Plant sensor-based precision irrigation for improved vineyard water use efficiency, grape and wine composition and quality, and vineyard profitability
Abstract
Prudent water management in Australian vineyards has become increasingly important in light of current energy market prices, potential oversupply of grapes and wine leading to low farm gate prices paid for grapes, as well as inefficiencies in ageing irrigation infrastructure in many vineyards. Increasing the efficiency of irrigation water use to maximise yield and/or quality is one strategy to address some of these issues, and can be done by precise monitoring of soil and vine moisture levels, and applying irrigation based on cultivar- specific thresholds relevant to each metric based on phenological stage.
We evaluated the benefits associated with implementing irrigation schedules on Cabernet Sauvignon and Shiraz grapevines in Coonawarra based on non-data-driven (CONV) and data-driven metrics including crop evapotranspiration (ETc), soil moisture thresholds (SWS), and two plant-based water status thresholds (PWS/PWS1, PWS2). SWS and PWS strategies were informed by remote monitoring of the respective parameters using continuous moisture sensors.
Our results indicated that using data-driven approaches was generally superior to non-data-driven methods, and that water use efficiency (WUE = yield/irrigation) could be enhanced, particularly when using metrics that were associated with the vine itself i.e. ETc and PWS. Despite inter-annual variations in the results that were attributed to seasonal weather conditions, we observed three- to six-fold increases in WUE based on data-driven methods compared to the conventional (non-data driven) method in Cabernet Sauvignon, and a doubling of WUE in Shiraz. Comparing various irrigation schedules, PWS1, based on proximal thermal sensors, had the highest WUE in Shiraz during the final season, while ET had the highest WUE in Cabernet Sauvignon in the same season. The PWS group consistently outperformed the conventional group every season. Despite reductions in irrigation in the data-driven treatments, no significant impacts to yield or grape composition parameters were observed. High resolution remote sensing was utilised to generate spatial and temporal information of all three-vineyard blocks; these data were used to develop predictive models of soil and vine water status, gas exchange and crop coefficients. Financial (cost-benefit) analysis revealed that the economic water productivity (gross margin $ per ML of water applied) for Cabernet Sauvignon was four-fold higher in the ET and PWS treatments and CONV was highest in Shiraz due to the high yields obtained in the final season. Finally, an irrigation practices survey conducted in 2021 across the Limestone Coast region revealed that over 70% of growers used experience or historical schedules to irrigate and only 6% of growers used plant-based sensors to inform their irrigation decisions.
The greatest barriers to adoption of new technology for irrigation decision-making were a lack of understanding of their value and high cost. This study has demonstrated the potential of several direct, proximal and remote irrigation sensors and tools to determine irrigation schedules in order to increase water use efficiency in grapevine through precision irrigation.
Summary
The overarching objective of this project was to assess the value of plant-sensor-based precision irrigation on grapevine performance, water use efficiency and grape and wine composition of Cabernet Sauvignon (CAS) and Shiraz (SHI) grapevines. The project was conducted in the Coonawarra viticultural region of South Australia. In the first three seasons, five irrigation strategies were investigated: conventional or grower-driven approach (CONV), 2x CONV for ‘well-watered’ vines (CONV+), and three data-driven (sensor-based) irrigation strategies: vine water status based on proximal thermal sensors (PWS/PWS1), soil water status (SWS), and crop evapotranspiration (ETc). In the fourth season (2021/22), an additional plant sensor-based irrigation strategy based on continuous measurement of trunk water potential (PWS2) was also evaluated. Additionally, UAV-based remote sensing was used to obtain high resolution (vine-level) estimates of grapevine crop coefficients, soil and water status, and canopy gas exchange.
For measuring plant performance and water status, various instruments for direct, proximal and remote sensing were used at key phenological stages of grapevine development. The evidence- or sensor-based irrigation strategies had a clear advantage of saving irrigation water in CAS and SHI grown in Terra rossa soil and Rendzina soils (SHI in Terra rossa only). For instance, in 2020/21 season (S3) in CAS (in lighter Terra rossa soil), ET- and PWS-treated vines received only 38% and 67% of the total irrigation of CONV+ treated vines. However, despite significantly lower soil and plant water status, ET- and PWS-treated vines showed similar net carbon assimilation (AN), stomatal conductance (gs), leaf intrinsic water use efficiency (WUEi), yield, and berry anthocyanin and phenolics concentrations relative to CONV+ vines. Reduction of irrigation by 38% in SWS treatments led to significant reductions in soil and plant water status, gs and AN however, vines maintained similar WUEi relative to CONV+ treatment. The reduction of irrigation did not result in a yield penalty, nor reduced berry and juice composition in the CAS vines on Terra rossa soils.
In the 2020/21 season in CAS on heavier Rendzina soils, sensor-based irrigation reduced water supply by 30-40% relative to CONV+. Despite significantly lower plant water status and gs, all vines maintained similar WUEi to CONV+. ET and PWS treatments did not result in yield penalties, a positive result, however, yield was significantly reduced in the SWS treatment relative to CONV+ vines.
In SHI grapevines on Terra rossa soils, plant sensor-based irrigation (PWS) reduced irrigation by 40-60% compared to CONV+ treated vines. Even though reduced water supply significantly reduced plant water status and leaf gas exchange, PWS1, PWS2 and SWS treatments significantly improved WUEi relative to CONV+ vines during 2021/22 season, without yield penalties or decreases in berry/juice composition parameters.
Overall, our results suggest that both ET- and plant sensor-based irrigation scheduling are superior approaches for high-quality grape/wine production for CAS, while in SHI, the plant sensor-based irrigation scheduling approach is superior in order to increase water use efficiency without yield or quality penalties.
Using high-resolution (UAV-based) thermal and multispectral remote sensing in conjunction with machine learning modelling, we obtained spatial (vine-level) and temporal (phenology-specific) information on soil moisture (Ψpd) and vine physiological parameters (Ψs, An, gs, WUEi, Kc) for the entire vineyard block and beyond the trial sub-block. These predictive models can aid practitioners in implementing precision irrigation i.e. irrigating blocks at the sub-block level, based on water requirements as determined by the various sensors such as those evaluated in this project. The spatial maps can also be used to inform the placement of proximal or direct plant and soil sensors for improved decision-making at the sub-block level.
Financial analysis of the various data-driven options (PWS, SWS, ET) versus the non-data-driven option (CONV/CONV+) indicated that there was a strong dependence of gross margin and payback period on yield and/or irrigation application rates. Hence, the ET (in CAS and SHI) and PWS (in SHI) treatments had the highest financial returns to the grower based on lower water application rates, as yields were similar across the different strategies. These differences would be even higher if growers had to pay for water, increasing the impetus for using sensors to inform irrigation decisions.
The project successfully met its objectives and delivered:
- a comprehensive evaluation of various irrigation scheduling methods available to grape growers that are based on subjective and objective assessments. Vine performance and fruit/wine level assessments were carried out for each irrigation regime.
- an evaluation of two new commercial crop water status sensors and determination of their thresholds to increase water use efficiency.
- a new high-resolution remote sensing platform for assessment of canopy performance, and spatial and temporal prediction of the same parameters.
- a financial analysis of the different irrigation scheduling strategies evaluated in this study.
- a comprehensive industry survey of current irrigation practices in the Limestone Coast.
- knowledge dissemination to the industry via seminars and scientific papers.