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Journal of Agriculture ›› 2026, Vol. 16 ›› Issue (3): 33-39.doi: 10.11923/j.issn.2095-4050.cjas2025-0182

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Correlation and Path Analysis of Main Agronomic Traits in Blueberry Hybrid F1 Generation

YANG Hongtao(), YANG Yanlin, HE Jiawei, YANG Zhengsong, SU Zechun(), YU Ying   

  1. Alpine Economic Plant Research Institute, Yunnan Academy of Agricultural Sciences, Lijiang, Yunnan 674100
  • Received:2025-09-24 Revised:2025-11-19 Online:2026-03-20 Published:2026-03-19

Abstract:

Correlation and path analysis of major agronomic traits and yield-related characteristics in blueberry F1 hybrids were conducted to clarify the characteristics and relationships between key agronomic traits and per-plant yield. This study aimed to explore the heterosis potential of blueberry hybrids and provide a reference for formulating appropriate breeding objectives. Using 21 blueberry hybrid progenies as test materials, 13 agronomic traits were investigated under subtropical climatic conditions. Correlation analysis revealed that stem diameter (X4) exhibited a significant positive correlation with per-plant yield, while east-west canopy width (X1), north-south canopy width (X2), leaf number (X5), fruiting branch number (X10), and total fruit set (X11) showed highly significant positive correlations with yield. Other traits displayed varying degrees of correlation. Path analysis indicated that the contribution of each trait to per-plant yield ranked as follows: total fruit set (X11)> single-fruit weight (X8) > fruit longitudinal diameter (X7)> north-south canopy width (X2)> hundred-fruit weight (X9)> fruiting branch number (X10)> east-west canopy width (X1)> plant height (X3)> fruit transverse diameter (X6)> average fruit set per branch (X12)> stem diameter (X4)> leaf number (X5). Through dimensionality reduction via multiple linear regression, 12 agronomic traits were consolidated into new variables represented by fruit longitudinal diameter (X7), single-fruit weight (X8), and total fruit set (X11). The adjusted coefficient of determination for these new variables reached 0.971, and the established regression equation Y=-0.4091-0.0057X7+0.2177X8+0.0022X11 effectively explained the influence of relevant factors on per-plant yield. Total fruit set (X11) of blueberry F1 hybrids demonstrated a highly significant positive correlation with yield, and the top three direct path coefficients were ranked as total fruit set (X11), single-fruit weight (X8), and fruit longitudinal diameter (X7). These three traits adequately explained the impact of correlated factors on yield. During the selection of blueberry F1 hybrids, the selection criteria for total fruit set, single-fruit weight, and fruit longitudinal diameter could be appropriately relaxed. Lines 29-2-2, 33-30-A and 30-29-B exhibited F-values of 1.99, 1.65 and 0.96, respectively, achieving the top three comprehensive scores and warranting further investigation.

Key words: blueberry, F1 hybrids, per-plant yield, correlation analysis, path analysis, multiple linear regression, principal component analysis