Abstract

Advances in electromagnetic sensor technologies in recent years have made automated irrigation scheduling a reality through the use of state-of-the-art soil moisture sensing devices. However, correct sensor positioning and interpretation of the measurements are key to the successful implementation of these management systems. The aim of this study is to establish guidelines for soil moisture sensor placement to support irrigation scheduling, taking into account the physiological response of the plant. The experimental work was carried out in Vegas Bajas del Guadiana (Extremadura, Spain) on a drip-irrigated experimental orchard of the early-maturing Japanese plum cultivar “Red Beaut”. Two irrigation treatments were established: control and drying. The control treatment was scheduled to cover crop water needs. In the drying treatment, the fruit trees were irrigated as in control, except in certain periods (preharvest and postharvest) in which irrigation was suspended (drying cycles). Over 3 years (2015–2017), a series of plant parameters were analyzed in relation to the measurements provided by a battery of frequency domain reflectometry probes installed in different positions with respect to tree and dripper: midday stem water potential (Ψstem), sap flow, leaf stomatal conductance, net leaf photosynthesis and daily fraction of intercepted photosynthetically active radiation. After making a comparison of these measurements as indicators of plant water status, Ψstem was found to be the physiological parameter that detected water stress earliest. The drying cycles were very useful to select the probe positions that provided the best information for irrigation management and to establish a threshold in the different phases of the crop below which detrimental effects could be caused to the crop. With respect to the probes located closest to the drippers, a drop in the relative soil water content (RSWC) below 0.2 would not be advisable for “non-stress” scheduling in the preharvest period. When no deficit irrigation strategies are applied in the postharvest period, the criteria are similar to those of preharvest. However, the probes located between the dripper at 0.15 and 0.30 m depth provide information on moderate water stress if the RSWC values falls below 0.2. The severe tree water stress was detected below 0.1 RSWC in probes located at 60 cm depth from this same position.

Highlights

  • The amount of water available for irrigation is limited [1], especially in the face of the increasing demand of a constantly growing world population which is predicted to rise to about 9.8 billion in Agronomy 2020, 10, 1757; doi:10.3390/agronomy10111757 www.mdpi.com/journal/agronomy2050 [2]

  • Three methods can be used in this respect for proper irrigation scheduling: the water balance-based method, the method based on monitoring soil water content or potential and the method which uses plant water status as the reference for irrigation scheduling [1,7]

  • Soil water content monitoring does not always provide information about plant water status, as this depends on the complex relationship between soil, plant and atmosphere, and in addition, the uncertainty caused by the heterogeneous distribution of water in the soil needs to be taken into account

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Summary

Introduction

The amount of water available for irrigation is limited [1], especially in the face of the increasing demand of a constantly growing world population which is predicted to rise to about 9.8 billion in Agronomy 2020, 10, 1757; doi:10.3390/agronomy10111757 www.mdpi.com/journal/agronomy2050 [2]. Increases in evaporation and reductions in precipitation rates are expected [4], which will entail a reduction of the available water resources for the twenty-first century [5] In this context, the adoption of efficient irrigation systems can help to decrease agricultural water consumption, improve farm profitability and reduce environmental impacts. The use of soil and plant measurements for irrigation scheduling assessment is a very attractive approach because they allow adaptation to specific plot and crop conditions. Such an approach entails greater complexity in terms of the collection, processing and interpretation of information

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