Nondestructive Detection Method for the Calcium and Nitrogen Content of Living Plants Based on Convolutional Neural Networks (CNN) Using Multispectral Images
| Autor: | Grzegorz Kunstman, Paweł Kunstman, Łukasz Lasyk, Jacek Stanisław Nowak, Agnieszka Stępowska, Waldemar Kowalczyk, Jakub Dybaś, Ewa Szczęsny-Małysiak |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Agriculture, Vol 12, Iss 6, p 747 (2022) |
| Druh dokumentu: | article |
| ISSN: | 12060747 2077-0472 |
| DOI: | 10.3390/agriculture12060747 |
| Popis: | Herein, we present the novel method targeted for determination of plant nutritional state with the use of computer vision and Neural Networks. The method is based on multispectral imaging performed by an exclusively designed Agroscanner and a dedicated analytical system for further data analysis with Neural Networks. An Agroscanner is a low-cost mobile construction intended for multispectral measurements at macro-scale, operating at four wavelengths: 470, 550, 640 and 850 nm. Together with developed software and implementation of a Neural Network it was possible to design a unique approach to process acquired plant images and assess information about plant physiological state. The novelty of the developed technology is focused on the multispectral, macro-scale analysis of individual plant leaves, rather than entire fields. Such an approach makes the method highly sensitive and precise. The method presented herein determines the basic physiological deficiencies of crops with around 80% efficiency. |
| Databáze: | Directory of Open Access Journals |
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