ORIGINAL RESEARCH article
Front. Environ. Sci.
Sec. Environmental Informatics and Remote Sensing
This article is part of the Research TopicPlant Phenotyping for AgricultureView all 23 articles
Analysis of Spectral Signatures and Vegetation Indices to Assess the Response of Faba Bean Plants to Varying Zinc Levels under Sandy Soil Conditions
Provisionally accepted
- 1National Authority for Remote Sensing & Space Sciences, El-Nozha El-Gedida, Egypt
- 2National Research Centre, Ad Doqi, Egypt
- 3Faculty of Agriculture, Tanta University, Tanta, Egypt
- 4Universidad de Cordoba, Córdoba, Spain
- 5King Saud University, Riyadh, Saudi Arabia
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Zinc (Zn) deficiency is a major limiting factor for crop productivity, particularly in sandy soils where nutrient retention and bioavailability are poor. The field experiment was conducted at the Agricultural Experimental Station, Cairo University (Giza, Egypt) during the 2022–2024 winter seasons. This study aimed to analyze the spectral responses of faba bean (Vicia faba L.) under different foliar Zn concentrations (0, 0.5, 1.0, 1.5, and 2.0 g L⁻¹ ZnSO₄·7H₂O) using a Randomized Complete Block Design (RCBD) with three replications, and to identify vegetation indices sensitive to Zn nutrition. Growth traits, biochemical attributes, seed yield, hyperspectral reflectance, and soil spectral properties were integrated to establish robust vegetation–soil indicators. Foliar Zn application increased chlorophyll content by 24.5%, protein by 18.3%, and seed yield by 27.6% compared with the control (p ≤ 0.05). Results revealed that foliar Zn application significantly enhanced chlorophyll content, protein accumulation, soluble sugars, and seed yield, with the optimum response observed at 2.0 g L⁻¹. Spectral signatures demonstrated that Zn enrichment decreased red reflectance (~670 nm), sharpened the red-edge slope (700–750 nm), and increased near-infrared reflectance (~800 nm), indicating improved canopy structure and photosynthetic activity. Vegetation indices such as Normalized Difference Vegetation Index (NDVI), Green NDVI (GNDVI), Photochemical Reflectance Index (PRI), Normalized Difference Red-Edge Index (NDRE), Red-Edge Position (REP), and Modified Chlorophyll Absorption Ratio Index (MCARI) were highly responsive to Zn levels, showing strong correlations with physiological traits and closely aligned with growth and yield performance. Soil-based spectral indices, including the Clay Ratio Index (CRI) and the Normalized Difference Soil Index (NDSI), also differentiated among soil samples, linking soil spectral features with Zn-associated crop responses. These findings confirm that hyperspectral reflectance and derived indices provide reliable, non-destructive tools for monitoring Zn nutrition in faba bean. The integration of spectral traits with agronomic and biochemical data emphasizes the potential of hyperspectral sensing for optimizing micronutrient management in sandy soils. This is a provisional file, not the final typeset article Moreover, the outcomes highlight the role of hyperspectral tools in precision agriculture, enabling site-specific nutrient strategies that enhance productivity, resource-use efficiency, and sustainable food security.
Keywords: faba bean, Zinc fertilization, Hyperspectral reflectance, vegetation indices, Soil indices, sandy soils, precision agriculture
Received: 17 Sep 2025; Accepted: 24 Nov 2025.
Copyright: © 2025 Khdery, El-Metwally, Shokr, Meroño de Larriva and Aldosari. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Ghada Khdery
Ali Abdullah Aldosari
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.