Mathematical modeling in animal agriculture can be applied at various levels including at the tissue, organ, animal, farm, regional and global levels. The purposes of this research were i) to evaluate models used to estimate volatile fatty acid (VFA) and methane (CH4) production and assess their impact on regional enteric CH4 inventory, and ii) to develop a process-based, whole-farm model to estimate net farm GHG emissions. In the first study, four VFA stoichiometric models were evaluated for their prediction accuracy of rumen VFA and enteric CH4 production. Comparison of measured and model predicted values demonstrated that predictive capacity of the VFA models varied with respect to the type of VFA in rumen fluid which impacted estimated enteric CH4 production. Moving to a larger scale assessment, we examined the enteric CH4 inventory from Manitoba beef cattle (from 1990 to 2008) using two mechanistic rumen models that incorporate VFA stoichiometric models: COWPOLL and MOLLY, and two empirical models: Intergovernmental Panel on Climate Change (IPCC) Tier 2 and a nonlinear equation (Ellis). The estimated absolute enteric CH4 production varied among models (7 to 63%) indicating that estimates of GHG inventory depend on model selection. This is an important consideration if the values are to be used for management and/or policy-related decisions. Development of models at the individual farm component level (animal, soil, crop) does not accurately reflect net GHG emissions generated from the whole production system. We developed a process-based, whole-farm model (Integrated Components Model, ICM), using the existing farm component models COWPOLL, manure-DNDC and some aspects of IPCC to integrate farm components and their associated GHG emissions. Estimates of total farm GHG emissions and their relative contribution using the ICM were comparable to estimates using two other whole-farm models (Integrated Farm System Model and Holos model). Variation was observed among models both in estimating whole-farm GHG emissions and the relative contribution of the different sources in the production system. Overall, whole-farm models are required to explore management options that will mitigate GHG emissions and promote best management practices. However, for full assessment of the production system, other benefits of the system (e.g., carbon sequestration, ecosystem services), which are not part of current whole-farm models, must be considered.

Mathematical modeling in animal agriculture can be applied at various levels including at the tissue, organ, animal, farm, regional and global levels. The purposes of this research were i) to evaluate models used to estimate volatile fatty acid (VFA) and methane (CH4) production and assess their impact on regional enteric CH4 inventory, and ii) to develop a process-based, whole-farm model to estimate net farm GHG emissions. In the first study, four VFA stoichiometric models were evaluated for their prediction accuracy of rumen VFA and enteric CH4 production. Comparison of measured and model predicted values demonstrated that predictive capacity of the VFA models varied with respect to the type of VFA in rumen fluid which impacted estimated enteric CH4 production. Moving to a larger scale assessment, we examined the enteric CH4 inventory from Manitoba beef cattle (from 1990 to 2008) using two mechanistic rumen models that incorporate VFA stoichiometric models: COWPOLL and MOLLY, and two empirical models: Intergovernmental Panel on Climate Change (IPCC) Tier 2 and a nonlinear equation (Ellis). The estimated absolute enteric CH4 production varied among models (7 to 63%) indicating that estimates of GHG inventory depend on model selection. This is an important consideration if the values are to be used for management and/or policy-related decisions. Development of models at the individual farm component level (animal, soil, crop) does not accurately reflect net GHG emissions generated from the whole production system. We developed a process-based, whole-farm model (Integrated Components Model, ICM), using the existing farm component models COWPOLL, manure-DNDC and some aspects of IPCC to integrate farm components and their associated GHG emissions. Estimates of total farm GHG emissions and their relative contribution using the ICM were comparable to estimates using two other whole-farm models (Integrated Farm System Model and Holos model). Variation was observed among models both in estimating whole-farm GHG emissions and the relative contribution of the different sources in the production system. Overall, whole-farm models are required to explore management options that will mitigate GHG emissions and promote best management practices. However, for full assessment of the production system, other benefits of the system (e.g., carbon sequestration, ecosystem services), which are not part of current whole-farm models, must be considered.

Submitted by Franciele Moreira (francielemoreyra@gmail.com) on 2018-01-31T14:05:36Z No. of bitstreams: 2 Tese - Elis Regina de Olivieira - 2017.pdf: 5392456 bytes, checksum: 68610e861c2d0e531893fa02a36401f5 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-01-31T14:28:36Z (GMT) No. of bitstreams: 2 Tese - Elis Regina de Olivieira - 2017.pdf: 5392456 bytes, checksum: 68610e861c2d0e531893fa02a36401f5 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-01-31T14:28:36Z (GMT). No. of bitstreams: 2 Tese - Elis Regina de Olivieira - 2017.pdf: 5392456 bytes, checksum: 68610e861c2d0e531893fa02a36401f5 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-12-15 / Fundação de Amparo à Pesquisa do Estado de Goiás - FAPEG / This thesis identified and analyzed the factors that determine the decision- making process of beef producers in relation to their investments in technology and the environmental consequences of these decisions, focusing on the Vermelho River basin as the geographical unit of analysis. The study analyzed the productive and economic viability of four models of beef production based on grazing systems, considering distinct levels of technology. This study defined three analytical dimensions: the socio- economic profile of the producer, the configuration of the production system, and management practices. The research used a stratified sampling design, with 60 randomly-selected cattle ranching establishments distributed in the strata according to their relief and the variability of their soils. The responses to the standard questionnaire provided primarily qualitative data, with the variables being measured on an ordinal or nominal scale. Multiple correspondence and cluster analyses were used to identify, respectively, the components that contributed most to the variance observed in the analyses, and the groups of variables and sampling units which best represented the indices of technology and pasture degradation, with a beta regression being applied to determine a mathematical function that could be applied to infer the classification of other sampling units in the study basin. The technological and pasture degradation indices did not present any spatial autocorrelation, based on Moran’s global or local indices. Nonparametric statistics (Fisher’s exact test, Spearman and Kendall) were used to verify the significance of the associations among the variables tested during the study. Principal results: the system with the lowest input of supplements was the most profitable; no significant relationship was found between the technological index and any of the variables: education, farm credit, cattle density, pasture degradation index, or the interaction of this index with the size of the property. Significant associations were identified between the technological index and the income, relief, and size of the property. The positive association between income and technology indicates that more technological systems are more profitable. The inverse relationship between relief and technology reflects the fact that the more technological systems tend to be installed on flatter or gently sloping terrain. The direct association between the size of the property and the use of technology reflects the importance of obtaining economies of scale to guarantee the profitability of the investment. The lack of any systematic relationship between the technological index and cattle density, as confirmed by the cluster analysis, indicates that high densities (above 2 animals per hectare) may be found in low technology systems, which impacts productivity and profitability, as well as long-term environmental sustainability. / Esta tese tem por objetivo identificar e analisar os fatores que condicionam a tomada de decisões dos produtores de bovinos por inversão de capital em níveis de tecnificação e suas consequências ambientais, utilizando a Bacia Hidrográfica do Rio Vermelho como unidade geográfica de estudo. Analisou-se a viabilidade produtiva e econômica de quatro modelos de produção de bovinos de corte em sistema de pastejo, considerando opções tecnológicas distintas. A partir desse estudo o instrumento de coleta de dados foi estruturado em três dimensões: perfil socioeconômico do gestor; composição do sistema de produção; e manejos. A pesquisa utilizou amostra estratificada por compartimentos com 60 estabelecimentos agropecuários, distribuídos entre os estratos, conforme a declividade e variabilidade de solos, selecionadas aleatoriamente. As perguntas e respostas fechadas constantes do formulário resultaram principalmente em variáveis de natureza qualitativa, com respectivas categorias medidas principalmente em escala nominal ou ordinal. Utilizou-se análise de correspondência múltipla e análise de cluster para identificar as componentes com maior proporção de variância explicada, e os respectivos agrupamentos de variáveis e unidades amostrais, que representassem melhor os indicadores de nível tecnológico e de degradação de pastagens, utilizando regressão beta para determinar equação matemática que possibilitasse inferir essa classificação para outras unidades amostrais da bacia. Indicador tecnológico e de degradação de pastagens não apresentaram autocorrelação espacial, considerando Índice Moran Global e Local. Utilizou-se de testes não paramétricos (teste exato de Fisher, Spearman e Kendall) para verificar a existência de associação entre as variáveis que compuseram as hipóteses científicas. Principais resultados: sistema de baixo consumo de suplemento apresentou maior índice de rentabilidade; não foi observada evidência estatística entre indicador tecnológico com cada uma das variáveis: educação, crédito rural, taxa de lotação, indicador de degradação de pastagens; e entre degradação de pastagens e tamanho da propriedade. As associações verificadas foram entre indicador tecnológico com cada uma das variáveis: renda, relevo e tamanho da propriedade. Renda associada positivamente com tecnologia sugere que, sistemas mais tecnificados remuneram melhor o gestor. Relevo, associado inversamente com tecnologia, revela que sistemas mais tecnificados estão instalados em relevos planos e em suave ondulados. Associação direta entre tamanho da propriedade e tecnologia evidencia que sistemas tecnificados de produção de bovinos em pastejo, demandam maior área para obter ganho de escala. A não associação entre indicador tecnológico e taxa de lotação, conforme observado também pela análise de cluster, sugere que taxas de lotação mais elevadas (acima de 2 UA/ha) podem ocorrer em sistemas com baixa tecnificação, comprometendo a sustentabilidade produtiva, econômica e ambiental.

Jordbruket är en sektor som står för en stor del av vår klimatpåverkan där animalieproduktionen bidrar med ungefär 15 %, främst från idisslare. För att minska klimatpåverkan kan klimatberäkningar utföras för att hitta möjligheter till förbättring. Dessa beräkningar är komplexa med stora osäkerheter. Studien syftar till att utvärdera två verktyg, Cool Farm Tool (CFT) och Vera, för beräkning av klimatpåverkan från gårdar med idisslare. Utvärdering skedde utifrån precision och hur väl resultatet redovisas utifrån gårdarnas möjlighet att använda resultatet för att identifiera förbättringsmöjligheter. Verktygen diskuterades också utifrån användarvänlighet. För utvärdering utfördes beräkningar i verktygen för tre system, en mjölk- och två nötköttssystem. För jämförelse utfördes egna beräkningar utifrån ett livscykelperspektiv. Resultatredovisningen analyserades utifrån egna och klimatrådgivares upplevelser. Även ett eget förslag till resultatredovisning redogörs. Resultaten från beräkningarna blev 1,1–1,2 kg koldioxidekvivalenter per liter fett och proteinkorrigerad mjölk och 8,6–8,7 kg koldioxidekvivalenter per kg levandevikt för djur till slakt för mjölkkor, 11–12 kg koldioxidekvivalenter för djur till slakt från nötsystemet med uppfödning av mjölkraskalvar som inte används för rekrytering och 14–17 kg koldioxidekvivalenter för köttsystemet med dikor. Skillnaderna mellan de två verktygen beror främst på skillnader i ”global warming potentials” och beräkningar av emissioner från fodersmältning, gödselhantering och foderproduktion. Vera har en stor fördel i att det använder svenska beräkningsmetoder och därmed är mer anpassat för svenska gårdar. Den är också flexibel då det finns schabloner som ofta går att ändra. CFT går snabbare att använda och det går att hantera bristfällig data till viss del. Vera redovisar resultatet på flera sätt med möjlighet att upptäcka områden för förbättring. CFT redovisar inte lika detaljerat. Vera skulle behöva minska tiden som går åt till att leta och lägga till produkter medan CFT skulle kunna öka sin flexibilitet och resultatredovisning. / The agricultural sector stands for a large part of our contribution to climate change where the livestock stands for about 15 %, mostly from ruminants. To reduce the climate impact climate calculations can be executed to find possibilities for improvements. These calculations are complex with great uncertainties. The purpose of the study was to evaluate two tools, Cool Farm Tool (CFT) and Vera, for climate calculations from farms with ruminants. The precision and how well the results are presented to identify improvement opportunities were evaluated. The tools ease of use where also discussed. For evaluation, calculations were performed with the tools for three systems, one milk system and two beef systems. For comparison, own calculations were performed with a life cycle perspective. The presentations of the results were analysed from own and advisor experiences. A suggestion for presentation of the results is also presented. The results from the calculations became 1.1–1.2 kg carbondioxide equlivents per litre fat and protein corrected milk, 8.6–8.7 kg carbondioxide equlivents per kg live-weight for slaughter from meat from milking cows, 11-12 kg carbondioxide equlivents from meet from the beef system with breeding of milk breed calves that don’t get used for replacement, and 14-17 kg carbondioxide equlivents for the beef system with suckler cows. The differences between the tools are mostly depending on different global warming potentials, calculations of emissions from enteric fermentation, manure management and feed production. Vera has a great advantage in using Swedish calculation methodes and therefore more suitable for Swedish farms. It is also flexible since there are standard values that mostly can be changed. CFT is faster to use and it can manage limitations in data at some level. Vera presents the results in several ways with the possibility to discover areas for improvement. CFT does not present the results in the same detail. Vera needs to limit the time needed to look for and ad products while CFT needs to improve the flexibility and presentation of results.