Review: Automatic GPS-based intra-row weed knife control system for transplanted row crops

Automated, non-chemical, intra-row weed control techniques for commercial crop production systems are an important and challenging task in industrialized countries. This study describes a fully automatic intra-row mechanical weed knife path control system for transplanted row crops. A real-time kinematics (RTK) global positioning system (GPS) was used to automatically detect crop planting geopositions and to control the path of a pair of intra-row weed knives travelling between crop plants along row centerline. RTK-GPS was utilized for autoguidance in seedbed preparation, and with automatic on-the-fly tomato geoposition mapping during transplanting. Trials in a Californian processing tomato field demonstrated that the intra-row weed knives successfully circumvented all 682 tomato plants in the study with no crop fatalities in trials conduced at continuous forward travel speeds of 0.8 and 1.6km/h. Field trial results showed that the GPS-based control system had a mean error of 0.8cm in centering the actual uncultivated close-to-crop zone about the tomato main stems with standard deviations of 1.75 and 3.28cm when travelling at speeds of 0.8 and 1.6km/h, respectively. Maintenance of the size of the operator's selected close-to-crop zone size was within +/-0.5cm of the target size on average with a standard deviation of 0.94cm at 0.8km/h and 1.39cm at 1.6km/h. These results demonstrate the feasibility of using RTK-GPS to automatically control a the path of mechanical weed knives operating in the intra-row zone between crop plants for automatic mechanical intra-row weed control in sustainable row crop production systems.

[1]  N. D. Tillett,et al.  A Robotic System for Plant-Scale Husbandry , 1998 .

[2]  M. Nørremark,et al.  Seed Mapping of Sugar Beet , 2005, Precision Agriculture.

[3]  José Blasco,et al.  AE—Automation and Emerging Technologies: Robotic Weed Control using Machine Vision , 2002 .

[4]  H. Søgaard.  Weed Classification by Active Shape Models , 2005 .

[5]  David C. Slaughter,et al.  Hyperspectral Imaging System for Precision Weed Control in Processing Tomato , 2009 .

[6]  Thomas Bak,et al.  Agricultural Robotic Platform with Four Wheel Steering for Weed Detection , 2004 .

[7]  Claus G. Sørensen,et al.  HortiBot: A System Design of a Robotic Tool Carrier for High-tech Plant Nursing , 2007 .

[8]  Barry R. Tickes.  Lettuce Injury from Preplant and Preemergence Herbicides , 1996 .

[9]  Hans W. Griepentrog,et al.  The development and assessment of the accuracy of an autonomous GPS-based system for intra-row mechanical weed control in row crops , 2008 .

[10]  Chris Rizos,et al.  Manual of Geospatial Science and Technology , 2009 .

[11]  N. D. Tillett,et al.  Inter-row vision guidance for mechanical weed control in sugar beet , 2002 .

[12]  David C. Slaughter,et al.  RTK GPS mapping of transplanted row crops , 2010 .

[13]  Björn Åstrand,et al.  Classification of crops and weeds extracted by active shape models , 2008 .

[14]  S. Christensen,et al.  Real‐time weed detection, decision making and patch spraying in maize, sugarbeet, winter wheat and winter barley , 2003 .

[15]  Francisca López Granados.  Weed detection for site-specific weed management: Mapping and real-time approaches , 2011 .

[16]  Francisca López-Granados,et al.  Weed detection for site-specific weed management: mapping and real-time approaches , 2011 .

[17]  H. Søgaard,et al.  Instrumentation and method for high accuracy geo-referencing of sugar beet plants , 2007 .

[18]  N. D. Tillett,et al.  Inter and intra-row mechanical weed control with rotating discs. , 2007 .

[19]  Morton B. Brown,et al.  Robust Tests for the Equality of Variances , 1974 .

[20]  J. Kouwenhoven,et al.  Intra-row mechanical weed control: possibilities and problems. , 1997 .

[21]  Lei Tian,et al.  MACHINE VISION IDENTIFICATION OF TOMATO SEEDLINGS FOR AUTOMATED WEED CONTROL , 1997 .

[22]  N. D. Tillett,et al.  Mechanical within-row weed control for transplanted crops using computer vision , 2008 .

[23]  N. D. Tillett,et al.  Row-following accuracy of an autonomous vision-guided agricultural vehicle , 1997 .

[24]  D. J. Hills,et al.  Autoguidance system operated at high speed causes almost no tomato damage , 2004 .

[25]  W. S. Lee,et al.  Robotic Weed Control System for Tomatoes , 2004, Precision Agriculture.

[26]  W. R. Buckland,et al.  Contributions to Probability and Statistics , 1960 .

[27]  B. Melander.  Optimization of the Adjustment of a Vertical Axis Rotary Brush Weeder for Intra-Row Weed Control in Row Crops , 1997 .

[28]  Carol Plouffe,et al.  Development and Field Evaluation of a Field-Ready Soil Compaction Profile Sensor for Real-Time Applications , 2008 .

[29]  Hans W. Griepentrog,et al.  A method for high accuracy geo-referencing of data from field operations. , 2003 .

[30]  Shrinivasa K. Upadhyaya,et al.  Seed location mapping using RTK GPS , 2004 .

[31]  Hans W. Griepentrog,et al.  A Specification for an Autonomous Crop Production Mechanization System , 2007 .

[32]  Dirk Kurstjens,et al.  Precise tillage systems for enhanced non-chemical weed management , 2007 .

[33]  Reyer Zwiggelaar,et al.  A review of spectral properties of plants and their potential use for crop/weed discrimination in row-crops , 1998 .

[34]  Esmaeil S. Nadimi,et al.  Site‐specific weed control technologies , 2009 .

[35]  Hans W. Griepentrog,et al.  Individual plant care in cropping systems , 2003 .

[36]  G. Polder,et al.  A Mobile Field Robot with Vision-Based Detection of Volunteer Potato Plants in a Corn Crop1 , 2006, Weed Technology.

[37]  Steven A. Fennimore,et al.  Evaluation and Economics of a Machine-Vision Guided Cultivation Program in Broccoli and Lettuce , 2010, Weed Technology.

[38]  R. Y. van der Weide,et al.  Innovation in mechanical weed control in crop rows , 2008 .

[39]  M. Pérez-Ruiz,et al.  Assessing GNSS correction signals for assisted guidance systems in agricultural vehicles , 2010, Precision Agriculture.

[40]  Gerrit Polder,et al.  A robot to detect and control broad‐leaved dock (Rumex obtusifolius L.) in grassland , 2011, J. Field Robotics.

[41]  J. V. Stafford,et al.  Potential for automatic weed detection and selective herbicide application , 1991 .

[42]  Albert-Jan Baerveldt,et al.  An Agricultural Mobile Robot with Vision-Based Perception for Mechanical Weed Control , 2002, Auton. Robots.