Design and Application of Agricultural Equipment in Tillage System

Edited by
April 2023
564 pages
  • ISBN978-3-0365-7294-9 (Hardback)
  • ISBN978-3-0365-7295-6 (PDF)

This book is a reprint of the Special Issue Design and Application of Agricultural Equipment in Tillage System that was published in

Biology & Life Sciences
Environmental & Earth Sciences

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.

  • Hardback
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© 2022 by the authors; CC BY-NC-ND license
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; machine vision; 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; parameter optimization; agricultural machinery; 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; no-tillage; 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; virtual simulation; parameters optimization; agricultural machinery; DEM; MBD; coupled simulation; seeding; soybean; seed–soil; corn seed; soil; collision restitution coefficient; EDEM; residual film recovery device; EDEM; virtual simulation; response surface regression model; parameters optimization; 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; discrete element method (DEM); force prediction; semi-analytical model; sandy soil; stubble management; no-till sowing; stalk cutting; post-harvest; prototype; discrete element method (DEM); 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