2016
DOI: 10.1080/14620316.2015.1110991
|View full text |Cite
|
Sign up to set email alerts
|

Thermal imaging to detect spatial and temporal variation in the water status of grapevine (Vitis viniferaL.)

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
34
0
3

Year Published

2016
2016
2023
2023

Publication Types

Select...
5
2
1

Relationship

0
8

Authors

Journals

citations
Cited by 59 publications
(37 citation statements)
references
References 33 publications
0
34
0
3
Order By: Relevance
“…Recently, however, the development of both cheaper image acquisition systems and user-friendly, powerful data image processing packages has substantially increased the potential of the method for irrigation scheduling in commercial orchards [55,56]. Thermal readings can be made both at the plant level (ground-based imagery) [55,57] and from above the crop (airborne imagery), after installing the sensors on towers or cranes [58,59], on unmanned aerial vehicles (UAVs), also known as remote piloted aerial systems (RPAS) [60], planes [61] or satellites [62,63]. Ground-based and airborne thermal images can be combined to assess within-orchard spatial heterogeneity in water status, as demonstrated with grape [64] and olive plants [65].…”
Section: Thermal Sensingmentioning
confidence: 99%
See 1 more Smart Citation
“…Recently, however, the development of both cheaper image acquisition systems and user-friendly, powerful data image processing packages has substantially increased the potential of the method for irrigation scheduling in commercial orchards [55,56]. Thermal readings can be made both at the plant level (ground-based imagery) [55,57] and from above the crop (airborne imagery), after installing the sensors on towers or cranes [58,59], on unmanned aerial vehicles (UAVs), also known as remote piloted aerial systems (RPAS) [60], planes [61] or satellites [62,63]. Ground-based and airborne thermal images can be combined to assess within-orchard spatial heterogeneity in water status, as demonstrated with grape [64] and olive plants [65].…”
Section: Thermal Sensingmentioning
confidence: 99%
“…The user must also bear in mind that relationships between thermal readings and water-stress-related physiological variables must be determined to properly evaluate the information provided by thermal imagery [66,75]. The literature provides examples on the use of ground-based thermal imagery to detect water status changes in a variety of plants, from ornamental [76] to herbaceous [59,77] and woody crops [57,68,78].…”
Section: Ground-based Imagerymentioning
confidence: 99%
“…Análisis de varianza para el contenido de agua en el suelo y potencial hídrico foliar de tallo. Grant et al (2016) exponen la alta variabilidad de la temperatura del dosel vegetal, refiriéndose a hojas laterales y superiores, lo que se corresponde con la variabilidad obtenida con la adquisición de imágenes aéreas, en el presente trabajo. …”
Section: -Resultados Y Discusiónunclassified
“…Los efectos del riego y la fertirrigación han mostrado una buena correlación con las temperaturas obtenidas con las imágenes, frente a los valores del contenido de agua en el suelo, si bien no con los parámetros medidos en planta. Estos resultados sugieren determinar el crop water stress index (CWSI) para tener presente las condiciones climáticas y sus efectos sobre el viñedo, así como determinar relaciones útiles entre el estado hídrico de la planta y las temperaturas de las hojas superiores, como ha sido propuesto por Grant et al (2016).…”
Section: -Conclusiones Y Recomendacionesunclassified
“…Conversely, LWP was more stable due to stomatal closure and the most leaves were exposed to sunlight around midday, thermal images contained the highest temperature differences and were suitable to assess the canopy water stress [122] . The other method for the separating canopy from background was simultaneously collect thermal and color images of canopy [123][124][125] . Thermal and color images were aligned registered, and then canopy can be extracted based on segmentation algorithms of color image processing.…”
Section: Water Stress Measurementsmentioning
confidence: 99%