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A Comprehensive Review on Machine Learning Approaches for Yield Prediction Using Essential Soil Nutrients
2022
Universal Journal of Agricultural Research
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Based on the findings of the reviews, an intelligent and robust machine learning technique provides the optimum option for achieving (i) soil fertility, (ii) crop prediction, and (iii) yield prediction ...
approaches such as Support Vector Machine, bayes classifier, decision tree, random forest, linear regression and Extreme Learning Machines. ...
The goal of precision agriculture (PA) is to develop an intelligent support system based on various crop parameters such as type of soil, presence of nutrients in the soil, level of water, humidity, quality ...
doi:10.13189/ujar.2022.100310
fatcat:z4js7cfq25hspadnrodljoc27u
Assessing the Long-Term Evolution of Abandoned Salinized Farmland via Temporal Remote Sensing Data
2021
Remote Sensing
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Thirty-two years of temporal Landsat imagery (from 1988 to 2019) was used to assess the evolution of salinization in Hetao, a two-thousand-year-old irrigation district in northern China. ...
The decrease in irrigation and the increase in drainage have deepened the groundwater table in Hetao, which weakens the salt collection capacity of the abandoned salinized farmland. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs13204057
fatcat:kd65lnza7vhcfjo7hqhe4t75vm
Machine Learning Technique for Crop Recommendation in Agriculture Sector
2019
International Journal of Engineering and Advanced Technology
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Also different analytical models like Decision Tree, Random Forest, Support Vector Machine and Bayesian Neural Network are available for required analysis. ...
These data mining techniques can be used to analyze the multidimensional, time specific data of agriculture sector to produce effective knowledge in support of the efforts to boost the economy. ...
Four clusters are formed on the basis of weather attribute, soil salinity and soil-PH, irrigated area, individual crop yields. ...
doi:10.35940/ijeat.a1171.109119
fatcat:mswwmt74lbbblbregy47hadr3q
Artificial neural networks and computer vision's based Phytoindication systems for variable rate irrigation improving
2022
IEEE Access
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The article proposes a methodology for optimizing the process of irrigation of crops using a phytoindication system based on computer vision methods. ...
Dynamic analysis of spatial and temporal variability leads to an increase in productivity and efficiency of water use. ...
An example is DLiSA's intelligent irrigation system based on a deep learning neural network for predicting the volumetric moisture content in the soil, the period of irrigation, and the spatial distribution ...
doi:10.1109/access.2022.3143524
fatcat:i5evcvxykbfkjn3xmjdzkvwvua
Water Allocation and Integrative Management of Precision Irrigation: A Systematic Review
2020
Water
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Precision irrigation, defined as an efficient water allocation technique characterized by the optimal management and best collaboration of various factors of the irrigation process, attracts considerable ...
Some frontier techniques such as data-oriented irrigation management, performance-proven water allocation, and cloud-based irrigation control are among the critical technologies capable of building a sustainable ...
Acknowledgments: We thank the editors for their hard work and the referees for their comments and valuable suggestions that helped to improve this paper. ...
doi:10.3390/w12113135
fatcat:q3ftrtlafzf2bikxrh2a5jnfce
Estimating salt content of vegetated soil at different depths with Sentinel-2 data
2020
PeerJ
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Firstly, 117 soil samples were collected from Jiefangzha Irrigation Area (JIA) in Hetao Irrigation District (HID), Inner Mongolia, China during August, 2019. ...
The accurate and timely monitoring of the soil salt content (SSC) at different depths is the prerequisite for the solution to salinization in the arid and semiarid areas. ...
ACKNOWLEDGEMENTS The authors would like to thank the Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas of Ministry of Education for providing the test equipment. ...
doi:10.7717/peerj.10585
pmid:33391883
pmcid:PMC7759139
fatcat:gvfz5bhefbblnp7bv3ocfezmh4
Remote Sensing Applications in Mapping Salt Affected Soils
2020
Agricultural Reviews
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The aim of this review paper is to provide a comprehensive overview of remote sensing-based mapping of salt affected soils. ...
Different bands of the multispectral data and the indices and transforms derived from them have been found useful in delineating salt affected soils. ...
Many methods of classification such as Maximum Likelihood (MLH), Support Vector Machine (SVM), Decision Tree (DT), and Logistic Regression (LR) based methods have been used successfully to identify SAS ...
doi:10.18805/ag.r-2008
fatcat:e7ncsefpq5hsraj4jmqa5kbkda
Adaptive Crop Management under Climate Uncertainty: Changing the Game for Sustainable Water Use
2021
Atmosphere
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Double and multiple cropping practices result in water savings because soil moisture is retained from one planting to another. ...
(2) What is the impact of drought on agricultural water consumption? ...
and irrigation district managers, and providing relevant documents and suggestions throughout the project period. ...
doi:10.3390/atmos12081080
fatcat:tqqnoakk5rhg7o5yln7pey3nxq
Remote sensing-based assessment of waterlogging and soil salinity: a case study from Kerala, India
2021
Results in Geophysical Sciences
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The methodology proposed in this study can potentially be used for cost-effective mapping of soil salinity in other geographical regions. ...
to formulate better management strategies in irrigated regions. ...
In another study, Wang et al. (2021) applied three machine learning-based modelling approach to estimate and map the soil salinity. ...
doi:10.1016/j.ringps.2021.100024
fatcat:srrinwnedzdtpneuozmrzz4hbe
Quantitatively estimating main soil water-soluble salt ions content based on Visible-near infrared wavelength selected using GC, SR and VIP
2019
PeerJ
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Finally, the performance of both models of partial least squares regression (PLSR) and support vector regression (SVR) was investigated on the basis of the sensitive spectral intervals. ...
Soil salinization is the primary obstacle to the sustainable development of agriculture and eco-environment in arid regions. ...
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ...
doi:10.7717/peerj.6310
pmid:30697491
pmcid:PMC6346982
fatcat:a4zdcprydzdzrfg7637b7uu2me
Yearly change in severely salt-damaged areas in paddy fields in Ban Phai in Northeast Thailand
2022
Hydrological Research Letters
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We conducted a field investigation of paddy fields from 2016 to 2019 in Ban Phai district, Khon Kaen province in Northeast Thailand to evaluate yearly changes in the effect of salinity damage on rice production ...
The investigation area was classified into severely saltaffected areas (2 nd of 5 classes) based on the definition used in Thailand. ...
ACKNOWLEDGMENTS This research was supported by JST/JICA SATREPS JPMJSA1502 and MEXT/JSPS KAKENHI 19H03069. ...
doi:10.3178/hrl.16.7
fatcat:o7j2k3dbjnhqlkxzbsshw6dvjy
Remote Sensing Data Fusion to Evaluate Patterns of Regional Evapotranspiration: A Case Study for Dynamics of Film-Mulched Drip-Irrigated Cotton in China's Manas River Basin over 20 Years
2022
Remote Sensing
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Supported by the promotion of FMDI technology, the area under cotton production in the basin increased by an average of 4.9% annually. ...
The dynamics of fused ET provide a reliable scientific basis for agricultural water resources planning and management and for the sustainable utilization of water and soil resources in the basin. ...
Acknowledgments: The authors gratefully acknowledge all the reviewers and editors for their comments on this paper.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs14143438
fatcat:mp4le3lfzjahpjiskjf73sbinq
Total dissolved salt prediction using neurocomputing models: Case study of Gypsum soil within Iraq region
2021
IEEE Access
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of soil salinization in an irrigation district based on the support vector
[11] Yuan Li, Zhou Li, Song Cui, and Qingping Zhang. Trade-off between soil machine. ...
On-line vis-NIR spectroscopy prediction
cation and estimation of soil properties using support vector machines. of soil organic carbon using machine learning. ...
doi:10.1109/access.2021.3071015
fatcat:3xwrg3gjnjccpdwjvjsekop7sa
Groundwater Suitability for Drinking and Irrigation Using Water Quality Indices and Multivariate Modeling in Makkah Al-Mukarramah Province, Saudi Arabia
2022
Water
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The PLSR models, which are based on physicochemical characteristics, have been shown to be the most efficient as alternative techniques for determining the six WQIs. ...
For instance, the PLSR models of all IWQs had determination coefficients values of R2 ranging between 0.848 and 0.999 in the Cal., and between 0.848 and 0.999 in the Val. datasets, and had model accuracy ...
Acknowledgments: "The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia, for funding this research work through the project number IFPRC ...
doi:10.3390/w14030483
fatcat:nihzqvzskbacrbtvsn6a3yrske
A Review of Irrigation Information Retrievals from Space and Their Utility for Users
2021
Remote Sensing
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Irrigation represents one of the most impactful human interventions in the terrestrial water cycle. ...
Knowing the distribution and extent of irrigated areas as well as the amount of water used for irrigation plays a central role in modeling irrigation water requirements and quantifying the impact of irrigation ...
The European Space Agency for supporting the activity via the ESA contract No. 4000129870/20/I-NB.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs13204112
fatcat:3iohcj5455ehpjhs2gbfhtzcfa
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