My journey towards developing the most accurate soil moisture sensor began as an undergraduate, a pursuit that continues to challenge me today. This quest has led me to explore alternative approaches, including plant-based methods for assessing soil moisture.
Inspired by the pioneering work of Jackson et al. (1981) and the USDA-ARS scientists at Bushland, TX on plant-based irrigation scheduling, my research at Washington State University, funded by METER Group, focused on plant water stress detection and irrigation management. This article summarizes our efforts and outlines the future direction of this research.
Objectives
Our research aimed to:
Develop a site-specific irrigation control and monitoring system that continuously monitors plant water status, determines water requirements, and automatically schedules irrigation.
Design and deploy a wireless network of soil, plant, and microclimate sensors.
Determine real-time plant water requirements.
Develop and assess irrigation scheduling algorithms based on plant, soil, and weather data.
Develop a sensor-based setup with plant-based models integrated into its software for precise non-contact sensing of soil water content, soil water potential, and stem water potential by measuring canopy temperature and micrometeorological parameters.
Challenges
Utilizing plant sensors, specifically the Crop Water Stress Index (CWSI), to detect plant water stress in apple orchards presented several challenges:
Limitations of Existing ET Models: Available ET models like Penman-Monteith did not adequately explain stomatal regulations in most crops, leading to unreliable estimations. The empirical or theoretical CWSI derived from FAO-56, primarily based on alfalfa or grass, may not accurately represent the behavior of trees like apples. Apple tree leaves exhibit a high degree of sensitivity to atmospheric conditions, actively controlling stomata to minimize water loss.
Lack of Established Practices: Automated plant-based irrigation scheduling methods were largely unexplored in apple trees and rarely implemented in other tree crops.
Crop-Specific Modeling Efforts
To address these challenges, we developed novel crop water stress indices and algorithms specifically for apple trees, incorporating our understanding of their physiology and research findings. Key developments include:
New Crop Water Stress Index: We developed a new theoretical CWSI for apple trees that accounts for stomatal regulations using a canopy conductance sub-model. This index estimates average actual and potential transpiration rates for the canopy area observed by an infrared temperature (IRT) sensor or thermal camera.
"Apple Tree" CWSI: This CWSI is grounded in the energy budget of a single apple leaf, eliminating the need to consider soil heat flux in the modeling.
Data Collection and Validation
To validate these models, we conducted field measurements in several experimental and commercial orchards across Washington State over four years.
Soil Moisture Measurements: We employed a neutron probe (NP) to measure soil water deficit in the top 60 cm of the soil profile (root zone), providing precise and volumetric data.
Plant and Environmental Data: We collected canopy surface temperature data using IRT sensors, continuous soil water content and soil water potential measurements using soil sensors, and comprehensive microclimate data.
Results
The results demonstrated a strong correlation between the new CWSI model and soil water deficit in the root zone of apple trees across all orchards. This model exhibited high sensitivity to subtle variations in soil water content, indicating its potential as a powerful indicator of water availability in the root zone.
Time Sensitivity of Relationships: While both soil water deficit and soil water potential correlated strongly with thermal-based water stress index models, the relationships exhibited significant time sensitivity.
Measurements taken between 10:00 am and 11:00 am (late morning, peak transpiration) showed the strongest correlations with soil water deficit and soil water potential.
Correlations decreased rapidly beyond this time window, highlighting the importance of considering the specific time of day for CWSI measurements. This observation contrasts with the conventional assumption that midday is the optimal time for CWSI measurements. Apple trees demonstrate unique stomatal behavior, with peak transpiration occurring late morning and late afternoon, and stomatal closure during the hottest hours of the afternoon to minimize water loss.
Comparison with Existing Research
While other studies have explored correlations between remotely sensed satellite-based thermal or NIR measurements and soil water content, these relationships typically lack the predictive power necessary for irrigation scheduling.
Colaizzi's Research: Paul Colaizzi's PhD research at USDA-ARS in Bushland, TX, investigated the relationship between canopy temperature, CWSI, and soil water status in Maricopa, Arizona, building upon the work of Jackson et al. (1981).
Evett's Research: Steve Evett and his team at Bushland, TX, are continuing this research by examining the relationship between CWSI, integrated over the daylight hours, and soil water content in the root zone, particularly near the end of the season when irrigated plots develop significant deficits.
Future Directions
Future research will focus on:
Universality of the Models: Determining the crop and soil specificity of the developed equations.
Application to Other Crops: Extending the research to other fruit trees and potentially row crops under diverse irrigation systems and climates.
Crop Health Monitoring: Incorporating crop health monitoring to ensure that measured signals accurately reflect water stress and not other plant health issues.
Real-time Soil Moisture Monitoring: Developing more efficient and accurate methods for real-time monitoring of soil moisture in the root zone as a reference for plant-based measurements. Currently, the neutron probe, while highly accurate, is labor-intensive and unsuitable for real-time monitoring.
This research has demonstrated the potential of plant-based measurements, particularly CWSI, to accurately assess available soil moisture in the root zone of apple trees. Further refinement and validation of these methods will contribute significantly to the development of more precise and efficient irrigation management strategies for a variety of crops.
References
Jackson, R. D., Idso, S. B., Reginato, R. J., Pinter, P. J. Jr., 1981. Canopy temperature as a crop water stress indicator. Water Resour. Res.17, 1133–1138.
Osroosh, Y., 2020. “Internet of Plants” and Plant-based Irrigation Scheduling.
Osroosh, Y., 2020. Do plant-based irrigation scheduling methods work?
Osroosh, Y., Peters, R.T., Campbell, C., Zhang, Q., 2016. Comparison of irrigation automation algorithms for drip-irrigated apple trees. Computers and Electronics in Agriculture, 128: 87–99.
Osroosh, Y., Peters, R.T., Campbell, C., 2016. Daylight crop water stress index for continuous monitoring of water status in apple trees. Irrigation Science, 34(3): 209–219.
Osroosh, Y., Peters, R.T., Campbell, C., Zhang, Q., 2015. Automatic irrigation scheduling of apple trees using theoretical crop water stress index with an innovative dynamic threshold. Computers and Electronics in Agriculture, 118: 193–203.
Osroosh, Y., Peters, R.T., Campbell, C., 2015. Estimating potential transpiration of apple trees using theoretical non-water-stressed baselines. Journal of Irrigation and Drainage Engineering, 141(9): 04015009.
Osroosh, Y., Peters, R.T., Campbell, C., 2015. Estimating actual transpiration of apple trees based on infrared thermometry. Journal of Irrigation and Drainage Engineering, 141(8): 04014084.
Ferrer-Alegre, F., Mohamed, A.Z., Osroosh, Y., Bates, T., Campbell, C., Peters, R.T., 2019. A comparative study of irrigation scheduling based on morning, daylight and daily crop water stress index dynamic threshold (CWSI-DT) in apple trees. IX International Symposium on Irrigation of Horticultural Crops. June 17-20. Matera, Italy.
Mohamed, A.Z., Osroosh, Y., Peters, R.T., Bates, T., Campbell, C., Ferrer-Alegre, F., 2019. Morning crop water stress index as a sensitive indicator of water status in apple trees. ASABE Annual International Meeting. July 7-10. Boston, MA.
Can Canopy Measurements Determine Soil Moisture? (Part 1-2), 2016. environmentalbiophysics.org
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