M.V. Cuevas

The use of sap flow measurements for scheduling irrigation in olive, apple and Asian pear trees and in grapevines

We evaluated three approaches for scheduling irrigation in wine grape vineyards and in olive, apple and Asian pear tree orchards, based on sap flow measurements and models of plant transpiration. In the first approach, we analysed how the shape of the sap-flow profile changed in response to root-zone soil water conditions and potential evaporative demand. The second approach was based on a transpiration ratio, as defined from the actual daily water use of a target plant divided by the potential daily water use of similar-sized plants under non-limiting soil water conditions (“well-irrigated” plants). Values of the actual plant water use were always determined from measured sap flow. Two independent methods were assessed for the calculation of potential plant water use; either sap flow was measured in well-irrigated plants or we used a leaf-area based model of plant transpiration. On some occasions water stress was found to modify the shape of the sap velocity profile. However, most of the time the velocity profile was found to be an insensitive indicator for triggering irrigation. The transpiration ratio method, using measured sap flow in well-irrigated plants, was more useful for irrigation scheduling, at least for the two species (i.e. olive and grape) that were investigated here. Nonetheless, realization of such an approach in a commercial orchard may not be practical due to problems associated with irrigation management e.g. excessive vegetative growth may occur on the reference plants over time. Besides, irrigating the orchard to maintain non-limiting soil water conditions is not always the best option for water and nutrient management. The alternative transpiration ratio method based on a leaf-area based model of plant water use, yielded the best results. Modelled transpiration rates always provided reliable information not only for well-irrigated plants, but also for deficit-irrigated plants. This result lends support to the use of the method for irrigation scheduling of vineyard and orchard trees. However, the use of models does require detailed microclimate data as well as a user-friendly technique to quantify plant leaf area. From a practical viewpoint the method should encompass the spatial variability of the soil and plants within the orchard. Accurate quantification of these factors is a cornerstone of precision horticulture and such information would help to minimise risks associated with insufficient as well as excessive irrigation applications.

Design and testing of an automatic irrigation controller for fruit tree orchards, based on sap flow measurements

We designed and tested an automatic irrigation control system for fruit tree orchards, designated CRP. At the end of each day, the device calculates the irrigation dose (ID) from sap flow readings in the trunk of trees irrigated to replenish the crop water needs, relative to similar measurements made in over-irrigated trees. It then acts on the pump and electrovalve to supply an ID sufficient to keep the soil close to its field capacity during the irrigation period. Remote control of the system is possible from any computer or Smartphone connected to the Internet. We tested the CRP in an olive orchard in southern Spain. The device was robust and able to filter and amplify the output voltages of the heat-pulse velocity probes and to calculate reliable sap flow data. It calculated and supplied daily irrigation amounts to the orchard according to the specified irrigation protocol. The remote control facility proved to be useful for getting real-time information both on the CRP behaviour and the applied IDs, and for changing parameters of the irrigation protocol. For our conditions, olive trees with big root systems growing in a soil with a remarkable water-holding capacity, the approach mentioned above for calculating ID had not enough resolution to replace the daily crop water consumption. The device, however, was able to react when the soil water content fell below the threshold for soil water deficit. The threshold value was identified with simultaneous measurements of stem water potential in the instrumented trees. Our results suggest a change in the irrigation protocol that will allow the CRP to apply a recovery irrigation whenever that threshold is reached, making the device suitable for applying a deficit irrigation strategy in the orchard.

The effect of strobilurins on leaf gas exchange, water use efficiency and ABA content in grapevine under field conditions

Strobilurins are one of the most important classes of agricultural fungicides. In addition to their anti-fungal effect, strobilurins have been reported to produce simultaneous effects in plant physiology. This study investigated whether the use of strobilurin fungicide improved water use efficiency in leaves of grapevines grown under field conditions in a Mediterranean climate in southern Spain. Fungicide was applied three times in the vineyard and measurements of leaf gas exchange, plant water status, abscisic acid concentration in sap ([ABA]), and carbon isotope composition in leaves were performed before and after applications. No clear effect on stomatal conductance, leaf water potential and intrinsic water use efficiency was found after three fungicide applications. ABA concentration was observed to increase after fungicide application on the first day, vanishing three days later. Despite this transient effect, evolution of [ABA] matched well with the evolution of leaf carbon isotope ratio, which can be used as a surrogate for plant water use efficiency. Morning stomatal conductance was negatively correlated to [ABA]. Yield was enhanced in strobilurin treated plants, whereas fruit quality remained unaltered.

Classification models for automatic identification of daily states from leaf turgor related measurements in olive

Abstract The leaf patch clamp pressure (LPCP) probe is being used to remotely assess leaf turgor pressure. Recently, different shapes of the LPCP daily curves have been suggested as potential water stress indicators for irrigation scheduling. These curves shapes, called states, have been studied and related to different water stress levels for olives. To our knowledge, the only way to differentiate these curves shapes or states is through the visual observation of the dynamics of the LPCP records during the day, which is highly time-consuming and reduces its potential to automatically schedule irrigation. The aims of this study were: (i) to obtain a random forest model to automatically identify the states from daily LPCP curves recorded in olive trees, by using visually identified states to train the model; (ii) to improve the identification of state II through a second random forest model, relating this state to the midday stem water potential, and; (iii) to obtain a random forest model to identify the states based on ranges of stem water potential. We used LPCP daily curves collected in a commercial olive orchard from 2011 to 2015. The states were visually identified for the days on which concomitant measurements of stem water potential and leaf stomatal conductance were made. We had a data set of 307 LPCP daily curves, being 157 curves in state I, 78 in state II and 71 in state III. The two biggest inflection points of the LPCP curves were used to adjust the models through the use of the R package “randomForest”, using the Leave-p-Out Cross-Validation method. With the first model, which was obtained from the whole dataset, its data regarding the inflection points and the visually identified states, we obtained an overall accuracy of 94.37%. With the second model, obtained with the use of the data regarding curves visually identified as state II only, the overall accuracy was of 88.64%. This model was adjusted to be used after the first model, to narrow the stem water potential range of state II curves. Finally, the third model was obtained using the whole dataset and the states established from ranges of stem water potential. This last model did not consider the visual identification, and yielded an overall accuracy of 88.08%. Our results facilitate the use of LPCP probes, since it allows for the automatic identification of the states related to leaf turgor pressure, a key information to schedule irrigation.

Precision Irrigation in Olive (Olea europaea L.) Tree Orchards

Abstract The olive tree is well adapted to water stress but, at the same time, it shows a remarkable response to irrigation. Full irrigation is rarely the best option, both because olive is usually grown in areas where water for irrigation is scarce and because of its remarkable response to low irrigation supplies. We address in this work new approaches for the management of deficit irrigation in olive orchards, in a context of a rational use of water in agriculture. Special attention is paid to precise irrigation and, more precisely, to irrigation strategies suitable for olive orchards, and to new methods allowing for the continuous and automatic assessment of tree water stress, with a potential for irrigation scheduling. We focus on methods based on measurements related to sap flow, trunk diameter variations, and leaf turgor pressure, since evidence shows the great potential of plant-based methods as compared to those using measurements of soil water status or atmospheric demand. This review includes the potential of those methods for precise irrigation in olive orchards, with particular attention to hedgerow olive orchards with high plant densities. Such potential is achieved after combining plant-based measurements with remote imagery and user-friendly applications for smartphones, tablets, or computers. After considering these new advances in the management of irrigation in olive orchards, we review the effects of irrigation on the production of both fruit and oil, with special attention to those aspects for which the impact of irrigation is still unclear.