This study explores the application of deep learning (DL) models to predict methane (CH) emissions from enteric fermentation in dairy cows using performance, feeding, behavioral and weather data from automated milking and feeding systems, behavioral ...
Machine learning has the potential to support the growing need for high-resolution greenhouse gas monitoring in urban and industrial environments, where deploying extensive sensor networks is often limited by cost and operational challenges. This stu...
Nonalcoholic fatty liver disease (NAFLD) is now the leading cause of global chronic liver disease, affecting approximately 32.4% of the population in various regions and imposing healthcare and economic burdens. The gold standard for the diagnosis of...
Measuring dairy cattle methane (CH4) emissions using traditional recording technologies is complicated and expensive. Prediction models, which estimate CH4 emissions based on proxy information, provide an accessible alternative. This review covers th...
Semi-continuous biogas production from fruit and vegetable waste by medium temperature anaerobic fermentation was conducted. Hydrogen production under different food-microorganism ratios (F/M 0.5, 0.75, 1.0, 1.5) and hydraulic retention times (HRT) (...
Two experiments evaluated the effect of calcium ammonium nitrate decahydrate (calcium nitrate [NIT]) and monensin sodium (MON) on in vitro fermentation parameters of 2 contrasting diets (100:0 and 10:90 forage-to-concentrate ratios). Diet addition of...
Water environment research : a research publication of the Water Environment Federation
Nov 1, 2016
Algae grown in wastewater treatment lagoons are a potentially important substrate for biofuel production. The feasibility of using upflow anaerobic sludge blanket (UASB) reactors in anaerobic digestion of algae to produce methane was investigated. ...
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