Skip to main content Accessibility help
×
Home
Hostname: page-component-59b7f5684b-8dvf2 Total loading time: 0.312 Render date: 2022-09-28T22:51:21.522Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "useRatesEcommerce": false, "displayNetworkTab": true, "displayNetworkMapGraph": false, "useSa": true } hasContentIssue true

On-the-go thermal imaging for water status assessment in commercial vineyards

Published online by Cambridge University Press:  01 June 2017

S. Gutiérrez
Affiliation:
Instituto de Ciencias de la Vid y del Vino (University of La Rioja, CSIC, Gobierno de La Rioja) Ctra. Burgos Km, 6, 26007 Logroño, Spain
M. P. Diago
Affiliation:
Instituto de Ciencias de la Vid y del Vino (University of La Rioja, CSIC, Gobierno de La Rioja) Ctra. Burgos Km, 6, 26007 Logroño, Spain
J. Fernández-Novales
Affiliation:
Instituto de Ciencias de la Vid y del Vino (University of La Rioja, CSIC, Gobierno de La Rioja) Ctra. Burgos Km, 6, 26007 Logroño, Spain
J. Tardaguila*
Affiliation:
Instituto de Ciencias de la Vid y del Vino (University of La Rioja, CSIC, Gobierno de La Rioja) Ctra. Burgos Km, 6, 26007 Logroño, Spain
Get access

Abstract

The goal of this work was the assessment of commercial vineyard water status using on-the-go thermal imaging. On-the-go thermal imaging acquisition was conducted with a thermal camera operating at 1.20 m distance from the canopy, mounted on a quad moving at 5 km/h. Canopy temperature, cross water stress index (CWSI) and stomatal conductance index (Ig) were strongly and significantly correlated to stem water potential (Ψstem) in east and west side of the canopy. For CWSI, the values of the coefficient of determination (R2) were 0.88*** and 0.73*** for east and west sides, respectively. As regards the index Ig, its relationships with Ψstem showed R2=0.89*** and R2=0.77*** for east and west sides, respectively. These results are promising and evidence the potential of on-the-go thermal imaging to become a new tool to evaluate the vineyard water status.

Type
Precision Horticulture and Viticulture
Copyright
© The Animal Consortium 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Acevedo-Opazo, C, Tysseire, B, Taylor, J, Ojeda, H and Guillaume, S 2010. Spatial prediction model of the vine (Vitis vinifera L.) water status using high resolution ancillary information. Precision Agriculture 11, 358378.CrossRefGoogle Scholar
Acevedo-Opazo, C, Tisseyre, B, Guillaume, S and Ojeda, H 2008. The potential of high resolution information to define within-vineyard zones related to vine water status. Precision Agriculture 9, 285302.CrossRefGoogle Scholar
Alchanatis, V, Cohen, Y, Cohen, S, Moller, M, Sprinstin, M, Meron, M, Tsipris, J, Saranga, Y and Sela, E 2010. Evaluation of different approaches for estimating and mapping crop water status in cotton with thermal imaging. Precision Agriculture 11, 2741.CrossRefGoogle Scholar
Baluja, J, Diago, MP, Balda, P, Zorer, R, Meggio, F, Morales, F and Tardaguila, J 2012. Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle (UAV). Irrigation Science 30, 511522.CrossRefGoogle Scholar
Bellvert, J, Zarco-Tejada, PJ, Marsal, J, Girona, J, González-Dugo, V and Fereres, E 2016. Vineyard irrigation scheduling based on airborne thermal imagery and water potential thresholds. Australian Journal of Grape and Wine Research 22 (2), 307315.CrossRefGoogle Scholar
Bellvert, J, Marsal, J, Girona, J and Zarco-Tejada, PJ 2014. Seasonal evolution of Crop Water Stress Index in grapevine varieties determined with high-resolution remote sensing thermal imagery. Irrigation Science 33, 8193.CrossRefGoogle Scholar
Cohen, Y, Alchanatis, V, Meron, M, Saranga, Y and Tsipris, J 2005. Estimation of leaf water potential by thermal imagery and spatial analysis. Journal of Experimental Botany 56, 18431852.CrossRefGoogle ScholarPubMed
Cohen, Y, Alchanatis, V, Prigojin, A, Levi, A, Soroker, V and Cohen, Y 2012. Use of aerial thermal imaging to estimate water status of palm trees. Precision Agriculture 13, 123140.CrossRefGoogle Scholar
Cohen, Y, Alchanatis, V, Sela, E, Saranga, Y, Cohen, S, Meron, M, Bosak, A, Tsipris, V, Ostrovsky, V, Orolov, A, Levi, R and Brikman, R 2015. Crop water status estimation using thermography: Multi-year model development using ground-based thermal images. Precision Agriculture 16, 311329.CrossRefGoogle Scholar
Cohen, Y, Alchanatis, V, Saranga, Y, Rosenberg, O, Sela, E and Bosak, A 2016. Mapping water status based on aerial thermal imagery: comparison of methodologies for upscaling from a single leaf to commercial fields. Precision Agriculture doi:10.1007/s11119-016-9484-3.Google Scholar
Costa, JM, Grant, OM and Chaves, MM 2010. Use of Thermal Imaging in Viticulture: Current Application and Future Prospects. In: Delrot S, Medrano H, Or E, Bavaresco L and Grando S Methodologies and Results in Grapevine Research. Springer, New York USA. Pp. 135150.CrossRefGoogle Scholar
Costa, JM, Grant, OM and Chaves, MM 2013. Thermography to explore plant–environment interactions. Journal of Experimental Botany 64 (13), 39373949.CrossRefGoogle ScholarPubMed
Fernández, JE 2014. Plant-based sensing to monitor water stress: applicability to commercial orchards. Agricultural Water Management 142, 99109.CrossRefGoogle Scholar
Fuentes, S, De Bei, R, Pech, J and Tyerman, S 2012. Computational water stress indices obtained from thermal image analysis of grapevine canopies. Irrigation Science 30, 523536.CrossRefGoogle Scholar
Grant, OM, Tronina, L, Jones, HG and Chaves, MM 2007. Exploring thermal imaging variables for the detection of stress responses in grapevine under different irrigation regimes. Journal of Experimental Botany 58, 815825.CrossRefGoogle Scholar
Grant, O, Baluja, J, Ochagavía, H, Diago, MP and Tardaguila, J 2016. Thermal imaging to detect spatial and temporal variation in the water status of grapevine (Vitis vinifera L.). The Journal of Horticultural Science & Biotechnology 91, 4455.CrossRefGoogle Scholar
Grant, OM, Tronina, L, Jones, HG and Chaves, MM 2007. Exploring thermal imaging variables for the detection of stress responses in grapevine under different irrigation regimes. Journal of Experimental Botany 58, 815825.CrossRefGoogle Scholar
Harrison-Murray, RS 1991. An electrical sensor for potential transpiration: principle and prototype. Journal of Horticultural Science 66, 141149.CrossRefGoogle Scholar
Idso, SB, Jackson, RD, Pinter, PJ, Reginato, RJ and Hatfield, JL 1981. Normalizing the stress-degree-day parameter for environmental variability. Agricultural Meteorology 24, 4555.CrossRefGoogle Scholar
Jones, HG 1999. Use of infrared thermometry for estimation of stomatal conductance as a possible aid to irrigation scheduling. Agriculture and Forest Meteorology 95, 139149.CrossRefGoogle Scholar
Jones, HG 2004. Irrigation scheduling: advantages and pitfalls of plant based methods. Journal of Experimental Botany 55, 24272436.CrossRefGoogle ScholarPubMed
Jones, HG, Stoll, M, Santos, T, de Sousa, C, Chaves, MM and Grant, OM 2002. Use of infra-red thermography for monitoring stomatal closure in the field: application to the grapevine. Journal of Experimental Botany 53, 22492260.CrossRefGoogle Scholar
Meron, M, Tsipris, J, Orlov, V, Alchanatis, V and Cohen, Y 2010. Crop water stress mapping for sitespecific irrigation by thermal imagery and artificial reference surfaces. Precision Agriculture 11, 148162.CrossRefGoogle Scholar
Möller, M, Alchanatis, V, Cohen, Y, Meron, M, Tsipris, J, Naor, A, Ostrovsky, V, Sprintsin, M and Cohen, S 2007. Use of thermal and visible imagery for estimating crop water status of irrigated grapevine. Journal of Experimental Botany 58, 827838.CrossRefGoogle ScholarPubMed
Pou, A, Diago, MP, Medrano, H, Baluja, J and Tardaguila, J 2014. Validation of thermal indices for water status identification in grapevine. Agricutural Water Management 134, 6072.CrossRefGoogle Scholar

Save article to Kindle

To save this article to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

On-the-go thermal imaging for water status assessment in commercial vineyards
Available formats
×

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox.

On-the-go thermal imaging for water status assessment in commercial vineyards
Available formats
×

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive.

On-the-go thermal imaging for water status assessment in commercial vineyards
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *