In-Season Potato Crop Nitrogen Status Assessment from Satellite and Meteorological Data

Goffart, D.;Abdallah, F. Ben;Curnel, Y.;Planchon, V.;Goffart, J.-P.;et.al.
(2022) Potato Research — Vol. Online (2022), n° 65, p. 729-755 (2022)

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Authors
  • Goffart, D.orcid-logo
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  • Abdallah, F. Ben
    Author
  • Curnel, Y.
    Author
  • Planchon, V.
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  • Goffart, J.-P.orcid-logo
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Abstract
For a conventional potato crop, splitting nitrogen (N) application is recognised as an efficient strategy to improve tuber yield and quality and to mitigate N losses to the environment. This approach requires the assessment of in-season crop N status for decisions on supplemental mineral N fertiliser application. This study focuses on the assessment of potato crop biophysical variables useful to establish crop N status. Field, satellite and meteorological data were collected in farmer’s fields during 3 years (2017– 2019) with contrasted meteorological conditions. Degree days (DD) and water balance from planting date were computed from meteo data, and a selection of relevant vegetation indices (VIs) was derived from Sentinel-2 reflectance. Multiple linear regression (MLR) and random forest regression (RFR) models predicting shoots biomass, shoots N content and shoots N uptake from a combination of meteo and/or satellite-based variables were defined and evaluated. The best combinations integrate DD and two to four VIs and perform with cross-validation RMSE of about 0.38 DM t ha−1, 0.41%, 21 kg ha−1 for MLR and 0.32 DM t ha−1, 0.31%, 19 kg ha−1 for RFR. Despite these performances, MLR was shown to be more robust. From these estimated variables, two methods are proposed to derive total N uptake and nitrogen nutrition index. The most relevant method uses shoots N uptake and biomass. It allows future estimation of in-season supplemental N fertiliser to be applied to reach a targeted tuber yield.
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Citations

Goffart, D., Abdallah, F. B., Curnel, Y., Planchon, V., Defourny, P., & Goffart, J.-P. (2022). In-Season Potato Crop Nitrogen Status Assessment from Satellite and Meteorological Data. Potato Research, Online (2022)(65), 729-755. https://doi.org/10.1007/s11540-022-09545-0 (Original work published 2022)