Background In northern Iran and other cold regions, winter freezing injury and resultant yield instability are major limitations to strawberry production. However, there is scarcity of information on the physiological and biochemical responses of strawberry cultivars to freezing stress. This study aimed to investigate the physiological and biochemical responses of strawberry cultivars (Tennessee Beauty, Blakemore, Kurdistan, Queen Elisa, Chandler, Krasnyy Bereg, and Yalova) to different freezing temperature treatments (− 5, − 10, − 15, − 20, and − 25 °C) under controlled conditions. Results All measured physiological and biochemical features were significantly affected by the interaction effect between low temperatures and cultivars. Tennessee Beauty showed the highest RWC at − 25 °C. The highest Fv/Fm was observed in Queen Elisa. Krasnyy Bereg had the least freezing injury (FI) in crown and leaf, while Yalova and Chandler showed the highest crown and leaf FI, respectively. At − 20 to − 25 °C, the highest carbohydrates contents of crown and leaf were noted in Blakemore and Krasnyy Bereg cultivars, respectively. The Yalova showed the highest protein content in both crown and leaf tissues at − 25 °C. The Tennessee Beauty and Blackmore cultivars showed the highest proline in crowns and leaves at − 15 °C, respectively. The highest ThioBarbituric Acid Reactive Substances (TBARS) contents in the crown and leaf were observed in Kurdistan and Queen Elisa, respectively. Queen Elisa and Krasnyy Bereg cultivars showed SOD and POD peaks in the crown at − 15 °C, respectively. Conclusion Freezing stress was characterized by decreased Fv/Fm and RWC, and increased FI, TBARS, total carbohydrates, total proteins, proline content, and antioxidant enzyme activity. The extent of changes in above mentioned traits was cultivar dependent. FI and TBARS were the best traits among destructive parameters for evaluating freezing tolerance. Moreover, maximum quantum yield of PSII (Fv/Fm index), as non-destructive parameters, showed a significant efficiency in rapid assessment for screening of freezing tolerant strawberry cultivars. The cultivars Krasnyy Bereg, Queen Elisa, and Kurdistan were the most tolerant cultivars to freezing stress. These cultivars can be used as parents in breeding programs to develop new freezing tolerant cultivars.

In estimation of genetic parameters in perennial tree species on the basis of analysis of variance (ANOVA), heterogeneity of years and genotype × environment interaction for data sets during the juvenility to maturity life period is ignored. Therefore, a linear mixed model based on restricted maximum likelihood (REML) approximation for modeling of covariance structure of longitudinal data can improve our ability to analyze repeated measures data. In the present research, a modeling of variance-covariance structure by mixed model based on the REML approach has been used for characteristics of 26 apricot genotypes recorded during three years. Fitting unstructured covariance (UN) models for all traits indicated a great heterogeneity of variances among repeated years and the trends of response variables in the genotypes (except for RWC) was due to imperfect correlation of subjects measured in different years. Based on the same structure, positive correlations were estimated among fruit set, potassium content, and yield of pistil in repetitive years, and most traits showed high heritability estimation. To our knowledge, this is the first report in plant that genotypic correlation and heritability and their standard errors are estimated in a repeated measures data over years using REML approximation.Key words: longitudinal data, unstructured covariance, mixed model, biplot, genotype × year interaction, Prunus armeniaca.Résumé : Lorsqu'on estime les paramètres génétiques des essences d'arbre pérennes par analyse de la variance (ANOVA), on ne tient pas compte de l'âge hétérogène des arbres ni des interactions entre leur génotype et l'environnement dans les jeux de données prélevées durant leur jeunesse, jusqu'à maturité. Un modèle linéaire mixte reposant sur l'approximation du maximum de vraisemblance restreint (REML) visant à reproduire la structure de la covariance des données longitudinales pourrait nous aider à mieux analyser les mesures répétitives. Les auteurs de cette étude ont modélisé la variance-covariance avec un modèle mixte s'appuyant sur le REML afin de vérifier les caractères de 26 génotypes d'abricot observés pendant trois ans. L'ajustement des modèles non structurés de covariance pour l'ensemble des caractères révèle la forte hétérogénéité de la variance les années où les relevés sont répétés, mais aussi que les tendances suivies par les variables-réaction du génotype (sauf la concentration d'eau relative) résultent d'une corrélation imparfaite entre les sujets évalués différentes années. Recourant à la même structure, les auteurs ont évalué les corrélations positives entre la nouaison, la teneur en potassium et le rendement des pistils lors des années répétitives et constaté que la plupart des caractères présentent une grande héritabilité. Pour autant qu'on le sache, il s'agit du premier rapport sur les plantes où l'on estime la corrélation génotypique, l'héritabilité et leurs écarts-types pour des mesures prises à répétition plusieurs années à partir d'une approximation du REML. [Traduit par...

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