ANALYSIS OF ENERGY EFFICIENCY IN PIG PRODUCTION IN THE WESTERN REGION OF PARANÁABSTRACT
The western region of Paraná is an important center for agricultural production, particularly in the pork chain. This study estimated the energy incorporated in this chain by analyzing three sectors: grain production system, feed mill, and pig breeding system. The physical dimensions of the systems and the energy incorporation rates were evaluated, resulting in energy units. The results showed that the grain production system and the feed mill had an energy return on investment (EROI) below one, indicating a negative return on the energy invested, whereas the energy balance (BE) reflected a net gain. The embodied energy (EI) was 3.42 MJ kg-1 for soybean, 1.89 MJ kg-1 for corn, and 0.17 MJ kg-1 for feed. In the pig breeding system, the average EROI was 4.68, with no energy return, and the BE was -4,205.50 GJ lot-1, with an EI of 43.11 MJ kg-1 in the feed produced.
KEYWORDS
energetic balance; embodied energy; life cycle
INTRODUCTION
The growing demand for food in response to population growth requires technological innovations in the agricultural sector and an increase in the energy used in production systems (Karunathilake et al., 2023; Bathaei & Štreimikienė, 2023). This increase in the energy required is typically supplied by the use of fossil sources, resulting in greater use of inputs such as fertilizers, pesticides, and equipment (Oliveira & Silva, 2023).
The definition of management strategies for agricultural systems requires a careful analysis of environmental conditions and data from energy and economic balances. Understanding the relationship between energy production and consumption is crucial for maximizing energy efficiency and promoting robust economic analyses (Pimentel et al., 2024; Campos et al., 2024).
Recently, several approaches have been proposed to estimate energy production and consumption in agricultural systems, reinforcing the importance of this process for sustainability (Zanini et al., 2023; Felemban et al., 2024). The relationship between energy and food production indicates that variations in fuel prices directly affect the production chain (Oliveira & Silva, 2023).
The pork production chain is highly dependent on the energy used in grain production, considering the use of inputs, machinery, and infrastructure. Given the relevance of pig farming to the Brazilian economy, particularly in the western region of Paraná, the absence of energy indices related to the use of inputs and labor costs justifies the need to develop new indicators of embodied energy (EI).
Research is vital to assess productivity and understand the cost–benefit ratio, considering variables that help identify total demand and efficiency, reflected by the net energy gain and input/output ratio (Felemban et al., 2024). The quantification of EI involves the translation of production factors and intermediate consumption into energy units, allowing the construction of comparable indicators that support interventions to improve system efficiency.
Thus, the present study aims to estimate the energy incorporated in the grain production chain, considering the demand and availability of energy. For this purpose, the energy consumptions of the following variables involved in the grain production system were evaluated: labor, seeds, fertilizers, pesticides, machinery and implements, fuels, electricity, and lubricants. In addition, the electricity used in the feed manufacturing process and the resources required in the pig breeding system were analyzed, including labor, feed, electricity, water, veterinary inputs, and civil construction supplies. The energy produced and consumed in the pig production chain was quantified by calculating the return on energy invested, energy balance (BE), and energy incorporated in the chain.
MATERIAL AND METHODS
This study was conducted in three areas of the swine production chain in western Paraná: grain production system, feed factory, and pig breeding system. The grain production system located in Tupãssi-PR covered 32.67 ha and used a no-tillage system with early cultivars.
The feed factory located in Toledo-PR developed cores and premixes for pigs and cattle and processed raw materials such as soybeans and corn stored in silos.
The pig breeding system, also in Toledo-PR, operated in confinement with a license from the Environmental Institute of Paraná and housed 1,200 pigs in 1,350 m2 sheds. Pigs were housed between 50 and 70 days of age, going through several stages from feeding to slaughter, with an average weight of 110 kg. Feed was supplied from the silos and water from a local spring. Effluents were managed by channels that led to anaerobic lagoons, sized to treat 8.4 m3 day-1.
The experiment was conducted between January 2016 and February 2019, focusing on the analysis of the production process and energy inputs in an area cultivated with Roundup-resistant® soybean (SYN1059 and SYN1257) and DKB 285 PRO 2 corn, using reduced tillage. The data were obtained from practices on the property and recommendations of C. Vale Agroindustrial Cooperative, seeking the ideal conditions to achieve regional average productivity.
Inputs such as labor, fuel, machinery, fertilizers, seeds, and pesticides were considered, with the harvest of grains as the only solution. This study encompassed the crop cycle, from soil preparation to harvesting and analyzed each operation (sowing, spraying, and harvesting) in terms of the flow of materials and energy. The time required for each operation was measured to determine the operational field capacity of the cultivated area.
Additionally, data on the feed mill were collected through document analysis and meetings with those responsible, focusing on the energy and productivity of the feed. The study also included pig fattening and effluent treatment that was conducted between May 2017 and July 2018 and evaluated four batches from the arrival of the piglets to slaughter.
To determine the energy flows of the system, items such as electricity, feed, water, and veterinary inputs were considered, as well as labor and civil construction supplies (sheds and effluent stabilization system), allowing for the estimation of the energy equivalent and energy demand of the system.
The efficient use of energy and natural resources in agriculture is crucial, leading to the adoption of measures that promote this efficiency in production systems (Bathaei & Štreimikienė, 2023). Together with the analysis of energy flows, energy efficiency indicators are important tools for understanding the use and depletion of resources, particularly fossil sources (Agostinho & Ortega, 2012). Energy efficiency is defined as the number of services performed with lower energy consumption (Banaeian & Zangeneh, 2011) and is evaluated by the ratio of the energy produced to the energy used (Agostinho & Ortega, 2012).
Energy efficiency in agroecosystems is a key parameter for environmental sustainability, although other factors such as the use of non-renewable resources are also important for a comprehensive assessment (Nogueira & Moreira, 2023). Indicators such as EROI, BE, and embodied energy (EI) were used to measure energy efficiency.
EROI quantified the energy produced in relation to the energy required in the production process, indicating the energy profitability of a system (Fernandes & Lima, 2023; Santos et al., 2024). BE analyzed energy flows to identify demands and efficiencies and help in the development of new agricultural techniques (Nogueira & Moreira, 2023). EI referred to the amount of energy required, directly and indirectly, for the production of goods or services, involving the quantification of inputs and their associated energy (Bathaei & Štreimikienė, 2023).
RESULTS AND DISCUSSION
Energy Flows in the Grain Production System
This study presents a detailed analysis of the energy consumption and production in soybean and corn cultivation, considering the use of machinery, labor, agricultural inputs, and fuels. Data on the useful life, mass, and operational capacity of machines such as tractors and harvesters were provided. The inputs used in the harvests, such as seeds and pesticides, and the consumption of fuels and lubricants were analyzed, comparing these data between the corn (2016–2018) and soybean (2017–2019) harvests. The correlation between fuel costs and the value of crops in the market during harvesting highlighted the relevance of energy efficiency in the agricultural process.
Finally, the energy components produced by the grain production system considered the efficiency of the physical production of grains per area (ha). The yields of corn crops for years 2016, 2017, and 2018 were 90.89, 74.37, and 103.29 bags ha-1, respectively. The productivities for the 2017, 2018, and 2019 harvests of soybean were 82.63, 63.17, and 27.66 bags ha-1, respectively.
The energy consumed and produced for the 2016, 2017, and 2018 harvests of corn are presented in Tables 1, 2, and 3, respectively.
The energy consumed and produced for the 2017, 2018, and 2019 harvests of soybean are presented in 4, 5, and 6, respectively.
The results revealed significant variations between the estimated data and those presented in publications, particularly with regard to energy expenditure. Owing to the relevance of the topic and the individual nature of the calculations, the discussion is divided into two parts: the first part compares the calculated energy matrix with data from publications on soybean production and the second part compares the results with those of Bathaei & Štreimikienė (2023), who addressed renewable energy indicators and their relationship with sustainable agriculture, emphasizing the need for a continuous and more accurate evaluation of the data available in the literature. The studied crop had its own characteristics, such as differences in response to the use of inputs and productivity, that varied according to sowing times and regions.
The differences observed in the 2016–2018 corn harvest and– the 2017–2019 soybean harvest could be largely attributed to regional meteorological factors. These included variations in rainfall distribution, temperature fluctuations, and the occurrence of extreme weather events such as periods of prolonged drought, frost, or excessive rainfall. In addition, global climatic phenomena such as El Niño and La Niña significantly affected the agro-climatic conditions of these agricultural cycles. These factors directly affected the development, productivity, and quality of the respective crops. Regarding the grain production system, the energy consumed in the corn crop in the 2016, 2017, and 2018 harvests was 10.30, 9.16, and 11.76 GJ ha-1, respectively, with an average of 10.40 GJ ha-1. The energy produced in these harvests was 91.29, 74.69, and 103.74 GJ ha-1, respectively, resulting in an average EROI of 0.12. For the soybean crop in the 2017, 2018, and 2019 harvests, the energy consumed was 13.33, 11.75, and 10.52 GJ ha-1, respectively, with an average of 11.87 GJ ha-1, whereas the energy produced was 82.89, 63.37, and 27.75 GJ ha-1, respectively, resulting in an average EROI of 0.20. The BE that reflected the net energy was 79.50 GJ ha-1 and EI was 1.89 MJ kg-1 for corn and BE was 46.13 GJ ha-1 and EI was 3.42 MJ kg-1 for soybean.
Energy Flows in the Feed Mill
For the energy components of the feed mill, the energy directly consumed and produced used in the previously established variables were quantified: the history of electricity bills between January 2018 and July 2018 and the respective monthly quantities of feed production. The methodology adopted in the analysis justified the absence of accounting for the hours worked by employees in the feed mill, unlike in the production system. In this case, electricity consumption was exclusively considered owing to its greater representativeness in direct operating costs and the difficulty of accurately attributing working hours to the specific stages of the production process because they were variable. Therefore, priority was given to measurable variables directly associated with the energy performance of the plant. Its energy consumed corresponding only to the average consumption of electricity (352,179.13 kWh month-1) in the project during the aforementioned months was 1,267,844.85 MJ month-1, and the energy produced, determined by the average amount of feed (7,580,060.00 kg month-1) manufactured was 128,861,020.00 MJ month-1.
Thus, the EROI resulting from the average of the energy consumed and produced in the factory was 0.01. The difference between the energy produced and consumed during production in the feed mill resulted in a BE of 127,593,175.10 MJ month-1. The EI of the manufactured feed was 0.17 MJ kg-1.
Energy Flows in the Pig Breeding System
The labor time spent on pig handling and fattening activities was recorded; total hours worked were 1,076; 1,004; 940; 1,004 for the batches between May 2017 and July 2018. The operations included washing, reception and organization of the piglets, cleaning of the breeding system, and daily monitoring, with a breakdown of the hours worked per operation.
In addition, the mass and energy flows were monitored using data on the inputs used such as feed, electricity, water, and antibiotics. The tables present detailed information on the amount of each input consumed per batch, evidencing the responsibility of the integrating company in the feed and the source of water supply. The final results of the energy consumed and produced for each batch were organized into specific tables, allowing for a comparative analysis of the data over time.
The energy consumed and produced by the pig breeding system for the batches of May 2017–August 2017, October 2017–January 2018, January 2018–April 2018, and April 2018–July 2018 are respectively presented in 7, 8, 9, and 10.
The energy consumed by the pig breeding system for the batches of May 2017–August 2017, October 2017–January 2018, January 2018–April 2018, and April 2018–July 2018, corresponded respectively to 5,758.87, 5,414.66, 4,846.10, and 5,372.64 GJ lot-1, with an average of 5,348.07 GJ lot-1, and the respective energy produced, determined by means of live pigs, was 1,200.80, 1,162.03, 1,033.09, and 1,174.37 GJ lot-1, with an average of 1,142.57 GJ lot-1 per harvest.
Thus, the EROI resulting from the average energy consumed and produced in the pig lots was 4.68. The difference between the energy produced and consumed during the production in the feed mill resulted in a BE of -4,205.50 GJ lot-1. The EI of the manufactured feed was 43.11 MJ kg-1.
CONCLUSIONS
The analysis of energy efficiency in the pig production chain in the western region of Paraná revealed significant disparities between the energy consumed and produced, particularly in the grain production system and feed mill, where the EROI was below one. These results indicated a low energy return relative to the amount of energy invested, reflecting inefficiencies at these stages of the production chain. Conversely, although the pig breeding system demonstrated a higher average EROI of 4.68, the BE remained negative, evidencing the high energy demand of the system.
Given this situation, strategies that can enhance energy performance and reduce environmental and economic impacts must be considered. One promising alternative is the use of biodigesters for biogas production, particularly in pig farming where organic waste is abundant and can be efficiently converted into renewable energy. This would allow for the partial or even total replacement of electricity from the grid, thereby reducing dependency and operational costs. In the feed mill, investments in more energy-efficient machinery and process automation can lead to substantial energy savings, particularly considering the high amount of electricity currently used in feed production. In agricultural operations, the use of thermal insulation materials in storage units and pig sheds, along with biological nitrogen fixers in grain production, can reduce the energy needs associated with temperature control and synthetic fertilizer application, thereby improving the energy balance of the system.
Additionally, the integration of renewable energy sources such as photovoltaic solar panels and biogas systems presents a viable path for diversifying the energy matrix in rural areas, particularly for powering grain drying, water pumping, and ventilation systems. Finally, optimizing logistics in grain transport by improving route planning, vehicle efficiency, and storage proximity can minimize the energy expended in the distribution of raw materials that is particularly relevant in regions with high agricultural productivity. These approaches represent technical opportunities to reduce energy consumption and serve as foundations for future research aimed at promoting more sustainable and resilient production systems.
ACKNOWLEDGEMENTS
I would like to thank the National Council for Scientific and Technological Development (CNPq), the Coordination for the Improvement of Higher Education Personnel (CAPES), and the Araucária Foundation for Scientific and Technological Development of the State of Paraná for their institutional and financial support, which was fundamental to the completion of this work. The encouragement of research and academic training promoted by these institutions is essential for the advancement of scientific knowledge in Brazil.
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Edited by
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Area Editor:
Maria Joselma de Moraes
Publication Dates
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Publication in this collection
15 Sept 2025 -
Date of issue
2025
History
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Received
10 Oct 2024 -
Accepted
04 July 2025
