USPTO Patent for an Ag Robot to process soil

USO10900877B1
(12) United States Patent
Pandey et al.
(10) Patent No.: US 10,900,877 B1
(45) Date of Patent: Jan. 26, 2021
(54) METHODS, APPARATUS, AND SYSTEMS TO
EXTRACT AND QUANTIFY MINUTE
OBJECTS FROM SOIL OR FECES,
INCLUDING PLANT-PARASITIC
NEMATODE PESTS AND THEIR EGGS IN
SOIL
(58) Field of Classification Search
CPC ...... GOIN 1/40; GOIN 35/0099; GOIN 35/02;
GOIN 35/00871 ; GOIN 1/286; GOIN
1/34;
(Continued)
(56) References Cited
(71) Applicant: Iowa State University Research
Foundation, Inc., Ames, IA (US) U.S. PATENT DOCUMENTS
3,905,895 A
4,081,356 A
9/1975 Addis
3/1978 Zierdt
(Continued)
FOREIGN PATENT DOCUMENTS
(72) Inventors: Santosh Pandey, Ames, IA (US);
Augustine Beeman, Ames, IA (US);
Leland E. Harker, Ames, IA (US);
Jared P. Jensen, Ames, IA (US);
Upender Kalwa, Ames, IA (US);
Taejoon Kong, Ames, IA (US); Zach
L. Njus, Ames, IA (US); Gregory L.
Tylka, Ames, IA (US); Christopher M.
Legner, Ames, IA (US)
CN 203735291 U 7/2014
OTHER PUBLICATIONS
(73) Assignee: Iowa State University Research
Foundation, Inc., Ames, IA (US)
Zayas, I. Y., and Paul W. Flinn. “ Detection of insects in bulkwheat
samples with machine vision.” Transactions of the ASAE 41.3
(1998): 883. (Year: 1998).*
(Continued)
( * ) Notice: Subject to any disclaimer, the term ofthis
patent is extended or adjusted under 35
U.S.C. 154(b) by 240 days.
Primary Examiner Amandeep Saini
(74) Attorney, Agent, or Firm — McKee, Voorhees &
Sease, PLC
(21) Appl. No.: 15 /914,735
(22) Filed: Mar. 7, 2018
(60)
Related U.S. Application Data
Provisional application No. 62/468,760, filed on Mar.
8, 2017.
(51) Int. Cl.
GOIN 1/28
GOIN 1/40
(2006.01)
(2006.01)
(Continued)
(57) ABSTRACT
A system , method, and apparatus for quantification of pre
determined particles in a soil or feces sample with certain
automated steps. In one aspect it includes aninput station for
inputting a soil or feces sample; a sieving/filtering station for
separating soil or feces from particles or particle carriers,
and/or separating particle carriers from particles; and a
collection station forreceiving the extractedparticles. It can
include quantification ofthe collected sample with an imag
ing stationto digitally image theparticles andrecognize and
counttheparticles collected.Amechanism canmechanically
move the filtered particles from the sieve/filter station to the
collection station. A controller can be programmed to auto
matically control at least certain functions of the mecha
nism. An optional feature includes acquisition of chemical,
(Continued)
(52) U.S. CI.
??? GOIN 1/40 (2013.01); GOIN 1/286
(2013.01); GOIN 1/34 (2013.01); GOIN
35/0099 (2013.01);
(Continued )
INPUT- 21 EXTRACTION - 22 COLLECTION USE
QUANTIFICATION
24
PLOKAL, PREPREPARED
SOX, SAMPLES
OS EXTRACTION OFTEMS OF
INTEREST FROM SAMOLE
MUO-STEP
S @VING
CONVEYOTE
COLLECTION OF TEMS OF
INTEPESTOR SUS $ 71
WASTE POSITIONER
QUANTIFICATION OF ITEMS OF
TEROSTOR SUKSET
IVACING
RECOGN::ON
FURTHER USE

US 10,900,877 B1
Page 2
biological, physical, or other parameters ofthe sample with
oneormore sensorspositionedorpositionableatthe sample.
25 Claims, 47 Drawing Sheets
(9 of 47 Drawing Sheet(s) Filed in Color)
5,526,705 A
6,202,829 B1
6,331,438 B1
7,123,750 B2
7,788,970 B2
7,830,504 B2
9,110,240 B2
2004/0005714 Al
2012/0202715 A1 *
6/1996 Skotnikov et al.
3/2001 Van Dyke, Jr. et al.
12/2001 Aylott et al.
10/2006 Lu et al.
9/2010 Hitt et al.
11/2010 Deppermann et al.
8/2015 Gill et al.
1/2004 Safar et al.
8/2012 Partida -Sanchez
BOIL 3/50255
506/23
OTHER PUBLICATIONS
(51) Int. Ci.
G06K 9/32 (2006.01)
G06T 7700 (2017.01)
GOIN 1/34 (2006.01 )
GOIN 35/00 (2006.01)
GOIN 35/02 (2006.01)
G06K 9700 (2006.01)
G05B 19/402 (2006.01)
(52) U.S. CI.
CPC GOIN 35/00871 (2013.01); GOIN 35/02
(2013.01); G05B 19/402 (2013.01); G06K
9/00134 (2013.01); G06K 9/3233 (2013.01);
GO6T 770012 (2013.01); GOIN 2001/2866
(2013.01); G05B 2219/23416 (2013.01); G06T
2207/10016 (2013.01); G06T2207/10056
(2013.01); G06T2207/30188 (2013.01); G06T
2207/30242 (2013.01 )
(58) Field of Classification Search
CPC GOIN 2001/2866; G06K 9/00134; G06K
9/3233; G05B 19/402; GO5B 2219/23416;
G06T 7/0012; G06T 2207/30188; G06T
2207/10056; GO6T 2207/30242; G06T
2207/10016
USPC 382/110
See application file for complete search history.
Syed, Farhan Abbas. Development of an automated system for
extraction and quantification ofsoybean cystnematode (SCN) eggs
and cysts. Diss. 2015. (Year: 2015).*
Winfield, A.L. et al., “ A Column Elutriator for Extracting Cyst
Nematodes and Other Small Invertebrates from Soil Samples”,
Association ofApplied Biologists, pp. 223-231. 1987.
Adamchuk, V.I. et al., “ On- The-Go Soil Sensors for Precision
Agriculture", Computers and Electronics in Agriculture, pp. 71-91.
Mar. 8, 2004.
Byrd, Jr., D. W. et al., “Two Semi-Automatic Elutriators for
Extracting Nematodes and Certain Fungi From Soil”, Journal of
Nematology, vol. 8, No. 3, pp. 206-212. Jan. 16, 1976 .
Faghihi, J. et al., “An Efficient New Device to Release Eggs From
Heterodera Glycines”, Journal ofNematology 32 (4): pp. 411-413.
2000.
Turntable Bearing Kit - VEX Robotics, https://www.vexrobotics.
com /276-1810.html, pp. 1-3, retrieved from internet on Feb. 22,
2018.
HumboldtManufacturing — ASTM Sieves, https://www.humboldtmfg.
com /sieves.html, pp. 1-2, retrieved from internet on Mar. 7, 2018.
Syed, Farhan, “Development of an Automated System for Extrac
tion and Quantification ofSoybean CystNematode (SCN) Eggs and
Cysts”, Grad Student Thesis, pp. 1-86. 2015.
Gerdemann, J. W., “Relation of a Large Soil-Borne Spore to
Phycomycetous Mycorrhizal Infections”, Mycological Society of
America, vol. 47, No. 5, pp. 619-632. 1955.
CN2037352910, English machine translation of part of China
patent publication, 1 page, published on Jul. 30, 2014.
Soil Sensor Types and Technologies, http://soilsensor.com/soil
sensor-types, pp. 1-6, retrieved from internet on Mar. 8, 2018.
(56) References Cited
U.S. PATENT DOCUMENTS
5,063,026 A
5,222,605 A *
11/1991 Wong
6/1993 Pogue B07B 1/38
209/239 * cited by examiner

U.S. Patent Jan. 26, 2021 Sheet 1 of 47 US 10,900,877 B1
12
female
teses
G azad temale)
Peluale
adult
juveniles Swollen juvenile

U.S. Patent
(
a
)
Mason
City
(
NC
) Arkgton
(
NB
)
Jan. 26, 2021
(
MS
)
uogoury
pypes
Sheet 2 of 47
10
US 10,900,877 B1
FIG
.
1B

INPUT
21
EXTRACTION
22
TIFICA
23
24
25
PLURALPREPREPAREDSOIL
SAMPLES
U.S. Patent
27
EXTRACTION
OF
ITEMS
OF
MULTI
-
STEP SIEVING
CONVEYOR
Jan. 26, 2021
COLLECTION
OF
ITEMS
OFINTEREST
(
OR
SUBSET
)
WASTE
ROBOTICPOSITIONER
Sheet 3 of 47
QUANTIFICATIONOFITEMSOFINTEREST
(
OR
SUBSET
)
RECOGNITION
US 10,900,877 B1
FURTHER
USE
FIG
.
2A

26
80
INPUT (SAMPLES) CONTROL SYSTEM AVO
28
180/190
EXTRACTION STATION
EXTRACTION OF TEMS OF
INTEREST FROM SAMPLE
29
QUANTIFICATION STATION
QUANTIFICATION OF ITEMS OF
INTEREST (OR SUBSET)
QUTPUT OF
QUANTIFICATION (FOR
FURTHER USE)
FIG. 2B

30A
30
PREPAREPLURALSAMPLES
U.S. Patent
GRIND
?
No
VBRATE
?
No
RINSE
?
NO
-
REPOSITION
?
CONVEYSAMPLE
(
S
)
Yes
Yes
Yes
Yes
300
30E
300
30F
Jan. 26, 2021
30B
VIBRATE
RINSE
REPOSITION
SAMPLE
Yes
30G
Sheet 5 of 47
CONTINUESIEVING
?
COLLECTITEMS
OF
INTEREST
NO
30L
REPOSITIONSIEVES
CONVEY
ITEMSOF
INTEREST
COUNT
ITEMSOF
INTEREST
301
301
US 10,900,877 B1
30K
RINSE
USEDSIEVES
COMMUNICATEDQUANTIFICATION
REMOVEWASTE
FIG
.
3A

32
INPUTCONVEYORMOTOR
(
S
)
GRINDERMOTOR
VIBRATORMOTOR(
ON
/
OFF
)
GRIPPERMOTOR(
OPEN /
CLOSE
)
U.S. Patent
(
GRIND
)
PRESSURIZEDWATERSOURCE
STATE
POST MOTOR(
ROTATION
)
GRINDERMOTOR(
UP
/
DOWN
)
GRIPPERPOST
MOTOR(
UP
/
DOWN
)
WATERVAUVE
(
S
)
(
OPEN
/
CLOSE
)
Jan. 26, 2021
GRIPPERPOST
MOTOR(
ROTATION
)
GRIPPERMOTOR(
TILT
)
CONTROLLER (
AUTOMATED
-
ORDER
/
TIMING
AND
FUNCTIONS
)
STAGE
POSTMOTOR(
UP
/
DOWN
)
Sheet 6 of 47
RING
SPRAYER
BAR
CODE
READER
OUTPUTCONVEYORMOTOR
(
S
)
INTERNET
PC
IMAGERECOGNITIONSOFTWARE
TABLET
OR SMART
REMOTECOMPUTER
/
SERVER
US 10,900,877 B1
DIGITALIMAGER
PHONE
FIG
.
3B

Home
56
60
DRAIN PAN
52

40
MMT
@
98888888
0
0
0
0
0
0
0
0
0
0
0
0
0
04
60
52
wey
-
o o
OOOOOOOOOO O
OOOOOOOOOOOO
·
0
0
0
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0
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0
o
OOOOOOOOOOOO
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0
Q o Q Q
A 0 o 9 ? ?
FIG . 4B

70
80
62
?

80
60
52
56
50

53
OPEN/CLOSE
56
ROTATE
FIG . 5A

50
PRESSURIZED
80
UP/DOWN
52
LU
56
55

OPENG
OPEN/CLOSE
FIG . 5C
?GC -571
57L
58
-59
FIG. 5D

I
63
64(2)
64(1)
64 (3) 62T
a
62M
2 62B
64(4)
ROTATE
FIG. 6A

63
62 T
62 M
?
62 B
FIG. 6B

70
72
73
ROTATE
FIG . 7A

- 70
o O
UP/DOWN
72
73
FIG . 7B

FIG
.
8A

U.S. Patent
81
COMPUTERSOFTWARE COMPUTERBOARD
Jan. 26, 2021
STAGEPOST
GRIPPERPOST
GRIPPER
GRINDER
WATERVALVES
Sheet 19 of 47
UP
/
ROTATE
ROTATE
OPENCLOSE
GRINDON
/
OFF
OPENCLOSE
FIG
.
8B
US 10,900,877 B1

InputSample
SieveWasher
1
U.S. Patent
Grinder
Grinder
Grinder
204
20
607
601
200
200t
Jan. 26, 2021
T
500
Sheet 20 of 47
Grinder
Grinder
201
20
?
201
F
60
200
200
500
with
eggs
500
portofolium modelului
OutputSample
US 10,900,877 B1
FIG
.
9A

Input
Sample
Grinder
27(# 20)
627
27 (# 60) 27(# 200)
62M
27(# 500)
FIG. 9B

Grinder
Sieve
Washer 52
# 20
FIRST
SIEVING
ACTION
#500
FIG. 9C

Grinder Pad 72
# 20
#60 with
Cysts
627 # 60 Moved
By Gripper 56
PPT
*** 3
}
62M
#500
62B
FIG.9D

Grinder 70
UP/DOWN
.
#20m ??
{
760 with
Cysts
SECOND
SIEVING
ACTION
# 200
~ # 500

Grinder
*20
# 200
SIEVING
ACTION
#500
FIG. 9F

Grinder
#20
SIEVED
PRODUCT
#500 with eggs
* 200
#500 Moved and Tipped
by Gripper 56
*
| 1
OutputSample
FIG. OG

Start
Density gradient
Centrifugation of
collectedsample
102
Scanner
imaging
Lensless
Imaging
Quantification
method ?
Stain the solution Load the solution
and initiate solution
flow in the device
Transfer to a substrate
placed on a scanner Record the video,
apply reconstruction
technique Record the final
particle count End
Scan the substrate
and splitthe image
into blocks
Open reconstructed
video
3
Yes
3 $
Read a
block
Read two
successive
frarnes
Is there another
frame/block ?
5
Convert the
colorspace apply
colorthresholds
Applybackground
subtraction Add Nioop to the
total particle count
Nioop - Nioop - 1
No
Identifyall objects,
set Nioop =0 Select an object Isthere another
object?
Extract parameters
of an object(size,
shape)
Does it match
aparticle of
interest? Yes
FIG . 10

01
A

117
X
323
)
FIG
.
11B
116

120
110 (PRIOR TO DENSITY
SEPARATION)
110 (AFTERDENSITY
SEPARATION)
116 (SAMPLE FROM 111)
r444
and
FIG. 12C
M
Hair
I
FIG. 12D FIG. 12E FIG. 12F

130
1
- Bottom
1
we Top
Ege
recovery
ratio - * -Interface
1
W W
% Optiprep solution
FIG. 13

140A
Error in 40% Interface
SoftwareCounts
5
Manual Counts
SoftwareCounts
Hilities
5
Manual Counts

SoftwareCounts W!
Manual Counts
Error in 50 % Interface
SoftwareCounts melulupoepooor!
Manual Counts
FIG . 14D

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154A
THE FLIER PAPER
WI DIGITAL
SCANNER
153 154B
FIG. 15A

SCANNER HOUSING
158
DIGITAL SCANNER
COMPUTERWITH IMAGEACQUISITIONAND
FILTERPAPER WTHSCH EGGS

12
9001793 m
700
actual
size
(
um
) 2?
500
14
100
soybean corn potato cereal
FIG . 16A

160
Imaging nematodes 16
-162
-163
FIG . 16B

Separation of SOK eos from a cleaner suspensionafts sucroseseparation step.
116'
FIG . 16C
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FIG. 160

174
173A
173B
FIG
.
17A
2
.
2
172

179A 179B
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.
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.
.
.
178
17
-------..............................
FIG
.
17B
36:28
.
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176

180A
176
n
D1
E1
VIDEO FRAME 1
AT IMAGING LOCATION

180B
E3
01
E2
03
D2 E1
VIDEO FRAME 2
FIG. 18B

180C
E3
Dm
E2
03 D1
En D2 £ 1
VIDEO FRAME 3

180D
E3
Om
1 03
En 02
VIDEO FRAME 4
FIG . 18D

191
190
192
LIGHT
U.S. Patent
SOURCE
SYRINGES
3X3
195
Jan. 26, 2021
3X3 FLOWOUT
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C3
09
016
019
194
C5
C8
Sheet 45 of 47
D3
018
D15
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01.1
014
017
3X3
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176
177
COMPUTER
3X3OUTTOIMAGERECONSTRUCTION
196
US 10,900,877 B1
198
FIG
.
19

Sensor 204B
Sensor 2044
Sensor2040
Sensor204E Sensor 204D
56
203 208
202
207
209
Sensor Circuit 205A
3
Sensor Circuit 205B
}
Sensor Circuit 2050
}
Sensor Circuit 205D }
Sensor Circuit 205E {
FIG . 20A

200
204A
1
www
Sensor Circuit 205A
FIG. 20B

US 10,900,877 B1
1 2
METHODS, APPARATUS, AND SYSTEMS TO volume of soil, the difficulty is (a) identifying whether
EXTRACT AND QUANTIFY MINUTE infestation has occurred and then (b) what severity. One
OBJECTS FROM SOIL OR FECES, cannot tell from simply looking at the soil, as the organisms
INCLUDING PLANT-PARASITIC are beneath the top of the soil. Also, quantification or
NEMATODE PESTS AND THEIR EGGS IN 5 severity cannot be accurately determined from simply look
SOIL ing at plants growing in the soil.
Decisions as to treatment or strategies of remediation
CROSS-REFERENCE TO RELATED require a reasonable quantification ofinfestation severity to
APPLICATIONS be practical and effective. In other words, a producer could
10 prophylactically apply chemicals to the soil, or utilize spe
This application claims the benefit of Provisional Appli cific SCN -resistant seed coatings, varieties or GMO seeds.
cation U.S. Ser. No. 62/468,760, filed on Mar. 8, 2017, But this might utilize quantities not needed and incur
which is herein incorporated by reference in its entirety. substantial unneeded expense or may result in ineffective
treatmentinterms oflevel ofchemicals ortype ofseedused.
GOVERNMENT RIGHTS 15 Another remediation technique is crop rotation for the field
of interest between different growing seasons.
This invention was made with government support under The dilemma is made worse by the fact that SCN is
NATIONAL SCIENCE FOUNDATION GRANT No. becoming increasingly resistant to GMO engineered seed.
DB11556370. The Government has certain rights in the Therefore, a better understanding of where infestation has
invention. 20 expandedto geographically andits severity wouldbehighly
valuable to the agricultural community. It could help on a
I. BACKGROUND OF THE INVENTION macro-scale with remedial strategies. Thus, individual pro
ducers addressing their specific SCN problems, to regional
A. Field of the Invention or even worldwide organizations or governments, face
25 increasing pressure because of the expanding infestations
Thepresent inventionrelatesto extractingrelatively small geographically and increasing resistance to typical treat
objects ororganisms ofinterest from a startingmixture, such ments. See, e.g. FIG. 1B.
as a soil or feces sample, and to apparatus, systems, and As can be appreciated, the small size ofthe SCN organ
methods of automating at least certain steps in not only ism, as well as its entrainment in soil, make both extraction
extraction, but in input, collection, and quantification ofthe 30 and quantification not just difficult, but unpredictable.
extracted items of interest for further use. In one example, Manual soil sampling from a field, manual sieving of the
the items of interest are plant-parasitic nematodes of field sample through increasingly fine mesh sizes to extract eggs,
crops that can be sampled with a mixture ofsoil and debris and then quantification ofnumber of SCN eggs per sample
froma field andfurtheruse ofcollectedandquantifieditems by suchthings as visual ormanual counting is laborious and
ofinterestto assist inmaking informed decisions onhow to 35 error-prone. Considering the increasingincidence of infes
manage the organisms and/or crops in the sampled field . tationandneedformorequantifiable, quickerunderstanding
Those skilled in the art will appreciate that at least aspects of severity of infestation, such manual procedures become
ofthe disclosed invention may be applied to different items almost untenable.
of interest. Therefore, the invention is not necessarily lim- A conventional way of estimating nematode population
itedtonematodes,soilorfeces samples, orquantificationfor 40 density froma soil sampleis to gatherfieldsoil samples and
remedial purposes. send them to a remote laboratory for analysis prior to the
growing season. There the sample is sub -divided into sub
B. Problems in the State of the Art samples of known volume. A sieving process is conducted
manually on selected sub-samples to try to extract the
Extraction ofrelatively small objects or organisms from a 45 relevant forms ofthe nematodepests, whether egg, worm , or
soil or feces sample has numerous challenges. For example, cyst stage from the sub-sample known volume of soil. Pest
the organism of interest can be in different stages of devel- population density estimates forthe field are made manually
opment. The soil or feces sample vary drastically in char- counting what the worker decides are pests in the sub
acteristics suchasparticularsizedistribution, debris, organic sample andthenrelatingthat countto apestdensityestimate
and inorganic matter, etc. Inparticular, the organisms canbe 50 pervolume ofsoil. This canbe extrapolatedinto anestimate
hard to distinguish from other components and other organ- correlated to whether pest density needs remediation.
isms in the sample. The foregoing technique relies heavily on human manual
Take the case of soybean cyst nematodes. They can exist actions andjudgements. As such, it is susceptible to human
in egg, juvenile worm , or egg-filled cyst form in soil. Each error, as well as resource costs and limitations related to
state varies in size and shape (see ref. nos. 10, 12, 14 and 16 55 labor and time. It also requires substantial targeted training
in FIG. 1A). Soil from field -to- field, and sometimes within of the workers.
a single field, can vary in texture, moisture, make-up, and Therefore, the inventors have identified room for
otherorganisms and organic and inorganic components. improvement in this technical area.
Soybean cyst nematodes (SCN) can cause substantial There is a need for more automated, quicker, repeatable,
yield decrease. Yield reduction typically is related to nema- 60 andprecise extraction ofnematode eggs and cysts, andtheir
todeeggs andcystspopulationdensity (ornumber) inafield. quantification. There is the need for a system that can
Knowledge ofestimated population density at the appropri- operate away from laboratory settings and, as such, can be
ate time ortimes, with sufficient accuracy, can at least allow substantially portable and robust.
the chance ofmeaningful remedial actions. However, there are many challenges. The small scale of
As is well knownin soybeanproductionagriculture, SCN 65 nematode eggs (e.g., microscale) presents technological
is the number one yield loss. While it has been demonstrated hurdles to not only identifying them but handling them in
that yield loss is proportional to number of SCN eggs per machine-based fashion. Technological hurdles include

25
30
US 10,900,877 B1
3 4
variation and content of soil sample. Most samples contain g. Portability of system. Can be carried and moved to
not only any nematodes but other organisms along with dirt different laboratory or non-laboratory settings or in
particles. Also, the soil in the sample can vary by compo- farm fields or other locations to perform functions on
sition (clay, loam , etc.) but also textures, particle sizes, not the soil or feces sample in a preferred location by the
to mention debris (e.g. organic trash, rocks, etc.). These 5 user or group of users.
types of factors make it difficult to differentiate objects of h. Speed. Can quantify a plurality of samples in much
interest from all else. Unpredictability results from both the quickertime-frame thanpresent techniques.Aspects of
foregoing challenges, andalso because designfactors canbe the invention can be implemented in single sample
antagonistic withone another.Forexample, betterextraction serial processing or high -throughput plural parallel
of such small objects tends to require more steps and more 10 sample processing.
time. But a need in this area is more efficient extraction i. Repeatability. Can be set up over a variety of different
techniques. Similarly, better automatic identification and sample make-ups and conditions to produce repeatable
countingtendto suggesthighercostandcomplexity.Butthis results.
is antagonistic with economical solutions. j. Precision and accuracy. As will be explained further
It will be further appreciated that analogous challenges 15 below, absolute precision and accuracy is not required
can exist regarding other items of interest. For example, for benefits. But repeatability and accuracy within a
there are other organisms that lay their eggs in soil or feces certain acceptable margin of error can be sufficient. It
of which efficient, economical, and accurate population is to be understood that the present invention can
density estimation would be useful. Some are parasitic. address and take advantage ofthat.
Others are non-parasitic or beneficial. There can be other 20 k. Macro- or micro -data. As will be appreciated, the
objects of interest in feces. But quantification could be increasing pressure at addressing problems discussed
beneficial, including for pest management and for research herein, exists over a range of scales. On one hand,
purposes. Still further, there are other relatively small items individual producers orresearchers wouldliketo better
that could benefit from a more efficient and economical quantify soil or feces samples not only at one sample
extraction, collection, and/or quantification. location but in as many per field or location as is
practical. Modern precision agricultural application
SUMMARY OF THE INVENTION and planting equipment allow on-the-go adjustment of
chemical application rate or seed selection which can
A. Objects, Features and Advantages of the be changed across a single field. Knowing ifinfestation
Invention levels differ in the same field can be meaningful as far
as cost ofmaterials. On the other hand, the ability to
It is therefore a principal object, feature, or advantage of have a technique that is repeatable, accurate within
the present invention to improve over or solve problems and needed margin of error, and precise within the margin
deficiencies in the state -of-the-art. of error can allow gathering of data on a more macro
Other objects, features, and advantages of the invention 35 scale. Use of multiple systems across wide range of
include a system, methods, or apparatus as above described geographical areas can gather such informationin a
which provide one or more ofthe following: consistent manner. Such information can be reliably
a. Efficiency. Does not require transport of samples to correlated in a data sense to help understand the SCN
dedicatedlaboratory,which is many times remotefrom problem and generate solutions regionally and world
sample site, or necessarily require advanced or highly 40 wide. Modern animal science could likewise benefit
specialized training from such systems in similar ways by gaining infor
b. Economy. Does not require high priced components, a mation from quantifying small organisms in feces
lab setting or specialized training. samples.
c. Throughput. Can allow at least substantially efficient 1. Startingunpurified sample.Aspects oftheinventioncan
automated movement through the system for good 45 be used with a dirty sample, in the sense it does not
throughput of plural samples, while keeping track of require substantial, costly, complex pre-processing of
each for documentation and identification purposes. the sample to remove substantially all impurities or
This can relate to speed per sample, or cumulative irrelevant substances.
number ofprocessed samples per unit time.
d. Uniformity of results. By reducing sources of human 50 B. Aspects of the Invention
error, and by consistent mechanized, automated func
tions, inconsistencies can be reduced, and results A first aspect of the present invention relates to a highly
obtained more consistently for improved comparisons flexible, highly adaptable substantially automated system
between samples from the same field to samples from and method of extracting, collecting, and/or quantifying
different fields. 55 relatively small items of interest to improve over highly
e. Effectiveness. High control ofextraction functions can manual techniques that require substantial technical training
improve extraction of relevant items and thus quanti- ofworkers. In particular, this aspect ofthe invention pres
fication ofthe same. ents a basic framework or functional technique to not only
f. Flexibility ofImplementationandUse. Allows multiple fosterrelatively highthroughput, highly controllable, highly
functions with same basic systems so that different 60 adjustable extraction, but also collection and/or quantifica
items of relevance can be extracted and quantified. tion, which allows the designer to apply these aspects to a
Different processes, different order of processes, and variety ofpossible tasks. For example, one implementation
sequence ofprocesses allows for application to differ- is improved efficiency inextractingrelatively small items of
ent target items ofrelevance or different treatments of interest from a mixture. Alternatively, the system and
suchtargets. Essentiallythe systemcanbereconfigured 65 method could be used for collection and quantification of
as to when, where, what, how, and why certain func- relatively small items of interest. An intelligent, program
tions occur but all within the same basic system. mable controller can orchestrate different operations to

US 10,900,877 B1
5 6
effectuate the desired operations to achieve such results. and any items of extracted from it between input to and
Examples of controllable functions are translation between output from the system to maintain correlation of samples.
operational stations, multiple steps for extraction, acquisi- A further aspect of the invention applies the concepts
tion of automated counting of the items of interest, and above to a single soil sample for quantifying nematodes in
communication and storage ofthe quantification for subse- 5 any of its life stages, including eggs, worms, and cysts.
quent use. Such uses can include, but are not limited to, A further aspect of the invention applies the concepts
decisions related to the quantification, research purposes, or above to a single feces sample for quantifying organisms in
other. it.
Another aspect ofthe invention comprises a comprehen Afurtheraspect ofthe inventionprovides efficientparallel
sive automated system and method of providing multiple 10 processing of many samples.
samples to an input station, serially extracting items of BRIEF DESCRIPTION OF THE DRAWINGS
interest from each sample, collecting the extracted items of
interest from each sample, and quantifying the number of
items of interest in each collection in a continuous or 15 executedincolor.Copies ofthispatentorpatent application
Thepatentorapplicationfile contains atleastone drawing
semi-continuous efficient manner. In one implementation, a publication with color drawing(s) will be provided by the
conveying sub-system presents samples sequentially to an Office upon request and payment ofthe necessary fee.
input station. Amechanized positioner guides a first sample FIGS. 1A-B are diagrammatic views and illustrations of
through one or more extraction functions at an extraction background information regarding SCN.
station. Examples of the extraction functions can include, 20 FIG. 2A is a high-level diagrammatic flowchart of a
but are not limited to, separating the items of interest from methodology using the system of FIG. 2B according to an
at least other constituent materials in the sample by one or exemplary embodiment ofthe invention.
more filtering or sieving steps.Additionally, extraction func- FIG. 2B is a high-level diagram ofa system and its major
tions can also include further operations on the extracted components according to one exemplary embodiment ofthe
items. One example is grinding the items to separate con- 25 invention.
stituent parts ofthe items ofinterest, such as to release eggs FIG. 3Ais a flowchart ofa method ofoperation according
from cysts. Another example is use of fluids to assist in to a first specific embodiment of the present invention.
separation ofobjects ofinterest orcleaning the sub-systems. FIG. 3B is a diagrammatic view of an apparatus and
Quantification can include further operations on extracted systemcomponentsto practicethemethodology ofFIG. 3A.
items ofinterest to prepare for evaluation at a quantification 30 FIG. 4Ais a perspective assembled view ofan extraction
station. Examples include but are not limited to moving station of FIG. 2A in one specific implementation and
extracted items to a rotational or centrifugation separation embodiment.
device to concentrate the items ofinterest in preparation of FIGS. 4B, 4C, and 4D are front, side, and inviews ofFIG.
imaging. Quantification can then be done by digital imaging 4A.
and using image recognition software to identify and count 35 FIG. 5A is an isolated, enlarged perspective ofa robotic,
the items of interest automatically. The count can be com- multiple-degree freedom ofmovement subassembly ofFIG.
municated to an intelligent programmable processor where 4A, namely a combined robotic gripper tool and washing
the count can be used, stored, or manipulated according to tool according to the system of FIG. 4A.
need or desire. Second and succeeding samples can be then FIG. 5B is a front elevation of FIG. 5A.
processed serially in a similar manner. FIGS. 5C and D are perspective isolated views of the
Another aspect ofthe invention comprises different tech- gripper tool of FIGS. 5A and B from two perspectives.
niques of quantifying extracted objects of interest. In one FIGS. 6A and B are enlarged isolated perspective and
example, image recognition of a digital image of a static front plan elevation views of a turntable assembly of the
sample from a scanned -based digital imager is used to system of FIG. 4A according to a specific exemplary
identifyandcountobjects ofinterestbasedondifferentiating 45 embodiment.
characteristics, such as size, shape and color. In another FIGS. 7Aand B are enlarged isolatedperspective and side
example, image reconstruction of digital video of a sample views ofa grinding tool according to a specific embodiment
entrained in a flowing liquid from a lens-less digital video of the system of FIG. 4A.
imager is used to identify and count objects ofinterest. FIG. 8A is a perspective, isolated view of a control
In a further aspect ofthe invention, a specific application 50 subsystem and circuit arrangement for the system of FIG.
can include an automatedextractionofitems ofinterest from 4A. FIG. 8B is a diagrammatic view of the functional
a starting sample mixture by directing the mixture through attributes of software used with the control subsystem of
at least two sieves. Each sieve may have pores of different FIG. 8Arelativeto operationofthe extraction stationofFIG.
sizes. This aspect involves filtering the sample mixture in a 4A.
first sieve and collecting what passes the first sieve in a 55 FIG. 9A is a simplified diagrammatic illustration of a
lower sieve, andthen either collecting what is not passedby sequence ofoperations for extracting SCN eggs from a soil
the second sieve or actuating further processing steps. The sample using the station of FIG. 4A. FIGS. 9B-G are
extraction can include automated ancillary functions such as isolated views of each ofthe sequence ofthe steps of FIG.
vibration, rinsing, ortipping ofone ormultiple sieves, either 9A.
sequentially or in parallel. In one embodiment, a robotic 60 FIG. 10 is a flowchart ofpossible functional operations of
hand can be automatically controlled relative to the sieves, the quantification station ofFIG. 2B according to a specific
actuators can be automatically controlled for vibration of embodiment of the invention.
sieves or the entire extraction system, and valves automati- FIG. 11A is an enlarged diagrammatic view ofa vial used
cally controlled for rinsing action of sieves or the entire in anoptional technique forseparating by density SCN eggs
extraction system . A programmable controller can coordi- 65 from other materials in solution prior to quantification by
nate timing and sequence of operations. The system can any of the techniques of FIG. 10, including showing how
further include techniques to maintain identity of a sample density separation through centrifuging occurs.
40

20
US 10,900,877 B1
7 8
FIG. 11B is a perspective view of a stack of filter paper aspects ofthe invention canbe a subset or even one ofthose
disks for receiving a sample for quantification, with dia- functions, depending on need or desire. For example,
grammatic isolated illustration ofone such disk with super- aspects of the invention can relate simply to extraction.
posedimagingzones orblockswhenscanning a static digital Other aspects can be limited to collection or quantification.
image ofthe surface ofthe disk used for imaging extracted 5
eggs fromthemiddle density-separatedvolume ofFIG. 11A, B. Generalized Example
deposited on the filter paper, for quantification of eggs
according to an exemplary embodiment ofthe invention. Ageneralizedexampleofamethod(indicatedgenerallyat
FIGS. 12A-F are photos and graphs showing proof of reference no. 20) and system (generally at 26) according to
concept of effective separation of SCN eggs in the centri- 10 aspects of the invention is illustrated at FIGS. 2A and 2B.
fuged vials of FIG. 11A. FIGS. 2A and 2B show at its highest level, aspects ofthe
FIG. 13 is a graph showing proofofconcept ofconsistent invention can include on a functional level. One or more of
recovery ofSCN density-separated eggs from other portions efficient extraction and/or quantification of an unknown
of the solution in the vial of FIG. 11A. quantity ofminute objects ofinterest can be accomplished,
FIGS. 14A-D are graphs showing proof of concept of 15 including from a relatively dirty starting raw sample. Auto
using imaging recognition software for counting SCN eggs mation or semi-automation can be applied to one or more of
on the filter paper ofFIG. 11B compared to manual counts. these. While specific embodiments are described in relation
FIG. 15Ais a high-level flow chart ofquantificationusing to soybean or other nematodes, the invention is not neces
the filterpaper ofFIG. 11B witha digital scanner and image sarily limited to those items of interest.
recognition software, according to one option in FIG. 10. FIG. 2A shows the basic methodology. One or more raw
FIG. 15B is a diagrammatic example of one possible samples are prepared (see step 21). In the example of
imaging subsystemforimagingfilterpapers ofFIG. 11B and nematodes, this can involve a soil sample obtained from a
then processing with image recognition software for count- field. Thus, it is "dirty" in the sense that it contains the
ing SCN eggs on filter paper as in FIG. 15A. objects ofinterest to be quantified (e.g. SCNs or its cysts or
FIGS. 16A-D are illustrations and color photos showing 25 eggs) but entrained in a substantialamount of objects or
shapes that are typical regarding SCN life stages and tech- substances not ofinterest (e.g. dirt, otherorganisms, debris).
niques forsamplepreparationfor imagingand countingwith It can be diluted or otherwise prepared for further process
image recognition software technique of FIGS. 15A-B. ing. But in one aspect, it does not need to be purified in the
FIG. 17A is a flowchart depiction ofan alternative tech- sense ofsubstantially separating the objects ofinterest from
nique ofSCN egg quantification in FIG . 10, namely use of 30 all else. In the case offeces, it can be obtained from a field,
microfluidics and lens-less video imaging capture offlowing an animal confinement, or otherwise.
eggs in solution with an illumination source for diffraction- An identification designation can be given to the sample.
based image reconstruction and object-of-interest identifi- In one example an identification number can be assigned.
cation. That number could be encoded in a bar code or other
FIG. 17B is a diagram of one hardware set up for the 35 machine-readableformona samplecontainer.Techniquesto
technique ofFIG. 17A. do so are well-known to those skilled in this area of
FIGS. 18A-D are simplified and highly diagrammatic technology. Sample(s) can be presented for processing
illustrations of video capture with the technique of FIGS. including by mechanized conveyance or otherwise.
17A -B to obtain a count of SCN eggs in a flowing sample 1. Extraction
solution. In this generalized embodiment, an extraction function
FIG. 19 is a diagram of an automated sample parallel- involves at least two separation or filtering steps. In the case
processing option according to another example of the ofnematodes, it caninvolve a first sievingwitha sievemesh
invention. size effective to pass nematodes in whatever stage (eggs,
FIGS. 20A and B are perspective and side elevation worms, cysts) through to a second sieve. As explained
views, respectively, of an optimal sensor tool that can be 45 further later,the second sieve is selectedbased onwhat item
used in the other embodiments of the invention. of interest and/or what stage of development of items of
interest is desired to be collected.
DETAILED DESCRIPTION OF EXEMPLARY In the case ofnematode eggs, the sieving may include a
EMBODIMENTS OF THE INVENTION grinding step to rupture or force the eggs in cysts to be
50 released through a second sieve to a third sieve. In the case
A. Overview ofworms, the second sieve may have a mesh size to collect
them and no third sieve is needed. Inthe case ofcysts,it may
For a better understanding of the invention, several be that only two sieves are needed.
examples of forms or embodiments the invention can take One aspect of the generalized embodiment is that the
will now be described in detail.These examples are neither 55 paradigm provides the designer/userwith high flexibility in
inclusive nor exclusive of all forms and embodiments. As selecting and adjusting the system to meet different require
will be appreciated by those skilled in this technical area, ments, with the advantages of automation at acceptable
variations and options are possible. levels of precision and accuracy, and further on a cost
The examples will focus on soybean nematodes and their effectivebasis at least comparedto conventional techniques.
cysts and eggs as the items of interest to be extracted, 60 As in the above example, the extraction (step 22) is adjust
collected, and/or quantified. As will be appreciated, the ablebasedonwhatneeds to be filteredaccordingto different
invention is not so limited. Application ofthe techniques of goals. Inthe nematode implementation, this involves two or
the invention can be applied in analogous ways to other more sieves 27. In some applications it might be just one
items of interest. sieve. Automatic actions are controlled to cause the starting
The examples will be focused on a substantially compre- 65 raw (“dirty”) sample mixture through a first filtering step at
hensive automated system for extraction, collection, and/or least at one sieve and collection ofwhat passes through on
quantification of items of interest. As will be appreciated, another. Further filtering through still smaller mesh-size
40

US 10,900,877 B1
9 10
sieves is possible. This processing can include controlled In one embodiment, the static image is acquired by a
movement of the sieves both in position relative to other flat-bed digital scanner. This can include using built-in
components of the system or relative to space generally zooming capabilities of the scanner to zoom in on the
(translation in XYZ directions to different position, or tilt- surface for higher magnification to promote better image
ing, vibration, or other). 5 recognition. This could include scanning the surface at the
As shown in FIG. 2A, the items of interest can be zoomed setting to acquire individual areas or blocks ofthe
collected after the extraction (step 23). Such collection can surface, each which could be evaluated by the software.
be a result ofthe extraction steps. For example, after sieving, Alternatively, or in combination, the imager could have a
items ofinterest can collect on top ofa sieve. In some uses, digital zoom function that could be employed after a digital
thecollecteditemsofinterest cansimplybeused for further 10 imageofatleastpartofthesurface (or allofit)isacquired.
research (e.g. biological research regarding nematodes). That digital zoom could magnify discrete portions of the
image to promote better image recognition of objects of
Optionally, a variety ofpost-collection steps are possible. interest. The count would accumulate over the entire surface
One example is to collect the contents of a sieve and then area to produce a quantification oftotal estimated nematode
further process that collected intermediate product. For 15 eggs in the sample from the static sample.
example, items ofinterest in the intermediate product could Another technique for imaging is a video, acquired by a
be quantified. Non-limiting examples include substantially lens-less digital sensor component, ofthe extracted sample
automated quantification (see FIG. 2A, step 24). One places in solution flowing past the sensor. With an appropriate
the intermediate product on a filter paper, plastic sheet, illumination source and optical set-up, inexpensive, small
counting slide, or other substrate, and uses image recogni- 20 form factor lens-free Talbot-effect interference patterns can
tion to count items of interest recognized on the substrate. be captured by the sensor. The interference patterns caused
Another moves the intermediate product past or through by non -transparent objects in the flow can be compared
some type of sensor configured to differentiate and count across several frames ofcapturedvideo. The software would
items of interest. Non-limiting examples includemicroflu- be pre-programmed to either identify diffraction patterns
idic flow past a video imager with image reconstruction 25 indicative ofan object ofinterest and count them or recon
identification ofitems or interest in the video or use offlow struct a truer optical image from the interference pattern and
cytometry techniques to singulate andcount items ofinterest use more typical image recognition to count. The count
in a flow. Furtheroptions can include techniques to improve would accumulate over the entire sample flow to produce a
onthe intermediate product.Non-limiting examples include quantification oftotal estimated SCN eggs (orother objects
purificationstepstopromoteagreaterpercentageofitemsof 30 of-interest) from the sample.
interestrelativeto otherparticles inthe intermediateproduct FIG. 2B indicates that a final quantification ofthe items
before counting. This can include, inter alia, shaking, cen- of interest can be then communicated automatically for
trifuging, rotating, heating, or otherwise manipulating (in- further use (step 25). Examples include digital storage for
cluding by automated techniques) to further separate, iso- later access. Another is transfer of information over a
late, concentrate, ordistributethe extracteditems ofinterest. 35 communications network (including wide-area networks
There are also enhancements possible regarding any carrier like the Internet or local networks). In the example of
fluids, surfactants or detergents combined with the items of nematodes, the quantificationcanbe correlatedwitha begin
interest, along with hydrophobic coating the inner walls of ning soil sample, the count converted into an estimate of
container and mechanical agitation to avoid clumping ofthe population density of nematode eggs and cysts per unit
items of interest. Examples will be discussed herein. 40 volume soil for the field sampled, and the further action
As illustrated in FIGS. 2A and 2B, different stations and involve a recommendation for remedial action for that field
components can effectuate the method steps. An extraction to reduce the effect of that density of nematodes on crop
station 28 can include robotic or automated motion control. growth and production.
An intelligent controller 80 (with software) can instruct The method can include additional automated steps. One
system operation. Further intelligent devices (e.g. tablets or 45 is control over waste or non -relevant components of the
smart phones) can communicate with the main controller. A sample (see FIG. 2A). Automated actions can be pro
quantification 24 (FIG. 2A) byvarious possible components grammed to move such substances to a waste location.
at a quantification station 29 (FIG. 2B) can produce a Additionally, automation can be controlled to present,
quantification count ofitems ofinterest in a highly flexible, sequentially and serially to the input, plural pre-prepared
efficient, and effective manner. 50 samples for processing. Such steps can allow high through
2. Quantification put by allowing automated processing of samples on a
Asshown in FIGS. 2A and2B, substantially automated continuous, even around-the-clock basis, if desired. Alter
quantification ofthe extracted items ofinterest in the inter- natively, parallel processing ofsamples is possible applying
mediate product can take different forms. One example is aspects of extraction and/or quantification according to the
transfer ofitems ofinterest fromthe extraction step or steps 55 exemplary embodiments. Examples ofthese techniques are
to then digitally image them . Image recognition or recon- available commercially from a variety of sources and are
struction software canbe usedto identify andcount what are well-known to those skilled in this technical area.
considered by the software to fit the profile orparameters of FIG. 2B is a block diagram for a generalized system
an item of interest. This could be by shape, size, color, or according to aspects of the invention. As indicated, the
other parameters or combinations ofparameters. 60 system can include the following stations:
As will be further discussed, digital imaging can be Input station for presenting one or more pre-prepared
implemented in different ways and techniques. One is by samples.
distributing an extracted sample across the surface of a Extraction station 28 - for automated separation ofitems
substrate and acquiring a static digital image ofthat surface ofinterest ofeach sample, and for collection in useful form
by a digital scanner. The image can be evaluated by image 65 of extracted items of interest.
recognition pre-programmed to identify objects of interest Quantification station 29 for in some fashion quantify
and count them . ing the items of interest as a raw quantity or in correlation

US 10,900,877 B1
11 12
with other relevant information. One example is computa- actuators to accomplishneededmovement, timing, andother
tion ofan estimate ofdensity ofnematode eggs and cysts per functions. The designer would have to coordinate them as
unit volume of soil. needed or desired.
It is to be appreciatedthatthe system ofFIG. 2B does not FIGS. 3Aand B are overall schematics ofone example of
necessarily require all stations to be automated. For 5 methodology (FIG. 3A) and system (FIG. 3B) that can be
example, there could be tasks which simply take advantage used with this specific embodiment. They show diagram
of automated extraction. One specific example is simply matically one example ofthe overall control and actuation
extracting nematode worms from a mixture for research system for automated operation ofthis embodiment. As will
purposes without quantifying their number in the sample. be appreciated, the specific components andtheir set-up and
As will be appreciated bythose skilled in the art, auto- 10 interconnection can be adjusted by the system designer
mated or semi-automatedtracking ofa soil or feces sample, according to needed functions.
through the extraction station and then to the quantification In this example, the system controls not only a robotic
station, can take a variety of forms. In some embodiments, gripperarmthathas multiple degrees freedom ofmovement,
simply by nature ofknown sequence and timing of actions but also a water rinsing sub -system and a rotatable turntable
through the stations, a soil or feces sample in can be 15 with multiple levels. There is also an available grinder that
correlated to the quantification measurement out. The sys- can be translated towards a sieve screen (or sieve screen
tem is simply reset for the next sample. translatedto the grinder) androtatedforgrinding actionnear
Onthe other hand, a variety of known commercially the sieve screen.
available technologies could be used. For example, a bar A computer is shown connected to the controller and
code on a containerwiththe first ofsoil or feces sample can 20 includes imager control as well as image recognition pro
be scanned and entered into the control system . Once the cessing, digital storage, or communication to other devices,
results of the extraction station are collected into a second including remote computers or devices.
container, a bar code or other identifier can be tracked or As will be appreciated by those skilled in the art,
assigned to correlate it to the input soil or feces sample appended FIGS. 3A and 3B schematically depict non-lim
barcode. This cancontinuethroughthequantificationstation 25 iting examples ofthe overallcontrol system (s)andmethod
and be correlated to a numerical quantification value that steps that are possible with this embodiment. As shown in
would match an SCN infestation characterization to that FIG. 3A, some type of programmable controller 180 (e.g.
original soil or feces sample. That can be communicated, Arduino UNO Controller board for NEMA 17 stepper
stored, displayed, printed out, etc. motor) can be programmed to control timing and actuation
Still further, even more automated identification and 30 ofa variety ofcomponents. In this example, there could be
tracking systems can be used. Those systems are quite timing of operation of conveyors, both input and output.
advanced and available in a variety oftesting or automated There is timing and sequencing ofturntable(s) and gripper,
systems. For example, when testing a plurality ofbiological as well as several degrees freedom of movement of the
samples with multi-well titrator trays, such automated com- gripper to allow movement of sieves in three dimensions.
ponents such as pipettes and othermaterial handling com- 35 The system can control spraying by controlling fluid
ponents can correlate an input sample to output data for that valve(s), as well as vibration by a motor or actuator ifused.
sample which can be utilized according to need or desire of Still further, the control system could sense and read
the designer. identification information about samples. Such techniques
As indicated in the generalized example of FIGS. 2A-B, arewell-known. It canutilizeanintelligentdevice andwired
discrete parts ofthe overall system 26 or method 20 could 40 or wireless communications (e.g. PC, laptop, tablet, smart
be implemented in certain situations. For example, as indi- phone, or other) or use the controller to control and process
cated earlier, just the extraction station 28 and functions 22 digital imaging and image recognition at the imaging sta
could be used for extraction of items of interest from a tion. Finally, optionally, the quantification calculated from
complex starting sample, even if the quantification station image recognition counting can be stored or communicated
29 or functions 24 are not used. Similarly, different extrac- 45 for further use.
tion systems or functions could benefit from just the quan FIG. 3A shows in flow chart form , one non-limiting
tification system or functions of the generalized example. methodaccordingto inventionwhichmakes the systemvery
But, as can be appreciated, combining the extraction and flexible in its application. For example, some processes
quantification functions can result in benefits. require one sieving step and then collection. But others
50 require a second orthird sieving step (with different sieves).
C. Specific Example 1 There couldbe repeats ormore sieving steps. Also, grinding
is not needed in all applications. For example, grinding is
One exemplary embodiment according to at least some of needed only when an egg count is desired where the cysts
the aspects ofthe present invention are set forth below. The are ruptured to release the eggs. Vibration and rinsing ofan
description outlines both apparatus and methods but also 55 individual sieve or multiple sieves is optional and is needed
some ofthe practical considerations with respect to extract- to enhance the extraction process and clean the sieves when
ing, collecting, and/or quantifying soybean nematodes in desired. This illustrates that the system could be pro
egg, cyst, or worm form in comparison to conventional grammed and configured easily for different sequences,
techniques. number, andtypes ofprocessing steps according to desire or
1. Overall Functions/Components of Specific Embodi- 60 need.
ment 1 (FIGS. 3A-B) FIG. 3B shows diagrammatically one non-limiting hard
FIGS. 3A and 3B illustrate diagrammatically examples of ware combination to effectuate at least the method 30A-L of
some of the automation requirements of the system and FIG. 3A. Variations are, of course, possible.
method of FIGS. 2A and 2B, such as might be applied to FIGS. 4A-D show, from different perspectives, one
nematodes in a specific implementation of the generalized 65 example of an assembled embodiment 40 for an extraction
invention discussed above. For example, one or more pro- station according to relevant components 32 in FIG. 3B.
grammable controllers would be needed to control different Then, FIGS. 5A-E, 6A-B, 7A-B, and 8A-B illustrate with

5
asin
US 10,900,877 B1
13 14
more detail the gripper, washer, turntable, grinder, and designed components, each having functionalities to pro
control sections of station 40. mote the process. Motion control is through an effective yet
Further illustrations of how the Specific Embodiment 1 flexible manner.
canbe operated, including in an automatic mode, are shown 2. Extraction Station 100 Assembled (FIGS. 4A-D)
at FIGS. 9A-G. The nematode egg extraction instrument 40 canbebroken
a) Method ofFIG. 3AApplied to Extraction ofSCN Eggs down into a number of subsystems including linear motor
from a Soil Sample sub -systems, gripper arm , washing tool, a set of rotational
FIG. 3A is a highly schematic depiction of examples of stage platforms, and grinder tool. FIGS. 4A-D shows the
automatically controlled functions for extractionand collec locations of these individual subsystems and how they fit
tionstepsaccordingto onewaythatSpecific Embodiment1 10 into theoverallinstrument40. Thelinearmotor subsystems
can be configured and operated. As will be discussed in control both the vertical motion of the combined gripper/
detail later, this automated control can be applied tomotion washing tools and their planar rotation, allowing for sieves
controlledhandlingofstandard-sized sieves. Oneexampleis
as follows. to bemovedverticallyto newpositions andthewashing tool
Asample is introduced(step 30A) to afirst#20 sieve (e.g., 15 to access and operate at any ofthose position. The gripper
~800 um openings). The #20 sieve is selected to pass cysts arm assists in this process by grabbing a cylindrical object,
and some ofthe dirtby gravity and, optionally, waterrinsing any ofthe sieves, in its fingers and holding it while the
(step 30C) and/or vibration (step 30E) from a soil sample linear systems carries out the transfer between turntable
onto a #60 sieve (~300 um openings) beneath but block stages. Each turntable stage can contain four sieve retainer
larger particles and debris.This isafirst purification or 20 positions (could bemore or less) allowing for up to four
extraction step (step 30B) for soybean cyst nematodes. different sieves or the same or different types to be housed
Afterapre-selectedtime, the gripperautomaticallymoves on each level of the instrument's stage subsystem . These
and grabs the #60 sieve, and automatically moves it into a stages can then rotate to the gripper or washing tool vertical
position (step 30F) where a grinder can automatically be axis independent of each other increasing the versatility of
converged towards the top ofthe small #60 sieve to gently 25 the instrument as a whole.
grind (step 30D) the cysts. This action releases and pushes FIG. 4A illustrates a specific, non-limiting embodiment
eggs from the cysts through the small #60 sieve to drop by 40 of the extraction station 28 of FIG. 2B. Its major
gravity (and optionally with vibration and/or water assis- subsystems are as follows.
tance) onto the top of a #200 sieve (~100 um openings) A framework 41, including a base or floor, has a length ,
below it. The #200 is sized to block larger debris than the 30 width, andheightthatcanbereasonablyportableandrobust.
eggs but allow the chance for smaller items (and any water) In one example it is table-top scale. This would allow the
to pass through (step 30G). This essentially is trying to entire integrated extraction station 40 to be mobile such as
purify the sample at this point down to just eggs and debris on a pickup truck orthe like. It couldbe taken directly to the
of similar or smaller size. At that point the gripper can field from which soil samples are obtained. Of course, can
manipulate the #200 sieve and pour its contents to a collec- 35 be scaled up or down depending a need or desire.
tionfunnel orconduitforquantification, orfurtherfilteronto The materials used for frame 41 can vary. One example
an even smaller sieve (e.g. #500), approx. 20 um openings, for beams is Aluminum Extrusion 10 Series, Part #: 1010-S
and the eggs (which are on the order of less than 100 um from 80/20 Inc. of Columbia City, Ind. (USA). See https://
dia.). 8020.net/shop/1010-s.html (incorporated by reference
As will be appreciated, this schematic shows the flexibil- 40 herein). Beams are connected by 10 Series 3 Way-Squared
ity ofthe embodiment. It canbe varied as to what size sieves Corner Connectors, Part #: 4042 from 80/20 Inc. See https://
and mesh pores are desired, how many sieving steps, when 8020.net/4042.html (incorporated by reference herein).
and how to collect, and whether to add ancillary steps such FIGS. 4B-D show various view angles of extraction
as grinding. Rinsing and vibration are examples of others. station40 ofFIG. 4A.Aswillbeappreciatedbythose skilled
An example of sieves is U.S.A. Standard ASTM Sieves 45 in the art, extraction station 40, in an integrated fashion,
Series (e.g. 6 " dia.) available from Humboldt Mfg. Co., provides not only high flexibility but specific functionalities
Elgin, Ill., USA. to enhance speed, accuracy, repeatability, and precision of
Counting/quantification (step 30H) and storage/commu- extracting SCN eggs from a raw soil sample. As will be
nication (step 301) of the count can occur, if desired. further appreciated, variations obvious to those skilled inthe
Waste removal (step 30J), rinsing ofall used sieves (step 50 art will be included within this example. The arrangement,
30K) and repositioning of sieves (step 30L) can reset the specific tools, specific operationparameters can be set up as
system for a next sample. desired or needed by the designer.
b) Apparatus of FIG. 3B Applied to Extraction of SCN Details about each sub system ortool in extraction station
Eggs from a Soil Sample 40 follow .
FIG. 3B is a block diagram depiction ofone configuration 55 3. Vertical andRotational Control Features ofGripperand
of automated control for the processing of FIG. 3A. It Washing Tools (FIGS. 5A-B)
illustrates how a programmable control board, by appropri- a. Function
ate programming, can control motors which perform the The fundamental functionalities ofcombined gripper and
different automatic steps described above. It will be appre- washing tools 50 ofFIGS. 5Aand B are in multiple degree
ciatedthat different configurations are possible according to 60 freedomofmovementbymotioncontrol to move sieves and
need or desire. to wash sieves.
As will be appreciated by details regarding each of the Using motion control, combined tool 50 is positioned in
component parts of extraction instrument 40 later in this frame 41 at the periphery of multilevel rotatable turn table
description, the fundamental aspect of instrument 40 is the 60. It can interact with any level and position turn table 60,
ability to automate sieving actionon araw sampleto extract 65 as well as grab a sieve or sieve-sized container with a raw
extremely small items ofinterest for further use. Extraction sample at input andretrieve a sieve andunloaditto an output
instrument 40 does this with a combination of carefully container or location.

US 10,900,877 B1
15 16
b. Apparatus to that action. The designer has flexibility such as building
One non-limiting example of combined tool 50 is shown into washing tool 52 custom spray patterns for achieving
at FIGS. 5A-H. Variations are possible. needed functions, use ofwater pressure to power rotation of
Vertical motion control is accomplished by mounting the the spray arm , and optimized spray pattern forboth rotation
combined tool 50 on a linear bearing that moves with the 5 and spray coverage for best results.
screw nut of a lead screw or ball screw in a vertical post Controller/software 80 can operate appropriate valving
along axis 53. from a pressurized water source to spin spray arm 54. This
Non-limiting examples ofprincipal components to allow can enhance a washing action relative to a raw soil sample
vertical motion control are as follows: to promote passage ofcysts and eggs through a first sieve of
Vertical Linear Motion Control of Both Gripper/Washer 10 #20 mesh size. The washing action of the rotating arm 54
Tool Combination and Turntable. can continually try to influence that action, as well as wash
Lead Screw. Part #:634052 from Servocity. Thread Size: off the sides of both the sieve and the hood, to attempt to
8 mm. Length: 24".See URL: https://www.servocity- move all cysts andeggs intheraw sampleto andthroughthe
.com /lead-screws# 371 = 326 first sieve, to improve the accuracy of the ultimate quanti
Linear Bearing. Part #6415 from 80/20 Inc. See https:// 15 fication. In other words, the design ofwashing tool 52 not
8020.net/shop/6415.html (incorporated byer reference only helps separate, in a first stage, the materials that are or
herein ). include the SCN eggs from larger particles, but also ensure
Set Screw Shaft, Part #: 625224 from Servocity. Bore: 5 that the whole raw sample is processed at this sieve to
mm to 5 mm. See https://www.servocity.com/set- recover as many of the eggs as possible (e.g. not leave a
screw -shaft-couplers. 20 significant number stuck to the side ofthe sieve or hood, or
NEMA 17 Stepping Motor. Step angle: 1.8º. onthe sieve screen ). Without the same, some canbe retained
As can be seen at FIGS. 4A-D, this allows access either along the sieve walls or not pass through the sieves.
of the tools to any level of the turn table. As can be further appreciated, washing tool 52 can be
c. Features used in other ways. For example, it can provide washing
Rotation of the combined tools 50 about axis 53 is 25 action to other sieves to further influence sieving action and
accomplished with a rotary geared bearing with onboard promote full collection of articles of interest.
motor mounted on the linear bearing that supports both the But furthermore, because station 40 can be used to
tools 52 and 56 of combined tool 50. An example is Vex efficiently process, in a serial manner, multiple different
turntable bearing kit. See https//www.vexrobotics.com /276- samples, washing tool 52 can also be used to clean or wash
1810.html. This allows eitherthe gripper orwashing tool to 30 out sieves after they are used and prepare them for a next
address the turntable at any level or other locations on frame sample. For example, after a first soil sample is processed
41. witha set ofsieves, eachcouldbe serially movedby gripper
Therefore, as canbe seen in FIGS. 5Aand B, there is both arm 56 to a position on turntable 50 accessible by washing
up/down motion control ofthe combined tool 50 as well as tool 52, andthenproceedto wash each (including by tipping
rotational motion control. 35 if needed), to help reset that set of sieves by removing
Motion control motors can be operatively connected to artifacts from the last sample which could contaminate the
control circuit 80 and, via software, respond to a prepro- next sample, before using the same sieves for the next
grammed sequence ofmotion instructions for desired rota- sample.
tion and vertical movement. These motions can be con- 5. Gripper Tool Features FIGS. 5C-D
trolled to approximately an acceptable degree of precision 40 a. Function
for these functions in a repeatable manner. The fundamental use of gripper tool 56 is movement of
4. Washing Tool Features FIGS. 5A-D sieves to, within, and from station 40. Importantly, with
a. Functions particular reference to FIGS. 5C and D, an additional
The primary function of washing tool 52 is to present freedom ofmovement with motion control is built-in to tool
water to any sieve at any accessible location oftool 50. This 45 56.
allows not only assistance in sieving actionby moving water It canberotatedaroundahorizontal axis 59 foressentially
through material on a sieve but can also help wash offsieve a tilt function.
sidewalls during sieving so that items ofinterest are not left Thus, it also has open/close motion control of its jaws
behind. Furthermore, it can be utilized to clean out used aroundjaw axes 57 R and L. This allows gripping but also
sieves in preparation for processing ofthe next sample. 50 other such things as oscillation during sieving or washing,
b. Apparatus dumping or pouring, or otherwise.
As shown in FIGS. 5A and B, washing tool 52, in this b. Apparatus
embodiment, includes basically a hood enclosing a spray Thejaws oftool 56 are supported on meshed gears, each
arm 54. As diagrammatically illustrated in FIG. 5A, spray ofwhich rotates around an axis 57 R or L. A motor driven
arm 54 would be in fluid communication with a source of 55 shaft connected to one ofthe gears allows motion control of
pressurized water. On/off and flow rates can be controlled one gear. Because they are meshed, they work together, and
through control circuit 80. Tubing would be long enough to oppositely, for the open/closemovement.
allow for up/down and rotation of tool 52. Tool 56 is carried on a base mounted on gear 58 that
c. Features rotates around axis 59 relative to the linear bearing that
The washing tool canhave a diameterthat fits over any of 60 moves up and down the vertical post of the combined tool
the sieves' upper lip to retain spray when installed over a 50. By motor and drive gear attached to that linear bearing
sieve. (see FIGS. 5C and D), the larger gear 58 responds to rotate
Nozzles 55 (FIG. 5B) on a spray arm can be designed to thewhole grippertool 56 aroundaxis 59 forthetilt function.
direct a spray pattern that, by reaction forces on the interior It can include 360° rotation in either direction.
ofthe hood, causes arm 54 to spin on its own. This can also 65 c. Features
distribute the spray in an effective pattern to continuously Inside profiles of the gripper jaws are specifically
cleanthe sieve sides. Spray arm 54 freely rotates inresponse designed with a wavy profile to help center a sieve that is

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US 10,900,877 B1
17 18
grasped by the gripper. Minor variations in sieve diameters c. Features
are possible. Most sieves have a top edge lip that would Each level 62 has multiple receivers designed to each
allow the gripper arms to open and that close around the receive and hold a sieve 27. In this example there are four
diameter ofthe sieve body, while the larger diametertop lip differentreceivers 64 pertray 62. That canvary andbemore
is a mechanical stop against the sieve falling through those 5 or less than four. Each level thus can hold four sieves in this
closed arms when sufficiently closed. embodiment. But it is noted that not all receivers need to
The gripperjaws can open sufficientlyto laterallypass by holda sieve for a cycle ofoperation ofextraction station40.
the greatest diameter of the sieve and then close to gently Thejaws ofeach receiver 64 are fixed to allow a sieve to
surround a sieve yet retain it for vertical movement or be dropped vertically into the complementary space ofeach
tipping purposes. The jaws are then reopened to slide pass receiver.
the greatest diameter of the sieve and release it in a given As can be appreciated, the number of levels 62 and the
position. numberofreceivers64 canvaryaccordingtoneedordesire.
Non -limiting examples ofcomponents that can be usedto In this example, three levels are used with four sieve
implement the foregoing for gripper 56 are as follows: receivers each, which is deemed sufficient for processing
1.00 " Bore 32 Pitch Aluminum Hub Gears. Part #: 615234 SCN cysts and eggs according to the present embodiment.
from Servocity. Diameter: 3.125". Number of Teeth: As can be further appreciated, each receiver 64 and each
100. See https://www.servocity.com/32p-1-00-bore level 62 cooperates with gripper tool 56 such that any
aluminum -hub-gears (incorporated by reference receiver 64 canberotatedto have its center axis alignedwith
herein 20 the center axis between the gripperjaws when gripper tool
Motor. S3305 Servo from Servocity. Specifications: 56 is appropriately rotated. This allows gripper tool 56 to
Dimensions: 1.6 "x0.8 "x1.5" (41x20x38 mm ). Product place orremove a sieve from any receiver 64 from any level
Weight: 1.64 oz. (46.5 g). Output Shaft Style: 25 Tooth 62 by correlated vertical movement and rotation of the
(3F) Spline. Voltage Range: 4.8V-6.0V. Stall Torque whole turntable 50.
(4.8V): 99 oz/ in. (7.1kg.cm ). Stall Torque (6.0V): 124 25 Likewise, washing tool 52 can be operatively positioned
oz/in . (8.9 kg:cm ). PulseAmplitude: 3-5V. MotorType: on center to any receiver 64.
3 Pole Ferrite. Potentiometer Drive: Indirect Drive
Output Shaft Support: Dual Ball Bearings. See: https:// Non-limiting examples ofcomponents that canbe usedto
www.servocity.com/s3305-servo (incorporated by ref achieve the foregoing functions include:
erence herein ). Turntable Stage System
1/4 " Stainless Steel Precision Shaft. Part #: 634160 from Motor. Vex Robotics, 2 -wire Vex Motor 393. See https://
Servocity. Length: 2". See: https://www.servocity.com/ www.vexrobotics.com/motors. html (incorporated by
0-250-1-4-stainless-steel-precision-shafting#371=246 reference herein). Specifications: Free Speed:100 rpm .
5 mm Bore 32 Pitch, 16T Shaft Mount Pinion Gear. Part Stall Torque:1.67 N-m (14.76 in-lbs). Stall Current:
#: 615342 from Servocity. Number of Teeth: 16. See 35 4.8A. Free Current:0.37A .
https://www.servocity.com/5 mm-bore-32p-16t-shaft
mount-pinion -gears. Vex Turntable Bearing Kit. See https://www.vexrobotics.
com /276-1810.html
Swivel Hub. https://www.servocity.com/swivel-hub.
0.770" Pattern Set Screw Hubs. Bore: 14". https://www.s- Used in: Linear Motor System, Turntable Stage System
ervocity.com/770-set-screw-hubs 7. Grinder Tool Features FIGS. 7A - B
12" Bore 32 Pitch Aluminum Hub Gear. Part #: 615190 a. Functions
from Servocity. Diameter: 1.5". Number of Teeth : 48.
https://www.servocity.com/32-pitch-50-bore-alumi- The primary functions ofgrinder 70 are to provide rotary
num -hub-gears. press action on top of material on a sieve. In the specific
As will be appreciated, the open/close and tilt functions 45 exampleofSCN, itis particularlyvaluableininfluencingthe
can be accomplished in other ways. bursting of the cysts to release their eggs. By bringing a
6. Turntable Stages Features FIGS. 6A-B rotating grinding pad 72 towards the sieve screen, calibrated
a. Function to come no closer than a minimum distance, the rotary
Theprimary function ofturntable 60 is to providevertical grinding andup-and -downpressing action onthe cysts have
co-location of sets of sieves of increasinglysmaller screen 50 been found to promote such egg release.
size. To do so, turntable 60 is designedto rotateplural levels In the present embodiment, grinding system 70 can both
62 T, M, and B (FIG. 6B) around a vertical axis 63. As will provide grinding pad rotary motion around axis 73. But it
be discussed below, programmed sequenced operation, by can also, through a gearing arrangement, provide up/down
motion control, allows manipulation ofa set ofsieves 27 for movement of pad 72.
this purpose. b. Apparatus
b. Apparatus
The nonlimiting example of a turntable in FIGS. 6A and As indicated in FIGS. 7A and B, both rotation and
B shows how each level 62 can be mounted on its own linear up/down movement of pad 72 are accomplished through
bearing along vertical post. In a similar fashion to up/down mechanical means. A motor provides rotary action that can
movementofcombinedtool 50 onitsverticalpost, asimilar 60 beconvertedbygearingtothepadrotation. Itcan also have
rotary geared and motorized bearing could be operatively a controlledup and downtravel range. This canbe calibrated
installed onthe linearbearing at each level 62. Motors could relative to a grinding vertical axis generally along 73 to
turn the entire combination in synchronization. Alterna automatically move down into a sievebutnot getcloserthan
a minimum distance.
tively, each level 62 could have independent rotation.
FIG. 6A shows this embodiment has four sieve receiving 65 One non-limiting example is utilization of essentially a
jaw sets 64 (1)-(4) at each level 62. Eachreceiver 64 is sized drill press. This provides both rotary and up/down move
to receive and hold a sieve 27. ment at its working tool end.
40
55

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US 10,900,877 B1
19 20
c. Features rotated back in line with the grinder for the second and third
Features ofthe grinder can include the following: press actions, with the rinse between each.
a. Not only is there rotational action ofpad 72, there can Anoptional enhancementcouldbevibration. Byeccentric
beanup -and -downmotionofpad72 by gearingraising weightedmotors appropriatelymountedandoperated, entire
and lowering the rotational axle of pad 72 during 5 turntable 60 or the entire extraction station frame 41 could
operation. be vibrated intermittently or continuously during the grind
b. There canbe up motionoftop level 62T ofturntable 60 ing process to also promote movement ofreleased eggs to
towards grinder pad 72, if enabled at turntable 60. the # 200 screen .
c. Motor and a gear system can allow selection of rota- Alternatively, there could be a dedicated sprayer installed
tional speed ofpad 72 over a range. at grinder 70 such that upon lifting or separation ofgrinder
Grinding tool 70 location on frame 41, and appropriate 70 from #60 sieve, the washing action could occur without
control ofplacement andmotion control ofa set ofsieves on having to rotate the turntable and operate the washing tool
turntable 60, allows grindertool 60 to enhance separation of 52.
SCN eggs from cysts to better produce an accurate account It is understood that both the up and down movement and
of eggs from the sample. rotation around the vertical posts on frame 41 can be
As can be appreciated, any sieve placed on top level 62T accurately and minutely controlled with such things as
of turntable 60 can be rotated to a position directly below stepper motors.
grinding pad 72. By controlling the vertical movement of Additionally, it is noted that grinder 70 has an almost
pad 72 and/or level 627, the pad 72 can be gradually 20 infinitely adjustable set of operating parameters. For
converged to the surface ofthe sieve, while spinning. example, pad rotation, distance ofraising and lowering, and
In this embodiment, a rubber pad (~6 inch dia. to match speed ofraising and lowering can be adjusted according to
need or desire.
internal diameter ofsieves 27 and the consistency ofrubber
stoppers used in laboratory flasks) is fixed to the grinder 8. Control Subsystem Features FIGS. 8A-B
a. Function
rotating plate 162. As noted, it is slightly offset (0.0050 in.) 25
from the rotational axis 73 of the grinder rotating shaft. It The overriding function of the control sub circuit 80 is
works like an orbital sander or grinder. motion and other control (see also FIGS. 3A and B) to
At 500 rpm , rubber pad 72 is moved towards and away effectuate a sample cycle according to this embodiment.
from the material on the sieve screen in an up/down press Conventional techniques of programming can be accom
action. In one example,grindingoccurs for 30 secondsand 30 plished by the designer to adjust operatingparameters.
then pad 72 is lifted. This is repeated two more times. b. Apparatus
Importantly, it is calibrated to never converge to the sieve FIGS. 8AandB present details about a control subsystem
screen surface. Cysts are approximately 200 um in largest 80 with software programmabletoaccomplish the foregoing
functions as indicated at FIG. 8B.
dimension, whereas eggs are much smaller, more on the
order of 20 um . Therefore, pad 72 vertical movement is 35 In this embodiment, electronics 80 are mounted at the top
of frame 41. Software is selected with the components of
calibrated to move closer than 200 um but never get closer
thanabout 20 um or so (usually a bit larger), to influence the circuitry 80 to effectuate the functions described herein.
bursting orrelease ofeggs fromthe cysts without destroying FIGS. 8A and B provide more details regarding the
control circuit 80.
the form factors ofthe eggs so they will better be counted,
and also to avoid damage to the sieve screen. This distance 40 c. Features
Control circuit 80 can have discrete sections that are
control also protects against significant damage risk to the
expensive and sometimes very sensitive sieve screens and mounted at top of frame 41. This allows separation from
small pore sizes. By distance control, keeping the orbitalpad water and mechanical movement. It can also make them
72 from coming into substantial contact with the top ofthe more accessible for testing and maintenance.
screen of the sieve deters the forces of the grinder from 45 FIG. 8B illustrates the type of functionalities 81 which
deformingthe screenpore sidewalls ormesh. Consistentand circuit 80 canperform . Software is used in conjunction with
correctpore size openings are critical to goodfiltering.Also, components in circuitry 80.
replacement ofthese expensive components is deterred. Those skilled in the art will appreciate that the functions
Such overall grinding process can take around can take canbe achieved in differentways with different components.
several minutes in this example around 6 minutes total). It 50 The designer can select those according to need or desire.
is working with a still somewhat “dirty sample” inthe sense Non-limiting examples ofcomponents thatmight beusedto
that it is a raw soil sample that has gone through only one implement configurations such as described are indicatedby
sieve at that point. vendor and model and/or selected relevant operating speci
fications.
One technique that can enhance this operation is as
follows. After each press action, the sieve and rubber 55
grinding surface can be separated sufficiently that the top
level 62T ofturntable 60 is rotatedto the side ofthe washing Example of Controller 80
Arduino Uno Controller Board from Arduino. Specifications:
station, washing station52 is lifted, rotated, andthenpressed
down on the sieve, and a washing action occurs. Since the Microcontroller ATmega328P
#200 sieve screen remains below the #60 screen during this 60 Operating Voltage
Input Voltage (recommended)
action, it influences eggs that have been released from the Input Voltage (limit)
cysts throughthe #60, by gravity andwithflow ofthewater, Digital I/0 Pins 14 (ofwhich 6 provide
into the #200. It also tends to remove material from the side PWM output)
of the #60 sieve. This also enhances quantification by PWM Digital I/O Pins
Analog Input Pins
promoting capture of all or as many ofthe eggs as possible 65 DC Current per I/O Pin 20 Ma
from eachsample.Oncewashinghas completed, thehood of DC Current for 3.3 V Pin
washing tool 52 is lifted from #60 sieve and turntable 60
5 V
7-12 V
6-20 V
6
6
50 Ma

SRAM
EEPROM
LED BUILTIN
16 MHz
13
68.6 mm
53.4 mm
25 g
20
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US 10,900,877 B1
21 22
-continued 3. #60 Sieve Moved by Gripper to Under Grinder at Top
of Turntable - FIGS. 9A and 9D
Example of Controller 80 As shown in dashed lines, the next step is to have gripper
Arduino Uno Controller Board from Arduino. Specifications: tool 56 grab and lift #60 sieve withthe cysts fromthemiddle
Flash Memory 32 KB (ATmega328P) 5 turntable level, rotate #60 away from the perimeter of
of which 0.5 KB used by turntable 60, and then rotate turntable and raise #60 into the
bootloader top empty receiver on the top level 62T. The # 60 sieve is
2 KB (ATmega328P) then rotated opposite from the side of gripper tool 56 to
1 KB (ATmega328P)
Clock Speed directlybelow grinderpad72. The #200 and#500 sieves are
10 in position underneath the #60.
Length 4. Cysts on #60 Release SCN Eggs under Influence of
Width Grinder to #200 Sieve Below It— FIGS. 9A and 9E
Weight
As explained, vertical distance between the #60 and
rotating grinder pad 72 can be minutely adjusted during
See https://www.arduino.cc/en/Main/ArduinoBoardUno 15 grinder pad rotation to effectively burst the cysts contained
(incorporated by reference herein ). in the #60. This spills out the SCN eggs from the cysts. The
Arduino Adafruit Motor/Stepper/Servo Shield for Ardu- #60 is intentionally selected to pass the eggs to the #200
ino v2 Kit- V2.3. below it but retain larger, non-egg objects and debris in a
PDF of Spec Sheet: https://cdn-shop.adafruit.com/ substantial manner.
datasheets/TB6612FNG_datasheet_en_20121101.pdf 5. Washing Influences Eggs Through #200 to #500 Sieve
URL: https://www.adafruit. com /products/1438 Below It— FIG . 9A and FIG. 9F.
Controller Communication . Grinding and washing influences sieving of materials
Bluetooth Module. Transceiver Module HC-06 from Sun through #60, onto #200 below it, andthen to #500 below it.
The sieve sizes are selectedto promote passage ofSCN eggs
founder. See:
25 to the top of #500, where they would not pass.
https://www.sunfounder.com/bluetooth-transceiver-mod
ule-hc-06 -rs232-4-pin-serial.html and https://www. To optionally assistthe foregoing step, somevibrationcan
be imparted to eitherthe #60 sieve or entire turntable 60 (or
sunfounder.com/wiki/ overall frame 41). One example is an eccentric vibratory
index.php?title= Bluetooth_Transceiver_Module_HC motor operatively connected to effectuate the same.
06 (both incorporated by reference herein ). Another option is to rotate the #200 over to washing tool
D. Operation 56.
One example of SCN extraction using extraction station In any event, and it has been found that grinding and
40 is diagrammatically depicted at FIGS. 9A-9F. Is to be gravity are effective to consistently filter SCN eggs into the
understood that FIG. 9A, in a single drawing, shows the #200 sieve below the #60, and then further filtering SCN
sequential steps. FIGS. 9B-9F are enlargements in isolation 35 eggs through #200 into #500, where they would notpass.
ofeach step. 6. Eggs Collected on #500 are Dumped into Container by
1. Raw Sample into #20 Sieve — FIGS. 9A and 9B Gripper Arm -FIG . 9A and FIG. 9G.
Asamplecontainer56 holding aninput sampleofraw soil As shown, the final step is, using rotation ofturntable 60
ofaconsistentvolume canbe grabbedbygrippertool 56 and over to gripper arm 56, grabbing the #500 and pouring into
moved and tipped to pour its contents into a sieve #20 40 an output sample container.
rotated, as shown in the upper right-hand ofFIG. 9Aand in As canbe seen, extraction station 40 cantake a relatively
FIG. 9B. As can be seen, sieve #60 is automatically under- dirty sample, meaning a soil sample without substantial
neath onthe secondlevel 62M ofturntable 60. Once sample pre-processing, and in a relatively short time (~6 minutes
is poured into top sieve, the sample container is removed, total) aftermerely suspending the soil sample andwaterand
and the extraction process continues. 45 letting it rest for 5 to 10 minutes, strain out a substantial
As can be appreciated with reference to FIGS. 3A, 3B, amount of irrelevant material at #20 with the washing tool
and 4A, controlled movement and operation of each tool 52. Washing tool 52 can be compressed and clamped over
relative to the sieves and their contents can automate extrac- the top of #20, and with water flow control, wash the eggs
tion of SCN eggs from a raw soil sample. through and deter sieve damage. A minimum flow rate is
As will be further appreciated, enhancement of such 50 basically enough to spin the washer spray nozzles.
processes with the rinsing tool 52 and other optional uses of The first strained material is moved to the top of the
water would require operative connection to a source of turntable 60 by gripper 56, grabbing and removing it from
water and controllable delivery as to pressure and quantity level 62M, rotating turntable 60, and gripper 56 placing the
at those locations ofextraction station 40 (see diagrammatic #20 in the top level 62T and aligned with the grinder 70.
depiction at FIG. 5A). Then, grinding action, both rotary and up-and-down but
2. FIGS. 9A and 9C neverdownto the sieve screen, bursts the cysts onthe screen
Withreferenceto middle andtopofFIG .9AandFIG.9C, and forces SCN eggs through #60 down to #200 below it.
sieve washer tool 52 is rotated and raised, and then lowered Furthermore, #200 passes eggs to #500 below it for a further
over sieve #20. Spray arms are activated with valved water. straining or purifying step. Smaller debris and water passes
The raw soil sample is wetted, and the sides ofthe sieve are 60 through #500. The eggs on #500 are collected and moved
cleaned offto instigate a first sieving step through the #20 into an output sample container.
screen. As is well known in the art, this tends to pass E. Quantification Station 29 (FIG. 2B and FIGS. 10-19)
nematode cysts and eggs, as they exist in soil, to #60 sieve. As indicated, another feature according to the embodi
The washing tends to suspend the larger, non-SCN items ment is quantification ofitems ofinterest, ifdesired. It can
suchthat cysts and eggs pass through and are caught on #60 65 also be used with any starting collected sample. It does not
sieve. Water and smaller particles pass through the #60 to a require use ofextraction station 28. Non-limiting examples
recovery tray or tank. of several techniques are now described.
55

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23 24
1. Example Overall Method (FIG. 10) SCN eggs fall in the same distance from the bottom ofvial
FIG. 10 illustrates a specific method 100 of how the 110 (e.g., in this example approximately 20 to 40 mm from
output sample from FIG. 9G can be quantifiedto produce an the bottom). Comparison to controls have revealed this
estimated SCN egg count related to the starting given stratification occurs over a range of test conditions. Filter
volume soil sample. Method 100 includes two different 5 papers 116 with samplings fromvial strata 111, 112, and 113
counting options. One is a scanner-based technique 102 to are also shown.
use image recognition to count SCN eggs in an automated Thus, this pre-processing step can essentially provide a
fashion. Another is a microfluidic lens-free or lensless photo relatively quick and non-complex way of isolating the
detector array video technique 104. FIG. 10 sets forth the objects of interest. This can improve image recognition by
basic steps of each. eliminating a lot ofother particles that could produce false
The fundamental purpose ofquantificationmethod 100 is negatives.
to produce an automated estimate ofobjects ofinterest from
anextracted sample.Nonlimiting examples are sub routines An optional feature is to utilize other fluids (e.g. sucrose
102 (scanner-based image recognition) and sub routine 104 or other density gradient solution) in the sample solution.
(microfluidic video image reconstruction ). Graph 130 of FIG. 13 shows how utilizing OPTIPREPTM
Basic steps of each are set forth in FIG. 10. Both follow (commercially available) as a part or percentage of the
basic pattern recognition through an acquired digital image solution can enhance egg recovery ratio from that strata 112
or images. after centrifugal action. OPTIPREPTM is a gradient density
Certainaspects developedbythe inventors enhance either chemical. FIG. 13 shows how it can improve density sepa
of these processes, as will be discussed below. 20 ration in the case ofSCN eggs. It is notedthat following the
The end result is an automated way ofproducing a count pre-processingdensity separationtechniquedescribedabove
of objects of interest automatically that can be put to likely will not recover 100% ofthe SCN eggs in vial 110.
beneficial use. But through calibration and control procedures, FIG. 13
As indicated in FIG. 10, either approach 102 or 104 is shows that even with manual removal with a pipette, a
conducted in an iterative fashion . Pattern recognition of 25 consistent 80to 90% ofeggs arerecovered. This is important
discrete portions of the static image or by comparison of because testing indicates this is consistent enough to use as
frames of video enhance the accuracy of counting small a compensation factor when estimating the final SCN count
objects of interest. At each iteration, a count is made, an for the starting soil sample. A 20% count is added back in to
inquiry is made ofwhether a further loop is needed . See sub each final count. Because absolutely accurate quantification
routine 106. Once all relevant images are reviewed by the 30 is not required forusefulness ofthis embodiment (but rather
software, a final count from the iterations is made. Sub placement of the count within a set of ranges that have
routine 108. relatively large distributions), using this compensation fac
As illustrated in FIG. 13, proof of concept on the 80 to tor allows not only acceptable, but statistically significant
90% recovery of eggs is shown. estimations ofactual egg quantity from a given soil sample
A description of quantification techniques 102 and 104 35 by that adjustment.
from FIG. 10 follows. In preparation for scanning, this embodiment distributes
2. Counting by Static Image Recognition (FIGS. 11-16) extracted solution from strata 112 of vial 110 across com
a. Function mercially available filterpaper 116. FIG. 11B. Serving as an
The fundamental technique ofscanner-based patternrec- imaging substrate, these inexpensive sheets (a stack ofthem
ognitiontechnique 102 ofFIG. 10 is preparing the sampleto 40 is shown to the left in FIG. 11B) have a pore size smaller
be imaged in a way beneficial to good image recognition. A than SCN eggs but would absorb fluid in the solution as it
static substrate on a scanner bed with the sample to be is distributed across its surface.
processed proceeds according to conventional image recog- As indicated in method 150 of FIG. 15A, quantification
nition procedures. This will be discussed below. would proceed by loading the filter paper with the distrib
b. Apparatus 45 uted sample into a scanner housing (FIG. 15B). As diagram
FIGS. 15A and B illustrate in a highly diagrammatic matically illustrated in FIG. 11B, scanner 157 can be pro
manner a non -limiting example ofsuch a method 150 and a grammedto zoom in on discrete areas ofthe surface offilter
set-up 156 for scanner-based imaging and its operation. paper 116. Static images ofeach such block 117, (1, 2, ...
c. Features x) (for example 323 across the surface), one at a time, to
Inthis example, several pre-processing enhancements are 50 enhance resolution of shapes for pattern recognition.
utilized. A sample on filter paper (step 151 of FIG. 15A) follows
First, the extracted sample (sieved sample with objects of a scan sequence of a block at a time (step 152) storage of
interest) is suspendedin solution. Inoneexample,itismixed each block image (step 153) and continue until all 323
with water and placed in a vial 110. FIG. 11A. That solution blocks have been imaged.
is then centrifuged (~2 min.). It has been found that good 55 By appropriate pre-programming, image recognition soft
separation of items of interest from water and other mate- ware 158 (FIG. 15B) would evaluate each block for pre
rials can be achieved. As diagrammatically illustrated in programmed patterns indicative of SCN eggs. For each
FIG. 11A, inthe case ofSCNeggs, theytendto floatrelative pattern recognition, a count would be incremented (steps
to water and other materials. Centrifugal action tends to 154A and B).
stratify them between water 111 at the top of vial 110 and 60 Pattern recognition would proceed for all blocks and,
denser materials at the bottom at 113. Thus, an intermediate once complete, a final cumulative count is stored (step 155).
zone 112 contains most of the SCN eggs. As diagrammatically illustrated in simplified fashion in
Testing has validatedthe same. Thephotos andassociated FIG. 15B, pattern recognition techniques would allow dif
graphs 120 of FIGS. 12A-F show various results. In each, ferentiationofSCN eggs E1, E2, En, from otherparticles
the starting mixture priorto such centrifugal action is shown 65 or materials, denoted as debris D1, D2, ..Dm . See
to the left. After centrifugal action the density separation is reference number 159 in FIG. 15B. Parameters for shape or
plainly apparent. The graphs show that a large majority of pattern recognition for SCN eggs can be based on criteria

USPTO Patent for an Ag Robot to process soil

USPTO Patent for an Ag Robot to process soil

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