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Hyperspectral Sensing: Imaging and Applications
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Hyperspectral Sensing: Imaging and Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 1 November 2025 | Viewed by 585

Special Issue Editor

Prof. Dr. A. G. Unil Perera

E-Mail Website
Guest Editor
Department of Physics & Astronomy, Georgia State University, Atlanta, GA 30303, USA
Interests: infrared sensing; nano and microstruture IR devices; medical diagnostics using infrared; plasmonic enhancements; novel materials
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Hyperspectral imaging has emerged as a groundbreaking technology, capturing detailed spectral information across a wide range of wavelengths to enable precise material identification and analysis. Its ability to collect rich spectral data without physical contact makes it a powerful tool across various disciplines, including environmental monitoring, agriculture and food safety, chemical and material characterization, medical and biomedical applications, defense and security, forensic science, and pharmaceutical quality control.

For example, in medicine, hyperspectral imaging is transforming non-invasive diagnostics by enabling early disease detection, tissue analysis, and surgical guidance. In chemical and material sciences, it provides unparalleled insights into molecular composition and structural properties.

This Special Issue, entitle “Hyperspectral Sensing: Imaging and Applications”, highlights the latest advancements in hyperspectral imaging techniques, data processing algorithms, and their multidisciplinary applications. We invite researchers to contribute original studies, reviews, and case studies that explore innovative methodologies, address challenges in spectral data analysis, and demonstrate the transformative potential of this technology in fields ranging from healthcare to environmental sustainability and material science.

Prof. Dr. A. G. Unil Perera
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • hyperspectral imaging
  • remote sensing applications
  • spectral data analysis
  • environmental monitoring
  • medical diagnostics and applications
  • defense and security
  • agriculture and food safety
  • forensic and pharmaceutical quality control

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Published Papers (1 paper)

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Research

18 pages, 18889 KiB  
Article
A Handheld Multispectral Device for Assessing Leaf Nitrogen Concentrations in Maize
by Felipe Hermínio Meireles Nogueira, Adunias dos Santos Teixeira, Sharon Gomes Ribeiro, Luís Clênio Jario Moreira, Odílio Coimbra da Rocha Neto, Fernando Bezerra Lopes and Ricardo Emílio Ferreira Quevedo Nogueira
Sensors 2025, 25(13), 3929; https://doi.org/10.3390/s25133929 - 24 Jun 2025
Viewed by 453
Abstract
This study presents the MSPAT (Multispectral Soil Plant Analysis Tool), a device designed for assessing leaf nitrogen concentrations in maize crops under field conditions. The MSPAT includes the AS7265x sensor, which has 18 bands and covers the spectrum from 410 to 940 nm. [...] Read more.
This study presents the MSPAT (Multispectral Soil Plant Analysis Tool), a device designed for assessing leaf nitrogen concentrations in maize crops under field conditions. The MSPAT includes the AS7265x sensor, which has 18 bands and covers the spectrum from 410 to 940 nm. This device was designed to be portable, using the ESP32 microcontroller and incorporating such functionalities as data storage on a MicroSD card, communication with a smartphone via Wi-Fi, and geolocation of acquired data. The MSPAT was evaluated in an experiment conducted at the Federal University of Ceará (UFC), where maize was subjected to different doses of nitrogen fertiliser (0, 60, 90, 120, 150, and 180 kg·ha−1 N). Spectral readings were taken at three phenological stages (V5, V10, and R2) using the MSPAT, an SPAD-502 chlorophyll meter, and a FieldSpec PRO FR3 spectroradiometer. After the optical measurements were taken, the nitrogen concentrations in the leaves were determined in a laboratory by using the Kjeldahl method. The data analysis included the calculation of normalised ratio indices (NRIs) using linear regression and the application of multivariate statistical methods (PLSR and PCR) for predicting leaf nitrogen concentrations (LNCs). The best performance for the MSPAT index (NRI) was obtained using the 900 nm and the 560 nm bands (R2 = 0.64) at stage V10. In the validation analysis, the MSPAT presented an R2 of 0.79, showing performance superior to that of SPAD-502, which achieved an R2 of 0.70. This confirms the greater potential of the MSPAT compared to commercial equipment and makes it possible to obtain results similar to those obtained using the reference spectroradiometer. The PLSR model with data from the FieldSpec 3 provided important validation metrics when using reflectance data with first-derivative transformation (R2 = 0.88, RMSE = 1.94 and MAE = 1.28). When using the MSPAT, PLSR (R2 = 0.75, RMSE = 2.77 and MAE = 2.26) exhibited values of metrics similar to those for PCR (R2 = 0.75, RMSE = 2.78 and MAE = 2.26). This study validates the use of MSPAT as an effective tool for monitoring the nutritional status of maize to optimize the use of nitrogen fertilisers. Full article
(This article belongs to the Special Issue Hyperspectral Sensing: Imaging and Applications)
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