Browsing Grassland Science by Subject "meta-analysis"
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Application of Meta-Analysis and Machine Learning Methods to the Prediction of Methane Production from In Vitro Mixed Ruminal Micro-Organism FermentationIn vitro gas production systems are utilized to screen feed ingredients for inclusion in ruminant diets. However, not all in vitro systems are set up to measure methane (CH4) production, nor do all publications report in vitro CH4. Therefore, the objective of this study was to develop models to predict in vitro CH4 production from total gas and volatile fatty acid (VFA) production data and to identify the major drivers of CH4 production in these systems. Meta-analysis and machine learning (ML) methodologies were applied to a database of 354 data points from 11 studies to predict CH4 production from total gas production, apparent DM digestibility (DMD), final pH, feed type (forage or concentrate), and acetate, propionate, butyrate and valerate production. Model evaluation was performed on an internal dataset of 107 data points. Meta-analysis results indicate that equations containing DMD, total VFA production, propionate, feed type and valerate resulted in best predictability of CH4 on the internal evaluation dataset. The ML models far exceeded the predictability achieved using meta-analysis, but further evaluation on an external database would be required to assess generalization ability on unrelated data. Between the ML methodologies assessed, artificial neural networks and support vector regression resulted in very similar predictability, but differed in fitting, as assessed by behaviour analysis. The models developed can be utilized to estimate CH4 emissions in vitro.
Meta-analysis of the effect of white clover inclusion in perennial ryegrass swards on milk productionThere is increased demand for dairy products worldwide, which is coupled with the realization that consumers want dairy products that are produced in a sustainable and environmentally benign manner. Forage legumes, and white clover (Trifolium repens L.; WC) in particular, have the potential to positively influence the sustainability of pasture-based ruminant production systems. Therefore, there is increased interest in the use of forage legumes because they offer opportunities for sustainable pasture-based production systems. A meta-analysis was undertaken to quantify the milk production response associated with the introduction of WC into perennial ryegrass swards and to investigate the optimal WC content of dairy pastures to increase milk production. Two separate databases were created. In the grass-WC database, papers were selected if they compared milk production of lactating dairy cows grazing perennial ryegrass-WC (GC) swards with that of cows grazing perennial ryegrass-only swards (GO). In the WC-only database, papers were selected if they contained milk production from lactating dairy cows grazing on GC swards with varying levels of WC content. Data from both databases were analyzed using mixed models (PROC MIXED) in SAS (SAS Institute, Cary, NC). Within the grass-WC database, where mean sward WC content was 31.6%, mean daily milk and milk solids yield per cow were increased by 1.4 and 0.12 kg, respectively, whereas milk and milk solids yield per hectare were unaffected when cows grazed GC compared with GO swards. Stocking rate and nitrogen fertilizer application were reduced by 0.25 cows/ha and 81 kg/ha, respectively, on GC swards compared with GO swards. These results highlight the potential of GC production systems to achieve similar levels of production to GO systems but with reduced fertilizer nitrogen inputs, which is beneficial from both an economic and environmental point of view. In the context of increased demand for dairy products, there may be potential to increase the productivity of GC systems by increasing fertilizer nitrogen use to increase stocking rate and carrying capacity while also retaining the benefit of WC inclusion on milk production per cow.