Rapid Prediction Methods And Models Of Methane Emission And Manure Nutrient Contents From Beef Cattle

Livestock manure excretion and methane emission are major environmental pollution sources of husbandry. Based on the research of the literature from home and abroad, this experiment was to study methods and models of rapidly estimating methane emission value of beef cattle and fertilizer value of beef cattle slurries, which would provide some theoretical support for controlling the output of animal wastes and harmless resource utilization of animal manures as well.Four beef cattle were subjected to different levels of feedstuff, energy intake and roughage proportion. Methane emission value was determined by SF6 permeation tubes. Analytical results of this experiment showed that methane emission value from ruminant livestock could be determined quickly by SF6 tracer method; Type of feedstuff was the most influencing factor, then energy intake and roughage proportion; Methane emission value when beef cattle were subjected to silage corn and alfalfa compared with corn stover and straw was less; Methane emission value increased when energy intake increased; Methane emission value increased when roughage proportion increased; Diet component and intake were highly correlative with methane emission value, and dry matter intake and general energy intake could be evaluated for estimating methane emission value of beef cattle.This experiment was to study correlations of physical and chemical properties and fertilizer value of beef cattle manure. Slurry samples from 220 beef cattle of 8 varieties were obtained from October 2002 to January 2004. The results indicated that SG (specific gravity) and DM (dry matter) content were quite correlative, thus SG could predict fertilizer value of beef cattle manure in place of DM content. SG and EC (electrical conductivity) could predict TN (total nitrogen) quite exactly, as well as SG and pH for TP (total phosphorus), EC for TK (total potassium). But they all couldn't predict AN (ammonium nitrogen) well.200 typical samples of beef cattle manure were collected and scanned from 1000 to 2500nm on a FT-IR NIR (Near infrared reflectance) system. Spectrum treated by first-dimension derivative was analyzed using PLS (partial least-squares) regression. Calibration equations were established after obtaining of optimal spectrum area of prediction for TN, TP, TK and AN, and optimal dimensions of main contents, also they were validated. Results showed that the difference between NIR results and their true value was not significant (p>0.05), so NIRS could be a viable method alternative to conventional laboratory analysis procedures for determining manure fertilizer content.