Estimating the environmental impact of broiler production process

Orientador: Irenilza de Alencar NääsTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia AgrícolaResumo: O objetivo deste estudo foi estimar os impactos ambientais do ciclo de vida e o custo ambiental do processo de produção de frangos de corte. No primeiro capítulo, o objetivo foi avaliar o impacto ambiental do processo produtivo de frangos de corte usando a abordagem de Avaliação do Ciclo de Vida (ACV). O estudo avaliou dados da produção de frango de corte de seis granjas, período de um ano, o total de seis ciclos produtivos por ano. O inventário do ciclo de vida incluiu todos os fluxos de entrada e saída dos subsistemas: produção de ração e criação de frangos, com finalidade de avaliar o impacto ambiental desde o alojamento das aves até o portão da granja. As categorias de impacto: potencial de aquecimento global, depleção de recursos abióticos (recursos minerais e fósseis), depleção da camada de ozônio, eutrofização, acidificação, ecotoxicidade aquática de água doce, ecotoxicidade aquática marinha, ecotoxicidade terrestre, toxicidade humana, oxidação fotoquímica e uso da terra. Os resultados mostraram que as emissões totais de Gases de Efeito Estufa (GEE) provenientes do gerenciamento de dejetos totalizaram 0,154 kg CO2-eq por kg de frango produzido. As contribuições de CH4, N2O direto e N2O indireto para o potencial de aquecimento global foram de 18,9%, 19,3% e 61.8% respectivamente. O resultado do potencial de aquecimento global total para o processo de produtivo de frangos de corte foi de 2,70 kg de CO2-eq por kg de frango vivo produzido no portão da granja. A fase de produção das aves apresentou maior contribuição no aquecimento global com 1,95 kg CO2-eq por kg de frango vivo produzido. A depleção de recursos abióticos (recursos minerais 5,1 E-8 kg e recursos fósseis 0,143 MJ) apresentaram valores maiores para a fase de produção de ração. No segundo capítulo, o objetivo foi estimar o custo ambiental do processo produtivo de frangos de corte usando a abordagem da contabilidade emergética. O processo produtivo de frangos de corte de uma granja padrão foi avaliado. Um diagrama sistêmico foi elaborado para identificar todos os componentes e fluxos de energia. Uma tabela que contém os valores dos fluxos de materiais e energia foi construída. Os índices emergéticos foram calculados a partir dos resultados encontrados na avaliação dos fluxos de emergia. A emergia total que suporta o sistema foi 7,00 E+05 sej/ha/ano. A contribuição mais importante no fluxo emergético do sistema provém dos materiais da economia com total de 6,60 E+05 sej/ha/ano, incluindo a ração com 4,60 E+05 sej/ha/ano, os pintos de um dia 1,48 E+05 sej/ha/ano e a energia elétrica 2,07 E+04 sej/ha/ano. O fluxo de emergia agregado do processo produtivo foi 69.693,84 sej/ha/ano. O índice de renovabilidade mostrou baixa sustentabilidade do sistema, a razão de rendimento emergético indicou que a quantidade de emergia da natureza incorporada na produção de frangos é baixa quando comparada com a emergia total usada, a razão de investimento emergético indicou um alto investimento para produzir frangos no sistema convencional, e a razão de carga ambiental indicou alta degradação ambientalAbstract: The objective of this study was to estimate the environmental impacts of the life cycle and the environmental cost of the process of production of broilers. In the first chapter, the objective was to evaluate the environmental impact of the productive process of broiler chickens using the Life Cycle Assessment (LCA) approach. The study evaluated data from the production of broiler from six farms, period of one year, the total of six productive cycles per year. The life cycle inventory included all inflows and outflows of the subsystems: feed production and broiler rearing to assess the environmental impact from broiler housing to farm gate. Impact categories: global warming potential, depletion of abiotic resources (mineral and fossil resources), ozone depletion, eutrophication, acidification, freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, terrestrial ecotoxicity, human toxicity, photochemical oxidation and land use. The results showed that total greenhouse gas emissions from waste management totaled 0.154 kg CO2-eq per kg of broiler produced. The contributions of CH4, direct N2O and indirect N2O to the global warming potential were 18.9%, 19.3% and 61.8% respectively. The total global warming potential for the broilers production process was 2.70 kg CO2-eq per kg of live broiler produced at the farm gate. The production phase of the poultry presented greater contribution in global warming with 1.95 kg CO2-eq per kg of live chicken produced. The depletion of abiotic resources (mineral resources 5.1 E-8 kg and fossil resources 0.143 MJ) presented higher values for the stage of production of feed. In the second chapter, the objective was to estimate the environmental cost of the productive process of broilers using the approach of the emergy accounting. The productive process of broilers from a standard farm was evaluated. A systemic diagram was designed to identify all components and energy flows. A table containing the values of the material and energy flows was constructed. The emergy indices were calculated from the results found in the evaluation of the emergy flows. The total emergy that supports the system was 7.00 E+05 sej/ha/year. The most important contribution in the emergy flow of the system comes from the economy materials with a total of 6.60 E+05 sej/ha/year, including the feed with 4.60 E+05 sej/ha/year, day-old chicks 1.48 E+05 sej/ha/year and the electric energy 2.07 E+04 sej/ha/year. The aggregate emergy flow of the productive process was 69,693.84 sej/ha/year. The renewability index showed low sustainability of the system, the rate of emergy indicated that the amount of emergy of the nature incorporated in broiler production is low when compared to the total emergy used, the rate of emergy investment indicated a high investment to produce broilers in the conventional system, and the environmental load ratio indicated high environmental degradationDoutoradoConstruções Rurais e AmbienciaDoutora em Engenharia Agrícol

Model-predicted ammonia emission from two broiler houses with different rearing systems

Ammonia (NH3) emissions from broiler production can affect human and animal health and may cause acidification and eutrophication of the surrounding environment. This study aimed to estimate ammonia emissions from broiler litter in two systems of forced ventilation, the tunnel ventilation (TV) and the dark house (DH). The experiment was carried out on eight commercial broiler houses, and the age of the birds (day, d), pH and litter temperature were recorded. Broilers were reared on built-up wood shaving litter using an average flock density of 14 bird m–2. Temperature and relative humidity inside the broiler houses were recorded in the morning during the grow-out period. A factorial experimental design was adopted, with two types of houses, four replicates and two flocks with two replicates each. A deterministic model was used to predict ammonia emissions using the litter pH and temperature, and the day of grow-out. The highest litter temperature and pH were found at 42 d of growth in both housing systems. Mean ambient air temperature and relative humidity did not differ in either system. Mean model predicted ammonia emission was higher in the DH rearing system (5200 mg NH3 m−2h−1 at 42 d) than in the TV system (2700 mg NH3m−2 h−1 at 42 d). TV presented the lowest mean litter temperature and pH at 42 d of growth. In the last week of the broilers’ grow-out cycle, estimated ammonia emissions inside DH reached 5700 mg m−2h−1 in one of the flocks. Ammonia emissions were higher inside DH, and they did not differ between flocks. Assuming a broiler market weight in Brazil of close to 2 kg, ammonia emissions were equivalent to 12 g NH3 bird-marketed−1. Model-predicted ammonia emissions provided comprehensible estimations and might be used in abatement strategies for NH3 emission

Classifying the Level of Energy-Environmental Efficiency Rating of Brazilian Ethanol

The present study aimed to assess and classify energy-environmental efficiency levels to reduce greenhouse gas emissions in the production, commercialization, and use of biofuels certified by the Brazilian National Biofuel Policy (RenovaBio). The parameters of the level of energy-environmental efficiency were standardized and categorized according to the Energy-Environmental Efficiency Rating (E-EER). The rating scale varied between lower efficiency (D) and high efficiency + (highest efficiency A+). The classification method with the J48 decision tree and naive Bayes algorithms was used to predict the models. The classification of the E-EER scores using a decision tree using the J48 algorithm and Bayesian classifiers using the naive Bayes algorithm produced decision tree models efficient at estimating the efficiency level of Brazilian ethanol producers and importers certified by the RenovaBio. The rules generated by the models can assess the level classes (efficiency scores) according to the scale discretized into high efficiency (Classification A), average efficiency (Classification B), and standard efficiency (Classification C). These results might generate an ethanol energy-environmental efficiency label for the end consumers and resellers of the product, to assist in making a purchase decision concerning its performance. The best classification model was naive Bayes, compared to the J48 decision tree. The classification of the Energy Efficiency Note levels using the naive Bayes algorithm produced a model capable of estimating the efficiency level of Brazilian ethanol to create labels

Model-predicted ammonia emission from two broiler houses with different rearing systems

Ammonia (NH3) emissions from broiler production can affect human and animal health and may cause acidification and eutrophication of the surrounding environment. This study aimed to estimate ammonia emissions from broiler litter in two systems of forced ventilation, the tunnel ventilation (TV) and the dark house (DH). The experiment was carried out on eight commercial broiler houses, and the age of the birds (day, d), pH and litter temperature were recorded. Broilers were reared on built-up wood shaving litter using an average flock density of 14 bird m–2. Temperature and relative humidity inside the broiler houses were recorded in the morning during the grow-out period. A factorial experimental design was adopted, with two types of houses, four replicates and two flocks with two replicates each. A deterministic model was used to predict ammonia emissions using the litter pH and temperature, and the day of grow-out. The highest litter temperature and pH were found at 42 d of growth in both housing systems. Mean ambient air temperature and relative humidity did not differ in either system. Mean model predicted ammonia emission was higher in the DH rearing system (5200 mg NH3 m−2h−1 at 42 d) than in the TV system (2700 mg NH3m−2 h−1 at 42 d). TV presented the lowest mean litter temperature and pH at 42 d of growth. In the last week of the broilers’ grow-out cycle, estimated ammonia emissions inside DH reached 5700 mg m−2h−1 in one of the flocks. Ammonia emissions were higher inside DH, and they did not differ between flocks. Assuming a broiler market weight in Brazil of close to 2 kg, ammonia emissions were equivalent to 12 g NH3 bird-marketed−1. Model-predicted ammonia emissions provided comprehensible estimations and might be used in abatement strategies for NH3 emission

IDADE DA MATRIZ E SUPLEMENTAÇÃO VITAMÍNICA SOBRE O DESEMPENHO DE FRANGOS DE CORTE / AGE OF BREEDER AND VITAMIN SUPPLEMENTATION ON THE BROILERS’ PERFORMANCE

O objetivo do trabalho foi avaliar o efeito da suplementação vitamínica na primeira semana de vida sobre o desempenho de frangos de corte provenientes de matrizes de diferentes idades. Foram alojados 2.592 pintos de um dia da linhagem Cobb®, em delineamento experimental inteiramente casualizado, distribuídos em arranjo fatorial 2x3, sendo duas idades de matrizes (29 e 44 semanas) e três níveis de inclusão de vitaminas (sem vitaminas, nível recomendado pelo fabricante e 50% superior ao do fabricante) com oito repetições por tratamento. A análise dos dados foram realizadas utilizando PROC GLM do SAS e comparadas por Teste de Tukey a 95% de probabilidade. A suplementação vitamínica não influenciou o desempenho das aves na primeira semana e nem aos 42 dias de idade. Houve influência da idade da matriz no ganho de peso médio, o peso médio final e o consumo de ração médio, na primeira semana de vida das aves. A utilização do complexo vitamínico pode ser recomendada em caso de limitações, como deficiência nutricional da matriz, aspectos e sanitários que podem afetar o desempenho das aves.</p

Model-predicted ammonia emission from two broiler houses with different rearing systems

Ammonia (NH3) emissions from broiler production can affect human and animal health and may cause acidification and eutrophication of the surrounding environment. This study aimed to estimate ammonia emissions from broiler litter in two systems of forced ventilation, the tunnel ventilation (TV) and the dark house (DH). The experiment was carried out on eight commercial broiler houses, and the age of the birds (day, d), pH and litter temperature were recorded. Broilers were reared on built-up wood shaving litter using an average flock density of 14 bird m–2. Temperature and relative humidity inside the broiler houses were recorded in the morning during the grow-out period. A factorial experimental design was adopted, with two types of houses, four replicates and two flocks with two replicates each. A deterministic model was used to predict ammonia emissions using the litter pH and temperature, and the day of grow-out. The highest litter temperature and pH were found at 42 d of growth in both housing systems. Mean ambient air temperature and relative humidity did not differ in either system. Mean model predicted ammonia emission was higher in the DH rearing system (5200 mg NH3 m−2h−1 at 42 d) than in the TV system (2700 mg NH3m−2 h−1 at 42 d). TV presented the lowest mean litter temperature and pH at 42 d of growth. In the last week of the broilers’ grow-out cycle, estimated ammonia emissions inside DH reached 5700 mg m−2h−1 in one of the flocks. Ammonia emissions were higher inside DH, and they did not differ between flocks. Assuming a broiler market weight in Brazil of close to 2 kg, ammonia emissions were equivalent to 12 g NH3 bird-marketed−1. Model-predicted ammonia emissions provided comprehensible estimations and might be used in abatement strategies for NH3 emission

Hybrid Metaheuristic Algorithm for Optimizing Monogastric Growth Curve (Pigs and Broilers)

Brazil is one of the world&rsquo;s biggest monogastric producers and exporters (of pig and broiler meat). Farmers need to improve their production planning through the reliability of animal growth forecasts. Predicting pig and broiler growth is optimizing production planning, minimizing the use of resources, and forecasting meat production. The present study aims to apply a hybrid metaheuristic algorithm (SAGAC) to find the best combination of values for the growth curve model parameters for monogastric farm animals (pigs and broilers). We propose a hybrid method to optimize the growth curve model parameters by combining two metaheuristic algorithms Simulated Annealing (SA) and Genetic Algorithm (GA), with the inclusion of a function to promote the acceleration of the convergence (GA + AC) of the results. The idea was to improve the coefficient of determination of these models to achieve better production planning and minimized costs. Two datasets with age (day) and average weight (kg) were obtained. We tested three growth curves: Gompertz, Logistic, and von Bertalanffy. After 300 performed assays, experimental data were tabulated and organized, and a descriptive analysis was completed. Results showed that the SAGAC algorithm provided better results than previous estimations, thus improving the predictive data on pig and broiler production consistency. Using SAGAC to optimize the growth parameter models for pigs and broilers led to optimizing the results with the nondeterministic polynomial time (NP-hardness) of the studied functions. All tuning of the growth curves using the proposed SAGAC method for broilers presented R2 above 99%, and the SAGAC for pigs showed R2 above 94% for the growth curve

Classifier’s Performance for Detecting the Pecking Pattern of Broilers during Feeding

Broiler feeding is an efficient way of evaluating growth performance, health, and welfare status. This assessment might include the number of meals, meal period, ingestion rate, meal intervals, and the proportion of time spent eating. These parameters can be predicted by studying the birds’ pecking activity. The present study aims to design, examine, and validate classifying algorithms to determine individual bird pecking patterns at the feeder. Broilers were reared from 1 to 42 days, with feed and water provided ad libitum. A feeder equipped with a force sensor was installed and used by the birds starting at 35 days of age, to acquire the pecking force data during feeding until 42 days. The obtained data were organized into two datasets. The first comprises 17 attributes, with the supervised attribute ‘pecking detection’ with two classes, and with ‘non-pecking’ and ‘pecking’ used to analyze the classifiers. In the second dataset, the attribute ‘maximum value’ was discretized in three classes to compose a new supervised attribute of the second dataset comprising the classes’ non-pecking, light pecking, medium, and strong. We developed and validated the classifying models to determine individual broiler pecking patterns at the feeder. The classifiers (KNN, SVM, and ANN) achieved high accuracy, greater than 97%, and similar results in all investigated scenarios, proving capable of performing the task of detecting pecking

Classifier&rsquo;s Performance for Detecting the Pecking Pattern of Broilers during Feeding

Broiler feeding is an efficient way of evaluating growth performance, health, and welfare status. This assessment might include the number of meals, meal period, ingestion rate, meal intervals, and the proportion of time spent eating. These parameters can be predicted by studying the birds&rsquo; pecking activity. The present study aims to design, examine, and validate classifying algorithms to determine individual bird pecking patterns at the feeder. Broilers were reared from 1 to 42 days, with feed and water provided ad libitum. A feeder equipped with a force sensor was installed and used by the birds starting at 35 days of age, to acquire the pecking force data during feeding until 42 days. The obtained data were organized into two datasets. The first comprises 17 attributes, with the supervised attribute &lsquo;pecking detection&rsquo; with two classes, and with &lsquo;non-pecking&rsquo; and &lsquo;pecking&rsquo; used to analyze the classifiers. In the second dataset, the attribute &lsquo;maximum value&rsquo; was discretized in three classes to compose a new supervised attribute of the second dataset comprising the classes&rsquo; non-pecking, light pecking, medium, and strong. We developed and validated the classifying models to determine individual broiler pecking patterns at the feeder. The classifiers (KNN, SVM, and ANN) achieved high accuracy, greater than 97%, and similar results in all investigated scenarios, proving capable of performing the task of detecting pecking

Hybrid Metaheuristic Algorithm for Optimizing Monogastric Growth Curve (Pigs and Broilers)

Brazil is one of the world’s biggest monogastric producers and exporters (of pig and broiler meat). Farmers need to improve their production planning through the reliability of animal growth forecasts. Predicting pig and broiler growth is optimizing production planning, minimizing the use of resources, and forecasting meat production. The present study aims to apply a hybrid metaheuristic algorithm (SAGAC) to find the best combination of values for the growth curve model parameters for monogastric farm animals (pigs and broilers). We propose a hybrid method to optimize the growth curve model parameters by combining two metaheuristic algorithms Simulated Annealing (SA) and Genetic Algorithm (GA), with the inclusion of a function to promote the acceleration of the convergence (GA + AC) of the results. The idea was to improve the coefficient of determination of these models to achieve better production planning and minimized costs. Two datasets with age (day) and average weight (kg) were obtained. We tested three growth curves: Gompertz, Logistic, and von Bertalanffy. After 300 performed assays, experimental data were tabulated and organized, and a descriptive analysis was completed. Results showed that the SAGAC algorithm provided better results than previous estimations, thus improving the predictive data on pig and broiler production consistency. Using SAGAC to optimize the growth parameter models for pigs and broilers led to optimizing the results with the nondeterministic polynomial time (NP-hardness) of the studied functions. All tuning of the growth curves using the proposed SAGAC method for broilers presented R2 above 99%, and the SAGAC for pigs showed R2 above 94% for the growth curve