Prediction of loquat soluble solids and titratable acid content using fruit mineral elements by artificial neural network and multiple linear regression

X Huang, H Wang, W Luo, S Xue, F Hayat, Z Gao - Scientia Horticulturae, 2021 - Elsevier
Mineral nutrient elements have an important impact on fruit quality, especially on soluble
solids (SSC), titratable acid content (TAC) and the ratio of soluble solids to titratable acid …

Improving the spatial prediction of soil salinity in arid regions using wavelet transformation and support vector regression models

R Taghizadeh-Mehrjardi, K Schmidt, N Toomanian… - Geoderma, 2021 - Elsevier
The low potential of agricultural productivity in the majority of central Iran is mainly attributed
to high levels of soil salinity. To increase agricultural productivity, while preventing any …

[HTML][HTML] Digital mapping of soil salinization based on Sentinel-1 and Sentinel-2 data combined with machine learning algorithms

G Ma, J Ding, L Han, Z Zhang, S Ran - Regional Sustainability, 2021 - Elsevier
Soil salinization is one of the most important causes of land degradation and desertification,
especially in arid and semi-arid areas. The dynamic monitoring of soil salinization is of great …

Assessing agricultural salt-affected land using digital soil mapping and hybridized random forests

K Nabiollahi, R Taghizadeh-Mehrjardi, A Shahabi… - Geoderma, 2021 - Elsevier
Salinization and alkalization are predominant environmental problem world-wide which their
accurate assessment is essential for determining appropriate ways to deal with land …

Investigation of the spatial and temporal variation of soil salinity using random forests in the central desert of Iran

H Fathizad, MAH Ardakani, H Sodaiezadeh, R Kerry… - Geoderma, 2020 - Elsevier
Traditional soil salinity studies, especially over large areas, are expensive and time-
consuming. Therefore, it is necessary to employ new methods to examine salinity of large …

Integrating remote sensing and landscape characteristics to estimate soil salinity using machine learning methods: A case study from Southern Xinjiang, China

N Wang, J Xue, J Peng, A Biswas, Y He, Z Shi - Remote Sensing, 2020 - mdpi.com
Soil salinization, one of the most severe global land degradation problems, leads to the loss
of arable land and declines in crop yields. Monitoring the distribution of salinized soil and …

Novel ensembles of COPRAS multi-criteria decision-making with logistic regression, boosted regression tree, and random forest for spatial prediction of gully erosion …

A Arabameri, M Yamani, B Pradhan, A Melesse… - Science of the total …, 2019 - Elsevier
Gully erosion is considered as a severe environmental problem in many areas of the world
which causes huge damages to agricultural lands and infrastructures (ie roads, buildings …

Using environmental variables and Fourier Transform Infrared Spectroscopy to predict soil organic carbon

MG Goydaragh, R Taghizadeh-Mehrjardi… - Catena, 2021 - Elsevier
Abstract Soil Organic Carbon (SOC) content is a key element for soil fertility and productivity,
nutrient availability and potentially represents a measurement of the sink for greenhouse …

Coupling of machine learning and remote sensing for soil salinity mapping in coastal area of Bangladesh

SK Sarkar, RR Rudra, AR Sohan, PC Das… - Scientific Reports, 2023 - nature.com
Soil salinity is a pressing issue for sustainable food security in coastal regions. However, the
coupling of machine learning and remote sensing was seldom employed for soil salinity …

Retrieval of soil salinity from Sentinel-2 multispectral imagery

MM Taghadosi, M Hasanlou… - European Journal of …, 2019 - Taylor & Francis
Soil salinity is a widespread environmental hazard and the main causes of land degradation
and desertification, especially in arid and semi-arid regions. The first step in finding such a …