Effects of urea-N and CO_(2) coupling fertilization on the growth,photosynthesis,yield and anthocyanin content of hydroponic purple cabbage Brassica campestris ssp.chinensis

Water and fertilizer coupling is a high-efficiency technology for the development of facility agriculture.However,the interaction effect of nitrogen(N)and air carbon dioxide(CO_(2))on hydroponic purple cabbage,especially on its leaf anthocyanins under hydroponic solution systems,remains unexplored.In this study,six treatments were set as C0N0,C0N2,C0N4,C1N0,C1N2 and C1N4,with N0,N2 and N4 being 0.0 g/L,0.2 g/L and 0.4 g/L exogenous urea-N to hydroponic solution dilution,respectively.C0 and C1 were set as with and without CO_(2)fertilizer(i.e.,800 g CO_(2)agent added one week after transplanting and 600 g CO_(2)agent added when the plant reached 15 cm in height),respectively.Pot experiments were conducted to investigate the interaction effect of N and air CO_(2)(N×CO_(2))on the growth,photosynthesis,yield and anthocyanin content of hydroponic purple cabbage Brassica campestris ssp.chinensis.The results showed N×CO_(2)extremely significantly influenced plant height(H),net photosynthetic rate(Pn),stomatal conductance(Gs),intercellular oxidation concentration(Ci),transpiration rate(Tr),leaf water use efficiency(LWUE)and yield.The C1N0 treatment had the largest yield at 262.5 g/plant,with higher values for root length,root weight,plant height and leaf number than the other treatments.The Pn,Ci and Tr of C1N4 were the highest at 3.05μmol CO_(2)/m2·s,352.8μmol CO_(2)/m2·s and 2.31 mmol H2O/m2·s,respectively.The C1N2 treatment received the largest Gs value of 0.70 mol H2O/m2·s and the largest Tr of 2.31 mmol H2O/m2·s.There was the highest LWUE for C0N2(1.41)and the highest anthocyanin content for C1N2(1.35 mg/kg).There was a significant negative correlation between leaf number and anthocyanin(r=-0.414,p<0.05).The findings demonstrated that adding CO_(2)fertilizer and 0.2 g/L exogenous urea-N to hydroponic solution dilution is a potential N×CO_(2)coupling strategy to increase anthocyanin and the yield of purple cabbage.

Irrigation decision model for tomato seedlings based on optimal photosynthetic rate

Soil moisture is a major environmental factor that influences tomato growth and development.Suitable soil moisture not only increases tomato production but also saves irrigation water.In this study,an irrigation decision model was developed,which called soil moisture regulation model,for optimizing growth of tomato seedlings while saving water.The data used for modeling were collected from a multi-gradient nested experiment,in which temperature,photosynthetic photon flux density(PPFD),carbon dioxide(CO2)concentration and soil moisture were variables and the corresponding photosynthetic rate was measured.Subsequently,a prediction model of tomato photosynthetic rate was constructed using support vector regression(SVR)algorithm.With photosynthetic rate prediction model as fitness function,genetic algorithm(GA)was used to find the optimal soil moisture under each combination of the above environmental factors.Finally,back propagation neural network(BPNN)algorithm was used to establish a decision model of tomato irrigation,which could provide the optimal soil moisture under current environment.For the soil moisture regulation model constructed here,the coefficient of determination was 0.9738,the mean square error of the test set was 1.51×10-5,the slope of the verified straight line was 0.9752,and the intercept was 0.00916.This model demonstrated high precision,which thereby provides a theoretical basis for accurate irrigation control in the greenhouse facility environment.