New approach to estimate macro and micronutrients in potato plants based on foliar spectral reflectance

Abstract

Tissue testing used to assess the chemical contents in potato plants is considered laborious, time-consuming, destructive, and expensive. Ground-based sensors have been assessed to provide efficient information on nitrogen using leaf canopy reflectance. In potatoes, however, the main organ required for tissue testing is the petiole to estimate the elements of all nutrients. This research aims to assess whether there is a correlation between the chemical contents of potato petioles and leaf spectrum, and to examine whether the spectrum of dried or fresh leaves have higher correlation values. Petiole chemical contents of all elements were tested as a reference point. Leaves were split equally into dried and fresh groups for spectral analysis (400–2500 nm). Lasso Regression models were built to estimate concentrations in comparison to actual values. The performances of the model were tested using the Ratio of (standard error of) Prediction to (standard) Deviation (RPD). All elements showed reasonable to excellent RPD values except for sodium. All elements showed higher correlation in the dried testing mode except for nitrogen and potassium. The models showed that the most significant wavebands were in the visible and very near infrared range (400–1100 nm) for all macronutrients except magnesium and sulfur, while all micronutrients had the most significant wavebands in full range (400–2500 nm) with a common significant waveband at 1932 nm. The results show high potentials of a new approach to estimate potato plant elements based on foliar spectral reflectance.

Publication DOI: https://doi.org/10.1016/j.compag.2022.107074
Divisions: College of Engineering & Physical Sciences
Additional Information: © 2022, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Publication ISSN: 1872-7107
Last Modified: 14 May 2024 07:29
Date Deposited: 20 May 2022 12:27
Full Text Link:
Related URLs: https://www.sci ... 16816992200391X (Publisher URL)
PURE Output Type: Article
Published Date: 2022-07
Published Online Date: 2022-05-28
Accepted Date: 2022-05-18
Authors: Abukmeil, Reem
Al-Mallahi, Ahmad
Campelo, Felipe (ORCID Profile 0000-0001-8432-4325)

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