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

Field-study science classrooms as positive and enjoyable learning environments

We investigated differences between field-study classrooms and traditional science classrooms in terms of the learning environment and students’ attitudes to science, as well as the differential effectiveness of field-study classrooms for students differing in sex and English proficiency. A modified version of selected scales from the What Is Happening In this Class? questionnaire was used to assess the learning environment, whereas students’ attitudes were assessed with a shortened version of a scale from the Test of Science Related Attitudes. A sample of 765 grade 5 students from 17 schools responded to the learning environment and attitude scales in terms of both their traditional science classrooms and classrooms at a field-study centre in Florida. Large effect sizes supported the effectiveness of the field-studies classroom in terms of both the learning environment and student attitudes. Relative to the home school science class, the field-study class was considerably more effective for students with limited English proficiency than for native English speakers

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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Human Resources Information Systems: A Recent Literature Survey

With the advent of technology and science, the business environment will keep changing very fast. Today, Information Technology (IT) is used in almost all business applications. The most important improvements are being realized at the management side since IT is fully supporting decision-making processes now. Human Resources Management (HRM) is being affected by IT such as web-based technologies and intelligent systems and these systems make HRM much more effective. Today’s HRM-related software do not deal with just payrolls, they also include recruiting and record-keeping, training and performance appraisal which have transitioned HRM from task-oriented to people-oriented. Today, Human Resources Information Systems (HRIS) and electronic HRM (e-HRM) are being utilized by many organizations all over the world and play a strategic role in decision-making processes for effective and efficient HRM. This study investigates the recent literature on HRIS, e-HRM and Decision Support Systems in HRM to identify the improvements and debates on contemporary Human Resources Management