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Multivariate Statistical Analyses and Predictive Model of Cold Resistance Associated with Eleven Crabapples and Fuji

Y Hu¹, Y Wang², Y Zhu¹

¹College of Horticulture, Gansu Agricultural University, Lanzhou 730070, China.

|April 10, 2019

Abstract

Background:

Cold is one of the bottlenecks restricting the development of apple industry in the Northwest Loess Plateau of China. Crabapples play indispensable roles in the apple industry as excellent rootstocks and potential pollination trees.

Objective:

The purpose of this experiment was to compare the cold resistance of crabapples and Fuji and provide reference for the simple evaluation of cold resistance.

Materials And Methods:

11 crabapples and '2001Fuji' were employed as test materials. Nine physiological parameters were measured under low temperature (0, -15, -20, -30, -35 and -40°C) treatments and the anatomical structures of the leaves were observed. Principal component analysis (PCA), regression analysis (RA) and system cluster analysis (SCA) were adopted to analyze the data of physiological parameters and leaf anatomical structure.

Results:

According to PCA, the cold resistance of 12 genotypes was identified and the order of cold resistance is as follows: HS, HB, HF, HY, FS, HS, XQ, XK, XL, DG, Q, and HL. Moreover, the regression equation evaluating cold resistance was obtained by RA and 12 genotypes were divided into 4 categories by SCA.

Conclusion:

Multivariate statistical analysis methods can overcome the defects of single index evaluation. The lethal-temperature (LT₅₀) can more accurately reflect the cold resistance of plants than other physiological parameters.

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