Selection of particle characteristics to distinguish amongst potential sources of particulate matter in poultry and pigs.

M. Cambra-Lopez; T. Hermosilla; A.J.A. Aarnink; N. Ogink

Selection of particle characteristics to distinguish amongst potential sources of particulate matter in poultry and pigs.

M. Cambra-Lopez, T. Hermosilla, A.J.A. Aarnink, N. Ogink

Research output: Contribution to conference › Conference paper › Academic

Abstract

The knowledge on the contribution of individual sources to particulate matter (PM) in different size fractions is essential to improve PM reduction from livestock houses. We investigated which input data (particle chemical, morphological or combined characteristics) were best to distinguish amongst specific potential sources of PM. We used a cross-validation procedure with classification rules based on decision trees and analyzed misclassification errors. The PM from two livestock species (poultry and pigs), and in two different fractions (fine and coarse) was studied. A total of 618 particles were analyzed from poultry houses for fine, and 805 for coarse PM. A total of 317 particles were analyzed from pig houses for fine, and 337 for coarse PM. Results showed the selection of the best input data varies depending on the sources, which depend on livestock species.

Original language	English
Publication status	Published - 2011
Event	ASABE 2011, Annual International Meeting, St. Joseph, USA - Duration: 7 Aug 2011 → 10 Aug 2011

Conference

Conference	ASABE 2011, Annual International Meeting, St. Joseph, USA
Period	7/08/11 → 10/08/11

Keywords

Atmospheric pollution
Dust
Image analysis
Livestock housing
SEM-EDX

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@conference{d799f0b49c16427ba6d797200e278ca6,

title = "Selection of particle characteristics to distinguish amongst potential sources of particulate matter in poultry and pigs.",

abstract = "The knowledge on the contribution of individual sources to particulate matter (PM) in different size fractions is essential to improve PM reduction from livestock houses. We investigated which input data (particle chemical, morphological or combined characteristics) were best to distinguish amongst specific potential sources of PM. We used a cross-validation procedure with classification rules based on decision trees and analyzed misclassification errors. The PM from two livestock species (poultry and pigs), and in two different fractions (fine and coarse) was studied. A total of 618 particles were analyzed from poultry houses for fine, and 805 for coarse PM. A total of 317 particles were analyzed from pig houses for fine, and 337 for coarse PM. Results showed the selection of the best input data varies depending on the sources, which depend on livestock species.",

keywords = "Atmospheric pollution, Dust, Image analysis, Livestock housing, SEM-EDX",

author = "M. Cambra-Lopez and T. Hermosilla and A.J.A. Aarnink and N. Ogink",

year = "2011",

language = "English",

note = "ASABE 2011, Annual International Meeting, St. Joseph, USA ; Conference date: 07-08-2011 Through 10-08-2011",

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TY - CONF

T1 - Selection of particle characteristics to distinguish amongst potential sources of particulate matter in poultry and pigs.

AU - Cambra-Lopez, M.

AU - Hermosilla, T.

AU - Aarnink, A.J.A.

AU - Ogink, N.

PY - 2011

Y1 - 2011

N2 - The knowledge on the contribution of individual sources to particulate matter (PM) in different size fractions is essential to improve PM reduction from livestock houses. We investigated which input data (particle chemical, morphological or combined characteristics) were best to distinguish amongst specific potential sources of PM. We used a cross-validation procedure with classification rules based on decision trees and analyzed misclassification errors. The PM from two livestock species (poultry and pigs), and in two different fractions (fine and coarse) was studied. A total of 618 particles were analyzed from poultry houses for fine, and 805 for coarse PM. A total of 317 particles were analyzed from pig houses for fine, and 337 for coarse PM. Results showed the selection of the best input data varies depending on the sources, which depend on livestock species.

AB - The knowledge on the contribution of individual sources to particulate matter (PM) in different size fractions is essential to improve PM reduction from livestock houses. We investigated which input data (particle chemical, morphological or combined characteristics) were best to distinguish amongst specific potential sources of PM. We used a cross-validation procedure with classification rules based on decision trees and analyzed misclassification errors. The PM from two livestock species (poultry and pigs), and in two different fractions (fine and coarse) was studied. A total of 618 particles were analyzed from poultry houses for fine, and 805 for coarse PM. A total of 317 particles were analyzed from pig houses for fine, and 337 for coarse PM. Results showed the selection of the best input data varies depending on the sources, which depend on livestock species.

KW - Atmospheric pollution

KW - Dust

KW - Image analysis

KW - Livestock housing

KW - SEM-EDX

M3 - Conference paper

T2 - ASABE 2011, Annual International Meeting, St. Joseph, USA

Y2 - 7 August 2011 through 10 August 2011

ER -

Selection of particle characteristics to distinguish amongst potential sources of particulate matter in poultry and pigs.

Abstract

Conference

Keywords

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