Investigating the inoculum dynamics of Cladosporium on the surface of raspberry fruits and in the air

Raspberry production is under threat from the emerging fungal pathogenic genus Cladosporium. We used amplicon-sequencing, coupled with qPCR, to investigate how fruit age, fruit location within a polytunnel, polytunnel location and sampling date affected the fruit epiphytic microbiome. Fruit age was the most important factor impacting the fungal microbiome, followed by sampling date and polytunnel location. In contrast, polytunnel location and fruit age were important factors impacting the bacterial microbiome composition, followed by the sampling date. The within-tunnel location had a small significant effect on the fungal microbiome and no effect on the bacterial microbiome. As fruit ripened, fungal diversity increased and the bacterial diversity decreased. Cladosporium was the most abundant fungus of the fruit epiphytic microbiome, accounting for nearly 44% of all fungal sequences. Rotorod air samplers were used to study how the concentration of airborne Cladosporium inoculum (quantified by qPCR) varied between location (inside and outside the polytunnel) and time (daytime vs. nighttime). Quantified Cladosporium DNA was significantly higher during the day than the night and inside the polytunnel than the outside. This study demonstrated the dynamic nature of epiphytic raspberry fruit microbiomes and airborne Cladosporium inoculum within polytunnels, which will impact disease risks on raspberry fruit.

The Dissection of Nitrogen Response Traits Using Drone Phenotyping and Dynamic Phenotypic Analysis to Explore N Responsiveness and Associated Genetic Loci in Wheat

Inefficient nitrogen (N) utilization in agricultural production has led to many negative impacts such as excessive use of N fertilizers, redundant plant growth, greenhouse gases, long-lasting toxicity in ecosystem, and even effect on human health, indicating the importance to optimize N applications in cropping systems. Here, we present a multiseasonal study that focused on measuring phenotypic changes in wheat plants when they were responding to different N treatments under field conditions. Powered by drone-based aerial phenotyping and the AirMeasurer platform, we first quantified 6 N response-related traits as targets using plot-based morphological, spectral, and textural signals collected from 54 winter wheat varieties. Then, we developed dynamic phenotypic analysis using curve fitting to establish profile curves of the traits during the season, which enabled us to compute static phenotypes at key growth stages and dynamic phenotypes (i.e., phenotypic changes) during N response. After that, we combine 12 yield production and N-utilization indices manually measured to produce N efficiency comprehensive scores (NECS), based on which we classified the varieties into 4 N responsiveness (i.e., N-dependent yield increase) groups. The NECS ranking facilitated us to establish a tailored machine learning model for N responsiveness-related varietal classification just using N-response phenotypes with high accuracies. Finally, we employed the Wheat55K SNP Array to map single-nucleotide polymorphisms using N response-related static and dynamic phenotypes, helping us explore genetic components underlying N responsiveness in wheat. In summary, we believe that our work demonstrates valuable advances in N response-related plant research, which could have major implications for improving N sustainability in wheat breeding and production.

CropQuant-Air: an AI-powered system to enable phenotypic analysis of yield- and performance-related traits using wheat canopy imagery collected by low-cost drones

As one of the most consumed stable foods around the world, wheat plays a crucial role in ensuring global food security. The ability to quantify key yield components under complex field conditions can help breeders and researchers assess wheat's yield performance effectively. Nevertheless, it is still challenging to conduct large-scale phenotyping to analyse canopy-level wheat spikes and relevant performance traits, in the field and in an automated manner. Here, we present CropQuant-Air, an AI-powered software system that combines state-of-the-art deep learning (DL) models and image processing algorithms to enable the detection of wheat spikes and phenotypic analysis using wheat canopy images acquired by low-cost drones. The system includes the YOLACT-Plot model for plot segmentation, an optimised YOLOv7 model for quantifying the spike number per m² (SNpM²) trait, and performance-related trait analysis using spectral and texture features at the canopy level. Besides using our labelled dataset for model training, we also employed the Global Wheat Head Detection dataset to incorporate varietal features into the DL models, facilitating us to perform reliable yield-based analysis from hundreds of varieties selected from main wheat production regions in China. Finally, we employed the SNpM² and performance traits to develop a yield classification model using the Extreme Gradient Boosting (XGBoost) ensemble and obtained significant positive correlations between the computational analysis results and manual scoring, indicating the reliability of CropQuant-Air. To ensure that our work could reach wider researchers, we created a graphical user interface for CropQuant-Air, so that non-expert users could readily use our work. We believe that our work represents valuable advances in yield-based field phenotyping and phenotypic analysis, providing useful and reliable toolkits to enable breeders, researchers, growers, and farmers to assess crop-yield performance in a cost-effective approach.

Location and Creation of Nest Sites for Ground-Nesting Bees in Apple Orchards

Wild ground-nesting bees are key pollinators of apple (Malus domestica). We explored, (1) where they choose to nest, (2) what influences site selection and (3) species richness in orchards. Twenty-three orchards were studied over three years; twelve were treated with additional herbicide to increase bare ground with the remainder as untreated controls. Vegetation cover, soil type, soil compaction, nest number and location, and species were recorded. Fourteen species of ground-nesting solitary/eusocial bee were identified. Most nests were in areas free of vegetation and areas treated with additional herbicide were utilised by ground nesting bees within three years of application. Nests were also evenly distributed along the vegetation-free strips underneath the apple trees. This area was an important ground-nesting bee habitat with mean numbers of nests at peak nest activity of 873 per ha (range 44-5705), and 1153 per ha (range 0-4082) in 2018 and 2019, respectively. Increasing and maintaining areas of bare ground in apple orchards during peak nesting events could improve nesting opportunities for some species of ground-nesting bee and, combined with flowers strips, be part of a more sustainable pollinator management approach. The area under the tree row is an important contributor to the ground-nesting bee habitat and should be kept bare during peak nesting.

Quantitative trait loci associated with apple endophytes during pathogen infection

The plant phyllosphere is colonized by microbial communities that can influence the fitness and growth of their host, including the host's resilience to plant pathogens.There are multiple factors involved in shaping the assemblages of bacterial and fungal endophytes within the phyllosphere, including host genetics and environment. In this work, the role of host genetics in plant-microbiome assembly was studied in a full-sibling family of apple (Malus x domestica) trees infected with the fungal pathogen Neonectria ditissima. A Quantitative Trait Loci (QTL) analysis showed that there are multiple loci which influence the abundance of individual endophytic taxa, with the majority of QTL having a moderate to large effect (20-40%) on endophyte abundance. QTL regions on LG 1, 3, 4, 5, 10, 12, 13, 14 and 15 were shown to affect multiple taxa. Only a small proportion of the variation in overall taxonomic composition was affected by host genotype, with significant QTL hits for principal components explaining <8% and <7.4% of the total variance in bacterial and fungal composition, respectively. Four of the identified QTL colocalised with previously identified regions associated with tolerance to Neonectria ditissima. These results suggest that there is a genetic basis shaping apple endophyte composition and that microbe-host associations in apple could be tailored through breeding.

Influence of plant genotype and soil on the cotton rhizosphere microbiome

Rhizosphere microbial communities are recognized as crucial products of intimate interactions between plant and soil, playing important roles in plant growth and health. Enhancing the understanding of this process is a promising way to promote the next green revolution by applying the multifunctional benefits coming with rhizosphere microbiomes. In this study, we propagated eight cotton genotypes (four upland cotton cultivars and four sea-land cotton cultivars) with varying levels of resistance to Verticillium dahliae in three distinct soil types. Amplicon sequencing was applied to profile both bacterial and fungal communities in the rhizosphere of cotton. The results revealed that soil origin was the primary factor causing divergence in rhizosphere microbial community, with plant genotype playing a secondary role. The Shannon and Simpson indices revealed no significant differences in the rhizosphere microbial communities of Gossypium barbadense and G. hirsutum. Soil origin accounted for 34.0 and 59.05% of the total variability in the PCA of the rhizosphere bacterial and fungal communities, respectively, while plant genotypes within species only accounted for 1.1 to 6.6% of the total variability among microbial population. Similar results were observed in the Bray-Curtis indices. Interestingly, the relative abundance of Acidobacteria phylum in G. barbadense was greater in comparison with that of G. hirsutum. These findings suggested that soil origin and cotton genotype modulated microbiome assembly with soil predominantly shaping rhizosphere microbiome assembly, while host genotype slightly tuned this recruitment process by changing the abundance of specific microbial consortia.

An effective 'push-pull' control strategy for European tarnished plant bug, Lygus rugulipennis (Heteroptera: Miridae), in strawberry using synthetic semiochemicals

BACKGROUND

European tarnished plant bug, Lygus rugulipennis (Heteroptera: Miridae), is a polyphagous pest damaging a range of arable and horticultural crops. Management is reliant upon chemical insecticides for control. These studies developed a synthetic semiochemical push-pull control strategy to reduce numbers of L. rugulipennis and subsequent fruit damage in UK strawberry crops. Using a series of small field experiments and testing in commercial strawberry crops we explored the efficacy of hexyl butyrate (HB) as the push element and female sex pheromone combined with phenylacetaldehyde as the pull element.

RESULTS

HB dispensers placed 1.0, 3.5, 5.0 and 7.0 m from all-green Unitraps baited with L. rugulipennis female sex pheromone significantly reduced male catches by 99%, 54%, 44% and 20% compared with untreated control, respectively. Subsequently, in commercial crops, HB dispensers at 2-m intervals along the crop row (the push) combined with a perimeter pull reduced numbers of adult and nymph L. rugulipennis by up to 80% in organic strawberry crops compared with the untreated control. Finally, the push-pull system halved fruit damage (8%) compared with untreated areas (16%) in conventional crops. In organic strawberry crops, 90% of untreated strawberries had some mirid damage compared with only 41-51% in push-pull-treated areas.

CONCLUSION

To our knowledge, this is the first demonstration of a push-pull approach using synthetic semiochemicals giving a significant reduction in crop damage by mirids and paves the way for non-pesticide control of a range of mirid species on multiple crops. © 2021 Society of Chemical Industry.

Composition of Rhizosphere Microbial Communities Associated With Healthy and Verticillium Wilt Diseased Cotton Plants

Rhizosphere microbial communities are known to be related to plant health; using such an association for crop management requires a better understanding of this relationship. We investigated rhizosphere microbiomes associated with Verticillium wilt symptoms in two cotton cultivars. Microbial communities were profiled by amplicon sequencing, with the total bacterial and fungal DNA quantified by quantitative polymerase chain reaction based on the respective 16S and internal transcribed spacer primers. Although the level of V. dahliae inoculum was higher in the rhizosphere of diseased plants than in the healthy plants, such a difference explained only a small proportion of variation in wilt severities. Compared to healthy plants, the diseased plants had much higher total fungal/bacterial biomass ratio, as represented by quantified total fungal or bacterial DNA. The variability in the fungal/bacterial biomass ratio was much smaller than variability in either fungal or bacterial total biomass among samples within diseased or healthy plants. Diseased plants generally had lower bacterial alpha diversity in their rhizosphere, but such differences in the fungal alpha diversity depended on cultivars. There were large differences in both fungal and bacterial communities between diseased and healthy plants. Many rhizosphere microbial groups differed in their abundance between healthy and diseased plants. There was a decrease in arbuscular mycorrhizal fungi and an increase in several plant pathogen and saprophyte guilds in diseased plants. These findings suggested that V. dahliae infection of roots led to considerable changes in rhizosphere microbial communities, with large increases in saprophytic fungi and reduction in bacterial community.

Defining strawberry shape uniformity using 3D imaging and genetic mapping

Strawberry shape uniformity is a complex trait, influenced by multiple genetic and environmental components. To complicate matters further, the phenotypic assessment of strawberry uniformity is confounded by the difficulty of quantifying geometric parameters 'by eye' and variation between assessors. An in-depth genetic analysis of strawberry uniformity has not been undertaken to date, due to the lack of accurate and objective data. Nonetheless, uniformity remains one of the most important fruit quality selection criteria for the development of a new variety. In this study, a 3D-imaging approach was developed to characterise berry shape uniformity. We show that circularity of the maximum circumference had the closest predictive relationship with the manual uniformity score. Combining five or six automated metrics provided the best predictive model, indicating that human assessment of uniformity is highly complex. Furthermore, visual assessment of strawberry fruit quality in a multi-parental QTL mapping population has allowed the identification of genetic components controlling uniformity. A "regular shape" QTL was identified and found to be associated with three uniformity metrics. The QTL was present across a wide array of germplasm, indicating a potential candidate for marker-assisted breeding, while the potential to implement genomic selection is explored. A greater understanding of berry uniformity has been achieved through the study of the relative impact of automated metrics on human perceived uniformity. Furthermore, the comprehensive definition of strawberry shape uniformity using 3D imaging tools has allowed precision phenotyping, which has improved the accuracy of trait quantification and unlocked the ability to accurately select for uniform berries.

Cultivar-Dependent Variation of the Cotton Rhizosphere and Endosphere Microbiome Under Field Conditions

Verticillium wilt caused by Verticillium dahliae is a common soil-borne disease worldwide, affecting many economically important crop species. Soil microbes can influence plant disease development. We investigated rhizosphere and endosphere microbiomes in relation to cotton cultivars with differential susceptibility to Verticillium wilt. Soil samples from nine cotton cultivars were assessed for the density of V. dahliae microsclerotia; plants were assessed for disease development. We used amplicon sequencing to profile both bacterial and fungal communities. Unlike wilt severity, wilt inoculum density did not differ significantly among resistant and susceptible cultivars. Overall, there were no significant association of alpha diversity indices with wilt susceptibility. In contrast, there were clear differences in the overall rhizosphere and endosphere microbial communities, particularly bacteria, between resistant and susceptible cultivars. Many rhizosphere and endosphere microbial groups differed in their relative abundance between resistant and susceptible cultivars. These operational taxonomic units included several well-known taxonomy groups containing beneficial microbes, such as Bacillales, Pseudomonadales, Rhizobiales, and Trichoderma, which were higher in their relative abundance in resistant cultivars. Greenhouse studies with sterilized soil supported that beneficial microbes in the rhizosphere contribute to reduced wilt development. These findings suggested that specific rhizosphere and endosphere microbes may contribute to cotton resistance to V. dahliae.

Spatial structuring of soil microbial communities in commercial apple orchards

Characterising spatial microbial community structure is important to understand and explain the consequences of continuous plantation of one crop species on the performance of subsequent crops, especially where this leads to reduced growth vigour and crop yield. We investigated the spatial structure, specifically distance-decay of similarity, of soil bacterial and fungal communities in two long-established orchards with contrasting agronomic characteristics. A spatially explicit sampling strategy was used to collect soil from under recently grubbed rows of apple trees and under the grassed aisles. Amplicon-based metabarcoding technology was used to characterise the soil microbial communities. The results suggested that (1) most of the differences in soil microbial community structure were due to large-scale differences (i.e. between orchards), (2) within-orchard, small-scale (1-5 m) spatial variability was also present, but spatial relationships in microbial community structure differed between orchards and were not predictable, and (3) vegetation type (i.e. trees or grass and their associated management) can significantly alter the structure of soil microbial communities, affecting a large proportion of microbial groups. The discontinuous nature of soil microbial community structure in the tree stations and neighbouring grass aisles within an orchard illustrate the importance of vegetation type and allied weed and nutrient management on soil microbial community structure.

Alimentary microbes of winter-form Drosophila suzukii

Drosophila suzukii (Matsumura) (Diptera: Drosophilidae) is a damaging pest of fruit. Reproductively diapausing adults overwinter in woodlands and remain active on warmer winter days. It is unknown if this adult phase of the lifecycle feeds during the winter period, and what the food source may be. This study characterized the flora in the digestive tract of D. suzukii using a metagenomics approach. Live D. suzukii were trapped in four woodlands in the south of England and their guts dissected for DNA extraction and amplicon-based metagenomics sequencing (internal transcribed spacer and 16S rRNA). Analysis at genus and family taxonomic levels showed high levels of diversity with no differences in digestive tract bacterial or fungal biota between woodland sites of winter-form D. suzukii. Female D. suzukii at one site appeared to have higher bacterial diversity in the alimentary canal than males, but there was a site, sex interaction. Many of the biota were associated with cold, wet climatic conditions and decomposition. This study provides the first evidence that winter-form D. suzukii may be opportunistic feeders during the winter period and are probably exploiting food sources associated with moisture on decomposing vegetation during this time. A core gut microbiome has been identified for winter-form D. suzukii.

What is the dose-response relationship between exercise training and blood pressure?

Most studies of exercise and blood pressure have used a standard exercise programme with a single level of physical activity. To determine the nature of the dose-response relationship however it is necessary to examine several levels of activity, preferably in the same subjects. We have recently performed several randomised crossover studies comparing different levels of regular exercise. The intensity and duration of exercise bouts were constant throughout the studies, but their frequency was varied. Standard bouts consisted of 30 min of bicycling at 60%-70% of maximum work capacity. The exercise was performed either three-weekly or 7-weekly in randomised order and each level was maintained for one month. In sedentary normal subjects three bouts of exercise/week for a total of 90 min lowered blood pressure by 10/7 mmHg. With seven bouts, i.e. a total of 210 min exercise/week, blood pressure was only slightly lower than 3-week exercise and was 12/7 mmHg below sedentary values. Responses to measures of physical fitness including maximum oxygen consumption and work capacity were linearly related to the amount of exercise performed each week. Similar results were obtained in hypertensives. Another randomised study was performed amongst expeditioners to Antarctica where environmental conditions determined that they were sedentary in winter and active in summer. The addition of either 3-week or 7-week exercise in winter significantly lowered blood pressure. In summer when the background level of activity was higher, blood pressure with no added exercise was similar to exercising levels in winter. There was no further fall in blood pressure with either 3-week or 7-week additional exercise.(ABSTRACT TRUNCATED AT 250 WORDS)

Exercise, cardiovascular disease and blood pressure

The "chronic" effect of exercise on blood pressure has been controversial and the debate has been confused by a large number of studies with inadequate methodology. Recent consistent findings in epidemiological, experimental and longitudinal intervention studies have suggested that a true antihypertensive effect which is independent of confounding effects of sodium intake, weight, etc. is more likely than not. Unlike some other measures of lowering blood pressure such as sodium restriction, alcohol moderation and some drugs, regular exercise is associated with beneficial effects on several risk factors and probably has an independent effect on cardiovascular mortality. The magnitude of the effect in previously sedentary subjects is greater than that of dietary measures which lower blood pressure except for weight reduction in the obese. Long-term effects on blood pressure are supported by evidence of a favourable influence on left ventricular hypertrophy. The mechanisms involved in the antihypertensive effect of exercise are unclear, but sympathetic withdrawal is one factor involved. Present evidence appears sufficient to include regular exercise amongst the useful therapies for hypertension.