Assessing the accuracy of current near infra-red reflectance spectroscopy analysis for fresh grass-clover mixture silages and development of new equations for this purpose

The purpose of this study was to ascertain whether Near Infra-Red Reflectance Spectroscopy (NIRS) prediction equations calibrated on grass silage samples, could accurately predict the chemical composition of mixed grass-clover silage samples, and furthermore, to develop and calibrate new grass-clover equations should the grass-based equations be insufficiently accurate for these silages. A set of 94 silage samples from mixed grass-clover swards (clover concentration (CC) ranging from 4 to 1000 g/kg as fed; determined manually) were analysed for chemical composition using reference laboratory techniques, in vivo digestible organic matter in the dry matter (DOMD, in sheep), and in situ degradability of dry matter and crude protein (in cows). The same samples were scanned fresh (undried and unmilled, as is standard practice for silage analysis within UK laboratories) using NIRS (at AFBI, Northern Ireland) and grass-based prediction equations applied. Predicted and observed results were compared. Of 15 chemical components that were tested for prediction accuracy, only volatile-corrected dry matter and nitrogen were well predicted (RPD values of 4.9 and 2.4 respectively, with low root mean square errors of prediction (RMSEP)). Neutral detergent fibre and DOMD showed low RPD values, however the predicted and observed datasets had no significant bias between them and were therefore also considered as fit for purpose. Variables with significant bias between predicted and observed datasets that were not considered suitably accurate included crude protein, acid detergent fibre, microbial dry matter yield and the effective degradability of protein. For many components, bias could be attributed at least in part to CC and changes in the fractionation of nutrients present. For some variables such as crude protein, grass-based equations were sufficiently accurate at low CCs but became inaccurate as CC increased, as expected. In response to inadequate prediction accuracy of certain nutrients, new grass-clover equations were calibrated using the obtained spectra. These were validated and results indicated that the grass-clover-based equations outperformed their grass-based counterparts. The adoption of new grass-clover equations, or alternatively, with further development, the use of a CC correction factor to the existing grass-based equations, is recommended for commercial laboratories offering undried and unmilled silage analysis on samples containing clover

The effects on cow performance and calf birth and weaning weight of replacing grass silage with brewers grains in a barley straw diet offered to pregnant beef cows of two different breeds

Background Experiential peers are increasingly involved in the development and delivery of interventions for individuals who are engaged in delinquent behavior. Experiential peer support, which is the provision of support to an individual engaged in delinquent behavior by someone who has previously also practiced such behavior, is one such application. Little is known, however, about its effects on desistance, or the mechanisms that explain these effects. On the basis of theoretical papers, program descriptions, and interviews with experts, we developed an initial program theory. We propose seven mechanisms that might play a role in the (potential) effects of support by experiential peers: (1) empathy and acceptance, (2) social learning, (3) social bonding, (4) social control, (5) narrative and identity formation, (6) hope and perspective, and (7) translation and connection. In addition, in this protocol paper, we describe the methods of a systematic realist literature review that will be conducted in order to investigate the evidence base for this program theory. Methods The study described in this protocol paper is a realist review, which is a suitable approach to study complex interventions and fits the explanatory purpose of the study. We outline the steps to be taken for the systematic realist review, including the selection and assessment of studies and the methods for synthesizing the findings. Discussion Investigating the effects and the underlying mechanisms of support by experiential peers for individuals with delinquent behavior is relevant because the forensic setting has some unique features, and the involvement of service users might create even more tension than in other settings due to stigma and perceived risks. The findings that will be reported in the realist review will contribute to the knowledge of the effects of support by experiential peers and will provide insight into which aspects remain to be studied. It might also provide formal care institutions with guidance on whether to involve experiential peers in the delivery of their services and the conditions under which these interventions are likely to lead to positive results

Estimated differences in economic and environmental performance of forage-based dairy herds across the UK

Differences in performance among the areas of England, Scotland, Wales and Northern Ireland can provide some insight into the resilience of UK milk supplies from forage-based dairy herds. This study used a Markov Chain approach to model the average herd in each region between the years 2010 to 2015. The effect of a single unit change in milk production (milk volume, fat yield and protein yield), fitness (survival, somatic cell count, mastitis and calving interval) and efficiency (methane) traits on the economic value and GHG emissions intensity (expressed as carbon dioxide equivalents per cow and per kg milk solids) were assessed. Production data were obtained from a total of about half a million milk recorded dairy cows in the UK and the Farm Business Surveys for each region. Across the UK improving the health (SCC and mastitis), fertility (calving intervals) and survival of cows will increase profitability and reduce emissions intensity of milk production. In Scotland, herds had higher milk yields but poorer survival, which potentially could be due to poor fertility indicated by a longer calving interval compared to other regions. Herds in Northern Ireland had the shortest average calving interval but the highest somatic cell counts (SCC), and thus greater estimated mastitis incidence and wasted milk. Notably, England had considerably higher economic values (between 10 and 30%) and emission intensity values (between 11 and 37%) for SCC and mastitis incidence than other regions, due to lost milk production and the higher gross margin. This study provides a framework that can be customised for individual herds to allow assessment of resilience and resource efficiency of milk production not only in the UK but for comparison with international dairy systems

Dynamic model development of enteric methane emission from goats based on energy balance measured in indirect open circuit respiration calorimeter

[EN] A dynamic model of methane (CH4) emission in goats was proposed and parameterized from energy balance experimental data. The model focused on dry matter intake and fat content of the diet as explanatory variables for CH4 emission. Experimental and literature data were used to develop the model. Then, data (n = 123) from five energy balance experiments were used to evaluate the model. The model was adequate to represent energy in milk, heat production and CH4 emissions. Residual analysis showed that most of the prediction errors were due to unexplained variations with small mean and slope bias (around zero with exception of CH4; <6%). The model tends to over-predict energy in CH4 at higher energy intake and, energy in milk and heat production at lower energy intake. Random bias was greater than 90%, signifying than more than 90% of the error was non-systematic indicating the mechanism in the model are properly represented. The model is a first step towards a mechanistic description of nutrient use by goats and, useful as a research tool for investigating energy partition in dairy goat systems. The model described in this study should be considered for preparation of enteric CH4 emissions inventories for goats. (c) 2018 The Author. Published by Elsevier B.V.This study was supported by LOW CARBON FEED Project reference LIFE2016/CCM/ES/000088.Fernández Martínez, CJ. (2018). Dynamic model development of enteric methane emission from goats based on energy balance measured in indirect open circuit respiration calorimeter. Global Ecology and Conservation. 15:1-14. https://doi.org/10.1016/j.gecco.2018.e00439S1141

A simulation model to investigate interactions between first season grazing calves and Ostertagia ostertagi

AbstractA dynamic, deterministic model was developed to investigate the consequences of parasitism with Ostertagia ostertagi, the most prevalent and economically important gastrointestinal parasite of cattle in temperate regions. Interactions between host and parasite were considered to predict the level of parasitism and performance of an infected calf. Key model inputs included calf intrinsic growth rate, feed quality and mode and level of infection. The effects of these varied inputs were simulated on a daily basis for key parasitological (worm burden, total egg output and faecal egg count) and performance outputs (feed intake and bodyweight) over a 6 month grazing period. Data from published literature were used to parameterise the model and its sensitivity was tested for uncertain parameters by a Latin hypercube sensitivity design. For the latter each parameter tested was subject to a 20% coefficient of variation. The model parasitological outputs were most sensitive to the immune rate parameters that affected overall worm burdens. The model predicted the expected larger worm burdens along with disproportionately greater body weight losses with increasing daily infection levels. The model was validated against published literature using graphical and statistical comparisons. Its predictions were quantitatively consistent with the parasitological outputs of published experiments in which calves were subjected to different infection levels. The consequences of model weaknesses are discussed and point towards model improvements. Future work should focus on developing a stochastic model to account for calf variation in performance and immune response; this will ultimately be used to test the effectiveness of different parasite control strategies in naturally infected calf populations