Abstract

Nutrient deficiency alters growth and development of crop plants and compromises yield. Real-time non-invasive monitoring of the nutritional status of crops would allow timely applications of fertilizers to optimize for growth and yield at different times of the plant’s life cycle. Here, we used Raman spectroscopy to characterize Arabidopsis and two varieties of leafy vegetable crops under nitrogen sufficient and deficient conditions. We showed that the 1046 cm–1 Raman peak serves as a specific signature of nitrogen status in planta, which can be used for early diagnosis of nitrogen deficiency in plants before onset of any visible symptoms. Our research can be applied toward crop management for sustainable and precision agriculture.

Highlights

  • Precision farming deploys intelligent systems to increase agricultural productivity and profitability while protecting the environment

  • We investigated possible correlation between intensity changes of Raman spectra and nitrogen status in the model plant Arabidopsis thaliana where metabolic pathways are well studied and mutants affected in specific metabolic pathways are available

  • Three-week-old Arabidopsis plants were grown under sufficient (+N; complete) or nitrogen-deficient (−N) hydroponic media

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Summary

Introduction

Precision farming deploys intelligent systems to increase agricultural productivity and profitability while protecting the environment. Fertilizer application can be tailored to specific crop health. Nitrogen is generally the most important and the major limiting factor for crop growth and agriculture productivity (Masclaux-Daubresse et al, 2010; Kant et al, 2011). Nitrogen-limiting conditions promote leaf senescence lowering yield and biomass in plants (Kant et al, 2011). When nitrogen supply surpasses vegetation’s nutritional needs, the excess is eliminated by runoff and infiltration into the water table leading to pollution of aquatic ecosystems resulting in eutrophication. Precision agriculture seeks to limit this pollution by using sensor data to deliver precisely enough fertilizer to meet the nutritional needs of plants

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