Machine-Learning Classification of Soil Bulk Density in Salt Marsh Environments

Hikouei, Iman Salehi; Kim, S. Sonny; Mishra, Deepak R.

doi:10.3390/s21134408

Cited by 16 publications

(4 citation statements)

References 105 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Sandy soil samples were ground to a smaller particle size and then sieved through a 2 mm mesh. The moisture of the samples was determined after drying in an oven (Jiangnan, China) at 65 • C. The soil bulk density method was according to Salehi Hikouei et al [20]. The methods for determining SOM and SOC followed those of Yeomans and Bremner [21].…”

Section: Determination Of the Physical-chemical Properties Of The San...mentioning

confidence: 99%

Long-Term Benefits of Cenchrus fungigraminus Residual Roots Improved the Quality and Microbial Diversity of Rhizosphere Sandy Soil through Cellulose Degradation in the Ulan Buh Desert, Northwest China

Li,

Zhang,

et al. 2024

Plants

View full text Add to dashboard Cite

Long-term plant residue retention can effectively replenish soil quality and fertility. In this study, we collected rhizosphere soil from the residual roots of annual Cenchrus fungigraminus in the Ulan Buh Desert over the past 10 years. The area, depth, and length of these roots decreased over time. The cellulose content of the residual roots was significantly higher in the later 5 years (2018–2022) than the former 5 years (2013–2017), reaching its highest value in 2021. The lignin content of the residual roots did not differ across samples except in 2015 and reached its highest level in 2021. The total sugar of the residual roots in 2022 was 227.88 ± 30.69 mg·g−1, which was significantly higher than that in other years. Compared to the original sandy soil, the soil organic matter and soil microbial biomass carbon (SMBC) contents were 2.17–2.41 times and 31.52–35.58% higher in the later 3 years (2020–2022) and reached the highest values in 2020. The residual roots also significantly enhanced the soil carbon stocks from 2018–2022. Soil dehydrogenase, nitrogenase, and N-acetyl-β-D-glucosidase (S-NAG) were significantly affected from 2019–2022. The rhizosphere soil community richness and diversity of the bacterial and fungal communities significantly decreased with the duration of the residual roots in the sandy soil, and there was a significant difference for 10 years. Streptomyces, Bacillus, and Sphigomonas were the representative bacteria in the residual root rhizosphere soil, while Agaricales and Panaeolus were the enriched fungal genera. The distance-based redundancy analysis and partial least square path model results showed that the duration of residual roots in the sandy soil, S-NAG, and SMBC were the primary environmental characteristics that shaped the microbial community. These insights provide new ideas on how to foster the exploration of the use of annual herbaceous plants for sandy soil improvement in the future.

show abstract

Section: Determination Of the Physical-chemical Properties Of The San...mentioning

confidence: 99%

Long-Term Benefits of Cenchrus fungigraminus Residual Roots Improved the Quality and Microbial Diversity of Rhizosphere Sandy Soil through Cellulose Degradation in the Ulan Buh Desert, Northwest China

Li,

Zhang,

et al. 2024

Plants

View full text Add to dashboard Cite

show abstract

“…SVM is an advanced and adaptable supervised machine learning technique that is commonly used for classification and regression applications. At its heart, SVM seeks the ideal hyperplane that optimally separates data points of distinct classes in the feature space [65]. For data that can be separated linearly, this hyperplane is a line (in two dimensions) or a plane (in three dimensions) that maximizes the margin between the two classes.…”

Section: Support Vector Machine (Svm)mentioning

confidence: 99%

Towards Improving Sustainable Water Management in Geothermal Fields: SVM and RF Land Use Monitoring

Utama,

Indriani,

Hermana

et al. 2024

J. Hum. Earth Future

View full text Add to dashboard Cite

The management and monitoring of land use in geothermal fields are crucial for the sustainable utilization of water resources, as well as for striking a balance between the production of renewable energy and the preservation of the environment. This study primarily compared Support Vector Machine (SVM) and Random Forest (RF) machine learning methods, using satellite imagery from Landsat 8 and Sentinel 2 between 2021 and 2023, to monitor land use in the Patuha geothermal area. The objective is to improve sustainable water management practices by accurately categorizing different land cover types. This comparative analysis assessed the efficacy of these techniques in upholding water sustainability in geothermal regions. This study examined the application of SVM and RF machine learning techniques, with particular emphasis on parameter refinement and model assessment, to enhance land use classification accuracy. By employing Kernlab and e1071 for algorithm comparison, the research sought to produce a precise Land Use Model Map, which underscores the significance of advanced analytical techniques in environmental management. This approach was of utmost importance in improving land use monitoring and reinforcing sustainable practices. The comparative evaluation of SVM and RF methods for land use classification demonstrates the superiority of RF in terms of accuracy, stability, and precision, particularly in intricate urban settings, hence establishing it as the preferred model for tasks demanding high reliability. The application of SVM and RF for monitoring land use in geothermal areas is in alignment with Sustainable Development Goals (SDGs) 6 and 15, as it fosters sustainable water management and the conservation of ecosystems. Doi: 10.28991/HEF-2024-05-02-06 Full Text: PDF

show abstract

“…Within each plot, three randomly chosen locations were selected to measure the previous soil parameters through the soil depth of 10 cm, then the samples were averaged for each replication. After drying for 48 hours at 105°C, the cores were analyzed to determine the bulk density [16]. In a complete block randomized design, the factorial design was used to determine the effects of tillage practices as well as fertilizers on soil bulk density, pH and EC.…”

Section: Soil and Organic Manure Analysesmentioning

confidence: 99%

Yield Performance of Wheat Under Different Practices of Tillage and Integrated Inorganic and Organic Fertilizers

Ramadhan

2022

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

Tillage management and fertilizer application are important components of wheat plant growth and productivity. Yet limited data are available on the consequences of simultaneous tillage and integrated fertilization on wheat production and soil chemical characteristics in the heavy soil of Sothern parts of Iraq. Hence, split-split plots were used to conduct a field experiments at two locations. The primary plots were divided into three tillage techniques that are no tillage (NT), tine cultivator (TC) and moldboard plow (MP). Five selected combinations of organic and inorganic nutrient sources were arranged in sub plots including the traditional chemical fertilizer application of nitrogen, phosphorus and potassium (CF), farm yard manure (FYM), poultry manure (PM), 50% CF+FYM and 50% CF+PM application, in addition to control treatment, and three wheat cultivars (Al-Rasheed, IPA-99 and Abu Ghraib-3) were allocated to sub-sub plots. The results showed positive superiority of MP and TC in the growth parameters, yield components, wheat yield and some soil properties at both experimental locations. Likewise, the MP and TC had the lowest bulk density, while MP had the lowest electrical conductivity and the highest soil pH. The results also revealed that organic and inorganic amendments affected plant growth, yield components, grain yield significantly. The 50% CF+PM and 50% CF+FYM gave significantly higher thousand grain weight, spikes number at the 2nd location, wheat yield, and tillers per square meter at the 2nd location. Furthermore, soil bulk density, pH and electrical conductivity were significantly affected by all organic and inorganic treatments. The results also indicated that the highest spikes number, grain yield, chlorophyll content SPAD were recorded by IPA-99 cultivar at both locations. Moreover, under experiment conditions, the flag leaf chlorophyll content was significantly related to grain yield.

show abstract

Machine-Learning Classification of Soil Bulk Density in Salt Marsh Environments

Cited by 16 publications

References 105 publications

Long-Term Benefits of Cenchrus fungigraminus Residual Roots Improved the Quality and Microbial Diversity of Rhizosphere Sandy Soil through Cellulose Degradation in the Ulan Buh Desert, Northwest China

Long-Term Benefits of Cenchrus fungigraminus Residual Roots Improved the Quality and Microbial Diversity of Rhizosphere Sandy Soil through Cellulose Degradation in the Ulan Buh Desert, Northwest China

Towards Improving Sustainable Water Management in Geothermal Fields: SVM and RF Land Use Monitoring

Yield Performance of Wheat Under Different Practices of Tillage and Integrated Inorganic and Organic Fertilizers

Contact Info

Product

Resources

About