Salt stress limits plant growth and crop productivity and is an increasing threat to agriculture worldwide. In this study, proteomic and physiological responses of Brassica napus leaves under salt stress were investigated. Seedlings under salt treatment showed growth inhibition and photosynthesis reduction. A comparative proteomic analysis of seedling leaves exposed to 200 mM NaCl for 24 h, 48 h and 72 h was conducted. Forty-four protein spots were differentially accumulated upon NaCl treatment and 42 of them were identified, including several novel salt-responsive proteins. To determine the functional roles of these proteins in salt adaptation, their dynamic changes in abundance were analyzed. The results suggested that the up-accumulated proteins, which were associated with protein metabolism, damage repair and defense response, might contribute to the alleviation of the deleterious effect of salt stress on chlorophyll biosynthesis, photosynthesis, energy synthesis and respiration in Brassica napus leaves. This study will lead to a better understanding of the molecular basis of salt stress adaptation in Brassica napus and provides a basis for genetic engineering of plants with improved salt tolerance in the future.

Background: Image processing techniques have been widely used in the analysis of leaf characteristics. Earlier techniques for processing digital RGB color images of plant leaves had several drawbacks, such as inadequate de-noising, and adopting normal-probability statistical estimation models which have few parameters and limited applicability. Results: We confirmed the skewness distribution characteristics of the red, green, blue and grayscale channels of the images of tobacco leaves. Twenty skewed-distribution parameters were computed including the mean, median, mode, skewness, and kurtosis. We used the mean parameter to establish a stepwise regression model that is similar to earlier models. Other models based on the median and the skewness parameters led to accurate RGB-based description and prediction, as well as better fitting of the SPAD value. More parameters improved the accuracy of RGB model description and prediction, and extended its application range. Indeed, the skewed-distribution parameters can describe changes of the leaf color depth and homogeneity. Conclusions: The color histogram of the blade images follows a skewed distribution, whose parameters greatly enrich the RGB model and can describe changes in leaf color depth and homogeneity.