肉牛甲烷排放与粪便肥料成分含量快速预测方法和模型的研究
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摘要
畜禽粪便和有害气体的排放是环境污染的主要来源之一。本研究在参考国内外相关文献资料的基础上，从理论的角度出发，以肉牛为研究对象，通过大量的试验，较系统地研究了肉牛废弃物排放的快速预测方法和模型，为有效控制畜禽废弃物的排放以及对畜禽粪便资源进行无害化、资源化利用提供了基础依据。
本研究在成功制备了SF_6渗透管的基础上，利用SF_6示踪法对肉牛在饲喂不同饲料类型、能量摄入水平、饲料精粗比情况下的甲烷排放量进行了测定，结果表明：SF_6示踪法可用来快速测定反刍动物的甲烷排放量；影响肉牛甲烷排放量因素的主次顺序依次为：饲料粗料类型＞能量摄入水平＞饲料精粗比；对肉牛饲喂紫花苜蓿和青贮玉米秸比饲喂稻草和干玉米秸时甲烷排放量要小，随着能量摄入水平的加大，肉牛的甲烷排放量也呈增加的趋势，日粮中粗饲料越多，则肉牛的甲烷排放量越大；肉牛日粮中各成分的日摄入量与甲烷排放量之间存在显著的相关关系，其中干物质摄入量和总能摄入量均可以很好地预测肉牛甲烷排放量。
本研究选用8个品种、220头不同肉牛于2002年10月～2004年1月期间进行饲养试验，采集具有代表性的粪样，研究了粪便的理化指标和主要肥料成分含量的相关关系，结果表明：粪便比重与干物质含量之间存在较好的正线性相关关系(R~2=0.80)，可以用比重代替干物质含量来预测肉牛粪便中的有关主要肥料成分含量；用比重、电导率可以较准确地来预测粪便中总氮的含量；用比重、pH可以较准确地来预测粪便中总磷的含量；用电导率可以较准确地来预测粪便中总钾的含量；但3个理化指标均不能很好地预测粪中AN含量。
从上述试验样品中选择了200个具有一定代表性的粪样，使用傅立叶变换近红外光谱仪扫描了1000～2500nm范围内的光谱，利用偏最小二乘法(PLS)对分辨率为8cm~(-1)并经过一阶导数预处理的光谱进行分析，得出了预测TN、TP、TK和AN的最佳谱区和最佳主成分维数，利用以上参数建立了预测肉牛粪便中主要肥料成分含量的模型，并对该模型进行了验证，结果表明：近红外光谱法的测定值与化学分析法的测定值差异不显著(P＞0.05)，因此可以使用近红外光谱法代替实验室化学分析法对牛粪中各主要肥料成分含量进行测定。
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.
本研究在成功制备了SF_6渗透管的基础上，利用SF_6示踪法对肉牛在饲喂不同饲料类型、能量摄入水平、饲料精粗比情况下的甲烷排放量进行了测定，结果表明：SF_6示踪法可用来快速测定反刍动物的甲烷排放量；影响肉牛甲烷排放量因素的主次顺序依次为：饲料粗料类型＞能量摄入水平＞饲料精粗比；对肉牛饲喂紫花苜蓿和青贮玉米秸比饲喂稻草和干玉米秸时甲烷排放量要小，随着能量摄入水平的加大，肉牛的甲烷排放量也呈增加的趋势，日粮中粗饲料越多，则肉牛的甲烷排放量越大；肉牛日粮中各成分的日摄入量与甲烷排放量之间存在显著的相关关系，其中干物质摄入量和总能摄入量均可以很好地预测肉牛甲烷排放量。
本研究选用8个品种、220头不同肉牛于2002年10月～2004年1月期间进行饲养试验，采集具有代表性的粪样，研究了粪便的理化指标和主要肥料成分含量的相关关系，结果表明：粪便比重与干物质含量之间存在较好的正线性相关关系(R~2=0.80)，可以用比重代替干物质含量来预测肉牛粪便中的有关主要肥料成分含量；用比重、电导率可以较准确地来预测粪便中总氮的含量；用比重、pH可以较准确地来预测粪便中总磷的含量；用电导率可以较准确地来预测粪便中总钾的含量；但3个理化指标均不能很好地预测粪中AN含量。
从上述试验样品中选择了200个具有一定代表性的粪样，使用傅立叶变换近红外光谱仪扫描了1000～2500nm范围内的光谱，利用偏最小二乘法(PLS)对分辨率为8cm~(-1)并经过一阶导数预处理的光谱进行分析，得出了预测TN、TP、TK和AN的最佳谱区和最佳主成分维数，利用以上参数建立了预测肉牛粪便中主要肥料成分含量的模型，并对该模型进行了验证，结果表明：近红外光谱法的测定值与化学分析法的测定值差异不显著(P＞0.05)，因此可以使用近红外光谱法代替实验室化学分析法对牛粪中各主要肥料成分含量进行测定。
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.
引文
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