scholarly journals Suaeda salsa/Zea mays L. intercropping in saline soil on plant growth and rhizospheric physiological processes

2021 ◽  
Author(s):  
Shoule Wang ◽  
Zhenyong Zhao ◽  
Shaoqing Ge ◽  
Ke Zhang ◽  
Changyan Tian ◽  
...  
Keyword(s):  
Zea Mays ◽  
Saline Soil ◽  
Salt Content ◽  
Treated Group ◽  
Suaeda Salsa ◽  
Nitrogen And Phosphorus ◽  
Available Nitrogen ◽  
Physiological Processes ◽  
Soil Salt Content ◽  
Soil Salt

Abstract Background and aims Halophytes possess the capacity to uptake high levels of salt through physiological processes and their root architecture. Here, we investigated whether halophyte/non-halophyte intercropping in saline soil decreases the soil salt content and contains root-dialogue. Methods Field and pot experiments were conducted to determine the plant biomasses and salt and nutrient distributions in three suaeda (Suaeda salsa) / maize (Zea mays L.) intercropping systems. The three treatments were set up by non-barrier, nylon barrier and plastic barrier between plant roots. Results The biomass of the non-barrier-treated maize was significantly lower than that of the nylon barrier-treated maize, whereas the suaeda root biomass showed a limited increase. The soil salt content negatively affected the non-barrier group’s roots compared with those in the nylon and plastic barrier-treated groups, and it was also higher on the maize side of the nylon-barrier treatment. There were higher available nitrogen and phosphorus contents in the soil of the non-barrier- and nylon barrier-treated groups compared with the plastic barrier-treated group. In addition, the pH was lower, and the available potassium content was higher, which suggested that rhizospheric processes occurred between the two species. Conclusions The suaeda/maize intercropping would decrease the soil salt content, and they also revealed potential rhizospheric effects though the role of root, which provides an effective way for the improvement of saline-alkali land.

scholarly journals The Effects of Suaeda salsa/Zea mays L. Intercropping on Plant Growth and Soil Chemical Characteristics in Saline Soil

Agriculture ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 107
Author(s):  
Shoule Wang ◽  
Zhenyong Zhao ◽  
Shaoqing Ge ◽  
Ke Zhang ◽  
Changyan Tian ◽  
...  
Keyword(s):  
Zea Mays ◽  
Plant Growth ◽  
Zea Mays L ◽  
Root Zone ◽  
Saline Soil ◽  
Nutrient Content ◽  
Suaeda Salsa ◽  
Available N ◽  
Physiological Processes ◽  
Set Up

Halophytes possess the capacity to uptake high levels of salt through physiological processes and their root architecture. Here, we investigated whether halophyte/non-halophyte intercropping in saline soil benefits plant growth and contains root-dialogue between interspecific species. Field and pot experiments were conducted to determine the plant biomasses and salt and nutrient distributions in three suaeda (Suaeda salsa)/maize (Zea mays L.) intercropping systems, set up by non-barrier, nylon-barrier, and plastic-barrier between plant roots. The suaeda/maize intercropping obviously transferred more Na+ to the suaeda root zone and decreased salt and Na+ contents. However, the biomass of the non-barrier-treated maize was significantly lower than that of the nylon and plastic barrier-treated maize. There was lower available N content in the soil of the non-barrier treated groups compared with the plastic barrier-treated groups. In addition, the pH was lower, and the available nutrient content was higher in the nylon barrier, which suggested that rhizospheric processes might occur between the two species. Therefore, we concluded that the suaeda/maize intercropping would be beneficial to the salt removal, but it caused an adverse effect for maize growth due to interspecific competition, and also revealed potential rhizospheric effects through the role of roots. This study provides an effective way for the improvement of saline land.

scholarly journals Determination of Soil Salt Content Using a Probability Neural Network Model Based on Particle Swarm Optimization in Areas Affected and Non-Affected by Human Activities

2018 ◽  
Vol 10 (9) ◽  
pp. 1387 ◽  
Author(s):  
Chengbiao Fu ◽  
Shu Gan ◽  
Xiping Yuan ◽  
Heigang Xiong ◽  
Anhong Tian
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Human Activities ◽  
Salt Content ◽  
Particle Swarm ◽  
Wave Band ◽  
Swarm Optimization ◽  
Affected Area ◽  
Soil Salt Content ◽  
Soil Salt

Traditional partial least squares regression (PLSR) and artificial neural networks (ANN) have been widely applied to estimate salt content from spectral reflectance in many different saline environments around the world. However, these methods entail a great amount of calculation, and their accuracy is low. To overcome these problems, a probability neural network (PNN) model based on particle swarm optimization was used in this study to build soil salt content models. Furthermore, there is a clear correlation between the level of human activities and the degree of salinization of an environment. This paper is the first to discuss this matter. Here, the performance of the PNN model to estimate soil salt content from reflectance data was investigated in areas non-affected (Area A) and affected (Area B) by human activities. The study area is located in Xingjinag, China. Different mathematical procedures, five wave band intervals, and two types of signal input sources were used for cross analysis. The coefficient of determination (R2), root mean square error (RMSE), and ratio of performance to deviation (RPD) index values were compared to verify the reliability of the model. Particle swarm optimization was used to adjust the optimal smoothing parameters of the PNN model and to avoid the long training processes required by the traditional ANN. The results show that the optimal wave band interval of the PNN is between 1000 nm and 1350 nm in Area A and between 400 nm and 700 nm in Area B. The reciprocal (1/R) transformation after Savitzky-Golay (SG) smoothing of the signal source is optimal for both areas. The RPD for both is greater than 30, which shows that the PNN model is applicable to areas with and without human activities and the prediction results are very good. The results indicated that the optimal wave band intervals for PNN modeling differed in areas affected and non-affected by human activities. The optimal interval of the artificial activities region falls in the visible light portion of the spectrum, and the optimized wave band region without human activities falls in the near-infrared short-wave portion of the spectrum.

Functions of Cotton Yield Response to Soil Salinity in Akesu River Irrigation District

2012 ◽  
Vol 535-537 ◽  
pp. 486-494
Author(s):  
Yu Zhang ◽  
Pei Tong Cong ◽  
Shun Jun Hu ◽  
Li Hong Wang ◽  
Feng Qing Guo ◽  
...  
Keyword(s):  
Salt Tolerance ◽  
Salt Content ◽  
Soil Layer ◽  
Relative Yield ◽  
Irrigation District ◽  
Yield Response ◽  
Yield Reduction ◽  
Soil Salt Content ◽  
Soil Salt ◽  
Salinized Soil

Based on experimental data from the five observation points during the three years, the linear subsected functions and the nonlinear s-shaped functions between the cotton relative yield and soil salt content on the salinized soil about the 0-20cm soil layer and the 0-40cm soil layer in Akesu River Irrigation District were constructed by linear regression and nonlinear least square approximation. Their applicabilities were analyzed and compared and it was found the nonlinear s-shaped function of the 0-20cm soil layer to fit better with the response relationship between the cotton relative yield and the soil salt content on the salinity soil than others in Akesu River Irrigation District.which and the indexes of cotton salt tolerance were definited, and then the indexes of cotton salt tolerance were drawn on with the function with better applicability. From the function, some indexes of salt tolerance，which contained the cotton critical soil salt content, the cotton threshold soil salt content, the soil salt content at the fastest rate of cotton relative yield reduction, and the soil salt content at the 50% cotton relative yield reduction, and so on, were determined, which can be provide as the important references for the agricultural planting, improvement of salinized soil and irrigation with saline water in Akesu River Irrigation District.

scholarly journals Cultivation of dandelion (Taraxacum erythropodium) on coastal saline land based on the control of salinity and fertilizer

2019 ◽  
Vol 31 (2) ◽  
pp. 277-284
Author(s):  
Zhe Wu ◽  
Zhizhong Xue ◽  
Haishan Li ◽  
Xiaodong Zhang ◽  
Xiuping Wang ◽  
...  
Keyword(s):  
Quality Control ◽  
Salt Tolerance ◽  
Salt Content ◽  
Technical Support ◽  
Physiological Parameters ◽  
Fresh Leaf ◽  
Soil Salt Content ◽  
Soil Salt ◽  
Leaf Yield ◽  
Saline Land

AbstractDandelion (Taraxacum spp.) is a widely distributed weed; in China, however, dandelion has been considered to be a kind of medicinal and edible vegetable in recent years. This transition from weed to vegetable requires corresponding cultivation and management. Thus, the production of dandelion on saline land was conducted based on the evaluation of dandelion salt tolerance. Low soil salt content (< 0.3%) did not significantly affect dandelion growth, and the salt tolerance threshold of dandelion ranged from 0.4% to 0.43% according to the correlation between salt content and morphological and physiological parameters, which was for guiding the preparation of saline land for dandelion field cultivation. Different fertilizer treatments significantly affected the leaf yield of dandelion, and the maximum fresh leaf yield of ~10.5 t ha−1 was obtained when urea was applied in batches at a ratio of 2:2:1 in the sowing, seedling and flowering stages, respectively. This research provided the theoretical and technical support for the cultivation on saline land, laying the foundation for further study of quality control for the cultivation of dandelion on saline land.

Salt-tolerance identification and quality evaluation of Abelmoschus manihot (L.) Medik

2020 ◽  
Vol 100 (5) ◽  
pp. 568-574
Author(s):  
Zhe Wu ◽  
Zhizhong Xue ◽  
Xuelin Lu ◽  
Yinsuo Jia ◽  
Xiuping Wang ◽  
...  
Keyword(s):  
Salt Tolerance ◽  
Quality Evaluation ◽  
Salt Content ◽  
Northern China ◽  
High Yield ◽  
Edible Plant ◽  
High Quality ◽  
Soil Salt Content ◽  
Soil Salt ◽  
Functional Components

Abelmoschus manihot (L.) Medik. is a medicinal and edible plant. To evaluate its suitability for cultivation on the coastal saline-alkali land in northern China for high quality functional products, salt-tolerance identification and flavonoid contents were evaluated under saline treatments. Results showed that the salt-tolerance threshold of A. manihot ranged from 4.1 to 6.9 g L−1; however, low soil salt content (<3 g L−1) had the best growth and accumulation of total flavonoids. Sixteen kinds of common functional components such as hyperoside, rutoside, and quercetin were found. Of these components, the four (myricetin-3-0-glucoside, rutoside, quercetin-3′-0-glucoside, and gossypetin-8-0-β-d-glucuronic acid) with the highest content were chosen as the quality evaluation indexes. High levels of quality and yield occurred at a soil salt content of 3 g L−1. Our results suggested that soil salt content should not exceed 3 g L−1 in field cultivation for high quality and high yield of A. manihot.

Hyperspectral Estimation Models for the Saline Soil Salinity in the Yellow River Delta

2015 ◽  
Vol 738-739 ◽  
pp. 197-203 ◽  
Author(s):  
Hong Yan Chen ◽  
Geng Xing Zhao ◽  
Ya Qiu Liu ◽  
Jing Chun Chen ◽  
Hong Zhang
Keyword(s):  
Soil Salinity ◽  
Yellow River ◽  
Saline Soil ◽  
Salt Content ◽  
Back Propagation ◽  
Yellow River Delta ◽  
Back Propagation Neural Network ◽  
Support Vector ◽  
Soil Salt Content ◽  
Input Variables

Quantitative identification of the saline soil salinity content is a necessary precondition for the reasonable improvement and utilization of saline land, the article aimed at comparing the different quantitative analysis methods and achieving fast estimation of the saline soil salt content in the Yellow River Delta based on the visible-near infrared spectroscopy. Kenli County in Shandong Province was selected as the experimental area, firstly, the representative soil samples were selected, hyperspectral reflectance of the soil samples were measured in situ and transformed to the first deviation. Secondly the correlate spectra, the characteristic spectra and indices were firstly filtered using correlation analysis. Finally, the estimation models of soil salinity content were built using the multiple linear regression (MLR), back propagation neural network (BPNN) and support vector machine (SVM) respectively. The results indicated that the characteristic wave bands of soil salinity were 684 nm and 2058 nm. On the condition of the same input variables, the prediction precision of the SVM models was the highest, followed by the BPNN, the MLR was the lowest. The SVM model based on the first deviation of the reflectance at 684 and 2058nm had the highest precision, with the calibration R2 of 0.91 and RMSE as 0.11%, the validation R2 of 0.93, RMSE as 0.26% and RPD as 2.61, which had very good prediction accuracy of soil salt content, and was very stable and reliable. Different input variables had a great impact on the model accuracy, among of the MLR models, only the precision of the model based on characteristic spectral indices was slightly higher and could be used to estimate salt content, among of the BPNN and SVM models, the precision of the models based on characteristic spectra and indices was more high and stable significantly than the models on the correlate spectra. Therefore, for the three modeling methods of multiple linear regression, back propagation neural network and support vector machine, building the estimation model of saline soil salinity content based on characteristic spectra indices was effective.

scholarly journals Hyperspectral reflectance models for soil salt content by filtering methods and waveband selection

2016 ◽  
Vol 23 (1) ◽  
pp. 117-130 ◽  
Author(s):  
Wen-Zhi Zeng ◽  
Jie-Sheng Huang ◽  
Chi Xu ◽  
Tao Ma ◽  
Jing-Wei Wu
Keyword(s):  
Salt Content ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Irrigation District ◽  
Hyperspectral Reflectance ◽  
Soil Salt Content ◽  
Soil Salt ◽  
Orthogonal Signal Correction ◽  
Signal Correction

Abstract For improving the understanding of interactions between hyperspectral reflectance and soil salinity, in situ hyperspectral inversion of soil salt content at a depth of 0-10 cm was conducted in Hetao Irrigation District, Inner Mongolia, China. Six filtering methods were used to preprocess soil reflectance data, and waveband selection combined by VIP (variable importance in projection) and b-coefficients (regression coefficients of model) was also applied to simplify model. Then statistical methods of partial least square regression (PLS) and orthogonal projection to latent structures (OPLS) were processed to establish the inversion models. Our findings indicate that the selected sensitive wavebands for the 6 filtering methods are different, among which the multiplicative signal correction (MSC) and standard normal variate methods (SNV) have some similar sensitive wavebands with unfiltered data. Derivatives (DF1 and DF2) could characterize sensitive wavebands along the scale of VNIR (350-1100 nm), especially the second derivative (DF2). The sensitive wavebands for continuum-removed reflectance method (CR) have protruded many narrow absorption features. For orthogonal signal correction method (OSC), the selected wavebands are centralized in the range of 565-1013 nm. The calibration and evaluation processes have demonstrated the second order derivate filtering method (DF2) combined with waveband selection is superior to other processes, for it has high R2 (larger than 0.7) both in PLS and OPLS models for calibration and evaluation, by choosing only 156 wavebands from the whole 700 wavebands. Meanwhile, OPLS method was considered to be more suitable for the analyzing than PLS in most of our situations.

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