Prediction of the Ym factor for livestock from on-farm accessible data

Jaurena, Gustavo; Cantet, Juan Manuel; Arroquy, José Ignacio; Palladino, Rafael Alejandro; Wawrzkiewicz, Marisa; Colombatto, D.

doi:10.1016/j.livsci.2015.04.009

Cited by 18 publications

(24 citation statements)

References 28 publications

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“…What is certain is the positive relationship between plant fiber digestion and high acetic acid production sides as well as between plant fiber digestion and high methanogenesis yields in the rumen (IPCC, , Jaurena et al., ). Roughage sources can change Y m because of the fiber compositions (Jaurena et al., ; Kennedy & Charmley, ). While dietary lipid is also undeniably a strong single indicator of Y m , the change is not constant (e.g., when sources of the lipid are different; Patra, ).…”

Section: Discussionmentioning

confidence: 99%

“…Recently, Jaurena et al. () demonstrated that the categories of cattle (beef or dairy) and roughage (fresh forage, conserved forage, straw) are the primary factors affecting Y m values. Conventionally, it has been known that Y m values reduce as ME intake (Blaxter & Clapperton, ; Chaokaur et al., ), feed quality (starch content), energy content (IPCC, ; Johnson & Johnson, ; Kurihara et al., ), and fat content rise (Chuntrakort et al., ; Patra, ).…”

Section: Discussionmentioning

confidence: 99%

“…The extant Y m models from the published works (Blaxter & Clapperton, ; FAO, ; IPCC, , Jaurena et al., , Patra, ; Ramin & Huhtanen, ; Yan, Agnew, Gordon, & Porter, ) presented in Table were selected to predict the Y m of the beef cattle dataset and to guide the model development. The model selection criteria were based on the model's possible use at the national or farm level as well as the existence of independent variables in the dataset.…”

Section: Methodsmentioning

confidence: 99%

“…Three parameters were used as model evaluation tools, namely the mean square prediction error (MSPE; Tedeschi, ), the concordance correlation coefficient (CCC; Lin,), and observed versus predicted values (Kebreab et al., ). These statistical analyses are widely used to assess biological models (Ellis, Bannink, France, Kebreab, & Dijkstra, ; Jaurena et al., ; Tedeschi, ).…”

Section: Methodsmentioning

confidence: 99%

“…Overall, extant models for estimating enteric methane emissions can be classified into two principal groups: empirical (statistical) or dynamic mechanistic models (Kebreab, Johnson, Archibeque, Pape, & Wirth, ). In terms of the former, independent variables such as animal and diet as well as energy utilization efficiency have been selected to develop empirical Y m models (Blaxter & Clapperton, ; IPCC, , Jaurena et al., ). Regarding the latter, a Danish‐specific Y m model has been developed using a mathematical description of ruminal fermentation biochemistry (Nielsen et al., ).…”

Section: Introductionmentioning

confidence: 99%

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Development of methane conversion factor models for Zebu beef cattle fed low‐quality crop residues and by‐products in tropical regions

Kaewpila

Sommart

2016

Ecology and Evolution

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The enteric methane conversion factor (Y m) is an important country‐specific value for the provision of precise enteric methane emissions inventory reports. The objectives of this meta‐analysis were to develop and evaluate the empirical Y m models for the national level and the farm level for tropical developing countries according to the IPCC's categorization. We used datasets derived from 18 in vivo feeding experiments from 1999 to 2015 of Zebu beef cattle breeds fed low‐quality crop residues and by‐products. We found that the observed Y m value was 8.2% gross energy (GE) intake (~120 g methane emission head−1 day−1) and ranged from 4.8% to 13.7% GE intake. The IPCC default model (tier 2, Y m = 6.5% ± 1.0% GE intake) underestimated the Y m values by up to 26.1% compared with its refinement of 8.4% ± 0.4% GE intake for the national‐level estimate. Both the IPCC default model and the refined model performed worse in predicting Y m trends at the farm level (root mean square prediction error [MSPE] = 15.1%–23.1%, concordance correlation coefficient [CCC] = 0.16–0.18, R 2 = .32). Seven of the extant Y m models based on a linear regression approach also showed inaccurately estimated Y m values (root MSPE = 16.2%–36.0%, CCC = 0.02–0.27, R 2 < .37). However, one of the developed models, which related to the complexity of the energy use efficiencies of the diet consumed to Y m, showed adequate accuracy at the farm level (root MSPE = 9.1%, CCC = 0.75, R 2 = .67). Our results thus suggest a new Y m model and future challenges for estimating Zebu beef cattle production in tropical developing countries.

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Section: Discussionmentioning

confidence: 99%