A Handheld Multispectral Device for Assessing Leaf Nitrogen Concentrations in Maize

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<sup>-1</sup> 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 (R<sup>2</sup> = 0.64) at stage V10. In the validation analysis, the MSPAT presented an R<sup>2</sup> of 0.79, showing performance superior to that of SPAD-502, which achieved an R<sup>2</sup> 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 (R<sup>2</sup> = 0.88, RMSE = 1.94 and MAE = 1.28). When using the MSPAT, PLSR (R<sup>2</sup> = 0.75, RMSE = 2.77 and MAE = 2.26) exhibited values of metrics similar to those for PCR (R<sup>2</sup> = 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.

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Journal
Sensors
Published
2025-06-24
DOI
https://doi.org/10.3390/s25133929
Citations
4
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
6.87

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article

A Handheld Multispectral Device for Assessing Leaf Nitrogen Concentrations in Maize

Adunias dos Santos Teixeira, Luís Clênio Jário Moreira, Ricardo Emílio Ferreira Quevedo Nogueira, Sharon Gomes Ribeiro et al.
4 citations
Sensors
Remote Sensing in Agriculture
6.87
article

A Handheld Multispectral Device for Assessing Leaf Nitrogen Concentrations in Maize

Adunias dos Santos Teixeira, Luís Clênio Jário Moreira, Ricardo Emílio Ferreira Quevedo Nogueira, Sharon Gomes Ribeiro, Felipe Hermínio Meireles Nogueira, Odílio Coimbra da Rocha Neto, Fernando Bezerra Lopes
article en
4 citations

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. 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<sup>-1</sup> 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 (R<sup>2</sup> = 0.64) at stage V10. In the validation analysis, the MSPAT presented an R<sup>2</sup> of 0.79, showing performance superior to that of SPAD-502, which achieved an R<sup>2</sup> 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 (R<sup>2</sup> = 0.88, RMSE = 1.94 and MAE = 1.28). When using the MSPAT, PLSR (R<sup>2</sup> = 0.75, RMSE = 2.77 and MAE = 2.26) exhibited values of metrics similar to those for PCR (R<sup>2</sup> = 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.

SensorsVol. 25(13)
Universidade Federal do Ceará (BR), Instituto Federal de Educação, Ciência e Tecnologia do Ceará (BR)
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Openalex Percentile: Top 4%
Remote Sensing in Agriculture
6.87
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