Canopy temperature for peach tree at various soil water contents

Year 2014, Volume: 3 Issue: 1, 56 - 64, 21.11.2014

Leinar Septar Cristian Paltineanu Emil Chitu Cristina Moale Hüsnü Demirsoy , Eyüp Selim Köksal Rıdvan Kızılkaya , İdris Macit

https://doi.org/10.18393/ejss.29944

Cited By: 1

Abstract

Canopy temperature measurements with infrared thermometry have been extensively studied as a means of assessing plant water status for field and row crops. Achieving high quality peach fruit depends on the ability to maintain mild to moderate levels of water stress in the crop during the growing season. The paper examined the spatial distribution of tree canopy temperature (Tc) using thermal images in a peach orchard for irrigation scheduling. The variation of Tc was investigated in three irrigation regime treatments (factor A) that produced various soil moisture content (SMC) values, three cardinal points (factor B): South, North and East-West aspects combined, and five up-down vertical position measurements (factor C: upper, middle upper, middle, middle lower and lower) across the tree canopy thermal images. It was found that Tc was significantly influenced by the irrigation regime. Cardinal point showed a significant Tc difference between South on the one hand and the other aspects. The vertical position within canopy image did not significantly influence Tc.

Keywords

Thermal imagery, leaf and air temperature, cardinal points, drip irrigation

References

• Allen, R.G., Pereira, L., Raes, D., Smith M., 1998. Crop evapotranspiration, Guidelines for computing crop water requirements. FAO Irrigation and Drain. Paper 56, Rome, 301.
• Ben-Gal, A., Agam, N., Alchanatis, V., Cohen, Y., Yermiyahu, U., Zipori, I., Presnov, E., Sprintsin, M., Dag, A., 2009. Evaluating water stress in irrigated olives: correlation of soil water status, tree water status, and thermal imagery. Irrigation Science 27: 367–376.
• Boissard, P., Guyot, G., Jackson, R.D., 1990. Factors affecting the radiative surface temperature of vegetative canopy. In: Steven M.D., Clark J.A., eds. Application of remote sensing in agriculture. London: Butterworths, pp. 45-72.
• Cohen, Y., Alchanatis, V., Meron, M., Sarang, Y. and Tsipris, T., 2005. Estimation of leaf water potential by thermal imagery and spatial analysis. Journal of Experimental Botany 56 (417): 1843–1852.
• Cohen, Y., Alchanatis, V., Prigojin, A., Levi, A., Soroker, V., 2012 and Cohen, Y. Use of aerial thermal imaging to estimate water status of palm trees. Precision Agriculture 13 (1): 123-140.
• Cressie, N.A.C., 1990. The Origins of Kriging. Mathematical Geology 22: 239-252.
• Deutsch, C.V., Journel, A.G., 1992. GSLIB - Geostatistical Software Library and User's Guide. Oxford University Press, New York, 338.
• Gardner, B.F., Blad, B.L., Watts, D.G., 1981. Plant and air temperatures in differentially irrigated corn. Agricultural Meteorology 25, 207-217.
• Goldhamer, D., Viveros, M., Salinas, M., 2006. Regulated deficit irrigation in almonds: effects of variations in applied water and stress timing on yield and yield components. Irrigation Science 24: 101-114.
• Grant, O.M., Tronina, L., Jones, H.G. and Chaves, M.M., 2007. Exploring thermal imaging variables for the detection of stress responses in grapevine under different irrigation regimes. Journal of Experimental Botany 58 (4): 815-825.
• Grant, O.M., Tronina, L., Ramalho, J.C., Besson, C.K., Lobo-do-Vale, R., Pereira, J.S. et al., 2010. The impact of drought on leaf physiology of Quercus suber L. trees: comparison of an extreme drought event with chronic rainfall reduction. Journal of Experimental Botany 61: 4361-4371.
• Idso, S.B., Jackson, R.D., Pinter, P.J. Jr, Reginato, R.J. and Hatfield, J.L., 1981. Normalizing the stress-degree-day parameter for environmental variability. Agricultural Meteorology 24: 45-55.
• Jones, H.G., 1999. Use of thermography for quantitative studies of spatial and temporal variation of stomatal conductance over leaf surfaces. Plant Cell Environment 22: 1043-1055.
• Leinonen, I., Jones, H.G., 2004. Combining thermal and visible imagery for estimating canopy temperature and identifying plant stress. Journal of Experimental Botany 55 (401): 1423-1431.
• Meron, M., Tsipris, J., Orlov, V., Alchanatis, V., Cohen, Y., 2010. Crop water stress mapping for site-specific irrigation by thermal imagery and artificial reference surfaces. Precision Agriculture 11 (2): 148-162.
• Paltineanu, C., Mihailescu, I.F., Seceleanu, I., Dragota, C., Vasenciuc, F., 2007. Ariditatea, seceta, evapotranspiratia si cerintele de apa ale culturilor agricole în Romania. Editura Ovidius University Press, Constanţa, 319.
• Paltineanu, C., Septar, L., Moale, C., 2013. Crop Water Stress in Peach Orchards and Relationships with Soil Moisture Content in a Chernozem of Dobrogea. Journal of Irrigation and Drainage Engineering 139 (1): 20–25.
• Paltineanu, C., Septar, L., Moale, C., Lamureanu, G., Demirsoy, H.,Köksal, E.S., Kızılkaya, R.,Macit, İ. 2014. Estimating soil moisture status in peach tree orchards by using crop water stress index. 9th International Soil Science Congress on “The Soul of Soil and Civilization”, 14-16 October 2014, Side, Antalya, Turkey
• Thomson, S.J., Ouellet-Plamondon, C.M., DeFauw, S.L., Huang, Y., Fisher, D.K., English, P.J., 2012. Potential and Challenges in Use of Thermal Imaging for Humid Region Irrigation System Management. Journal of Agricultural Science 4(4): 103-116.
• Wheaton A.D., Cooley N.C., Dunn G.M., Wang X., Moran B., Goodwin I. and Yang W., 2011. Use of thermal imagery to detect water stress during berry ripening in Vitis vinifera L. “Cabernet Sauvignon”. In: Ortega- Farias, S., Selles, G. (Eds). VI International Symposium on Irrigation of Horticultural Crops. Acta Horticulturae 889: 123-127.
• Zia, S., Wenyong, D., Spreer,W., Spohrer, K., Xiongkui, H., Müller, J., 2012. Assessing crop water stress of winter wheat by thermography under different irrigation regimes in North China Plain. For. International Journal of Agricultural and Biological Engineering 5 (3): 24-34.
• *Surfer 8 Program, Surface Mapping System, Golden Software Inc 2002, Available at www.goldensoftware.com
• **World Reference Base for Soil Resources, 2006. A framework for international classification, correlation and communication. Food and Agriculture Organization of the United Nations, Rome, Available at http://ftp.fao.org/agl/agll/docs/wsrr103e.pdf