Application of a low-cost RGB sensor to detect basil ( Ocimum basilicum L.) nutritional status at pilot scale level
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Application of a low‑cost RGB sensor to detect basil (Ocimum basilicum L.) nutritional status at pilot scale level Massimo Brambilla1 · Elio Romano1 · Marina Buccheri2 · Maurizio Cutini1 · Pietro Toscano1 · Sonia Cacini3 · Daniele Massa3 · Serena Ferri5 · Danilo Monarca5 · Marco Fedrizzi4 · Gianluca Burchi3 · Carlo Bisaglia1
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract In this work, basil plants were fertilized with 0, 2.5 mM and 10 mM nitrogen (with different NO3−/NH4+ ratios), and then monitored using a low-power technique based on an optical leaf meter and a low-cost RGB sensor interfaced with an Arduino UNO board. The study aimed to investigate possible relationships between the concentration of some plant compounds (i.e., leaf chlorophyll and flavonoids content) and the nitrogen balance index, with the output data of a low-cost RGB sensor to indicate its capability in discriminating among different levels of nutrition. The data obtained underwent univariate and multivariate analysis. The univariate data analysis showed that the low-cost RGB sensor readings followed the development of the plants according to the varying applications of nitrogen. The multivariate analysis of the data showed that the indices related to plant metabolic efficiency and leaf colour were those most affected by the nitrogen levels of the solutions used. The comparison of the discrimination powers of the systems showed that both systems achieved comparable discrimination performances (85.0% and 89.4%) for plants supplied with 0 mM nitrogen solution. However, at increasing levels of nitrogen, the RGB sensor performed worse than the optical leaf meter (− 15.8% and − 8.6% for the 2.5 and 10 mM N treatments). The effect of the NO3−/NH4+ ratio could hardly be distinguished (except for the total chlorophyll resulting from the optical leaf meter readings). More data is, however, necessary to create a more robust model for future implementation of the application of such a sensor. Keywords Arduino UNO · Plant monitoring · Optical leaf meter · Nitrogen · Leaf colour
Introduction Sweet basil (Ocimum basilicum L.) is one of the most widely consumed herbs in many countries (Makri and Kintzios 2008). Its use (fresh, dried and processed) has increased worldwide following the growing interest in “Mediterranean cuisine” and in consideration * Massimo Brambilla [email protected] Extended author information available on the last page of the article
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of the importance of the phenolics that basil plants contain (Tenore et al. 2017). Many factors influence the concentrations of vitamins and phenolics in basil leaves, including soil, irrigation and climatic conditions (Nurzyńska-Wierdak et al. 2013; Muráriková et al. 2017). As for many other leafy vegetables, the leaf colour is a fundamental parameter for basil because its deterioration results in a loss of market quality of the plant and of its derived products (Purnamasari 2017). Besides plant senescence
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