Computers and Electronics in Agriculture 80 (2012) 41–49

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Computers and Electronics in Agriculture

journal homepage: www.elsevier .com/locate /compag

Review

Automatic GPS-based intra-row weed knife control system for transplantedrow crops

M. Pérez-Ruiz a, D.C. Slaughter b,⇑, C.J. Gliever b, S.K. Upadhyaya b

a Universidad de Sevilla, Área de Ingeniería Agroforestal, Dpto. de Ingeniería Aeroespacial y Mecánica de Fluidos, Spainb University of California, Davis, Department of Biological and Agricultural Engineering, United States

a r t i c l e i n f o a b s t r a c t

Article history:Received 26 April 2011Received in revised form 26 September 2011Accepted 10 October 2011

Keywords:Intra-row weed controlAutomationPrecision agricultureRTK-GPS

0168-1699/$ - see front matter � 2011 Elsevier B.V. Adoi:10.1016/j.compag.2011.10.006

⇑ Corresponding author. Address: University ofBiological and Agricultural Engineering, One ShieldUnited States. Tel.: +1 530 752 0102; fax: +1 530 752

E-mail address: dcslaughter@ucdavis.edu (D.C. Sla

Automated, non-chemical, intra-row weed control techniques for commercial crop production systemsare an important and challenging task in industrialized countries. This study describes a fully automaticintra-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 tocontrol 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 tomatogeoposition mapping during transplanting. Trials in a Californian processing tomato field demonstratedthat the intra-row weed knives successfully circumvented all 682 tomato plants in the study with no cropfatalities in trials conduced at continuous forward travel speeds of 0.8 and 1.6 km/h. Field trial resultsshowed that the GPS-based control system had a mean error of 0.8 cm in centering the actual uncultivatedclose-to-crop zone about the tomato main stems with standard deviations of 1.75 and 3.28 cm when trav-elling at speeds of 0.8 and 1.6 km/h, respectively. Maintenance of the size of the operator’s selected close-to-crop zone size was within ±0.5 cm of the target size on average with a standard deviation of 0.94 cm at0.8 km/h and 1.39 cm at 1.6 km/h. These results demonstrate the feasibility of using RTK-GPS to automat-ically control a the path of mechanical weed knives operating in the intra-row zone between crop plantsfor automatic mechanical intra-row weed control in sustainable row crop production systems.

� 2011 Elsevier B.V. All rights reserved.

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412. Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

2.1. Intra-row knife weeder design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432.2. Global positioning system (GPS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 442.3. Real-time control system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 452.4. Field experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 452.5. Data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

3. Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

1. Introduction

Mechatronic weed control, specifically the development of anautomatic machine for the non-chemical control of weed plants

ll rights reserved.

California, Department ofs Avenue, Davis, CA 95616,2640.

ughter).

intra-row (within the crop row), remains one of the biggest chal-lenges to agricultural row crop production in industrialized coun-tries today. Intra-row weeds are more difficult to eliminate thaninter-row weeds due to their proximity to the crop or seed line.There continues to be an ever increasing interest in the use ofmechanical intra-row weeding machines because of the high costand declining availability of manual labor, concerns over environ-mental degradation associated with pesticides and an increasing

Fig. 1. Illustration showing the three weeding zones: A = inter-row (blue border with gray diagonal hatching), B = intra-row (purple dashes with + symbols), and C = close-to-crop (black circles) and the ideal path of the intra-row weed knives (red triangles). On the left side of the figure, the intra-row weed knives are shown in the closed positionwhere they touch each other, and they kill all plants in zone B, which was 14 cm wide in this design. In the center of the figure, the intra-row weed knives are shown in theopen position, leaving the 6.4 cm gap in zone B uncultivated in order to bypass the tomato plant. (For interpretation of the references to colour in this figure legend, the readeris referred to the web version of this article.)

42 M. Pérez-Ruiz et al. / Computers and Electronics in Agriculture 80 (2012) 41–49

demand for organically produced food (Åstrand and Baerveldt,2002; Kurstjens, 2007; Dedousis et al., 2007; Tillett et al., 2008;Nørremark et al., 2008).

In geospatial relationship to the crop plants, three weedingzones have been identified: inter-row, intra-row and close-to-crop,Fig. 1 (Griepentrog et al., 2003). Nowadays, mechanical weed con-trol is mainly used and associated with traditional inter-row culti-vation. While intra-row hand weeding can be reduced bynarrowing the uncultivated band about the seedline through theuse of precision inter-row cultivation (Fennimore et al., 2010),most weeds growing in the intra-row region are uncontrolled byinter-row cultivation as are the highly competitive weeds in theclose-to-crop zone (Tillett et al., 2002; Melander, 1997). Thus in-creased research effort is being focused into the development of in-tra-row weeding systems to remove or destroy the weeds withinthe row without causing excessive crop damage (Åstrand and Bae-rveldt, 2002; Bak and Jakobsen, 2004; Blasco et al., 2002; Van Evertet al., 2006; Gobor and Schulze, 2007; Tillett et al., 2008).

Advanced technologies for intra-row weed control have poten-tial for integration and implementation into intelligent systems forarable weed control management strategies. However, finding anoverall solution for effective and selective weed control, thusreducing the need for hand weeding, minimizing negative environ-mental impacts, and increasing economic returns, is not an effort-less task, remains great challenges in the mechanization of cropprotection. It is critical to maintain a weed-free zone around vege-table crops so the crops do not have to compete with the weeds forwater and nutrients.

A major advantage of RTK-GPS mapping technology over ma-chine vision-based methods is that accuracy and precision areindependent of the visual appearance of the crop, shadows, miss-ing plants, weed density or other conditions that degrade the per-formance of machine vision or other plant sensing systems. Inaddition, no crop specific knowledge, such as visual texture, biolog-ical morphology, or spectral reflectance characteristics, is requiredfor operation, simplifying the transition from one crop to another.RTK-GPS auto-guidance based systems can be used to cultivate orspray very close to the plant crop row (about 5 cm) at very highground speeds (up to 11 km/h) and chisel or subsoil a field veryclose to buried drip irrigation tapes without damaging them(Abidine et al., 2004). Pérez-Ruiz et al. (2010) reported that preci-sion transplanter and drill seeder positioning (<0.04 m below) arepossible only with RTK-GPS auto-guidance based systems andobserved that the use of RTK-GPS auto-steering can result in signif-icant cost savings for vegetable producers.

Several researchers have been working to develop automaticsystems to detect separated (i.e., non-occluded) plants from the

background scene and to determine different weed species foroptimizing and simplifying agricultural work, or for creating weedmaps (Pedersen, 2001; Søgaard, 2005; Persson and Åstrand, 2008;Christensen et al., 2009; Staab et al., 2009; López-Granados, 2011).Machine vision-based guidance and weed detection systems havebeen developed mainly to make more effective use of pesticides,either for band spraying along a crop row or detecting individualweed or crop plants for treatment (Thompson et al., 1991; Mar-chant et al., 1997; Kouwenhoven, 1997; Tian et al., 1997; Millerand Paice, 1998; Tillett et al., 1998; Fennimore et al., 2010).

A geospatial crop seed or plant map may be a good alternativeto real-time weed sensing for use in removing intra-row weeds(Griepentrog et al., 2003, 2005). Ehsani et al. (2004) retrofitted afour-row vacuum planter with a centimeter-accuracy RTK-GPSsystem and mapped corn seeds during planting. The seed mapcoordinates obtained were within an average distance of 3.4 cmof the crop plants after germination. Sun et al. (2010) developedand evaluated a centimeter-level accuracy transplant mapping sys-tem for precision geospatial mapping of vegetable crops. Theirrow-crop transplanter, modified for RTK-GPS mapping, had a map-ping accuracy of 2 cm on average, with 95% of crop plants mappedwithin a distance of 5.1 cm from their true location. Recently, a sys-tem for geospatial mapping of crop plants using a RTK-GPS auto-matic guidance system mounted on the tractor without a secondGPS system on the planter has been developed, greatly reducingthe total equipment cost of the system with only a �1 cm accuracypenalty (Pérez-Ruiz et al., 2011 reported a mean accuracy of 3.2 cmcompared to the 2 cm accuracy reported by Sun et al., 2010).

Many investigations have attempted to develop mechanical in-tra-row weeding systems with varied levels of success. Thesemethods can be characterized by the level of technology utilized.Low-tech implements are based on some type of physical propertydifferences between crop and weed that can be exploited for weedcontrol, similar in concept to a selective herbicide or the use offlame weeding in cotton, but based upon mechanical methods.The success of their performance is highly dependent on the cropvs. weed selectivity of the physical factor exploited (Van der Weideet al., 2008). For example, finger weeders place small metal tinesinto the soil at a shallow depth close to the crop plant and relyon the crop plant having a stronger attachment to the soil thanthe weeds due to a greater crop planting depth or a larger root sys-tem because the crop plants are older than the weeds. For directseeded crops, the dependence on the weeds being younger orweaker than the crop plants causes the performance of these sys-tems to be erratic in commercial production systems. High-techtools are equipped with electronic systems for row centering orweed detection. For instance: Nørremark et al. (2008) developed

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a complex weed control system that required three GPS missionplanning files, one each for the tractor, the side-shifting cultivationsled, and the third for the rotating cycloid hoe mechanism. The cy-cloid hoe consisted of a complex linkage designed to guide eight,sigmoidally shaped soil tillage tines along a non-linear cycloidlooping pattern in the soil designed so that the looped path drovethe soil tines into the intra-row zone to kill weeds between cropplants. Additional mechanical latching linkages were used to alterthe cycloid path of individual tines in order to avoid killing cropplants along the row. The system was evaluated in a simulatedcrop row using 102 plastic sticks as artificial crop plants hand-placed 0.2 m apart along a 21 m single row where a ruler was usedto determine the stick placement between the statically deter-mined geo-referenced endpoints. The mean distance and 95% con-fidence interval about the mean between the tine and the plasticsticks ranged from 47 mm ± 37 mm to 80 mm ± 42 mm in simu-lated planting and weeding trials. Tillett et al. (2008) constructedan experimental implement based on a vision-guided inter-rowsteerage hoe system with two rotary disc cultivators. The rotatinghoe blade system had a fixed section cut out from each disc toavoid crop damage. The computer vision system was used to locatethe crop plants along the row and attempted to match the phase ofthe rotating hoe to the crop spacing in order to kill intra-rowweeds and spare crop plants. Like the complex control system de-signed by Nørremark et al. (2008), this design also required a com-plex feedback control system for accurate hoe positioning.

Some work has been done on autonomous vehicles with real-time robotic weed control systems that navigate through the field,detect, and remove any weeds found (Åstrand and Baerveldt, 2002;Jørgensen et al., 2007; Nørremark et al., 2008; Van Evert et al.,2011). These researchers believe that challenges for robotic weedcontrol are related to: (i) the diversity of the commercial agricul-tural environment, where differences in weed species and abun-dance leads to erratic performance in weed detection, (ii)automation and control technology that must respond to changesin terrain levels or static and dynamic obstacles, and (iii) safetyin the interaction with both the environment and field workers,e.g. autonomous systems must know when to stop in anemergency.

The aim of this work was to investigate the performance of anautomated, intra-row weed knife path control system, where thereal-time control input was based on an RTK-GPS geoposition sys-tem, an odometry sensor, and an automatically generated GPS mapcontaining the individual geoposition of the crop plants. The spe-cific objectives were (i) to develop a mechanical intra-row weedknife system suitable for RTK-GPS control based upon a crop plant

Fig. 2. Weed knife system for row crops. (a) Side perspective view showing the inter-rowintra-row knives (red) in the closed position about 2.5 cm below the soil surface. (b) Topweeds in the central 14 cm seedline region (called zone B in Fig. 1). (c) Top view shouncultivated gap to allow crop plants to pass unharmed. (For interpretation of the referearticle.)

map, (ii) to develop a real-time control system designed to pre-cisely control the path of weed knives operating in the intra-rowzone so that they automatically circumvent the crop plants with-out damage, and (iii) assess the performance of the automatedweed knife path control system under standard field conditionsin California.

2. Materials and methods

2.1. Intra-row knife weeder design

An automatic intra-row weeding machine was designed using apair of intra-row mechanical weed knives similar in concept to thethinning knife used in the commercial vegetable crop thinnerdeveloped by Eversman (Kepner et al., 1978) but modified for pre-cision intra-row weed control and RTK-GPS actuation, Fig. 2. Eachintra-row weed knife blade (shown in red in Figs. 2 and 3) was con-structed from a 6.4 mm thick plate of hardened tool steel (modelAristocrat D-2, air hardened to Rockwell 60, Precision MarshallSteel, Washington, PA, USA) and cut into a isosceles triangularshape, with a triangle base width of 7 cm and a triangle height of3.2 cm. The two forward pointing sides of the triangular plate weresharpened to create a cutting edge. Each intra-row knife blade wasfastened to the bottom of an arm in a linkage (shown in yellow inFig. 3) with the tip of the triangular blade and the sharpened edgesfacing the forward travel direction and the blade plane held paral-lel to and approximately 2.5 cm below the soil surface as shown inFig. 2. The linkage had a single pivot point about 30.5 cm above thesoil surface which allowed the knife blades to move in a directiontransverse to the direction of travel. The intra-row blade shape wasselected to provide good cutting performance for both plant mate-rial and the Yolo clay-loam soil present on the UC Davis campusfarm (Andrade-Sanchez et al., 2008). Intra-row knife actuationwas achieved using a pair of double acting pneumatic cylinders(Model CCD15-SBP-004, Ingersoll Rand plc., Dublin, Ireland)attached between a frame on the cultivation sled and the knifelinkage arms (Fig. 2). The pneumatic cylinders had a stroke lengthof 1.3 cm (0.5 in) and a bore size of 3.8 cm (1.5 in). Knife motionwas controlled by an electronically actuated solenoid air controlvalve (Model A212SD-024-D, Ingersoll Rand plc., Dublin, Ireland)that provided air pressure (0.7 MPa) to the pneumatic cylinders.

Fig. 1 shows an illustration of the three weed control zonesrelated to precision weed control: region A is the inter-row zone,region B is the intra-row zone, and region C is the close-to-cropzone. The intra-row weed knives where positioned directly behind

cultivation disks (gray) and sweep knives (gray), the soil surface (yellow), and theview showing the intra-row knives (red triangles) in the closed position, killing anywing the intra-row knives (red triangles) in the open position, creating a 6.4 cmnces to colour in this figure legend, the reader is referred to the web version of this

Fig. 3. UC Davis intra-row weed knife system for row crops. (a) Front view photo of the intra-row weed knife system in the closed position with knife tips touching. (b) Close-up of the triangular intra-row weed knives (red) from (a). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of thisarticle.)

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an inter-row close cultivation implement (Tonsfeldt, 1972) asshown in Fig. 2. The inter-row implement consisted of a pair of30.5 cm diameter concave cultivation disks, and a pair of15.25 cm wide sweep-style cultivation knives, both shown in grayin Fig. 2 and used to kill weeds in region A in Fig. 1. The tillagedepth of the sweep knives, and the intra-row knives were bothset to be 2.5 cm below the soil surface, following standard industrypractice, and was controlled by a set of mechanical guide wheelsmounted on the cultivation sled. The cutting paths of the two diskswere positioned 14 cm apart and centered about the seedline. Fol-lowing standard industry practice, the disks were used to cut anycrust at the soil surface and allow smooth passage of the sweepknives with less soil disruption in region B.

The intra-row weed knives had two operating positions. The po-sition shown in Figs. 2b and 3b, where the inside tips of the red tri-angular blades touched each other, was defined to be the ‘‘closed’’position. With the intra-row knives in the closed position, all plantmaterial in the central 44.5 cm area of regions A and B of the croprow was killed, either by the inter-row cultivation implement (kill-ing plants in region A) or by the intra-row weed knives (killingplants in region B). Additional intra-row mechanical weeding tools(not shown) used in standard inter-row cultivation killed all weedsin the furrows and along the edges of the planting beds. The secondoperating position was defined to be the ‘‘open’’ position, shown inFig. 2c. By actuating the pneumatic valve, each linkage arm and theassociated intra-row knife blade was positioned away from theseedline and toward the two sweep knives, creating a knife-freeuncultivated central region 6.4 cm wide centered about the seed-line. With the intra-row knives in the open position, any plantsgrowing within the central 6.4 cm wide region were not killed,while all plants growing outside the central 6.4 cm region wouldbe killed.

During cultivation, as the intra-row knives approached eachclose-to-crop zone C, the knives were propelled apart to the openposition that prevented damage to the crop plant. Once past thecrop plant’s stem, the knives were returned to the closed positionto continue intra-row weed control. Because on/off control wasused, the intra-row knives follow the purple dashed line pathrather than the ideal circular boundary of zone C shown in Fig. 1.In this study two geospatial locations, called Open and Close, weredefined for each crop plant in the map. The Open Location for acrop plant was the longitudinal point along the row centerlineand before reaching the crop plant where opening was initiated.The Open Distance was defined as the distance between the Openlocation and the point where the crop plant’s main stem pene-trated the soil surface. Ideally the Open Distance would be the

radius of the close-to-crop circle C shown in Fig. 1. The operationof this mechanical intra-row weed knife system was much simplerand had fewer moving parts than the mechanically complex cy-cloid hoe used by Nørremark et al. (2008), and the on/off pneu-matic power control algorithm required for precision intra-rowweed control was much simpler than the elaborate control algo-rithm based on two-dimensional wavelets required by either theNørremark et al. (2008) or Tillett et al. (2008) systems.

Precision implement guidance was required in this system inorder to ensure reliable centering of the intra-row knives aboutthe crop stem when in the open position. The 6.4 cm intra-rowknife tip clearance, shown in Fig. 2c, was selected as a compromisebetween a short lateral knife repositioning time when switchingfrom the closed to open position, and the ability to precisely con-trol the lateral position of the knife system along the crop rowusing the RTK-GPS automatic guidance system mounted on thetractor. RTK-GPS guidance was selected because it was built-intothe tractor, eliminated driver error and reduced the error in lateralpositioning to less than 2.5 cm, typically (Heraud and Lange, 2009).

2.2. Global positioning system (GPS)

A real-time kinematics global positioning system (RTK-GPS)mounted on the cultivation sled was used as an input to the in-tra-row weed knife path control system. The RTK-GPS system usedwas similar to that described in Sun et al. (2010) and consisted of arover RTK-GPS (model MS750, Trimble Navigation Ltd., Sunnyvale,CA, USA) with the GPS antenna mounted 3 m above soil surface tomaximize access to high quality satellite geometries and minimizeGPS multipath error. A dual axis inclinometer (Accustar II/DAS 20Schaevitz Sensors) was mounted below the GPS antenna to provideground level offset correction of GPS data due to tilting of the cul-tivation sled. The GPS rover communicated with a local GPS basestation (model 4700, Trimble) to acquire the GPS correction signalrequired for RTK Fixed quality (�1 cm level accuracy) locationinformation (Bossler, 2010). A GPS clock reference pulse (calledPPS for pulse per second), was produced by the GPS receiver forprecise synchronization of the RTK Fixed quality geoposition datawith weed knife actuation events. The GPS was programmed tooutput the geoposition data in the National Marine ElectronicsAssociation (NEMA) format ‘‘NMEA-0183 PTNL, PJK’’ as an ASCIItext string containing the UTM coordinates (Easting and Northing)at 1 Hz via an RS-232 serial connection. GPS location was aug-mented with ground-wheel odometry using an incremental opticalshaft encoder (model 0622 Grayhill, Inc., IL, USA) interfaced to anunpowered ground wheel to provide a resolution of 0.6 mm in

M. Pérez-Ruiz et al. / Computers and Electronics in Agriculture 80 (2012) 41–49 45

the direction of travel. Both the 1 Hz GPS geoposition data streamand the 0.6 mm resolution odometry data pulse stream were inputto the real-time control system described below.

2.3. Real-time control system

A ruggedized, real-time, embedded controller (cRIO-9004, Na-tional Instruments, Austin, TX, USA) was used for weed knife pathcontrol. The controller was interfaced to a field programmable gatearray (FPGA; cRIO-9104, National Instruments, Austin, TX, USA)with 3 million reconfigurable logic gates. Sensor data input andcontrol signal output was interfacted to the FPGA using off-the-shelf input/output modules (NI 9201, NI 9411, NI 9403 and NI9870, National Instruments, Austin, TX, USA) designed for analogvoltage measurement, high-speed pulse detection/counting, TTLdigital and RS-232 serial data were utilized for tilt, odometry, sole-noid control, and GPS data transfer, respectively. All software forthe embedded controller was written in LabVIEW™ (NationalInstruments, Austin, TX, USA). At run time, the graphical LabVIEWcode was automatically translated into text-based VHDL code,which was then compiled into a hardware circuit realization andused to reconfigure the FPGA logic for real-time operation.

An automatic, real-time, open loop, position control system wasdeveloped for intra-row weed knife path control. A flowchart of thesoftware kernel of the main loop of the control algorithm is shownin Fig. 4. All events in this control algorithm were controlled by tra-vel distance. Due to the asynchronous nature of intra-row knifeactuation events and the 1 Hz data rate of the GPS position infor-mation, all real-time events were based upon the 0.6 mm/pulsedata stream coming from the ground-wheel odometry system.The odometry signal was interfaced to a hardware pulse counterin the FPGA, and the current position could be accessed in real-time by examining the current cumulative odometry pulse count.A separate parallel task in the FPGA continually updated (at the1 Hz GPS data rate) the conversion constant to convert between

Fig. 4. Primary kernel of the real-time GPS-based automatic control loop for theintra-row weed knife path.

meters travelled and odometry pulse counts. In addition, this taskalso continually updated an estimate of the forward velocity of theintra-row weed knives.

The basic operation of the intra-row knife control system shownin Fig. 4 was to read the GPS coordinates of the next crop plant andthen at the time of the PPS, calculate the Euclidian distance in me-ters between the current knife position and the upcoming B to Czone boundary for the next plant. That distance was then con-verted into a knife open event scheduled to occur at the odometrycount equivalent to the distance in meters. A similar calculationwas done for the knife close event scheduled to occur when theknives reached the C to B zone boundary after the knives bypassedthe crop stem. The FPGA would monitor, in real-time, the travelleddistance and execute the appropriate knife path events (open orclose) at the appropriate location. Once the intra-row knife systemmoved into the next B zone, then a new crop plant location wasread from the GPS map of plant locations and the process repeated.

In practice, knife actuation events are not instantaneous andthere was a time delay due to a number of sources including airvalve opening time, air cylinder pressurization, and the change inknife momentum due to inertia and friction. To estimate the open-ing and closing times and to assess the weed cutting performance ofthe intra-row weed knives, a preliminary field test was conductedon the UC Davis campus farm. No herbicides were applied in anyof the test plots used in this study; otherwise all industry standardcultural practices were utilized including preparatory soil tillageand raised-bed shaping tasks. The predominant weed species inall test plots for this study were red-root pigweed (Amaranthusretroflexus), purselane (Portulaca oleracea) and black nightshade(Solanum nigrum). The field contained a small amount of commonlambsquarter (Chenopodium album) and no grass-type weeds werepresent. The knife blades were placed at the industry standarddepth, 2.5 cm below the soil, during the test. The preliminary testwas conducted at 1.6 km/h in a field with Yolo clay–loam soil(�30% sand, 50% silt, and 20% clay). A digital video camera (modelDCR-HC96, Sony Corporation, Japan) was mounted directly abovethe intra-row weed knives to record the timing and motion of thesupport arms during open and close events.

Preliminary results showed that all weeds present in zone Bwere cut by the intra-row knives when in the closed positionshowing that the intra-row knife blade design was effective in con-trolling the three predominant weed species present in the trial.The time delay for switching from the closed to open position orvisa versa was consistently less than 16.7 ms. In a second test,the knife blades were raised slightly above the soil surface so thatthe real-time knife blade position relative to the plant stem couldbe accurately recorded. No noticeable change in knife opening orclosing velocity was observed. These results show that the frictionand shear forces associated with the motion of the knife blades inthe Yolo loam soil did not visually affect the knife opening andclosing times. This was not surprising given the industry standardpractice for using freshly tilled, raised planting beds to eliminatesoil compaction at planting in order to promote good root develop-ment in crop plants. Thus all future tests to assess the accuracy ofthe GPS weed knife control system were conducted with the knifeblades slightly above the soil surface in order to provide reliablemeasurement information about the error in the location of theknife relative to the crop plant stem.

2.4. Field experiments

Field tests were conducted at the Western Center for Agricul-tural Equipment (WCAE), on the University of California, Daviscampus (Latitude: 38.53894946 N, Longitude: 121.7751468 W)using processing tomato transplants as the target row crop. In thisstudy, four rows were planted (single crop row/bed, 1.5 m bed

46 M. Pérez-Ruiz et al. / Computers and Electronics in Agriculture 80 (2012) 41–49

spacing, and 43 cm crop plant spacing) with the GPS mappingtransplanter described by Sun et al. (2010). The field layout wassuch that the rows were predominantly in the North–South direc-tion. All the rows were planted in raised beds at a constant travelspeed of 1.6 km/h. All conventional seedbed preparation opera-tions, planting and automatic intra-row weeding trials were con-ducted with a tractor steered by RTK-GPS autoguidance using acommon set of GPS AB line coordinates for all tillage, plantingand cultivation operations.

The field trials were carried out at two nominal travel speeds of1.6 km/h and 0.8 km/h. The sizes of the target close-to-crop zone Cdiameter set by the operator for the two speeds were 15.24 cm, and7.62 cm, respectively. The nominal forward travel speed was set inthe autoguidance tractor and was kept constant during driving. Theblades of the intra-row weed knives were held slightly above thesoil surface, to provide a clear view of the knife blade position atall times, minimize any dust creation which might obscure theview, and so that both speed trials could be conducted on the sameset of 4 rows. At the start of the automatic intra-row weeding trial,the GPS crop plant localization map was uploaded into the memoryof the embedded controller. At the beginning of each row, the dig-ital GPS crop plant map was accessed and searched to find the clos-est plant. The direction of heading was then determined based oncomparing the first and last plants in the map of the row containingthis plant to the current GPS location of the implement.

A digital video camera (model DCR-HC96, Sony Corporation, Ja-pan) was mounted directly above the intra-row weeding knives tocontinuously record the entire set of open and close event se-quences for each row during each intra-row weeding trial. At thebeginning of each row, a standard scale was placed on the soil sur-face to give a visual length reference for position calibration.

2.5. Data analysis

Video software (Premier, Adobe Inc., San Jose, CA) was used toview the sequence of frames captured by the video camera. Eachvideo sequence was used to determine the distance before theplant at which the knives opened and the distance after the plantat which the knives closed. The frame at the instant the knivesopened and the frame at the instant the knives closed were ex-ported into a pair of digital image files for each crop plant. The dis-tance between the knives and the plant at the time the knivesopened and the distance between the plant and the knives at thetime the knives closed were determined using image analysis soft-ware (Image J, 2009, NIMH, Bethesda, MD). Statistical inferenceanalysis of the knife event data was conducted using SAS/STAT�

software, (version 9.2, SAS Institute Inc., Cary, NC, USA.).

Table 1Accuracy and precision of intra-row weed knife position control.

Row Plants Speed Opening distance* err

Mean

1 110 1.6 1.32 78 1.6 1.1

0.8 0.6

3 110 1.6 0.30.8 0.5

4 98 1.6 1.00.8 0.8

All 396 1.6 0.9a286 0.8 0.6a

* Differences in values between the 1.6 km/h and 0.8 km/h travel speeds with the sameANOVA, or Levene’s homogeneity of variance test for the mean and standard deviation

3. Results and discussion

An automatic intra-row weed knife control system, which uti-lized a GPS crop plant map and a RTK-GPS -based real-time controlsystem to determine the geospatial position of the weed knifeblades with respect to each mapped tomato plant in the field,was successfully developed and operated in a processing tomatofield. The system successfully controlled the path of a pair of weedknives in the intra-row zone B in the center of the row and mini-mized intrusion into the close-to-crop zone C where mechanicalweed control in close proximity to the crop plant may cause rootdamage to the crop (Blackmore, 2004).

The results of the field trials, where the automatic intra-rowsystem was operated in four crop rows under two different nomi-nal forward travel speeds, are shown in Table 1. Within this study,the real-time intra-row weed knife path to circumvent a total of682 tomato plants were used to assess the performance of theknife control system: 396 for the test conducted at a forward travelspeed of 1.6 km/h and 286 at the 0.8 km/h travel speed. The videodata for row 1 at the 0.8 km/h travel speed was lost due to acciden-tal mishandling, which accounts for the difference in plant counts.The average size of the close-to-crop zone C achieved by the knifewas 15.70 cm at the travel speed of 1.6 km/h and 7.15 cm at thetravel speed of 0.8 km/h on average for the four rows, which areclose to the operator selected target sizes 15.24 cm, and 7.62 cm,respectively for the two travel speeds. Ideally this would representthe diameter of the circles labeled C in Fig. 1. However, with theon/off style solenoid valve used in this design, the knives followan approximate straight-line path (assuming constant knife open-ing and tractor velocities) represented by the purple dashed linesin Fig. 1.

The average knife opening distance errors shown in Table 1 rep-resent the performance of the system in its ability to center the cropplant inside the intended unweeded zone, represented by the purpledashed diamond-shaped regions in Fig. 1. Results from a Levene’shomogeneity of variance test (Levene, 1960) show that the standarddeviation values where significantly different (p-value < 0.0001)between forward travel speeds. Analysis of variance (ANOVA), aftervariable transformation to correct for the heteroscedascity usingPROC TRANSREG� (SAS/STAT� software, (version 9.2, SAS InstituteInc., Cary, NC, USA.), failed to show that the mean opening distanceerror values were significantly different (p-value = 0.235) betweentravel speeds. Ideally, the actual close-to-crop zone C would be cen-tered inside the true unweeded diamond-shaped zone, resulting inthe opening distance error being zero. The small (0.3–1.3 cm) butsystematic shift in knife opening distance errors shown across allrows was significantly above zero (p-value < 0.0001) and believed

or (cm) Close-to-crop zone* error (cm)

Std Mean Std

3.68 0.6 1.383.45 0.8 1.501.85 �0.4 0.95

2.94 0.5 1.281.83 �0.6 0.97

3.03 0.0 1.221.57 �0.4 0.89

3.28b 0.5d 1.39f1.75c �0.5e 0.94g

letter for a specific table column are not significantly different (p-value < 0.0001) byvalues, respectively.

M. Pérez-Ruiz et al. / Computers and Electronics in Agriculture 80 (2012) 41–49 47

to have occurred because of the use of a static odometry conversionfactor (counts/meter) applied in the calculation of the odometrycount offset value for the forward distance travelled during the knifeopening event. While a dynamic value, updated at 1 Hz, was used inthe odometry count to meter conversion applied each time a newplant location was extracted from the map, post-trial analysis re-vealed that accidental oversight resulted in the use of a constant va-lue for the conversion of the knife opening time delay into forwarddistance travelled. Changes in the deformation of the odometer’spneumatic tire, the relative motion between this wheel and the soil(i.e., slip), the compressibility of the soil from row to row due to mul-tiple passes over the same row, and differences in soil moisture canall lead to changes in the conversion factor for odometry counts permeter. The �0.8 cm overall mean shift was smaller than the 1.9 cmsystematic shift in sugar beet plant RTK-GPS position localization er-ror reported by Søgaard and Nørremark (2004) when an autono-mous robot attempted to locate the crop plants based upon a GPScrop plant map. They attributed the error to be due to a small dis-placement of the framework carrying the antenna of the RTK-GPSsystem, which may have been a contributing factor in the presentstudy as well. Future designs should incorporate dynamic odometryconversion factors in order to minimize this error. Overall, the meanoffset error in centering of the unweeded zone about the tomatoplant stem was 2.5 cm, lower than the results (3–3.8 cm error) ob-tained by Ehsani et al. (2004) in RTK-GPS mapping of direct-seededcorn.

In order to achieve a circular close-to-crop zone, a more com-plex closed-loop knife position control system would be required.The weed control difference in uncultivated area between the cur-rent diamond-shaped zone and the ideal circular-shaped zone areunlikely to justify the increased complexity of the design requiredto obtain a circular unweeded area. The standard deviation for thetotal size of the close-to-crop zone at the 1.6 km/h travel speedwas 1.39 cm on average or about 9% of the mean and 0.94 cm onaverage or about 13% of the mean at 0.8 km/h. Replicate RTK-GPSmeasurements with the GPS survey system for 230 transplants, ta-ken on five different dates, provided a benchmark Easting standarddeviation of 1.06 cm and a Northing standard deviation of 1.40 cm.Nørremark et al. (2003) reported a 24-h RTK-GPS static trial RMSerror of 0.95 cm. The standard deviations for the size of theclose-to-crop zone left by the automatic weed knife were compara-ble to that of the benchmark RTK-GPS survey measurements error.These results show that the precision of the system in maintaininga consistent close-to-crop zone size was reasonable given the 1 HzGPS update rate used on a travelling platform, where, unlike sur-veying applications, time averaging of GPS measurements is notfeasible. In this design, the size of the close to crop zone wasmainly a function of the precision of the ground-wheel odometrysystem since the GPS geoposition data was only used to initiatethe knife opening event. The closing event was dictated by odom-etry. The precision of the ground wheel-driven odometry systemobserved in this study was consistent with the precision observed

Fig. 5. Histograms showing the distributions of the knife opening distance and the size ospeed.

by Lee et al. (1999) for odometry in a precision spray applicationthat was similar in scale and was also conducted in a processing to-mato field.

Fig. 5 shows the histograms of the knife opening distance andthe size of the close-to-crop zone for the 0.8 km/h travel speed. Atheoretical Normal distribution based on the observed mean andstandard deviation has been overlaid on the histograms. As ob-served by Nørremark et al. (2008), the distribution of the knifeopening distance produced by this system did not show significantevidence of non-Normality (p-value = 0.35 by the Anderson–Dar-ling test). The distributions of the knife opening distance and thesize of the close-to-crop zone for the 1.6 km/h travel speed wheresimilar in shape to those in Fig 5. Likewise the distribution of theknife opening distance at 1.6 km/h did not show significant evi-dence of non-normality (p-value = 0.53 by the Anderson–Darlingtest). The distribution of values shown in Fig. 5a are similar tothe distribution (�7 cm range) in position error reported bySøgaard and Nørremark (2004) when an autonomous robotstopped to photograph each crop plant in the GPS crop plantmap. The increased variation with increased travel speed shownin Table 1 was believed to be principally due to the larger distancestravelled between GPS update events at 1.6 km/h and the associ-ated increase in distance projection by odometry required to deter-mine knife actuation positions. Overall, the precision of the knifeopening distance for both speeds was generally comparable tothe double RTK-GPS benchmark measurement error. It is importantto remember that these knife actuation control points are basedupon two GPS measurement events, the first one occurred at plant-ing, and the second at weeding. The precision of the system wassimilar in magnitude to that observed by Sun et al. (2010), andNørremark et al. (2007) in GPS transplant and seed mapping trials,confirming that the performance was consistent with the currentlevel of mobile RTK-GPS system accuracy.

While several studies have documented the potential for cropinjury due to the use of selective herbicides (e.g., Tickes and Kerns,1996), limited research has been done to develop the basic knowl-edge to precisely define the size of the close-to-crop zone requiredfor mechanical weed control methods. Blackmore et al. (2007) de-fined the close-to-crop zone to be the area that is within the leafand root envelope, however the economic impact of this definitionis unknown. Nørremark and Griepentrog (2004) reported that forsugar beets, the size of the close-to-crop zone changed with plantage. A 6 cm radius was required in sugar beet from the cotyledon to8-leaf stage to avoid uprooting of crop plants, while older plantswere more tolerant to mechanical stress within that zone. Fenni-more et al. (2010) noted that, in addition to crop characteristics,the ability to mechanically cultivate in close proximity to cropplants also depends on soil conditions, where cloddy soil generallyincreases the required size of the close-to-crop zone. Nørremarket al. (2008) used a 10 mm radius for the target close-to-crop zonesize when evaluating their GPS-based system for intra-rowmechanical weed control, although no justification for selecting

f the diamond-shaped close-to-crop zone for intra-row knife at the 0.8 km/h travel

48 M. Pérez-Ruiz et al. / Computers and Electronics in Agriculture 80 (2012) 41–49

this particular size was given. They reported a 1.5% hoe intrusionrate for their intra-row cycloid hoe system. In comparison, whenusing Nørremark et al’s 10 mm close-to-crop zone radius, the sys-tem reported here had a 0.6% intrusion rate at 1.6 km/h and a 1.4%intrusion rate at 0.8 km/h, which compare quite well especiallyconsidering that Nørremark et al. used hand-placed plastic sticksin place of crop plants and their GPS map was created using a staticGPS antenna. In no case were any of the 396 tomato plants killedby the intra-row weed knives during the field trials in this study.As intra-row mechanical weed control techniques become avail-able, additional research will be needed to better understand theeconomic costs and benefits associated with specific close-to-cropzone sizes as well as the impact of crop, temporal, and environ-mental interactions.

Despite the high cost of hand hoeing, few farmers have adoptedsite-specific weed management techniques. Gerhards and Chris-tensen (2003) found that the main barrier was the balance be-tween the potential savings and the cost of weed sensingtechnology. Several studies (e.g., Christensen et al., 2009; Zwigge-laar, 1998) have noted that site-specific weed control is limitedby the restriction of several automated weed sensing technologiesto a small set of crop and weed species. A major advantage of thesystem developed in this study is that it does not require a weedsensor. Further, while many weed sensing techniques are severelychallenged by visual occlusion or by the change in plant appear-ance over time, the GPS crop plant map remains valid throughoutthe crop life cycle and is unaffected by the diversity or quantity ofweed species present in the field. This study has demonstrated thein-field feasibility of a complete GPS-based system for intra-rowweed knife control, where RTK-GPS was used in all operations fromautoguidance in seedbed preparation, to planting with on-the-flytomato transplant mapping, and then finally the utilization of theactual crop map to control the path of a pair of mechanical intra-row weed knives in real-time as they traversed the intra-row zoneand automatically circumvented the tomato plants in the row.

4. Conclusion

An automatic, intra-row, weed knife control system, which uti-lized an automatically generated GPS crop plant map to determinethe geospatial position of each tomato plant and on-board RTK-GPSfor monitoring the mobile system’s current geoposition in real-time, was successfully developed and operated in a processing to-mato field in California. The system was specifically designed toautomatically control the path of a pair of mechanical weed knifeblades in real-time as they travelled along the intra-row zoneand to circumvent the close-to-crop zones where mechanical weedcontrol in close proximity to the crop plant may damage the crop.A high-speed pneumatic actuator was used to quickly repositionthe pair of mechanical weed knives between the intra-row controlstate, to the inter-row control state in either direction in real-time.A 0.6 mm resolution, ground-wheel based odometry sensor wasused for real-time position control since the GPS data stream andthe knife path state change events were asynchronous.

In-field trials demonstrated that the knife blade design waseffective in killing three weed species: red-root pigweed (A. retro-flexus), purselane (P. oleracea) and black nightshade (S. nigrum).Video analysis showed that soil friction and shear forces did notvisibly impair knife blade actuation between the intra-row andinter-row path states. The system successfully circumvented all682 tomato plants in the study with no crop fatalities in trialsconduced at continuous forward travel speeds of 0.8 km/h and1.6 km/h. Knife path control was good, with a mean error of0.8 cm in centering the actual uncultivated close-to-crop zoneabout the tomato main stem. The knife blade path errors at the

intra-row to close-to-crop zone boundary appeared to be normallydistributed with standard deviations of 1.75 cm and 3.28 cm whentravelling at speeds of 0.8 km/h and 1.6 km/h, respectively. Mainte-nance of the size of the operator’s selected close-to-crop zone sizewas within ±0.5 cm of the target size on average with a standarddeviation of 0.94 cm at 0.8 km/h and 1.39 cm at 1.6 km/h.

These results demonstrate the feasibility of using RTK-GPS geo-position technology for automated, precision plant care tasks fromautoguidance in seedbed preparation, to planting with on-the-flytomato transplant mapping, and culmination with the control thepath of a pair of mechanical intra-row weed knives based uponthe automatically generated crop plant map. The system has anadvantage over most weed sensor-based intra-row plant care sys-tems in that species-specific knowledge is not required and visualocclusion of weeds or crop plants does not adversely impact sys-tem performance. While future study is required to evaluate thetrue economic value of this technology, expanding the use ofRTK-GPS across an increasing number of plant care tasks providesbetter utilization of the technology and distributes the per taskcapital cost.

Acknowledgements

The research was supported in part by the Specialty Crop BlockGrant program of the California Department of Food and Agricul-ture. The authors thank Burt Vannucci, Loan-anh Nguyen, GarryPearson, Jim Jackson, and Mir Shafii of UC Davis, and Claes Janssonand Tord Holmqvist at SWEMEC in Woodland, CA for technicalassistance.

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