Miniaturized Vis-NIR handheld spectrometer for non-invasive plant pigment quantification

Abstract

Advanced precision agriculture requires the objective measurement of the structural and functional properties of plants. Biochemical profiles in leaves can differ depending on plant growing conditions. By quantitatively detecting these changes, farm production processes can be optimized to achieve high-yield, high-quality, and nutrient dense agricultural products. To enable the rapid and non-destructive detection on site, this study demonstrates the development of a new custom-designed portable handheld Vis-NIR spectrometer that collects leaf reflectance spectra, wirelessly transfers the spectral data through Bluetooth, and provides both raw spectral data and processed information. The spectrometer has two preprogramed methods: anthocyanin and chlorophyll quantification. Anthocyanin content of red and green lettuce estimated with the new spectrometer showed an excellent correlation coefficient of 84% with those determined by a destructive gold standard biochemical method. The differences in chlorophyll content were measured using leaf senescence as a case study. Chlorophyll Index calculated with the handheld spectrometer gradually decreased with leaf age as chlorophyll degrades during the process of senescence. The estimated chlorophyll values were highly correlated with those obtained from a commercial fluorescence-based chlorophyll meter with a correlation coefficient of 77%. The developed portable handheld Vis-NIR spectrometer could be a simple, cost-effective, and easy to operate tool that can be used to non-invasively monitor plant pigment and nutrient content efficiently.

Plant phenotyping relevance

葉の反射スペクトルからアントシアニン・クロロフィルを非破壊定量する携帯型センサーを開発し、標準法および市販メーターと相関検証しており、植物表現型取得手法が中心である。

Code and data availability

The paper describes a custom handheld Vis-NIR spectrometer and plant pigment measurements (anthocyanin in lettuce, chlorophyll during senescence), but no public phenotype datasets, spectral data, analysis code, or trained models are deposited. The only availability statement is on-request access from the corresponding,

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