A intermediate concentration of atmospheric nitrogen dioxide enhances PSII activity and inhibits PSI activity in expanded leaves of tobacco seedlings.

Nitrogen dioxide (NO2) is a major air pollutant that affects plant growth, development and yields. Previous studies have found that atmospheric NO2 changes plant photosynthesis in a concentration-dependent manner. Low concentrations of NO2 (4.0 µL L-1) can increase photosynthetic rates, while high concentrations of NO2 (16.0 µL L-1) can have an inhibitory effect. However, the specific effects of a critical intermediate concentration of NO2 on the photosynthetic apparatus of plants has remained unknown. Therefore, in this study, tobacco seedlings at three-leaf ages were fumigated with a intermediate concentration of 8.0 µL L-1 NO2 for 15 days to determine the effects on leaf weight, leaf number per plant, chlorophyll content, net photosynthetic rate, the reaction center activity of photosystems I and II (PSI and PSII, respectively) and core protein gene expression (PsbA and PsaA). Fumigation with 8.0 µL L-1 NO2 increased the number of leaves per plant and the weight of leaves, and the leaves became dark green and curly after 10 days of fumigation. During NO2 fumigation for 15 days, the chlorophyll content, PSII maximum photochemical efficiency (Fv/Fm), electron transfer rate (ETR) and non-photochemical quenching (NPQ) increased most in the oldest leaves (Lmax leaves), but decreased PSI activity (∆I/Io). The Fv/Fm, ETR and NPQ in the youngest leaves (Lmin leaves) were lower than those of Lmax leaves, but the actual photochemical efficiency (ΦPSII) of PSII increased most and ∆I/Io was the highest in these samples. The Fv/Fm, ETR, NPQ and ΦPSII in the leaves at the middle leaf age (Lmid leaves) were lower than those of Lmin and Lmax leaves, but the relative fluorescence intensity of point L (VL) and the relative fluorescence intensity of point K (VK) decreased the most in these samples. Thus, this critical concentration of atmospheric NO2 increased the activity of PSII and inhibited PSI activity in expanded leaves of tobacco seedlings.

Effects of salt concentration, pH, and their interaction on plant growth, nutrient uptake, and photochemistry of alfalfa (Medicago sativa) leaves.

In order to explore the main limiting factors affecting the growth and physiological function of alfalfa under salt and alkali stress, the effect of the salt and alkali stress on the growth and physiological function of alfalfa was studied. The results showed that effects of the excessive salt concentration (100 and 200 mM) on the growth and physiological characteristics were significantly greater than that of pH (7.0 and 9.0). Under 100 mM salt stress, there was no significant difference in the growth and photosynthetic function between pH 9.0 and pH 7.0. Under the 200 mM salt concentration the absorption of Na+ by alfalfa treated at the pH 9.0 did not increase significantly compared with absorption at the pH 7.0. However, the higher pH directly reduced the root activity, leaf's water content, and N-P-K content also decreased significantly. The PSII and PSI activities decreased with increasing the salt concentration, especially the damage degree of PSI. Although the photoinhibition of PSII was not significant, PSII donor and electron transfer from the QA to QB of the PSII receptor sides was inhibited. In a word, alfalfa showed relatively strong salt tolerance capacity, at the 100 mM salt concentration, even when the pH reached 9.0. Thus, the effect on the growth and photosynthetic function was not significant. However, at 200 mM salt concentration, pH 9.0 treatment caused damage to root system and the photosynthetic function in leaves of alfalfa was seriously injured.

Elevated NO2 damages the photosynthetic apparatus by inducing the accumulation of superoxide anions and peroxynitrite in tobacco seedling leaves.

This study aimed to further understand the toxicity of high concentrations of nitrogen dioxide (NO2) to plants, especially to plant photosynthesis. Tobacco plants in the six-leaf stage were exposed to 16.0 µL L-1 NO2 to determine the activities of photosystem II (PSII) and photosystem I (PSI) reaction centers, the blocking site of PSII electron transport, the degree of membrane peroxidation and the relative expression of PsbA, PsbO and PsaA genes in the third fully expanded leaves by using gas exchange and chlorophyll fluorescence techniques, biochemical and RT-PCR analysis. The results showed that 16.0 µL L-1 NO2 caused necrotic lesions to form on leaves and significantly increased the generation rate of superoxide anions (O2-) and the content of peroxynitrite (ONOO-) in leaves of tobacco seedling, leading to damage to cell membrane, chlorophyll content and net photosynthetic rate reduction, and photosynthetic apparatus destruction. Fumigation with 16.0 µL L-1 NO2 decreased the activity of PSII reaction center and oxygen evolution complex, and the relative expression of PabA in leaves of tobacco seedlings to inhibit the electron transport from the donor side to the receptor side of PSII, especially blocking the electron transport from QA to QB on the receptor side. The activity of the PSI reaction center and the relative expression of PsaA decreased, weakening the ability to accept electrons and inhibiting the electron transfer from PSII to PSI, which further increased the damage of PSII of tobacco seedling leaves caused by 16.0 µL L-1 NO2. Therefore, 16.0 µL L-1 NO2 leaded to the accumulation of O2- and ONOO-, which damaged the cell membrane and thylakoid membrane, inhibit the electron transport, and destroyed the photosynthetic apparatus in leaves of tobacco seedlings. The results from this study emphasized the importance of reducing the NO2 concentration in the atmosphere.

Design and implementation of a parallel geographically weighted k-nearest neighbor classifier.

The development of high-performance classifiers represents an important step in improving the timeliness of remote sensing classification in the era of high spatial resolution. Geographically weighted k-nearest neighbors (gwk-NN)-a classifier that incorporates spatial information into the traditional k-NN classifier-has demonstrated to be better at mitigating salt-and-pepper noise and misclassification. However, the integration of spatial dependence relationships into spectral information is computationally intensive. To improve computing performance, this paper discusses two commonly used parallel strategies-data and task parallelism-used to parallelize the gwk-NN classifier in the model training and classification stages, and implements the parallel algorithm by calling MPI and GDAL in the C++ development environment on a standalone eight-core computer. We further investigate the potential performance of dual parallelism (the simultaneous exploitation of data and task parallelism) in image classification. The experimental results demonstrate that the parallel gwk-NN classifier can improve the efficiency of high-resolution, remotely sensed images with multiple land cover types. Specifically, data parallelism is more effective than task parallelism in both model training and classification stages because of the minor role of parallel overhead in total execution time. In addition, dual parallelism can take advantage of data and task parallel strategies in the image classification stage, as evidenced by the two largest speedups attained under dual parallelism I (5.28×) and II (5.73×). Comparatively, dual parallelism II, in which priority is given to data decomposition, achieves the best performance by overlapping computation and data transmission, which is compatible with the current trend toward multicore architectures.