Resolving the identification of weak-flying insects during flight: a coupling between rigorous data processing and biology

1. Bioacoustic methods play an increasingly important role for the detection of insects in a range of surveillance and monitoring programs. 2. Weak-flying insects evade detection because they do not yield sufficient audio information to capture wingbeat and harmonic frequencies. These inaudible insects often pose a significant threat to food security as pests of key agricultural crops worldwide. 3. Automatic detection of such insects is crucial to the future of crop protection by providing critical information to assess the risk to a crop and the need for preventative measures. 4. We describe an experimental setup designed to derive audio recordings from a range of weak-flying aphids and beetles using an LED array. 5. A rigorous data processing pipeline was developed to extract meaningful features, linked to morphological characteristics, from the audio and harmonic series for six aphid and two beetle species. 6. An ensemble of over 50 bioacoustic parameters was used to achieve species discrimination with a success rate of 80%. The inclusion of the dominant and fundamental frequencies improved prediction between beetles and aphids due to large differences in wingbeat frequencies. 7. At the species level, error rates were minimised when harmonic features were supplemented by features indicative of differences in species’ flight energies

Beyond the one-way ANOVA for 'omics data

Background: With ever increasing accessibility to high throughput technologies, more complex treatment structures can be assessed in a variety of 'omics applications. This adds an extra layer of complexity to the analysis and interpretation, in particular when inferential univariate methods are applied en masse. It is well-known that mass univariate testing suffers from multiplicity issues and although this has been well documented for simple comparative tests,few approaches have focussed on more complex explanatory structures. Results: Two frameworks are introduced incorporating corrections for multiplicity whilst maintaining appropriate structure in the explanatory variables. Within this paradigm, a choice has to be made as to whether multiplicity corrections should be applied to the saturated model, putting emphasis on controlling the rate of false positives, or to the predictive model, where emphasis is on model selection. This choice has implications for both the ranking and selection of the response variables identified as differentially expressed. The theoretical difference is demonstrated between the two approaches along with an empirical study of lipid composition in Arabidopsis under differing levels of salt stress. Conclusions: Multiplicity corrections have an inherent weakness when the full explanatory structure is not properly incorporated. Although a unifying `single best' recommendation is not provided, two reasonable alternatives are provided and the applicability of these approaches is discussed for different scenarios where the aims of analysis will differ. The key result is that the point at which multiplicity is incorporated into the analysis will fundamentally change the interpretation of the results, and the choice of approach should therefore be driven by the specific aims of the experiment

Spectral soil analysis for fertilizer recommendations by coupling with QUEFTS for maize in East Africa: A sensitivity analysis

Laboratory analysis of soil properties is prohibitively expensive and difficult to scale across the soils in sub Saharan Africa. This results in a lack of soil-specific fertilizer recommendations, where recommendation can only be provided at a regional scale. This study aims to assess the feasibility of using spectral soil analysis to provide soil-specific fertilizer recommendations. Using a range of spectrometers [NeoSpectra Saucer (NIR), FieldSpec 4 (vis-NIR) with contact probe or mug light interface, FTIR Bruker Tensor 27 (MIR)], 346 archived soil samples (0–20 cm) with known soil chemical properties collected from Ethiopia, Kenya and Tanzania were scanned. Partial least square regression (PLSR) was used to develop prediction models for selected soil properties including pH, soil organic carbon (SOC), total nitrogen, Olsen P, and exchangeable K. These predicted properties, and associated uncertainty, were used to derive fertilizer recommendations for maize using the Quantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) model parameters for sub-Saharan Africa. Most soil properties (pH, SOC, total nitrogen, and exchangeable K) were well predicted (Concordance Correlation Coefficient values between 0.88 and 0.96 and Ratio of Performance to Interquartile values between 1.4 and 5.9) by all the spectrometers but there were performance variations between soil properties and spec- trometers. Use of the predicted soil data for the development of fertilizer recommendations gave promising results when compared to the recommendations obtained with the conventional soil analysis. For example, the least performing NeoSpectra Saucer over/under-estimated up to 8 and 24 kg ha-1N and P, respectively, though there was insignificant variation in estimation of P fertilizer among spectrometers. We conclude that spectral technology can be used to determine major soil properties with satisfactory precision, sufficient for specific fertilizer decision making in East Africa, possibly even with portable equipment in the fiel

Uncovering Trait Associations Resulting in Maximal Seed Yield in Winter and Spring Oilseed Rape

Seed yield is a complex trait for many crop species including oilseed rape (OSR) (Brassica napus), the second most important oilseed crop worldwide. Studies have focused on the contribution of distinct factors in seed yield such as environmental cues, agronomical practices, growth conditions, or specific phenotypic traits at the whole plant level, such as number of pods in a plant. However, how female reproductive traits contribute to whole plant level traits, and hence to seed yield, has been largely ignored. Here, we describe the combined contribution of 33 phenotypic traits within a B. napus diversity set population and their trade-offs at the whole plant and organ level, along with their interaction with plant level traits. Our results revealed that both Winter OSR (WOSR) and Spring OSR (SOSR); the two more economically important OSR groups in terms of oil production; share a common dominant reproductive strategy for seed yield. In this strategy, the main inflorescence is the principal source of seed yield, producing a good number of ovules, a large number of long pods with a concomitantly high number of seeds per pod. Moreover, we observed that WOSR opted for additional reproductive strategies than SOSR, presenting more plasticity to maximise seed yield. Overall, we conclude that OSR adopts a key strategy to ensure maximal seed yield and propose an ideal ideotype highlighting crucial phenotypic traits that could be potential targets for breeding

Feeling the Heat: Investigating the dual assault of Zymoseptoria tritici and Heat Stress on Wheat (Triticum aestivum)

As a result of climate change, field conditions are increasingly challenging for crops. Research has shown how elevated temperatures affect crop performance, yet the impact of temperature on host-pathogen relationships remains unknown. Understanding the effects of combined abiotic and biotic stresses on crop plants and the plant-microbial interaction is crucial in developing strategies to improve crop stress tolerance and manage diseases effectively. Lipids sense, signal, and mitigate temperature elevation effects, and lipid remodelling plays a key role in the plant and fungal response to heat stress. Our study uses a systems approach to examine the Z. tritici wheat model system, combining transcriptomics, lipidomics, and phenotyping to decipher the impact of high-temperature stress on the plant-pathogen interaction. Microscopy in vivo and RNA-Seq analyses confirmed that Z. tritici responds to high-temperature treatments with morphological and transcriptomic changes. Temperature-related configuration of the transcriptome was associated with the accessory chromosomes and expression of ‘accessory’ pan-genome-derived genes. Metabolism-related gene expression predominated, indicated by GO enrichment and analysis of KOG classes, and large-scale lipid remodelling was likely given the proportion of lipid transport and metabolism-related expression changes in response to temperature. Changes in lipid content and composition were then validated by LC-MS analysis. Heat-responsive fungal genes and pathways, including scramblase family genes, are being tested by reverse genetics to ascertain their importance for fungal adaption to elevated temperatures. Elevated temperature schemes were applied to wheat to study the impact of combined stress on the plant-pathogen interaction, based on long-term climate data from Rothamsted Research, using transcriptomic, lipidomic and phenotypic analyses. Comparing non-infected and infected wheat plants under typical and elevated temperatures. Our initial analysis of the transcriptomic data indicates a delay in the development of Z. tritici, followed by its adaptation to the warmer environment. Once the infection was established, the fungus exhibited resilience to the impact of higher external temperatures. Our results indicate that temperature elevations associated with climate change directly impact plant-pathogen interactions. Furthermore, the study demonstrates a need for further detailed understanding to sustain crop resilience

High level accumulation of EPA and DHA in field-grown transgenic Camelina – a multi-territory evaluation of TAG accumulation and heterogeneity

The transgene-directed accumulation of non-native omega-3 long chain polyunsaturated fatty acids in the seed oil of Camelina sativa (Camelina) was evaluated in the field, in distinct geographical and regulatory locations. A construct, DHA2015.1, containing an optimal combination of biosynthetic genes, was selected for experimental field release in the UK, USA and Canada, and the accumulation of eicosapentaenoic acid and docosahexaenoic acid determined. The occurrence of these fatty acids in different triacylglycerol species was monitored and found to follow a broad trend irrespective of the agricultural environment. This is a clear demonstration of the stability and robust nature of the transgenic trait for omega-3 long chain polyunsaturated fatty acids in Camelina. Examination of nonseed tissues for the unintended accumulation of EPA and DHA failed to identify their presence in leaf, stem, flower, anther or capsule shell material, confirming the seed-specific accumulation of these novel fatty acids. Collectively these data confirm the promise of GM plant-based sources of so called omega-3 fish oils as a sustainable replacement for oceanically-derived oils

Accounting for data sparsity when forming spatially coherent zones

Efficient farm management can be aided by the identification of zones in the landscape. These zones can be informed from different measured variables by ensuring a sense of spatial coherence. Forming spatially coherent zones is an established method in the literature, but has been found to perform poorly when data are sparse. In this paper, we describe the different types of data sparsity and investigate how this impacts the performance of established methods. We introduce a set of methodological advances that address these shortcomings to provide a method for forming spatially coherent zones under data sparsity

Overexpression of an endogenous type 2 diacylglycerol acyltransferase in the marine diatom Phaeodactylum tricornutum enhances lipid production and omega-3 long-chain polyunsaturated fatty acid content

Background: Oleaginous microalgae represent a valuable resource for the production of high-value molecules. Considering the importance of omega-3 long-chain polyunsaturated fatty acids (LC-PUFAs) for human health and nutrition the yields of high-value eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) require significant improvement to meet demand; however, the current cost of production remains high. A promising approach is to metabolically engineer strains with enhanced levels of triacylglycerols (TAGs) enriched in EPA and DHA. Results: Recently, we have engineered the marine diatom Phaeodactylum tricornutum to accumulate enhanced levels of DHA in TAG. To further improve the incorporation of omega-3 LC-PUFAs in TAG, we focused our effort on the identification of a type 2 acyl-CoA:diacylglycerol acyltransferase (DGAT) capable of improving lipid production and the incorporation of DHA in TAG. DGAT is a key enzyme in lipid synthesis. Following a diatom based in vivo screen of candidate DGATs, a native P. tricornutum DGAT2B was taken forward for detailed characterisation. Overexpression of the endogenous P. tricornutum DGAT2B was confirmed by qRT-PCR and the transgenic strain grew successfully in comparison to wildtype. PtDGAT2B has broad substrate specificity with preferences for C16 and LC-PUFAs acyl groups. Moreover, the overexpression of an endogenous DGAT2B resulted in higher lipid yields and enhanced levels of DHA in TAG. Furthermore, a combined overexpression of the endogenous DGAT2B and ectopic expression of a Δ5-elongase showed how iterative metabolic engineering can be used to increase DHA and TAG content, irrespective of nitrogen treatment. Conclusion: This study provides further insight into lipid metabolism in P. tricornutum and suggests a metabolic engineering approach for the efficient production of EPA and DHA in microalgae