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Volatilization

Volatilization

Volatilization gravimetry is an analytical technique that measures the mass lost due to the volatilization of the substance. This technique is used to estimate the amount of volatile material in a sample. To perform this method, heat a known amount of the sample to a high temperature in a crucible or other suitable vessel. The volatile substance in the sample evaporates, and the vapor is completely expelled from the crucible either by heating the sample or bubbling a stream of inert gas through...

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Predicting manure volatile solid output of lactating dairy cows.

J A D R N Appuhamy¹, L E Moraes², C Wagner-Riddle³

¹Department of Animal Science, Iowa State University, Ames 50011; Department of Animal Science, University of California, Davis 95616.

Journal of Dairy Science

|November 7, 2017

Summary

New models accurately estimate volatile solids (VS) and biodegradable VS (dVS) in dairy cow manure using farm data. This improves methane emission calculations from stored manure, aiding environmental management.

Keywords:

dairy cow manure prediction model volatile solid

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Area of Science:

Agricultural Science
Environmental Science
Animal Science

Background:

Methane emissions from livestock manure are influenced by volatile solids (VS), comprising biodegradable (dVS) and nonbiodegradable fractions.
Current Intergovernmental Panel on Climate Change (IPCC) Tier 2 guidelines use VS for methane estimation, but only dVS generates methane.
Accurate estimation of dVS is crucial for precise methane emission calculations from dairy manure.

Purpose of the Study:

To develop and validate mathematical models for estimating VS and dVS outputs from lactating dairy cows.
To compare the predictive accuracy of new models against the existing IPCC Tier 2 methodology.
To provide practical tools for dairy farms to improve methane emission estimations.

Main Methods:

Developed empirical models using 857 VS and dVS measurements from 43 metabolic trials at USDA.
Utilized predictor variables such as organic matter intake, dietary crude protein, and neutral detergent fiber.
Validated models with an independent dataset of 209 VS and dVS measurements from UC Davis trials.

Main Results:

New models incorporating organic matter intake and dietary components accurately predicted VS (RMSPE 12.5%) and dVS (RMSPE 12.7%).
The IPCC Tier 2 model showed a higher RMSPE (13.7%) and overpredicted VS.
Models utilizing dry matter intake (DMI) predicted by the Cornell Net Carbohydrate and Protein System also showed good performance for VS and dVS.

Conclusions:

Empirical models were developed to accurately predict VS and dVS in dairy cows using routinely available farm data.
These models offer a more precise method for estimating methane emissions from stored manure compared to current IPCC guidelines.
The findings support improved environmental management strategies in dairy farming through better emission quantification.