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Scholarly Works (3 results)

  • Thesis
  • Peer Reviewed
UC Davis Electronic Theses and Dissertations (2024)

The steady increase in atmospheric CO2 since the industrial revolution is well established as the major driver of global climate change but its direct impacts on biochemical processes like photosynthesis are also of major concern. Some crop plant species have been shown to be less effective at assimilating nitrate, the most abundant form of nitrogen available to plants in most agricultural soils, when grown under elevated CO2. This indicates that rising CO2 concentrations could negatively impact the nitrogen use efficiency of many important crop species and may explain why protein content in some plant species decreases with CO2 enrichment. Improved techniques to measure nitrogen metabolism in plants are needed to further study the underlying cause of this phenomenon and mitigate the impact of rising atmospheric CO2 on our food supply. The three projects described here are a part of this effort. Chapter 1 describes a rosette area measurement tool that was developed as part of a larger study investigating the genetic basis of plant response to different nitrogen forms and concentrations. This tool was able to accurately estimate rosette area from photographs of Arabidopsis seedlings grown on agar plates even when the photographs did not provide a scale. We present a general-purpose ultra-high-resolution data acquisition system in chapter 2. The system interfaces a 32-bit analog to digital converter with a Raspberry Pi single board computer. We provide a simple open-source hardware design and easy to use software libraries enabling this system to be easily built and adapted for any purpose. Finally, we demonstrate the high performance of the system by making precise temperature measurements. Many elements of this data acquisition system were used in the Oxygen analyzer described in chapter 3. Chapter 3 documents the design and characterization of a novel high-resolution oxygen analyzer designed to measure small O2 fluxes against the large ambient background. The original motivation for this instrument was to estimate nitrate assimilation in plants through the ratio of CO2 assimilated to O2 evolved. The design is based around a zirconia O2 sensor that has not traditionally been used for high precision applications. The O2 measurement repeatability of the analyzer was better than 70 ppm, nearly 2 orders of magnitude better than what had previously been reported for an analyzer using this type of sensor. Further improvements to temperature control may yield even higher precision enabling measurements of photosynthetic O2 fluxes.

    Cover page: A High-Resolution Oxygen Analyzer and Other Tools for Plant Nutrition Research and Beyond
    • Article
    • Peer Reviewed
    UC Davis Previously Published Works (2022)

    Premise

    High-precision data acquisition (DAQ) is essential for developing new methods in the plant sciences. Commercial high-resolution DAQ systems are cost prohibitive, whereas the less expensive systems that are currently available lack the resolution and precision required for many physiological measurements.

    Methods and results

    We developed the software libraries, called piadcs, and hardware design for a DAQ system based on an ultra-high-resolution analog-to-digital converter and a Raspberry Pi computer. We tested the system precision with and without a thermocouple attached and found the precision with the sensor to be better than ±0.01°C and the maximum possible system resolution to be 0.4 ppm.

    Conclusions

    The ultra-high-resolution DAQ system described here is inexpensive, flexible enough to be used with many different sensors, and can be built by researchers with rudimentary electronic and computer skills. This system is most applicable in the development of new measurement techniques and the improvement of existing methods.
      Cover page: Easy as piadcs: A low‐cost, ultra‐high‐resolution data acquisition system using a Raspberry Pi
      • Article
      • Peer Reviewed
      UC Davis Previously Published Works (2022)

      Premise

      The agar-based culture of Arabidopsis seedlings is widely used for quantifying root traits. Shoot traits are generally overlooked in these studies, probably because the rosettes are often askew. A technique to assess the shoot surface area of seedlings grown inside agar culture dishes would facilitate simultaneous root and shoot phenotyping.

      Methods

      We developed an image processing workflow in Python that estimates rosette area of Arabidopsis seedlings on agar culture dishes. We validated this method by comparing its output with other metrics of seedling growth. As part of a larger study on genetic variation in plant responses to nitrogen form and concentration, we measured the rosette areas from more than 2000 plate images.

      Results

      The rosette area measured from plate images was strongly correlated with the rosette area measured from directly overhead and moderately correlated with seedling mass. Rosette area in the large image set was significantly influenced by genotype and nitrogen treatment. The broad-sense heritability of leaf area measured using this method was 0.28.

      Discussion

      These results indicated that this approach for estimating rosette area produces accurate shoot phenotype data. It can be used with image sets for which other methods of leaf area quantification prove unsuitable.
        Cover page: Novel method for the quantification of rosette area from images of Arabidopsis seedlings grown on agar plates
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