Evaluation and development of prediction models for enteric methane emissions from cattle in India

India is home to more than 525 million ruminants, which are major contributors to global warming via enteric methane (Ent CH4 ) emissions. Various mitigation strategies exist to reduce Ent CH4 emissions but accurate emission estimates are needed to establish the true potential of these strategies. Measuring Ent CH4 emissions is expensive and unrealistic at such a large scale, so an urgent need exists for accurate Ent CH4 prediction models. The present study evaluated the accuracy of various existing models and developed a new model to predict Ent CH4 emissions from cattle in India. Six Ent CH4 prediction models based on either DMI or gross energy intake (GEI) were identified as applicable to and suitable for the Indian context. Models based on DMI and GEI were derived from various works, including those of the Intergovernmental Panel on Climate Change and others (designated as IPCC DMI , IPCC GEI , Ribeiro DMI , Ribeiro GEI , Patra DMI , and Patra GEI ). These were evaluated using 2 independent datasets characterizing 528 lactating (dairy) and 122 nonlactating (nondairy) cattle from 15 and 13 studies, respectively, under different management practices across 13 Indian states. Furthermore, the same datasets were combined to develop an empirical Ent CH4 prediction model using a linear mixed-effects framework. The relative prediction error (RPE) and mean bias error (MBE) were used to evaluate model accuracy. A model's prediction was considered acceptable when RPE was