Simulating leaf net CO_2 assimilation rate of C_3 & C_4 plants and its response to environmental factors

Basic structure and algorithm of leaf mechanism photosynthesis model were described in first part of this study based on former researcher results. Then, considering some environmental factors influencing on leaf photosynthesis, three numerical sensitivity experiments were carried out. We simulated the sing le leaf net CO2 assimilation, which acts as a function of different light, carbo n dioxide and temperature conditions. The relationships between leaf net photosy nthetic rate of C3 and C4 plant with CO2 concentration intercellular, leaf tempe rature, and photosynthetic active radiation (PAR) were presented, respectively. The results show the numerical experiment may indicate the main characteristic o f plant photosynthesis in C3 and C4 plant, and further can be used to integrate with the regional climate model and act as land surface process scheme, and bett er understand the interaction between vegetation and atmosphere.

Simulating leaf net CO2 assimilation rate of C3 & C4 plants and its response to environmental factors

Basic structure and algorithm of leaf mechanism photosynthesis model were described in first part of this study based on former researcher results. Then, considering some environmental factors influencing on leaf photosynthesis, three numerical sensitivity experiments were carried out. We simulated the sing le leaf net CO2 assimilation, which acts as a function of different light, carbo n dioxide and temperature conditions. The relationships between leaf net photosy nthetic rate of C3 and C4 plant with CO2 concentration intercellular, leaf tempe rature, and photosynthetic active radiation (PAR) were presented, respectively. The results show the numerical experiment may indicate the main characteristic o f plant photosynthesis in C3 and C4 plant, and further can be used to integrate with the regional climate model and act as land surface process scheme, and bett er understand the interaction between vegetation and atmosphere.

Universality of an improved photosynthesis prediction model based on PSO-SVM at all growth stages of tomato

CO_(2)concentration is an environmental factor affecting photosynthesis and consequently the yield and quality of tomatoes.In this study,a photosynthesis prediction model for the entire growth stage of tomatoes was constructed to elevate CO_(2)level on the basis of crop requirements and to evaluate the effect of CO_(2)elevation on leaf photosynthesis.The effect of CO_(2)enrichment on tomato photosynthesis was investigated using two CO_(2)enrichment treatments at the entire growth stage.A wireless sensor network-based environmental monitoring system was used for the real-time monitoring of environmental factors,and the LI-6400XT portable photosynthesis system was used to measure the net photosynthetic rate of tomato leaf.As input variables for the model,environmental factors were uniformly preprocessed using independent component analysis.Moreover,the photosynthesis prediction model for the entire growth stage was established on the basis of the support vector machine(SVM)model.Improved particle swarm optimization(PSO)was also used to search for the best parameters c and g of SVM.Furthermore,the relationship between CO_(2)concentration and photosynthetic rate under varying light intensities was predicted using the established model,which can determine CO_(2)saturation points at the various growth stages.The determination coefficients between the simulated and observed data sets for the three growth stages were 0.96,0.96,and 0.94 with the improved PSO-SVM and 0.89,0.87,and 0.86 with the original PSO-SVM.The results indicate that the improved PSO-SVM exhibits a high prediction accuracy.The study provides a basis for the precise regulation of CO_(2)enrichment in greenhouses.

Measurement and prediction of tomato canopy apparent photosynthetic rate

Given the lack of technical conditions and research methods,instruments that can measure the canopy apparent photosynthetic rate have low precision and are rarely studied.Comparative studies on canopy apparent photosynthetic rate and single leaf photosynthetic rate are also relatively few.This study aims to measure and predict the canopy apparent photosynthetic rate of tomato.A canopy apparent photosynthetic rate measuring system,which was comprised of a wireless sensor network(WSN),an assimilation chamber,and a LI-6400XT photosynthetic rate instrument was established.The system was used to determine the greenhouse environmental parameters and CO2 absorptive capacity of the whole growth stage of tomato.A semi-closed assimilation chamber was designed as a side opening to conveniently measure the canopy apparent photosynthetic rate.WSN nodes were placed in the chamber to monitor environmental parameters,including air temperature,air humidity,and assimilation chamber temperature.A grid and pixel conversion method was used to measure the whole plant leaf areas of tomato.As a semi-closed measurement system,the assimilation chamber was used to calculate the canopy apparent photosynthetic rate.To conduct a comparative research on the canopy apparent photosynthetic rate and the single leaf photosynthetic rate,the LI-6400XT portable photosynthesis system was used to measure the single leaf photosynthetic rate,and the support vector machine was used to establish the prediction model of canopy apparent photosynthetic rate.The experimental results indicated that the correlation coefficients of the photosynthesis prediction model in the seeding and flowering stages were 0.9420 and 0.9226,respectively,showing the high accuracy of the SVM model.