Graduate Student Exit Seminar: Rajveer Dhillon, Monday, Nov . 10, 10-11 am, 2045 Bainer Hall

BAE Graduate Student Exit Seminar 

Monday, November 10, 2014 
10-11 am, 2045 BAINER HALL


Presenter: Rajveer S. Dhillon 
Ph.D. Candidate 
Department of Biological & Agricultural Engineering 
University of California, Davis 

Limited water resources, increasing population and environmental concerns, are making it necessary to move towards sustainable agriculture practices. Recent drought situations like the one in California highlight the need for developing techniques to use available water resources very efficiently and produce more food for every drop of water by applying just the right amount of water to the right plant or group of plants at the right time, i.e., implementation of precision irrigation techniques to improve water use efficiency. Measuring or estimating water stress of crops is the most important step in developing efficient precision irrigation techniques so that water can be delivered according to the need of plants. To explore spatio-temporal variability of plant water stress, we need to develop economically feasible and convenient to use sensors systems to predict plant water status. The goal of this study was to develop an inexpensive sensor system to predict plant water status on a continuous basis. In this study a leaf monitoring system was developed to continuously monitor plant water status by measuring leaf temperature and other microclimatic parameters in vicinity of the leaf. The sensor system also consisted of leaf holder, solar radiation diffuser dome, and a wind barrier for improved performance of the unit. The system was evaluated for remote data collection and precision irrigation management in commercial almond and walnut orchards. 

Field experiments were conducted during 2013 and 2014 growing seasons. "Leaf monitor" was incorporated into a mesh network of wireless eKo nodes for obtaining the data at a time interval of 16 minutes and for transmitting the data remotely over the web. The leaf monitor data were used to develop Crop Water Stress Index (CWSI) and Modified Crop Water Stress Index (MCWSI) to quantify water stress level. Spatial variability in plant water stress level was accounted for by developing three different management zones and a method was developed and verified to calculate tree specific/ zone specific stress index using leaf monitor data. Temporal variability in stress index was explored by adjusting the stress calculation algorithm over several different time periods. Three temporal resolutions (i) crop specific, (ii) month specific for each crop, and (iii) irrigation specific for each crop, for developing saturation base line to compute stress index values were compared. We found that higher temporal resolution (i.e., irrigation specific) had better sensitivity for detecting changes in plant water stress. 

Relationship between DSWP (Deficit Stem Water Potential) and MCWSI were developed for both crops. Linear relationship was found in case of walnut crop (R2 = 0.66) and a quadratic relationship (R2 = 0.71) was found in case of almond crop. These results indicate more tolerance of almond crop to water stress as compared to walnut crop. The relationships between MCWSI and DSWP were used to implement variable rate irrigation for validating purposes. MCWSI measured before irrigation was used to calculate irrigation amount for low frequency irrigation in walnut crop. Preliminary analysis showed 92 percent accuracy in making irrigation management decisions. On an average 40% less water was used for these variable rate irrigation as compared to 100% ET replacement method. In summary, the leaf monitor has indicated a great potential for use in irrigation management as it was able to provide daily stress index values that correlated well with traditional plant water stress measurements. 

Coffee and cookies will be served.