Abstract
A crop’s health can be determined by its leaf nutrient status; more precisely, leaf nitrogen (N) level, is a critical indicator that carries a lot of worthwhile nutrient information for classifying the plant’s health. However, the existing non-invasive techniques are expensive and bulky. The aim of this study is to develop a low-cost, quick-read multi-spectral sensor array to predict N level in leaves non-invasively. The proposed sensor module has been developed using two reflectance-based multi-spectral sensors (visible and near-infrared (NIR)). In addition, the proposed device can capture the reflectance data at 12 different wavelengths (six for each sensor). We conducted the experiment on canola leaves in a controlled greenhouse environment as well as in the field. In the greenhouse experiment, spectral data were collected from 87 leaves of 24 canola plants, subjected to varying levels of N fertilization. Later, 42 canola cultivars were subjected to low and high nitrogen levels in the field experiment. The k-nearest neighbors (KNN) algorithm was employed to model the reflectance data. The trained model shows an average accuracy of 88.4% on the test set for the greenhouse experiment and 79.2% for the field experiment. Overall, the result concludes that the proposed cost-effective sensing system can be viable in determining leaf nitrogen status.
Highlights
Nitrogen (N) is one of the most indispensable elements for plants owing to its vital role in major physiological processes [1]
The device can capture the reflectance at 12 wavelengths ranging from 450 to
The trained model shows an average accuracy of 88.4% on the test set for the greenhouse experiment and 79.2% for the field experiment
Summary
Nitrogen (N) is one of the most indispensable elements for plants owing to its vital role in major physiological processes [1]. Various enzymatic proteins that regulate plant growth processes are formed basically from N [2]. To achieve high yield, sometimes farmers over-fertilize N, which can be leached below the root zone or might get lost in run-off. These occurrences may cause the rise of nitrate ion in water, which creates human health issues [4]. Photosynthesis and crop yield are negatively affected by N deficiency; N content monitoring during the vegetative growth stage is needed for optimal fertilizer application [6]
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