2025 AOCS Annual Meeting & Expo.
Processing
Aicha Asma Houfani
Ph.D.
University of British Columbia, British Columbia, Canada
Praiya Asavajaru
Technical Officer
National Research Council Canada
Saskatoon, Saskatchewan, Canada
Jogindh Sivakumar Suganthi
BSc researcher
UBC, Canada
Prem Prakash Das
Ph.D.
National Research Council Canada, Canada
Kishore Rajagopalan
Ph.D.
National Research Council Canada, Canada
Richard Huang
Ph.D.
RedShiftBio, United States
Anusha Samaranayaka, PhD
Ph.D.
National Research Council Canada
Saskatoon, SK, Canada
Derek R. Dee (he/him/his)
Ph.D.
University of British Columbia
Vancouver, British Columbia, Canada
Pea proteins are widely used in foods, yet relatively little is known about the pea seed proteome and how its composition changes across plant varieties and growing and processing conditions. This project examined the proteome of peas, with particular attention to the proteins impacting functionality, nutrition and quality. Data-Independent Acquisition (DIA) quantitative mass spectrometry (LC-MS/MS) was used to examine protein expression patterns in Pisum sativum (yellow field pea) across cultivars CDC Lewochko, CDC Meadow, CDC Amarillo, CDC Spectrum and AAC Profit, and across processing conditions (flour, dry and wet fractionation, and radiofrequency and infrared heating). Furthermore, correlations between the proteomes and protein techno-functional (e.g. WHC, OHC, gellation, foaming, and solubility) and structural (e.g. hydrophobicity, secondary structure) features were investigated. Over 3,600 proteins were identified, among which 1,796 were differentially expressed across processing treatments. We observed distinct clusters of proteins with varying expression levels across the different conditions. Protein groups such as vicilin, albumin, and seed lipoxygenase were particularly sensitive to thermal processing. Notably, a consistent group of proteins (vicilin, legumin, and albumin) exhibited higher relative abundance in the wet fractionation condition. Understanding the protein expression patterns will help optimize processing techniques to enhance the functional and nutritional qualities of pea-based products.