This factsheet is a summary of the most important information currently available on Cobweb disease (Cladobotryum spp.). Its objective is to provide guidance on the recognition, prevention and control of the disease.

Sensory science has advanced significantly in the past decade and is quickly evolving to become a key tool for predicting food product success in the marketplace. Increasingly, sensory data techniques are moving towards more dynamic aspects of sensory perception, taking account of the various stages of user-product interactions. Recent technological advancements in virtual reality and augmented reality have unlocked the potential for new immersive and interactive systems which could be applied as powerful tools for capturing and deciphering the complexities of human sensory perception. This paper reviews recent advancements in virtual and augmented reality technologies and identifies and explores their potential application within the field of sensory science. The paper also considers the possible benefits for the food industry as well as key challenges posed for widespread adoption. The findings indicate that these technologies have the potential to alter the research landscape in sensory science by facilitating promising innovations in five principal areas: consumption context, biometrics, food structure and texture, sensory marketing and augmenting sensory perception. Although the advent of augmented and virtual reality in sensory science offers new exciting developments, the exploitation of these technologies is in its infancy and future research will understand how they can be fully integrated with food and human responses. Industrial relevance: The need for sensory evaluation within the food industry is becoming increasingly complex as companies continuously compete for consumer product acceptance in today's highly innovative and global food environment. Recent technological developments in virtual and augmented reality offer the food industry new opportunities for generating more reliable insights into consumer sensory perceptions of food and beverages, contributing to the design and development of new products with optimised consumer benefits. These technologies also hold significant potential for improving the predictive validity of newly launched products within the marketplace.

Freshwaters worldwide are affected by multiple stressors. Timing of inputs and pathways of delivery can influence the impact stressors have on freshwater communities. In particular, effects of point versus diffuse nutrient inputs on stream macroinvertebrates are poorly understood. Point-source inputs tend to pose a chronic problem, whereas diffuse inputs tend to be acute with short concentration spikes. We manipulated three key agricultural stressors, phosphorus (ambient, chronic, acute), nitrogen (ambient, chronic, acute) and fine sediment (ambient, high), in 112 stream mesocosms (26 days colonisation, 18 days of manipulations) and determined the individual and combined effects of these stressors on stream macroinvertebrate communities (benthos and drift). Chronic nutrient treatments continuously received high concentrations of P and/or N. Acute channels received the same continuous enrichment, but concentrations were doubled during two 3-hour periods (day 6, day 13) to simulate acute nutrient inputs during rainstorms. Sediment was the most pervasive stressor in the benthos, reducing total macroinvertebrate abundance and richness, EPT (mayflies, stoneflies, caddisflies) abundance and richness. By contrast, N or P enrichment did not affect any of the six studied community-level metrics. In the drift assemblage, enrichment effects became more prevalent the longer the experiment went on. Sediment was the dominant driver of drift responses at the beginning of the experiment. After the first acute nutrient pulse, sediment remained the most influential stressor but its effects started to fade. After the second pulse, N became the dominant stressor. In general, impacts of either N or P on the drift were due to chronic exposure, with acute nutrient pulses having no additional effects. Overall, our findings imply that cost-effective management should focus on mitigating sediment inputs first and tackle chronic nutrient inputs second. Freshwater managers should also take into account the length of exposure to high nutrient concentrations, rather than merely the concentrations themselves.

Sustainable dairy cow performance relies on coevolution in the development of breeding and management strategies. Tailoring breeding programs to herd performance metrics facilitates improved responses to breeding decisions. Although herd-level raw metrics on performance are useful, implicitly included within such statistics is the mean herd genetic merit. The objective of the present study was to quantify the expected response from selection decisions on additive and nonadditive merit by herd performance metrics independent of herd mean genetic merit. Performance traits considered in the present study were age at first calving, milk yield, calving to first service, number of services, calving interval, and survival. Herd-level best linear unbiased estimates (BLUE) for each performance trait were available on a maximum of 1,059 herds, stratified as best, average, and worst for each performance trait separately. The analyses performed included (1) the estimation of (co)variance for each trait in the 3 BLUE environments and (2) the regression of cow-level phenotypic performance on either the respective estimated breeding value (EBV) or the heterosis coefficient of the cow. A fundamental assumption of genetic evaluations is that 1 unit change in EBV equates to a 1 unit change in the respective phenotype; results from the present study, however, suggest that the realization of the change in phenotypic performance is largely dependent on the herd BLUE for that trait. Herds achieving more yield, on average, than expected from their mean genetic merit, had a 20% greater response to changes in EBV as well as 43% greater genetic standard deviation relative to herds within the worst BLUE for milk yield. Conversely, phenotypic performance in fertility traits (with the exception of calving to first service) tended to have a greater response to selection as well as a greater additive genetic standard deviation within the respective worst herd BLUE environments; this is suggested to be due to animals performing under more challenging environments leading to larger achievable gains. The attempts to exploit nonadditive genetic effects such as heterosis are often the basis of promoting cross-breeding, yet the results from the present study suggest that improvements in phenotypic performance is largely dependent on the environment. The largest gains due to heterotic effects tended to be within the most stressful (i.e., worst) BLUE environment for all traits, thus suggesting the heterosis effects can be beneficial in mitigating against poorer environments.

Post-mixing aggression in pigs is a harmful and costly behaviour which negatively impacts both animal welfare and farm efficiency. There is vast unexplained variation in the amount of acute and chronic aggression that dyadic behaviours do not fully explain. This study hypothesised that certain pen-level network properties may improve prediction of lesion outcomes due to the incorporation of indirect social interactions that are not captured by dyadic traits. Utilising current SNA theory, we investigate whether pen-level network properties affect the number of aggression-related injuries at 24 hours and 3 weeks post-mixing (24hr-PM and 3wk-PM). Furthermore we compare the predictive value of network properties to conventional dyadic traits. A total of 78 pens were video recorded for 24hr post-mixing. Each aggressive interaction that occurred during this time period was used to construct the pen-level networks. The relationships between network properties at 24hr and the pen level injuries at 24hr-PM and 3wk-PM were analysed using mixed models and verified using permutation tests. The results revealed that network properties at 24hr could predict long term aggression (3wk-PM) better than dyadic traits. Specifically, large clique formation in the first 24hr-PM predicted fewer injuries at 3wk-PM and high betweenness centralisation at 24hr-PM predicted increased rates of injury at 3wk-PM. This study demonstrates that network properties present during the first 24hr-PM have predictive value for chronic aggression, and have potential to allow identification and intervention for at risk groups.

Cattle breeding programs that strive to reduce the animal-level incidence of lameness are often hindered by the availability of informative phenotypes. As a result, indicator traits of lameness (i.e., hoof health and morphological conformation scores) can be used to improve the accuracy of selection and subsequent genetic gain. Therefore, the objectives of the present study were to estimate the variance components for hoof health traits using various phenotypes collected from a representative sample of Irish dairy cows. Also of interest to the present study was the genetic relationship between both hoof health traits and conformation traits with producer-scored lameness. Producer-recorded lameness events and linear conformation scores from 307,657 and 117,859 Irish dairy cows, respectively, were used. Data on hoof health (i.e., overgrown sole, white line disease, and sole hemorrhage), mobility scores, and body condition scores were also available from a research study on up to 11,282 Irish commercial dairy cows. Linear mixed models were used to quantify variance components for each trait and to estimate genetic correlations among traits. The estimated genetic parameters for hoof health traits in the present study were greater (i.e., heritability range: 0.005 to 0.27) than previously reported in dairy cows. With the exception of analyses that considered hoof health traits in repeatability models, little difference in estimated variance components existed among the various hoof-health phenotypes. Results also suggest that producer-recorded lameness is correlated with both hoof health (i.e., genetic correlation up to 0.48) and cow mobility (i.e., genetic correlation = 0.64). Moreover, cows that genetically tend to have rear feet that appear more parallel when viewed from the rear are also genetically more predisposed to lameness (genetic correlation = 0.39); genetic correlations between lameness and other feet and leg type traits, as well as between lameness and frame type traits, were not different from zero. Results suggest that if the population breeding goal was to reduce lameness incidence, improve hoof health, or improve cow mobility, genetic selection for either of these traits should indirectly benefit the other traits. Results were used to quantify the genetic gains achievable for lameness when alternative phenotypes are available.

To investigate the effects ultrasound (20 kHz, 150–600 W) on physicochemical properties of emulsion stabilized by myofibrillar protein (MP) and xanthan gum (XG), the emulsions were characterized by Fourier transform infrared (FT-IR) spectroscopy, ζ-potential, particle size, rheology, surface tension, and confocal laser scanning microscopy (CLSM). FT-IR spectra confirmed the complexation of MP and XG, and ultrasound did not change the functional groups in the complexes. The emulsion treated at 300 W showed the best stability, with the lowest particle size, the lowest surface tension (26.7 mNm−1) and the largest ζ-potential absolute value (25.4 mV), that were confirmed in the CLSM photos. Ultrasound reduced the apparent viscosity of the MP-XG emulsions, and the changes of particle size were manifested in flow properties. Generally, ultrasound was successfully applied to improve the physical stability of MP-XG emulsion, which could be used as a novel delivery system for functional material.

The application of ultraviolet (UV) light to water, food contact surfaces and medical equipment for microbial inactivation is widely employed. To date, UV disinfection sources employed are primarily low-pressure and medium-pressure mercury lamps; emitting monochromatic and polychromatic light, respectively. Despite the widespread use of mercury lamps, there are multiple drawbacks associated with their use including; high energy consumption, large size which limits reactor design, high heat emission and the presence of mercury. Light emitting diodes (LEDs) have potential for use as a highly efficient UV decontamination technology. Recent advances in semiconductor development have resulted in UV-LEDs becoming more widely available. UV-LEDs emit monochromatic light, which enables customised UV-LED disinfection systems at specific wavelengths to be developed. The application of UV-LEDs for disinfection purposes has been studied in recent years, particularly with respect to water disinfections systems. In this review, studies relating to UV-LED food applications are discussed. Furthermore, the chemical changes induced in foods, as a result of UV treatment, together with advantages and limitations of the technology are outlined.

Atmospheric cold plasma is a green and emerging technology, highly interesting to the food industry for its application. Dielectric Barrier Discharges (DBD) can generate atmospheric cold plasma inside sealed packages filled with air through the use of high voltages. This study investigated the use of a large gap DBD design to generate a plasma discharge within the headspace of packaged herring fillets, and its effects on microbiological and quality markers of the fish stored for 11 days at 4 °C. DBD plasma treatment conditions were 70 kV or 80 kV for 5 min treatment time. Results showed that the microbial load (total aerobic mesophilic, total aerobic psychrotrophics, Pseudomonas, lactic acid bacteria and Enterobacteriaceae) were significantly (p < 0.05) lower in the treated samples compared to the control samples. However, samples exposed to the lowest applied voltage better retained key quality factors (lower oxidation and less colour modification). DBD-treatment caused a reduction in trapped water in the myofibrillar network (T21), identified using low-field nuclear magnetic resonance of protons (1H LF NMR). The results indicate that in-package plasma treatment could be employed as an effective treatment for reducing spoilage bacteria in fish.