Improved modelling of manure mineralisation through new methods for characterising carbohydrate pools

Daud, Mohammad Feizal, Parsons, David, Malau-Aduli, Aduli, and Lane, Peter (2010) Improved modelling of manure mineralisation through new methods for characterising carbohydrate pools. In: Proceedings of the 15th Australian Agronomy Conference. From: 15th Australian Agronomy Conference: Food Security from Sustainable Agriculture, 15-18 November 2010, Lincoln, New Zealand.

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Particularly in tropical low-input systems, manure plays an important role in soil fertility management, where effective use of nutrient sources is crucial to maintaining productivity. It is important to be able to understand and predict the complex mineralisation behaviour of manure in soil. In this study we developed an improved method to characterise manure, focusing on the composition of carbohydrate pools, including soluble, fibre, and lignin. A selection of laboratory analyses was used to determine the carbon to nitrogen ratios of carbohydrate pools for a range of temperate and tropical manures. The method was generally able to characterise the carbohydrate pools in manure samples and their carbon to nitrogen ratios; however calculating the NFC fraction by difference sometimes led to negative values and thus direct measurement of the non-fibre (soluble) carbohydrate components may be preferable. The generally greater C:N ratios for the fibre fraction compared to the lignin fraction support the hypothesis that overall C:N ratio is not a good indicator of manure quality.

Item ID: 55051
Item Type: Conference Item (Research - E1)
Keywords: detergent fibre method, APSIM, simulation models, organic matter
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Date Deposited: 21 Aug 2018 03:50
FoR Codes: 07 AGRICULTURAL AND VETERINARY SCIENCES > 0701 Agriculture, Land and Farm Management > 070105 Agricultural Systems Analysis and Modelling @ 100%
SEO Codes: 83 ANIMAL PRODUCTION AND ANIMAL PRIMARY PRODUCTS > 8398 Environmentally Sustainable Animal Production > 839804 Management of Solid Waste from Animal Production @ 100%
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