Design and Application of Agricultural Equipment in Tillage System

Agricultural productivity should increase to meet the growing food demand. Tillage is defined as the mechanical manipulation of agricultural soil, and it is an extremely vital part of crop production, particularly for seedbed preparation and weed control. Tillage operations are carried out using mec...

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Format: Online
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:
DEM
MBD
GMM
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Online Access:ONIX_20230511_9783036572949_77
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collection Directory of Open Access Books
description Agricultural productivity should increase to meet the growing food demand. Tillage is defined as the mechanical manipulation of agricultural soil, and it is an extremely vital part of crop production, particularly for seedbed preparation and weed control. Tillage operations are carried out using mechanical force, commonly with a tractor-drawn tool to achieve the cutting, inversion, pulverization, and disturbance of soil. A significant part of the energy (from fossil fuels) used in crop production is expended in tillage. This energy use results in greenhouse gas emissions. It is essential that we reduce energy use (hence, greenhouse gas emissions) to achieve sustainable farming practices and improve crop production and design new tillage tools or optimize the existing tools. Although the design and evaluation of tillage tools are generally carried out using analytical methods and field experiments, with recent technological improvements, computer technology has been used for the design and evaluation of tillage tools. Additionally, sensor technology can improve the efficiency of tillage tools. This Special Issue collated innovative papers that make a significant contribution to the design and application of agricultural equipment in tillage systems. It involved original research and review papers from different research fields, such as agricultural engineering, engineering simulation, and precision agriculture.
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spelling doab-20.500.12854ir-1000602024-04-11T15:10:54Z Design and Application of Agricultural Equipment in Tillage System Ucgul, Mustafa Chang, Chung-Liang deep learning machine vision weeder smart agriculture mechanical control agricultural unmanned electrical tractor no-tillage disc spring-tine soil property traffic rapeseed transplanting hole-forming device key components experiment electric tractor motor efficiency dual motor coupling drive I-SA algorithm generalization ability parameter identification image processing two-wheeled robot trailer steering control strip farming no-tillage sowing sowing strip cleaning spiral discharge straw discrete element simulation anti-blocking and row-sorting compound planter ditching soil separation spiral discrete element method parameter optimization agricultural machinery HMCVT correction of characteristics I-PSO algorithm parameter match residual film recovery machine DEM virtual simulation hydro-mechanical continuously variable transmission tractor optimization design simulation experiments I-GA geometric principle plough ploughshares durability calculation method agricultural machine wear plasma-hardening surface simulation quality improvement improved genetic algorithm full-factorial test single evaluation index modeling method control strategy soil cover discrete element soil-covering thickness seed offset rice combine harvester throwing device wind blades fluid analysis deflector optimization throwing width cotton recovery device EDEM parameters optimization MBD coupled simulation seeding soybean seed–soil corn seed collision restitution coefficient residual film recovery device response surface regression model seedbed clearing and shaping stone removal rate seeding furrow dry direct-seeded rice discrete element modeling dual vs. single tyres rut depth soil bearing capacity soil displacement tractive efficiency tyre size and inflation pressure Kmeans DBSCAN GMM tilling depth well-cellar cavitating mechanism MBD-DEM bidirectional coupling model optimal design cavitating law flat disc analytical force prediction model discrete element method (DEM) soil-tool interaction disc seeder disc blade force prediction semi-analytical model sandy soil stubble management no-till sowing stalk cutting post-harvest prototype multi-body dynamics (MBD) DEM-MBD coupling topsoil burial tillage traction compaction neural networks support vector regression fuzzy inference system adaptive neuro-fuzzy inference system calibration DEM contact models soil dynamics soil failure soil forces cohesive and frictional soils n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Agricultural productivity should increase to meet the growing food demand. Tillage is defined as the mechanical manipulation of agricultural soil, and it is an extremely vital part of crop production, particularly for seedbed preparation and weed control. Tillage operations are carried out using mechanical force, commonly with a tractor-drawn tool to achieve the cutting, inversion, pulverization, and disturbance of soil. A significant part of the energy (from fossil fuels) used in crop production is expended in tillage. This energy use results in greenhouse gas emissions. It is essential that we reduce energy use (hence, greenhouse gas emissions) to achieve sustainable farming practices and improve crop production and design new tillage tools or optimize the existing tools. Although the design and evaluation of tillage tools are generally carried out using analytical methods and field experiments, with recent technological improvements, computer technology has been used for the design and evaluation of tillage tools. Additionally, sensor technology can improve the efficiency of tillage tools. This Special Issue collated innovative papers that make a significant contribution to the design and application of agricultural equipment in tillage systems. It involved original research and review papers from different research fields, such as agricultural engineering, engineering simulation, and precision agriculture. 2023-05-11T17:18:52Z 2023-05-11T17:18:52Z 2023 book ONIX_20230511_9783036572949_77 9783036572949 9783036572956 https://directory.doabooks.org/handle/20.500.12854/100060 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/7153 https://mdpi.com/books/pdfview/book/7153 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-7295-6 10.3390/books978-3-0365-7295-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036572949 9783036572956 564 Basel open access
spellingShingle deep learning
machine vision
weeder
smart agriculture
mechanical control
agricultural
unmanned
electrical tractor
no-tillage
disc
spring-tine
soil
property
traffic
rapeseed transplanting
hole-forming device
key components
experiment
electric tractor
motor efficiency
dual motor coupling drive
I-SA algorithm
generalization ability
parameter identification
image processing
two-wheeled robot trailer
steering control
strip farming
no-tillage sowing
sowing strip cleaning
spiral discharge straw
discrete element simulation
anti-blocking and row-sorting
compound planter
ditching
soil separation spiral
discrete element method
parameter optimization
agricultural machinery
HMCVT
correction of characteristics
I-PSO algorithm
parameter match
residual film recovery machine
DEM
virtual simulation
hydro-mechanical continuously variable transmission
tractor
optimization design
simulation experiments
I-GA
geometric principle
plough
ploughshares
durability calculation method
agricultural machine
wear
plasma-hardening surface
simulation
quality improvement
improved genetic algorithm
full-factorial test
single evaluation index modeling method
control strategy
soil cover
discrete element
soil-covering thickness
seed offset
rice combine harvester
throwing device
wind blades
fluid analysis
deflector optimization
throwing width
cotton recovery device
EDEM
parameters optimization
MBD
coupled simulation
seeding
soybean
seed–soil
corn seed
collision restitution coefficient
residual film recovery device
response surface regression model
seedbed clearing and shaping
stone removal rate
seeding furrow
dry direct-seeded rice
discrete element modeling
dual vs. single tyres
rut depth
soil bearing capacity
soil displacement
tractive efficiency
tyre size and inflation pressure
Kmeans
DBSCAN
GMM
tilling depth
well-cellar cavitating mechanism
MBD-DEM bidirectional coupling model
optimal design
cavitating law
flat disc
analytical force prediction model
discrete element method (DEM)
soil-tool interaction
disc seeder
disc blade
force prediction
semi-analytical model
sandy soil
stubble management
no-till sowing
stalk cutting
post-harvest
prototype
multi-body dynamics (MBD)
DEM-MBD coupling
topsoil burial
tillage
traction
compaction
neural networks
support vector regression
fuzzy inference system
adaptive neuro-fuzzy inference system
calibration
DEM contact models
soil dynamics
soil failure
soil forces
cohesive and frictional soils
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Design and Application of Agricultural Equipment in Tillage System
title Design and Application of Agricultural Equipment in Tillage System
title_full Design and Application of Agricultural Equipment in Tillage System
title_fullStr Design and Application of Agricultural Equipment in Tillage System
title_full_unstemmed Design and Application of Agricultural Equipment in Tillage System
title_short Design and Application of Agricultural Equipment in Tillage System
title_sort design and application of agricultural equipment in tillage system
topic deep learning
machine vision
weeder
smart agriculture
mechanical control
agricultural
unmanned
electrical tractor
no-tillage
disc
spring-tine
soil
property
traffic
rapeseed transplanting
hole-forming device
key components
experiment
electric tractor
motor efficiency
dual motor coupling drive
I-SA algorithm
generalization ability
parameter identification
image processing
two-wheeled robot trailer
steering control
strip farming
no-tillage sowing
sowing strip cleaning
spiral discharge straw
discrete element simulation
anti-blocking and row-sorting
compound planter
ditching
soil separation spiral
discrete element method
parameter optimization
agricultural machinery
HMCVT
correction of characteristics
I-PSO algorithm
parameter match
residual film recovery machine
DEM
virtual simulation
hydro-mechanical continuously variable transmission
tractor
optimization design
simulation experiments
I-GA
geometric principle
plough
ploughshares
durability calculation method
agricultural machine
wear
plasma-hardening surface
simulation
quality improvement
improved genetic algorithm
full-factorial test
single evaluation index modeling method
control strategy
soil cover
discrete element
soil-covering thickness
seed offset
rice combine harvester
throwing device
wind blades
fluid analysis
deflector optimization
throwing width
cotton recovery device
EDEM
parameters optimization
MBD
coupled simulation
seeding
soybean
seed–soil
corn seed
collision restitution coefficient
residual film recovery device
response surface regression model
seedbed clearing and shaping
stone removal rate
seeding furrow
dry direct-seeded rice
discrete element modeling
dual vs. single tyres
rut depth
soil bearing capacity
soil displacement
tractive efficiency
tyre size and inflation pressure
Kmeans
DBSCAN
GMM
tilling depth
well-cellar cavitating mechanism
MBD-DEM bidirectional coupling model
optimal design
cavitating law
flat disc
analytical force prediction model
discrete element method (DEM)
soil-tool interaction
disc seeder
disc blade
force prediction
semi-analytical model
sandy soil
stubble management
no-till sowing
stalk cutting
post-harvest
prototype
multi-body dynamics (MBD)
DEM-MBD coupling
topsoil burial
tillage
traction
compaction
neural networks
support vector regression
fuzzy inference system
adaptive neuro-fuzzy inference system
calibration
DEM contact models
soil dynamics
soil failure
soil forces
cohesive and frictional soils
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
topic_facet deep learning
machine vision
weeder
smart agriculture
mechanical control
agricultural
unmanned
electrical tractor
no-tillage
disc
spring-tine
soil
property
traffic
rapeseed transplanting
hole-forming device
key components
experiment
electric tractor
motor efficiency
dual motor coupling drive
I-SA algorithm
generalization ability
parameter identification
image processing
two-wheeled robot trailer
steering control
strip farming
no-tillage sowing
sowing strip cleaning
spiral discharge straw
discrete element simulation
anti-blocking and row-sorting
compound planter
ditching
soil separation spiral
discrete element method
parameter optimization
agricultural machinery
HMCVT
correction of characteristics
I-PSO algorithm
parameter match
residual film recovery machine
DEM
virtual simulation
hydro-mechanical continuously variable transmission
tractor
optimization design
simulation experiments
I-GA
geometric principle
plough
ploughshares
durability calculation method
agricultural machine
wear
plasma-hardening surface
simulation
quality improvement
improved genetic algorithm
full-factorial test
single evaluation index modeling method
control strategy
soil cover
discrete element
soil-covering thickness
seed offset
rice combine harvester
throwing device
wind blades
fluid analysis
deflector optimization
throwing width
cotton recovery device
EDEM
parameters optimization
MBD
coupled simulation
seeding
soybean
seed–soil
corn seed
collision restitution coefficient
residual film recovery device
response surface regression model
seedbed clearing and shaping
stone removal rate
seeding furrow
dry direct-seeded rice
discrete element modeling
dual vs. single tyres
rut depth
soil bearing capacity
soil displacement
tractive efficiency
tyre size and inflation pressure
Kmeans
DBSCAN
GMM
tilling depth
well-cellar cavitating mechanism
MBD-DEM bidirectional coupling model
optimal design
cavitating law
flat disc
analytical force prediction model
discrete element method (DEM)
soil-tool interaction
disc seeder
disc blade
force prediction
semi-analytical model
sandy soil
stubble management
no-till sowing
stalk cutting
post-harvest
prototype
multi-body dynamics (MBD)
DEM-MBD coupling
topsoil burial
tillage
traction
compaction
neural networks
support vector regression
fuzzy inference system
adaptive neuro-fuzzy inference system
calibration
DEM contact models
soil dynamics
soil failure
soil forces
cohesive and frictional soils
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
url ONIX_20230511_9783036572949_77