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Inducible volatile chemical signalling drives antifungal activity of Trichoderma hamatum GD12 during confrontation with the pathogen Sclerotinia sclerotiorum
No full textBACKGROUND: The use of beneficial soil fungi or their natural products offers a more sustainable alternative to synthetic fungicides for pathogen management in crops. Volatile organic compounds (VOCs) produced by such fungi act as semiochemicals that inhibit pathogens, with VOC production influenced by physical interactions between competing fungi. This study explores the interaction between the beneficial soil fungus Trichoderma hamatum GD12 strain (GD12), previously shown to antagonize crop pathogens such as Sclerotinia sclerotiorum, to test the hypothesis that its antagonistic effect is mediated by volatile chemical signalling RESULTS: In dual-culture confrontation assays, co-inoculation of GD12 and S. sclerotiorum led to fungistatic interactions after 7 days. VOCs collected from individual and co-cultures were analysed by gas chromatography – flame ionization detector (GC-FID) analysis and coupled GC-mass spectrometry (GC-MS), revealing significant differences in VOC production between treatments, with VOC production notably upregulated in the GD12 + S. sclerotiorum co-culture. Peak production of 6-pentyl-2H-pyran-2-one occurred 17 days post-inoculation. Synthetic VOC assays revealed several compounds inhibitory to S. sclerotiorum, including 1-octen-3-one, which also arrested the growth of key fungal pathogens (Botrytis cinerea, Pyrenopeziza brassicae, and Gaeumannomyces tritici). Structural insights into 1-octen-3-one’s antifungal activity against S. sclerotiorum are also presented. CONCLUSIONS: These findings support the hypothesis that the antagonistic properties of T. hamatum GD12 against crop fungal pathogens can, in part, be attributed to VOC production. Further research is needed to assess the potential of these semiochemicals as tools for pathogen management in agriculture
Variable spatio-temporal source contributions during storm hydrographs revealed by composite fingerprinting
No full textStudy Region: The Kasilian watershed with an area of 67.22 km2 is located in the eastern part of Mazandaran province.
Study Focus: This study investigated the spatio-temporal variations in sediment sources during rainfall events. For this purpose, source samples were collected from various land uses, including rangeland, natural forest, hand-planted forest, and agriculture, as well as from the river bed.
Suspended sediment sampling was conducted at 60-minute intervals during three rainfall events at two monitoring stations: MS1 (mid-watershed) and MS2 (watershed outlet). The concentration of 59 geochemical elements in source and sediment samples was measured, and composite fingerprints
were selected using statistical tests in the FingerPro package in R software. New Hydrological Insights for the Region: The study found that the contributions of rangelands,
natural forests, hand-planted forests, and the river bed at MS1 were 46 %, 24 %, 19 %, and 11 %, respectively, while at MS2, the contributions were 72 %, 7 %, 4 %, 14 %, and 3 % for agricultural lands. Additionally, intra-event variations showed that at MS1, rangelands contributed the most
at the hydrograph peak, whereas during the rising and falling limbs, both rangelands and natural forests were dominant. At MS2, rangelands had the highest contribution throughout all hydrograph phases. These findings provide valuable information for managers in developing management programs
Soil sample size and physical properties matter in experimental studies of the moisture and temperature response of soil respiration
No full textThe influence of soil water and temperature on soil respiration is often studied using incubation experiments due to the challenges associated with field measurements. While incubations preserve most chemical and biological properties of the soil, they alter the physical environment. A critical issue is whether these alterations make incubation results unrepresentative of those under field conditions. To address this gap, we developed a multiscale model to explicitly resolve key processes controlling anaerobic CO₂ production and microbial respiration of dissolved and gaseous oxygen (O₂) in the pore space, which include heterogeneous microbial distribution and O₂ dissolution and diffusion. These processes are integrated into a macroscopic model to simulate CO₂ emissions in soil profiles. We applied the model to published incubation and field experiments to evaluate its accuracy and ability to predict the moisture and temperature sensitivity of CO₂ emissions. The model was then used to investigate how physical factors often overlooked in incubation experiments, such as soil depth, porosity, and alteration of soil structure, impact the moisture and temperature response of CO₂ emissions. Our results show that incubations substantially overestimate the temperature sensitivity of CO₂ emissions compared to that under field conditions, due to changes in the physical environment. Modifying soil structure also alters the moisture and temperature response of CO₂ emissions. These findings demonstrate the role of physical factors in regulating CO₂ emissions and underscore the need for caution when extrapolating incubation results to field conditions or using them to predict the response of soil carbon dynamics to global warming
Fingerprinting using compound-specific δ13C of n-alkanes reveals the temporary role of paddy fields as a secondary source for watershed sediment loss
No full textSediment fingerprinting generates reliable sediment provenance information which supports policy or practical strategies for catchment sediment management. But the approach remains challenging in areas with complex landscape configuration. This investigation evaluated the seasonality of biomarker signatures and their variability among particle size fractions, and accordingly apportioned target time-integrated suspended sediment to land-use based sources in an intensive farming watershed with mosaic land use patch configurations and crop-specific farming practices. Source materials (i.e., topsoil) from dry croplands, paddy fields and citrus orchards were sampled, and time-integrated suspended sediment was collected at the watershed outlet. The absolute concentrations and compound-specific δ13C of long-chain saturated n-alkanes (C23-C33) were determined for two absolute particle size fractions (i.e., <25 μm and 25-63 μm). The δ13C of monomeric n-alkanes displayed no significant variabilities between the particle size fractions nor across the whole sampling period. The MixSIAR Bayesian model was employed to quantify sediment source contributions. Due to human activities, paddy fields have become an important sediment source, but dry farmland remains the largest contributor. Based on sediment source information for the study watershed, a range of measures such as soil virginization, returning straw to fields, and pasture cultures in orchards are recommended
Detection of aphid infestation on faba bean (Vicia faba L.) by hyperspectral imaging and spectral information divergence methods
No full textAphids hide under leaves, reproduce rapidly, and require early detection to prevent crop damage, disease transmission, and ensure effective pest management. This study presents a novel approach for aphid detection by utilizing hyperspectral imaging, multivariate classification methods and spectral information divergence (SID) analyses. The hyperspectral images average spectrum (n = 336) showed significant differences between healthy and infested leaves. Time-series classification was performed over 14 days after infestation using four distinct machine learning algorithms. Early-stage infection detection may not relate to internal physiological alterations within the leaf but rather to the physical presence of the aphid behind the leaf, obstructing subtle physiological signatures. Implementation of spectral endmembers in the VIS–NIR reference spectrum led to the identification of an informative abundance SID map within the 710–825 nm range, useful for further classification. Machine learning classification resulted in support vector machines achieving 99.20 accuracy. Using random forest, twenty-two most important variables found effective in boosting classifier performance. The selected model also extended to real-world scenarios by testing progressing infestation patterns over 14 days on independent data sets, confirming the system’s reliability. Signal normal variant pre-treatment with partial least squares regression was effective in the estimation of aphid populations, achieving a 0.81 coefficient of determination (R2) and a 10.29 root-mean-square error of prediction for test datasets. In conclusion, the proposed method was able to successfully detect aphid colony infestation, both earlier and in locations that are invisible during standard human inspection
NWFP_Daily_Data_QC_Adjusted_Summary_Report_2012-01-01-2023-12-31
No full textThis report includes tables and graphics of summary statistics of the daily means data set ‘NWFP_Daily_Means_QCadjusted_2012-01-01_2023-12-31.csv’ published on the Rothamsted Research data repository [https://data.rothamsted.ac.uk/dataset/qc-adjusted]. The published data set was calculated from yearly csv files(2012‐2023) of 15-minute time steps for water flow, various water quality parameters, soil temperature, soil moisture and precipitation that were downloaded from the North Wyke Farm Platform Data Portal [https://nwfp.rothamsted.ac.uk/].
The 15-minute data were first screened based on the Quality Control (QC) flag that was assigned to the value at each time step during the QC process. Values that did not have ‘Good’, ‘Acceptable’ and ‘Outlier’ QC flags were set to ‘NA’ to represent missing value
Biomass burning smoke pollution stimulates painted lady butterflies (Vanessa cardui L.) to increase flight speed
No full textSmoke from biomass burning significantly degrades air quality due to high concentrations of particulate matter (PM2.5) and trace gases. While the ecological and health impacts of smoke pollution are well documented, its effects on insect migration remain poorly understood. In this study, we conducted two experiments to investigate the flight performance of Vanessa cardui butterflies under varying smoke conditions and identify the mechanisms influencing their behaviour. Butterflies were tethered to flight mills (TFMs) for 6 h, during which flight speed, distance, and duration were recorded across clean-air conditions and three levels of PM2.5 concentrations. Statistical analysis revealed that flight speed increases significantly as smoke concentration increases, although the increased range decreases. At a mean PM2.5 concentration of 120 μg m−3, flight speed increased by 52 % compared to clean-air conditions. To determine whether particulate matter was driving this response, individuals were exposed to smoke with and without particulates. In smoke with particulates retained, butterflies exhibited nearly double the flight speed compared to filtered smoke, indicating that particulates play a key role in altering flight behaviour. Scanning electron microscopy revealed significant deposition of smoke particulates on the antennae and abdomen, suggesting a sensory or physical response triggering accelerated flight. We interpret these findings as evidence that Vanessa cardui accelerates flight in smoky environments as an escape response. This study highlights the remarkable sensitivity of butterflies to smoke pollution and provides novel insights into the ecological consequences of biomass burning, particularly its potential impacts on insect behaviour and migration dynamics
Proteomic Profiling of Celiac-Toxic Motifs and Allergens in Cereals Containing Gluten
No full textCereal-based foods can cause immune-mediated adverse reactions, including celiac disease and IgE-mediated allergies, but the potency of different cereal species to cause such reactions appears to vary, with oats being less celiac-toxic and allergenic than wheat. In order to define differences in the immunological potential of wheat, barley, rye, and oats, proteomic profiling of proteins carrying celiac-toxic motifs and allergens has been undertaken. Total protein extracts were subjected to chymotryptic digestion and analyzed using data-independent ion mobility mass spectrometry and a pipeline employing a curated gluten protein sequence database. Depending on the cereal species, 376−2769 proteins were identified, the majority being grain storage proteins. Relative quantitation of proteins containing celiac-toxic motifs showed that they were most abundant and diverse in wheat, with only a limited number, at much lower abundance, identified in oats. Allergens belonging to the seed storage prolamins were the most abundant, while allergens belonging to the α-amylase/trypsin inhibitor family associated with respiratory allergy were of only moderate abundance in comparison. Wheat allergen homologues were identified in other cereal species but at a very low level in oats. These data suggest that the relative risk of oats in the context of both celiac disease and IgE-mediated allergy is low
Evaluating the efficacy of a novel multi-component feed additive for methane mitigation and performance enhancement in sheep
No full textEnteric methane emissions from ruminants significantly contribute to global greenhouse gas emissions, necessitating effective mitigation strategies that also support animal productivity. This study assessed the efficacy of NuAdvent+, a novel feed additive combining medium-chain fatty acids (MCFAs), live yeast, plant-based agents, and Vitamin B, in reducing methane emissions, improving feed efficiency, and enhancing growth and immune function in sheep. Twenty crossbred castrated male sheep (52 ± 3.7 kg) were divided into control and treatment groups (n = 10 each), with the treatment group receiving grass pellets supplemented with NuAdvent+ (20 g/day) for 71 days, including a 30-day acclimatisation period. Feed intake, methane emissions, growth performance, and blood parameters were monitored using BioControl pens, GreenFeed units, and haematological analyses. The treatment group exhibited a 24% increase in daily feed intake (p < 0.001) and a 22.2% reduction in methane yield per kg of dry matter ingested (p < 0.001), attributed to MCFAs’ anti-methanogenic properties and yeast’s rumen modulation. However, no significant improvements were observed in daily live weight gain, feed conversion efficiency, or immune markers, suggesting limited energy utilisation for growth. These findings highlight NuAdvent+ as a promising tool for methane mitigation in forage-based systems, though its benefits are tempered by trade-offs in fibre digestibility and productivity. Further optimisation of dosage and dietary integration could enhance its application across ruminant species, contributing to sustainable livestock production