Relationships among slurry characteristics and gaseous emissions at different types of commercial Spanish pig farms
Becaccia, Amanda | Ferrer, Pablo | Ibañez, Miguel A. | Estellés, Fernando | Rodríguez, Carlos | Moset, Verónica | de Blas, Carlos | Calvet, Salvador | García-Rebollar, Paloma
This study aimed to analyse several factors of variation of slurry composition and to establish prediction equations for potential methane (CH4) and ammonia (NH3) emissions. Seventy-nine feed and slurry samples were collected at two seasons (summer and winter) from commercial pig farms sited at two Spanish regions (Centre and Mediterranean). Nursery, growing-fattening, gestating and lactating facilities were sampled. Feed and slurry composition were determined, and potential CH4 and NH3 emissions measured at laboratory. Feed nutrient contents were used as covariates in the analysis. Near infrared reflectance spectroscopy (NIRS) was evaluated as a predicting tool for slurry composition and potential gaseous emissions. A wide variability was found both in feed and slurry composition. Mediterranean farms had a higher pH (p<0.001) and ash (p=0.02) concentration than those located at the Centre of Spain. Also, type of farm affected ether extract content of the slurry (p=0.02), with highest values obtained for the youngest animal facilities. Results suggested a buffer effect of dietary fibre on slurry pH and a direct relationship (p<0.05) with fibre constituents of manure. Dietary protein content did not affect slurry nitrogen content but decreased (p=0.003) total and volatile solids concentration. Prediction models of potential NH3 emissions (R2=0.89) and CH4 yield (R2=0.61) were obtained from slurry composition. Predictions from NIRS showed a high accuracy for most slurry constituents (R2>0.90) and similar accuracy of prediction of potential NH3 and CH4 emissions (R2=0.84 and 0.68, respectively) to models using slurry characteristics, which can be of interest to estimate emissions from commercial farms and establish mitigation strategies or optimize biogas production.
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