Desenvolvimento e teste de modelos agrometeorológicos para a estimativa de produtividade do cafeeiro (&gt;i&lt;Coffea arabica&gt;/i&lt; L.) a partir do monitoramento da disponibilidade hídrica do solo

Picini, Angélica Giarolla

doi:10.11606/d.11.1998.tde-20220208-105006

Cited by 1 publication

(1 citation statement)

References 9 publications

(13 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Studies with orbital imaging have already observed a relationship between the index and productivity. They are generally used in spectral agrometerological models, with NDVI being the spectral component representing the leafing aspects of the crop (Picini, 1998;Rosa et al, 2010;Silva et al, 2011;Bernardes et al, 2012;Almeida et al, 2017). The NDVI multiple regression equation obtained by UAS images, can be used in large-scale mapping, enabling to estimate productivity at the plant level and thus exercise greater accuracy in precision agriculture.…”

Section: Resultsmentioning

confidence: 99%

The Coffee Ndvi Modeling Using Built-in RGB Passive Sensor in Uas

Campos

Alves²,

Miranda³

et al. 2022

Theor Appl Eng

View full text Add to dashboard Cite

Studies carried out used different sensors and field applications can be accomplished to obtain information and make decisions related to coffee management. The objective of this work was to train machine learning algorithms to estimate the NDVI based on the GreenseekerTM active optical sensor in 20 arabica coffee cultivars in the experimental area of the National Institute of Coffee Science and Technology (INCT of Coffee) using a passive RGB sensor. in unmanned aerial system (UAS) and its relationship with foliage. With the spectral signatures recorded in the RGB images of the 20 coffee cultivars, the relationships with the foliage and the NDVI data obtained with the Greenseeker™ active optical sensor were analyzed. Through machine learning and digital image processing techniques, it was possible to obtain an NDVI equation using the RGB bands based on the NDVI of the Greenseeker TM active optical sensor. The results were satisfactory when compared to in situ data, providing the use of a simple and effective method of evaluating the vegetative vigor of different coffee cultivars.

show abstract

Section: Resultsmentioning

confidence: 99%