Application of carboxymethyl cellulose sodium (CMCNa) in maize-wheat cropping system (MWCS) in coastal saline-alkali soil.

Sodium carboxymethyl cellulose (CMCNa) application has been a promising approach to improve soil quality. The purpose of this study was to explore the effects of CMC-Na on soil infiltration, evaporation, water-salt distribution, crop growth, water use efficiency and net profit (Net) in a coastal saline-alkali soil maize-wheat cropping system (MWCS). Five CMC-Na application amounts (0, 0.1, 0.2, 0.4 and 0.6 g kg-1) were designed for the soil column experiment indoor, and five CMC-Na application amounts were used in 2019-2020 field experiment (CK: 0, C10: 10 kg ha-1, C20: 10 kg ha-1, C30: 10 kg ha-1 and C50: 10 kg ha-1), No treatment will be applied in 2021. The results showed that (1) CMC-Na treatment reduced soil cumulative infiltration, infiltration rate, daily evaporation, and cumulative evaporation. (2) After the application of CMCNa, the average soil water storage (SWS) in the 0-60 cm soil layer increased, and soil salinity (SSC) decreased in most treatments. (3) In the 2019-2020, the maize aboveground biomass (B), yield (Y) and water use efficiency (WUE) were the highest under the C20 and C30 treatments, which were 15.24 and 15.32 t ha-1, 5.67 and 5.49 t ha-1 and 1.74 and 1.52 kg ha-1 mm-1, respectively, and the wheat under C30 treatment is the highest, which were 10.98 t ha-1, 5.27 t ha-1 and 1.78 kg ha-1 mm-1. (4) A dose of 25.5 kg ha-1 and 38.9 kg ha-1 was recommended as the most optimal CMC-Na application for maize and wheat in coastal saline alkali soil, respectively.

Effect of Sodium Carboxymethyl Cellulose on Water and Salt Transport Characteristics of Saline-Alkali Soil in Xinjiang, China.

The scientific use of sodium carboxymethyl cellulose (CMC) to improve the production capacity of saline-alkali soil is critical to achieve green agriculture and sustainable land use. It serves as a foundation for the scientific use of CMC to clarify the water and salt transport characteristics of CMC-treated soil. In this study, a one-dimensional soil column infiltration experiment was carried out to investigate the effects of different CMC dosages (0, 0.2, 0.4, 0.6, and 0.8 g/kg) on the infiltration characteristics, infiltration model parameters, water and salt distribution, and salt leaching of saline-alkali soil in Xinjiang, China. The results showed that the final cumulative infiltration of CMC-treated soil increased by 8.63-20.72%, and the infiltration time to reach the preset wetting front depth increased by 1.02-3.96 times. The sorptivity (S) in the Philip infiltration model and comprehensive shape coefficient (α) in the algebraic infiltration model showed a trend of increasing first and then decreasing with CMC dosage, revealing a quadratic polynomial relationship. The algebraic model could accurately simulate the water content profile of CMC-treated soil. CMC enhanced the soil water holding capacity and salt leaching efficiency. The average soil water content, desalination rate, and leaching efficiency were increased by 5.18-15.54%, 21.17-57.15%, and 11.61-30.18%, respectively. The effect of water retention and salt inhibition on loamy sand was the best when the CMC dosage was 0.6 g/ kg. In conclusion, the results provide a theoretical basis for the rational application of CMC to improve saline-alkali soil in arid areas.

Simulation Models of Leaf Area Index and Yield for Cotton Grown with Different Soil Conditioners.

Simulation models of leaf area index (LAI) and yield for cotton can provide a theoretical foundation for predicting future variations in yield. This paper analyses the increase in LAI and the relationships between LAI, dry matter, and yield for cotton under three soil conditioners near Korla, Xinjiang, China. Dynamic changes in cotton LAI were evaluated using modified logistic, Gaussian, modified Gaussian, log normal, and cubic polynomial models. Universal models for simulating the relative leaf area index (RLAI) were established in which the application rate of soil conditioner was used to estimate the maximum LAI (LAIm). In addition, the relationships between LAIm and dry matter mass, yield, and the harvest index were investigated, and a simulation model for yield is proposed. A feasibility analysis of the models indicated that the cubic polynomial and Gaussian models were less accurate than the other three models for simulating increases in RLAI. Despite significant differences in LAIs under the type and amount of soil conditioner applied, LAIm could be described by aboveground dry matter using Michaelis-Menten kinetics. Moreover, the simulation model for cotton yield based on LAIm and the harvest index presented in this work provided important theoretical insights for improving water use efficiency in cotton cultivation and for identifying optimal application rates of soil conditioners.