Search

Sap-sucking insects, including whiteflies, are amongst the most devastating and widely distributed organisms on the planet. They are often highly invasive and endosymbiont communities within these insects help them adapt to new or changing environments. Bemisia tabaci (Gennadius; Hemiptera: Aleyrodidae) whitefly species are vectors of more than 500 known plant-viruses and harbour highly diverse endosymbionts communities. To date, however, whitefly–endosymbiont interactions, community structure and their spatio-temporal changes are still poorly understood. In this study, we investigated the spatio-temporal changes in the composition and diversity of bacterial endosymbionts in the agricultural crop pest whitefly species, Bemisia tabaci sub-Saharan Africa 1-subgroup 1 and 2 (SSA1-SG1 and SSA1-SG2). 16S rRNA amplicon sequencing analysis was carried out to characterise endosymbiont compositionsin field-collected SSA1 (SSA1-SG1 and SSA1-SG2) populations infesting cassava in Uganda in 1997 and 2017. We detected Portiera, Arsenophonus, Wolbachia, Hamiltonella and Hemipteriphilus, with Arsenophonus and Wolbachia infections being predominant. Hemipteriphilus and Hamiltonella frequencies were very low and were detected in seven and two samples, respectively. Bacterial diversity based on three independent parameters including Simpson index, number of haplotypes and Bray–Curtis dissimilarity matrix was significantly higher in 1997 than in 2017. This period also coincided with the advent of super-abundant cassava-whitefly populations on cassava crops in Uganda. We discuss how endosymbionts may influence the biology and behaviour of whiteflies leading to population explosions.

The whitefly Bemisia tabaci Middle East-Asia Minor 1 (MEAM1), previously known as B biotype, is a major agricultural pest with a reputation for developing resistance to insecticides. DNA-based identification revealed that B. tabaci MEAM1 is the dominant species within Australian cotton cropping. Discriminating doses of 10 mg/L for pyriproxyfen and 300 mg/L for both diafenthiuron and bifenthrin were determined from bioassay data collected in 2010–2015. Resistance to these insecticides was tested in whitefly populations collected in 2017 from cotton crops in Queensland and New South Wales. This study reports on the presence of pyriproxyfen resistance in B. tabaci MEAM1 at seven locations in Queensland and New South Wales. One population from Goondiwindi was resistant to bifenthrin, whereas no populations tested had resistance to diafenthiuron. To determine the presence of resistance alleles to organophosphates and pyrethroids, reference populations of susceptible and resistant whiteflies (pyriproxyfen, bifenthrin and neonicotinoid) were tested. The resistance mutation L925I was found in a pyrethroid-resistant population and in some individuals from the pyriproxyfen-resistant population. The mutation F331W that confers organophosphate and carbamate resistance was found in all individuals tested including the susceptible reference population, indicative of a widespread distribution in Australian B. tabaci MEAM1. The cotton industry has revised the insecticide resistance management strategy for B. tabaci, to restrict the usage of pyriproxyfen to a single application within a 30-day window. Our results argue against the use of organophosphate and carbamate insecticides in Australian cotton, because B. tabaci MEAM1 populations show significant resistance levels. Furthermore, both pesticide groups are highly disruptive to a diverse range of natural enemy populations, and as such, widespread use likely contributes to pest outbreaks.

The whitefly Bemisia tabaci Middle East-Asia Minor 1 (MEAM1), previously known as B biotype, is a major agricultural pest with a reputation for developing resistance to insecticides. DNA-based identification revealed that B. tabaci MEAM1 is the dominant species within Australian cotton cropping. Discriminating doses of 10 mg/L for pyriproxyfen and 300 mg/L for both diafenthiuron and bifenthrin were determined from bioassay data collected in 2010–2015. Resistance to these insecticides was tested in whitefly populations collected in 2017 from cotton crops in Queensland and New South Wales. This study reports on the presence of pyriproxyfen resistance in B. tabaci MEAM1 at seven locations in Queensland and New South Wales. One population from Goondiwindi was resistant to bifenthrin, whereas no populations tested had resistance to diafenthiuron. To determine the presence of resistance alleles to organophosphates and pyrethroids, reference populations of susceptible and resistant whiteflies (pyriproxyfen, bifenthrin and neonicotinoid) were tested. The resistance mutation L925I was found in a pyrethroid-resistant population and in some individuals from the pyriproxyfen-resistant population. The mutation F331W that confers organophosphate and carbamate resistance was found in all individuals tested including the susceptible reference population, indicative of a widespread distribution in Australian B. tabaci MEAM1. The cotton industry has revised the insecticide resistance management strategy for B. tabaci, to restrict the usage of pyriproxyfen to a single application within a 30-day window. Our results argue against the use of organophosphate and carbamate insecticides in Australian cotton, because B. tabaci MEAM1 populations show significant resistance levels. Furthermore, both pesticide groups are highly disruptive to a diverse range of natural enemy populations, and as such, widespread use likely contributes to pest outbreaks.

Efficient and reliable diagnostic tools for the routine indexing and certification of clean propagating material are essential for the management of pospiviroid diseases in horticultural crops. This study describes the development of a true multiplexed diagnostic method for the detection and identification of all nine currently recognized pospiviroid species in one assay using Luminex bead-based suspension array technology. In addition, a new data-driven, statistical method is presented for establishing thresholds for positivity for individual assays within multiplexed arrays. When applied to the multiplexed array data generated in this study, the new method was shown to have better control of false positives and false negative results than two other commonly used approaches for setting thresholds. The 11-plex Luminex MagPlex-TAG pospiviroid array described here has a unique hierarchical assay design, incorporating a near-universal assay in addition to nine species-specific assays, and a co-amplified plant internal control assay for quality assurance purposes. All assays of the multiplexed array were shown to be 100% specific, sensitive and reproducible. The multiplexed array described herein is robust, easy to use, displays unambiguous results and has strong potential for use in routine pospiviroid indexing to improve disease management strategies.

Background The paper introduces a multispectral imaging system and data-processing approach for the identification and discrimination of morphologically indistinguishable cryptic species of the destructive crop pest, the whitefly Bemisia tabaci. This investigation and the corresponding system design, was undertaken in two phases under controlled laboratory conditions. The first exploited a prototype benchtop variant of the proposed sensor system to analyse four cryptic species of whitefly reared under similar conditions. The second phase, of the methodology development, employed a commercial high-precision laboratory hyperspectral imager to recover reference data from five cryptic species of whitefly, immobilized through flash freezing, and taken from across four feeding environments. Results The initial results, for the single feeding environment, showed that a correct species classification could be achieved in 85–95% of cases, utilising linear Partial Least Squares approaches. The robustness of the classification approach was then extended both in terms of the automated spatial extraction of the most pertinent insect body parts, to assist with the spectral classification model, as well as the incorporation of a non-linear Support Vector Classifier to maintain the overall classification accuracy at 88–98%, irrespective of the feeding and crop environment. Conclusion This study demonstrates that through an integration of both the spatial data, associated with the multispectral images being used to separate different regions of the insect, and subsequent spectral analysis of those sub-regions, that B. tabaci viral vectors can be differentiated from other cryptic species, that appear morphologically indistinguishable to a human observer, with an accuracy of up to 98%. The implications for the engineering design for an in-field, handheld, sensor system is discussed with r

Background The paper introduces a multispectral imaging system and data-processing approach for the identification and discrimination of morphologically indistinguishable cryptic species of the destructive crop pest, the whitefly Bemisia tabaci. This investigation and the corresponding system design, was undertaken in two phases under controlled laboratory conditions. The first exploited a prototype benchtop variant of the proposed sensor system to analyse four cryptic species of whitefly reared under similar conditions. The second phase, of the methodology development, employed a commercial high-precision laboratory hyperspectral imager to recover reference data from five cryptic species of whitefly, immobilized through flash freezing, and taken from across four feeding environments. Results The initial results, for the single feeding environment, showed that a correct species classification could be achieved in 85–95% of cases, utilising linear Partial Least Squares approaches. The robustness of the classification approach was then extended both in terms of the automated spatial extraction of the most pertinent insect body parts, to assist with the spectral classification model, as well as the incorporation of a non-linear Support Vector Classifier to maintain the overall classification accuracy at 88–98%, irrespective of the feeding and crop environment. Conclusion This study demonstrates that through an integration of both the spatial data, associated with the multispectral images being used to separate different regions of the insect, and subsequent spectral analysis of those sub-regions, that B. tabaci viral vectors can be differentiated from other cryptic species, that appear morphologically indistinguishable to a human observer, with an accuracy of up to 98%. The implications for the engineering design for an in-field, handheld, sensor system is discussed with r