainfed wheat (Triticum aestivum L.) systems in Horsham, Victoria, Australia. In the present study, results showed that under irrigated wheat systems in Maricopa, Arizona, USA, the theoretical derivation of foliage temperature unmixing produced relationships similar to those in Horsham. Derivation of the CCCI led to an r2 relationship with chlorophyll a of 0.53 after Zadoks stage 43. This was later than the relationship (r2 = 0.68) developed for Horsham after Zadoks stage 33 but early enough to be used for potential mid-season N fertilizer recommendations. Additionally, ground-based hyperspectral data estimated plant N (g kg)1) in Horsham with an r2 = 0.86 but was confounded by water supply and N interactions. By combining canopy thermal and spectral properties, varying water and N status can potentially be identified eventually permitting targeted N applications to those parts of a field where N can be used most efficiently by the crop.

Distributions of lesser mealworm (Coleoptera: Tenebrionidae) in litter of a compacted earth floor broiler house in subtropical Queensland, Australia

Distributions of lesser mealworm, Alphitobius diaperinus (Panzer) (Coleoptera: Tenebrionidae), in litter of a compacted earth floor broiler house in southeastern Queensland, Australia, were studied over two flocks. Larvae were the predominant stage recorded. Significantly low densities occurred in open locations and under drinker cups where chickens had complete access, whereas high densities were found under feed pans and along house edges where chicken access was restricted. For each flock, lesser mealworm numbers increased at all locations over the first 14 d, especially under feed pans and along house edges, peaking at 26 d and then declining over the final 28 d. A life stage profile per flock was devised that consisted of the following: beetles emerge from the earth floor at the beginning of each flock, and females lay eggs, producing larvae that peak in numbers at 3 wk; after a further 3 to 4 wk, larvae leave litter to pupate in the earth floor, and beetles then emerge by the end of the flock time. Removing old litter from the brooder section at the end of a flock did not greatly reduce mealworm numbers over the subsequent flock, but it seemed to prevent numbers increasing, while an increase in numbers in the grow-out section was recorded after reusing litter. Areas under feed pans and along house edges accounted for 5% of the total house area, but approximately half the estimated total number of lesser mealworms in the broiler house occurred in these locations. The results of this study will be used to determine optimal deployment of site-specific treatments for lesser mealworm control.

Establishment and management of salt-tolerant amenity grasses to reduce urban salinity effect

This project built upon the successful outcomes of a previous project (TU02005) by adding to the database of salt tolerance among warm season turfgrass cultivars, through further hydroponic screening trials. Hydroponic screening trials focussed on new cultivars or cultivars that were not possible to cover in the time available under TU02005, including: 11 new cultivars of Paspalum vaginatum; 13 cultivars of Cynodon dactylon; six cultivars of Stenotaphrum secundatum; one accession of Cynodon transvaalensis; 12 Cynodon dactylon x transvaalensis hybrids; two cultivars of Sporobolus virginicus; five cultivars of Zoysia japonica; one cultivar of Z. macrantha, one common form of Z. tenuifolia and one Z. japonica x tenuifolia hybrid. The relative salinity tolerance of different turfgrasses is quantified in terms of their growth response to increasing levels of salinity, often defined by the salt level that equates to a 50% reduction in shoot yield, or alternatively the threshold salinity. The most salt tolerant species in these trials were Sporobolus virginicus and Paspalum vaginatum, consistent with the findings from TU02005 (Loch, Poulter et al. 2006). Cynodon dactylon showed the largest range in threshold values with some cultivars highly sensitive to salt, while others were tolerant to levels approaching that of the more halophytic grasses. Coupled with the observational and anecdotal evidence of high drought tolerance, this species and other intermediately tolerant species provide options for site specific situations in which soil salinity is coupled with additional challenges such as shade and high traffic conditions. By recognising the fact that a salt tolerant grass is not the complete solution to salinity problems, this project has been able to further investigate sustainable long-term establishment and management practices that maximise the ability of the selected grass to survive and grow under a particular set of salinity and usage parameters. Salt-tolerant turf grasses with potential for special use situations were trialled under field conditions at three sites within the Gold Coast City Council, while three sites, established under TU02005 within the Redland City Council boundaries were monitored for continued grass survival. Several randomised block experiments within Gold Coast City were established to compare the health and longevity of seashore paspalum (Paspalum vaginatum), Manila grass (Zoysia matrella), as well as the more tolerant cultivars of other species like buffalo grass (Stenotaphrum secundatum) and green couch (Cynodon dactylon). Whilst scientific results were difficult to achieve in the field situation, where conditions cannot be controlled, these trials provided valuable observational evidence of the likely survival of these species. Alternatives to laying full sod such as sprigging were investigated, and were found to be more appropriate for areas of low traffic as the establishment time is greater. Trials under controlled and protected conditions successfully achieved a full cover of Paspalum vaginatum from sprigs in a 10 week time frame. Salt affected sites are often associated with poor soil structure. Part of the research investigated techniques for the alleviation of soil compaction frequently found on saline sites. Various methods of soil de-compaction were investigated on highly compacted heavy clay soil in Redlands City. It was found that the heavy duplex soil of marine clay sediments required the most aggressive of treatments in order to achieve limited short-term effects. Interestingly, a well constructed sports field showed a far greater and longer term response to de-compaction operations, highlighting the importance of appropriate construction in the successful establishment and management of turfgrasses on salt affected sites. Fertiliser trials in this project determined plant demand for nitrogen (N) to species level. This work produced data that can be used as a guide when fertilising, in order to produce optimal growth and quality in the major turf grass species used in public parkland. An experiment commenced during TU02005 and monitored further in this project, investigated six representative warm-season turfgrasses to determine the optimum maintenance requirements for fertiliser N in south-east Queensland. In doing so, we recognised that optimum level is also related to use and intensity of use, with high profile well-used parks requiring higher maintenance N than low profile parks where maintaining botanical composition at a lower level of turf quality might be acceptable. Kikuyu (Pennisetum clandestinum) seemed to require the greatest N input (300-400 kg N/ha/year), followed by the green couch (Cynodon dactylon) cultivars ‘Wintergreen’ and ‘FLoraTeX’ requiring approximately 300 kg N/ha/year for optimal condition and growth. ‘Sir Walter’ (Stenotaphrum secundatum) and ‘Sea Isle 1’ (Paspalum vaginatum) had a moderate requirement of approximately 200 kg/ha/year. ‘Aussiblue’ (Digitaria didactyla)maintained optimal growth and quality at 100-200 kg N/ha/year. A set of guidelines has been prepared to provide various options from the construction and establishment of new grounds, through to the remediation of existing parklands by supporting the growth of endemic grasses. They describe a best management process through which salt affected sites should be assessed, remediated and managed. These guidelines, or Best Management Practices, will be readily available to councils. Previously, some high salinity sites have been turfed several times over a number of years (and Council budgets) for a 100% failure record. By eliminating this budgetary waste through targeted workable solutions, local authorities will be more amenable to investing appropriate amounts into these areas. In some cases, this will lead to cost savings as well as resulting in better quality turf. In all cases, however, improved turf quality will be of benefit to ratepayers, directly through increased local use of open space in parks and sportsfields and indirectly by attracting tourists and other visitors to the region bringing associated economic benefits. At the same time, environmental degradation and erosion of soil in bare areas will be greatly reduced.

Allocasuarina tree hosts determine the spatial distribution of hypogeous fungal sporocarps in three tropical Australian sclerophyll forests

Across three tropical Australian sclerophyll forest types, site-specific environmental variables could explain the distribution of both quantity (abundance and biomass) and richness (genus and species) of hypogeous fungi sporocarps. Quantity was significantly higher in the Allocasuarina forest sites that had high soil nitrogen but low phosphorous. Three genera of hypogeous fungi were found exclusively in Allocasuarina forest sites including Gummiglobus, Labyrinthomyces and Octaviania, as were some species of Castoreum, Chondrogaster, Endogone, Hysterangium and Russula. However, the forest types did not all group according to site-scale variables and subsequently the taxonomic assemblages were not significantly different between the three forest types. At site scale, significant negative relationships were found between phosphorous concentration and the quantity of hypogeous fungi sporocarps. Using a multivariate information theoretic approach, there were other more plausible models to explain the patterns of sporocarp richness. Both the mean number of fungal genera and species increased with the number of Allocasuarina stems, at the same time decreasing with the number of Eucalyptus stems. The optimal conditions for promoting hypogeous fungi sporocarp quantity and sporocarp richness appear to be related to the presence and abundance of Allocasuarina (Casuarinaceae) host trees. Allocasuarina tree species may have a higher host receptivity for ectomycorrhizal hypogeous fungi species that provide an important food resource for Australian mycophagous animals.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

Development and testing of allometric equations for estimating above-ground biomass of mixed-species environmental plantings

To quantify the impact that planting indigenous trees and shrubs in mixed communities (environmental plantings) have on net sequestration of carbon and other environmental or commercial benefits, precise and non-biased estimates of biomass are required. Because these plantings consist of several species, estimation of their biomass through allometric relationships is a challenging task. We explored methods to accurately estimate biomass through harvesting 3139 trees and shrubs from 22 plantings, and collating similar datasets from earlier studies, in non-arid (>300mm rainfallyear-1) regions of southern and eastern Australia. Site-and-species specific allometric equations were developed, as were three types of generalised, multi-site, allometric equations based on categories of species and growth-habits: (i) species-specific, (ii) genus and growth-habit, and (iii) universal growth-habit irrespective of genus. Biomass was measured at plot level at eight contrasting sites to test the accuracy of prediction of tonnes dry matter of above-ground biomass per hectare using different classes of allometric equations. A finer-scale analysis tested performance of these at an individual-tree level across a wider range of sites. Although the percentage error in prediction could be high at a given site (up to 45%), it was relatively low (<11%) when generalised allometry-predictions of biomass was used to make regional- or estate-level estimates across a range of sites. Precision, and thus accuracy, increased slightly with the level of specificity of allometry. Inclusion of site-specific factors in generic equations increased efficiency of prediction of above-ground biomass by as much as 8%. Site-and-species-specific equations are the most accurate for site-based predictions. Generic allometric equations developed here, particularly the generic species-specific equations, can be confidently applied to provide regional- or estate-level estimates of above-ground biomass and carbon. © 2013 Elsevier B.V.

Water-use efficiency and productivity trends in Australian irrigated cotton: a review

The aim of this review is to report changes in irrigated cotton water use from research projects and on-farm practice-change programs in Australia, in relation to both plant-based and irrigation engineering disciplines. At least 80% of the Australian cotton-growing area is irrigated using gravity surface-irrigation systems. This review found that, over 23 years, cotton crops utilise 6-7ML/ha of irrigation water, depending on the amount of seasonal rain received. The seasonal evapotranspiration of surface-irrigated crops averaged 729mm over this period. Over the past decade, water-use productivity by Australian cotton growers has improved by 40%. This has been achieved by both yield increases and more efficient water-management systems. The whole-farm irrigation efficiency index improved from 57% to 70%, and the crop water use index is >3kg/mm.ha, high by international standards. Yield increases over the last decade can be attributed to plant-breeding advances, the adoption of genetically modified varieties, and improved crop management. Also, there has been increased use of irrigation scheduling tools and furrow-irrigation system optimisation evaluations. This has reduced in-field deep-drainage losses. The largest loss component of the farm water balance on cotton farms is evaporation from on-farm water storages. Some farmers are changing to alternative systems such as centre pivots and lateral-move machines, and increasing numbers of these alternatives are expected. These systems can achieve considerable labour and water savings, but have significantly higher energy costs associated with water pumping and machine operation. The optimisation of interactions between water, soils, labour, carbon emissions and energy efficiency requires more research and on-farm evaluations. Standardisation of water-use efficiency measures and improved water measurement techniques for surface irrigation are important research outcomes to enable valid irrigation benchmarks to be established and compared. Water-use performance is highly variable between cotton farmers and farming fields and across regions. Therefore, site-specific measurement is important. The range in the presented datasets indicates potential for further improvement in water-use efficiency and productivity on Australian cotton farms.

Population dynamics of Thaumastocoris peregrinus in Eucalyptus plantations of South Africa

Thaumastocoris peregrinus is a sap-sucking insect that infests non-native Eucalyptus plantations in Africa, New Zealand, South America and parts of Southern Europe, in addition to street trees in parts of its native range of Australia. In South Africa, pronounced fluctuations in the population densities have been observed. To characterise spatiotemporal variability in T. peregrinus abundance and the factors that might influence it, we monitored adult population densities at six sites in the main eucalypt growing regions of South Africa. At each site, twenty yellow sticky traps were monitored weekly for 30 months, together with climatic data. We also characterised the influence of temperature on growth and survival experimentally and used this to model how temperature may influence population dynamics. T. peregrinus was present throughout the year at all sites, with annual site-specific peaks in abundance. Peaks occurred during autumn (February-April) for the Pretoria site, summer (November-January) for the Zululand site and spring (August-October) for the Tzaneen, Sabie and Piet Retief monitoring sites. Temperature (both experimental and field-collected), humidity and rainfall were mostly weakly, or not at all, associated with population fluctuations. It is clear that a complex interaction of these and other factors (e.g. host quality) influence population fluctuations in an annual, site specific cycle. The results obtained not only provide insights into the biology of T. peregrinus, but will also be important for future planning of monitoring and control programs using semiochemicals, chemical insecticides or biological control agents. © 2014 Springer-Verlag Berlin Heidelberg.

Population dynamics of Thaumastocoris peregrinus in Eucalyptus plantations of South Africa

Thaumastocoris peregrinus is a sap-sucking insect that infests non-native Eucalyptus plantations in Africa, New Zealand, South America and parts of Southern Europe, in addition to street trees in parts of its native range of Australia. In South Africa, pronounced fluctuations in the population densities have been observed. To characterise spatiotemporal variability in T. peregrinus abundance and the factors that might influence it, we monitored adult population densities at six sites in the main eucalypt growing regions of South Africa. At each site, twenty yellow sticky traps were monitored weekly for 30 months, together with climatic data. We also characterised the influence of temperature on growth and survival experimentally and used this to model how temperature may influence population dynamics. T. peregrinus was present throughout the year at all sites, with annual site-specific peaks in abundance. Peaks occurred during autumn (February–April) for the Pretoria site, summer (November–January) for the Zululand site and spring (August–October) for the Tzaneen, Sabie and Piet Retief monitoring sites. Temperature (both experimental and field-collected), humidity and rainfall were mostly weakly, or not at all, associated with population fluctuations. It is clear that a complex interaction of these and other factors (e.g. host quality) influence population fluctuations in an annual, site specific cycle. The results obtained not only provide insights into the biology of T. peregrinus, but will also be important for future planning of monitoring and control programs using semiochemicals, chemical insecticides or biological control agents.

Strategic tillage in no-till farming systems in Australia’s northern grains-growing regions: II. Implications for agronomy, soil and environment

In semi-arid sub-tropical areas, a number of studies concerning no-till (NT) farming systems have demonstrated advantages in economic, environmental and soil quality aspects over conventional tillage (CT). However, adoption of continuous NT has contributed to the build-up of herbicide resistant weed populations, increased incidence of soil- and stubble-borne diseases, and stratification of nutrients and organic carbon near the soil surface. Some farmers often resort to an occasional strategic tillage (ST) to manage these problems of NT systems. However, farmers who practice strict NT systems are concerned that even one-time tillage may undo positive soil condition benefits of NT farming systems. We reviewed the pros and cons of the use of occasional ST in NT farming systems. Impacts of occasional ST on agronomy, soil and environment are site-specific and depend on many interacting soil, climatic and management conditions. Most studies conducted in North America and Europe suggest that introducing occasional ST in continuous NT farming systems could improve productivity and profitability in the short term; however in the long-term, the impact is negligible or may be negative. The short term impacts immediately following occasional ST on soil and environment include reduced protective cover, soil loss by erosion, increased runoff, loss of C and water, and reduced microbial activity with little or no detrimental impact in the long-term. A potential negative effect immediately following ST would be reduced plant available water which may result in unreliability of crop sowing in variable seasons. The occurrence of rainfall between the ST and sowing or immediately after the sowing is necessary to replenish soil water lost from the seed zone. Timing of ST is likely to be critical and must be balanced with optimising soil water prior to seeding. The impact of occasional ST varies with the tillage implement used; for example, inversion tillage using mouldboard tillage results in greater impacts as compared to chisel or disc. Opportunities for future research on occasional ST with the most commonly used implements such as tine and/or disc in Australia’s northern grains-growing region are presented in the context of agronomy, soil and the environment.

Physiological basis of yield variation in response to row spacing and plant density of mungbean grown in subtropical environments

In this study, we investigated the extent and physiological bases of yield variation due to row spacing and plant density configuration in the mungbean Vigna radiata (L.) Wilczek variety “Crystal” grown in different subtropical environments. Field trials were conducted in six production environments; one rain-fed and one irrigated trial each at Biloela and Emerald, and one rain-fed trial each at Hermitage and Kingaroy sites in Queensland, Australia. In each trial, six combinations of spatial arrangement of plants, achieved through two inter-row spacings of 1 m or 0.9 m (wide row), 0.5 m or 0.3 m (narrow row), with three plant densities, 20, 30 and 40 plants/m2, were compared. The narrow row spacing resulted in 22% higher shoot dry matter and 14% more yield compared to the wide rows. The yield advantage of narrow rows ranged from 10% to 36% in the two irrigated and three rain-fed trials. However, yield loss of up to 10% was also recorded from narrow rows at Emerald where the crop suffered severe drought. Neither the effects of plant density, nor the interaction between plant density and row spacing, however, were significant in any trial. The yield advantage of narrow rows was related to 22% more intercepted radiation. In addition, simulations by the Agricultural Production Systems Simulator model, using site-specific agronomy, soil and weather information, suggested that narrow rows had proportionately greater use of soil water through transpiration, compared to evaporation resulting in higher yield per mm of soil water. The long-term simulation of yield probabilities over 123 years for the two row configurations showed that the mungbean crop planted in narrow rows could produce up to 30% higher grain yield compared to wide rows in 95% of the seasons.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

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.