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Attraction of cabbage stem flea beetle (Psylliodes chrysocephala) to host plant odors
No full textBACKGROUND
Oilseed rape (OSR, Brassica napus) faces substantial yield losses in Europe due to the cabbage stem flea beetle (CSFB, Psylliodes chrysocephala). Synthetic insecticide use is constrained by resistance and environmental concerns, necessitating innovative pest control strategies. Understanding CSFB host plant selection, particularly through volatile organic compounds (VOCs), is essential for developing sustainable and efficient methods. This study investigated the olfactory response of CSFB in their pre-aestivation stage to plant VOCs.
RESULTS
Olfactometer bioassays showed that female CSFB were attracted to VOCs from mechanically damaged OSR plants (BBCH 10 and BBCH 14), while undamaged OSR plants elicited no response. Damaged seedlings of Sinapis alba and Brassica rapa were not attractive. When testing individual isothiocyanates, again only female CSFB showed a positive response in the olfactometer bioassays, while no response was found for two green leaf volatiles.
CONCLUSION
This research provides insights into the olfactory behavior of CSFB and, to our knowledge, is the first to show behavioral responses of adult CSFB towards host plant volatiles in olfactometer tests. Interestingly, only females responded to VOCs, suggesting sexual dimorphism in olfactory sensitivity during this life stage. These findings may help to lay the groundwork for further studies aimed at improving pest management strategies in OSR cultivation. © 2025 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry
Socio-economic factors constrain climate change adaptation in a tropical export crop
No full textClimate change will alter the geographical locations most suited for crop production, but adaptation to these new conditions may be constrained by edaphic and socio-economic factors. Here we investigate climate change adaptation constraints in banana, a major export crop of Latin America and the Caribbean. We derived optimal climatic, edaphic and socio-economic conditions from the distribution of intensive banana production across Latin America and the Caribbean, identifed using remote sensing imagery. We found that intensive banana production is constrained to low-lying, warm aseasonal regions with slightly acidic soils, but is less constrained by precipitation, as irrigation facilitates production in drier regions. Production is limited to areas close to shipping ports and with high human population density. Rising temperatures, coupled with requirements for labour and export infrastructure, will result in a 60% reduction in the area suitable for export banana production, along with yield declines in most current banana producing areas
A new conceptual model for seed germination and seedling tillering of winter wheat in the field
Full text linkSeed germination is a crucial stage in plant development, intricately regulated by various environmental stimuli. Understanding these interactions is essential for optimizing planting and seedling management but remains challenging due to the trade-off effects of environmental factors on the germination process. We proposed a new conceptual model by viewing seed germination as a dynamic process in a physiological dimension, with the influence of environmental factors and seed heterogeneity characterized by a germination speed and a dispersion coefficient. To validate the model, we conducted field experiments by drilling wheat seeds at different dates to establish a temperature gradient and in different plots to create a soil water content gradient. Comparisons with our experimental data and literature results show the model accurately reproduces all germination patterns and the subsequent seedling tillering, with R2>0.95. Our results reveal that within suboptimal temperature range, the seed germination increases asymptotically with temperature, and that as soil water content increases, the germination speed increases initially before decreasing, illustrating the trade-off effect of soil water on bioavailability of water and oxygen. Introducing a physiological dimension enables seed germination and the subsequent tillering proces to be modelled as a continuous physiological process, providing deeper insight into plant growth dynamics
Fermentation kinetics of finger millet-based Injera dough recipes: Implications for raffinose hydrolysis, amino acid content and other metabolites
No full textFinger millet is a nutritious, gluten-free cereal crop commonly consumed as whole flour. Despite its nutritional benefits, it contains antinutritional factors such as raffinose, which can cause intestinal distress and affect nutrient absorption and digestion. Fermentation is one of the methods that can be employed to reduce antinutrients in cereals. However, detailed studies on raffinose hydrolysis as well as changes in sugar profiles, amino acid content and other metabolites during the traditional fermentation of finger millet based Injera dough (typically 4–7 days) are limited. This study investigated the fermentation kinetics and its implication in changes in raffinose levels and levels of other metabolites in finger millet-based dough recipes used to prepare Injera, a staple Ethiopian flatbread. Over a seven-day fermentation period, samples from finger millet and finger millet-maize composite dough recipes were analyzed at 24-hour intervals for pH, titratable acidity (TA), microbial growth, raffinose content, amino acids and levels of other metabolites following standard procedures. A decrease in pH and an increase in TA was observed across all recipes at the later stages of fermentation. LAB counts increased from 2.55 to 9.86logcfu/g and yeast counts increased from 1.13 to 6.41logcfu/g from the initial stage to 168 h of fermentation. A two-step fermentation process involving both lactic acid and alcoholic fermentation was observed, resulting in lactic acid and mannitol as the main end products. Fermentation significantly enriched the metabolite profile of fermented dough recipes (p < 0.05) including mono and disaccharides, sugar alcohols, organic acids, while reducing the raffinose content with a decrease ranging from 77.83 % to 99.83 % for the various dough recipes. Both essential and non-essential amino acids also increased (increment ranging from 30.9 % to 140.5 %) across all dough recipes with an increase in fermentation time. In conclusion, the seven-day fermentation process significantly decreased the raffinose content while increasing the levels of amino acids and other beneficial metabolites across all dough recipes. The reduction in raffinose suggests improved digestibility, while the increased amino acids and metabolites further support the use of finger millet as a nutritious staple food option in Ethiopia
The number of phosphorus loss events will increase with variability and seasonality in far future climate scenarios
No full textClimate change is likely to add further pressures to water quality degradation across the globe. The development of robust climate-smart mitigation measures necessitates understanding the impact of extreme hydrological events on catchment hydrology and nutrient losses. Here, empirical modelling (EM) was applied on 14 years of sub-hourly water quality and weather data from six hydrologically diverse agricultural catchments in Ireland to understand the climatic factors that trigger an increase in phosphorus (P) losses [manifested as increase of 0.01 mg L−1 in total phosphorus (TP) and increase of 0.005 mg L−1 in total reactive phosphorus (TRP) over one day]. Plausible future P-loss due to extreme weather events was then modelled using climate change scenarios (from 2010 to 2100) for medium and high emission pathways, i.e. Representative concentration pathways (RCP) 4.5 and RCP8.5, respectively. EM identified three climatic conditions that trigger TP and TRP losses across all study catchments, namely: (i) cumulative effective rainfall >5mm over five days followed by effective rainfall>5 mm in one day; (ii) effective rainfall>5 mm in one day, and; (iii) effective rainfall over ten mm in one day. Together, these criteria captured up to 80% of the events across all catchments despite their different characteristics. From the projected climate change scenarios, the frequency of triggering events and their associated discharge rates, increases significantly towards the end of the century in all catchments, especially under RCP8.5. The sensitivity of catchment response to the changing weather patterns and the monthly trend of precipitation throughout the century strongly depended on catchment characteristics. The hydrologically flashy catchments in the dataset tend to be most sensitive to climate driven changes, returning the highest percentage increase of annual P-loss events in both RCPs. Considering far-future scenario, there would be 10–66% increase in the number of P-loss events under RCP4.5, and 28–67% under RCP8.5, taking into account the potential underestimation of projected precipitation probability. Assuming no changes in P-inputs in the future scenarios, the projections also indicated average discharge of up to 8.5 mm per a single triggering event that would directly contribute to increases in P-concentrations and mass loads leaving the catchments. Changes in climate are likely to compound already significant challenges in improving/ maintaining good water quality. It is therefore critical to incorporate the influences of climate change on nutrient losses in developing mitigation/adaptation strategies that are tailored to catchment-specific characteristic
The distinct roles of genome, methylation, transcription, and translation on protein expression in Arabidopsis thaliana resolve the Central Dogma’s information flow
No full textBackground: We investigate the flow of genetic information from DNA to RNA to protein as described by the Central Dogma in molecular biology, to determine the impact of intermediate genomic levels on plant protein expression.
Results: We perform genomic profiling of rosette leaves in two Arabidopsis accessions, Col-0 and Can-0, and assemble their genomes using long reads and chromatin interaction data. We measure gene and protein expression in biological replicates grown in a controlled environment, also measuring CpG methylation, ribosome-associated transcript levels, and tRNA abundance. Each omic level is highly reproducible between biological replicates and between accessions despite their ~1% sequence divergence; the single best predictor of any level in one accession is the corresponding level in the other. Within each accession, gene codon frequencies accurately model both mRNA and protein expression. The effects of a codon on mRNA and protein expression are highly correlated but independent of genome-wide codon frequencies or tRNA levels which instead match genome-wide amino acid frequencies. Ribosome-associated transcripts closely track mRNA levels.
Conclusions: DNA codon frequencies and mRNA expression levels are the main predictors of protein abundance. In the absence of environmental perturbation neither gene-body methylation, tRNA abundance nor ribosome-associated transcript levels add appreciable information. The impact of constitutive gene-body methylation is mostly explained by gene codon composition. tRNA abundance tracks overall amino acid demand. However, genetic differences between accessions associate with differential gene-body methylation by inflating differential expression variation. Our data show that the dogma holds only if both sequence and abundance information in mRNA are considered
Ruderal Tithonia diversifolia inclusion in sheep diets: impacts on digestibility and greenhouse gas emissions
No full textEmissions from ruminant livestock represent an important component of agricultural greenhouse gas output. The sector, however, has substantial potential for emission reduction through improved practices. Tithonia diversifolia (TD), a shrub that thrives in low-fertility soils, offers promise as a sustainable feed alternative. This study explores whether ruderal TD, accessible but with variable nutritional quality, can be used to reduce enteric methane (CH4) emissions and nitrogen (N) excretion in sheep, offering a low-input strategy for enhancing ruminant sustainability. Eight adult rams were used to evaluate diets with 4 increasing levels of TD hay on carbon dioxide (CO2), CH4, nitrous oxide (N2O) and ammonia (NH3) emissions, apparent digestibility, and fermentation parameters. The animals received four increasing levels of TD hay (0, 90, 270, 450 g kg-1 DM) in a diet based on Tifton 85 hay, soybean meal, and ground corn. Feeding sheep with ruderal TD had no effects on intake and N balance but reduced digestibility of dry matter, organic matter, neutral and acid detergent fiber, while crude protein digestibility remained unaffected. There was also a decrease in acetate and ruminal N-NH3 concentrations, alongside an increase in iso-acid proportions. CO2, CH4, N2O and NH3 emissions were consistent across diets, averaging 98.05 gCO2 kg-1 DMI, 9.3 gCH4 kg-1 DMI, 2.62 gN2O kg-1 excreted N, and 37.8 gNH3 kg-1 excreted N. In conclusion, incorporating ruderal TD into sheep diets reduced nutrient digestibility and ruminal fermentation but did not impact feed intake, protein digestibility, or greenhouse gas emissions
The Global Wheat Full Semantic Organ Segmentation (GWFSS) dataset
No full textComputer vision is increasingly used in farmers' fields and agricultural experiments to quantify important traits. Imaging setups with a sub-millimeter ground sampling distance enable the detection and tracking of plant features, including size, shape, and colour. Although today's AI-driven foundation models segment almost any object in an image, they still fail for complex plant canopies. To improve model performance, the global wheat dataset consortium assembled a diverse set of images from experiments around the globe. After the head detection dataset (GWHD), the new dataset targets a full semantic segmentation (GWFSS) of organs (leaves, stems and spikes) covering all developmental stages. Images were collected by 11 institutions using a wide range of imaging setups. Two datasets are provided: i) a set of 1096 diverse images in which all organs were labelled at the pixel level, and (ii) a dataset of 52,078 images without annotations available for additional training. The labelled set was used to train segmentation models based on DeepLabV3Plus and Segformer. Our Segformer model performed slightly better than DeepLabV3Plus with a mIOU for leaves and spikes of ca. 90 %. However, the precision for stems with 54 % was rather lower. The major advantages over published models are: i) the exclusion of weeds from the wheat canopy, ii) the detection of all wheat features including necrotic and senescent tissues and its separation from crop residues. This facilitates further development in classifying healthy vs. unhealthy tissue to address the increasing need for accurate quantification of senescence and diseases in wheat canopies
A Global Short Rotation Coppice (SRC) Willow Dataset for the Bioeconomy: Implications for the Yield in the United Kingdom
No full textShort rotation coppice (SRC) willow is a second-generation lignocellulosic energy crop with a background of research and breeding programmes carried out globally for more than three decades. While commercial standards include planting in mixtures of 6–8 willow genotypes of genetic diversity, much research to date has focused on monoculture trials. Research has found significant differences in willow performance through different management methods, soil properties and environmental interactions (GxE), when applied locally. However, global analysis of these interactions remains a challenge. We present a global SRC willow dataset to facilitate researchers and growers with a resource not available to date to help in closing the gap between research and industry. Data has been collected through literature review and personal communications with key researchers on willow in the United Kingdom. Global annual average yield is 9 Mg Dry Matter (DM) ha−1 year−1 with 17 genotypes, including two types of mixtures, above the economic threshold of 10 Mg DM ha−1 year−1. Canada and the United States are the best and worst performers with 10.6 and 6.7 Mg DM hr−1 year−1, respectively. We expect this dataset to provide an efficient way of estimating yields at a smaller scale by multiple combinations of GxE interactions. Biomass production from 1-year-old stems in the first harvest cycle is significantly lower than for the second and third year of the first harvest cycle (ANOVA, p < 0.001). Harvest cycles of 2 and 3 years did show significant but small differences in final yield (t = 3.87, p < 0.001). A random forest statistical procedure was applied to test for the association of the predictor variables with biomass production. The model explained up to 63.65% of the variance observed in yield for all genotypes and sites, with genetic diversity among the most important variables
Soil microbial diversity: A key factor in pathogen suppression and inoculant performance
No full textSoil microbial diversity plays a crucial role in plant health, influencing pathogen suppression and biocontrol efficacy. This study investigated how soil microbial diversity modulates interactions between the pathogen Bipolaris sorokiniana and the biocontrol bacterium Pseudomonas inefficax in the wheat rhizosphere. Using a dilution-to-extinction method, we established five soil microbial diversity levels: natural soil, dilutions at 10-1, 10-3, 10-6, and fully autoclaved soil. This gradient allowed us to evaluate disease severity, plant growth, and rhizosphere microbiome shifts. Inoculation with Pseudomonas inefficax significantly reduced disease severity caused by Bipolaris sorokiniana, particularly in low-diversity soils, emphasizing the effectiveness of P. inefficax in these simplified environments where microbial competition is reduced. Despite higher pathogen abundance in low-diversity soils, P. inefficax effectively mitigated disease severity, likely through direct antagonistic activity. Alpha diversity indices confirmed a reduction in microbial diversity across the gradient, while beta diversity analyses revealed distinct shifts among treatments. Although Chitinophaga, Pseudomonas and Dyadobacter were significantly enriched in natural soils with inoculation of the P. inefficax, statistically significant disease suppression was not observed under these higher-diversity conditions. On the other hand, in low-diverse soils (autoclaved soil), where disease is suppressed with P. inefficax inoculation, Fluviicola showed a significant enrichment when compared with the treatment inoculated only with the pathogen, suggesting that this bacterial taxon can play a role in disease suppression along with the inoculant. These findings underscore the critical role of the soil microbial diversity in shaping the success of biocontrol interventions