Miniaturized Vis-NIR handheld spectrometer for non-invasive pigment quantification in agritech applications.

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 0.84 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 0.77. 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

携帯型Vis-NIR分光計を開発し、葉の色素量を非破壊推定して標準法・市販センサーと検証しており、植物フェノタイピング手法が中心である。

Code and data availability

The article describes a custom handheld Vis-NIR spectrometer and lettuce pigment measurements, but contains no data availability statement, no public dataset or spectral data deposit, no author code/scripts or firmware repository, and no trained model release. All URLs in the text are references to cited prior work or,

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