scholarly journals Characteristics of Saline Soil in Extremely Arid Regions: A Case Study Using GF-3 and ALOS-2 Quad-Pol SAR Data in Qinghai, China

2021 ◽  
Vol 13 (3) ◽  
pp. 417
Author(s):  
Yao Gao ◽  
Xiuqing Liu ◽  
Wentao Hou ◽  
Yonghui Han ◽  
Robert Wang ◽  
...  
Keyword(s):  
Negative Correlation ◽  
Soil Salinity ◽  
Arid Regions ◽  
Saline Soil ◽  
Correlation Coefficients ◽  
Polarization Ratio ◽  
Backscattering Coefficient ◽  
Sar Images ◽  
L Band ◽  
Radar Backscattering

Soil salinization is a global problem, which seriously damages the ecological environment and considerably reduces agricultural productivity, especially in arid regions. Synthetic aperture radar (SAR) has been widely used in remote sensing due to its weather and sunlight independence. Polarimetric SAR has great potential for large-scale mapping and monitoring salt-affected soils. In this study, we investigate the characteristics of saline soil in extremely arid regions using dual-band quadrature-polarimetric (quad-pol) SAR images acquired by GF-3 (C-band) and ALOS-2 (L-band). Firstly, the effectiveness of the modified dielectric mixing model and integral equation model (IEM) in describing saline soil is evaluated. Secondly, the potential relationships between polarimetric parameters and salinity are discussed in both the C- and L-band, respectively, such as co-polarization ratio, scattering entropy H, and scattering angle α. Finally, a linear regression model for monitoring salt content is established. The main contributions of this article are as follows: (1) Simulation results suggest that the radar backscattering coefficient is a weak function of salinity at low water content, but our experimental data show that soil salinity significantly contributes to the radar backscattering coefficient, which indicates the modified dielectric mixing model and IEM model is not applicable in extremely arid areas. (2) A negative correlation between the co-polarization ratio and salinity is observed, and the correlation coefficients are 0.64 (C-band) and 0.71 (L-band). Besides, scattering entropy and scattering angle exhibit a positive correlation with salinity in the C-band with correlation coefficients 0.686 and 0.669, respectively, whereas a negative correlation is found in the L-band with correlation coefficients 0.682 and 0.680, respectively. This can be attributed to the different penetration depths and sensitivity to the surface roughness of the electromagnetic waves at two frequencies. (3) A regression model for salinity estimating based on radar backscattering coefficient, co-polarization ratio, and scattering entropy is established, with a determination coefficient (R2) of 0.79 and a root mean square error (RMSE) of 6.56%, allowing us to determine soil salinity from quad-pol SAR images without using backscattering models. Therefore, our results can be a reference for future soil salinity monitoring and inversion.

Effect of forest thinning on the radar backscattering coefficient at L-band

1998 ◽  
Vol 19 (11) ◽  
pp. 2233-2238 ◽  
Author(s):  
I. Champion ◽  
D. Guyon ◽  
J. Riom ◽  
T. Le Toan ◽  
A. Beaudoin
Keyword(s):  
Backscattering Coefficient ◽  
Forest Thinning ◽  
L Band ◽  
Radar Backscattering

scholarly journals Grafting Improves Fruit Yield of Cucumber Plants Grown under Combined Heat and Soil Salinity Stresses

Horticulturae ◽  
2021 ◽  
Vol 7 (3) ◽  
pp. 61
Author(s):  
Yousry Bayoumi ◽  
Emad Abd-Alkarim ◽  
Hassan El-Ramady ◽  
Farouk El-Aidy ◽  
El-Samahy Hamed ◽  
...  
Keyword(s):  
Arid Regions ◽  
Saline Soil ◽  
Growth Yield ◽  
High Temperature Stress ◽  
Cucumis Sativus L ◽  
Chlorophyll Contents ◽  
Flower Abortion ◽  
Yield Quality ◽  
Si Content ◽  
Better Than

Improving the productivity of cucumber (Cucumis sativus L.) plants subjected to combined salinity and heat stresses is a significant challenge, particularly in arid and semi-arid regions. Gianco F1 cucumbers were grafted onto five cucurbit rootstocks and, together with an ungrafted control, were grown in Egypt in a net house with saline soil during the summer season over two years. The vegetative growth, yield, quality, biochemical, and mineral composition traits were measured. Although many differences were observed among treatments, in general, the grafted plants had a performance better than or similar to that of the ungrafted plants, based on the different parameters measured. In particular, the cucumber plants grafted onto the Cucurbita maxima × C. moschata interspecific hybrid rootstocks VSS-61 F1 and Ferro had the highest early and total marketable yields. These two rootstocks consistently conferred higher vigor to the scion, which had lower flower abortion rates and higher chlorophyll contents. The fruit quality and N, P, and K composition in the leaves suffered few relevant changes as compared with the control. However, the leaves of the VSS-61 F1 had higher catalase activity, as well as proline and Se contents, while those of Ferro had higher Si content. This study reveals that the grafting of cucumber plants onto suitable rootstocks may mitigate the adverse effects caused by the combination of saline soil and heat stresses. This represents a significant improvement for cucumber cultivation in saline soil under high-temperature stress conditions in arid regions.

scholarly journals Screening of Salt Tolerant CIP Potato Germplasm for Saline Areas

2013 ◽  
Vol 11 (1) ◽  
pp. 95-102 ◽  
Author(s):  
MH Rahman ◽  
MM Alam Patwary ◽  
H Barua ◽  
M Hossain ◽  
MM Hasan
Keyword(s):  
Soil Salinity ◽  
Agricultural Research ◽  
Saline Soil ◽  
The Other ◽  
Salt Tolerant ◽  
Agricultural Research Institute ◽  
International Potato ◽  
Local Variety ◽  
Potato Germplasm ◽  
High Level

Fifteen salt tolerant CIP (International Potato Centre) Potato genotypes along with BARI (Bangladesh Agricultural Research Institute) Alu 7 (Diamant) and one local variety viz., Dohazari Sada were evaluated at Bashkhali, Chittagong during 2011-12 to screen the suitable genotypes for cultivation in saline areas of Bangladesh. Diamant and Dohazari Sada and all of the CIP genotypes were found to grow well up to 60 DAP (Days After Planting) at saline areas having healthy plants and no senescence was noticed but after that 61-100% plants died due to high level of soil salinity (6.41dS/m) depending on genotypes. Genotype CIP 112 gave the highest yield (21.07 t/ha) and CIP 102 was comparatively less affected by soil salinity than the other genotypes. However, all the salt tolerant CIP genotypes were found to be promising in the saline soil. DOI: http://dx.doi.org/10.3329/agric.v11i1.15249 The Agriculturists 2013; 11(1) 95-102

scholarly journals Analysis of the Dielectric Constant of Saline-Alkali Soils and the Effect on Radar Backscattering Coefficient: A Case Study of Soda Alkaline Saline Soils in Western Jilin Province Using RADARSAT-2 Data

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Yang-yang Li ◽  
Kai Zhao ◽  
Jian-hua Ren ◽  
Yan-ling Ding ◽  
Li-li Wu
Keyword(s):  
Dielectric Constant ◽  
Soil Salinity ◽  
Frequency Effect ◽  
Complex Dielectric Constant ◽  
Saline Soils ◽  
Suitable Model ◽  
Backscattering Coefficient ◽  
Mixed Pixel ◽  
Western Jilin Province

Soil salinity is a global problem, especially in developing countries, which affects the environment and productivity of agriculture areas. Salt has a significant effect on the complex dielectric constant of wet soil. However, there is no suitable model to describe the variation in the backscattering coefficient due to changes in soil salinity content. The purpose of this paper is to use backscattering models to understand behaviors of the backscattering coefficient in saline soils based on the analysis of its dielectric constant. The effects of moisture and salinity on the dielectric constant by combined Dobson mixing model and seawater dielectric constant model are analyzed, and the backscattering coefficient is then simulated using the AIEM. Simultaneously, laboratory measurements were performed on ground samples. The frequency effect of the laboratory results was not the same as the simulated results. The frequency dependence of the ionic conductivity of an electrolyte solution is influenced by the ion’s components. Finally, the simulated backscattering coefficients measured from the dielectric constant with the AIEM were analyzed using the extracted backscattering coefficient from the RADARSAT-2 image. The results show that RADARSAT-2 is potentially able to measure soil salinity; however, the mixed pixel problem needs to be more thoroughly considered.

scholarly journals Relationship Between Carcass Weight, Muscle, Fat, and Predicted Lean Yield for Commercial Pigs in Ontario

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
R. S. Barducci ◽  
Z. Zhou ◽  
D. Tulpan ◽  
B. M. Bohrer
Keyword(s):  
Negative Correlation ◽  
Correlation Coefficients ◽  
Carcass Weight ◽  
Linear Regression Models ◽  
Strong Negative Correlation ◽  
Statistical Software ◽  
Carcass Parameters ◽  
Scatter Plots ◽  
Positive Correlations ◽  
Meaningful Relationships

ObjectivesGreater knowledge of variance and relationships of pork carcass parameters could be used to improve performance, efficiency, and profitability of the pork industry. Previous research has investigated the correlation between pork carcass parameters; however, there are still many misunderstandings, particularly in commercially representative pigs. Thus, the purpose of this study was to examine the correlation and variance of carcass weight, fat depth, muscle depth, and predicted lean yield in commercial pigs.Materials and MethodsThe second largest commercial pig slaughter facility in Ontario slaughtered approximately 1.5 million pigs in 2018. Carcass data (hot carcass weight, fat depth, muscle depth, and predicted lean yield) from 1025,572 pigs was used for this study with pigs slaughtered on each production day of 2018 (between January 2, 2018 and December 31, 2018). Hot carcass weight was reported immediately following slaughter as a head-on weight, and fat depth and muscle depth were measured with a Destron PG-100 probe (International Destron Technologies, Markham, Ontario). The equation used for predicted lean yield was the Canadian Lean Yield equation (CLY (%) = 68.1863– (0.7833 × fat depth) + (0.0689 × muscle depth) + (0.0080 × fat depth2) – (0.0002 × muscle depth2) + (0.0006 × fat depth × muscle depth). Pearson product moment correlation coefficients were calculated among all parameters using RStudio version 1.1.456 and R version 3.5.1 statistical software. Correlation coefficients were considered significantly different from 0 at P < 0.05. Correlations were considered weak (in absolute value) for r < 0.35, moderate for 0.36 ≤ r ≤ 0.67, and strong for r ≥ 0.68. Linear regression models were created between parameters that had meaningful relationships using the RStudio statistical software. Gnuplot version 5.2 was used to create scatter plots to allow for better visualization of the correlation between meaningful parameters.ResultsThe mean ± standard deviation for fat depth, muscle depth, hot carcass weight, and predicted lean yield were 18.27 ± 4.12 mm, 65.69 ± 9.06 mm, 105.93 ± 8.39 kg, and 61.03 ± 1.91%, respectively. We observed weak positive correlations between fat depth and hot carcass weight (r = 0.27; P < 0.0001), and between muscle depth and hot carcass weight (r = 0.17; P < 0.0001). We obtained a weak negative correlation between predicted lean yield and hot carcass weight (r = –0.21; P < 0.0001). The predicted lean yield equation used for this set of pigs included measurements for fat depth and muscle depth, so strong correlation between these parameters was expected. We obtained a moderate positive correlation between muscle depth and predicted lean yield (r = 0.39; P < 0.0001) and a strong negative correlation between fat depth and predicted lean yield (r = –0.96; P < 0.0001).ConclusionResults from this dataset revealed that hot carcass weight was generally not correlated with fat depth, muscle depth, or predicted lean yield. The conclusion of this study based on the current dataset is that pigs do not reach a weight threshold where they consistently become fatter or heavier muscled.

scholarly journals Long-Term Amelioration Practices Reshape the Soil Microbiome in a Coastal Saline Soil and Alter the Richness and Vertical Distribution Differently Among Bacterial, Archaeal, and Fungal Communities

2022 ◽  
Vol 12 ◽  
Author(s):  
Ruibo Sun ◽  
Xiaogai Wang ◽  
Yinping Tian ◽  
Kai Guo ◽  
Xiaohui Feng ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Soil Salinity ◽  
Saline Soil ◽  
Saline Water ◽  
Soil Microbial Communities ◽  
Soil Microbiome ◽  
Economic Losses ◽  
Saline Water Irrigation ◽  
Coastal Saline Soil ◽  
Plastic Mulching

Globally soil salinity is one of the most devastating environmental stresses affecting agricultural systems and causes huge economic losses each year. High soil salinity causes osmotic stress, nutritional imbalance and ion toxicity to plants and severely affects crop productivity in farming systems. Freezing saline water irrigation and plastic mulching techniques were successfully developed in our previous study to desalinize costal saline soil. Understanding how microbial communities respond during saline soil amelioration is crucial, given the key roles soil microbes play in ecosystem succession. In the present study, the community composition, diversity, assembly and potential ecological functions of archaea, bacteria and fungi in coastal saline soil under amelioration practices of freezing saline water irrigation, plastic mulching and the combination of freezing saline water irrigation and plastic mulching were assessed through high-throughput sequencing. These amelioration practices decreased archaeal and increased bacterial richness while leaving fungal richness little changed in the surface soil. Functional prediction revealed that the amelioration practices, especially winter irrigation with saline water and film mulched in spring, promoted a community harboring heterotrophic features. β-null deviation analysis illustrated that amelioration practices weakened the deterministic processes in structuring coastal saline soil microbial communities. These results advanced our understanding of the responses of the soil microbiome to amelioration practices and provided useful information for developing microbe-based remediation approaches in coastal saline soils.

Effects of Genotype and Rainfall on Forage Oats in a Semi-arid Region

1977 ◽  
Vol 13 (3) ◽  
pp. 217-223 ◽  
Author(s):  
A. Hadjichristodoulou
Keyword(s):  
Arid Region ◽  
Selection Criteria ◽  
Crude Protein ◽  
Dry Matter ◽  
Arid Regions ◽  
Correlation Coefficients ◽  
Annual Rainfall ◽  
Varietal Response ◽  
Semi Arid Region ◽  
Semi Arid

SUMMARYThere were significant differences in dry matter yield among five forage oat varieties tested at ten environments during 1970–75. The correlation coefficients between annual rainfall and DM yield varied with variety from 0·69 to 0·88, late varieties tending to give higher yields. Lateness, and high varietal response to annual rainfall and improved environmental conditions, can be used as selection criteria in semi-arid regions. Late varieties had higher DM and lower crude protein contents, and forage produced under lower rainfall conditions tended to have more DM and crude protein.

scholarly journals Permafrost Soil Moisture Monitoring Using Multi-Temporal TerraSAR-X Data in Beiluhe of Northern Tibet, China

2018 ◽  
Vol 10 (10) ◽  
pp. 1577 ◽  
Author(s):  
Chao Wang ◽  
Zhengjia Zhang ◽  
Simonetta Paloscia ◽  
Hong Zhang ◽  
Fan Wu ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Winter Season ◽  
Tibet Plateau ◽  
Permafrost Soil ◽  
Permafrost Region ◽  
Backscattering Coefficient ◽  
Sar Images ◽  
Northern Tibet ◽  
Variation Patterns

Global change has significant impact on permafrost region in the Tibet Plateau. Soil moisture (SM) of permafrost is one of the most important factors influencing the energy flux, ecosystem, and hydrologic process. The objectives of this paper are to retrieve the permafrost SM using time-series SAR images, without the need of auxiliary survey data, and reveal its variation patterns. After analyzing the characteristics of time-series radar backscattering coefficients of different landcover types, a two-component SM retrieval model is proposed. For the alpine meadow area, a linear retrieving model is proposed using the TerraSAR-X time-series images based on the assumption that the lowest backscattering coefficient is measured when the soil moisture is at its wilting point and the highest backscattering coefficient represents the water-saturated soil state. For the alpine desert area, the surface roughness contribution is eliminated using the dual SAR images acquired in the winter season with different incidence angles when retrieving soil moisture from the radar signal. Before the model implementation, landcover types are classified based on their backscattering features. 22 TerraSAR-X images are used to derive the soil moisture in Beiluhe, Northern Tibet with different incidence angles. The results obtained from the proposed method have been validated using in-situ soil moisture measurements, thus obtaining RMSE and Bias of 0.062 cm3/cm3 and 4.7%, respectively. The retrieved time-series SM maps of the study area point out the spatial and temporal SM variation patterns of various landcover types.

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