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May 20, 2026npj Nanophotonics0 citationsOpen Access

Broadband Hybrid Multispectral Sensing for Ripeness Monitoring

ARAbdel K. Ruvalcaba-PerezGSGunter SiessFCFernando Castaño

Key Points

  • This research aims to develop a broadband multispectral sensor for monitoring apple ripeness to optimize harvest timing without destructive testing.
  • Developed an integrated sensor array combining Silicon and GaSb photodetectors.
  • Utilized 19 bandpass dielectric filters to achieve spectral selectivity from 400–2300 nm.
  • Assessed weekly spectral measurements from multiple apple cultivars to derive data.
  • Demonstrated effective resolution of spectral signatures tied to carotenoids, chlorophylls, starch, and moisture content.
  • Enabled the evaluation of optimal harvest times, reducing reliance on chemical analysis.
  • Highlighted the potential for large-scale deployment in agricultural monitoring, improving yield and minimizing post-harvest losses.

Abstract

Abstract Spectral sensing has been widely employed in applications ranging from satellite-based remote imaging to biomedicine and precision agriculture. However, broader deployment has been constrained by the complexity and cost of traditional hyperspectral instrumentation. In recent years, efforts have shifted toward the development of compact spectrometers targeting specific spectral regions, often at the expense of broadband analytical capability. In this work, we present the proof-of-concept for an integrated multispectral sensor array for broadband spectral applications, combining Silicon- and GaSb-based photodetectors. Spectral selectivity across the VIS/NIR/SWIR spectral domain (400–2300 nm) is enabled with 19 bandpass dielectric filters in a combined active footprint of 2.02 mm². The sensor assessed in this work was specifically designed to evaluate the optimal harvest time based on weekly spectral measurements from multiple apple cultivars, without the need for destructive chemical analysis. Moreover, we demonstrate a deterministic method that employs a high-scattering region in the NIR as an internal normalization reference, enabling the resolution of temporally evolving spectral signatures associated with carotenoids, anthocyanins, chlorophylls, starch, and moisture content. These results demonstrate that broadband spectral sensors can be deployed at scale in agricultural monitoring with multi-crop validation, enhancing field yield potential and reducing post-harvest losses.

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Cite This Study

Ruvalcaba-Perez et al. (2026) studied this question.

synapsesocial.com/papers/6a0d4f34f03e14405aa9a799https://doi.org/10.1038/s44310-026-00132-6
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