The Runoff Risk Advisory Forecast (RRAF) provides Wisconsin's farmers with an innovative decision support tool which communicates the threat of undesirable conditions for manure and nutrient spreading for up to 10 days in advance. The RRAF is a pioneering example of applying the National Weather Service's hydrologic forecasting abilities towards the Nation's water quality challenges. Relying on the North Central River Forecast Center's (NCRFC) operational Snow17 and Sacramento Soil Moisture Accounting Models, runoff risk is predicted for 216 modeled watersheds in Wisconsin. The RRAF is the first-of-its-kind real-time forecast tool to incorporate 5-days of future precipitation as well as 10-days of forecast temperatures to generate runoff risk guidance. The forecast product is updated three times daily and hosted on the Wisconsin Department of Agriculture, Trade, and Consumer Protection (DATCP) website. Developed with inter-agency collaboration, the RRAF model was validated against both edge-of-field observed runoff as well as small USGS gauged basin response. This analysis indicated promising results with a Bias Score of 0.93 and a False Alarm Ratio (FAR) of only 0.34 after applying a threshold method. Although the threshold process did dampen the Probability of Detection (POD) from 0.71 to 0.53, it was found that the magnitude of the events categorized as hits was 10-times larger than those classified as misses. The encouraging results from this first generation tool are aiding State of Wisconsin officials in increasing awareness of risky runoff conditions to help minimize contaminated agriculture runoff from entering the State's water bodies.

This study investigates the impact of nutrient management regulations on pig farms in Ontario, Canada. Using mathematical programming, small, medium and large farrow to finish and finishing pig farms are examined using uniform and crop requirement based manure application. The model scenarios characterize the cost of compliance when nutrient application standards are applied from the Nutrient Management Act and a previously proposed standard from the Clean Water Act. Compliance costs for scenarios with uniform manure application are ≤6.47%; while compliance costs for scenarios with crop requirement based manure application are ≤0.25%. The Nutrient Management Act has two calculations for nutrient application standards, producers must comply with the less binding calculation. Compliance costs for producers under the less binding standard following a uniform manure application strategy are ≤1.53%; while producers following a crop requirement based manure application strategy have no compliance costs. The proposed Clean Water Act standard is more restrictive than the Nutrient Management Act standards. / Ontario Pork, OMAFRA

Storing manure on dairy farms is essential for maximizing its fertilizer value, reducing management costs, and minimizing potential environmental pollution challenges. However, ammonia loss through volatilization during storage remains a challenge. Quantifying these losses is necessary to inform decision-making processes to improve manure management, and design ammonia mitigation strategies. In 2003, the National Research Council recommended using process-based models to estimate emissions of pollutants, such as ammonia, from animal feeding operations. While much progress has been made to meet this call, still, their accuracy is limited because of the inadequate values of manure properties such as heat and mass transfer coefficients. Additionally, the process-based models lack realistic estimations for manure temperatures; they use ambient air temperature surrogates which was found to underestimate the atmospheric emissions during storage. This study uses machine learning algorithms' unique abilities to address some of the challenges of process-based modeling. Firstly, ammonia concentrations, manure temperature, and local meteorological factors were measured from three dairy farms with different manure management practices and storage types. This data was used to estimate the influence of manure characteristics and meteorological factors on the trend of ammonia emissions. Secondly, the data was subjected to four data-driven machine learning algorithms and a physics-informed neural network (PINN) to predict manure temperature. Finally, a deep-learning approach that combines process-based modeling and recurrent neural networks (LSTM) was introduced to estimate ammonia loss from dairy manure during storage. This method involves inverse problem-solving to estimate the heat and mass transfer coefficients for ammonia transport and emission from stored manure using the hyperparameters optimization tool, Optuna. Results show that ammonia flux patterns mirrored manure temperature closely compared to ambient air temperature, with wind speed and crust thickness significantly influencing ammonia emissions. The data-driven machine learning models used to estimate the ammonia emissions had a high predictive ability; however, their generalization accuracy was poor. However, the PINN model had superior generalization accuracy with R2 during the testing phase exceeded 0.70, in contrast to -0.03 and 0.66 for finite-elements heat transfer and data-driven neural network, respectively. In addition, optimizing the process-based model parameters has significantly improved performance. Finally, Physics-informed LSTM has the potential to replace conventional process-based models due to its computational efficiency and does not require extensive data collection. The outcomes of this study contribute to precision agriculture, specifically designing suitable on-farm strategies to minimize nutrient loss and greenhouse gas emissions during the manure storage periods. / Doctor of Philosophy / Dairy farming is critical for meeting the global demand for animal protein products; however, it generates a lot of manure that must be appropriately managed. Manure can only be applied to crop or pasture lands during growing seasons. Typically, manure is stored on farms until time permits for land application. During storage, microbial processes occur in the manure, releasing gases such as ammonia. Ammonia emitted contributes to the degradation of ambient air quality, human and animal health problems, biodiversity loss, and soil health deterioration. Furthermore, releasing ammonia from stored manure reduces the nitrogen fertilizer value of stored manure. Implementing control measures to mitigate ammonia emission is necessary to reduce nitrogen loss from stored manure. Deciding and applying appropriate control measures require knowledge of the rate of ammonia emission and when it occurs. Process-based models are a less expensive and more reliable method for estimating ammonia emissions from stored liquid dairy manure. Process-based model is a mathematical model that simulates processes related to ammonia production and emission from stored manure. However, process-based models have limitations because they require estimates of manure properties, which vary depending on the manure management. Additionally, these models use air temperature instead of manure temperature, underestimating the ammonia lost during storage. Therefore, this study used machine learning algorithms to develop more accurate models for predicting manure temperature and estimating ammonia emissions. First, we collected manure temperature, ammonia emissions, and weather data from three dairy farms with different manure management practices and storage structures. We used it to estimate the factors that affect ammonia emissions. The data was then used to develop four machine-learning models and one integrated machine-learning-based to assess their ability to predict manure temperature. Finally, a different machine learning approach that combines process-based modeling and neural networks was used to directly estimate ammonia loss from dairy manure during storage. The results show that manure temperature is closely related to the amount of ammonia lost, and factors like wind speed and crust thickness also influence the amount of ammonia lost. Machine learning algorithms offer a more accurate way to predict manure temperature than traditional methods. Finally, combining machine learning and process-based modeling improved the ammonia emission estimates. This study contributes to precision agriculture by designing suitable on-farm strategies to minimize nutrient loss during manure storage periods. It provides valuable information for dairy farmers and policymakers on managing manure storage more effectively and sustainably.

Anaerobic digestion (AD) is a sustainable waste management technology that primarily generates two products: biogas and digestate. The technology relies on the microorganisms' activity, which depends on several operational factors, such as pH, temperature, solid contents, and ammonia levels. Ammonia is an inorganic form of nitrogen resulting from the biodegradation of organic nitrogen. It is considered one of the major concerns for AD operations due to its inhibitory effects on some microorganisms, particularly methanogens. A common feedstock characterized by high nitrogen content is poultry manure (PM). PM is often avoided in anaerobic digesters due to the anticipated inhibition resulting from its high ammonia levels. However, since poultry manure is one of the most widely available organic wastes, researchers have extensively investigated ways to include PM as a primary feedstock for AD. One possible way to treat high ammonia levels in digestate is ammonia stripping, the physio-chemical separation of ammonia from a solution by introducing a stripping (carrier) gas. There are a few approaches to performing ammonia stripping in AD applications; the most commonly discussed in the literature are pre-hydrolysis and side-stream ammonia stripping. Pre-hydrolysis ammonia stripping is performed on raw feedstock after increasing pH and temperature and is usually not restricted in selecting the gas carrier. On the other hand, side-stream ammonia stripping is when a portion of the digester's working volume is filtered, and the filtrate is sent to a unit where pH and temperature are increased. The carrier gas in these systems is often limited to anaerobic gases such as biogas or steam. The third and most novel approach is post-hydrolysis ammonia stripping, conducted at an intermediate stage between hydrolysis and methanogenesis in a two-stage AD process. This configuration would address the shortcomings of the other two systems. However, there is minimal information on the feasibility and potential of this approach in the literature. This study aims to comprehensively investigate the post-hydrolysis ammonia stripping approach through the following four phases: Phase I) Proof of Concept; Phase II) Optimization; Phase III) Assessment of Alternative Carrier Gases; and Phase IV: Comparison of Different Ammonia Stripping Configurations. Phase I provided the proof of concept under the batch mode and compared the performance of post-hydrolysis ammonia stripping with two-stage AD and co-digestion to improve poultry manure's methane potential as the primary substrate. It was observed that ammonia stripping successfully improved methane potential by up to 150%, whereas improvements due to two-stage AD and co-digestion were limited to 41 and 9%, respectively. Phase II provided more insight into optimizing the ammonia stripping process. Different stripping conditions were tested (pH 7.8 (unadjusted), 9 and 10, temperature 25 (unadjusted), 40 and 55 °C, and flow rate 300 L/L/hour). The results showed that higher pH and temperature lead to higher removal efficiency. However, it was concluded that optimal conditions ultimately depend on the initial and target ammonia levels. Moreover, Analysis of Variance showed that pH and temperature were significant factors affecting the ammonia removal efficiency. In addition, it was observed that higher stripping temperatures (55 °C) enhanced the digestibility of PM and increased its methane potential more than stripping at 40 °C. It was concluded that the optimum stripping conditions were pH 9.5, temperature 40 or 55 °C, and flowrate of 100 L/L/hour to collectively increase ammonia removal while reducing the associated costs and material handling. In Phase III, renewable natural gas (RNG) was evaluated as a stripping medium in batch testing as a potential replacement for biogas and air. Ammonia stripping with RNG yielded promising results comparable to the application of air in terms of ammonia removal and enhancing biogas production from PM (60 and 69% ammonia removal for RNG and air, respectively). In addition, a metagenomic shotgun analysis showed that most biogas production was conducted through hydrogenotrophic methanogens instead of acetoclastic methanogens, which are more susceptible to high ammonia levels. Phase IV assessed the semi-continuous flow two-stage operation of mesophilic AD reactors coupled with different ammonia stripping configurations. Post-hydrolysis ammonia stripping successfully achieved a stable operation of PM mono-digestion at ammonia levels of 1700 and 2400 mg NH₃-N/L in the cases of stripping with air and RNG, respectively. In addition, post-hydrolysis ammonia stripping in semi-continuous flow mode may have promoted acetoclastic methanogens growth since volatile fatty acid concentrations were reduced in the digesters. Phase IV also proved that the performance of post-hydrolysis ammonia stripping is superior over pre-hydrolysis and side-stream ammonia stripping. In the semi-continuous flow reactors, post-hydrolysis ammonia stripping with air achieved on average 831 L biogas/ kg VS at an organic loading rate (OLR) of 2.6 g VS/L/day, whereas side-stream ammonia stripping resulted in average of 700 L biogas/ kg VS at OLR of 1.8 g VS/L/day and higher ammonia stripping requirements. Having said that, the base scenario (no ammonia stripping) was inhibited, indicating that both ammonia stripping configurations were considered successful in alleviating inhibitory effects of ammonia from poultry manure. Phase IV results also proved that air stripping repeatedly outperformed RNG as stripping mediums by having higher ammonia removal efficiencies resulting in higher methane production. However, stripping with RNG is believed to have more practical advantages than air due to avoiding the risk of oxygen infiltration into the reactor. Moreover, renewable natural gas has proven to be an efficient stripping medium that is available on-site. The final stage of Phase IV tested pre-hydrolysis ammonia stripping using air in batch mode and compared it with post-hydrolysis ammonia stripping. Pre-hydrolysis ammonia stripping provided little to no improvement to the methane potential of PM in batch mode and therefore was excluded from the semi-continuous flow experiment. The four phases of this study demonstrated the flexibility and the superiority of post-hydrolysis ammonia stripping over the other pre-hydrolysis and side-stream ammonia stripping. In addition, post-hydrolysis ammonia stripping was proven efficient and feasible for ammonia removal and enabling the mono- or co-digestion of poultry manure. The study also showed that using RNG instead of biogas can significantly reduce the operational costs of the treatment.

Antibiotics and antibiotic resistance genes from animal manure applied to soil as fertilizer are now among the most concerned contaminants in soil. The widespread use of antibiotics in livestock might amplify the risk of developing antibiotic resistance, causing once treatable diseases to turn deadly. The World Health Organization declared antibiotic resistance as "one of the biggest threats to global health, food security, and development". The goal of this dissertation was to develop best manure management practices by understanding the behavior of manure-associated antibiotics in manure, water, and soil. In particular, my research focused on the effects of manure application methods, on-site manure treatment methods, manure application seasons, and manure-rainfall time gaps on antibiotic surface runoff losses, antibiotic distribution and movement in soil, antibiotic dissipation in soil, and development of antibiotic resistance. Rainfall simulation field-scale and soil incubation lab studies were combined to find the best manure management practices. My research has shown for the first time that using the manure soil subsurface injection method, especially during spring application season due to moist soil, applying manure at least 3 days before a subsequent rainfall, and using composted manure, can significantly reduce the quantity of antibiotic loss with runoff from manure-applied fields to the surrounding environment. The majority of applied antibiotics remained in soil. All antibiotics showed a similar dissipation pattern with fastest kinetics during the first 14 d before slowing down. The effect of two manure application methods on antibiotic dissipation kinetics varied with different antibiotics. Although the half-life of tested antibiotics in soil was short (<21 days), some remained detectable even at 6 months after a single manure application. Results also showed that compared to the surface application, the subsurface injection slits acted as a "hot zone" with a higher amount of antibiotics, manure microbes, and antibiotic resistance. The results provide information for policy makers, manure managers, and farmers to develop better manure management practices that can use manure as fertilizer while minimizing the spread of antibiotics to surrounding water, soil, and plants. / Doctor of Philosophy / There is growing concern about antibiotic resistance as a serious human health threat because a resistant infection may kill, can spread, and increases health costs. Every year in the United States, there are 2 million people infected with antibiotic resistant bacteria, 23,000 people die as a direct result of these infections, and $55 billion is lost due to increased hospital stay and lost work days. Although bacteria naturally develop the ability to resist antibiotics, the problem is the length between antibiotic introduction and resistance development is shortening because of the widespread and overuse of antibiotics, especially in the livestock industry. The goal of this study was to develop the best manure management practices balancing the benefits of antibiotics in livestock and animal manure and their impact on the environment. In particular, we monitored, using field-scale and laboratory studies, the effects of manure application methods, on-site manure treatment methods, manure application seasons, and manure-rainfall time gaps on antibiotic loss through surface runoff, antibiotic distribution and movement in soil, antibiotic dissipation in soil, and development of antibiotic resistance. In order to reduce the amount of antibiotic loss with surface runoff from manure-applied fields to the surrounding environment, farmers are recommended to 1) compost manure before application, 2) watch the forecast to apply manure at least 3 days before a subsequent rainfall, and 3) use the subsurface injection method, especially when the soil is wet (spring season). The majority of applied antibiotics remained in soil. All tested antibiotics showed a similar dissipation pattern with the fastest rate during the first two weeks after manure application, then slowing down. Although the half-life of tested antibiotics in soil was short (<21 days), some remained detectable even at 6 months after a single manure application. Besides, the subsurface injection slits acted as a hot zone with a concentrated amount of antibiotics, manure microbes, and antibiotic resistance. The results provide recommendations for policy makers, manure managers, and farmers to maximize benefits of manure as fertilizer while minimizing the spread of manure-associated antibiotics to surrounding water, soil, and plants.

[Abstract]: The disposal of animal waste has become a problem in many parts of the world due to the rapid growth in the number and the size of intensive animal industries. Safe waste disposal sites are rarely available and the relocation and/or treatment of animal waste is seldom economically viable. The reuse of animal waste for energy recovery and re-feeding is also not popular. Animal waste is a valuable source of plant nutrients and a very good soil conditioner, and has been commonly applied as fertiliser to agricultural fields. However, due to the increasing oversupply of animal waste in recent years, it has often been applied in excess to the agricultural fields. Excessive application of animal waste, without due consideration of its implications, is a serious concern. The run-off and leaching losses of nutrients from the fields fertilised with animal waste have contributed significantly to the eutrophication and toxic blue-green algae blooms in surface water systems and nitrification of ground water systems. It has also led to nutrient imbalances in the soils and odour pollution to the surrounding communities. The animal waste, which is a valuable source of plant nutrients, has thus become both an economic and environmental burden, and there is a need to develop a strategy for its sensible use as a fertiliser in agricultural fields. Sensible use of animal waste involves the consideration of all the agricultural, environmental, social, and economical limitations. A rational method of achieving this is to restrict the use of animal waste to sites suitable for such uses, identify areas where it can be relocated and applied economically, limit the application rates to a safe level, and observe appropriate manure management practices. This study addressed each of these components by developing a comprehensive manure application plan (MAP) for the site-specific use of animal waste as fertiliser in agricultural fields. Various geographic information systems (GIS) based techniques, including a weighted linear combination model and map algebra based cartographic modelling, were employed to achieve the goal. The appropriateness of the existing techniques and procedures were evaluated and modified to meet the current input requirements. New methods of analysis were devised as necessary. The Westbrook sub-catchment of the Condamine River catchment in south-east Queensland was selected as the study area. The sub-catchment covers 24,903 hectares and contains 39 intensive animal industries. The catchment is also a part of the Murray-Darling Basin, which has been suffering from toxic blue green algae blooms recurrently since 1991. This study identified that only about one-fifth of the sub-catchment area is suitable for animal waste application. Depending on the method of site suitability analysis and the number of input factors used the suitable area ranged between 16 and 22 percent. This comparatively small area is mainly due to the presence of a large proportion of non-agricultural areas in the sub-catchment. The suitable areas were also found to have various degrees of suitability for waste application. However, the degree of site suitability was affected by the number of input factors used in the analysis, the weighting of the factors, and the method of factor attribute standardisation. Conventional methods of weighting input factors were found to be cumbersome and not particularly suitable. Hence, this study developed a new ‘objective oriented comparison’ method of factor weighting. Standardisation of input factors using a continuous, rather than discrete, classification (ie fuzzy set) method was found to be more consistent in degree of suitability determination. The discrete classification of factor attributes into classes of different numbers and sizes, and the weighting of classes to a sum of one, were identified as a limitation in using this standardisation method. A new ‘weight adjustment’ method was devised and demonstrated to reduce factor-weighting biases. The suitable sites, degree of site suitability, and other relevant spatial and non-spatial information were processed within a GIS framework to develop a comprehensive manure application plan. The inherently high presence of available phosphorus in the soils of the study area was recognised and the P2O5 content in the manure was used as the basis for determining manure application rates. A complimentary nitrogen supply map was also generated. Manure management practices applicable to the areas with a lower degree of suitability were also suggested.

Enhanced biological phosphorus removal (EBPR) has been widely used in municipal wastewater treatment, but no previous studies have examined the application of EBPR to treat dairy manure. This study was conducted to evaluate the (i) performance of pilot-scale EBPR systems treating liquid dairy manure, to balance the ratio of nitrogen to phosphorus in manure to meet crop nutrient requirements, (ii) effects of dissolved oxygen and solids retention time on the efficiency of EBPR, and (iii) effectiveness of gravity thickening for reducing the volume of harvested EBPR aerated mixed liquor. Two pilot-scale EBPR systems were used in this study. The ratio of the manure chemical oxygen demand expressed as volatile fatty acids to phosphorus used ranged from 18:1 to 45:1. The phosphorus removal efficiencies of the EBPR system were investigated at three solids retention times (4, 6 and 10 d), and three dissolved oxygen levels (3, 4 and 6 mg O₂/L). The total phosphorus removal was highest (84%) at 10 d solids retention time and lowest (63%) at 4 d solids retention time. The sludge from the 6 d solids retention time tests had better sludge settling characteristics with a sludge volume index of 62 mL/g compared to 80 mL/g for the 4 d solids retention time. The EBPR system achieved 90% dissolved reactive phosphorus removal when the system was operated at 4 mg O₂/L, and the ratio of nitrogen to phosphorus in effluent increased to about 5:1, which was higher than the normal ratio in dairy manure. On the other hand, phosphorus removal performance deteriorated when dissolved oxygen level was 3 mg O₂/L. In the gravity thickening tests, 93-95 % total suspended solids (TSS) was removed from the settled supernatant, with 1.2 to 1.54 % total solids (TS) in the settled solids after 90 min gravity-induced thickening. The extent of phosphorus release during gravity thickening process needs to be further investigated. / Master of Science

Made available in DSpace on 2017-05-12T14:46:52Z (GMT). No. of bitstreams: 1 Larissa.pdf: 1850942 bytes, checksum: 055f99877063a1e529d77540c0b94279 (MD5) Previous issue date: 2013-02-01 / Livestock, especially cattle, has been considered one of the main sectors that is responsible for global warming due to rumen methane emission and, to a lesser extent, methane emission by residues. Another concern is the correct disposal of agroindustrial residues. The wet brewery grain is considered as polluting as animal wastes. Thus, such wastes must have correct destination, so their use to feed animal is an option. The wet brewery grain has been recorded as an important substitute for fodder and/or grain in ruminants diet. Thus, this study aimed at evaluating the potential for methane production in cattle fed diets containing different levels of wet brewery grain inclusion, to replace bulky diet, with 0, 20, 25 and 30% rates in dry matter percentage. Four castrated steers, with rumen cannula were studied and distributed in a Latin square design (4x4) in four experimental periods of 21 days each (14 days of adjustment and 7 days for data collection). During the last week of each period, the animals manure and ruminal fluid were collected, whose anaerobic digestion essays were analyzed, during the period of 120 days. So, the following parameters were evaluated: removal of total and volatile solids, removal of soluble chemical oxygen demand, cumulative and daily production of methane, volatile fatty acids production (lactic, acetic, propionic and butyric), acidity/alkalinity ratio and pH of reactors. In order to record ruminal fluid, 96-hour tests were performed in the laboratory to observe the influence of wet brewery grain inclusion on methane and volatile fatty acids production inside the rumen. The statistical evaluation of the process was obtained with curves of cumulative production of methane that were adjusted according to Gompertz modified model. Tukey test was used to compare averages with 5% significance. According to these data, it is concluded that wet brewery grain inclusion influenced on methane production for these animals. There was effect of treatment and period for cumulative production of methane (L). The treatment with the largest inclusion of wet brewery residue showed the highest potential of methane production in wastes. The wet brewery residue inclusion did not affect the production of volatile fatty acids inside rumen. The cumulative methane production (mL) of ruminal fluid was influenced by the inclusion of wet brewery residue on animals diet. Nevertheless, the lowest production occurred with an increasing supply of wet brewery residue. The Gompertz modified model provided a good adjustment to the methane production data. Consequently, wet brewery residue can be considered an alternative diet to replace corn silage up to 30% (DM), since it reduces methane production inside the rumen (environmental benefit) and increases methane production from residues (energy and economic benefit). / A pecuária, sobretudo a bovina, tem sido considerada um dos principais setores responsáveis pelo aquecimento global, devido à emissão de metano ruminal e, em menor proporção, à emissão de metano pelos dejetos. Outra preocupação é a correta destinação dos resíduos agroindustriais. O resíduo úmido de cervejaria é considerado tão poluidor quanto os dejetos animais. Desta forma, é importante que este subproduto tenha destino correto e uma opção é o uso na alimentação animal. O resíduo úmido de cervejaria tem se mostrado um importante substituto para forragens e/ou grãos na dieta de ruminantes. Portanto, o objetivo deste trabalho foi avaliar o potencial de produção de metano de bovinos alimentados com dietas que continham diferentes níveis de inclusão de resíduo úmido de cervejaria (RUC), em substituição ao volumoso da dieta, cujas doses foram: 0, 20, 25 e 30% em porcentagem de massa seca. Foram utilizados quatro bovinos machos, castrados, portadores de cânula ruminal, distribuídos em delineamento quadrado latino (4x4), em quatro períodos experimentais de 21 dias cada (14 dias de adaptação e 7 dias de coleta de dados). Na última semana de cada período, coletaram-se dejetos e líquido ruminal dos animais. Com os dejetos coletados, realizaram-se ensaios de biodigestão anaeróbia, no período de 120 dias, nos quais foram avaliados a remoção de sólidos totais e voláteis, a remoção da demanda química de oxigênio solúvel, a produção diária e acumulada de gás metano, a produção de ácidos graxos voláteis (lático, acético, propiônico e butírico), a relação acidez/alcalinidade e o pH dos reatores. Em relação ao líquido ruminal, foram realizados testes de 96 horas, em laboratório, para verificar a influência da inclusão de RUC na produção de gás metano e ácidos graxos voláteis no rúmen. Para a avaliação estatística do processo, utilizaram-se curvas de produção acumulada de metano, ajustadas segundo modelo de Gompertz modificado. O teste de Tukey foi adotado para comparação das médias, com nível de significância de 5%. Com os dados obtidos, conclui-se que a inclusão de resíduo úmido de cervejaria teve influência na produção de metano nesses animais; houve efeito de tratamento e período para a produção acumulada de metano (L). O tratamento com maior inclusão de resíduo úmido de cervejaria apresentou maior potencial de produção de metano nos dejetos; a inclusão de RUC não alterou o perfil de produção de ácidos graxos voláteis no rúmen; a produção acumulada de metano (mL) do líquido ruminal foi influenciada pela inclusão de resíduo úmido de cervejaria à dieta. Todavia, a menor produção ocorreu com o aumento do fornecimento de resíduo úmido de cervejaria. O modelo de Gompertz modificado apresentou bom ajuste aos dados de produção de gás metano. Logo, o resíduo úmido de cervejaria pode ser considerado alimento alternativo para substituir a silagem de milho, em até 30% (MS), uma vez que diminui a produção de metano no rúmen (benefício ambiental) e aumenta a produção de metano nos dejetos (benefício energético e econômico).

Made available in DSpace on 2017-07-10T19:23:40Z (GMT). No. of bitstreams: 1 Larissa.pdf: 1850942 bytes, checksum: 055f99877063a1e529d77540c0b94279 (MD5) Previous issue date: 2013-02-01 / Livestock, especially cattle, has been considered one of the main sectors that is responsible for global warming due to rumen methane emission and, to a lesser extent, methane emission by residues. Another concern is the correct disposal of agroindustrial residues. The wet brewery grain is considered as polluting as animal wastes. Thus, such wastes must have correct destination, so their use to feed animal is an option. The wet brewery grain has been recorded as an important substitute for fodder and/or grain in ruminants diet. Thus, this study aimed at evaluating the potential for methane production in cattle fed diets containing different levels of wet brewery grain inclusion, to replace bulky diet, with 0, 20, 25 and 30% rates in dry matter percentage. Four castrated steers, with rumen cannula were studied and distributed in a Latin square design (4x4) in four experimental periods of 21 days each (14 days of adjustment and 7 days for data collection). During the last week of each period, the animals manure and ruminal fluid were collected, whose anaerobic digestion essays were analyzed, during the period of 120 days. So, the following parameters were evaluated: removal of total and volatile solids, removal of soluble chemical oxygen demand, cumulative and daily production of methane, volatile fatty acids production (lactic, acetic, propionic and butyric), acidity/alkalinity ratio and pH of reactors. In order to record ruminal fluid, 96-hour tests were performed in the laboratory to observe the influence of wet brewery grain inclusion on methane and volatile fatty acids production inside the rumen. The statistical evaluation of the process was obtained with curves of cumulative production of methane that were adjusted according to Gompertz modified model. Tukey test was used to compare averages with 5% significance. According to these data, it is concluded that wet brewery grain inclusion influenced on methane production for these animals. There was effect of treatment and period for cumulative production of methane (L). The treatment with the largest inclusion of wet brewery residue showed the highest potential of methane production in wastes. The wet brewery residue inclusion did not affect the production of volatile fatty acids inside rumen. The cumulative methane production (mL) of ruminal fluid was influenced by the inclusion of wet brewery residue on animals diet. Nevertheless, the lowest production occurred with an increasing supply of wet brewery residue. The Gompertz modified model provided a good adjustment to the methane production data. Consequently, wet brewery residue can be considered an alternative diet to replace corn silage up to 30% (DM), since it reduces methane production inside the rumen (environmental benefit) and increases methane production from residues (energy and economic benefit). / A pecuária, sobretudo a bovina, tem sido considerada um dos principais setores responsáveis pelo aquecimento global, devido à emissão de metano ruminal e, em menor proporção, à emissão de metano pelos dejetos. Outra preocupação é a correta destinação dos resíduos agroindustriais. O resíduo úmido de cervejaria é considerado tão poluidor quanto os dejetos animais. Desta forma, é importante que este subproduto tenha destino correto e uma opção é o uso na alimentação animal. O resíduo úmido de cervejaria tem se mostrado um importante substituto para forragens e/ou grãos na dieta de ruminantes. Portanto, o objetivo deste trabalho foi avaliar o potencial de produção de metano de bovinos alimentados com dietas que continham diferentes níveis de inclusão de resíduo úmido de cervejaria (RUC), em substituição ao volumoso da dieta, cujas doses foram: 0, 20, 25 e 30% em porcentagem de massa seca. Foram utilizados quatro bovinos machos, castrados, portadores de cânula ruminal, distribuídos em delineamento quadrado latino (4x4), em quatro períodos experimentais de 21 dias cada (14 dias de adaptação e 7 dias de coleta de dados). Na última semana de cada período, coletaram-se dejetos e líquido ruminal dos animais. Com os dejetos coletados, realizaram-se ensaios de biodigestão anaeróbia, no período de 120 dias, nos quais foram avaliados a remoção de sólidos totais e voláteis, a remoção da demanda química de oxigênio solúvel, a produção diária e acumulada de gás metano, a produção de ácidos graxos voláteis (lático, acético, propiônico e butírico), a relação acidez/alcalinidade e o pH dos reatores. Em relação ao líquido ruminal, foram realizados testes de 96 horas, em laboratório, para verificar a influência da inclusão de RUC na produção de gás metano e ácidos graxos voláteis no rúmen. Para a avaliação estatística do processo, utilizaram-se curvas de produção acumulada de metano, ajustadas segundo modelo de Gompertz modificado. O teste de Tukey foi adotado para comparação das médias, com nível de significância de 5%. Com os dados obtidos, conclui-se que a inclusão de resíduo úmido de cervejaria teve influência na produção de metano nesses animais; houve efeito de tratamento e período para a produção acumulada de metano (L). O tratamento com maior inclusão de resíduo úmido de cervejaria apresentou maior potencial de produção de metano nos dejetos; a inclusão de RUC não alterou o perfil de produção de ácidos graxos voláteis no rúmen; a produção acumulada de metano (mL) do líquido ruminal foi influenciada pela inclusão de resíduo úmido de cervejaria à dieta. Todavia, a menor produção ocorreu com o aumento do fornecimento de resíduo úmido de cervejaria. O modelo de Gompertz modificado apresentou bom ajuste aos dados de produção de gás metano. Logo, o resíduo úmido de cervejaria pode ser considerado alimento alternativo para substituir a silagem de milho, em até 30% (MS), uma vez que diminui a produção de metano no rúmen (benefício ambiental) e aumenta a produção de metano nos dejetos (benefício energético e econômico).