High Throughput Phenomics Pipeline for Pulse Crop Nutritional Breeding

Author

• Amod Udayanga Madurapperumage, Clemson UniversityFollow

Date of Award

5-2026

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Plant and Environmental Science

Committee Chair/Advisor

Dr. Dil Thavarajah

Committee Member

Dr. William Bridges

Committee Member

Dr. M.Z. Naser

Committee Member

Dr. Lucas Boatwright

Committee Member

Dr. George Vandemark

Abstract

Dry pea (Pisum sativum L.), lentil (Lens culinaris Medik.), and chickpea (Cicer arietinum L.) are major pulse crops valued for their high nutritional composition and importance to global food systems. Pulses are rich in carbohydrates, protein, and essential minerals, making them ideal whole foods and critical contributors to food and nutrition security. Due to these advantages, pulse breeding programs are increasingly focusing on enhancing nutritional traits, such as protein quality, amino acid balance, and micronutrient density, through the process of biofortification. However, improvement of agronomic traits remains equally essential. Characteristics such as plant height, standability, stress tolerance, and disease resistance have a direct influence on grain yield, farmer adoption, and mechanical harvesting efficiency. Therefore, pulse improvement requires simultaneous progress in nutrition, agronomy, and end-use quality. A major barrier to progress is the inefficiency of phenotyping. Traditional laboratory and field-based methods for nutritional and morphological assessment are cost-prohibitive, slow, and limited in throughput. Therefore, breeding programs often analyze fewer samples than are required for accurate selection, creating a phenomics bottleneck that slows discovery and genetic gain. High-throughput phenotyping (HTP) strategies provide a solution by generating rapid and large-scale datasets that support predictive breeding decisions.

This dissertation evaluates two complementary HTP systems. First, Fourier transform mid-infrared (FT-MIR) spectroscopy is used to quantify macronutrients by analyzing chemical vibration signatures within the mid-infrared spectrum. When paired with chemometric modeling, FT-MIR can replace labor-intensive wet chemistry assays, reducing analytical time and cost while maintaining accuracy. Second, unmanned aerial vehicles (UAVs) equipped with visible, red, green, and blue (RGB) sensors are used to measure agronomic traits, including canopy area and canopy height, as well as monitor physiological maturity for dry pea and other cash crops in South Carolina. Advances in photogrammetry and spectral index modeling now enable UAV tools to capture complex plant traits efficiently at the field scale. A third research component targets dry pea flavor quality. Off-flavors such as beany, earthy, and grassy notes limit consumer acceptance despite the nutritional benefits of pulses. This work applies chromatographic instruments, including gas chromatography coupled with mass spectrometry (GC-MS) and high performance liquid chromatography (HPLC), to identify chemical precursors associated with flavor development, with the long-term objective of constructing a rapid FT-MIR-based screening tool for flavor-related molecular markers.

Collectively, these studies integrate nutritional, agronomic, and flavor characterization into a unified high-throughput pipeline for pulse breeding. The outcomes aim to improve phenotyping speed and cost-efficiency, enable better trait prediction, and accelerate the development of pulse cultivars with superior nutrition, agronomic resilience, and consumer quality. This integrated approach supports future breeding decisions and strengthens the role of pulses in global food and health systems.

Recommended Citation

Madurapperumage, Amod Udayanga, "High Throughput Phenomics Pipeline for Pulse Crop Nutritional Breeding" (2026). All Dissertations. 4204.
https://open.clemson.edu/all_dissertations/4204

Author ORCID Identifier

https://orcid.org/0009-0004-7263-7745