2024-03-28T16:53:16Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/2192602021-12-28T15:44:11Zcom_10261_31565com_10261_4col_10261_31566
00925njm 22002777a 4500
dc
Ferreira Lima, Matheus Cardim
author
Krus, Anne
author
Valero, Constantino
author
Barrientos, Antonio
author
Cerro, Jaime del
author
Roldán-Gómez, Juan Jesús
author
2020-01-13
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 di erent 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 di erent treatments: (T0: 0 mL, T1:
6.25 mL, T2: 12.5 mL and T3: 25 mL) and the vermicomposting was added inWeeks 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.
Sensors 20 (2): 435 (2020)
http://hdl.handle.net/10261/219260
10.3390/s20020435
1424-8220
http://dx.doi.org/10.13039/501100000780
31941027
Multispectral image
Computer vision
Precision agriculture
Vegetation indices
Monitoring Plant Status and Fertilization Strategy through Multispectral Images