Determination of threshold soil salinity with consideration of salinity stress alleviation by applying nitrogen in the arid region

Che, Zheng; Wang, Jun; Li, Jiusheng

doi:10.1007/s00271-021-00762-y

Cited by 10 publications

(3 citation statements)

References 50 publications

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“…When the salinity exceeded the threshold, salinity significantly affected cotton growth. This was similar to the result of Che et al [34].…”

Section: Response Of Aboveground Biomass To Soil Salinitysupporting

confidence: 93%

Water-Salt Thresholds of Cotton (Gossypium hirsutum L.) under Film Drip Irrigation in Arid Saline-Alkali Area

Feng

et al. 2022

Agriculture

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Crop models are valuable tools for exploring the responses of crops to changes in environmental factors, and have been widely used to analyze the response of crops to varying soil water content and salinity levels in extreme drought and high salinity conditions. To obtain suitable water-salt thresholds and the total irrigation amount for cotton in the arid oasis of southern Xinjiang, the AquaCrop model was calibrated and validated using measured data from 2020 and 2021 (total irrigation amount: 255–480 mm; initial soil salinity levels: 0.2–0.6%). With the same initial soil water content, when the initial soil salinity < 7 dS/m, cotton yield did not significantly change under different levels of total irrigation amount, while when the initial soil salinity was 10 dS/m, there was a significant difference in cotton yield with a total irrigation amount > 300 mm. The total irrigation amount of 375 mm is the threshold for cotton at the low-salinity treatment, while it increases to 450 mm at the high-salinity treatment. Based on cotton performance with the AquaCrop model, the threshold values of soil salinity were 7, 9.3, 8.2 and 9.3 dS/m (ECe) during the cotton stage of seedling, squaring, flower-boll and maturity, respectively. The total irrigation amount of 450 to 500 mm could achieve a win-win scenario for both cotton yield and water use efficiency under sandy loam soil. In summary, this study can serve as a reference for regulating water and salt in arid saline-alkali regions.

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“…When the salinity exceeded the threshold, salinity significantly affected cotton growth. This was similar to the result of Che et al [34].…”

Section: Response Of Aboveground Biomass To Soil Salinitysupporting

confidence: 93%

Water-Salt Thresholds of Cotton (Gossypium hirsutum L.) under Film Drip Irrigation in Arid Saline-Alkali Area

Feng

et al. 2022

Agriculture

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“…However, flood irrigation can easily raise the groundwater level, and lead to increased surface salinity. Additionally, the excessive application of nitrogen fertilizer can also accelerate soil salinization [52]. The coefficient of variation of soil nutrients was lower than other indices.…”

Section: Analysis Of Soil Quality Evaluation Indicesmentioning

confidence: 90%

Soil Quality Evaluation for Cotton Fields in Arid Region Based on Graph Convolution Network

Fan,

Gao,

Zuo

et al. 2023

Land

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Accurate soil quality evaluation is an important prerequisite for improving soil management systems and remediating soil pollution. However, traditional soil quality evaluation methods are cumbersome to calculate, and suffer from low efficiency and low accuracy, which often lead to large deviations in the evaluation results. This study aims to provide a new and accurate soil quality evaluation method based on graph convolution network (GCN). In this study, soil organic matter (SOM), alkaline hydrolysable nitrogen (AN), available potassium (AK), salinity, and heavy metals (iron (Fe), copper (Cu), manganese (Mn), and zinc (Zn)) were determined and evaluated using the soil quality index (SQI). Then, the graph convolution network (GCN) was first introduced in the soil quality evaluation to construct an evaluation model, and its evaluation results were compared with those of the SQI. Finally, the spatial distribution of the evaluation results of the GCN model was displayed. The results showed that soil salinity had the largest coefficient of variation (86%), followed by soil heavy metals (67%) and nutrients (30.3%). The soil salinization and heavy metal pollution were at a low level in this area, and the soil nutrients and soil quality were at a high level. The evaluation accuracy of the GCN model for soil salinity/heavy metals, soil nutrients, and soil quality were 0.91, 0.84, and 0.90, respectively. Therefore, the GCN model has a high accuracy and is feasible to be applied in the soil quality evaluation. This study provides a new, simple, and highly accurate method for soil quality evaluation.

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“…Considering that seed germination and emergence are particularly sensitive to top-soil salinity, the spatial patterns of localized salinization in the field can have long-lasting impacts on crop emergence and, later, the spatial distribution of the canopy. For instance, the tolerance threshold of cotton, one of the most common crops in the arid regions, to soil salinity (EC 1:5 ) is 0.69 dS m −1 at seedling stage, and 1.02 dS m −1 at the flowering and bolling stage [10]. Therefore, to ensure crop emergence rate and the final crop yield, it is critically important to identify how intensively and persistently flood irrigation can affect the spatial variations of soil salinity before sowing [11].…”

Section: Introductionmentioning

confidence: 99%

Temporal and Spatial Assessment of Soil Salinity Post-Flood Irrigation: A Guide to Optimal Cotton Sowing Timing

He,

Li,

Jin

2023

Agronomy

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Flood irrigation is often applied in the arid regions of Northwest China to facilitate the leaching of salts accumulated in the soil during cotton growth in the previous season. This will, in turn, affect the temporal and spatial patterns of soil salinity, and thus cotton germination. To reveal the salinity of the two soil layers (0–20 cm and 20–60 cm), so as to determine the optimal cotton sowing timing, an electronic ground conductivity meter (EM38-MK2) was employed to measure the soil apparent electrical-conductivity (ECa) on different days: 4 days prior to flood irrigation, and, respectively, 6, 10, 15, 20, and 45 days after flood irrigation. Moreover, geostatistical analysis and block kriging interpolation were employed to analyze the spatial-temporal variations of soil salinity introduced by flood irrigation. Our results indicate that: (1) soil salinity in the two layers on different days can be well inverted from binary first-order equations of ECa at two coils (i.e., ECa1.0 and ECa0.5), demonstrating the feasibility of applying EM38-MK2 to estimate soil salinity in the field; and (2) soil salinity in the 0–20 cm layer significantly decreased during the first 15 days after flood irrigation with the greatest leaching rate of 88.37%, but tended to increase afterwards. However, the salinity in the 20–60 cm layer was persistently high before and after flood irrigation, with merely a brief decrease during the first 10 days after flood irrigation at the highest leaching rate of 40.74%. (3) The optimal semi-variance models illustrate that, after flood irrigation, the sill value (C0 + C) in the 0–20 cm layer decreased sharply, but the 20–60 cm Range of the layer significantly increased, suggesting that flood irrigation not only reduces the spatial variability of surface soil salinity, but also enhances spatial dependence in the 20–60 cm layer. (4) The correlation of the soil salinity between the two soil layers was very poor before flood irrigation, but gradually enhanced during the first 15 days after flood irrigation. Overall, for the study year, the first 15 days after flood irrigation was an optimal timing for cotton sowing when the leaching effects during flood irrigation were most efficient, and overrode the effects of evaporation and microtopography. Although not directly applicable to other years or regions, the electromagnetic induction surveys and spatiotemporal analysis of soil salinity can provide a rapid and viable guide to help determine optimal cotton sowing timing.

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Determination of threshold soil salinity with consideration of salinity stress alleviation by applying nitrogen in the arid region

Cited by 10 publications

References 50 publications

Water-Salt Thresholds of Cotton (Gossypium hirsutum L.) under Film Drip Irrigation in Arid Saline-Alkali Area

Water-Salt Thresholds of Cotton (Gossypium hirsutum L.) under Film Drip Irrigation in Arid Saline-Alkali Area

Soil Quality Evaluation for Cotton Fields in Arid Region Based on Graph Convolution Network

Temporal and Spatial Assessment of Soil Salinity Post-Flood Irrigation: A Guide to Optimal Cotton Sowing Timing

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