Single and combined effect of tetracycline and polyethylene microplastics on two drought contrasting cultivars of Oryza sativa L. (Rice) under drought stress.

Co-exposure of tetracycline (TC) and polyethylene microplastic (MP-PE) pollution might result in more intricate effects on rice growth and grain quality. In present study, two different rice cultivars of contrasting drought tolerance, Hanyou73 (H73, drought-resistant) and Quanyou280 (Q280, drought-sensitive) were grown on MP-PE and TC-contaminated soils under drought. It was found that drought stress had different influence on TC accumulation in the two rice cultivars. H73 accumulated more TC in leaves and grains without drought stress while Q280 accumulated more TC under drought stress. Furthermore, metabolomics results demonstrated that under drought stress, about 80 % of metabolites in H73 and 95 % in Q280 were down-regulated as compared to non-drought treatments. These findings provide insights into the effects of TC and MP-PE with and without drought stress on potential risks to rice growth and grain quality, which has implications on rice production and cultivar election under multiple-stress conditions.

Determination of Fv /Fm from Chlorophyll a Fluorescence without Dark Adaptation by an LSSVM Model.

Evaluation of photosynthetic quantum yield is important for analyzing the phenotype of plants. Chlorophyll a fluorescence (ChlF) has been widely used to estimate plant photosynthesis and its regulatory mechanisms. The ratio of variable to maximum fluorescence, Fv /Fm , obtained from a ChlF induction curve, is commonly used to reflect the maximum photochemical quantum yield of photosystem II (PSII), but it is measured after a sample is dark-adapted for a long time, which limits its practical use. In this research, a least-squares support vector machine (LSSVM) model was developed to explore whether Fv /Fm can be determined from ChlF induction curves measured without dark adaptation. A total of 7,231 samples of 8 different experiments, under diverse conditions, were used to train the LSSVM model. Model evaluation with different samples showed excellent performance in determining Fv /Fm from ChlF signals without dark adaptation. Computation time for each test sample was less than 4 ms. Further, the prediction performance of test dataset was found to be very desirable: a high correlation coefficient (0.762 to 0.974); a low root mean squared error (0.005 to 0.021); and a residual prediction deviation of 1.254 to 4.933. These results clearly demonstrate that Fv /Fm , the widely used ChlF induction feature, can be determined from measurements without dark adaptation of samples. This will not only save experiment time but also make Fv /Fm useful in real-time and field applications. This work provides a high-throughput method to determine the important photosynthetic feature through ChlF for phenotyping plants.

Impact of polystyrene microplastics with combined contamination of norfloxacin and sulfadiazine on Chrysanthemum coronarium L.

Antibiotics and microplastics including nanoplastics are emerging contaminants which have become global environmental issues. The application of antibiotics along with microplastics in soil and their entrance in food chain may pose a major threat to human health. The single and combined exposure of polystyrene microplastic (MPS), norfloxacin (NF) and sulfadiazine (SFD) on Chrysanthemum coronarium L. a medicinal food crop, were investigated. Accumulation of nutrient element contents (Fe, Mn, Mg, Zn, K) differentially responded to the single or combined treatments compared to the control. Scanning electron microscopy and transmission electron microscopy analysis indicated that MPS, NF and SFD accumulated in roots, shoots, and leaves and affected their ultrastructure. Compared with that of the single contamination, the co-contamination of microplastics and antibiotics had a greater effect on leaf metabolites due to combination of multiple abiotic stresses. MPS, NF and SFD accumulated from roots and transported to shoots and leaves which ultimately impacts plant metabolites and, nutritional value. They subsequently impact agricultural sustainability and food safety of medicinal food plants. This investigation suggests the possible ecological risks of microplastics to medicinal food plants, especially in co-exposure with organic pollutants like antibiotics and help to reveal potential mechanisms of phytotoxicity of different antibiotics with polyethylene microplastic.

Development of a minimized model structure and a feedback control framework for regulating photosynthetic activities.

In this work, the main activities of the plant photosynthesis process are discussed to yield a minimized mathematical model structure with photosystem II (PSII) chlorophyll a fluorescence (ChlF) as a measurable output. After experimental validation of the model structure, we demonstrate that the states of the photosynthetic process may be observed by using this model and the extended Kalman filter method. We then show a feedback control framework that can be used to alter a given photosynthetic activity. The control framework is demonstrated with an example in which PSII ChlF is used as the feedback signal and light intensity is used as a controllable process input to regulate plastoquinone reduction. Although there are caveats, and further research is needed, the results lay the groundwork for further research on novel methods for optimization and regulation of photosynthetic activities, with a goal for sustainability.

Modelling and simulation of chlorophyll fluorescence from PSII of a plant leaf as affected by both illumination light intensities and temperatures.

The emission of chlorophyll fluorescence (ChlF) from photosystem II (PSII) of plant leaves the couple with photoelectron transduction cascades in photosynthetic reactions and can be used to probe photosynthetic efficiency and plant physiology. Because of population increase, food shortages, and global warming, it is becoming more and more urgent to enhance plant photosynthesis efficiency by controlling plant growth rate. An effective model structure is essential for plant control strategy development. However, there is a lack of reporting on modelling and simulation of PSII activities under the interaction of both illumination light intensities and temperatures, which are the two important controllable factors affecting, plant growth, especially for a greenhouse. In this work, the authors extended their work on modelling photosynthetic activities as affected by light and temperature to cover both the interaction effects of illumination light intensities and temperature on ChlF emission. Experiments on ChlF were performed under different light intensities and temperatures and used to validate the developed model structure. The average relative error between experimental data and model fitting is <0.3%, which shows the effectiveness of the developed model structure. Simulations were performed to show the interaction effect of light and temperature effects on photosynthetic activities.

Modelling and simulation of photosystem II chlorophyll fluorescence transition from dark-adapted state to light-adapted state.

Green houses play a vital role in modern agriculture. Artificial light illumination is very important in a green house. While light is necessary for plant growth, excessive light in a green house may not bring more profit and even damages plants. Developing a plant-physiology-based light control strategy in a green house is important, which implies that a state-space model on photosynthetic activities is very useful because modern control theories and techniques are usually developed according to model structures in the state space. In this work, a simplified model structure on photosystem II activities was developed with seven state variables and chlorophyll fluorescence (ChlF) as the observable variable. Experiments on ChlF were performed. The Levenberg-Marquardt algorithm was used to estimate model parameters from experimental data. The model structure can fit experimental data with a small relative error (<2%). ChlF under different light intensities were simulated to show the effect of light intensity on ChlF emission. A simplified model structure with fewer state variables and model parameters will be more robust to perturbations and model parameter estimation. The model structure is thus expected useful in future green-house light control strategy development.