Chlorophyll detection and monitoring play crucial roles in plant physiology, water quality, agricultural management, and ecosystem health. Based on their principles and application characteristics, current chlorophyll detection methods can be classified into several categories such as spectroscopic measurements (such as spectrophotometry and fluorescence techniques), compositional analysis (such as high-performance liquid chromatography, HPLC), and morphological observation (such as microscopic counting and high-resolution spectral imaging). However, many of these methods present various drawbacks. Spectrophotometric methods involve cumbersome detection steps and suffer from low sensitivity; the HPLC method takes a long time and is costly; the fluorescence method does not work well with high-concentration solutions; some detection equipment demands on-site measurement, hindering long-distance detection; and real-time capabilities are often lacking, demanding significant manpower and resources. In recent times, microwave photonics (MWP) technology evolves rapidly. Microwave photonic filters (MPF), pivotal technologies within this realm, capitalize on the fiber optic sensor’s resilience to high pressure, high temperature, corrosion, and electromagnetic interference. These sensors process RF signals and manage optical carrier signal processing within the optical domain. This study introduces a chlorophyll detection system rooted in the microwave photonic filter RF intensity. This novel detection method stands out for its compactness, robust anti-interference capabilities, and potential for long-distance detection. The focus here is the application of microwave photonic filters for chlorophyll detection. Our experiment underscores the feasibility of this principle and highlights a pioneering approach to chlorophyll detection with expansive application prospects.
The system comprised a broad-spectrum light source (ASE), a microwave signal source (RF), an optical fiber amplifier (EDFA), an electro-optical modulator (EOM), an isolator (ISO), an optical coupler (OC), a photodetector (PD), a spectrometer (ESA), and optical fibers. Together, they formed a microwave photonic filter with a Michelson interferometer structure. The upper arm (reference arm) of the system had a fiber-end-face placed in a test tube containing a matching solution with consistent reflectivity. This matching solution was 95% ethanol, and the fiber end face was labeled as PC1. The lower arm (sensing arm) connected with a 2 km fiber optic, enabling detection and monitoring over extended distances. The end fiber face of this arm was placed in a test tube containing a chlorophyll solution, and its fiber-end-face was labeled as PC2. The principle of chlorophyll determination in this study centered on the variation in RF power at a particular frequency due to shifts in chlorophyll concentration. Following the Fresnel reflection principle, when the chlorophyll content at the optical fiber’s end face varied, the solution’s refractive index (n) altered. This change led to a modification in the effective reflectivity (Fresnel reflection coefficient R), influencing the amplitude coefficients of the microwave photonic filters.
Chlorophyll solutions extracted from various vegetables are tested (Fig.2) to verify the feasibility of detecting plant chlorophyll (Fig.4). Through the time stability experiment, it is concluded that when the chlorophyll sample solution of the experimental stock solution is placed in a shaded room at a temperature of 25 ℃ for 2 h, the relative error of the maximum value of the RF intensity measured by the chlorophyll solution stays within 0.73%, and the relative error of the minimum value of the RF intensity is within 0.72% (Fig.5, Table 3, and Table 4). This indicates that the chlorophyll solution made by the experimental stock solution remains stable, suggesting the properties of the standard substance do not change notably within the experimental time range, ensuring the reliability of the experiment. Temperature effect experiments show that the system remains more stable concerning the chlorophyll concentration of the experimental samples in the measurement range of 25?35 ℃ (Fig.6). Different gradients of chlorophyll solutions, prepared from chlorophyll experimental stock solution and standard solution, are tested, confirming that the RF intensity and chlorophyll mass concentration maintain a strong linear relationship. For the measurements of the chlorophyll experimental stock solution, the linear degree of fitting (R2) at the maximum RF intensity is 0.9583 with a sensitivity of 0.2994 dB/(mg·L-1), and the R2 at the minimum RF intensity is 0.9596 with a sensitivity of 0.3336 dB/(mg·L-1) (Fig.7). For the measurements of the standard chlorophyll solution, the R2 at the maximum RF intensity is 0.9741 with a sensitivity of 0.007881 dB/(μg·L-1), and the R2 at the minimum RF intensity is 0.9841 with a sensitivity of 0.02258 dB/(μg·L-1) (Fig 8). These experimental results demonstrate that the system exhibits high sensing performance at high and low chlorophyll mass concentrations.
In this study, a novel chlorophyll detection system is demonstrated, which utilizes microwave photonic signals to capture the RF spectral lines of the system. This method extracts chlorophyll sensing information from the peaks (RF intensity maxima and RF intensity minima) without the need for expensive optical spectral demodulation instruments. It offers rapid demodulation speed, enabling real-time long-distance detection and monitoring of solutions with varying chlorophyll mass concentrations. The introduced sensing system exhibits outstanding sensing performance and proves versatile for detection in both low- and high-mass concentration of chlorophyll environments. This research paves the way for future applications in areas such as water pollution monitoring and industrial chlorophyll concentration detection. Beyond detecting the chlorophyll content of various vegetables, this system has the potential for diagnosing plant health and growth, with implications for agricultural development. Although promising chlorophyll mass concentration detection results are achieved, there remains potential for further optimization. This includes reducing noise impact, enhancing system sensitivity and fit, and solidifying its foundation for future applications.
