Fluorescence-based sensing for leaf nicotine prediction, nitrogen estimation and variable rate fertilization of tobacco

Abstract

Sustainable and low-nicotine production of tobacco requires rapid and accurate on-site assessment of the leaf nitrogen (N) status. This issue can be supported by fluorescence-based sensors, which are promising tools for precision N management. We then aimed to 1) evaluate the suitability of the Multiplex® fluorescence sensor (Mx) to predict, at an early stage, the final nicotine content of tobacco leaves; 2) develop a model for in-season tobacco foliar N estimation using the Partial Least Square (PLS) multivariate regression technique; and finally, 3) test the effectiveness of a Mx map-based Variable Rate Nitrogen Fertilization (VRNF) in reducing the spatial variability in leaf Nitrogen Balance Index (NBI), that is the N status, of a commercial field of Virginia Bright tobacco. The NBI measured by the Mx about two months after transplanting was found to linearly relate to the nicotine content measured after curing (R² = 0.72, P < 0.001) over a nicotine range of 0.25 – 4.12 %. NBI, defined as the ratio between the leaf chlorophyll (SFRR) and Flavonoids (FLAV) indices better related to nicotine than the single SFRR and FLAV indices (R² = 0.47, P < 0.001 and R² = 0.52, P < 0.001, respectively. Furthermore, the NBI estimated the actual leaf N content before flowering better (R² = 0.33) than single SFRR and FLAV indices (R² = 0.28), over a range of 21 – 37.6 mgg⁻¹. Leaf fluorescence sensor indices were thus combined with growth stages and weather variables across diverse varieties and sites. The resulting PLS model successfully predicted leaf N (R² = 0.72, RMSEP = 2.73 mgg⁻¹ and relMAE = 7.75 %) over a range of 20.6–28.0 mgg⁻¹. The most significant variables, primarily related to solar radiation, were identified for a robust general model development. Finally, the spatial pattern of the NBI was mapped over a 2.04 ha commercial plot of the ITB 6118 variety, and used to produce a three-zone prescription map. Two weeks after the intervention of VRNF based on the defined prescription map, the overall NBI variability had dropped from 23.5 % coefficient of variation (CV) to 7.9 % CV. Our results show the feasibility of using the Mx sensor for precision fertilization of Virginia Bright tobacco and highlight its potential to support future developments aimed at more sustainable production of plants with reduced nicotine content.

Plant phenotyping relevance

蛍光センサーによる葉のニコチン含量・窒素状態の推定モデルを開発・検証し、NBIマッピングと可変施肥へ応用しており、植物形質の取得・推定手法が中心である。

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