Scholarlink

<p>The textural properties of preserved egg white gel (PEWG) are critical for consumer acceptability, yet quality assessment remains largely reliant on subjective sensory evaluation. Existing texture profile analysis (TPA) protocols lack standardization, compromising reproducibility. Here, TPA parameters were systematically optimized using a coefficient of variation (CV) minimization strategy. The recommended protocol uses cubic samples (10 × 10 × 10 mm<sup>3</sup>), a P50 probe, 55% compression, and a test speed of 1.0 mm/s. Ten commercial preserved egg samples representing diverse market brands were analyzed under these conditions. Based on triplicate TPA measurements, a principal component analysis (PCA) model integrated key texture attributes (e.g., hardness, springiness, and chewiness) into a comprehensive texture score, which showed strong correlation (R<sup>2</sup> &gt; 0.97) with sensory evaluations by a trained panel (10 assessors) and was consistent with protein structural indicators (β-sheet and disulfide bond content). This standardized protocol improves measurement reproducibility and provides an objective tool for PEWG quality assessment.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Optimizing TPA of Preserved Egg Gel with Sensory-Structural Validation

  • 期刊论文

  • 发表日期：

    2026年2月24日

查看全文
  • Miaomiao Zhang,
  • Baochang Li,
  • Xiaoyu Lv,
  • Bin Xu,
  • Jun Sun

摘要

The textural properties of preserved egg white gel (PEWG) are critical for consumer acceptability, yet quality assessment remains largely reliant on subjective sensory evaluation. Existing texture profile analysis (TPA) protocols lack standardization, compromising reproducibility. Here, TPA parameters were systematically optimized using a coefficient of variation (CV) minimization strategy. The recommended protocol uses cubic samples (10 × 10 × 10 mm3), a P50 probe, 55% compression, and a test speed of 1.0 mm/s. Ten commercial preserved egg samples representing diverse market brands were analyzed under these conditions. Based on triplicate TPA measurements, a principal component analysis (PCA) model integrated key texture attributes (e.g., hardness, springiness, and chewiness) into a comprehensive texture score, which showed strong correlation (R2 > 0.97) with sensory evaluations by a trained panel (10 assessors) and was consistent with protein structural indicators (β-sheet and disulfide bond content). This standardized protocol improves measurement reproducibility and provides an objective tool for PEWG quality assessment.