High-throughput phenotyping of plant resistance to aphids by automated video tracking

Assessing the impact of piercing-sucking pests on greenhouse-grown industrial hemp (Cannabis sativa L.)

Cannabis sativa or hemp, defined as <0.3% total tetrahydrocannabinol (THC), is a specialty crop in the United States, of particular interest among growers in the southeastern United States to replace tobacco production. Tetranychus urticae (twospotted spider mite), Aculops cannabicola (hemp russet mite), Polyphagotarsonemus latus (broad mites), and Phorodon cannabis (cannabis aphids) are considered the most significant pests in greenhouse grown hemp. Mite and aphid injury can cause cupping and yellowing of leaves, resulting in leaf drop, and reduced flower and resin production. We sought to understand the effects of feeding by T. urticae and Myzus persicae (green peach aphid), as a proxy for P. cannabis, on the concentration of economically significant cannabinoids through a series of experiments on greenhouse grown plants. First, we compared the variability of chemical concentrations in samples collected from individual plants versus pooled samples from 5 plants, and found that chemical concentrations in single plants were similar to those in pooled plant samples. Next, we compared chemical concentrations prior to arthropod infestation and post infestation. When evaluating the mite feeding damage in 2020, cannabinoids in plants infested with high densities of T. urticae increased more slowly than in uninfested control plants or plants infested with low T. urticae densities. In 2021, the concentration of tetrahydrocannabinol did not differ significantly between treatments. Cannabidiol increased more slowly in plants with low T. urticae densities when compared to uninfested controls but did not differ from the high T. urticae densities 14 days after infestation.

Antifeedant Potential of Geranylacetone and Nerylacetone and Their Epoxy-Derivatives against Myzus persicae (Sulz.)

Geranylacetone and nerylacetone are natural sesquiterpenoids, which play various roles in plant-insect interactions, including the deterrent and repellent effects on herbivores. The structural modifications of natural compounds often change their biological activities. The aim of the study was to evaluate the effect of geranylacetone, nerylacetone and their epoxy-derivatives on the probing and settling behavior of Myzus persicae (Sulz.) (Hemiptera: Aphididae). The no-choice test using the Electrical Penetration Graph (EPG) technique showed that the probes before the first phloem phase were usually shorter than 3 min, which means that they were terminated within the epidermis and/or outer layers of mesophyll. This resulted in a tendency to delay the initiation of the phloem phase in aphids, which reflects a weak preingestive deterrent activity of the studied compounds at the level of non-vascular tissues. Most M. persicae showed bouts of sustained phloem sap ingestion. However, the 24-h free-choice test demonstrated that aphids did not settle on the leaves treated with geranylacetone, nerylacetone, and their epoxy-derivatives. The refusal to settle after the consumption of phloem sap on treated plants indicated that the studied compounds had postingestive deterrent activity. The epoxidation of geranylacetone and nerylacetone did not evoke significant changes in their activity profiles.

Perspectives for integrated insect pest protection in oilseed rape breeding

In the past, breeding for incorporation of insect pest resistance or tolerance into cultivars for use in integrated pest management schemes in oilseed rape/canola (Brassica napus) production has hardly ever been approached. This has been largely due to the broad availability of insecticides and the complexity of dealing with high-throughput phenotyping of insect performance and plant damage parameters. However, recent changes in the political framework in many countries demand future sustainable crop protection which makes breeding approaches for crop protection as a measure for pest insect control attractive again. At the same time, new camera-based tracking technologies, new knowledge-based genomic technologies and new scientific insights into the ecology of insect-Brassica interactions are becoming available. Here we discuss and prioritise promising breeding strategies and direct and indirect breeding targets, and their time-perspective for future realisation in integrated insect pest protection of oilseed rape. In conclusion, researchers and oilseed rape breeders can nowadays benefit from an array of new technologies which in combination will accelerate the development of improved oilseed rape cultivars with multiple insect pest resistances/tolerances in the near future.

A Comprehensive Review of High Throughput Phenotyping and Machine Learning for Plant Stress Phenotyping

During the last decade, there has been rapid adoption of ground and aerial platforms with multiple sensors for phenotyping various biotic and abiotic stresses throughout the developmental stages of the crop plant. High throughput phenotyping (HTP) involves the application of these tools to phenotype the plants and can vary from ground-based imaging to aerial phenotyping to remote sensing. Adoption of these HTP tools has tried to reduce the phenotyping bottleneck in breeding programs and help to increase the pace of genetic gain. More specifically, several root phenotyping tools are discussed to study the plant's hidden half and an area long neglected. However, the use of these HTP technologies produces big data sets that impede the inference from those datasets. Machine learning and deep learning provide an alternative opportunity for the extraction of useful information for making conclusions. These are interdisciplinary approaches for data analysis using probability, statistics, classification, regression, decision theory, data visualization, and neural networks to relate information extracted with the phenotypes obtained. These techniques use feature extraction, identification, classification, and prediction criteria to identify pertinent data for use in plant breeding and pathology activities. This review focuses on the recent findings where machine learning and deep learning approaches have been used for plant stress phenotyping with data being collected using various HTP platforms. We have provided a comprehensive overview of different machine learning and deep learning tools available with their potential advantages and pitfalls. Overall, this review provides an avenue for studying various HTP platforms with particular emphasis on using the machine learning and deep learning tools for drawing legitimate conclusions. Finally, we propose the conceptual challenges being faced and provide insights on future perspectives for managing those issues.

Quantitative phenotyping and evaluation for lettuce leaves of multiple semantic components

BACKGROUND

Classification and phenotype identification of lettuce leaves urgently require fine quantification of their multi-semantic traits. Different components of lettuce leaves undertake specific physiological functions and can be quantitatively described and interpreted using their observable properties. In particular, petiole and veins determine mechanical support and material transport performance of leaves, while other components may be closely related to photosynthesis. Currently, lettuce leaf phenotyping does not accurately differentiate leaf components, and there is no comparative evaluation for positive-back of the same lettuce leaf. In addition, a few traits of leaf components can be measured manually, but it is time-consuming, laborious, and inaccurate. Although several studies have been on image-based phenotyping of leaves, there is still a lack of robust methods to extract and validate multi-semantic traits of large-scale lettuce leaves automatically.

RESULTS

In this study, we developed an automated phenotyping pipeline to recognize the components of detached lettuce leaves and calculate multi-semantic traits for phenotype identification. Six semantic segmentation models were constructed to extract leaf components from visible images of lettuce leaves. And then, the leaf normalization technique was used to rotate and scale different leaf sizes to the "size-free" space for consistent leaf phenotyping. A novel lamina-based approach was also utilized to determine the petiole, first-order vein, and second-order veins. The proposed pipeline contributed 30 geometry-, 20 venation-, and 216 color-based traits to characterize each lettuce leaf. Eleven manually measured traits were evaluated and demonstrated high correlations with computation results. Further, positive-back images of leaves were used to verify the accuracy of the proposed method and evaluate the trait differences.

CONCLUSIONS

The proposed method lays an effective strategy for quantitative analysis of detached lettuce leaves' fine structure and components. Geometry, color, and vein traits of lettuce leaf and its components can be comprehensively utilized for phenotype identification and breeding of lettuce. This study provides valuable perspectives for developing automated high-throughput phenotyping application of lettuce leaves and the improvement of agronomic traits such as effective photosynthetic area and vein configuration.

Terpene synthases in cucumber (Cucumis sativus) and their contribution to herbivore-induced volatile terpenoid emission

Terpenoids play important roles in flavour, pollinator attraction and defence of plants. In cucumber (Cucumis sativus) they are important components of the herbivore-induced plant volatile blend that attracts natural enemies of herbivores. We annotated the cucumber TERPENE SYNTHASE gene (CsTPS) family and characterized their involvement in the response towards herbivores with different feeding guilds using a combined molecular and biochemical approach. Transcripts of multiple CsTPS genes were upregulated in leaves upon herbivory and the products generated by the expressed proteins match the terpenoids recorded in the volatile blend released by herbivore-damaged leaves. Spatial and temporal analysis of the promoter activity of CsTPS genes showed that cell content-feeding spider mites (Tetranychus urticae) and thrips (Frankliniella occidentalis) induced promoter activity of CsTPS9 and CsTPS19 within hours after initiation of infestation, while phloem-feeding aphids (Myzus persicae) induced CsTPS2 promoter activity. Our findings offer detailed insights into the involvement of the TPS gene family in the dynamics and fine-tuning of the emission of herbivore-induced plant volatiles in cucumber, and open a new avenue to understand molecular mechanisms that affect plant-herbivore interactions.

High-Throughput Feeding Bioassay for Lepidoptera Larvae

Finding plant cultivars that are resistant or tolerant against lepidopteran pests, takes time, effort and is costly. We present here a high throughput leaf-disk consumption assay system, to screen plants for resistance or chemicals for their deterrence. A webcam capturing images at regular intervals can follow the feeding activities of 150 larvae placed into individual cages. We developed a computer program running under an open source image analysis program to analyze and measure the surface of each leaf disk over time. We further developed new statistical procedures to analyze the time course of the feeding activities of the larvae and to compare them between treatments. As a test case, we compared how European corn borer larvae respond to a commercial antifeedant containing azadirachtin, and to quinine, which is a bitter alkaloid for many organisms. As expected, increasing doses of azadirachtin reduced and delayed feeding. However, quinine was poorly effective at the range of concentrations tested (10-5 M to 10-2 M). The model cage, the camera holder, the plugins, and the R scripts are freely available, and can be modified according to the users' needs.

Plant Transcription Factors Involved in Drought and Associated Stresses

Transcription factors (TFs) play a significant role in signal transduction networks spanning the perception of a stress signal and the expression of corresponding stress-responsive genes. TFs are multi-functional proteins that may simultaneously control numerous pathways during stresses in plants-this makes them powerful tools for the manipulation of regulatory and stress-responsive pathways. In recent years, the structure-function relationships of numerous plant TFs involved in drought and associated stresses have been defined, which prompted devising practical strategies for engineering plants with enhanced stress tolerance. Vast data have emerged on purposely basic leucine zipper (bZIP), WRKY, homeodomain-leucine zipper (HD-Zip), myeloblastoma (MYB), drought-response elements binding proteins/C-repeat binding factor (DREB/CBF), shine (SHN), and wax production-like (WXPL) TFs that reflect the understanding of their 3D structure and how the structure relates to function. Consequently, this information is useful in the tailored design of variant TFs that enhances our understanding of their functional states, such as oligomerization, post-translational modification patterns, protein-protein interactions, and their abilities to recognize downstream target DNA sequences. Here, we report on the progress of TFs based on their interaction pathway participation in stress-responsive networks, and pinpoint strategies and applications for crops and the impact of these strategies for improving plant stress tolerance.

Ento(o)mics: the intersection of 'omic' approaches to decipher plant defense against sap-sucking insect pests

Plants are constantly challenged by insect pests that can dramatically decrease yields. Insects with piercing-sucking mouthparts, for example, aphids, whiteflies, and leaf hoppers, seemingly cause less physical damage to tissues, however, they feed on the plant's sap by piercing plant tissue and extracting plant fluids, thereby transmitting several plant-pathogenic viruses as well. As a counter-defense, plants activate an array of dynamic defense machineries against insect pests including the rapid reprogramming of the host cell processes. For a holistic understanding of plant-sap-sucking insect interactions, there is a need to call for techniques with the capacity to concomitantly capture these dynamic changes. Recent progress with various 'omic' technologies possess this capacity. In this review, we will provide a concise summary of application of 'omic' technologies and their utilization in plant and sap-sucking insect interaction studies. Finally, we will provide a perspective on the integration of 'omics' data in uncovering novel plant defense mechanisms against sap-sucking insect pests.

β-Thujone and Its Derivatives Modify the Probing Behavior of the Peach Potato Aphid

Thujone is a natural biologically active monoterpene ketone component of essential oils of numerous plants. The aim of the study was to evaluate the effect of β-thujone and β-thujone derivatives bisulfite adduct, lactone, oxime, and lactam application on behavior of Myzus persicae (Sulz.) (Hemiptera: Aphididae) during probing and settling. The choice and no-choice tests (aphid settling and Electrical Penetration Graph (EPG), respectively) revealed that stereochemistry of thujone was important for biological activity (β-thujone caused changes in aphid behavior while α-thujone did not) and that cyclopentane ring modifications and functional groups addition gave derivatives that possessed stronger and more durable deterrent effects. The most effective modification was the incorporation of a lactam moiety into the β-thujone molecule. Application of β-thujone lactam limited aphid settling for at least 24 h, caused restlessness in aphids and a delay or failure in reaching phloem phase by M. persicae. β-Thujone lactam can be considered a deterrent of medium potency with activity expressed at preingestive phase of aphid probing. Other compounds did not restrain aphid stylet penetration in non-phloem tissues but slightly limited sap ingestion (lactone, oxime), and restrained aphid settling for a period of less than 24 h (β-Thujone, bisulphite adduct, lactone).

High-throughput phenotyping for crop improvement in the genomics era

Tremendous progress has been made with continually expanding genomics technologies to unravel and understand crop genomes. However, the impact of genomics data on crop improvement is still far from satisfactory, in large part due to a lack of effective phenotypic data; our capacity to collect useful high quality phenotypic data lags behind the current capacity to generate high-throughput genomics data. Thus, the research bottleneck in plant sciences is shifting from genotyping to phenotyping. This article review the current status of efforts made in the last decade to systematically collect phenotypic data to alleviate this 'phenomics bottlenecks' by recording trait data through sophisticated non-invasive imaging, spectroscopy, image analysis, robotics, high-performance computing facilities and phenomics databases. These modern phenomics platforms and tools aim to record data on traits like plant development, architecture, plant photosynthesis, growth or biomass productivity, on hundreds to thousands of plants in a single day, as a phenomics revolution. It is believed that this revolution will provide plant scientists with the knowledge and tools necessary for unlocking information coded in plant genomes. Efforts have been also made to present the advances made in the last 10 years in phenomics platforms and their use in generating phenotypic data on different traits in several major crops including rice, wheat, barley, and maize. The article also highlights the need for phenomics databases and phenotypic data sharing for crop improvement. The phenomics data generated has been used to identify genes/QTL through QTL mapping, association mapping and genome-wide association studies (GWAS) for genomics-assisted breeding (GAB) for crop improvement.

An Integrated System for the Automated Recording and Analysis of Insect Behavior in T-maze Arrays

Host-plant resistance to insects like thrips and aphids is a complex trait that is difficult to phenotype quickly and reliably. Here, we introduce novel hardware and software to facilitate insect choice assays and automate the acquisition and analysis of movement tracks. The hardware consists of an array of individual T-mazes allowing simultaneous release of up to 90 insect individuals from their individual cage below each T-maze with choice of two leaf disks under a video camera. Insect movement tracks are acquired with computer vision software (EthoVision) and analyzed with EthoAnalysis, a novel software package that allows for automated reporting of highly detailed behavior parameters and statistical analysis. To validate the benefits of the system we contrasted two Arabidopsis accessions that were previously analyzed for differential resistance to western flower thrips. Results of two trials with 40 T-mazes are reported and we show how we arrived at optimized settings for the different filters and statistics. The statistics are reported in terms of frequency, duration, distance and speed of behavior events, both as sum totals and event averages, and both for the total trial period and in time bins of 1 h. Also included are higher level analyses with subcategories like short-medium-long events and slow-medium-fast events. The time bins showed how some behavior elements are more descriptive of differences between the genotypes during the first hours, whereas others are constant or become more relevant at the end of an 8 h recording. The three overarching behavior categories, i.e., choice, movement, and halting, were automatically corrected for the percentage of time thrips were detected and 24 out of 38 statistics of behavior parameters differed by a factor 2-6 between the accessions. The analysis resulted in much larger contrasts in behavior traits than reported previously. Compared to leaf damage assays on whole plants or detached leaves that take a week or more to complete, results were obtained in 8 h, with more detail, fewer individuals and higher significance. The potential value of the new integrated system, named EntoLab, for discovery of genetic traits in plants and insects by high throughput screening of large populations is discussed.

Automated high-throughput individual tracking system for insect behavior: Applications on memory retention in parasitic wasps

BACKGROUND

Insects are important models to study learning and memory formation in both an ecological and neuroscience context due to their small size, behavioral flexibility and ecological diversity. Measuring memory retention is often done through simple time-consuming set-ups, producing only a single parameter for conditioned behavior. We wished to obtain higher sample sizes with fewer individuals to measure olfactory memory retention more efficiently.

NEW METHOD

The high-throughput individual T-maze uses commercially available tracking software, Ethovision XT^®, in combination with a Perspex stack of plates as small as 18 × 18 cm, which accommodates 36 olfactory T-mazes, where each individual wasp could choose between two artificial odors. Various behavioral parameters, relevant to memory retention, were acquired in this set-up; first choice, residence time, giving up time and zone entries. From these parameters a performance index was calculated as a measure of memory retention. Groups of 36 wasps were simultaneously tested within minutes, resulting in efficient acquisition of sufficiently high sample sizes.

RESULTS

This system was tested with two very different parasitic wasp species, the larval parasitoid Cotesia glomerata and the pupal parasitoid Nasonia vitripennis, and has proven to be highly suitable for testing memory retention in both these species.

COMPARISON WITH EXISTING METHODS

Unlike other bioassays, this system allows for both high-throughput and recording of detailed individual behavior.

CONCLUSIONS

The high-throughput individual T-maze provides us with a standardized high-throughput, labor-efficient and cost-effective method to test various kinds of behavior, offering excellent opportunities for comparative studies of various aspects of insect behavior.

SIEVE ELEMENT-LINING CHAPERONE1 Restricts Aphid Feeding on Arabidopsis during Heat Stress

The role of phloem proteins in plant resistance to aphids is still largely elusive. By genome-wide association mapping of aphid behavior on 350 natural Arabidopsis thaliana accessions, we identified the small heat shock-like SIEVE ELEMENT-LINING CHAPERONE1 (SLI1). Detailed behavioral studies on near-isogenic and knockout lines showed that SLI1 impairs phloem feeding. Depending on the haplotype, aphids displayed a different duration of salivation in the phloem. On sli1 mutants, aphids prolonged their feeding sessions and ingested phloem at a higher rate than on wild-type plants. The largest phenotypic effects were observed at 26°C, when SLI1 expression is upregulated. At this moderately high temperature, sli1 mutants suffered from retarded elongation of the inflorescence and impaired silique development. Fluorescent reporter fusions showed that SLI1 is confined to the margins of sieve elements where it lines the parietal layer and colocalizes in spherical bodies around mitochondria. This localization pattern is reminiscent of the clamp-like structures observed in previous ultrastructural studies of the phloem and shows that the parietal phloem layer plays an important role in plant resistance to aphids and heat stress.

Genetic architecture of plant stress resistance: multi-trait genome-wide association mapping

Plants are exposed to combinations of various biotic and abiotic stresses, but stress responses are usually investigated for single stresses only. Here, we investigated the genetic architecture underlying plant responses to 11 single stresses and several of their combinations by phenotyping 350 Arabidopsis thaliana accessions. A set of 214 000 single nucleotide polymorphisms (SNPs) was screened for marker-trait associations in genome-wide association (GWA) analyses using tailored multi-trait mixed models. Stress responses that share phytohormonal signaling pathways also share genetic architecture underlying these responses. After removing the effects of general robustness, for the 30 most significant SNPs, average quantitative trait locus (QTL) effect sizes were larger for dual stresses than for single stresses. Plants appear to deploy broad-spectrum defensive mechanisms influencing multiple traits in response to combined stresses. Association analyses identified QTLs with contrasting and with similar responses to biotic vs abiotic stresses, and below-ground vs above-ground stresses. Our approach allowed for an unprecedented comprehensive genetic analysis of how plants deal with a wide spectrum of stress conditions.

Plant Tolerance: A Unique Approach to Control Hemipteran Pests

Plant tolerance to insect pests has been indicated to be a unique category of resistance, however, very little information is available on the mechanism of tolerance against insect pests. Tolerance is distinctive in terms of the plant's ability to withstand or recover from herbivore injury through growth and compensatory physiological processes. Because plant tolerance involves plant compensatory characteristics, the plant is able to harbor large numbers of herbivores without interfering with the insect pest's physiology or behavior. Some studies have observed that tolerant plants can compensate photosynthetically by avoiding feedback inhibition and impaired electron flow through photosystem II that occurs as a result of insect feeding. Similarly, the up-regulation of peroxidases and other oxidative enzymes during insect feeding, in conjunction with elevated levels of phytohormones can play an important role in providing plant tolerance to insect pests. Hemipteran insects comprise some of the most economically important plant pests (e.g., aphids, whiteflies), due to their ability to achieve high population growth and their potential to transmit plant viruses. In this review, results from studies on plant tolerance to hemipterans are summarized, and potential models to understand tolerance are presented.

AtWRKY22 promotes susceptibility to aphids and modulates salicylic acid and jasmonic acid signalling

Aphids induce many transcriptional perturbations in their host plants, but the signalling cascades responsible and the effects on plant resistance are largely unknown. Through a genome-wide association (GWA) mapping study in Arabidopsis thaliana, we identified WRKY22 as a candidate gene associated with feeding behaviour of the green peach aphid, Myzus persicae The transcription factor WRKY22 is known to be involved in pathogen-triggered immunity, and WRKY22 gene expression has been shown to be induced by aphids. Assessment of aphid population development and feeding behaviour on knockout mutants and overexpression lines showed that WRKY22 increases susceptibility to M. persicae via a mesophyll-located mechanism. mRNA sequencing analysis of aphid-infested wrky22 knockout plants revealed the up-regulation of genes involved in salicylic acid (SA) signalling and down-regulation of genes involved in plant growth and cell-wall loosening. In addition, mechanostimulation of knockout plants by clip cages up-regulated jasmonic acid (JA)-responsive genes, resulting in substantial negative JA-SA crosstalk. Based on this and previous studies, WRKY22 is considered to modulate the interplay between the SA and JA pathways in response to a wide range of biotic and abiotic stimuli. Its induction by aphids and its role in suppressing SA and JA signalling make WRKY22 a potential target for aphids to manipulate host plant defences.

Automated video tracking of thrips behavior to assess host-plant resistance in multiple parallel two-choice setups

BACKGROUND

Piercing-sucking insects cause severe damage in crops. Breeding for host-plant resistance can significantly reduce the yield losses caused by these insects, but host-plant resistance is a complex trait that is difficult to phenotype quickly and reliably. Current phenotyping methods mainly focus on labor-intensive and time-consuming end-point measurements of plant fitness. Characterizing insect behavior as a proxy for host-plant resistance could be a promising time-saving alternative to end-point measurements.

RESULTS

We present a phenotyping platform that allows screening for host-plant resistance against Western flower thrips (WFT, Frankliniella occidentalis (Pergande)) in a parallel two-choice setup using automated video tracking of thrips behavior. The platform was used to establish host-plant preference of WFT with a large plant population of 345 wild Arabidopsis accessions and the method was optimized with two extreme accessions from this population that differed in resistance towards WFT. To this end, the behavior of 88 WFT individuals was simultaneously tracked in 88 parallel two-choice arenas during 8 h. Host-plant preference of WFT was established both by the time thrips spent on either accession and various behavioral parameters related to movement (searching) and non-movement (feeding) events.

CONCLUSION

In comparison to 6-day end-point choice assays with whole plants or detached leaves, the automated video-tracking choice assay developed here delivered similar results, but with higher time- and resource efficiency. This method can therefore be a reliable and effective high throughput phenotyping tool to assess host-plant resistance to thrips in large plant populations.