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Pyrolisis-MS and FT-IR analysis of fresh and decomposed dairy manure

机译:新鲜和分解乳牛粪的热解-MS和FT-IR分析

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The ability to predict manure nitrogen mineralization is essential for optimizing crop growth while preventing N losses to the environment. However, estimating mineralizable manure N is problematic because of the wide variety of organic manure N forms, as well as the lack of a rapid standardized method. Fourier-transformed infrared spectroscopy (FT-IR) is a promising technology, since it can detect the absorbance of proteins and primary amines, in addition to being instantaneous and non-destructive. Likewise, analytical pyrolysis-mass spectrometry (Py-GC/MS) has been used to study lignin and protein composition of forages. We carried out a 10-week laboratory incubation of manure-amended soil in order to test the sensitivity of FT-IR and Py-GC/MS to detect changes in manure during decomposition in soil. Four different dairy or beef manures were included. The manures (0.15 mg manure-N g~(-1) soil) were placed inside mesh bags during the soil incubation to allow for the recovery and analysis of fresh as well as decomposed manure. Infrared spectroscopy of the fresh and incubated manures showed that this technique is sensitive to changes in manure organic N after soil application. Bands associated with primary amines decreased during the incubation, while bands associated with proteins increased during manure decomposition. Bands associated with fatty acids tended to decrease during the incubation, possibly due to utilization as C sources. The spectroscopic data also showed that lignin-specific signals increase during manure decomposition, suggesting that the relative amount of lignin in manure increases as it decomposes in soil. The changes in peak areas of pyrolyzates were related to changes in manure constituents during decomposition. The Py-GC/MS data showed qualitative changes in manure lignin during decomposition. The relative amounts of nitrogen containing pyrolyzates, such as phenylacetonitrile and methylindole, changed during the decomposition, but the changes were not consistent across manures. In summary, this experiment showed that the use of manure bags is valuable in discerning between the N cycling dynamics of manure and soil, and that infrared spectroscopy, as well as Py-GC/MS show potential as analytical tools to study manure decomposition in soil.
机译:预测肥料氮矿化的能力对于优化作物生长同时防止氮素向环境的损失至关重要。但是,由于有机肥料N形式的多样性以及缺乏快速标准化的方法,估计可矿化肥料的N是有问题的。傅里叶变换红外光谱(FT-IR)是一项很有前途的技术,因为它不仅可以即时且无损检测到蛋白质和伯胺的吸收。同样,分析热解质谱法(Py-GC / MS)已用于研究饲料中木质素和蛋白质的组成。为了测试FT-IR和Py-GC / MS对在土壤中分解过程中粪便变化的敏感性,我们对粪便改良过的土壤进行了为期10周的实验室培养。包括四种不同的乳制品或牛肉肥料。在土壤培养过程中,将肥料(0.15 mg肥料-N g〜(-1)肥料)放在网袋内,以回收和分析新鲜以及分解后的肥料。新鲜和温育肥料的红外光谱显示,该技术对土壤施用后肥料中有机氮的变化敏感。在孵化过程中,与伯胺相关的条带减少,而在粪便分解过程中,与蛋白质相关的条带增加。在孵育过程中,与脂肪酸相关的条带倾向于减少,这可能是由于用作C源。光谱数据还表明,木质素特异性信号在粪肥分解过程中增加,表明粪便中木质素的相对量随着其在土壤中的分解而增加。热解产物峰面积的变化与分解过程中肥料成分的变化有关。 Py-GC / MS数据显示分解过程中粪便木质素的质变。分解过程中含氮的热解产物(如苯乙腈和甲基吲哚)的相对量发生了变化,但不同肥料之间的变化不一致。总而言之,该实验表明,使用粪便袋对于区分粪便和土壤的N循环动力学非常有价值,并且红外光谱法和Py-GC / MS都显示出了研究土壤中粪便分解的潜在分析工具的潜力。 。

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