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April 15, 2026Phyton0 citationsOpen Access

The Effects of Planting at Varying Seedling Ages on the Agronomic Traits and Nutritional Components of Stem

SBSijun BaoYCYingping ChenXWXiaoqiang Wei

Key Points

  • To determine the effects of planting at varying seedling ages on the agronomic traits and nutritional content of stem lettuce varieties.
  • Evaluated early-maturing variety 'WS120' and late-maturing variety 'WS1'.
  • Established four seedling age treatments at 20, 25, 30, and 35 days.
  • Employed correlation analysis, principal component analysis, and cluster analysis for data evaluation.
  • Significant correlations identified in WS1 (18 pairs) and WS120 (25 pairs) indicators.
  • Principal component analysis consolidated 14 agronomic traits and 4 quality indicators into 3 components with 94.068% contribution.
  • WS1 categorized into two groups based on treatments; superior root indicators at 30 and 35 days, enhanced traits at 20 and 25 days.

Abstract

This study aimed to elucidate the effects of varying seedling ages at planting on the agronomic traits and nutrient content of stem lettuce. The early-maturing variety “WS120” and the late-maturing variety “WS1” were employed as experimental materials. Four seedling age treatments were established at 20, 25, 30, and 35 d. By measuring the agronomic traits and nutrient content of the stem lettuce, we employed correlation analysis, principal component analysis, cluster analysis, and the membership function method for a comprehensive evaluation. This study aims to elucidate the optimal planting age for stem lettuce in plateau regions. By addressing the issues of inconsistent quality and yield that arise from arbitrary selection of planting age in production, we seek to establish a theoretical foundation for the development of a high-quality and efficient cultivation technology system for this crop. The results of the correlation analysis revealed that a total of 18 pairs of indicators in WS1 exhibited significant correlations, comprising 8 pairs that were positively correlated and 10 pairs that were negatively correlated. In WS120, 25 pairs of indicators reached a significant correlation level, with 13 pairs positively correlated and 12 pairs negatively correlated. Principal component analysis identified 14 agronomic traits and 4 quality indicators, which were consolidated into 3 principal components, achieving cumulative contribution rates of 94.068%. Cluster analysis results indicated that WS1 could be categorised into two groups based on different treatments. At 30 d and 35 d, the samples were grouped together due to superior root-related indicators and nutritional components, whereas at 25 d and 20 d, they formed a separate group owing to enhanced agronomic traits. WS120 was classified into Group I, reflecting relatively favourable agronomic traits at 25 d and 20 d. Group II (30 d) was characterised by all indicators falling within the mid-range. Class III (35 d) was distinctly categorised due to elevated levels of vitamin C, soluble sugars, and soluble proteins. A comprehensive evaluation employing the membership function method indicated that the overall performance of WS1 and WS120 under varying treatments was ranked as follows: 25 d > 30 d > 20 d > 35 d. It can be utilised directly to inform production practices and holds considerable practical importance for advancing the high-quality and efficient cultivation of stem lettuce, thereby contributing to the growth of the plateau vegetable industry.

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Cite This Study

Bao et al. (2026) studied this question.

synapsesocial.com/papers/69df2c88e4eeef8a2a6b1bf2https://doi.org/10.32604/phyton.2026.080248
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