Objective: This study aimed to evaluate the effect of chitosan on germination indicators and the activity of antioxidant enzymes in safflower seedlings under salinity stress.
Method: The experiment was conducted using a factorial arrangement based on a completely randomized design with three replications at the University of Mohaghegh Ardabili in 2024. The experimental treatments included four salinity levels (0, 50, 100, and 150 mM NaCl) and four concentrations of chitosan (0, 0.2, 0.4, and 0.5% w/v), which were dissolved in 1% acetic acid.
Results: The results showed that salinity stress reduced the germination rate, radicle length, plumule length, seedling length, seedling fresh weight, and seedling dry weight. However, priming with different concentrations of chitosan, especially at 0.5%, improved these traits. The highest daily germination rate (0.114) was observed in the control group (distilled water priming) under 150 mM salinity. The activity of catalase and peroxidase enzymes in the control under 150 mM salinity increased by approximately 43% and 70%, respectively, compared to the 0.5% chitosan treatment under non-saline conditions. Similarly, the activity of superoxide dismutase enzyme in the 0.5% chitosan treatment under 150 mM salinity increased by about 67% compared to the control under non-saline conditions. Furthermore, the ascorbate peroxidase enzyme activity in seeds primed with 0.5% chitosan increased by 37% compared to the control (distilled water priming).
Conclusions: The results indicated that seed treatment with different concentrations of chitosan can mitigate the harmful effects of salinity on some traits of safflower seedlings and improve seedling growth. The best results were achieved when 0.5% chitosan was used under salinity conditions.
Highlights
Objective: This study introduces functional analysis of variance as a method for comparing germination trends under different treatments over a given time interval. This approach not only enables the comparison of treatments over the entire time period but also allows for treatment comparisons at each specific moment in time. Moreover, it identifies critical time points at which the maximum significant difference between treatments occurs, which can serve as novel germination indices.
Method: In this study, real experimental data from four germination studies were analyzed: (1) the effect of temperature on Nigella sativa germination, (2) the effect of salinity stress on Zea mays seed germination, (3) the comparison of germination among different Triticum astivum cultivars, and (4) the effect of water stress on Brassica napus germination. Using spline functions, germination data from these experiments were modeled as a function of time. The results of functional analysis were then used to compare treatments in terms of both germination percentage and germination time across the four experiments.
Results: The results of the functional analysis demonstrated its high efficiency in detecting significant or non-significant differences between treatments throughout the germination period. Furthermore, this method enabled comparisons of germination percentages at any given time point, as well as comparisons of germination times at various germination percentiles, providing detailed insights into the nature of differences among treatments. This approach also facilitated the introduction of new germination indices applicable to different seed types.
Conclusions: Overall, the results of this study indicate that the stepwise functional analysis method introduced here is an effective and precise tool for comparing treatments in germination data. This approach not only enhances treatment comparisons but also provides detailed insights into the nature of differences between treatments. Moreover, it overcomes the limitations associated with using conventional germination indices for treatment comparisons.
Highlights
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