Section 20: Correlations among methods - Revision history

Bgolden: Bgolden moved page Correlations among methods to Section 20: Correlations among methods without leaving a redirect

2025-04-25T14:08:46Z

Bgolden moved page Correlations among methods to Section 20: Correlations among methods without leaving a redirect

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Bgolden at 13:50, 25 April 2025

2025-04-25T13:50:48Z

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			<b>NOTE: This version of Section 20 has been approved by the working group's Chair. Please be aware that further revisions may occur before final review and approval by the Board and ICAR members per the [[Approval of Page Process]].
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	Table 4 shows correlations between the respiratory chamber method as the gold standard to measure CH<sub>4</sub> emission from cows and other methods from Garnsworthy et al. (2019)<ref name=":0">Garnsworthy, P.C. Difford, G.F. Bell, M.J. Bayat, A.R. Huhtanen, P. Kuhla, B. Lassen, J. Peiren, N. Pszczola, M; Sorg, D. Visker, M.H., and Yan, T. 2019 Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle. Animals 9:837, 12p.</ref>.		Table 4 shows correlations between the respiratory chamber method as the gold standard to measure CH<sub>4</sub> emission from cows and other methods from Garnsworthy et al. (2019)<ref name=":0">Garnsworthy, P.C. Difford, G.F. Bell, M.J. Bayat, A.R. Huhtanen, P. Kuhla, B. Lassen, J. Peiren, N. Pszczola, M; Sorg, D. Visker, M.H., and Yan, T. 2019 Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle. Animals 9:837, 12p.</ref>.
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Aashish at 08:12, 16 July 2024

2024-07-16T08:12:29Z

← Older revision		Revision as of 08:12, 16 July 2024
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	Table 4 shows correlations between the respiratory chamber method as the gold standard to measure CH<sub>4</sub> emission from cows and other methods from Garnsworthy et al. (2019)<ref name=":0">Garnsworthy, P.C. Difford, G.F. Bell, M.J. Bayat, A.R. Huhtanen, P. Kuhla, B. Lassen, J. Peiren, N. Pszczola, M; Sorg, D. Visker, M.H., and Yan, T. 2019 Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle. Animals 9:837, 12p.</ref>.		Table 4 shows correlations between the respiratory chamber method as the gold standard to measure CH<sub>4</sub> emission from cows and other methods from Garnsworthy et al. (2019)<ref name=":0">Garnsworthy, P.C. Difford, G.F. Bell, M.J. Bayat, A.R. Huhtanen, P. Kuhla, B. Lassen, J. Peiren, N. Pszczola, M; Sorg, D. Visker, M.H., and Yan, T. 2019 Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle. Animals 9:837, 12p.</ref>.
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Aashish at 08:12, 16 July 2024

2024-07-16T08:12:14Z

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	Table 4 shows correlations between the respiratory chamber method as the gold standard to measure CH<sub>4</sub> emission from cows and other methods from Garnsworthy et al. (2019)<ref name=":0">Garnsworthy, P.C. Difford, G.F. Bell, M.J. Bayat, A.R. Huhtanen, P. Kuhla, B. Lassen, J. Peiren, N. Pszczola, M; Sorg, D. Visker, M.H., and Yan, T. 2019 Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle. Animals 9:837, 12p.</ref>.		Table 4 shows correlations between the respiratory chamber method as the gold standard to measure CH<sub>4</sub> emission from cows and other methods from Garnsworthy et al. (2019)<ref name=":0">Garnsworthy, P.C. Difford, G.F. Bell, M.J. Bayat, A.R. Huhtanen, P. Kuhla, B. Lassen, J. Peiren, N. Pszczola, M; Sorg, D. Visker, M.H., and Yan, T. 2019 Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle. Animals 9:837, 12p.</ref>.
	{\| class="wikitable"		{\| class="wikitable"
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			! colspan="3" \| ''Table 4. Correlations between CH<sub>4</sub> measuring methods. Data were taken from Garnsworthy et al. (2019)<ref name=":0" />.''
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	\|}~~Table 4. Correlations between CH~~<~~sub>4</sub> measuring methods. Data were taken from Garnsworthy et al. (2019)<ref name=":0"~~ />.		\|}</center>

	In method comparison studies, simultaneous repeated measures per cow with two or more methods are required in order to assess systematic differences between methods (means) and random differences (precision) and correlation between methods free of residual error. Furthermore, adequately short time differences between repeated measures per subject are needed to ensure the underlying biology of the cow has not changed. Not all methods can be recorded simultaneously and CH<sub>4</sub> emission of cows’ changes both within day and over the lactation period. In such instances either cross-over designs or matched pair repeated measures designs are needed. Members of METHAGENE WG2 provided data from studies in which two or more methods had been used to measure CH<sub>4</sub> output (g/day) by individual dairy cows. Methods were applied to each cow either concurrently or consecutively within a short timeframe.		In method comparison studies, simultaneous repeated measures per cow with two or more methods are required in order to assess systematic differences between methods (means) and random differences (precision) and correlation between methods free of residual error. Furthermore, adequately short time differences between repeated measures per subject are needed to ensure the underlying biology of the cow has not changed. Not all methods can be recorded simultaneously and CH<sub>4</sub> emission of cows’ changes both within day and over the lactation period. In such instances either cross-over designs or matched pair repeated measures designs are needed. Members of METHAGENE WG2 provided data from studies in which two or more methods had been used to measure CH<sub>4</sub> output (g/day) by individual dairy cows. Methods were applied to each cow either concurrently or consecutively within a short timeframe.

Lbenzoni at 14:11, 6 March 2024

2024-03-06T14:11:26Z

← Older revision		Revision as of 14:11, 6 March 2024
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	Table 4 shows correlations between the respiratory chamber method as the gold standard to measure ~~CH4~~ emission from cows and other methods from Garnsworthy et al. (2019).		Table 4 shows correlations between the respiratory chamber method as the gold standard to measure CH<sub>4</sub> emission from cows and other methods from Garnsworthy et al. (2019)<ref name=":0">Garnsworthy, P.C. Difford, G.F. Bell, M.J. Bayat, A.R. Huhtanen, P. Kuhla, B. Lassen, J. Peiren, N. Pszczola, M; Sorg, D. Visker, M.H., and Yan, T. 2019 Comparison of Methods to Measure Methane for Use in Genetic Evaluation of Dairy Cattle. Animals 9:837, 12p.</ref>.
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	\|}Table 4. Correlations between ~~Ch4~~ measuring methods. Data were taken from Garnsworthy et al. (2019).		\|}Table 4. Correlations between CH<sub>4</sub> measuring methods. Data were taken from Garnsworthy et al. (2019)<ref name=":0" />.

	In method comparison studies, simultaneous repeated measures per cow with two or more methods are required in order to assess systematic differences between methods (means) and random differences (precision) and correlation between methods free of residual error. Furthermore, adequately short time differences between repeated measures per subject are needed to ensure the underlying biology of the cow has not changed. Not all methods can be recorded simultaneously and ~~CH4~~ emission of cows’ changes both within day and over the lactation period. In such instances either cross-over designs or matched pair repeated measures designs are needed. Members of METHAGENE WG2 provided data from studies in which two or more methods had been used to measure ~~CH4~~ output (g/day) by individual dairy cows. Methods were applied to each cow either concurrently or consecutively within a short timeframe.		In method comparison studies, simultaneous repeated measures per cow with two or more methods are required in order to assess systematic differences between methods (means) and random differences (precision) and correlation between methods free of residual error. Furthermore, adequately short time differences between repeated measures per subject are needed to ensure the underlying biology of the cow has not changed. Not all methods can be recorded simultaneously and CH<sub>4</sub> emission of cows’ changes both within day and over the lactation period. In such instances either cross-over designs or matched pair repeated measures designs are needed. Members of METHAGENE WG2 provided data from studies in which two or more methods had been used to measure CH<sub>4</sub> output (g/day) by individual dairy cows. Methods were applied to each cow either concurrently or consecutively within a short timeframe.

	Seven main methods were represented: respiration chambers; SF6; GreenFeed; LMD; and three breath-sampling systems based on different gas analysers. Gas analysers incorporated different technologies to measure ~~CH4~~, which were NDIR (e.g. Guardian Plus, Edinburgh Instruments, Edinburgh, UK), FTIR (e.g. Gasmet 4030, Gasmet Technologies Oy, Helsinki, Finland), or PAIR (e.g. F10, Gasera Ltd, Turku, Finland). In the contributing studies, NDIR and FTIR were used in automatic milking stations, and PAIR was used in concentrate feeding stations. One NDIR study and all FTIR and PAIR studies used ~~CO2~~ as a tracer gas, with daily ~~CO2~~ output calculated either from milk yield, live weight and days pregnant or from metabolisable energy intake. Two NDIR studies were based on ~~CH4~~ concentration in eructation peaks rather than mean ~~CH4~~ concentration, so were treated as separate methods. By separating NDIR studies, a total of 8 distinct methods were available giving a matrix of 28 potential combinations for comparisons. Data were available for 13 method combinations (Garnsworthy et al., 2019).		Seven main methods were represented: respiration chambers; SF6; GreenFeed; LMD; and three breath-sampling systems based on different gas analysers. Gas analysers incorporated different technologies to measure CH<sub>4</sub>, which were NDIR (e.g. Guardian Plus, Edinburgh Instruments, Edinburgh, UK), FTIR (e.g. Gasmet 4030, Gasmet Technologies Oy, Helsinki, Finland), or PAIR (e.g. F10, Gasera Ltd, Turku, Finland). In the contributing studies, NDIR and FTIR were used in automatic milking stations, and PAIR was used in concentrate feeding stations. One NDIR study and all FTIR and PAIR studies used CO<sub>2</sub> as a tracer gas, with daily CO<sub>2</sub> output calculated either from milk yield, live weight and days pregnant or from metabolisable energy intake. Two NDIR studies were based on CH<sub>4</sub> concentration in eructation peaks rather than mean CH<sub>4</sub> concentration, so were treated as separate methods. By separating NDIR studies, a total of 8 distinct methods were available giving a matrix of 28 potential combinations for comparisons. Data were available for 13 method combinations (Garnsworthy et al., 2019<ref name=":0" />).

	Method comparisons were conducted using bivariate models (repeatability animal models) to obtain correlations between ‘true values’, also known as repeated measures correlations or individual level correlations (Bakdash and Marusich, 2017). Variance components including between cow variation and within cow variation (precision) and means (accuracy) were used in the calculation of between cow coefficient of variation (CV, %) and total CV and repeatability. Where single measurements were available for each method Pearson’s correlation was reported and where repeated measures per subject were available repeated measures correlation was reported.		Method comparisons were conducted using bivariate models (repeatability animal models) to obtain correlations between ‘true values’, also known as repeated measures correlations or individual level correlations (Bakdash and Marusich, 2017<ref>Bakdash, J.Z., and Marusich, L.R. 2017. Repeated measures correlation. Front. Psychol. 8:1–13. doi:10.3389/fpsyg.2017.00456.</ref>). Variance components including between cow variation and within cow variation (precision) and means (accuracy) were used in the calculation of between cow coefficient of variation (CV, %) and total CV and repeatability. Where single measurements were available for each method Pearson’s correlation was reported and where repeated measures per subject were available repeated measures correlation was reported.

	Respiration chambers were the most precise method, as can be seen by the smaller between cow CV% and total CV compared to alternative methods, and respiration chambers are by definition the most accurate. All methods tested showed high correlations with respiration chambers but none of the correlations exceeded 0.90. This is in part due to the increased imprecision of alternative methods, as even the most accurate and precise method will compare poorly to a less precise method. These correlations are also likely to be underestimated because none of the methods could be recorded simultaneously with respiration chambers and had to be recorded in cross over designs. Consequently, the true value for each cow may have changed due to changes in the underlying biology of the cow over time between measurements. Comparisons among alternative methods generally had lower correlations than comparisons with respiration chambers, despite having relatively higher numbers of animals and in most cases simultaneous or near simultaneous repeated measures per cow per method due to the increased variability and imprecision of alternative methods as is seen by the increased CVs or due to the possibility that different aspects of ~~CH4~~ emission are captured using different methods.		Respiration chambers were the most precise method, as can be seen by the smaller between cow CV% and total CV compared to alternative methods, and respiration chambers are by definition the most accurate. All methods tested showed high correlations with respiration chambers but none of the correlations exceeded 0.90. This is in part due to the increased imprecision of alternative methods, as even the most accurate and precise method will compare poorly to a less precise method. These correlations are also likely to be underestimated because none of the methods could be recorded simultaneously with respiration chambers and had to be recorded in cross over designs. Consequently, the true value for each cow may have changed due to changes in the underlying biology of the cow over time between measurements. Comparisons among alternative methods generally had lower correlations than comparisons with respiration chambers, despite having relatively higher numbers of animals and in most cases simultaneous or near simultaneous repeated measures per cow per method due to the increased variability and imprecision of alternative methods as is seen by the increased CVs or due to the possibility that different aspects of CH<sub>4</sub> emission are captured using different methods.

	For the methods with repeated measures per cow the two mass flux methods, SF6 and GreenFeed, had the highest repeated measures correlations (0.87 ± 0.08 and 0.81 ± 0.10) which outperformed the concentration based NDIR method using ~~CO2~~ tracer gas. Of the two concentration methods evaluated against respiration chambers using single measurements, NDIR Peaks had a higher correlation (0.89 ± 0.07) than the PAIR ~~CO2~~ tracer gas (0.80 ± 0.10). The study of Hristov et al. (2016) comparing SF6 and GreenFeed reported a low Pearson correlation of 0.40, despite having a large number of animals with repeated measures per method, the authors appear not to have estimated a repeated measures correlation, which could be larger. Estimating a repeated measures correlation between these two mass flux methods is a priority as it would clarify the inexplicable disagreement between two methods which both correlate highly with the gold standard method. With the exception of the aforementioned study, the imprecision was low in the mass flux measure comparisons as compared to the concentration-based methods.		For the methods with repeated measures per cow the two mass flux methods, SF6 and GreenFeed, had the highest repeated measures correlations (0.87 ± 0.08 and 0.81 ± 0.10) which outperformed the concentration based NDIR method using CO<sub>2</sub> tracer gas. Of the two concentration methods evaluated against respiration chambers using single measurements, NDIR Peaks had a higher correlation (0.89 ± 0.07) than the PAIR CO<sub>2</sub> tracer gas (0.80 ± 0.10). The study of Hristov et al. (2016)<ref>Hristov, A.N., O,h J., Giallongo, F., Frederick, T., Harper, M.T., Weeks, H., Branco, F., Price, W.J., Moate, P.J., Deighto,n M.H., Williams, S.R.O., Kindermann, M., and Duval, S. 2016. Short communication: Comparison of the GreenFeed system with the sulfur hexafluoride tracer technique for measuring enteric methane emissions from dairy cows. J. Dairy Sci. 5461–5465. doi:10.3168/jds.2016-10897.</ref> comparing SF6 and GreenFeed reported a low Pearson correlation of 0.40, despite having a large number of animals with repeated measures per method, the authors appear not to have estimated a repeated measures correlation, which could be larger. Estimating a repeated measures correlation between these two mass flux methods is a priority as it would clarify the inexplicable disagreement between two methods which both correlate highly with the gold standard method. With the exception of the aforementioned study, the imprecision was low in the mass flux measure comparisons as compared to the concentration-based methods.

	Two of the sniffer methods evaluated, FTIR ~~CO2t1~~ and NDIR ~~CO2t1~~, correlated close to unity (0.97), most likely due to the shared prediction equation for ~~CO2~~ tracer gas. Nevertheless, all correlations derived from actual data were positive. This suggests that combination of datasets obtained with different methods is a realistic proposition for genetic studies. Calculation of adjustment or weighting factors for bias, accuracy and precision would improve the value of combined datasets.		Two of the sniffer methods evaluated, FTIR CO<sub>2</sub>t1 and NDIR CO<sub>2</sub>t1, correlated close to unity (0.97), most likely due to the shared prediction equation for CO<sub>2</sub> tracer gas. Nevertheless, all correlations derived from actual data were positive. This suggests that combination of datasets obtained with different methods is a realistic proposition for genetic studies. Calculation of adjustment or weighting factors for bias, accuracy and precision would improve the value of combined datasets.

Lbenzoni: Created page with "Table 4 shows correlations between the respiratory chamber method as the gold standard to measure CH4 emission from cows and other methods from Garnsworthy et al. (2019). {| class="wikitable" |+ !Method !Correlation !S.E. |- |Respiratory chamber - SF6 |0.87 | - 0.08 |- |Respiratory chamber - Greenfeed |0.81 | - 0.1 |- |Respiratory chamber - NDIR | - 0.07 |0.88 |- |Respiratory chamber - NDIR peak |0.72 | - 0.11 |- |Respiratory chamber - PAIR | - 0.08 |0.7 |- |SF6 - Greenf..."

2024-02-14T20:42:36Z

Created page with "Table 4 shows correlations between the respiratory chamber method as the gold standard to measure CH4 emission from cows and other methods from Garnsworthy et al. (2019). {| class="wikitable" |+ !Method !Correlation !S.E. |- |Respiratory chamber - SF6 |0.87 | - 0.08 |- |Respiratory chamber - Greenfeed |0.81 | - 0.1 |- |Respiratory chamber - NDIR | - 0.07 |0.88 |- |Respiratory chamber - NDIR peak |0.72 | - 0.11 |- |Respiratory chamber - PAIR | - 0.08 |0.7 |- |SF6 - Greenf..."

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Table 4 shows correlations between the respiratory chamber method as the gold standard to measure CH4 emission from cows and other methods from Garnsworthy et al. (2019).
{| class="wikitable"
|+
!Method
!Correlation
!S.E.
|-
|Respiratory chamber - SF6
|0.87
| - 0.08
|-
|Respiratory chamber - Greenfeed
|0.81
| - 0.1
|-
|Respiratory chamber - NDIR
| - 0.07
|0.88
|-
|Respiratory chamber - NDIR peak
|0.72
| - 0.11
|-
|Respiratory chamber - PAIR
| - 0.08
|0.7
|-
|SF6 - Greenfeed
|0.4
| - 0.8
|-
|LMD - Greenfeed
|0.77
| - 0.23
|-
|NDIR - Greenfeed
|0.64
| - 0.18
|-
|NDIR - LMD
|0.6
| - 0.11
|-
|FTIR - LMD
|0.57
| - 0.25
|-
|NDIR - NDIR peaks
|0.58
| - 0.15
|-
|FTIR - NDIR
|0.97
| - 0.02
|-
|FTIR - NDIR
|0.53
| - 0.17
|}Table 4. Correlations between Ch4 measuring methods. Data were taken from Garnsworthy et al. (2019).

In method comparison studies, simultaneous repeated measures per cow with two or more methods are required in order to assess systematic differences between methods (means) and random differences (precision) and correlation between methods free of residual error. Furthermore, adequately short time differences between repeated measures per subject are needed to ensure the underlying biology of the cow has not changed. Not all methods can be recorded simultaneously and CH4 emission of cows’ changes both within day and over the lactation period. In such instances either cross-over designs or matched pair repeated measures designs are needed. Members of METHAGENE WG2 provided data from studies in which two or more methods had been used to measure CH4 output (g/day) by individual dairy cows. Methods were applied to each cow either concurrently or consecutively within a short timeframe.

Seven main methods were represented: respiration chambers; SF6; GreenFeed; LMD; and three breath-sampling systems based on different gas analysers. Gas analysers incorporated different technologies to measure CH4, which were NDIR (e.g. Guardian Plus, Edinburgh Instruments, Edinburgh, UK), FTIR (e.g. Gasmet 4030, Gasmet Technologies Oy, Helsinki, Finland), or PAIR (e.g. F10, Gasera Ltd, Turku, Finland). In the contributing studies, NDIR and FTIR were used in automatic milking stations, and PAIR was used in concentrate feeding stations. One NDIR study and all FTIR and PAIR studies used CO2 as a tracer gas, with daily CO2 output calculated either from milk yield, live weight and days pregnant or from metabolisable energy intake. Two NDIR studies were based on CH4 concentration in eructation peaks rather than mean CH4 concentration, so were treated as separate methods. By separating NDIR studies, a total of 8 distinct methods were available giving a matrix of 28 potential combinations for comparisons. Data were available for 13 method combinations (Garnsworthy et al., 2019).

Method comparisons were conducted using bivariate models (repeatability animal models) to obtain correlations between ‘true values’, also known as repeated measures correlations or individual level correlations (Bakdash and Marusich, 2017). Variance components including between cow variation and within cow variation (precision) and means (accuracy) were used in the calculation of between cow coefficient of variation (CV, %) and total CV and repeatability. Where single measurements were available for each method Pearson’s correlation was reported and where repeated measures per subject were available repeated measures correlation was reported.

Respiration chambers were the most precise method, as can be seen by the smaller between cow CV% and total CV compared to alternative methods, and respiration chambers are by definition the most accurate. All methods tested showed high correlations with respiration chambers but none of the correlations exceeded 0.90. This is in part due to the increased imprecision of alternative methods, as even the most accurate and precise method will compare poorly to a less precise method. These correlations are also likely to be underestimated because none of the methods could be recorded simultaneously with respiration chambers and had to be recorded in cross over designs. Consequently, the true value for each cow may have changed due to changes in the underlying biology of the cow over time between measurements. Comparisons among alternative methods generally had lower correlations than comparisons with respiration chambers, despite having relatively higher numbers of animals and in most cases simultaneous or near simultaneous repeated measures per cow per method due to the increased variability and imprecision of alternative methods as is seen by the increased CVs or due to the possibility that different aspects of CH4 emission are captured using different methods.

For the methods with repeated measures per cow the two mass flux methods, SF6 and GreenFeed, had the highest repeated measures correlations (0.87 ± 0.08 and 0.81 ± 0.10) which outperformed the concentration based NDIR method using CO2 tracer gas. Of the two concentration methods evaluated against respiration chambers using single measurements, NDIR Peaks had a higher correlation (0.89 ± 0.07) than the PAIR CO2 tracer gas (0.80 ± 0.10). The study of Hristov et al. (2016) comparing SF6 and GreenFeed reported a low Pearson correlation of 0.40, despite having a large number of animals with repeated measures per method, the authors appear not to have estimated a repeated measures correlation, which could be larger. Estimating a repeated measures correlation between these two mass flux methods is a priority as it would clarify the inexplicable disagreement between two methods which both correlate highly with the gold standard method. With the exception of the aforementioned study, the imprecision was low in the mass flux measure comparisons as compared to the concentration-based methods.

Two of the sniffer methods evaluated, FTIR CO2t1 and NDIR CO2t1, correlated close to unity (0.97), most likely due to the shared prediction equation for CO2 tracer gas. Nevertheless, all correlations derived from actual data were positive. This suggests that combination of datasets obtained with different methods is a realistic proposition for genetic studies. Calculation of adjustment or weighting factors for bias, accuracy and precision would improve the value of combined datasets.