Citation Information

  • Title : Transpiration of irrigated apple trees and citrus from a water potential gradient approach in the leaf-atmosphere system.
  • Source : Revista Brasileira de Meteorologia
  • Publisher : Sociedade Brasileira de Meteorologia
  • Volume : 26
  • Issue : 2
  • Pages : 181 - 188
  • Year : 2011
  • DOI : 10.1590/S0102-77
  • ISBN : 10.1590/S0102-77862011000200002
  • Document Type : Journal Article
  • Language : English
  • Authors:
    • Pires, L. F.
    • Nova, N. A. V.
    • Pereira, A. B.
    • Alfaro, A. T.
  • Climates: Temperate (C). Humid subtropical (Cwa, Cfa). Marintime/Oceanic (Cfb, Cfc, Cwb).
  • Cropping Systems: Citrus. Fruit. Irrigated cropping systems.
  • Countries: Brazil. France.

Summary

The uptake of water from the roots of crops comes to being a physiological response of the plant to the water loss process through its stomata. Getting to know the daily transpiration rates throughout the phenological cycle allows for the application of the ideal amount of irrigation water at the right moment to maximize production with environmental protection. Since transpiration direct measurements at the field, mainly for trees in general, are to be of operational difficulty and relatively high cost we came up with a methodology that allows one to calculate the daily transpiration rates of apple trees and citrus orchards from variables of both the physical environment and the crop. The input data of the proposed model are air temperature, air relative humidity, photoperiod duration, and leaf area. Estimated transpiration rates based on the water potential gradient between the air and leaf approach were comparable in apple trees and citrus orchards. Sap flow daily values were obtained by means of the heat balance method at Bordeaux, France, and Piracicaba, SP, Brazil. All the coefficients of determination of the regression equations obtained herein were higher than 0.93. This allows one to calculate the amount of irrigation water to be applied throughout the crop growing seasons with a high precision as a function of meteorological data and crop covering density at the sites in the study.

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