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.

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.

Viral Interactions and Pathogenesis during Multiple Viral Infections in Agaricus bisporus.

Viral interactions during multiple viral infections were examined in Agaricus bisporus cultures harboring 9 viruses (comprising 18 distinct viral RNAs) by statistically analyzing their relative abundance in fruitbodies. Four clusters of viral RNA were identified that suggested synergism and coreplication. Pairwise correlations revealed negative and positive correlations between clusters, indicating further synergisms and an antagonism involving a group containing a putative hypovirus and four nonhost ORFan RNAs (RNAs with no similarity to known sequences) possibly acting as defective interfering RNAs. The disease phenotype was observed in 10 to 15% of the fruitbodies apparently randomly located among asymptomatic fruitbodies. The degree of symptom expression consistently correlated with the levels of the multipartite virus AbV16. Diseased fruitbodies contained very high levels of AbV16 and AbV6 RNA2; these levels were orders of magnitude higher than those in asymptomatic tissues and were shown statistically to be discretely higher populations of abundance, indicating an exponential shift in the replicative capacity of the virus. High levels of AbV16 replication were specific to the fruitbody and not found in the underlying mycelium. There appeared to be a stochastic element occurring in these viral interactions, as observed in the distribution of diseased symptoms across a culture, differences in variance between experiments, and a number of additional viruses undergoing the step-jump in levels between experiments. Possible mechanisms for these multiple and simultaneous viral interactions in single culture are discussed in relation to known virus-host regulatory mechanisms for viral replication and whether additional factors could be considered to account for the 1,000-fold increase in AbV16 and AbV6 RNA2 levels.IMPORTANCE How viruses interact in a multiple-virus infection was examined by quantifying the levels of 18 viral RNAs in fruiting cultures of the agriculturally cultivated fungus Agaricus bisporus and statistically analyzing and modeling their abundance. Synergistic, antagonistic, and neutral interactions occurred simultaneously in cultures. The viral RNAs were grouped into four clusters, each displaying similar relative abundance, and between clusters, further interactions were found with positive, negative, or no correlations. Mushroom fruitbodies showing disease symptoms were distributed apparently randomly across the culture. These symptoms were associated with the presence of viral RNAs from two different clusters at very high levels, 1,000-fold higher than asymptomatic fruitbodies. The role of viral interaction together with stochastic factors and the regulation of host antiviral defenses in pathogenesis are discussed.

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.

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.

Soil microbiome data of two apple orchards in the UK.

The microbial communities in two apple orchards were characterised using amplicon-based metabarcoding. Samples were taken from tree station locations along a linear transect and from adjacent grass aisles, at both orchards. Comparison was made between the communities occurring at tree station locations and the grass aisles, and between orchards. Further discussion of these datasets is given in https://doi.org/10.1016/j.apsoil.2018.05.015 (Deakin et al., 2018).

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.

Genome sequence of the button mushroom Agaricus bisporus reveals mechanisms governing adaptation to a humic-rich ecological niche.

Agaricus bisporus is the model fungus for the adaptation, persistence, and growth in the humic-rich leaf-litter environment. Aside from its ecological role, A. bisporus has been an important component of the human diet for over 200 y and worldwide cultivation of the "button mushroom" forms a multibillion dollar industry. We present two A. bisporus genomes, their gene repertoires and transcript profiles on compost and during mushroom formation. The genomes encode a full repertoire of polysaccharide-degrading enzymes similar to that of wood-decayers. Comparative transcriptomics of mycelium grown on defined medium, casing-soil, and compost revealed genes encoding enzymes involved in xylan, cellulose, pectin, and protein degradation are more highly expressed in compost. The striking expansion of heme-thiolate peroxidases and ß-etherases is distinctive from Agaricomycotina wood-decayers and suggests a broad attack on decaying lignin and related metabolites found in humic acid-rich environment. Similarly, up-regulation of these genes together with a lignolytic manganese peroxidase, multiple copper radical oxidases, and cytochrome P450s is consistent with challenges posed by complex humic-rich substrates. The gene repertoire and expression of hydrolytic enzymes in A. bisporus is substantially different from the taxonomically related ectomycorrhizal symbiont Laccaria bicolor. A common promoter motif was also identified in genes very highly expressed in humic-rich substrates. These observations reveal genetic and enzymatic mechanisms governing adaptation to the humic-rich ecological niche formed during plant degradation, further defining the critical role such fungi contribute to soil structure and carbon sequestration in terrestrial ecosystems. Genome sequence will expedite mushroom breeding for improved agronomic characteristics.