Non-Destructive Classification of Oil Palm Ripeness Using Free-Space Measurement: An Evaluation of the Nicolson-Ross-Weir Method

Yosy Rahmawati; Fitri Yuli Zulkifli; Mia Rizkinia

doi:10.48084/etasr.16060

Authors

Yosy Rahmawati Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Jawa Barat, Indonesia
Fitri Yuli Zulkifli Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Jawa Barat, Indonesia
Mia Rizkinia Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Jawa Barat, Indonesia

Volume: 16 | Issue: 2 | Pages: 34126-34134 | April 2026 | https://doi.org/10.48084/etasr.16060

Received: 6 November 2025 | Revised: 14 January 2026, 6 February 2026, 10 February 2026, and 11 February 2026 | Accepted: 13 February 2026 | Online: 6 March 2026

Corresponding author: Mia Rizkinia

Abstract

This study presents a non-destructive free-space electromagnetic sensing system for classifying the ripeness of oil palm fruits. Free-Space Measurement (FSM) was performed over a frequency range of 1 to 26 GHz to acquire reflection (S₁₁) and transmission (S₂₁) responses from oil palm fruit at three stages of ripeness: unripe, ripe, and overripe. The Nicolson-Ross-Weir (NRW) formulation was applied as a mathematical transformation tool to extract frequency-dependent electromagnetic response features, rather than to determine intrinsic dielectric material properties. The measured transmission responses exhibit systematic variations with ripeness. Unripe fruit shows a stronger electromagnetic interaction with resonance behavior occurring in lower frequency regions, while ripening leads to a consistent shift of resonance features toward higher frequencies. These trends are associated with physiological changes during maturation, including moisture reduction, oil accumulation, and tissue degradation. This work is an exploratory feasibility study that emphasizes comparative electromagnetic response trends and system-level resonance behavior under fixed measurement conditions, rather than absolute material characterization. The results demonstrate the potential of free-space electromagnetic sensing as a non-contact approach for oil palm ripeness classification and provide preliminary response features to support future development of microwave, Software-Defined Radio (SDR), and Artificial Intelligence (AI)-based precision agriculture sensing systems. This study experimentally demonstrates that dielectric-based inversion using the NRW formulation becomes unstable and non-physical when applied to a free-space Vector Network Analyzer (VNA) configuration involving non-homogeneous oil palm fruit, as evidenced by phase ambiguity and negative extracted parameters.

Keywords:

free-space electromagnetic sensing, non-destructive ripeness classification, oil palm fruit, transmission response (S21), NRW-based feature extraction, precision agriculture

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