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Performance Assessment of a Sensor-Based Variable-Rate Real-Time Fertilizer Applicator for Rice Crop

Author

Listed:
  • Hasan Mirzakhaninafchi

    (Department of Agricultural Machinery and Technologies Engineering, Faculty of Agriculture, Ataturk University, Erzurum 25240, Turkey)

  • Manjeet Singh

    (Department of Farm Machinery and Power Engineering, College of Agricultural Engineering and Technology (COAET), Punjab Agricultural University (PAU), Ludhiana 141004, India)

  • Anoop Kumar Dixit

    (Department of Farm Machinery and Power Engineering, College of Agricultural Engineering and Technology (COAET), Punjab Agricultural University (PAU), Ludhiana 141004, India)

  • Apoorv Prakash

    (Department of Farm Machinery and Power Engineering, College of Agricultural Engineering and Technology (COAET), Punjab Agricultural University (PAU), Ludhiana 141004, India)

  • Shikha Sharda

    (Department of Farm Machinery and Power Engineering, College of Agricultural Engineering and Technology (COAET), Punjab Agricultural University (PAU), Ludhiana 141004, India)

  • Jugminder Kaur

    (Department of Farm Machinery and Power Engineering, College of Agricultural Engineering and Technology (COAET), Punjab Agricultural University (PAU), Ludhiana 141004, India)

  • Ali Mirzakhani Nafchi

    (Precision Agriculture Extension, Raven Precision Agriculture Center, South Dakota State University, Brookings, SD 57007, USA)

Abstract

Variable-rate technology (VRT) may reduce input costs, increase crop productivity and quality, and help to protect the environment. The present study was conducted to evaluate the performance of a variable-rate fertilizer applicator for rice ( Oryza sativa L.). Three replications were conducted, each of which was divided into four plots. Field performance of the system was assessed at different nitrogen levels (N1 to N4, i.e., 75, 125, 175, 225 kg ha −1 ), growth stages (tillering, panicle initiation, heading), and heights (40, 60, 80, 100 cm) of the sensor from the crop canopy. Fertilizer rate was at minimum 12.59 kg ha −1 at 10 rpm of drive-shaft rotational speed and at maximum 50.41 kg ha −1 at 40 rpm. The system response time was within the range of 3.53 to 4.93 s, with overall error ranging between 0.83% to 4.92%. Across different growth stages, when fertilizer rate was increased from N1 to N4, NDVI increased from 0.49 to 0.69. Hence, drive-shaft rotational speed is decreased from 25 to 7 rpm to shift the application rate from 30.83 to 9.15 kg ha −1 . There was a 45% reduction in total fertilizer rate applied by the system, with respect to the recommended rate.

Suggested Citation

  • Hasan Mirzakhaninafchi & Manjeet Singh & Anoop Kumar Dixit & Apoorv Prakash & Shikha Sharda & Jugminder Kaur & Ali Mirzakhani Nafchi, 2022. "Performance Assessment of a Sensor-Based Variable-Rate Real-Time Fertilizer Applicator for Rice Crop," Sustainability, MDPI, vol. 14(18), pages 1-25, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11209-:d:909075
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    References listed on IDEAS

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    1. Muhammad Nurfaiz Abd. Kharim & Aimrun Wayayok & Ahmad Fikri Abdullah & Ahmad Fikri Abdullah, 2020. "Effect Of Variable Rate Application On Rice Leaves Burn And Chlorosis In System Of Rice Intensification," Malaysian Journal of Sustainable Agriculture (MJSA), Zibeline International Publishing, vol. 4(2), pages 66-70, March.
    2. Sharma, Vasudha & Irmak, Suat, 2021. "Comparative analyses of variable and fixed rate irrigation and nitrogen management for maize in different soil types: Part I. Impact on soil-water dynamics and crop evapotranspiration," Agricultural Water Management, Elsevier, vol. 245(C).
    3. Mohammad Rokhafrouz & Hooman Latifi & Ali A. Abkar & Tomasz Wojciechowski & Mirosław Czechlowski & Ali Sadeghi Naieni & Yasser Maghsoudi & Gniewko Niedbała, 2021. "Simplified and Hybrid Remote Sensing-Based Delineation of Management Zones for Nitrogen Variable Rate Application in Wheat," Agriculture, MDPI, vol. 11(11), pages 1-24, November.
    4. Bertrand Hirel & Thierry Tétu & Peter J. Lea & Frédéric Dubois, 2011. "Improving Nitrogen Use Efficiency in Crops for Sustainable Agriculture," Sustainability, MDPI, vol. 3(9), pages 1-34, September.
    5. Nahry, A.H. El & Ali, R.R. & Baroudy, A.A. El, 2011. "An approach for precision farming under pivot irrigation system using remote sensing and GIS techniques," Agricultural Water Management, Elsevier, vol. 98(4), pages 517-531, February.
    6. Xu, Junzeng & Peng, Shizhang & Yang, Shihong & Wang, Weiguang, 2012. "Ammonia volatilization losses from a rice paddy with different irrigation and nitrogen managements," Agricultural Water Management, Elsevier, vol. 104(C), pages 184-192.
    7. Egidijus Šarauskis & Marius Kazlauskas & Vilma Naujokienė & Indrė Bručienė & Dainius Steponavičius & Kęstutis Romaneckas & Algirdas Jasinskas, 2022. "Variable Rate Seeding in Precision Agriculture: Recent Advances and Future Perspectives," Agriculture, MDPI, vol. 12(2), pages 1-24, February.
    8. Anna Vatsanidou & Spyros Fountas & Vasileios Liakos & George Nanos & Nikolaos Katsoulas & Theofanis Gemtos, 2020. "Life Cycle Assessment of Variable Rate Fertilizer Application in a Pear Orchard," Sustainability, MDPI, vol. 12(17), pages 1-25, August.
    9. Jelle Van Loon & Alicia B. Speratti & Louis Gabarra & Bram Govaerts, 2018. "Precision for Smallholder Farmers: A Small-Scale-Tailored Variable Rate Fertilizer Application Kit," Agriculture, MDPI, vol. 8(4), pages 1-14, March.
    10. Hasan Mirzakhaninafchi & Manjeet Singh & Vishal Bector & O. P. Gupta & Rajvir Singh, 2021. "Design and Development of a Variable Rate Applicator for Real-Time Application of Fertilizer," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
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    Cited by:

    1. Ankit Sharma & Apoorv Prakash & Shiva Bhambota & Santosh Kumar, 2025. "Investigations of precision agriculture technologies with application to developing countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(7), pages 15135-15171, July.

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