Optimizing Seed Physiological Maturity and Quality in Camelina Through Plant Density Variation: A Nonlinear Regression Approach

Abstract

Investigations into the seed physiological maturity (PM) and achieving optimal seed quality (SQ) across varying plant densities are crucial. This is because harvesting seeds at the right time is critical to assure their viability and vigor. The use of nonlinear regression models could estimate the accurate time of PM and SQ in camelina at all plant densities based on days after flowering (DAF) and/or seed moisture content (SMC). To attain this goal, camelina seeds were sown manually at a 2–3 cm burial depth with four plant densities (150, 600, 1050, and 1500 m⁻² with ± 5% bias) in eight replicates. Seeds were sampled from 10 DAF at regular intervals every 5 or 10 days (depending on the weather conditions) for all plant densities. We examined the changes in fresh weight, dry weight, moisture content, oil content, and electrical conductivity of seeds. We also studied seed germination rate, normal seedling, and dry weight and length of seedlings about the flowering date across different plant densities. Our results were successful in accurately predicting the timing PM and SQ in camelina across all plant densities using DAF and/or SMC (R² ≥ 80) as a basis. Besides, no significant difference among all studied plant densities in terms of the studied traits was detected. These findings enable the fine-tuning of agronomic practices, such as determining the optimal harvest period. They also provide valuable support for developmental studies aiming to establish connections between physiological parameters and genetic or physiological factors.