IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i13p6211-d1696188.html

Optimizing UAV Spraying for Sustainable Agriculture: A Life Cycle and Efficiency Analysis in India

Author

Listed:
  • Shefali Vinod Ramteke

    (Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Prayagraj 211015, India)

  • Pritish Kumar Varadwaj

    (Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Prayagraj 211015, India)

  • Vineet Tiwari

    (Department of Management Studies, Indian Institute of Information Technology Allahabad, Prayagraj 211015, India)

Abstract

Problem: Agriculture in India faces pressing challenges related to water scarcity, excessive pesticide use, and inefficient energy consumption, impacting both economic sustainability and environmental health. Methodology: This study integrates Life Cycle Assessment (LCA), Data Envelopment Analysis (DEA), Intelligent Management Models (IMMs), and Multi-Criteria Decision Analysis (MCDA) to assess the economic and environmental benefits of UAV-based spraying in Indian agriculture. Data were collected from UAV service providers and field trials in Punjab, Haryana, and Rajasthan. Results: UAV spraying achieved a 70% reduction in water use, 40% reduction in pesticide consumption, and a 50% reduction in CO 2 emissions compared to conventional spraying. DEA results showed higher efficiency scores for UAVs, while IMM optimization achieved 95% pesticide coverage and reduced drift by 80%. Implications: MCDA ranked government subsidies as the most effective policy intervention. These findings support UAV spraying as a viable, scalable solution for climate-smart agriculture in India, offering both productivity and sustainability gains.

Suggested Citation

  • Shefali Vinod Ramteke & Pritish Kumar Varadwaj & Vineet Tiwari, 2025. "Optimizing UAV Spraying for Sustainable Agriculture: A Life Cycle and Efficiency Analysis in India," Sustainability, MDPI, vol. 17(13), pages 1-30, July.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:13:p:6211-:d:1696188
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/13/6211/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/13/6211/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    2. Munda, Giuseppe, 2004. "Social multi-criteria evaluation: Methodological foundations and operational consequences," European Journal of Operational Research, Elsevier, vol. 158(3), pages 662-677, November.
    3. Thiam, Abdourahmane & Bravo-Ureta, Boris E. & Rivas, Teodoro E., 2001. "Technical efficiency in developing country agriculture: a meta-analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 235-243, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Baldos, Uris Lantz C. & Hertel, Thomas W., 2012. "Economics of global yield gaps: A spatial analysis," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124978, Agricultural and Applied Economics Association.
    2. B.C. Okoye & A. Abass & B. Bachwenkizi & G. Asumugha & B. Alenkhe & R. Ranaivoson & R. Randrianarivelo & N. Rabemanantsoa & I. Ralimanana, 2016. "Differentials in technical efficiency among smallholder cassava farmers in Central Madagascar: A Cobb Douglas stochastic frontier production approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1143345-114, December.
    3. Thanh Ngo & Hung V. Vu & Huong Ho & Thuy T. T. Dao & Hai T. H. Nguyen, 2019. "Performance of Fish Farms in Vietnam–Does Financial Access Help Improve Their Cost Efficiency?," IJFS, MDPI, vol. 7(3), pages 1-10, August.
    4. Thanh Ngo & David Tripe & Duc Khuong Nguyen, 2024. "Estimating the productivity of US agriculture: The Fisher total factor productivity index for time series data with unknown prices," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 68(3), pages 701-712, July.
    5. Frija, Aymen & Chebil, Ali & Speelman, Stijn & Buysse, Jeroen & Van Huylenbroeck, Guido, 2009. "Water use and technical efficiencies in horticultural greenhouses in Tunisia," Agricultural Water Management, Elsevier, vol. 96(11), pages 1509-1516, November.
    6. Yeşim Aytop, 2023. "Determination of Energy Consumption and Technical Efficiency of Cotton Farms in Türkiye," Sustainability, MDPI, vol. 15(14), pages 1-14, July.
    7. Chebil, Ali & Frija, Iheb & Bahri, Walid, 2014. "Irrigation water efficiency in wheat production in Chbika (Tunisia):Parametric versus Nonparametric Comparisons," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 15(01), pages 1-14.
    8. Anirban Nandy & Piyush Kumar Singh & Alok Kumar Singh, 2021. "Systematic Review and Meta- regression Analysis of Technical Efficiency of Agricultural Production Systems," Global Business Review, International Management Institute, vol. 22(2), pages 396-421, April.
    9. Watto, Muhammad Arif & Mugera, Amin William, "undated". "Measuring Groundwater Irrigation Efficiency in Pakistan: A DEA Approach Using the Sub-vector and Slack-based Models," Working Papers 144943, University of Western Australia, School of Agricultural and Resource Economics.
    10. Musa, H. Ahmed & Lemma, Z. & Endrias, G., 2015. "Measuring Technical, Economic and Allocative Efficiency of Maize Production in Subsistence Farming: Evidence from the Central Rift Valley of Ethiopia," APSTRACT: Applied Studies in Agribusiness and Commerce, AGRIMBA, vol. 9(3), pages 1-12, December.
    11. Galanopoulos, Konstantinos & Aggelopoulos, Stamatis & Kamenidou, Irene & Mattas, Konstadinos, 2006. "Assessing the effects of managerial and production practices on the efficiency of commercial pig farming," Agricultural Systems, Elsevier, vol. 88(2-3), pages 125-141, June.
    12. Marchetti, Dalmo & Wanke, Peter F., 2019. "Efficiency in rail transport: Evaluation of the main drivers through meta-analysis with resampling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 83-100.
    13. Alene, Arega D. & Manyong, Victor M. & Gockowski, James, 2006. "The production efficiency of intercropping annual and perennial crops in southern Ethiopia: A comparison of distance functions and production frontiers," Agricultural Systems, Elsevier, vol. 91(1-2), pages 51-70, November.
    14. Gelaw, Fekadu, 2013. "Inefficiency and Incapability Gaps as Causes of Poverty: A Poverty Line-Augmented Efficiency Analysis Using Stochastic Distance Function," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 8(2), pages 1-45, August.
    15. Andreu, Monica Lopez & Featherstone, Allen M. & Langemeier, Michael R. & Grunewald, Orlen C., 2006. "Impact of Financial Variables on Production in Kansas Farms Efficiencies," 2006 Annual meeting, July 23-26, Long Beach, CA 21406, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. Houshyar, Ehsan & Azadi, Hossein & Almassi, Morteza & Sheikh Davoodi, Mohammad Javad & Witlox, Frank, 2012. "Sustainable and efficient energy consumption of corn production in Southwest Iran: Combination of multi-fuzzy and DEA modeling," Energy, Elsevier, vol. 44(1), pages 672-681.
    17. Justice G. Djokoto & Ferguson K. Gidiglo & Francis Y. Srofenyoh & Kofi Aaron A-O. Agyei-Henaku & Akua A. Afrane Arthur & Charlotte Badu-Prah & John Fry, 2020. "Sectoral and spatio-temporal differentiation in technical efficiency: A meta-regression," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1773659-177, January.
    18. Hai-Dang Nguyen & Thanh Ngo & Tu DQ Le & Huong Ho & Hai T.H. Nguyen, 2019. "The Role of Knowledge in Sustainable Agriculture: Evidence from Rice Farms’ Technical Efficiency in Hanoi, Vietnam," Sustainability, MDPI, vol. 11(9), pages 1-10, April.
    19. Merkel, Axel & Holmgren, Johan, 2017. "Dredging the depths of knowledge: Efficiency analysis in the maritime port sector," Transport Policy, Elsevier, vol. 60(C), pages 63-74.
    20. Phuc Trong Ho & Michael Burton & Chunbo Ma & Atakelty Hailu, 2022. "Quantifying heterogeneity, heteroscedasticity and publication bias effects on technical efficiency estimates of rice farming: A meta‐regression analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(2), pages 580-597, June.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:13:p:6211-:d:1696188. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.