Introduction
Agriculture stands out as one of the few industries capable of sustainably generating resources from nature, producing output by leveraging elements found in nature. This sector plays a dual role as both an energy consumer and producer. Modern agribusiness maximises the conversion of natural resources into agricultural assets, such as land, equipment, buildings, structures, procedures, and systems, by applying scientific concepts, with the aim of boosting productivity. The remarkable gains in productivity observed in Latin American agriculture since the 1960s can be attributed to scientific advancements and the widespread adoption of modern techniques. Between 1979 and 2011, the region experienced substantial increases in agricultural output per worker and total factor productivity. These improvements were driven by increased fertilizer usage, increased land yield, and higher investment that extended the per worker cultivated area.
As agriculture in Latin America transitions from subsistence farming to agribusiness, it has grown more reliant on diesel-powered equipment, natural gas, and chemical fertilisers made from fossil fuels. Produce distribution, processing, and storage are frequently energy-intensive tasks as well. Because of this dependency on energy inputs, future productive potential and input productivity may be jeopardised due to the enormous uncertainty around the cost and availability of energy required for agricultural operations and essential inputs like fertilisers and irrigation. As a result, increased energy expenses directly and significantly affect the profitability of agribusinesses. Although the sector is beginning to recognise the significance of energy efficiency, Latin American cultures' economic and cultural constraints prevent the complete implementation of enforcement standards for energy. Additionally, budgetary constraints lead to a lack of human resources, resulting in inefficient monitoring and enforcement systems. The availability and quality of data remain major constraints, often causing decision-makers to hesitate due to lack of precise information. The purpose of this research is to provide a cost-based approach to quantifying agricultural energy efficiency while accounting for uncertainty.
Efficiencies—Technical and Allocative
Despite their differences, phrases "energy efficiency" and "energy conservation" are sometimes applied synonymously. Energy efficiency refers to consuming energy efficiently and is mostly a technical improvement; energy conservation, on the other hand, entails making do with less energy and is typically involves a change human behaviour. The term "energy efficiency" usually refers to the conversion of inputs and outputs into energy. The fundamental concept of energy efficiency, defines “energy efficiency” as the ratio of "useful energy outputs to the heat content, or calorific value, of fuel inputs”. Technical efficiency plus allocative efficiency are usually understood to produce overall productive efficiency.
Allocative efficiency evaluates a producer's ability to select an optimal input mix based on their energy content, distinct from technical efficiency which assesses maximum output from given inputs. As some producers fail to optimize, analysis has shifted from traditional production functions to frontier-based approaches that envelop rather than intersect data. This involves using linear programming to construct non-parametric frontiers for measuring and decomposing energy efficiency. Measuring energy efficiency requires assessing direct and indirect energy content of inputs, which is controversial. Life Cycle Energy Assessment (LCEA) is a common method accounting for all energy inputs in production. However, it struggles with issues of energy quality differences stemming from thermodynamic laws, arbitrary value assignments, rigid system boundaries, and data reliability concerns.
When precise input energy content is unknown, energy efficiency can be computed using scenarios with differently sloped iso-energy lines. This can result in varying allocative and energy efficiencies while maintaining the same technical efficiency. A study examined 21 public sector banana plantations in Latin America. Bananas, grown primarily near the equator, are a major export from Ecuador and Colombia to the European Union. The banana industry is characterized by integrated value chains and competitive low-cost exports from Latin America. Monoculture practices have led to increased susceptibility to diseases, resulting in heavy reliance on energy-intensive agrochemicals. This has created a cycle of pesticide resistance, challenging plantation managers attempting to reduce chemical use. The energy content of inputs varies significantly across different studies and regions, with data collected from various locations including Denmark, Iran, India, and Turkey.
The energy consumption for five inputs - farmyard manure, chemical fertilizers, diesel fuel, machinery, and human labor - was analyzed across all farms. The average total input energy was calculated at 50,000 MJ per hectare. Nitrogen and fuel were the most significant energy consumers, accounting for nearly 49% and 40% of the total input energy in banana production, respectively. Other chemicals (Phosphorus and Potassium) and machinery also contributed substantially, while farmyard manure and human labor had minimal impact. This distribution highlights the heavy reliance on chemical inputs in contemporary agricultural practices.
To assess energy efficiency deterministically, linear programming models were employed, assuming constant returns to scale, convexity, and strong disposability for inputs and outputs. Using the energy content values from Table 1, the total energy consumed in MJ was normalized by dividing it by the banana output in kg. The most efficient farm was assigned a score of 1, serving as a benchmark for other farms. The analysis revealed a mean Technical Efficiency of 0.69, Allocative Efficiency of 0.91, and Energy Efficiency of 0.59. These results suggest a potential for reducing inputs and associated energy consumption by approximately 38%.
Conclusion
The study shows that there are two primary causes of energy inefficiency in contemporary agribusiness: improper input allocation and mismanagement. Our examination of Latin American banana plantations shows that there is a lot of room for energy efficiency growth. There is a chance to cut input consumption and ensuing energy use by as much as 38% with a mean technical efficiency of 0.69, an allocated efficiency of 0.91, and an overall energy efficiency of 0.59. This study presents a methodology for assessing energy efficiency in public sector organisations, with a focus on the agriculture sector. We are able to evaluate both technical and allocative efficiency by using linear programming to build a non-parametric frontier. This gives us a complete picture of how energy is used in agriculture activities.
It is crucial to remember that this study is just the beginning of tackling the intricate problem of energy efficiency in agriculture. The method described here must be expanded to handle situations in which the inputs’ energy content is ambiguous, which occurs frequently in practical applications. Future work should concentrate on creating reliable techniques to deal with this uncertainty, maybe using fuzzy logic or stochastic frontier analysis techniques. In addition, the results highlight the necessity of focused interventions in agricultural practices, policy development, and technology adoption to improve sector energy efficiency. Energy utilisation can be significantly improved, leading to more sustainable and financially successful agriculture enterprises throughout Latin America and beyond, by addressing both management practices and resource allocation.
References
- Atilgan, A., Krakowiak-Bal, A., Ertop, H., Saltuk, B., & Malinowski, M. (2023). The energy potential of waste from banana production: a case study of the mediterranean region. Energies, 16(14), 5244. [CrossRef]
- Asthana, A. N. (2011). The business of water: fresh perspectives and future challenges African Journal of Business Management.5(35), 13398-13403.
- Tock, J. Y., Lai, C. L., Lee, K. T., Tan, K. T., & Bhatia, S. (2010). Banana biomass as potential renewable energy resource: A Malaysian case study. Renewable and sustainable energy reviews, 14(2), 798-805. [CrossRef]
- Asthana, A. N. (2014). Profitability Prediction in Cattle Ranches in Latin America: A Machine Learning Approach. Global Veterinaria, 13(4), 473-495.
- Asthana, A. N. (2014). Thirty years after the cataclysm: toxic risk management in the chemical industry. Journal of Toxicological Sciences, 6(1), 01-08.
- Bhushan, S., Rana, M. S., Nandan, N., & Prajapati, S. K. (2019). Energy harnessing from banana plant wastes: A review. Bioresource Technology Reports, 7, 100212. [CrossRef]
- Asthana, A. N. (2015). Sustainable Fisheries Business in Latin America: Linking in to Global Value Chain. World Journal of Fish and Marine Sciences, 7(3), 175-184.
- Asthana, A. N. (2022). Impact of mindfulness on irrigation water consumption. Frontiers in Water, 4. [CrossRef]
- Gumisiriza, R., Hawumba, J. F., Okure, M., & Hensel, O. (2017). Biomass waste-to-energy valorisation technologies: a review case for banana processing in Uganda. Biotechnology for biofuels, 10, 1-29. [CrossRef]
- Fernandes, E. R. K., Marangoni, C., Souza, O., & Sellin, N. (2013). Thermochemical characterization of banana leaves as a potential energy source. Energy conversion and management, 75, 603-608. [CrossRef]
- Asthana, A. N. (2023). Wastewater Management through Circular Economy: A Pathway Towards Sustainable Business and Environmental Protection. Advances in Water Science, 34(3), 87-98.
- Singh, S. S. (2022). Mergers and Acquisitions: Implications for public enterprises in developing countries. Public Enterprise, 26(1), 43-52. [CrossRef]
- Asthana, A. N., & Tavželj, D. (2022). International Business Education Through an Intergovernmental Organisation. Journal of nternational Business Education, 17, 247-266.
- Singh, S. S. (2023). Using Natural Experiments in Public Enterprise Management, Public Enterprise, 27(1), 52-63. [CrossRef]
- Asthana, A. N. (2023) Determinants of Cultural Intelligence of Operations Management Educators. The Seybold Report, 18(6), 789-800.
- Rincón-Catalán, N. I., Cruz-Salomón, A., Sebastian, P. J., Pérez-Fabiel, S., Hernández-Cruz, M. D. C., Sánchez-Albores, R. M.,... & Nájera-Aguilar, H. A. (2022). Banana waste-to-energy valorization by microbial fuel cell coupled with anaerobic digestion. Processes, 10(8), 1552. [CrossRef]
- Awedem Wobiwo, F., Happi Emaga, T., Fokou, E., Boda, M., Gillet, S., Deleu, M.,... & Gerin, P. A. (2017). Comparative biochemical methane potential of some varieties or residual banana biomass and renewable energy potential. Biomass Conversion and Biorefinery. [CrossRef]
- Asthana, A. N. (2011). Entrepreneurship and Human Rights: Evidence from a natural experiment. African Journal of Business Management, 5(3), 9905-9911.
- Abdullah, N., Sulaiman, F., & Taib, R. M. (2013, May). Characterization of banana (Musa spp.) plantation wastes as a potential renewable energy source. In AIP Conference Proceedings (Vol. 1528, No. 1, pp. 325-330). American Institute of Physics.Asthana, A. N. (2023). Reskilling. International Journal of Business and Emerging Markets, 15(3), 267-286.
- Velásquez-Arredondo, H. I., & Ruiz-Colorado, A. A. (2010). Ethanol production process from banana fruit and its lignocellulosic residues: energy analysis. Energy, 35(7), 3081-3087. [CrossRef]
- Emaga, T. H., Bindelle, J., Agneesens, R., Buldgen, A., Wathelet, B., & Paquot, M. (2011). Ripening influences banana and plantain peels composition and energy content. Tropical animal health and production, 43, 171-177. [CrossRef]
- Saxena, N. C. (2021). Yogic Science for Human Resource Management in Public Enterprises. Public Enterprises 25(1-2), 27-38. [CrossRef]
- Asthana, A., & Asthana, A. N. (2012). Yogic science for human Resource management in business. World Applied Sciences Journal, 19(1), 120–130.
- de Souza, J. V. B., Perazzini, H., Lima-Corrêa, R. A., & Borel, L. D. (2024). Combined infrared-convective drying of banana: Energy and quality considerations. Thermal Science and Engineering Progress, 48, 102393. [CrossRef]
- Hossain, A. B. M. S., Ahmed, S. A., Alshammari, A. M., Adnan, F. M., Annuar, M. S. M., Mustafa, H., & Hammad, N. (2011). Bioethanol fuel production from rotten banana as an environmental waste management and sustainable energy. Afr J Microbiol Res, 5(6), 586-598.
- Asthana, A. N. (2003). Decentralisation and supply efficiency: the case of rural water supply in Central India. Journal of Development Studies, 39(4), 148-159. [CrossRef]
- Gundogmus, E. (2013). Energy use pattern and econometric models of banana production. Актуальні прoблеми екoнoміки, (3), 233-242.Gonzales, C. (2023). Privatisation of water: New perspectives and future challenges, Public Enterprise, 27(1), 26-38. [CrossRef]
- Asthana, A. N. (2023). Prosocial behavior of MBA students: The role of yoga and mindfulness. Journal of Education for Business, 98(7), 378-386. [CrossRef]
- Selvarajoo, A., Muhammad, D., & Arumugasamy, S. K. (2020). An experimental and modelling approach to produce biochar from banana peels through pyrolysis as potential renewable energy resources. Modeling Earth Systems and Environment, 6, 115-128. [CrossRef]
- Mohan, S. (2021). Non-tariff measures a trade barrier for developing countries’ agricultural processed products exports. Public Enterprise, 25(1-2), 1-17. [CrossRef]
- Tadesse, M. G., Kasaw, E., Fentahun, B., Loghin, E., & Lübben, J. F. (2022). Banana peel and conductive polymers-based flexible supercapacitors for energy harvesting and storage. Energies, 15(7), 2471. [CrossRef]
|
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).