<div><p>Wheat is among the most important cereal crops in the world today with respect to the area harvested (219 million ha), production (772 million tonnes), and productivity (3.53 tons/ha). However, global wheat production goals for the coming decades are falling short of needed increases. Among the leading factors hindering yields is abiotic stress which is present in nearly 38% of wheat acres globally. Nevertheless, many standard wheat breeding programs focus on yield and yield related traits (i.e. grain yield, plant height, and test weight) in ideal environments rather than evaluating traits that could lead to enhanced abiotic stress tolerance. In this thesis, we explore the use of root and high-throughput phenotyping strategies to aid in further development of abiotic stress tolerant varieties. </p><p>In the first three experiments, root phenotypes were evaluated in two nitrogen (N) treatments. Over a series of seedling, adult, and multiple-growth-stage destructive plant biomass measurements, above-ground and below-ground traits were analyzed in seven geographically diverse wheat accessions. Root and shoot biomass allocation in fourteen-day-old seedlings were analyzed using paper-roll-supported hydroponic culture in two Hoagland solutions containing 0.5 (low) and 4.0 (high) mM of N. Root traits were digitized using a WINRhizo platform. For biomass analysis at maturity, plants were grown in 7.5-liter pots filled with soil mix using the same concentrations of N. Traits were measured as plants reached maturity. In the third N experiment, above- and below-ground traits were measured at four-leaf stage, stem elongation, heading, post-anthesis, and maturity. At maturity, there was a ~15-fold difference between lines with the largest and smallest root dry matter. However, only ~5-fold difference was observed between genotypes for above-ground biomass. In the third experiment, root growth did not significantly change from stem elongation to maturity. </p><p>In the final experiment, two of these lines were selected for further evaluation under well-watered and drought treatments. This experiment was implemented in a completely randomized design in the Controlled Environment Phenotyping Facility (CEPF) at Purdue University. The differential water treatments were imposed at stem elongation and continued until post-anthesis, when all plants were destructively phenotyped. Image-based height and side-projected area were associated with height and shoot dry matter with correlations of r=1 and r=0.98, respectively. Additionally, 81% of the variation in tiller number was explained using convex hull and side-projected area. Image-based phenotypes were used to model crop growth temporally, through which one of the lines was identified as being relatively more drought tolerant. Finally, the use of the Munsell Color System was explored to investigate drought response.</p><p>These experiments illustrate the value of phenotyping and the use of novel phenotyping strategies in wheat breeding to increase adaptation and development of lines with enhanced abiotic tolerance.</p></div><br>

<p>Plant root phenotyping technologies play an important role in breeding, plant protection, and other plant science research projects. The root phenotyping customers urgently need technologies that are low-cost, in situ, non-destructive to the roots, and suitable for the natural soil environment. Many recently developed root phenotyping methods such as minirhizotron, CT, and MRI scanners have their unique advantages in observing plant roots, but they also have disadvantages and cannot meet all the critical requirements simultaneously. The study in this paper focuses on the development of a new plant root phenotyping robot that is minimally invasive to plants and working in situ inside natural soil, called “MISIRoot”. The MISIRoot system (patent pending) mainly consists of an industrial-level robotic arm, a mini-size camera with lighting set, a plant pot holding platform, and the image processing software for root recognition and feature extraction. MISIRoot can take high-resolution color images of the roots in soil with minimal disturbance to the root and reconstruct the plant roots’ three-dimensional (3D) structure at an accuracy of 0.1 mm. In a test assay, well-watered and drought-stressed groups of corn plants were measured by MISIRoot at V3, V4, and V5 stages. The system successfully acquired the RGB color images of the roots and extracted the 3D points cloud data which showed the locations of the detected roots in the soil. The plants measured by MISIRoot and plants not measured (controls) were carefully compared with Purdue’s Lilly 13-4 Hyperspectral Imaging Facility (reference). No significant differences were found between the two groups of plants at different growth stages. Therefore, it was concluded that MISIRoot measurements had no significant disturbance to the corn plant’s growth.</p>