Graphene nanoparticles improve alfalfa (Medicago sativa L.) growth through multiple metabolic pathways under salinity-stressed environment.

Graphene, one of the emerging carbon nanomaterials, has many advantages and applications. Salinity stress seriously affects ecology and agroforestry worldwide. The effects of graphene on alfalfa under salinity stress were investigated. The results indicated that graphene promoted alfalfa growth under non-salinity stress but caused some degree of damage to root cells and leaf parameters. Graphene used in salinity stress had a positive effect on growth parameters, chlorophyll, photosynthetic gas parameters, stomatal opening, ion balance, osmotic homeostasis, cell membrane integrity and antioxidant system, while it decreased Na+, lipid peroxidation and reactive oxygen species levels. Correlation analysis revealed that most of the parameters were significantly correlated; and principal component analysis indicated that the first two dimensions (78.1% and 4.1%) explained 82.2% of the total variability, and the majority of them exceeded the average contribution. Additionally, Gene Ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes signaling pathway enrichment analysis showed that there were numerous differentially expressed genes and pathways to regulate alfalfa responding to salinity stress. Taken together, the findings reveal that graphene does not enter the plant, but improves the properties and adsorption of soil to enhance salt tolerance and seedling growth of alfalfa through morphological, physiological, biochemical, and transcriptomic aspects. Furthermore, this study provides a reference for the application of graphene to improve soil environment and agricultural production.

Effects of Melatonin on Morphological Characteristics, Mineral Nutrition, Nitrogen Metabolism, and Energy Status in Alfalfa Under High-Nitrate Stress.

Melatonin is an indoleamine small molecular substance that has been shown to play an important role in the growth, development, and stress response of plants. The effects of melatonin on the morphological characteristics, mineral nutrition, nitrogen metabolism, and energy status in alfalfa (Medicago sativa L.) under high-nitrate stress were studied. The alfalfa plants were treated with water (CK), 200 mmol L-1 nitrates (HN), or 200 mmol L-1 nitrates + 0.1 mmol L-1 melatonin (HN+MT), and then were sampled for measurements on days 0 and 10, respectively. The results showed that the HN treatment resulted in a decrease in the morphological characteristics (such as shoot height, leaf length, leaf width, leaf area, and biomass), phosphorus, soluble protein (SP), nitrogen-related enzymes activities and gene relative expression, adenosine triphosphate (ATP), and energy charge (EC). It also caused an increase in nitrogen, sodium, potassium, calcium, nitrate-nitrogen ( NO 3 - -N), ammonium-nitrogen ( NH 4 + -N), adenosine diphosphate (ADP), and adenosine monophosphate (AMP). However, these parameters were conversely changed in the HN+MT treatment. Besides, these parameters were closely related to each other, and were divided into two principal components. It reveals that melatonin plays an important role in modulating the morphology, mineral nutrition, nitrogen metabolism and energy status, thereby alleviating the adverse effects of high-nitrate stress and improving the growth of alfalfa.

Effects of exogenous ascorbic acid on seed germination and seedling salt-tolerance of alfalfa.

Alfalfa (Medicago sativa L.) is an important legume crop for forage, agriculture, and environment in the world. Ascorbic acid (AsA) plays positive roles in plants. However, its effects on germination and salt-tolerance of alfalfa are unknown. The effects of AsA applications on seed germination and seedling salt-tolerance of alfalfa were investigated. The results revealed that 0.1 and 1 mmol L-1 of exogenous AsA increased germination, amylase, and protease, as well as seedling length, fresh weight (FW), dry weight (DW), and endogenous AsA both in the shoots and roots, except that 1 mmol L-1 AsA reduced the activities of α-amylase, ß-amylase and protease on day 3. However, 10 and 100 mmol L-1 AsA inhibited these parameters and even caused serious rot. It indicates that 0.1 mmol L-1 AsA has the optimal effects, whereas 100 mmol L-1 AsA has the worst impacts. Another part of the results showed that 0.1 mmol L-1 AsA not only enhanced stem elongation, FW and DW, but also increased chlorophyll and carotenoids both under non-stress and 150 mmol L-1 NaCl stress. Furthermore, 0.1 mmol L-1 AsA mitigated the damages of membrane permeability, malondialdehyde, and excessive reactive oxygen species (ROS) and ions both in the shoots and roots under 150 mmol L-1 NaCl stress. Hence, 0.1 mmol L-1 AsA improves growth and induces salt-tolerance by inhibiting excessive ROS, down-regulating the ion toxicity and up-regulating the antioxidant system. The principal component analysis included two main components both in the shoots and roots, and it explained the results well. In summary, the optimum concentration of 0.1 mmol L-1 AsA can be implemented to improve the seed germination and seedling growth of alfalfa under salt stress.

Demonstration of Three-Dimensional Indoor Visible Light Positioning with Multiple Photodiodes and Reinforcement Learning.

To provide high-quality location-based services in the era of the Internet of Things, visible light positioning (VLP) is considered a promising technology for indoor positioning. In this paper, we study a multi-photodiodes (multi-PDs) three-dimensional (3D) indoor VLP system enhanced by reinforcement learning (RL), which can realize accurate positioning in the 3D space without any off-line training. The basic 3D positioning model is introduced, where without height information of the receiver, the initial height value is first estimated by exploring its relationship with the received signal strength (RSS), and then, the coordinates of the other two dimensions (i.e., X and Y in the horizontal plane) are calculated via trilateration based on the RSS. Two different RL processes, namely RL1 and RL2, are devised to form two methods that further improve horizontal and vertical positioning accuracy, respectively. A combination of RL1 and RL2 as the third proposed method enhances the overall 3D positioning accuracy. The positioning performance of the four presented 3D positioning methods, including the basic model without RL (i.e., Benchmark) and three RL based methods that run on top of the basic model, is evaluated experimentally. Experimental results verify that obviously higher 3D positioning accuracy is achieved by implementing any proposed RL based methods compared with the benchmark. The best performance is obtained when using the third RL based method that runs RL2 and RL1 sequentially. For the testbed that emulates a typical office environment with a height difference between the receiver and the transmitter ranging from 140 cm to 200 cm, an average 3D positioning error of 2.6 cm is reached by the best RL method, demonstrating at least 20% improvement compared to the basic model without performing RL.

Seed yield can be explained by altered yield components in field-grown western wheatgrass (Pascopyrum smithii Rydb.).

Western wheatgrass (Pascopyrum smithii Rydb.) is an important cool-season forage and turfgrass. However, due to seed dormancy and poor seedling vigor, it is difficult to develop high seed yield production systems, and assessing these components in response to seed yield. Based on multifactor orthogonally designed field experimental plots under various field management regimes, the effects of numbers of fertile tillers m-2 (Y1), spikelets/fertile tiller (Y2), florets/spikelet (Y3), seed numbers/spikelet (Y4), and seed weight (Y5) on seed yield (Z) were determined over three successive years. Correlation analysis indicated that fertile tillers (Y1) was the most important seed yield component. And the biggest contribution of those five yield component is fertile tillers (Y1), followed by seed numbers/spikelet (Y4), spikelets/fertile tiller (Y2), florets/spikelet (Y3) and seed weight (Y5), respectively. By using ridge regression analysis, we have developed an accurate model of seed yield with its five components. Finally, the results of synergism and antagonism among these yield components on seed yield showed that fertile tillers and seed numbers/spikelet had an antagonistic effect on seed yield. Therefore, selection for high seed yield by direct selection for large values of fertile tillers and seed numbers/spikelet would be the most effective breeding strategy for western wheatgrass.

Phytoremediation of Cd and Pb interactive polluted soils by switchgrass (Panicum virgatum L.).

Using phytoremediation as an efficient technique to remove heavy metals from contaminated soils is a current research hotspot. This study used an orthogonal matrix experimental design with three factors (Cd, Pb, and pH) and five levels (Cd at 9.45, 30, 60, 90, and 110.46 µg/g; Pb at 195.4, 400, 700, 1000, and 1204.6 µg/g; and pH at 3, 4.1, 5.8, 7.5, and 8.6) to investigate the phytoremediation potential of Panicum virgatum L. for soils polluted with cadmium (Cd) and lead (Pb). The results indicated that there was a significant decrease in belowground biomass in plants exposed to the stresses compared to the control. Superoxide dismutase (SOD) activity, peroxidase (POD) activity, and malondialdehyde (MDA) content were affected. Interaction of Cd with Pb in the soil had an antagonistic effect on the Cd bioaccumulation factor, whereas the interaction of pH with Cd or Pb had synergistic effects on the Cd bioaccumulation factor. When exposed to the three stressors, switchgrass plants could grow in soil that had a Cd concentration of a 46.68 µg/g, Pb concentration of 568.75 µg/g and pH of 5.34, which is a mildly acidic condition. Switchgrass, used as a phytoremediation plant, was more efficient in Cd-contaminated than in Pb-contaminated soil.