Raman spectroscopy enables non-destructive quantification of nitrate in C3 and C4 plants.

Abstract

Accurate assessment of plant nitrate status is critical for growth and productivity, yet early and non-destructive quantification remains challenging. Although Raman spectroscopy has been used to detect nitrate deficiency in plants, quantitative estimation of nitrate concentration from Raman spectra has not been demonstrated. Here, we evaluated whether Raman spectroscopy can be used to quantitatively predict leaf nitrate concentrations during early nitrogen stress. Two-week-old Pak Choi (C3) and Amaranthus (C4) plants were subjected to nitrate deprivation for 1–3 days, and Raman spectra were collected and correlated with nitrate concentrations determined by biochemical assays. A strong linear relationship was observed between nitrate concentration and the intensity ratio of the nitrate-associated Raman peak at 1046 cm - ¹ to the neighboring 1067 cm - ¹ peak. This relationship was consistent among plants of the same species and across different levels of nitrogen deficiency. Linear regression models achieved root-mean-square errors of 101 µg g - ¹ fresh weight (FW) in Pak Choi (~7% of nitrate under sufficient nitrogen) and 32 µg g - ¹ FW in Amaranthus (~19%), closely matching biochemical measurements and revealing species-specific nitrate dynamics. These findings demonstrate that Raman spectroscopy enables rapid, non-destructive, and quantitatively reliable estimation of leaf nitrate levels during early nitrogen stress, providing a promising platform for precision nutrient management and real-time plant phenotyping.

Plant phenotyping relevance

ラマン分光法による葉の硝酸濃度の非破壊・定量推定手法を開発・検証しており、植物フェノタイプ取得が研究の中心である。

Code and data availability

The article describes Raman spectra, biochemical nitrate assays, and Python-based regression modeling, but no block contains a data availability statement with a public deposit, no author code/model URL, and the supplementary material link is generic with no stated contents of datasets or code. No paper-specific public

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