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Potentiality of Multispectral Vegetation Indexes for Evaluating the Influence of the Sowing Technique on Durum Wheat Cultivation Density

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Safety, Health and Welfare in Agriculture and Agro-Food Systems (SHWA 2023)

Abstract

Crop monitoring using multispectral sensors on board drones is a significant application in the agricultural sector. These sensors capture high-resolution images that can be used to assess crop vigor and health by calculating spectral indices. This enables a quick identification of areas with developmental issues due to biotic or abiotic stresses, facilitating precision agriculture strategies. This study focuses on monitoring the greenness of durum wheat cultivation (Sicily, Italy) from stem elongation to inflorescence emergence, comparing two sowing techniques: conventional (CS) and sod-seeding (SS). Five flight campaigns were conducted using a multispectral sensor mounted on a DJI quadcopter drone. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) were calculated using ArcGIS, assessing potential differences among the sowing techniques. Preliminary results indicate that both vegetation indexes revealed significant differences among sowing techniques, with CS having generally significantly higher values than SS. Both sowing techniques exhibited similar standard deviation values, suggesting their equal effectiveness in durum wheat cultivation. Discrepancies between NDVI and NDRE were observed at high vegetation index values, highlighting the main limitation of NDVI, saturating at high crop development stages. This saturation was not observed in NDRE, becoming an alternative to NDVI when working with high biomass crops.

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References

  1. International Grains Council (IGC). Available online: https://www.igc.int/en/subscriptions/subscription.aspx. Accessed 16 Oct 2023

  2. Yang, H., Reichert, P., Abbaspour, K.C., Zehnder, A.J.B.A.: Water resources threshold and its implications for food security. Environ. Sci. Technol. 37, 3048–3054 (2003)

    Article  Google Scholar 

  3. Liliane, T.N., Charles, M.S.: Factors affecting yield of crops. In: Amanullah (ed.) Agronomy—Climate Change & Food Security. IntechOpen, London (2020)

    Google Scholar 

  4. Cantero-MartÍnez, C., Angás, P., Lampurlanés, J.: Long-term yield and water use efficiency under various tillage systems in Mediterranean rainfed conditions. Ann. Appl. Biol. 150, 293–305 (2007)

    Article  Google Scholar 

  5. Failla, S., Pirchio, M., Sportelli, M., Raffaelli, M., Peruzzi, A.: Evolution of smart strategies and machines used for conservative management of herbaceous and horticultural crops in the Mediterranean basin: a review. Agronomy 11(1), 106 (2021)

    Article  Google Scholar 

  6. Farooq, M., Siddique, K.: Conservation agriculture: concepts, brief history, and impacts on agricultural systems. In: Farooq, M., Siddique, K. (eds.) Conservation Agriculture. Cham, Springer (2015). https://doi.org/10.1007/978-3-319-11620-4_1

    Chapter  Google Scholar 

  7. Zheng, C.-Y., et al.: Effects of tillage practices on water consumption, water use efficiency and grain yield in wheat field. J. Integr. Agric. 13, 2378–2388 (2014)

    Article  Google Scholar 

  8. Jakab, G., et al.: Infiltration and soil loss changes during the growing season under ploughing and conservation tillage. Sustainability 9, 1726 (2017)

    Article  Google Scholar 

  9. Failla, S., Ingrao, C., Arcidiacono, C.: Energy consumption of rainfed durum wheat cultivation in a Mediterranean area using three different soil management. Energy 195, 116960 (2020)

    Article  Google Scholar 

  10. Marszalek, M., Körner, M., Schmidhalter, U.: Prediction of multi-year winter wheat yields at the field level with satellite and climatological data. Comput. Electron. Agric. 194, 106777 (2022)

    Article  Google Scholar 

  11. Sishodia, R.P., Ray, R.L., Singh, S.K.: Applications of remote sensing in precision agriculture: a review. Remote Sens. 12, 3136 (2020)

    Article  Google Scholar 

  12. Calcagno, F., Romano, E., Furnitto, N., Jamali, A., Failla, S.: Remote sensing monitoring of durum wheat under no tillage practices by means of spectral indices interpretation: a preliminary study. Sustainability 14(22), 15012 (2022)

    Article  Google Scholar 

  13. Romano E., Calcagno F., Bisaglia C., Furnitto N., Schillaci G., Failla S.: Application of Spectral Indices for the Evaluation of Conservative Techniques in Crops Management. In: Lecture Notes in Civil Engineering, vol. 337, LNCE, pp. 871–879 (2023). https://doi.org/10.1007/978-3-031-30329-6_89

  14. Kizilgeci, F., Yildirim, M., Islam, M.S., Ratnasekera, D., Iqbal, M.A., Sabagh, A.E.: Normalized difference vegetation index and chlorophyll content for precision nitrogen management in durum wheat cultivars under semi-arid conditions. Sustainability 13, 3725 (2021)

    Article  Google Scholar 

  15. USDA Natural Resources Conservation Service. Available online: https://www.nrcs.usda.gov/resources/education-andteaching-materials/soil-texture-calculator. Accessed 27 Oct 2023

  16. Köppen Climate Classification. Available online: https://www.britannica.com/science/Koppen-climate-classification/Worlddistribution-of-major-climatic-types. Accessed 27 Oct 2023

  17. Servizio Informativo Agrometeorologico Siciliano (SIAS). Available online: http://www.sias.regione.sicilia.it/. Accessed 18 Oct 2023

  18. Cavalaris, C., et al.: Modeling of durum wheat yield based on sentinel-2 imagery. Agronomy 11(8), 1486 (2021)

    Article  Google Scholar 

  19. Pittelkow, C.M., et al.: When does no-till yield more? A global meta-analysis. Field Crop Res 183, 156–168 (2015)

    Article  Google Scholar 

  20. Prabhakara, K., Hively, W.D., McCarty, G.W.: Evaluating the relationship between biomass, percent groundcover and remote sensing indices across six winter cover crop fields in Maryland, United States. Int. J. Appl. Earth Obs. Geoinf. 39, 88–102 (2015)

    Google Scholar 

  21. Wang, Z., Yao, F., Li, W., Wu, J.: Saturation correction for nighttime lights data based on the relative NDVI. Remote Sens. 9(7), 759 (2017)

    Article  Google Scholar 

  22. Rehman, T.H., Borja Reis, A.F., Akbar, N., Linquist, B.A.: Use of normalized difference vegetation index to assess N status and predict grain yield in rice. Agron. J.. J. 111(6), 2889–2898 (2019)

    Article  Google Scholar 

  23. Farias, G.D., et al.: Normalized Difference Vegetation Index (NDVI) for soybean biomass and nutrient uptake estimation in response to production systems and fertilization strategies. Front. Sustain. Food Syst. 6, 959681 (2023)

    Article  Google Scholar 

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Acknowledgement

The research study was funded by the Italian P.O.N. “RICERCA E INNOVAZIONE” 2014 – 2020, Azione II – Obiettivo Specifico 1b – Progetto “Miglioramento delle produzioni agroalimentari mediterranee in condizioni di carenza di risorse idriche–WATER4AGRIFOOD”; by PRIN2020 “DATA-BUS - Digital Agriculture Technology to Achieve data to Build User-friendly Sustainability indicators”; and by the project SAMOTHRACE (E63C22000900006; MUR-PNRR, NextGeneration EU). The authors are very grateful to Dr Marco Frasson for giving hospitality to the experimental tests in his agricultural farm; and for providing agricultural machineries to perform the experimental campaign and for his valuable support during the experimental tests.

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Correspondence to Juan Miguel Ramírez-Cuesta .

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Furnitto, N., Ramírez-Cuesta, J.M., Sottosanti, G., Longo, D., Schillaci, G., Failla, S. (2024). Potentiality of Multispectral Vegetation Indexes for Evaluating the Influence of the Sowing Technique on Durum Wheat Cultivation Density. In: Berruto, R., Biocca, M., Cavallo, E., Cecchini, M., Failla, S., Romano, E. (eds) Safety, Health and Welfare in Agriculture and Agro-Food Systems. SHWA 2023. Lecture Notes in Civil Engineering, vol 521. Springer, Cham. https://doi.org/10.1007/978-3-031-63504-5_32

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  • DOI: https://doi.org/10.1007/978-3-031-63504-5_32

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