Irrigation decision support based on leaf relative water content determination in olive grove using near infrared spectroscopy

Abstract

The relative water content (RWC) provides a measurement of the water deficit of the leaf and may indicate a degree of stress, endured under conditions of drought and high temperatures. Its measurement is therefore essential for the appropriate management of irrigation. This study sought to ascertain the viability of near infrared spectroscopy (NIRS), using a handheld portable NIR instrument, for the non-destructive and in situ determination of RWC in olive tree leaves cultivated under higher temperatures than ambient. Different combinations of pre-treatments and first and second derivative were assayed to obtain information of spectral data and to develop calibration models. A calibration equation with enough prediction performance to support irrigation decision-making (standard error of cross-validation, SECV = 1.52%; r2cv = 0.61; residual predictive deviation for cross-validation, RPDcv = 2.01) was obtained. The findings obtained from the external validation of the model (standard error of prediction, SEP = 1.63%; r2p = 0.64; residual predictive deviation for prediction, RPDp = 2.17) suggest the viability of the on-tree use of NIRS technology for the instant measurement of RWC in olive groves, ensuring a major saving in time and avoiding the disadvantage of transporting samples to the lab, thereby favouring real-time decision-making in the field regarding the optimal amounts of irrigation to be applied; this is of enormous significance for the future, given that the availability of irrigation water for such vital crops to the Mediterranean region as the olive could be limited in years to come by a gradual increase in global temperature.