Energy balance methodology and modeling of supplementary forage production for cattle in Brazil

A pecuária é a principal fonte de proteína no Brasil, e sofre pela estacionalidade das chuvas, necessitando-se da suplementação alimentar. Para amenizar tais problemas surgem técnicas visando o aumento da produtividade, porém demandando mais energia. O balanço energético é uma importante ferramenta para avaliar a eficiência com que um sistema de produção utiliza os insumos, pois relaciona os fluxos de energia de entrada (input) e a energia disponibilizada pelo sistema (output). No entanto, não há uma metodologia padrão para tal análise, e ainda analisar diferentes opções não é uma tarefa fácil, pela complexidade de sistemas agrícolas e pelas interações de suas variáveis. Sendo assim, o presente trabalho objetivou propor uma metodologia de determinação do balanço energético, que desse suporte ao desenvolvimento de um modelo em planilha eletrônica. Este foi utilizado para avaliar dois sistemas: um de produção de silagem de milho (Zea mays L.) e um de silagem emurchecida de Tifton 85 (Cynodon spp.). A silagem de milho apresentou balanços energéticos bruto de 14,08 e a emurchecida 0,98, já para o balanço de energia digestível foram 9,12 e 0,99, respectivamente. As adubações demandaram 73,4% do total de energia na silagem de milho e a irrigação 99,7% na emurchecida. A análise de sensibilidade indicou produtividade e teor de matéria seca como variáveis críticas do balanço energético para a silagem de milho. Na emurchecida tal análise não indicou variável alguma. Reduções da concentração do fertilizante e uso de irrigação foram as melhores alternativas para o milho e o Tifton 85, respectivamente.Cattle is the main protein source in Brazil and cattle production depends on preserving forage in order to decrease the influence of dry periods on grass production. To minimize such problems, some new techniques have been created to increase the yield which also leads to energy demand increase. Energy balance is a vital tool to evaluate the efficiency of energy consumption in production systems. There is no standard methodology established for this determination. It is also difficult to analyze different management options because of the complexity of the production systems and the interactions among variables. Therefore the purpose of this study is to develop a methodology that supports the development of a model, using a spreadsheet, and to use it to analyze the energy balance of production systems. The model was applied to a traditional production system of maize (Zea mays L.) silage and a Bermuda grass (Cynodon spp.) haylage. The gross energy balance presented was 14.1 energy units of output per energy units of input for maize silage and 0.98 for haylage. For the digestible energy balance, the values were 9.1 and 0.99, respectively. The total energy demanded was 74.3% in maize silage fertilizations and 99.7% in haylage irrigation. Yield and dry matter contents were indicated in a sensitivity analysis as the main critical variables for maize, whereas for haylage, it was not possible to indicate any. The best alternative scenarios for improving energy efficiency in maize silage and haylage production were the reductions of fertilizer concentration and irrigation use, respectively

Determinação de fluxo de materiais por meio do gerenciamento de máquinas agrícolas

The approach of material embodiment in agricultural production systems is important because it determines the convergence of inputs (indirectly, the natural resources) to the field. Additionally, material flow is the basis for both environmental (energy analysis, emergy synthesis, life-cycle analysis and carbon inventories) and economical analyses. Since different materials cannot compose a single index, generally these flows are not shown, making comparisons among approaches difficult. Another aspect that makes comparisons difficult is the definition of the boundary of the studied system. If these boundaries differ, results will also be different, hiding actual distinctions among systems. The present study aims to suggest an arrangement of existing models to determine material flow in agricultural production systems. The following steps were considered: i) the adoption of a diagram language to represent the analyzed system; ii) determination of the material flow for directly applied inputs; iii) determination of the material flow for indirectly applied inputs, which included: determination of the effective field capacity; fuel consumption; machinery depreciation; and labor. Data on fuel consumption were compared with the models presented. The best model applied was a fixed parameter based on engine power (0.163 L kW-1 h-1). The determination of the material flow for maize silage production presented similar results as those obtained in regional databases.A abordagem da incorporação material em sistemas agrícolas é importante, pois determina a convergência de insumos (indiretamente, de recursos naturais) no campo. Além disso, os fluxos de materiais são a base para quaisquer análises ambientais (análises de energia, síntese de emergia, ciclo de vida e inventários de carbono) e econômicas. Uma vez que diferentes materiais não podem compor um único índice, geralmente esses fluxos não são mostrados. Isso dificulta comparações entre análises. Outro aspecto que contribui para isso é a definição dos limites dos sistemas estudados. Se eles diferirem os resultados serão diferentes, disfarçando as distinções reais entre eles. O presente estudo visa sugerir um arranjo de modelos existentes para a determinação dos fluxos de energia e materiais em sistemas agrícolas. Os seguintes passos foram considerados: i) a adoção de uma linguagem de diagramação para representar o sistema analisado; ii) a determinação do fluxo de materiais dos insumos diretamente aplicados; iii) a determinação do fluxo de materiais dos insumos indiretamente aplicados, que envolve a capacidade de campo operacional dos sistemas mecanizados, o consumo de combustível, a depreciação de maquinário e a mão-de-obra. Dados de consumo de combustível foram comparados com os modelos apresentados. O melhor modelo aplicado foi o fixado em função da potência do motor (0,163 L kW-1 h-1). A determinação dos fluxos de materiais para a produção de silagem de milho apresentou resultados similares aos dados de abordagem mais ampla

Material flow determination through agricultural machinery management

A abordagem da incorporação material em sistemas agrícolas é importante, pois determina a convergência de insumos (indiretamente, de recursos naturais) no campo. Além disso, os fluxos de materiais são a base para quaisquer análises ambientais (análises de energia, síntese de emergia, ciclo de vida e inventários de carbono) e econômicas. Uma vez que diferentes materiais não podem compor um único índice, geralmente esses fluxos não são mostrados. Isso dificulta comparações entre análises. Outro aspecto que contribui para isso é a definição dos limites dos sistemas estudados. Se eles diferirem os resultados serão diferentes, disfarçando as distinções reais entre eles. O presente estudo visa sugerir um arranjo de modelos existentes para a determinação dos fluxos de energia e materiais em sistemas agrícolas. Os seguintes passos foram considerados: i) a adoção de uma linguagem de diagramação para representar o sistema analisado; ii) a determinação do fluxo de materiais dos insumos diretamente aplicados; iii) a determinação do fluxo de materiais dos insumos indiretamente aplicados, que envolve a capacidade de campo operacional dos sistemas mecanizados, o consumo de combustível, a depreciação de maquinário e a mão-de-obra. Dados de consumo de combustível foram comparados com os modelos apresentados. O melhor modelo aplicado foi o fixado em função da potência do motor (0,163 L kW-1 h-1). A determinação dos fluxos de materiais para a produção de silagem de milho apresentou resultados similares aos dados de abordagem mais ampla.The approach of material embodiment in agricultural production systems is important because it determines the convergence of inputs (indirectly, the natural resources) to the field. Additionally, material flow is the basis for both environmental (energy analysis, emergy synthesis, life-cycle analysis and carbon inventories) and economical analyses. Since different materials cannot compose a single index, generally these flows are not shown, making comparisons among approaches difficult. Another aspect that makes comparisons difficult is the definition of the boundary of the studied system. If these boundaries differ, results will also be different, hiding actual distinctions among systems. The present study aims to suggest an arrangement of existing models to determine material flow in agricultural production systems. The following steps were considered: i) the adoption of a diagram language to represent the analyzed system; ii) determination of the material flow for directly applied inputs; iii) determination of the material flow for indirectly applied inputs, which included: determination of the effective field capacity; fuel consumption; machinery depreciation; and labor. Data on fuel consumption were compared with the models presented. The best model applied was a fixed parameter based on engine power (0.163 L kW-1 h-1). The determination of the material flow for maize silage production presented similar results as those obtained in regional databases

Machinery management as an environmental tool - material embodiment in agriculture

The material embodiment in agricultural production systems is important because it determines the convergence of inputs (indirectly, the natural resources) into the crop.  Besides this, the material flows are the basis for any environmental (energy analysis, emergy evaluation, life-cycle analysis and carbon inventories) and economical analyses. Since different materials cannot compose a single index, generally these flows are not shown and this fact makes comparisons difficult to be done. Another aspect that makes comparisons more difficult is the establishment of the studied system's boundary. If they differ, results will be different, disguising actual distinctions among systems. This study aimed to apply a methodology in order to determine material flows in agricultural production systems. A secondary goal is to show that machinery management can propitiate less material convergence into the crop. A diagram language to represent the analyzed system was adopted in order to establish the systems' limit. The determination of the material flows of indirectly applied inputs (fuel consumption; the machinery depreciation; and labor) included the determination of the effective field capacity, since the latter aggregates efficiency and is able to make data related to time to be related to area. Data of fuel consumption were compared with the models presented (the most accurate for the surveyed system was presented by Molin and Milan, 2002). The material embodiment of a maize silage production system was determined and compared with regional data, presenting similar data. For this system and a haylage (Tifton 85) production system the embodiment was calculated for different aspects (area, yield and qualitative aspects) in order to show the importance of establishing the limit of study and indicators. A comparison approaching the efficiency was also done, the variables considered were farm size, machinery use and labor requirement, efficiency increased more than the area increase

Capacidade do processo de corte de rebolos de cana-de-açúcar colhidos mecanicamente

The mechanized harvest of sugar cane (Saccharum officinarum L.) in Brazil is an irreversible trend and it comes with a great concern about the quality of the cane delivered to the industry. A key component to quality is the billet length which affects the processing of raw material, cane deterioration, invisible losses and load density of transport vehicles. Thus, due to the importance of the billet standard in quality and cost of raw material, this study aimed to evaluate if the mechanized harvesting of sugar cane can supply the quality requirements for the crushing process, regarding the billet length. A plot with burnt sugar cane (3.2 ha) and another one with green sugar cane (8.0 ha) were selected to be harvested by two (2) self-propelled sugar cane harvesters. For each harvested 0.4 ha a sample from each infield wagon was collected. The sample was composed by ten billets. The variability in burnt sugar cane was higher than in green sugar cane, and both harvesters did not present the capacity of keeping the billets with similar lengths when operating either in burnt or green conditions.A colheita mecanizada de cana-de-açúcar (Saccharum officinarum L.) no Brasil é uma tendência irreversível e junto a ela vem à preocupação com a qualidade da matéria-prima que chega à indústria. O tamanho de rebolos tem influência nessa qualidade por afetar o processo de deterioração da cana, perdas invisíveis e a densidade de carga no transbordo e transporte. Considerando-se a importância do padrão do rebolo na qualidade e custo da matéria-prima, avaliou-se se a colheita mecanizada de cana-de-açúcar pode atender às exigências de qualidade da moagem no que se refere ao indicador tamanho de rebolo. Para tanto, uma área de cana queimada (3,2 ha) e outra de cana crua (8,0 ha) foram selecionadas. As áreas foram colhidas por duas colhedoras automotrizes. Para cada colhedora e área, uma amostra a cada 0,4 ha colhidos foi coletada, junto ao conjunto de transbordo e cada amostra era composta por dez rebolos. Os resultados foram analisados por meio de gráficos de controle, e a capacidade do processo de corte foi determinada. Houve maior variabilidade na condição de cana queimada em relação à cana crua, e que ambas as colhedoras não têm a capacidade de manter os rebolos em tamanhos semelhantes, quando operando nessas duas condições diferentes

A cost prediction model for machine operation in multi-field production systems

Capacity planning in agricultural field operations needs to give consideration to the operational system design which involves the selection and dimensioning of production components, such as machinery and equipment. Capacity planning models currently onstream are generally based on average norm data and not on specific farm data which may vary from year to year. In this paper a model is presented for predicting the cost of in-field and transport operations for multiple-field and multiple-crop production systems. A case study from a real production system is presented in order to demonstrate the model’s functionalities and its sensitivity to parameters known to be somewhat imprecise. It was shown that the proposed model can provide operation cost predictions for complex cropping systems where labor and machinery are shared between the various operations which can be individually formulated for each individual crop. By so doing, the model can be used as a decision support system at the strategic level of management of agricultural production systems and specifically for the mid-term design process of systems in terms of labor/machinery and crop selection conforming to the criterion of profitability

Energy embodiment in Brazilian agriculture: an overview of 23 crops

The amount of energy required to produce a commodity or to supply a service varies from one production system to another and consequently giving rise to differing levels of environmental efficiency. Moreover, since energy prices have been continuously increasing over time, this energy amount may be a factor that has economic worth. Biomass production has a variety of end-products such as food, energy, and fiber; thus, taking into account the similarity in end-product of different crops (e.g.: sunflower, peanuts, or soybean for oil) it is possible to evaluate which crops require less energy per functional unit, such as starch, oil, and protein. This information can be used in decision-making about policies for food safety or bioenergy. In this study, 23 crops were evaluated allowing for a comparison in terms of energy embodied per functional unit. Crops were grouped as follows: starch, oil, horticultural, perennial and fiber, to provide for a deeper analysis of alternatives for the groups, and subsidize further studies comparing conventional and alternative production systems such as organic or genetically modified organisms, in terms of energy. The best energy balance observed was whole sugarcane (juice, bagasse and straw) with a surplus of 268 GJ ha−1 yr−1; palm shows the highest energy return on investment with a ratio of approximately 30:1. For carbohydrates and protein production, cassava and soybean, respectively, emerged as the crops offering the greatest energy savings in the production of these functional foods

Energy analysis of Jatropha curcas under irrigation and rainfed at the Southeast Brazilian humid subtropical

Jatropha (Jatropha curcas L.) is an oil seed species, adaptive to different climate and soil conditions. It is known due to its high-oil-content seed, being an option for biodiesel production and presenting competitive yields under irrigated condition. This study was developed in an experimental area located in a humid subtropical region of Brazil and the objective was to evaluate Jatropha’s energy balance under irrigation and rainfed condition during the first four years of its cycle. First, the material flows were determined, which supported the calculation of, energy input and output flows were obtained. These were used to determine the energy indices: energy balance (EB), and energy return on investment (EROI) for both conditions. Fertilizers had the highest contribution on energy input (42.58 GJ ha-1, 37.7% in irrigated area and 45.9% in rainfed area) followed by fuel consumption (32.96 GJ ha-1, 29.8% in irrigated area and 35.5% in rainfed area). Total energy input for the first four years in the irrigated area was 114.84 GJ ha-1 (which 19.22% was due to the irrigation) and 92.8 GJ ha-1 in the rainfed area. The output energy flows were 73.78 and 47.88 GJ ha-1 for irrigated and rainfed areas, respectively. In this study, a negative value for EB and unviable EROI (< 1) were obtained. However, EROI showed evolution when evaluated year-by-year, reaching values above 1 in the 4th year for both systems, as expected from perennial crops. Considering just the period evaluated, this crop was not sustainable for energy production, but this is a long lifespan crop and for the following years it is expected yield levels like the last one and values positive of energy balance