e-Agri: How might we link sensors, systems and networks ... · PDF filePhotos courtesy of Syngenta ... Business School e-Agri integration consumer products ... fully integrated meta

www.manchester.ac.uk/eee/e-agri

Sensors and sensing technologies for effective land management:

production agriculture and the environment, Henfaes Research

Centre, Bangor University, Gwynedd, Wales. 29th June 2016

Prof Bruce Grieve, e-Agri Sensors Centre, E&E Engineering,

University of Manchester

e-Agri: How might we link sensors,

systems and networks for best effect?


Why are Sensors & ICT important to Agri-Food?

Ubiquitous!

Legislative & Regulatory

Market Forces

Technology

City Planning

www.manchester.ac.uk/eee/e-agri Photos courtesy of Syngenta

The e-Agri concept is unique as it seeks

to inform the electronics & IT community

of the distinctive needs of modern

agronomy & food science…

... So that they can fundamentally

engineer new systems and “e-” devices

for reducing waste, increasing yields and

improving nutrition.


Stakeholders = exploitation

seed breeders

crop protection

businesses

grain processors

retailers

fuel processors

distributors

food processors

arable farmers

government

Science & Tech R&D = technology push

physics

chem eng

plant sci

biology

mechanical eng materials eng

comp sci

Business School

e-Agri = systems integration

consumer products

processors maths

Business & Social R&D = market pull

regulators

consumers

ICT, energy & electronics providers

textile processors

furtigation businesses

food tech

agronomy

Ext Res

Sustainable Consumption Institute

chemistry

livestock

dairy

levy bodies

NGOs

Brooks World

Poverty Institute


“CHEAP & CHEERFUL” (Prof Lutz Plümer, University of Bonn, Germany)

Smart, Ubiquitous, Agri-Electronics


Sensors for protecting

crop YIELD

Exemplar: ‘Syield’

A Mimic-Sensors for Predicting Sclerotinia Outbreaks in Oilseed Rape

Implications for Sub-Soil?


Current Methods Have Drawbacks

● Current methods:

- Field walking (manual and late disease detection)

- Satellite / aerial imaging (sporadic and very late disease detection)

- Weather models (limited accuracy)

• German Sklero-Pro prediction model

• Petal kit test (Syngenta France)

● Motivation:

- Current sensing techniques are too late to effect a CP treatment

- Early sensing enables appropriate CP formulation cocktail to be

delivered to prevent yield losses + Wide area forecasting

• Avoid ad-hoc spraying

● Approach:

- In field sentinel sensors linked to cellnet grid & IT

infrastructure


Early Adoption of Technology Platform: Sclerotinia in Oil Seed Rape

Can germinate on plants but not infect without

exogenous source of nutrients

Oxalic acid is required for pathogenicity

Can penetrate using a variety of mechanisms

Sclerotia can survive up to 8 years in the soil


Grow Measure Capture

Stealing Translating the Diabetes Tech

● Oxalic acid, produced by the incubating spores, can be detected using

enzyme technology which is similar to that in blood glucose sensors

● Oxalate oxidase catalyses the reaction:

HOOC-COOH + O2→ 2CO2 + H2O2

● Horseradish peroxidase catalyses the reaction:

H2O2→O2+ 2H+ + 2e-

● Electrons are picked up by the sensor electrodes, generating current.

● Signal converted into risk prediction.


What is “SYield”?


Integrated Farm Package: 24/7 Cover


Towards Precision Agriculture

● Syngenta’s Adjacent Technology

- First Biotic stress sensor – in Sclerotinia

- Utility in carrot, sunflower, soybean

● Opportunities for expansion into new families of

Pathogens and their hosts

- Rusts, Fusarium

● Development of not just the sensor biology but

fully integrated meta data & information flow

● Can the concept of a mimic sensor be

translated under the soil?

- Tricking a pathogen or pest and sensing

it’s interaction with the soil or

rhizosphere


Vision: Linking sensors, systems and networks

Exemplar: Above & Below Ground Monitoring for Every Lab & Field

IBERS– above ground screening

Multiple parameters

High capacity

Detailed screening

But

Greenhouse = limited environment control

water; limited temp control (slow response)

Slow turnover time (long measuring time)

Plants moved to measuring station

Existing UK crop analysis systems:

Nottingham – root screening

X-ray CT based system

High resolution

Can screen large plants

But

Limited capacity

High cost – not practical on a commercial

scale (e.g. breeding


Delivering the Above Ground part: Origins - UoB Hyperspectral System

Line scaner


How?: Optical Processes Within Plant Leaves

fluorescence


What?: Hypercube Images

Source: Principles of Hyperspectral Imaging Technology, Elsevier, 2010


1.16 * (R800-R670)

(R800+R670+0.16)

Exploiting Plant’s Natural Sunscreen


Early Prototype Light Board

● Contains over 1000 LEDs

● Designed to measure

530nm, 570nm, 670nm,

735nm, 830nm

● LED spacing designed to

give uniform illumination over

field of View

● Bright light source enabling

faster image acquisition


Cercospora leaf spot on Sugarbeet

𝐶𝐿𝑆 =𝑅698 − 𝑅570𝑅698 + 𝑅570

− 𝑅734 RGB CLS


Syngenta Plant Speciation: Hyperweeding - Weed Control

● Weed control is becoming increasingly difficult due to herbicide

resistant weeds and restriction of herbicides due to higher regulatory

demands

● Resulting problems:

- In cereals, resistant blackgrass a severe problem with no good

solution. Other examples worldwide

- Weed control in minor crops, such as vegetables, now extremely

problematic as older herbicides have been de-registered

- In general active ingredients being rate restricted at sub optimal

rates

● There is an urgent need to examine alternative or complimentary

technologies for weed control to allow growers to grow crops

profitably

● Directed treatment is one such technology


Spin-out: to Protein Control


Spin-out to Smallholders Farmers

Handy Hyperspectra: Crop

stress sensing on your phone

● 120M Smallholder farmers in

India (480M worldwide)

● 1 in 10 have smartphones and

full internet connectivity

● Add a cheap attachment to

turn phone into hyperspectral

imager

= 12M possible customers

now for agricultural

management packages!


Case Study - Cassava

Gates Foundation in Africa

In Partnership with


Africa’s Main Source of Carbohydrate

• The cassava plant gives the third-

highest yield of carbohydrates per

cultivated area among crop plants

• Cassava plays a particularly

important role in agriculture in

developing countries, especially in

sub-Saharan Africa, because it

does well on poor soils and with

low rainfall

• Perennial crop so susceptible to viruses

• Mosaic Virus is now considered one of the

most damaging crop viruses in the world.

Annual economic losses in East and

Central Africa are estimated to be

between US$1.9 billion and $2.7 billion

Source: J. Molecular Plant Pathology, 2009

https://en.wikipedia.org/wiki/Carbohydrates


Whitefly – Spreading the Virus West

Source: Makerere University, Uganda, 2012


Science in Action: Research into Whitefly Spread


Automating Disease Spread Studies

“Mcrops”

• Ernest Mwebaze,

• School of Computing &

IT, Kampala, Uganda

But it cannot tell which

Whiteflies are carrying

the virus


Early Results: Translate to Blue Tongue in Livestock?

3-Band Classifier, 4 x Replicates (vertical column) for Australia, Africa & Latin America adult B. tabaci. (a) All, (b), Australia only, (c) Africa only

B

A

C


The Current ‘Alpha’ Handheld Unit

0

1 104

2 104

3 104

4 104

5 104

6 104

400 500 600 700 800 900

Wavelength (nm)

Inte

nsity (

arb

. U

nits)

• 20 Discreet Wavelengths

• Hand-held

• Wi-Fi Connectivity

• Battery Powered

• Automatic Imaging Sequence


62 Waveband ‘Bravo’ Desktop Unit Wavelengths (61 narrow + 2 x white): 365-370,

370-375, 375-380, 380-385, 395-400, 400-405,

(405-410 x 2), 410-415, 415-420, 420-425, 425-

430, 430-435, 435-440, 445-450, 450-455, 455-

460, 460-465, 465-470, 470-475, 475-480, 480-

485, 485-490, 490-495, 495-500, 500-505, 505-

510, 510-515, 520-525, 525-530, 585-595, 595-

600, 600-610, 620-630, 640-650, 650-655, 655-

665, 670, 680, 690, 700, 710, 720, 730, 740,

750, 760, 770, 780, 790, 800, 810, 830, 850,

870, 880, 900, 910, 940nm, warm white, cool

white


Texture Profiling Comes Free? HSI Affected

by Lighting

Angle

Make that an

advantage – ‘2.5D

Imaging’

Image courtesy of I Hales, (Univ West England)

Image courtesy of L. Plümer , (Univ Bonn)


Fluorescence Imaging Comes Free?

Image courtesy of J. Scholes, (Univ Sheffield)

RGB / NIR

Sensor Response

LED Response

PSII: Photochemical

& NPQ Imaging


GPS

Camera

Micro Processor

Web linked

+ Subtle light manipulation

= Active Close-Proximity

Hyperspectral Imaging

Fluorescence Imaging

Stereo photometric

Imaging

Solid State Active

Ellipsometry

• Crop disease sensing

• Early weed / plant

detection;

• Speciating insect

disease-vectors;

• Carbon footprint

(protein in crops);

• Leaf viral symptoms;

• Harvested fruit

bruising & sugars

• Soil organic carbon

• Aquatic parasites

• Frogs in salads ...

The “Tricorder” for < US$100

Image courtesy of CBS Inc.


... Going Underground ...

Chemical plant

research…

…translated to

plant breeding


Electrical Impedance Tomography Background

What is EIT?


Delivering the Below Ground part: Origins – Droughting trials with UoN


Towards Subsoil Biotic Phenotyping

• Clubroot (Plasmodiophora brassicae) is an important pathogen of

Brassica crops including oil seed rape (OSR), both in the UK and

worldwide.

• Up to 10% of cultivated land worldwide is infected by clubroot and it is

found in all UK regions where OSR is grown.

• Identification of quantitative resistance requires quantitative measures

of plant responses to the pathogen which is particularly problematical

for below-ground diseases.

• Currently using phenomics

approaches to characterise above-

ground responses to this important

disease (thermography - IBERS).


ElT for Clubroot Infection Detection

• EIT to directly measure below-ground responses as a complementary

method of identifying quantitative resistance to clubroot infection in

Brassica crops.

• Infection leads to an inhibition of lateral root formation, repression

of xylogenesis, a localised induction of vascular cambium activity

leading to gall formation and altered water relationships, all of which

can potentially be measured and quantified using EIT.

• Cumulative water uptake measured on a daily

basis in control and plants inoculated with low

and high spore concentrations.

Control and P. brassicae-

infected Chinese var

Wong Bok 51 days post

inoculation


● Initially driven by the need to gauge ‘available soil moisture for Sub-

Saharan Africa: Collaboration 2013 with Leeds Africa College

● Solid hydrogel formulations engineered to draw upon available soil

moisture in a similar manner to plant roots

- Low cost optical detection of NIR water bands

- Surface engineered to emulate surface area of mycorrhizal fungi

and mimic key elements of plant / fungi symbiosis

● Wireless prototype node delivered 2013 but suffered cross

interferences with soil electrolyte content…

Foundation: Soil Moisture Sensing


● Sensor layout

€50 Cellar Networked Sensor nodes for soil phenotype mapping

MCU

(TI MSP430)

Analogue Front End

(MAX11300)

SPI

GSM

(Sierra Wireless

HL6528)

UART Antenna Power regulation /

conditioning +/- 7.5V 3.3 V

Li-Ion cell

Energy harvest

controller module Solar Panel

Gnd

Vout+ Vout- Vin+ Vin-

Sns+ Sns-

3.7 V

DC Supply

(for initial charging)

T0

SPI

Temperature

sensing

SPI

SPI

SPI

T1

T2

T3

● Systems Architecture


iMAGiMAT™: SARIC

Proposal on livestock

protein conversion and

gait monitoring – linked to

biometric analysis of pigs.

AB-Agri, Bristol Robotics

Lab, SRUC

e-Agri: … a Few More Examples.

Pollinator

and Insect

Pest

Scanning:

Optical back

scatter

analysis of

iridescence

of insect

wings – ‘N2’

concept with

Lancaster

(c/o Andrew

Wilby)

Saturn-Sense: MIP sensors for P

measurement (+ N, Ca, S, Mg, etc.)

within hydroponics


Linking Remote & Local Sensor Networks: STFC FoodNetwork+

GCRF (£m) (£m)

Resource

Body/programme 16/17 17/18 18/19* 19/20* 20/21* SR

Total

National Academies 11 11 11 11 11 45

AHRC 5 7 7 7 7 25

BBSRC 10 20 20 20 20 70

EPSRC 10 15 15 15 15 55

ESRC 5 10 10 10 10 35

HEFCE 20 37 37 37 37 130

MRC 14 34 34 34 34 115

NERC 5 10 10 10 10 35

STFC 0 4 4 4 4 11

International Partnership Programme

32 30 30 30 30 122

Unallocated GCRF 0 38 122 216 315 377

Totals 112 215 299 393 492 1,019

http://www.stfc.ac.uk/funding/research-grants/funding-opportunities/global-challenge-networks/

Prof Sarah Bridle: [email protected]










mailto:[email protected]


Questions

http://www.ukppn.org.uk/hyperspectral-imaging-workshop/






Documents

e-Agri: How might we link sensors, systems and networks ... · PDF filePhotos courtesy of Syngenta ... Business School e-Agri integration consumer products ... fully integrated meta