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Crop rotation phase has a greater impact on soil biology than crop rotation diversity
No full textThe effect of plant diversity on the belowground soil food web remains poorly understood. In this study the soil microbial community structure and biomass, and the abundance of microfauna, mesofauna, and macrofauna were assessed at three levels of crop rotation diversity: A Simple rotation (2 plant species), a Moderate rotation (4 plant species), and a Diverse rotation (10 plant species). Soils subjected to more diverse crop rotations did not differ in their microbial community structure, were lower in soil total C, and exhibited a smaller microbial biomass, but a higher crop yield. The mean abundance of Collembola and mites exhibited a trend of Simple > Moderate > Diverse. These observations may be associated with higher levels of disturbance in soils of more diverse rotations due to more frequent tillage operations to establish a greater diversity of crops. The lack of a significant positive effect of crop rotation diversity on soil biology was observed despite the field experiment being established three to four years prior to these measurements. We did observe effects due to the phase of the crop rotation. Within the Simple rotation, we found a significant effect of crop rotation phase on collembolan and mite abundances, and within the Diverse rotation on earthworm biomass. These observations suggest that the crop rotation phase, and perhaps the identity of the individual plants used in a crop rotation, affect soil biology more than the diversity of the crop rotation per se
Using artificial mixtures to test the impacts of tracer combinations and model selection on the performance of sediment source fingerprinting in a burned area
No full textSediment source fingerprinting can be an effective method for identifying sediment sources in wildfire-impacted areas, but the effects of tracer and model selection on robustness remain poorly understood. In this study, soil samples were collected from three potential sources (burned surface, unburned surface, and channel banks) in a wildfire-affected area, and artificial mixtures with known source proportions were created. Three types of tracers (fallout radionuclides, magnetic susceptibilities, and soil colour parameters) were tested for their sensitivity to wildfire. Ten composite fingerprints, generated through the traditional three-step procedure (TSP) as well as consensus ranking and the conservativeness index (CM) were used to assess the accuracy of two un-mixing models. These comprised one frequentist (FingerPro) and one Bayesian (MixSIAR) model. The results indicated that wildfire had substantial effects on most tracer properties, with the median concentration and variance increased by up to 104% and 374%, respectively. Among the ten composite fingerprints, the CM selection method performed best, with the average and standard deviation of the corresponding MAE being 7% and 1%, respectively. While the TSP method could achieve a near-global optimum in some cases, it was the least stable among the ten tracer sets, generating a standard deviation for the MAE of 9%. Compared to FingerPro, MixSIAR solutions calculated using composite fingerprints excluding TSP returned lower MAE values (reduced by an average of 28%). The standard deviations of MAE for MixSIAR solutions employing tracer sets, except for CM, were lower (decreased by an average of 37%), suggesting that MixSIAR delivered higher accuracy and precision for our case study. These findings offer valuable insights for future fingerprinting research in wildfire impacted areas, which can support soil conservation and catchment restoration efforts in burned regions
Erioglossum rubiginosum, a new alternative host of rubber tree powdery mildew Erysiphe quercicola
No full textErioglossum rubiginosum (synonym as Lepisanthes rubiginosa), is a shrub-like plant belonging to the family Sapindaceae. This species is a common undergrowth plant species in rubber tree plantations, which provide more than 90% of the total natural rubber production. Powdery mildew was found to occur seriously on E. rubiginosum during an investigation on powdery mildew of rubber tree caused by Erysiphe quercicola. In this study, leaves of E. rubiginosum with powdery mildew symptoms were collected and the pathogen was identified using morphological and molecular analyses using the internal transcribed spacer (ITS) and 28 S rDNA regions. The results
indicated that E. quercicola was the causal agent of E. rubiginosum powdery mildew. Based on cross-pathogenicity
analysis, E. quercicola from E. rubiginosum and rubber tree could cause typical symptoms on each other, which confirmed that E. rubiginosum is an alternative host of rubber tree powdery mildew. To our knowledge, this is the first report of E. quercicola causing powdery mildew on E. rubiginosum. Whether E. rubiginosum can be one of the primary sources of the rubber tree powdery mildew epidemics needs future studies
Short-term effects of overwintering on porosity of the compacted topsoil due to harvest traffic in Northeast China
No full textThe multi-hydrothermal processes in agricultural soils during overwintering modify compacted soil structure in cold winter regions. The depth-dependent changes in the topsoil pore-network within field-based compacted zones caused by harvest traffic, before and after winter, remain poorly understood. In this study, we aimed to investigate the short-term effects of overwintering on topsoil porosity of a clay loam soil in the harvest traffic zone in Northeast China using X-ray CT. Undisturbed soil cores were collected in the 0–10 cm layer of the non-traffic and traffic zones before and after winter. After harvest, both total porosity (εtotal) and porosity of > 0.04 mm (εX-ray) significantly decreased by 0.04 and 0.07 cm3 cm−3 due to the machinery traffic, respectively. Following winter, the εtotal of the traffic zone significantly increased by 0.08 cm3 cm−3 and was greater than that of non-traffic zone porosity before winter. The loosening effects of overwintering on compacted soil in the traffic zone diminished with increasing soil depth, and marked alterations limited to the uppermost 3.5 cm. The increase in εX-ray was primarily resulted from the changes in 0.04–1.0 mm pores. Therefore, it is indicated that overwintering can alleviate soil compaction of traffic zone only in the uppermost layer
Linking soil structure and microbial communities to predict CO2 emissions from drained arable peatlands
No full textUnderstanding the interactions between soil structure, microbial communities, and greenhouse gas dynamics is critical for predicting carbon losses from drained peatlands under agricultural use. This study investigates CO₂ emissions across winter wheat, sugar beet, and bare soil treatments on a productive UK peat farm, integrating high-resolution X-ray Computed Tomography (XCT), microbial community profiling, and in situ gas and soil measurements.
Soil structure differed between treatments, with bare soil exhibiting the highest pore connectivity and gas diffusivity. These structural conditions aligned with higher in situ CO₂ concentrations, despite reduced root inputs and microbial diversity. In contrast, cropped soils supported more diverse microbial communities, especially fungi, but exhibited lower gas diffusivity and CO₂ concentrations—likely reflecting restricted oxygen availability and plant–microbe competition.
Relative gas diffusivity (Dp/D₀) was strongly regulated by soil moisture across all treatments, with a consistent inverse relationship (R² > 0.93). A machine learning model (XGBoost) accurately predicted CO₂ concentrations (R² = 0.83) using microbial and physical soil properties, identifying microbial taxa potentially linked to carbon cycling.
These findings demonstrate that subtle differences in pore architecture can shape microbial function and carbon loss, even in the absence of statistically significant structural differences. This highlights the need to integrate microbial ecology and soil physics in greenhouse gas modelling for sustainable management of agricultural peatlands
Metabolite-Based Resistance in Wheat Varieties to Aphid Virus Vectors: Progress and Future Opportunities
Full text linkCereal aphids Sitobion avenae and Rhopalosiphum padi are vectors for the barley yellow dwarf virus (BYDV) which, in addition to direct aphid damage, causes severe yield loss in wheat. Insecticides have commonly been used to control these pests. The advent of insecticide resistance spreading across aphid populations and the push to reduce insecticide use, however, requires new approaches to control aphid numbers. Screening studies have identified wheat varieties with natural product-based aphid resistance, which can act as an alternative to insecticides. Resistance induced by natural products include volatile organic compound-mediated (antixenotic) and development-modifying (antibiotic) processes. Full characterisation of these resistance mechanisms is still required and associated challenges, such as the influence of biotic and abiotic interactions, need to be addressed prior to their implementation into integrated pest management (IPM) or engineered into modern elite wheats. In this review, current literature on natural product-based S. avenae and R.padi resistance in wheat is discussed, outlining current knowledge gaps and challenges and highlighting future work required
Identification of universal grass genes and estimates of their monocot-/commelinid-/grass-specificity
Full text linkThe evolutionary success of grasses is due to characteristics of resilience and fast growth in open habitats that led to their underpinning of agriculture and is attributable to many grass-specific traits. Genes responsible for these traits are likely specific to grasses, highly conserved and present in all grasses (universal genes) as they perform essential functions for fitness. A bioinformatics pipeline was developed to identify such genes using 16 grass full genomes in Ensembl Plants release 56. The first steps used existing gene models to generate groups of grass orthologs to rice and maize genes present in most grass species and refined membership of these groups such as to optimise the Hidden Markov Model (HMM) profile score from the HMMER package. These were then supplemented using new gene models found in grass genomes with the genBlastG tool; this step increased the number of universal groups by >2-fold to give 12,855 highly conserved, universal groups. Specificity for these groups was assessed using closest matching gene models from non-monocot species. Possible cut-off values were tested with sets of known genes expected to be either of common function for all plants, or of commelinid- / grass-specific function. A specificity metric based on HMM score from grass group profiles performed better than % identity as a means of discriminating between these common and specific function test sets. Using an appropriate cut-off for this metric, 5,701 of the groups were identified as monocot- / commelinid- / grass-specific of which 72% appeared to be grass specific. These results comprise the universal_grass_peps database available at DOI doi.org/10.23637/rothamsted.98ywz. This database can be searched by researchers to determine whether their experimentally identified grass genes match universal groups and, for those that do, to obtain systematic estimates of monocot- / commelinid- / grass-specificity
Advances in genome editing in plants within an evolving regulatory landscape, with a focus on its application in wheat breeding
Full text linkPopulation growth, diminishing resources and climate change are some of the many challenges that agriculture must address
to satisfy the needs of the global population whilst ensuring the safety and nutritional value of our food. Wheat (Triticum
aestivum) is tremendously important for human nutrition, providing starch (and, therefore, energy), fibre, protein, vitamins, and micronutrients. It is the second most widely grown crop behind maize (Zea mays), with 808 million tonnes of grain being produced in 2021–2022. In comparison, the production figure for 1961 was 222 million tonnes, and there have been similar increases for maize and rice (Oryza sativa). World population over the same period has increased from just over 3 billion to just over 8 billion, a stark reminder of just how important increased crop production has been in maintaining food security over that period, and for these cereals it has been achieved without additional land use. Plant breeding has played an important part in enabling crop production to keep increasing to meet demand and this will have to continue through the coming decades. Innovative technologies will play a part in that, and here we review how the new technology of genome editing is being applied in crop genetic improvement, with a focus on wheat. We cover oligonucleotide-directed mutagenesis and the use of site-directed nucleases, including meganucleases (MegNs), zinc-finger nucleases (ZFNs), transcription activator-like
effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeats (CRISPR)-associated (Cas) nucleases. We describe established genome editing strategies, mainly involving gene ‘knockouts’, and the new applications of base and prime editing using CRISPR/Cas. We also discuss how genome editing for crop improvement is developing in the context of an evolving regulatory landscape
Microfluidics for the biological analysis of atmospheric ice-nucleating particles: Perspectives and challenges
Full text linkAtmospheric ice-nucleating particles (INPs) make up a vanishingly small proportion of atmospheric aerosol, but are key to triggering the freezing of supercooled liquid water droplets, altering the lifetime and radiative properties of clouds and having a substantial impact on weather and climate. However, INPs are notoriously difficult to model due to a lack of information on their global sources, sinks, concentrations, and activity, necessitating the development of new instrumentation for quantifying and characterising INPs in a rapid and automated manner. Microfluidic technology has been increasingly adopted by ice nucleation research groups in recent years as a means of performing droplet freezing analysis of INPs, enabling the measurement of hundreds or thousands of droplets per experiment at temperatures down to the homogeneous freezing of water. The potential for microfluidics extends far beyond this, with an entire toolbox of bioanalytical separation and detection techniques developed over 30 years for medical applications that could easily be adapted to biological and biogenic INP analysis to revolutionise the field, for example in the identification and quantification of ice-nucleating bacteria and fungi. Combined with miniaturised sampling techniques, we can envisage the development and deployment of microfluidic sample-to-answer platforms for automated, user-friendly sampling and analysis of biological INPs in the field that would enable a greater understanding of their global and seasonal activity. Here, we review the various components that such a platform would incorporate to highlight the feasibility, and the challenges, of such an endeavour, from sampling and droplet freezing assays to separations and bioanalysis
The influence of large-scale climate patterns on sediment loss from agricultural land-exploration using an instrumented field and catchment scale platform
Full text linkAccelerated soil erosion and sediment delivery are threats to water quality. In western Europe, weather patterns are strongly influenced by large scale climate systems such as the North Atlantic Oscillation (NAOi). Recently, however, a new climate index has been developed, called the West Europe Pressure Anomaly (WEPAi), which may be more relevant for weather in northwestern Europe. Recent attempts have tried to link variability in weather patterns as described by hydro-climatic indices and amplifications in the degradation of water quality. However, to our knowledge, no previous work has been undertaken on investigating their effects on suspended sediment concentrations.
A study was conducted in southwest England using long-term meteorological, monthly NAOi and WEPAi, and 15-min discharge and turbidity datasets collected from an instrumented field and catchment scale monitoring platform. Monthly winter precipitation totals, and air temperature were both found to be significantly positively related to NAOi, but not in the summer. Both variables were significant and more strongly related with the WEPAi for both seasons. Flow weighted mean suspended sediment concentrations calculated for both seasons over a 4-year period were compared to monthly NAOi and WEPAi. In winter months, no significant relationships were found at any scale for NAOi. However, significant positive relationships with the WEPAi were present regardless of catchment size. In the summer months there were no significant relationships with either climate indices.
Large-scale climate drivers are important in the sediment responses of agricultural landscapes. An ability to forecast monthly climate scale drivers could enable farmers to better plan for those periods when hydro-sedimentological responses are likely to be elevated. More work is needed across a range of landscape typologies to confirm that the relationships observed hold true more widely