Mapping crop water stress index in a ‘Pinot-noir’ vineyard: Comparing ground measurements with thermal remote sensing imagery from an unmanned aerial vehicle

Precision Agriculture

Volumn 15, Issue 4, 2014, Pages 361-376

  Bellvert, J ^a   Zarco Tejada, P J ^b   Girona, J ^a   Fereres, E ^b,c  

^a IRTA   (Spain)

^b INSTITUTO DE AGRICULTURA SOSTENIBLE   (Spain)

^c UNIVERSITY OF CÓRDOBA   (Spain)

Author keywords

Canopy temperature; CWSI; Grapevine; Leaf water potential; Thermal imagery; Water stress

Indexed keywords

VITIS;

EID: 84911480845     PISSN: 13852256     EISSN: 15731618     Source Type: Journal    
DOI: 10.1007/s11119-013-9334-5     Document Type: Article

References (29)

1. Acevedo-Opazo, C., Tisseyre, B., Guillaume, S., & Ojeda, H. (2008a). The potential of high spatial resolution information to define within-vineyard zones related to vine water status. Precision Agriculture, 9, 285-302.
2. Acevedo-Opazo, C., Tisseyre, B., Ojeda, H., Ortega-Farias, S., & Guillaume, S. (2008b). Is it possible to assess the spatial variability of vine water status? Journal International des Sciences de la Vigne et du Vin., 42, 203-219.
3. Basile, B., Marsal, J., Mata, M., Vallverdú, X., Bellvert, J., & Girona, J. (2011). Phenological sensitivity of Cabernet Sauvignon to water stress: vine physiology and berry composition. American Journal of Enology and Viticulture, 62, 452-461.
4. Bellvert, J., Marsal, J., Mata, M., & Girona, J. (2012). Identifying irrigation zones across a 7.5-ha 'Pinotnoir' vineyard based on the variability of vine water status and multispectral images. Irrigation Science, 30, 499-509.
5. Berni, J. J., Zarco-Tejada, J. P., Sepulcre-Cantó, G., Fereres, E., & Villalobos, F. (2009a). Mapping canopy conductance and CWSI in olive orchards using high resolution thermal remote sensing imagery. Remote Sensing of Environment, 113, 2380-2388.
6. Berni, J. A., Zarco-Tejada, P. J., Suarez, L., & Fereres, E. (2009b). Thermal and narrow-band multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on Geoscience and Remote Sensing, 47, 722-738.
7. Bramley, R. G. V., & Hamilton, R. P. (2004). Understanding variability in winegrape production systems. 1. Within vineyard variation in yield over several vintages. Australian Journal of Grape and Wine Research, 10, 32-45.
8. Bramley, R. G. V., Proffitt, A. P. B., Hinze, C. J., Pearse, B., & Hamilton, R. P. (2005). Generating benefits from precision viticulture through selective harvesting. In J. V. Stafford (Ed.), Precision Agriculture '05, Proceedings of the 5th European Conference on Precision Agriculture (pp. 891-898). Wageningen: Wageningen Academic Publishers.
9. FAO (2010) FAO statistical database (online). Retrieved September, 2013, from http://faostat.fao.org/.
10. Fulton, A., Schwankl, L., Lynn, K., Lampinen, B., Edstrom, J., & Prichard, T. (2011). Using EM and VERIS technology to assess land suitability for orchard and vineyard development. Irrigation Science, 29, 497-512.
11. Girona, J., Mata, M., del Campo, J., Arbonés, A., Bartra, E., & Marsal, J. (2006). The use of midday leaf water potential for scheduling deficit irrigation in vineyards. Irrigation Science, 24, 115-127.
12. Gonzalez-Dugo, V., Zarco-Tejada, P., Berni, J. A. J., Suárez, L., Goldhamer, D., & Fereres, E. (2012). Almond tree canopy temperature reveals intra-crown variability that is water stress-dependent. Agricultural and Forest Meteorology, 154-155, 156-165.
13. Hipps, L. E., Asrar, G., & Kanemasu, E. T. (1985). A theoretically-based normalization of environmentaleffects on foliage temperature. Agricultural and Forest Meteorology, 27, 59-70.
14. Idso, S. B., Jackson, R. D., Pinter, P. J., Reginato, R. J., & Hatfield, J. L. (1981). Normalizing the stressdegree day parameter for environmental variability. Agricultural Meteorology, 24, 45-55.
15. Jackson, R. D., Idso, S., Reginato, R., & Pinter, P, Jr. (1981). Canopy temperature as a crop water stress index indicator. Water Resources Research, 17, 1133-1138.
16. Johnson, L. F., Bosch, D. F., Williams, D. C., & Lobitz, B. M. (2001). Remote sensing of vineyard management zones: Implications for wine quality. American Society of Agricultural Engineers, 17, 557-560.
17. Jones, H. G., Stoll, M., Santos, T., de Sousa, C., Chaves, M. M., & Grant, O. M. (2002). Use of infrared thermography for monitoring stomatal closure in the field: Application to grapevine. Journal of Experimental Botany, 53(378), 2249-2260.
18. Martinez-Casasnovas, J. A., Vallés Bigorda, D., & Ramos, M. C. (2009). Irrigation management zones for precision viticulture according to intra-field variability. In A. Breft, S. Wolfert, J. E. Wien, & C. Lokhorst (Eds.), EFITA conference'09. Proceedings of the 7th EFITA Conference (pp. 523-529). Wageningen: Wageningen Academic Publishers.
19. Möller, M., Alchanatis, V., Cohen, Y., Meron, M., Tsipris, J., Naor, A., et al. (2007). Use of thermal and visible imagery for estimating crop water status of irrigated grapevine. Journal of Experimental Botany, 58(4), 827-838.
20. Rogiers, S. Y., Greer, D. H., Hatfield, J. M., Hutton, R. J., Clarke, S. J., Hutchinson, P. A., et al. (2012). Stomatal response of an anisohydric grapevine cultivar to evaporative demand, available soil moisture and abscisic acid. Tree Physiology, 32, 249-261.
21. SAS. (2002). Enterprise Guide version 4.2 (SAS Institute Inc. Cary, NC, USA).
22. Sepulcre-Canto, G., Zarco-Tejada, P. J., Jimenez-Muñoz, J. C., Sobrino, J. A., de Miguel, E., & Villalobos, F. J. (2006). Detection of water stress in an olive orchard with thermal remote sensing imagery. Agricultural and Forest Meteorology, 136, 31-44.
23. Testi, L., Goldhamer, D. A., Iniesta, F., & Salinas, M. (2008). Crop water stress index is a sensitive water stress indicator in pistachio trees. Irrigation Science, 26, 395-405.
24. Turner, N. C., & Long, M. J. (1980). Errors arising from rapid water loss in the measurement of leaf water potential by pressure chamber technique. Australian Journal of Plant Physiology., 7, 527-537.
25. Van Zyl, J. L. (1987). Diurnal variation in grapevine water stress as a function of changing soil status and meteorological conditions. South African Journal of Enology and Viticulture, 8(2), 45-52.
26. Wetterlind, J., Stenberg, B., & Söderström, M. (2008). The use of near infrared (NIR) spectroscopy to improve soil mapping at the farm scale. Precision Agriculture, 9, 57-69.
27. Williams, L. E., & Arujo, F. J. (2002). Correlations among predawn leaf, midday leaf, and midday stem water potential and their correlations with other measures of soil and plant water status in Vitis vinifera. Journal of the American Society for Horticultural Science, 127, 448-454.
28. Zarco-Tejada, P. J., González-Dugo, V., & Berni, J. A. J. (2012). Fluorescence, temperature and narrowband indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera. Remote Sensing of Environment, 117, 322-337.
29. Zia, S., Klaus, S., Nikolaus, M., Wenyong, D., Xiongkui, H., & Müller, J. (2009). Non-invasive water status detection in grapevine (Vitis vinifera L.) by thermography. International Journal of Agricultural and Biological Engineering, 2(4), 46-54.