Experimental analysis of IoT based camera SI-NDVI values for tomato plant health monitoring application

Avotiņš, Ansis; Kviesis, Krists; Bicans, Janis; Alsiņa, I.; Dubova, L.

doi:10.15159/ar.20.087

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…The readings obtained for industrial tomato NDVI using a spectroradiometer showed mean values of 0.80, 0.78, and 0.65 at 37, 53, and 69 DAT, respectively, which aligns with the findings of Marino et al (2014) andFortes Gallego et al (2015). Avotins et al (2020) studied the NDVI for 6 tomato cultivars at plant heights, and observed that the values varied between 0.667 and 0.871. The results that the authors found show potential application in crop management by monitoring the quality parameters of tomato plant growth.…”

Section: Resultssupporting

confidence: 83%

Spatial and Temporal Variability of Vegetation Indices with Industrial Tomato Yield

O. Martins,

Reis,

L. Lopes

2023

JSD

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Vegetation indices indicate crop development and help identify areas with potential productivity reduction in the desired crop. Thus, this study aimed to determine the spatial and temporal influence of vegetation indices on industrial tomato (Solanum lycopersicum L.) yield. The research was conducted at Barcelos Farm in Anápolis, GO, covering a 55-hectare area. A sampling grid of 61-point pairs, spaced at 90 x 90 meters, was established using a GPS receiver. Vegetation indices were characterized by measuring the Soil Plant Analysis Development (SPAD) index, foliar nitrogen content through the Kjeldahl method, and Normalized Difference Vegetation Index (NDVI) using both a spectroradiometer and satellite imagery. Industrial tomato yield was assessed during harvest. Through the results, it was observed that temporal variability between vegetation indices and actual foliar nitrogen content exhibited a significant and positive correlation with industrial tomato productivity, particularly during the flowering stage. However, temporal variability between vegetation indices and foliar nitrogen content displayed low correlation across the mapped areas over time. Determining foliar nitrogen content and vegetation indices during the flowering stage is recommended for the industrial tomato crop. The relationship between ground-based remote sensing NDVI and orbital NDVI displayed a 55% positive correlation during the flowering stage.

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Section: Resultssupporting

confidence: 83%

Spatial and Temporal Variability of Vegetation Indices with Industrial Tomato Yield

O. Martins,

Reis,

L. Lopes

2023

JSD

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RGB based sensor for semi-spherical light measurements

Apse-Apsitis

Avotiņš

Graudone

et al. 2020

19th International Scientific Conference Engineering for Rural Development Proceedings

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Different light sources emit light in various directions in a different spectrum, making this a complex task in real application environments. In the case of a greenhouse, evaluation of spherical lighting must be carried out to understand how much power the plant is getting at the top, inter, and bottom layers. Part of the light is both absorbed and reflected by plant leaves, and the greenhouse elements themselves. Determination of received μmol amount from sunlight and/or artificial lighting is vital for plant growth and also the energy efficiency of the total greenhouse system. For best results, this parameter needs measurements over time by a specific sensor for this application. The article deals with a new design of the RGB light sensor -RGB sensor matrix in spherical form, where obtained raw data are processed on the controller and through communication network sent to the IoT database. The article deals with the initial measurement design, and tests for the proof of the concept and later overall discussion. The conclusion at the end is that such an approach can be applied for light parameter monitoring in greenhouse systems.

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Experimental analysis of IoT based camera SI-NDVI values for tomato plant health monitoring application

Cited by 2 publications

References 4 publications

Spatial and Temporal Variability of Vegetation Indices with Industrial Tomato Yield

Spatial and Temporal Variability of Vegetation Indices with Industrial Tomato Yield

RGB based sensor for semi-spherical light measurements

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