Sustainable Agriculture in the Digital Era: Balancing Profitability and Environmental Stewardship
Konathala Kusumavathi
PGDM-Rural Management Programme, Xavier Institute of Social Service, Ranchi, Jharkhand, India, Email: [email protected]
ABSTRACT:
Agriculture is continuously facing different critical challenges in controlling pests, weeds, and pathogens across different spatio-temporal scales of crop growth and development. The modern agricultural practices create a serious threat of depleting natural resources and cause environmental pollution. Besides that, absolute reliance on and injudicious use of agrochemicals, like pesticides, herbicides, and fungicides, have emerged, raising concerns about the sustainability of agroecosystems and human health. Different transformative approaches, including the integration of the Internet of Things, artificial intelligence, remote sensing, machine learning, and precision farming with drones, sensors, and robots, are broadly under the digitization of agriculture. Digitization of agriculture provides real-time and site-specific solutions, thereby maximizing use efficiency of resources and ensuring economic viability with ecological resilience. The comprehensive approach to the sustainability of digital agriculture assures work accessibility and efficiency of reduction of agricultural labour. The article mainly focuses on the applications of integrated IoT and smart sensors for farming, along with a bibliometric analysis on artificial intelligence in agriculture. The widespread adoption of IoT enabled smart farming depends on supportive economic policies, data encryption, and strengthening capacity-building programs. The concept of digitalization in sustainable agriculture is not about increasing production, but it’s about optimizing the on-farm and off-farm resources by leveraging the advanced technologies and enhancing economic profitability with environmental stewardship.
Keywords: Digitalization, Internet of Things, Artificial intelligence, Sensors, Sustainability.
DOI: https://doi.org/10.70994/jjdms.11173.11191
FULL TEXT:
REFERENCES:
Alaoui, A., Barão, L., Ferreira, C. S. S., & Hessel, R. (2022). An overview of sustainability assessment frameworks in agriculture. Land, 11(4), 537. doi:10.3390/land11040537
Almaraz, M. J., Roberto, R., de Jesus Romero-Troncoso, R. G., Guevara- Gonzalez, L. M., Contreras-Medina, R. V., Carrillo-Serrano, R. A., Osornio-Rios, C., Duarte-Galvan, M. A., Rios-Alcaraz, I., & Torres-Pacheco. (2010). FPGA-based fused smart sensor for real-time plant-transpiration dynamic estimation. Sensors, 10 (9), 8316–8331, doi:10.1016/j.compag.2013.04.009.
Balafoutis, A., Beck, B., Fountas, S., Vangeyte, J., Wal, T., Soto, I., Gómez Barbero, M., Barnes, A., & Eory, V. (2017). Precision agriculture technol ogies positively contributing to GHG emissions mitigation, farm productivity and economics. Sustainability, 9(8), 1339–1367. doi:10.3390/su9081339
Basso, B., & Antle, J. (2020). Digital agriculture to design sustainable agricultural systems. Nat Sustain, 3, 254–256. doi:10.1038/ s41893-020-0510-0.
Da Silveira, F., Lermen, F. H., & Amaral, F. G. (2021). An overview of agriculture 4.0 development: Systematic review of descriptions, technologies, barriers, advantages, and disadvantages. Computers and Electronics in Agriculture, 189, 106405, doi:10.1016/j.compag.2021.106405
Daosawang, W., Wongkalasin, K., & Katewongsa, N. (2020). A study sound absorption for ripeness and unripe classification of watermelon. In 2020 8th International Electrical Engineering Congress (iEECON) (Conference paper), Chiang Mai, Thailand, 1–4. doi:10.1109/iEECON48109.2020.229521
Del Río Castro, G., González Fernández, M. C., & Uruburu Colsa, Á. (2021). Unleashing the convergence amid digitalization and sustainability towards pursuing the sustainable development goals (SDGs): A holistic review. Journal of Cleaner Production, 280, 122204. doi:10.1016/j.jclepro.2020.122204
Dong, K., Wang, Y., Zhang, R., Wang, Z., Zhao, X., Chang, Z., Lu, B., & Zhao, Q. (2023) Flexible and shape-morphing plant sensors designed for microenvironment temperature monitoring of irregular surfaces. Advanced Materials Technologies, 8(4), 2201204, doi:10.1002/admt.202201204.
Ehlers, M., Huber, R., & Finger, R. (2021). Agricultural policy in the era of digitalisation. Food Policy, 100:102019. doi:10.1016/j. foodpol.2020.102019
FAO. (2022). SDG indicator 2.4.1 metadata. Retrieved from https://unstats.un.org/sdgs/metadata/files /Metadata-02-04-01.pdf
Freidenreich, A., Barraza, G., Jayachandran, K., & Khoddamzadeh, A. A. (2019). Precision agriculture application for sustainable nitrogen management of Justicia brandegeana using optical sensor technology. Agriculture, 9 (5), 98. doi:10.3390/agriculture9050098.
Grogan, A. (2012). Smart farming. Engineering & amp; Technology, 7, 38–40. doi:10.1049/et.2012.0601
Guo, J., Xue, H., Feng, P., & Yang, Y. (2025). Efficiency and resilience: Common and differentiated priorities for agricultural sustainable development goals. Journal of Cleaner Production, 532, 2025. 146965. doi:10.1016/j.jclepro.2025.146965
Hemmat, A., Binandeh, A. R., Ghaisari, J., & Khorsandi, A. (2013). Development and field testing of an integrated sensor for on-the-go measurement of soil mechanical resistance. Sensors and Actuators A: Physical, 198, 61–68, doi:10.1016/j. sna.2013.04.027.
Ingram, J., Maye, D., Bailye, C., Barnes, A., Bear, C., Bell, M., Cutress, D., Davies, L., de Boon, A., Dinnie, L., Gairdner, J., Hafferty, C., Holloway, L., Kindred, D., Kirby, D., Leake, B., Manning, L., Marchant, B., Morse, A., Oxley, S., & Wilson, L. (2022). What are the priority research questions for digital agriculture? Land Use Policy, 114, 105962. doi:10.1016/j.landusepol.2021.105962
Islam, M. Z., & Wang, S. (2023). Exploring the unique characteristics of environmental sustainability in China: Navigating future challenges. Chinese Journal of Population, Resources and Environment, 21 (1), 37–42. doi:10.1016/j.cjpre.2023.03.004
Jan van Eck, N., & Waltman, L. (2023). Manual for VOSviewer version 1.6.20. https://www.vosviewer.com/documentation/Manual_VOSviewer_1.6.20.pdf.
Jiang, J., Zhang, S., Wang, B., Ding, H., & Wu, Z. (2020). Hydroprinted liquid-alloy-based morphing electronics for fast-growing/tender plants: from physiology monitoring to habit manipulation. Small, 16(39), e2003833. doi:10.1002/ smll.202003833.
Jin, B., Jiang, D., Xiong, J., Chen, L., & Li, Q. (2018). Data privacy protection mechanism based on reliability and homomorphic encryption. IEEE, 6,51140–51150, doi:10.1109/ACCESS.2018.2869575.
Jones, E. O., Tham-Agyekum, E. K., Ankuyi, F., Ankrah, D. A., Akaba, S., Shafiwu, A. B., & Richard, F. N. (2023). Mobile agricultural extension delivery and climate-smart agricultural practices in a time of a pandemic: Evidence from southern Ghana. Environ. Sustain. Indic, 19, 100274. doi:10.1016/j. indic.2023.100274
Jouanjean, M. (2019). Digital opportunities for trade in the agriculture and food sectors. OECD food, agriculture and fisheries papers, no. 122. Paris: OECD Publishing. doi:10.1787/91c40e07-en
Jungblut, Sarah-Indra. (2024). We investigate the role digitalisation plays in sustainable agriculture. Retrieved from https://en.reset.org/sustainable-agriculture-what-role-does-digitalisation play/?gad_source=1&gad_campaignid=23140286608&gbraid=0AAAAAD27btlLlRdk9gXJCvE0WkoaNn3U&gclid=CjwKCAiA9aPKBhBhEiwAyz82J2V1KSh1SI77NYuRgh4tLfDlcP396sH6rzywRoUVmN6cz95Bku3xoCrg8QAvD_BwE
Kadomtseva, M. Y. (2022). Theoretical and methodological aspects of ensuring the sustainable development of agro-food systems. Izvestiâ Saratovskogo Universiteta Novaâ Seriâ, 22 (3), 277–86. doi: 10.18500/1994-2540-2022-22-3-277-286
Kamilaris, A., Kartakoullis, A., & Prenafeta-Boldú, F. (2017). A review on the practice of big data analysis in agriculture. Comput Electron Agric, 143, 23-37. doi:10.1016/j.compag.2017.09.037
Khan, N., Ray, R. L., Kassem, H. S., & Zhang, S. (2022). Mobile internet technology adoption for sustainable agriculture: Evidence from wheat farmers, Appl. Sci, 12, 4902. doi:10.3390/APP12104902.
Kim, M.Y., Lee, J. W., Park, D. J., Lee, J. Y., Myung, N. V., & Kwon, S. W. (2021). Highly stable potentiometric sensor with reduced graphene oxide aerogel as a solid contact for detection of nitrate and calcium ions. Journal of Electroanalytical Chemistry, 897, 115553. doi:10.1016/j.jelechem.2021.115553
Lan, L., Le, X., Dong, H., Xie, J., Ying, Y., & Ping, P. (2020). One-step and large-scale fabrication of flexible and wearable humidity sensor based on laser-induced graphene for real-time tracking of plant transpiration at bio-interface. Biosens. Bioelectron, 165, 112360. doi:10.1016/j.bios.2020.112360.
Li, Z., Liu, Y., Hossain, O., Paul, R., Yao, S., Wu, S., Ristaino, J.B., Zhu, Y., & Wei, Q. (2021). Real-time monitoring of plant stresses via chemiresistive profiling of leaf volatiles by a wearable sensor. Matter, 4 (7), 2553–2570. doi:10.1016/j. matt.2021.06.009.
Mohanty, S. P., Hughes, D. P., & Salathe, M. (2016). Using deep learning for image-based plant disease detection. Front. Plant Sci, 7 215232. doi:10.3389/FPLS.2016.01419/BIBTEX.
Nguyen, T. T., Grote, U., Neubacher, F., Do, M. H., & Paudel, G. P. (2023). Security risks from climate change and environmental degradation: Implications for sustainable land use transformation in the global south. Curr. Opin. Environ. Sustain, 63, 101322.
Oukaira, A., Benelhaouare, A. Z., Kengne, E., & Lakhssassi, A. (2021). FPGA-embedded smart monitoring system for irrigation decisions based on soil moisture and temperature sensors. Agronomy 11(9), 1881. doi:10.3390/ agronomy11091881.
Pherson, J. M., Slavinsky, A. V., Olbrisch, M., Schöbel, P., Dönitz, E., Mouratiadou, I., & Helming, K. (2022). Future agricultural systems and the role of digitalization for achieving sustainability goals. A review. Agronomy for Sustainable Development, 42, 70. doi:10.1007/s13593-022-00792-6
Poppe, K., Wolfert, S., Verdouw, C., & Verwaart, T. (2013). Information and com munication technology as a driver for change in agri-food chains. EuroChoices, 12(1), 60–65. doi:10.1111/1746-692X.12022
Potyrailo, R. A., Nagraj, N., Tang, Z, Mondello, F. J., Surman, C., & Morris, W. (2012) Battery- free radio frequency identification (RFID) sensors for food quality and safety. J. Agric. Food Chem, 60, 8535–8543. doi:10.1021/jf302416y
Rajak, P., Ganguly, A., Adhikary, S., & Bhattacharya, S. (2023). Internet of Things and smart sensors in agriculture: Scopes and challenges. Journal of Agriculture and Food Research, 14, 100776. doi:10.1016/j.jafr.2023.100776.
Ranjbari, M., Esfandabadi, Z. S., Zanetti, M. C., Scagnelli, S. D., Siebers, P. O., Aghbashlo, M., Peng, W., Quatraro, F., & Tabatabaei, M. (2021). Three pillars of sustainability in the wake of COVID-19: A systematic review and future research agenda for sustainable development. J. Clean. Prod, 297, 126660. doi:10.1016/j.jclepro.2021.126660
Ritter, T., & Pedersen, C. L. (2020). Digitization capability and the digitalization of business models in business-to business firms: Past, present, and future. Industrial Marketing Management, 86, 180–190. doi:10.1016/j.indmarman.2019.11.019
Rose, D. C., & Chilvers, J. (2018). Agriculture 4.0: Broadening Responsible Innovation in an Era of Smart Farming. Frontiers in Sustainable Food Systems, 2, 87. doi:10.3389/fsufs.2018.00087
Rotz, S., Gravely, E., Mosby, I., Duncan, E., Finnis, E., Horgan, M., LeBlanc, J., Martin, R., Neufeld, H.T., Nixon, A., Pant, L., Shalla, V., & Fraser, E. (2019). Automated pastures and the digital divide: How agricultural technol ogies are shaping labour and rural communities. J Rural Stud, 68: 112–122. doi:10.1016/j.jrurstud.2019.01.023
Roy, S., Arshad, F., Eissa, S., Safavieh, M., Alattas, S. G., Ahmed, M, U., & Zourob, M. (2022). Recent developments towards portable point-of-care diagnostic devices for pathogen detection. Sens. Diagn, 1, 87–105.
Schoor, M., Arenas-Salazar, A. P., Torres-Pacheco, I., Guevara-González, R. G., & Rico-García, E. (2023). A review of sustainable pillars and their fulfillment in agriculture, aquaculture, and aquaponic production. Sustainability, 15, 7638.
doi:10.3390/su15097638
Singh, B., Sharma, R. K., Jat, M. L., Martin, K. L., & Chandna, P. (2011). Assessment of the nitrogen management strategy using an optical sensor for irrigated wheat. Agron. Sustain. Dev. 31, 589–603. doi:10.1007/s13593-011-0005-5.
Smith, M. (2020). Getting value from artificial intelligence in agriculture. Anim Prod Sci, 60:46–54. doi:10.1071/AN18522
Srivastava, N., Chopra, G., Jain, P., & Khatter, B. (2013). Pest monitor and control system using wireless sensor network with special reference to acoustic device wireless sensor, International Conference on Electrical and Electronics Engineering, Goa (Conference paper). doi:10.4018/978-1-7998-5003-8.ch001
Su, W., Liang, D., & Tan, M. (2021). Microfluidic strategies for sample separation and rapid detection of food allergens. Trends Food Sci. Technol. 110. 213–225.
Tang, W., Yan, T., Wang, F., Yang, J., Wu, J., Wang, J., & Yue, T. Z. L. (2019). Rapid fabrication of wearable carbon nanotube/graphite strain sensor for real-time monitoring of plant growth, Carbon, 147, 295–302. doi:10.1016/j. carbon.2019.03.002.
Uddin, J., Hancock, N. H., Smith, R. J., & Foley, J. P. (2013). Measurement of evapotranspiration during sprinkler irrigation using a precision energy budget (Bowen ratio, eddy covariance) methodology. Agric. Water Manag, 116, 89–100. doi:10.1016/j.agwat.2012.10.008
Walter, A., Finger, R., Huber, R., & Buchmann, N. (2017). Smart farming is key to developing sustainable agriculture. Proceedings of the National Academy of Sciences USA 114(24), 6148–6150. doi:10. 1073/pnas.1707462114
Weiss, U., & Biber, P. (2011). Plant detection and mapping for agricultural robots using a 3D LIDAR sensor. Robotics and Autonomous Systems, 59 (5), 265–273. doi:10.1016/j.robot.2011.02.011.
Wiseman, L., Sanderson, J., Zhang, A., & Jakku, E. (2019). Farmers and their data: An examination of farmers’ reluctance to share their data through the lens of the laws impacting smart farming, NJAS – Wageningen. J. Life Sci, 90–91, 100301.
Wolfert, S., Ge, L., Verdouw, C and Bogaardt, M. J. (2017). Big data in smart farming – A review. Agricultural System. 153, 69–80. doi:10.1016/j.agsy.2017.01.023
Yunus, M. A. M., & Mukhopadhyay, S. C. (2011). Novel planar electromagnetic sensors for detection of nitrates and contamination in natural water sources. IEEE Sensor. J, 11 (6), 1440–1447. doi:10.1109/JSEN.2010.2091953
Zamir, M. A., & Sonar, R.M. (2023). Application of internet of things (IoT) in agriculture: A review. 2023 8th International Conference on Communication and Electronics Systems (ICCES) (Conference paper), Coimbatore, India, 425-431. doi:10.1109/ICCES57224.2023.10192761.
Zoll, U., Brümmer, C., Schrader, F., Ammann, C., Ibrom, A., Flechard, C. R., Nelson, D. D., Zahniser, M., & Kutsch, W. L. (2016). Surface–atmosphere exchange of ammonia over peatland using QCL-based eddy-covariance measurements and inferential modelling. Atmos. Chem. Phys, 16, 11283–11299. doi:10.5194/acp-16-11283-2016.