Hyperspectral imaging (HSI) is a promising tool in chlorophyll quantification, providing a non-invasive method to collect important information for effective crop management. HSI contributes to food security solutions by optimising crop yields. In this study, we presented a custom HSI system specifically designed to provide a quantitative analysis of leaf chlorophyll content (LCC). To ensure precise estimation, significant wavelengths were identified using optimal-band analysis. Our research was centred on two sets of 120 leaf samples sourced from Thailand’s unique Chaew Khing rice variant. The samples were subjected to (i) an analytical LCC assessment and (ii) HSI imaging for spectral reflectance data capture. A linear regression comparison of these datasets revealed that the green (575 ± 2 nm) and near-infrared (788 ± 2 nm) bands were the most outstanding performers. Notably, the green normalised difference vegetation index (GNDVI) was the most reliable during cross-validation ($R^2=0.78$ and RMSE = 2.4 µg∙cm⁻²), outperforming other examined vegetable indices (VIs), such as the simple ratio (RED/GREEN) and the chlorophyll index. The potential development of a streamlined sensor dependent only on these two wavelengths is a significant outcome of identifying these two optimal bands. This innovation can be seamlessly integrated into farming landscapes or attached to UAVs, allowing real-time monitoring and rapid, targeted N management interventions.

Hyperspectral imaging (HSI) is an effective technique for material identification and classification, utilizing spectral signatures with applications in remote sensing, environmental monitoring, and allied disciplines. Despite its potential, the broader adoption of HSI technology is hindered by challenges related to compactness, affordability, and durability, exacerbated by the absence of standardized protocols for developing practical hyperspectral cameras. This study introduces a comprehensive framework for developing a compact, cost-effective, and robust hyperspectral camera, employing commercial off-the-shelf (COTS) components and a volume phase holographic (VPH) grism. The use of COTS components reduces development time and manufacturing costs while maintaining adequate performance, thereby improving accessibility for researchers and engineers. The incorporation of a VPH grism enables an on-axis optical design, enhancing compactness, reducing alignment sensitivity, and improving system robustness. The proposed framework encompasses spectrograph design, including optical simulations and tolerance analysis conducted in ZEMAX OpticStudio, alongside assembly procedures, performance assessment, and hyperspectral image acquisition via a pushbroom scanning approach, all integrated into a structured, step-by-step workflow. The resulting prototype, housed in an aluminum enclosure, operates within the 420–830 nm wavelength range, achieving a spectral resolution of 2 nm across 205 spectral bands. It effectively differentiates vegetation, water, and built structures, resolves atmospheric absorption features, and demonstrates the ability to distinguish materials in low-light conditions, providing a scalable and practical advancement in HSI technology.