A scientometric analysis of agricultural pollution by using bibliometric software VoSViewer and Histcite™.

While modern agriculture brings more food to people, it causes environmental pollution as well. Agricultural pollution has attracted extensive public attention. A lot of reviews on agricultural research were conducted from different research aspects, but there is a lack of work on analyzing the research trend from large volumes of publications in the field of agricultural pollution. In the present work, a scientometric analysis of agricultural pollution was conducted to fill the gap by using the software of VoSviewer and HistCite™. The datasets are collected from the core database of Web of Science from 1991 to 2019, totally 1338 records on the topic of agricultural pollutions. In most years (1996, 1999, 2002, 2006, 2009, 2011, and 2013), the total local citation score (TLCS) and total global citation score (TGCS) have coincident peaks. Zhang, Ju, and Zhu have the highest TLCS and TGCS. In terms of institutes, Chinese Acad Sci and China Agr Univ are the leading institutes in this field. The Univ Calif Davis, INRA, and USDA ARS have very high global impacts. From the research hot topics, the representative words include "soil," "agriculture," "contamination," "environment," "lead," and "balance." Representative words like "heavy-metals," "groundwater," "land-use," and "water" are emerging in the latter time period. Five leading research co-cited reference clusters are identified, including environment management, underground water, monitoring and alarming for the agriculture-environment standards, intrinsic mechanism to the circulatory system, and ecology system and land use. The recent trend is revealed from the bibliographical-coupling network, focusing on classical and old-fashion research, like pollution chemicals including N management, pesticides, and heavy metal. This work provides a holistic picture on the research in the field of agriculture pollution.

Sensing Plant Physiology and Environmental Stress by Automatically Tracking Fj and Fi Features in PSII Chlorophyll Fluorescence Induction.

Following a step excitation, chlorophyll fluorescence (ChlF) from photosystem II (PSII) of a dark-adapted photosynthetic organism exhibits the well-known OJIP pattern. The OJIP induction has been widely used in plant science and agriculture engineering. While the J and I phases are related to transitions of photochemical reaction redox states, characteristic fluorescence intensities at the two phases (Fj and Fi ) are often treated at fixed time points in routine measurement and thus do not account for variations in plant and experimental conditions, this (1) neglects the differences in the time of appearance of these phases, which is potentially useful information for characterizing plant status and environmental factors, and (2) leads to errors in measured Fj and Fi values in the many publications. In this work, an alternative method for consistent measurement of Fj and Fi was presented. The proposed method measures the curvatures in the OJIP curve and automatically tracks the characteristic transition points under variable sample and experimental conditions. Experiments were carried out to demonstrate the concept and classification capabilities of the method. This research has established a new framework to analyze ChlF and has enhanced the application capability of ChlF. It is expect useful in analysis ChlF from PSII.

Modelling and simulation of photosynthetic activities in C3 plants as affected by CO2.

CO2 concentration ([CO2]) in a greenhouse may be a limiting factor for plant growth. Current greenhouse CO2 control strategy usually depends on expert experience, which may control [CO2] in a moderate range but cannot make it optimal due to lack of considering plant photochemistry reactions. A state-space kinetic model structure covering major photosynthetic reactions as affected by CO2 is useful for [CO2] control strategy development in a greenhouse because modern control theories are usually based on state-space models. In this work, a state-space kinetic model structure for photosynthesis was built, which describes the major reaction cascades of photophosphorylation, Calvin cycle, and biophysical processes such as CO2 transport through the stomata under moderate [CO2] range without considering photorespiration. Simulations were performed with a large range of model parameters to demonstrate the effect of [CO2] on stable sugar production and the flexibilities of the developed model structure. The results clearly show whether increasing of CO2 will lead to more production of sugar or not in different scenarios. The model structure may be extended to cover other photosynthetic influence factors such as temperature by using the well-known Arrhenius equation.

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.

Modelling and simulation of chlorophyll fluorescence from photosystem II as affected by temperature.

Emission of chlorophyll fluorescence (ChlF) from photosystem II (PSII) is affected by both plant status and environmental conditions. In this work, a state space model structure for ChlF from PSII with temperature as a variable model parameter was developed to provide insights into the temperature effects on photosynthesis and greenhouse temperature control. Experiments were carried out at 20, 25, and 30°C to validate the capability and flexibility of the developed model structure. Simulations of ChlF emission were performed for different temperatures. The results demonstrated the effectiveness of the ChlF model structure and the findings are useful for the development of greenhouse temperature control strategies.