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Monitoring Plant Status and Fertilization Strategy through Multispectral Images

Cardim Ferreira Lima, Matheus; Krus, Anne; Valero, Constantino; Barrientos, Antonio; del Cerro, Jaime and Roldán, Juan Jesús (2020) Monitoring Plant Status and Fertilization Strategy through Multispectral Images. Sensors, 20 (2), p. 435.

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Online at: https://www.mdpi.com/1424-8220/20/2/435

Summary

A crop monitoring system was developed for the supervision of organic fertilization status on tomato plants at early stages. An automatic and nondestructive approach was used to analyze tomato plants with different levels of water-soluble organic fertilizer (3 + 5 NK) and vermicompost. The evaluation system was composed by a multispectral camera with five lenses: green (550 nm), red (660 nm), red edge (735 nm), near infrared (790 nm), RGB, and a computational image processing system. The water-soluble fertilizer was applied weekly in four different treatments: (T0: 0 mL, T1: 6.25 mL, T2: 12.5 mL and T3: 25 mL) and the vermicomposting was added in Weeks 1 and 5. The trial was conducted in a greenhouse and 192 images were taken with each lens. A plant segmentation algorithm was developed and several vegetation indices were calculated. On top of calculating indices, multiple morphological features were obtained through image processing techniques. The morphological features were revealed to be more feasible to distinguish between the control and the organic fertilized plants than the vegetation indices. The system was developed in order to be assembled in a precision organic fertilization robotic platform.


EPrint Type:Journal paper
Keywords:multispectral image; computer vision; precision agriculture; vegetation indices; morphological features
Agrovoc keywords:
LanguageValueURI
Englishmultispectral imageryhttp://aims.fao.org/aos/agrovoc/c_36765
Englishcomputer vision -> imageryhttp://aims.fao.org/aos/agrovoc/c_36760
Englishprecision agriculturehttp://aims.fao.org/aos/agrovoc/c_92363
Englishvegetation indexhttp://aims.fao.org/aos/agrovoc/c_9000171
Englishmorphologyhttp://aims.fao.org/aos/agrovoc/c_49903
Subjects: Farming Systems > Buildings and machinery
Research affiliation: European Union > CORE Organic Cofund > SUREVEG
DOI:10.3390/s20020435
Deposited By: Krus, A.M.
ID Code:38516
Deposited On:27 Oct 2020 15:38
Last Modified:27 Oct 2020 15:38
Document Language:English
Status:Published
Refereed:Peer-reviewed and accepted

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