High-throughput methods for measuring protein extractability in sugar beet (Beta vulgaris L.) leaves.

Abstract

Background Most components from the roots of sugar beet (Beta vulgaris ssp. vulgaris) are valorized by industry. However, the leaves are currently left on the field, even though they contain large amounts of protein. To support leaf protein valorization, high-throughput methods and phenotyping tools were developed to facilitate the selection of beet varieties with superior protein production. This study presents high-throughput methods to measure total protein content in leaves and to determine the amount of soluble protein extracted through pressing, enabling the calculation of leaf protein extractability. Results The influence of harvested leaf sample size and within-plant leaf selection on protein measurements is demonstrated. Representative samples of a plot entailed collection of the middle leaves from a minimum of 25 plants. To determine total leaf protein, a near-infrared-based model was developed, exhibiting excellent predictive performance. Protein measurements on leaf protein extracts, based on total nitrogen, were found to correlate strongly with RuBisCO quantification obtained through size-exclusion chromatography. Non-protein nitrogenous compounds were measured to assess their impact on protein estimates derived from total nitrogen measurements. A strong correlation between total nitrogen and proteinogenic nitrogen was observed, confirming total nitrogen as a reliable indicator of true protein content in sugar beet leaves. Conclusion This study provided high-throughput methods for assessing leaf protein content and extractability in sugar beet. The strong correlation between total nitrogen and true protein confirms their reliability for protein quantification. These findings aid efficient screening of sugar beet germplasm for improved leaf protein yield, contributing to sustainable leaf valorization. © 2025 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Plant phenotyping relevance

葉のタンパク質含量・抽出性を高スループットに測定する手法を開発し、NIRモデルや窒素測定を検証しており、植物形質の取得法が研究の中心である。

Code and data availability

The paper's phenotype measurements (protein content, extractability, NIR spectra, RuBisCO data) are not publicly deposited; the authors state they are available only on request. A custom R script (S1) exists in supporting information but no public authors' URL is provided.

No evidence-backed public reproduction asset is currently recorded.