Smart Farming Technology Trends: Economic and Environmental Effects, Labor Impact, and Adoption Readiness

Abstract

Farming faces challenges that increase the adverse effects on farms’ economics, labor, and the environment. Smart farming technologies (SFTs) are expected to assist in reverting this situation. In this work, 1064 SFTs were derived from scientific papers, research projects, and industrial products. They were classified by technology readiness level (TRL), typology, and field operation, and they were assessed for their economic, environmental, and labor impact, as well as their adoption readiness from end-users. It was shown that scientific articles dealt with SFTs of lower TRL than research projects. In scientific articles, researchers investigated mostly recording technologies, while, in research projects, they focused primarily on farm management information systems and robotic/automation systems. Scouting technologies were the main SFT type in scientific papers and research projects, but variable rate application technologies were mostly located in commercial products. In scientific papers, there was limited analysis of economic, environmental, and labor impact of the SFTs under investigation, while, in research projects, these impacts were studied thoroughly. Further, in commercial SFTs, the focus was on economic impact and less on labor and environmental issues. With respect to adoption readiness, it was found that all of the factors to facilitate SFT adoption became more positive moving from SFTs in scientific papers to fully functional commercial SFTs, indicating that SFTs reach the market when most of these factors are addressed for the benefit of the farmers. This SFT analysis is expected to inform researchers on adapting their research, as well as help policy-makers adjust their strategy toward digitized agriculture adoption and farmers with the current situation and future trends of SFTs.

Full text

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Agronomy2020,10,743;doi:10.3390/agronomy10050743www.mdpi.com/journal/agronomy
Article
SmartFarmingTechnologyTrends:Economic
andEnvironmentalEffects,LaborImpact,
andAdoptionReadiness
AthanasiosT.Balafoutis
1,
*,FritsK.VanEvert
2
andSpyrosFountas
3

1
InstituteofBio‐Economy&Agro‐Technology,CentreofResearch&TechnologyHellas,
DimarchouGeorgiadou118,38333Volos,Greece
2
AgrosystemsResearch,WageningenUniversity&Research,P.O.Box16,
6700AAWageningen,TheNetherlands;frits.vanevert@wur.nl
3
DepartmentofNaturalResourcesManagementandAgriculturalEngineering,AgriculturalUniversityof
Athens,11855Athens,Greece;sfountas@aua.gr
*Correspondence:a.balafoutis@certh.gr;Tel.:+30‐2311‐257‐651
Received:18February2020;Accepted:18May2020;Published:21May2020
Abstract:Farmingfaceschallengesthatincreasetheadverseeffectsonfarms’economics,labor,and
theenvironment.Smartfarmingtechnologies(SFTs)areexpectedtoassistinrevertingthissituation.
Inthiswork,1064SFTswerederivedfromscientificpapers,researchprojects,andindustrial
products.Theywereclassifiedbytechnologyreadinesslevel(TRL),typology,andfieldoperation,
andtheywereassessedfortheireconomic,environmental,andlaborimpact,aswellastheir
adoptionreadinessfromend‐users.ItwasshownthatscientificarticlesdealtwithSFTsoflower
TRLthanresearchprojects.Inscientificarticles,researchersinvestigatedmostlyrecording
technologies,while,inresearchprojects,theyfocusedprimarilyonfarmmanagementinformation
systemsandrobotic/automationsystems.ScoutingtechnologieswerethemainSFTtypeinscientific
papersandresearchprojects,butvariablerateapplicationtechnologiesweremostlylocatedin
commercialproducts.Inscientificpapers,therewaslimitedanalysisofeconomic,environmental,
andlaborimpactoftheSFTsunderinvestigation,while,inresearchprojects,theseimpactswere
studiedthoroughly.Further,incommercialSFTs,thefocuswasoneconomicimpactandlesson
laborandenvironmentalissues.Withrespecttoadoptionreadiness,itwasfoundthatallofthe
factorstofacilitateSFTadoptionbecamemorepositivemovingfromSFTsinscientificpapersto
fullyfunctionalcommercialSFTs,indicatingthatSFTsreachthemarketwhenmostofthesefactors
areaddressedforthebenefitofthefarmers.ThisSFTanalysisisexpectedtoinformresearcherson
adaptingtheirresearch,aswellashelppolicy‐makersadjusttheirstrategytowarddigitized
agricultureadoptionandfarmerswiththecurrentsituationandfuturetrendsofSFTs.
Keywords:smartfarmingtechnologies;recording;reacting;guiding;farmmanagement
informationsystem;agriculturalrobots;automatedsystems

1.Introduction
AgriculturalperformanceintermsofproductivityledfarmingpracticesaftertheGreen
Revolutionofthe1950s,withlimitedattentionpaidtotherespectiveimpactonsustainability.
However,conventionalfarmingpracticesareatapointwhereagriculturalinputsareoverused,labor
isnolongerinabundance,andtheenergydemandiscontinuouslyincreasing[1].Newopportunities
areemerginginfarming,asaresultoftherapiddevelopmentofcommunicationnetworksandthe
availabilityofawiderangeofnewremote,proximal,andcontactsensors[2–6].Intheagricultural

Agronomy2020,10,7432of25
context,thesetechnologieshelpcaptureandtransmitgeo‐localizedreal‐timeinformationatlowcost
[7–10].Oncegathered,processed,andanalyzed,thesedatacanassistindeterminingthestateofthe
agro‐environment(e.g.,soil,crop,andclimate)and,whencombinedwithagro‐climaticand
economicmodels,technicalinterventionscanbeappliedatthefieldlevelbyeitherconventional
meansorautomated/robotizedsolutions[11].
Alltheseaspectsareundertheconceptnamed“smartfarming”thatrepresentstheapplication
ofmoderninformationandcommunicationtechnologies(ICT)intoagriculture[12–14].Theseinclude
variablerateapplicators[15–17],Internetofthings(IoT)[18,19],geo‐positioningsystems[20,21],big
data[22–24],unmannedaerialvehicles(UAVs,drones)[18,25],automatedsystems,androbotics
[26,27].Smartfarmingisbasedonapreciseandresource‐efficientapproachandattemptstoachieve
higherefficiencyonagriculturalgoodsproductionwithincreasedqualityinasustainablebasis[28].
However,fromthefarmer’spointofview,smartfarmingshouldprovideaddedvalueintheformof
moreaccurateandtimelydecision‐makingand/ormoreefficientexploitationoperationsand
management[29].
Smartfarmingtechnologies(SFTs)canbedividedintothreemaincategories:farmmanagement
informationsystems(FMIS),precisionagriculture(PA)systems,andagriculturalautomationand
robotics.FMISsrepresentmainlysoftwaresystemsforcollecting,processing,storing,and
disseminatingdataintheformrequiredtocarryoutafarm’soperationsandfunctions.Significant
researchworkwascarriedoutinthisareainthelast20years[30–33]andthisdevelopmentassisted
inhavingmanycommercialproductsalreadyonthemarketthat,inmanycases,showsignificant
economic,environmental,andsocialbenefits[28].
PAreferstothefarmingmanagementconceptaimedatoptimizinginputusebasedonrecording
technologiestoobserveandmeasureinter‐andintra‐fieldspatialandtemporalvariabilityincrops,
aimingtoimproveeconomicreturnsandreduceenvironmentalimpact[34].PAisabletoincrease
inputefficiencyformaintainingorevenincreasingproductionrate[35–37],usingremotesensing
technologiesfordatagatheringwitheithersatelliteplatformsforspaceimagery[38–40]or
aircrafts/UAVsforaerialapplications[41–43],combineduseofsensorsforgrounddataacquisition
[44],wirelessnetworksforinterconnectingthem[4,10,45,46],geospatialdataanalyticscomingfrom
differentsources[47],decisionsupportsystems(DSSs)foroptimizedfarmingdecision‐making
[48,49],andothers.
Reactingtechnologiesarebasedonagriculturalautomationandroboticsthatareseparate,but
closelyrelatedICTsectors.Inthecaseofopen‐fieldagriculture,theyareinterconnectedtocoverthe
processofapplyingautomaticcontrol,artificialintelligencetechniques,androboticplatformsatall
levelsofagriculturalproduction.Automationtechnologiesinagriculturefoundhighresearch
interestwithmachinelearningbeingthoroughlyusedforagriculturalpurposes[50–52],aswellas
computervisionandartificialintelligence[53,54],three‐dimensional(3D)imagery[55],and
navigationsystemsforoff‐roadagriculturalvehicles[56].Basedonthesedevelopmentsandonthe
industrialroboticstateoftheart,agriculturalrobotsofalltypeswereappliedinrecentyears[26,57–
59]withspecifictasks,suchasweedcontrol[60],harvesting[61],etc.
Attentiontowardsmartfarmingisgrowingrapidly,andseveralstudiesofthecurrentstatusof
SFTdevelopmentandadoptionrateamongfarmersworldwidewerereleased.Themostknown,due
toitscontinuousbi‐annualreleasefrom1997untiltoday,istheCropLife/PurduePrecisionAgSurvey
thatdealswithadoptionratesofcertainSFTsintheUnitedStates(US)andCanada,basedonretail
cropinputdealersregardingtheirsmartfarmingservices.Thelastversion(2019)[62]showedthe
increasinguseofdataforcropmanagementdecisions,withsensingtechnologyservices(soil
sampling,satellite/UAVimaging,yieldmapping)andvariablerateservicesbeingsignificantly
increasedincomparisontothepreviousedition(2017),presentingthecontinuousSFTadoption
incrementintheUS.
InEurope,wheresmartfarmingislessdiffusedthanNorthAmerica,SFTuptakeislessexplored,
whilemoststudiesarecountry‐specific[63].However,recentSFTadoptionresearchwasconducted
indifferentEuropeancountriestoalsoobservegeographicalandculturalcausesofreducedadoption
rates[29,63,64].Particularly,Barnesetal.(2019a)[63]consideredmachineguidanceandvariablerate

Agronomy2020,10,7433of25
nitrogentechnologiesasthemostsignificantSFTsforarablefarmingandconductedanempirical
examinationofuptakeinfiveEuropeancountries.Theyshowedthatfarmsizeandincomereflectthe
mostimportantbarrierstoadoptionforallcountriesunderinvestigation;furthermore,incountries
withsmallfarmsoflowincome,subsidyandtaxationwereconsideredthemainpositivedriversof
SFTuptake.Barnesetal.(2019b)[64]alsoidentifiedincentivesforSFTstobeadoptedinEuropeusing
datafromthesamefivecountriesasinReference[63],anditwasfoundthatcurrentSFTadoptersare
divergentfromnon‐adopters,whilethefirstadoptersareinfluencedbyeconomicandinformational
interventions.Increasingadoptionisconstrainedbyskepticismtowardeconomicreturnsandthat
EuropeanUnion(EU)policydoesnotrecognizecomplexityacrossdomainstoenableuptake.
Kerneckeretal.(2020)[29]alsoworkedontheadoptionoftechnologicalinnovationsinagriculture
byconductingasurveyinsevenEuropeancountriesandinfourcroppingsystems,andtheyshowed
thatadoptionincreaseswithfarmsizeinarablefarms.FarmersperceiveSFTasuseful,buttheyare
stillnotconvincedofSFTpotential.Ontheotherhand,expertsseemtobemoreconvincedofSFT
assetsandexpectalotfromSFTfuturedevelopment.Countryspecificitiesshouldbeconsideredto
improveSFTdiffusion.
EvenifadoptionratescanbeincreasedthroughoptimizationofSFTresultsandrelatedpolicies
andincentives,SFTscomeswiththeriskofreboundeffectsoftheiruseinagriculturalpractices.This
isbecause,evenifsmartfarmingisexpectedtoconsiderablycontributetoenvironmentaland
resourceprotection(asstatedaboveusingPAtechniques),theoccurrenceofpotentialreboundeffects
foragriculturalland,water,fertilizers,andplantprotectionproductsishighlyprobable[65–67].
Itisevidentthatsmartfarmingevolvestechnologicallyatafastpaceinbothresearchandmarket
domains,butitsadoptionfromend‐usersdoesnotfollowthesamefootsteps.Ifanevaluationofthe
promisingpositiveimpactofSFTsaccompaniedbyanadoptionreadinessanalysiswouldbe
available,thentheuptakeofsuchtechnologieswouldpossiblyincrease.Hence,athorough
assessmentandcomparisonofSFTsfromresearch(scientificpapers),innovation(researchprojects),
andmarket(commercialproducts)couldassistinbetterunderstandingtheevolutionofSFTsand
howthisevolutionaffectsfactorsofadoptionreadinessandrelatedeconomic,environmental,and
laboraspectswithinafarm.Basedonthisneed,theobjectiveofthisstudywas(i)tomaptheexisting
researchandcommercialSFTswithregardtotheirtechnologicalreadinesslevel,type,andthefield
operationtheyareusedfor;(ii)toidentifytheeaseofSFTadoption;and(iii)toprovidethemain
impactsofSFTsonfarmeconomics,environment,andlabor.Thisworkisexpectedtocontributeto
theliteraturewithaglobalperspectiveofvariousSFTsdevelopedfromresearchtoinnovationand
thentothemarket,aswellasshowthedifferencesintheirimpactandadoptionreadiness.
2.MaterialsandMethods
Thisworkfocusesonopen‐fieldproduction;hence,weconsideredSFTsusedinarable
(includingfodderproduction)andhorticultural(fruitandvegetableproduction)farming.Areview
ofsuchSFTswasconductedbasedonscientificliterature,currentandpastEUresearchprojects,and
commerciallyavailableproducts.TheeconomicandenvironmentalchallengesthatSFTsfacewere
determinedbyasetofkeyperformanceindicators(KPIs)(Section2.1).FortheselectionoftheSFTs,
asystematicsearchprocedurewasdevelopedforscientificpapers,researchprojects,andcommercial
products(Section2.2).Finally,informationabouttheidentifiedSFTswascollectedbydevelopinga
questionnairetorecorddataforeachSFT’sadoptionreadinessanditsperformanceregardingthe
selectedKPIs(Section2.3).
2.1.KeyPerformanceIndicatorsforOpenFieldProduction
Severalauthorsproposedgroupingindicatorstomeasuretheperformanceofagricultural
systems.InastudyintheUnitedKingdom(UK),indicatorclusters(e.g.,biodiversity,energy,value
chain)weredefined,withmeasurableparametersforeachcluster(e.g.,numberofspeciesonthe
farm,energybalance,totalvalueofproduction)[68].Inanotherstudy,theliteratureonagricultural
sustainabilitywassurveyed,andindicatorswereidentifiedandgroupedinathree‐levelhierarchy
[69].Anin‐depthreviewofindicatorconstructionisalsoavailable[70].Indicatorsetswerealso

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proposedbypublicorganizations,suchastheEuropeanEnvironmentalAgency(EEA)[71]andthe
OrganizationforEconomicCo‐operationandDevelopment(OECD)[72],aswellasprivate
organizations,suchasTheSustainabilityConsortium(TSC)[73]andGlobalReportingInitiative
(GRI)[74].Alltheseindicatorsetsaredifferentandhaveslightlydifferentpurposes.Thereisnotone
singlesetofindicatorsthatsuitsourcurrentpurposebetterthanalltheothers.Weusedthepublished
indicatorsetsforourstudy.
Weexaminedthepublishedindicatorsandderivedchallengesinagriculturethatcouldbe
possiblyaddressedbySFTs.InTable1,thesechallengesarelistedalongwithSFTsthatcanbeused
toaddressthem.
Table1.Challengesidentifiedinopen‐fieldfarmingaccompaniedbyrelevantsmartfarming
technologies(SFTs)thatcouldaddressthem.DSS—decisionsupportsystem;FMIS—farm
managementinformationsystem;VRA—variablerateapplication;RFID—radiofrequency
identification;QR–QuickResponse..
Challeng
e
RelevantSmartFarmingTechnologies
Resourceefficiency(e.g.,water,nutrients,
pesticides,labor)
 sensorsandnetworks
 bigdataanalytictools
 DSS
 FMIS
 intelligentwaterapplicationsystems
 VRAfertilization/pesticidessystems
 RFIDtags
Management/preventionofdiseases,
weeds,etc.
 earlywarningsensorsandnetworks
 specificfarmmachines
 FMIS
 DSSforinfestationmanagement
 VRAsprayingsystem
Riskmanagement(e.g.,foodsafety,
pesticideresidueeliminationand
emissionofagro‐chemicals,etc.)
 sensors(e.g.,weatherstation,multispectral
cameras,thermalcameras,etc.)
 traceabilitytechnology
 barcodes,QRcodes,RFID
 real‐timerecordingsystems
Compliancewithlegislationand
standards(greeningofCAP;regulations
onsoilmanagement,pesticide,fertilizer,
andwateruse)
 recordingtechnologies
 web‐based,open,andinteroperablestandardsfor
end‐to‐endtrackingsystems
Collaborationacrossthesupplychain
(supplychainofcompaniesand
processors)
 smarttraceabilitysystem
 smartlogisticssystem
 variousanalyticaltools
WeexaminedthepublishedindicatorstocreatealistofKPIstobeusedforassessingtheimpact
ofSFTsintermsofthreemainissuesassociatedwithagriculturalsystemsthatareofhighimportance
forend‐usersandthegeneralpublic:farmeconomics,theenvironment,andlaborwithinthefarm
(Table2).ThedefinitionofeachKPIandthereasoningforincludingthemaregiveninTable2.These
KPIsare,inmanycases,interconnectedandmightalsohaveanimpactoneachother.

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Table2.Keyperformanceindicators(KPIs)combinedwiththeirdescriptionandthereasoningfor
theirinclusiontoassesstheimpactofsmartfarmingtechnologies(SFTs)inopen–fieldfarming,
regardingfarmeconomics,environment,andlaborwithinthefarm.
A/A
Key
Performance
Indicator
DescriptionoftheKPIinRelationtothe
SpecificImpactCategory
ReasoningtobeSelectedasSignificant
KPIintheSpecificImpactCategory
FarmEconomics
1Productivity
Ratioofavolumemeasureofoutputto
avolumemeasureofinputuseinfarm
production[75]
Itisanindextoexpressthe
optimizationoftheagricultural
practicesofafarmthroughSFTuse,
whichreflectsfarmeconomics
2Qualityof
product
Qualitativefeaturesofagricultural
products(e.g.,intact,sound,clean,free
ofpests,freshappearance,normaland
sufficientphysiologicaland
morphologicaldevelopment,maturity,
firmness,freeofdecayaffecting
edibility,absenceofdefects)[76]
TheinfluenceofSFTsonthe
productqualitycouldincrease
productvalue
3Revenue
Incomeofafarmfromitsnormal
businessactivities,usuallyfromthe
salesofagriculturalgoodstocustomers
[77]
Revenueiscrucialfortheviability
offarms,andSFTscouldassistinits
increasebyoptimizingproduction
andquality
4InputcostsCostofinputs(e.g.,seeds,fertilizers,
pesticides,fuel,irrigationwater)[78]
ThemainroleofSFTsisthe
optimizationofinputsthatreflect
costreductionforafarm
5Variablecosts
Expensesthatvaryindirectproportion
tothequantityofoutput(e.g.,raw
materials,packaging,labor)[79]
Reductionofallfarmexpenses
employingdifferentkindsofSFTs
canpositivelyimpactthefinal
income
6Cropwastage
Cropthatgetsspilledorspoiltbeforeit
reachesthemarket(e.g.,fruitswith
blotsorblemishfrompests,orof
irregularshapefromabnormal
development)[80]
SFTscouldassistinbettercrop
protectionschemesandselective
harvestingreducingcropwastage
7EnergyuseAmountofenergythatisusedforall
needsofafarm[81]
Optimizedprocessesinthefarm
(e.g.,tractororrobotrooting,
selectiveharvestingthatreduces
storageneeds,etc.)canreduce
energyuseandtherespectivecost
Environment
8Soil
biodiversity
Thevariationinsoillife,fromgenesto
communities,andtheecological
complexesofwhichtheyarepart,i.e.,
fromsoilmicro‐habitatstolandscapes
[82]
Optimizedcropproductionusing
SFTs(i.e.,minimizingfieldpasses
usingauto‐guidance)could
preservesoilbiodiversityand
sustainability,allowingsoillife
conservation
9Biodiversity
Thenumberandtypesofplantsand
animalsthatexistinaparticularareaor
intheworldgenerally[83]
Reducedbiodiversityimpact
throughoptimizationofinputs
(variableratefertilizationor
pesticideapplication)andspray
driftreductionusingSFTs
10FertilizeruseExtentoffertilizeruseinagricultural
production[84]
Decreasingthefertilizeruse
applyingSFTsmeansthatleaching
togroundwaterorhighsoilGHG
emissionscanbereduced
11Pesticideuse Extentofpesticideuseinagricultural
production[85]
Pesticideusereductionemploying
SFTscanprovidelesspointand

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diffusecontaminationofnon‐crop
areas
12Irrigation
wateruse
Waterappliedbyanirrigationsystem
tosustainplantgrowthinagricultural
andhorticulturalpractices[86]
OptimizingwaterusewithSFT
applicationwouldassistin
maintainingwaterreservesand
reduceover‐pumping
13CH4emissions
Allreleasesofthemaingreenhouse
gasesrelatedtoagriculturalactivity
(CH4,CO2,N2O)derivedduringcrop
productiononafarm[87]
Improvingallaspectsofinput
application(seeds,fertilizers,
pesticides,fuel,irrigationwater)
canresultinlessGHGemissions
withapositiveimpactonglobal
warmingpotential
14CO2emissions
15N2Oemissions
16NH3emissionsNH3releasesmainlyfromfertilizeruse
forcropproductiononafarm[88]
Acidificationeffectsattributedto
drydepositionofNH3couldbe
reducedbynitrogenapplication
throughSFTs
17NO3leaching
MovementofNO3tothegroundwater
increasingnitrogenlossesfrom
nitrogenfertilizerinputstoagricultural
land[89]
Controllingnitrogenfertilizationto
optimizeitsusefromthecrops
wouldreduceNO3leachingwitha
positiveimpactonsoilandwater
resources
18Pesticide
residues
Anysubstanceormixtureofsubstances
infoodresultingfromtheuseofa
pesticideontherespectivecrop
includinganyspecifiedderivatives
consideredtobeoftoxicological
significance[90]
VariableratesprayingthroughSFTs
canlessenpesticidedosage
reducingtheresiduesonproducts
intherespectivefieldanddiminish
spraydriftforlessresiduesin
neighboringfields
19Weedpressure
Effectsofweed,pest,anddisease
growthinafield[91]
Controllingweed,pest,anddisease
populationanddensitymainlywith
timelyandprecisepesticide
applicationwouldreducetheir
impactonthefinalyieldandquality
20Pestpressure
21Disease
pressure
Labor 
22Labortime
Timedevotedtolaborandconsidered
asacommodityorasameasureof
effort[92]
SFTscouldreducethelabortime,
throughroboticapplications,auto‐
guidance,tele‐operation
23Farmer’sstress
Adversereactionpeoplehaveto
excessivepressureorothertypesof
demandplacedonthem[93]
SFTscouldreducefarmers’stress
throughbetteroptimizationofthe
resourcesandschedulingofthe
operations
24HeavylaborHeavypracticalwork,especiallywhen
itinvolveshardphysicaleffort[94]
SFTscouldreduceheavylabor
usingautomationandrobotic
technologiesfordemandingfield
operations
25Workers’
injury
Injuryorillnesscaused,contributedor
significantlyaggravatedbyeventsor
exposuresintheworkenvironment[95]
Automationandroboticscould
reducefarmers’injuries,i.e.,
automatichitchcouplingor
automaticsprayerfilling
26Accidents
Discreteoccurrenceinthecourseof
workleadingtophysicalormental
occupationalinjury[96]
SFTsprovideadvancedsensorsfor
activeandpassiveoperations,such
asauto‐guidanceforautomatic
turningsinheadlandsthatreduce
accidents
2.2.Search
WesearchedforSFTsderivedfromscientificpapers,researchprojects,andindustrialproducts.
Themethodologyusedisgivenbelow.

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2.2.1.Peer‐ReviewedScientificPapers
WeemployedScopus(www.scopus.com)asithasabroadcoverageincludingmanydisciplines
(notjustagriculture)andscientificjournalsofdifferentranking(notonlytopjournals).
Aquerywasdevelopedinconsultationwithaprofessionallibrariantosearcharticlesthatmight
describeSFTs.Thequeryconsistedoftwoparts:afirstpartthataimedtoselectallarticlesrelatedto
technology,andasecondpartthataimedtoselectallarticlesrelatedtoopen‐fieldfarming.Thetwo
partsofthequerywerejoinedwithan“AND”clause.Theselectionofkeywordswassupplemented
byconsiderationsonthescopeofrelevanttimeandsubjectrelatedsettings.Thefollowingquerywas
usedtoselectarticles:
(TITLE‐ABS‐KEY(sensorordecision‐supportorDSSordatabaseorICTorautomat*or
autonom*orrobot*orGPSorGNSSor“informationsystem”or“imageanalysis”or“image
processing”or“precisionagriculture”or“smartfarming”or“precisionfarming”))
AND
(TITLE‐ABS‐KEY(agricult*orcrop*orarabl*orfarm*orvineyardororchardorhorticult*or
vegetabl*))
AND
(LIMIT‐TO(DOCTYPE,”ar”)ORLIMIT‐TO(DOCTYPE,”re”))AND(LIMIT‐TO(SUBJAREA,
”AGRI”)ORLIMIT‐TO(SUBJAREA,”ENGI”)),
wherekeywordsendingwith“*”couldhavedifferentendings(e.g.,automat*willretrieve
“automatic”,aswellas“automated”);GPS—globalpositioningsystem,GNSS—globalnavigation
satellitesystem.
Resultswerelimitedbyyear,documenttype(article),subjecttype(agriculture),andlanguage
(English).Forourpurpose,wecollectedpapersonlyfrom2012andlater,inordertofocusonrecent
SFTsthatarelikelyofinteresttoallrelatedstakeholdersandespeciallyend‐users.Thequerywas
optimizedandverifiedbyusingarandomsampleof10keypapersthatwereconsideredrelevantto
thedevelopmentofSFTspracticalforfarmers.Thequerywasconsideredcompletedwhenthese10
paperswereincludedinthequeryresult.
TheScopusqueryresultedinalargenumberofarticlesthatareexpectedtoholdinformationon
SFTs.Fromthesepapers,thereweremanythatwerenotrelevanttotheopen‐fieldagriculture.
Therefore,amanualselectionprocedurewasusedtoselectonlythearticlesthatarerelevant,namely,
articlesdescribingatechnologythatcan(orcouldbe)usedbyafarmerintheirdailyfarmingpractice.
Throughout,wefocusedonthequestion,“isthisarelevantSFT?”.Weusedanexclusionapproach
andremovedpapersrelatedto(i)post‐harvest,processing,distributing,ormarketing,(ii)
evapotranspirationcalculations,(iii)landsuitability(selectingonlyDSSsrelatedtocropssuitability),
(iv)watermanagement,likedroughts(butincludinganythingrelatedtoirrigation),(v)tractor
engines,and(vi)greenhousecultivation.
Havingavailableonlythescientificpapersrelevanttooursearch,themanualselectionofarticles
continuedinthreerounds.Firstly,weusedthetitletoremovepapersthatwerenotrelevant.For
example,apaperwiththetitle“ANewAssessmentofSoilLossDuetoWindErosioninEuropean
AgriculturalSoilsUsingaQuantitativeSpatiallyDistributedModelingApproach”wasselectedby
ourquerybecauseitsabstractcontainedtheterms“geographicinformationsystem”and“arable
land”.However,thetitleclearlydoesnotdescribeatoolusefultofarmers.Therefore,weremovedit
fromourlist.Secondly,forthosepaperswithrelevanttitles,wealsoreadtheabstractandexcluded
thosenotpracticallyusefulforfarmers.Asanexample,apaperwiththetitle“WirelessSensor
NetworkandInternetofThings(IoT)SolutioninAgriculture”seemedofinterest.Theabstractmade
itclearthatthispaperdescribednetworkinfrastructurethatcouldcertainlybeusedinafarm.
However,thiswouldnotbeuseddirectlybyfarmers.Ratheritwouldbeacomponentinthe
developmentandoperationalizationofasensornetworkthatinturnwouldsupporttoolsfor
decision‐makingbyfarmers.Inshort,thispaperdidnotdescribeanSFTdirectlyusefulforafarmer
inopen‐fieldagriculture,anditwasexcluded.Asathirdstep,weattemptedtolocatethefulltextof
thepaper.Ifthatprovedimpossible,orifthepaperturnedouttobewritteninalanguageotherthan
English,thenweremovedfromthelist.Ifthefulltextindicatedthatthepaperwasnotrelevantto

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open‐fieldagriculture,itwasalsoremovedfromthelist.Forpapersleftattheendofstepthree,the
authorsansweredthequestionsofthesurveyofSection2.3usingthefulltextofthepaper.
2.2.2.ResearchProjects
Fortheretrievalofresearchprojects,anactivesearchwascarriedoutforEU‐fundedprojects.
Horizon2020andFP7programswerecollectedfromtheCORDIS[97]websiteoftheEUand
importedintoarelationaldatabase.TheScopusquerywastranslatedtoanSQLquerywhich
searchedcolumns“title”and“objective”forEUresearchprojects,usingthesamelistofkeywordsas
intheScopusquery.Inthisprocess,theauthorsansweredthequestionsofthesurveyofSection2.3
usingtheinformationoftheproject’swebsiteanddeliverablesand,inmanycases,viapersonal
communicationwiththeprojects’coordinators.
2.2.3.IndustrialProducts(CommerciallyAvailableProductsandServices)
Forthecollectionofindustryresults,acallwasannouncedthroughtheSmart‐AKISproject
newsletter(www.smart‐akis.com),aswellthroughtheEuropeanAssociationofAgricultural
Machinery(CEMA)tobecomeknownbythenetworkofSFTcompaniesunderitsumbrellaorrelated
totheassociation.Awebsearchgaveinsightintothecompaniesthatarepossiblyinvolvedinthe
developmentofSFTs.Wesearchedforcompanieswithrelevantcredentialsforsmartfarming,such
asinvolvementintheproductionoffarmingequipmentandmachineryorstakeholdersinvolvedin
thedevelopmentofagronomicsoftware.TherelevantnetworksofFIWAREFRACTALSandSmart
AgrifoodIIwereconsulted.Furthermore,weusedallSmart‐AKISpartnersnetworkofadvisersto
contactrelevantstakeholders,andthelaststepwasfortheauthorsofthisworktoconductadesk
searchthoughinternettolocatemorecommercialSFTs.ThequestionnairewasansweredbytheSFT
providerswiththeassistanceoftheauthorsofthiswork.Inthecasethatthequestionnairewas
inadequatelyfilledin,theSFTproviderswerecontactedagain(thequestionnaireaskedfortheir
consenttodoso)toprovidethemissingorinconsistentinformation.Ifthequestionnairewasstillnot
totallyfilledin,thentheSFTwasexcludedfromthesearch.
2.3.QuestionnaireDevelopment
AquestionnairewasconstructedforrecordingdataabouteachSFTfoundinthethreecategories
(scientificpapers,researchprojects,commercialproducts).Thequestionnairewasdevelopedbased
ontheassessmentofthefulllistofchallengesandrespectiveKPIs,andthreeversionswereproduced
(oneforeachcategory).Thequestionnaireconsistedoftwomainparts:(1)descriptiveinformation
fortheSFT,includingbasicinformation,technologyreadinesslevel,type,andfieldoperationthatit
isusedfor;(2)assessmentinformationabouteaseofadoptionandpossibleeffectsonfarmeconomics,
environment,andlabor.TheassessmentsectionwasevaluatedusingaLikertscaleoffivelevels.The
responseswereanalyzedusingdescriptivestatisticsforLikertdatainRsoftware(freesoftwareby
theRFoundationfromStatisticalComputing,Vienna,Austria).Thequestionnairewasalsobasedon
theEIP‐AGRIcommonformat[98]asmuchaspossible,anditwasdistributedonlineviaalinktothe
identifiedstakeholders.Thespecificcontentofeachpartinthequestionnaireisdescribedbelow.
2.3.1.BasicInformationaboutSFT
Afterquestionsthatwerespecifictothetypeofentry(scientificpaper,researchproject,or
industrialproduct),somebasicinformationquestionswereaskedabouttheSFT.Indicatively,for
papers,theauthorship,scientificjournal,yearofpublication,andDOIwereasked,while,forprojects,
durationandstatus(ongoingorterminated),typeofEUfunding,budget,andthecoordinatorwere
given.Finally,forproducts,thedetailsofthecompanyandthepersoninchargeweredefined.
2.3.2.TechnologyReadinessLevel(TRL)
TheTRLofatechnologyindicatesitsmaturitylevelandrangesfromTRL1(basicprinciples
observed)toTRL9(actualsystemproveninoperationalenvironment)[99].Basedonthis

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classification,TRLwasspecifiedfortheSFTspresentedinscientificpapersandtheresearchprojects,
while,forcommercialproducts,itwasconsideredasTRL9becausetheyarealreadyoperationalon
themarket.TRLwasdefinedbytheauthorsusingtheAFRLTRLCalculator(version2.2.)[100]for
eachoftheincludedSFTsinthesearch.Theprocesswasasfollows:threeequalbatchesofSFTsfrom
bothscientificpapers(177papersineachbatch)andresearchprojects(twobatchesof31projectsand
onebatchof32projects)wererespectivelydefined.Then,eachauthorwasassignedwithtwobatches
ofeachcategory,inordertoremainneutralinallpapers,andprojectsofthethirdbatch.Incaseof
disagreementabouttheTRLlevelofacertainSFTbetweenthetwoauthorsthatassessedthesame
batch,thethirdauthorwouldbeaskedtoevaluate,andhisassessmentwouldbetakenintoaccount.
Itshouldbementionedthatthelevelofdisagreementwasverylow(in17outof531scientificpapers
(3%)andinsixoutof94researchprojects(6%)),anditremainedbetweentwoneighboringTRLlevels
duetotheaccuratedefinitionsgivenbyReferences[77,78]andtheexperienceoftheauthors.
2.3.3.TypologyofSFTs
ForabetterunderstandingoftheSFTlandscape,theclassificationofSchwarzandHerold[101]
wasused.TheseauthorsclassifiedSFTsasrecording,reacting,orguidingtechnologies.Inaddition
totheseclasses,inthiswork,“FMIS”and“robotic/automationsystem”wereused,becauseresearch,
innovation,andmarketapplicationoftheseSFTcategoriesfoundhighinterestinrecentyears
[28,52,59].Itshouldbenotedthatthesefiveclassesarenotmutuallyexclusive,meaningthata
particularSFTmayberecordingandreactingatthesametime.AroboticSFTwilltypicallyusesome
kindofguidingtechnologyandeitherrecordorreact,orpossiblydoboth.Theprincipalfunction
wasusedinouranalysis.
2.3.4.FieldOperationConductedwiththeSFT
ThemainfieldoperationsthateachSFTcouldbeusedweregiveninthequestionnairetobe
chosen,namely,(1)tillage,(2)sowing,(3)transplanting,(4)fertilization,(5)pesticideapplicationfor
weed,pest,anddiseasecontrol,(6)irrigation,and(7)cropscouting(measuringandrecordingcrop
andsoilparametersinthefield),forexample,inthesituationoffielddataretrieval.Theoptionto
includeanotherfieldoperationwasprovided.
2.3.5.EaseofAdoptionoftheSFT
InadditiontocharacteristicsofSFTsthatrelatetothechallengesthatfarmersface,therewere
alsoquestionsrelatedtoeaseofadoptionofSFTs.TheRogersmethod[102]forevaluationof
innovationswasused,wherepotentialadoptersevaluateaninnovationintermsofitsrelative
advantage(theperceivedefficienciesgainedrelativetocurrenttoolsorprocedures),compatibility
withthepre‐existingsystem,complexityordifficultytolearn,testability,potentialforreinvention
(usingthetoolforinitiallyunintendedpurposes),andobservedeffects.Respondentswereaskedto
indicatewhetherornottheyagreedwiththefollowingsevenstatements,usingtheLikertscalein
fivelevelsofagreement(stronglydisagree,disagree,noopinion,agree,andstronglyagree):
1. TheSFTreplacesatoolortechnologythatiscurrentlyused.TheSFTisbetterthanthecurrent
tool.
ThisquestionisspecificallytargetedatSFTsthataimatcreatingaddedvalueoverexistingtools.
2. TheSFTcanbeusedwithoutmakingmajorchangestotheexistingsystem.
SomeSFTsareexpectedtorequiremorechangestotheexistingsystemthanothers.
3. TheSFTdoesnotrequiresignificantlearningbeforethefarmercanuseit.
Thisstatementcangiveanindicationonthelearningeffortthatneedstobemadebythefarmer
andcanbeusefulinordertocomparethedifferenceinlearningrequirementsbetweenSFTs.
4. TheSFTcanbeusedinotherusefulwaysthanintendedbytheinventor.

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SomeSFTsmayholdmultiplepurposesusefulfortheachievementofmanyverydifferent
effects.
5. TheSFThaseffectsthatcanbedirectlyobservedbythefarmer.
Itisconsideredanadvantagewheneffectscanbedirectlyobservablebyafarmer,asitwillmake
itmorelikelythatthefarmerwillfindtheSFTrelevantfortheirsituation.
6. UsingtheSFTrequiresalargetimeinvestmentbythefarmer.
Thisstatementwillgiveanindicationonthetimeinvestmentthatisneededfromthefarmerin
ordertousetheSFT,whichwillplayaroleinhowattractivetheSFTistouse.
7. TheSFTproducesinformationthatcanbeinterpreteddirectly(exampleoftheopposite:theSFT
producesavegetationindexbutnobodyknowswhattodowithit).
Itisdesirablewhenresultsarepresentedinsuchamannerthattheyareeasytointerpret.This
makestheresultsmoreinterestingforend‐usersandresultsininterpretationconsistency.
2.3.6.EffectofUsingtheSFT
AveryimportantpartofthisworkwastodefinetheeffectofeachSFTinagriculturalproduction.
TheidentifiedKPIsinSection2.1wereusedascriteriatomeasuretheimpactonfarmeconomics,the
environment,andlaborwithinthefarm.Effectswereexpectedonthese26criticalaspects,ofwhich
fiveareinfluencedpositivelybytheSFTs,increasingthem(productivity;qualityofaproduct;
revenue;soilbiodiversity;biodiversity),and21areaffectedpositivelybytheSFTs,decreasingthem
(inputcosts;variablecosts;cropwastage;energyuse;CH4emissions;CO2emissions;N2Oemissions;
NH3emissions;NO3,emissions;fertilizeruse;pesticideuse;irrigationwater;labortime;farmers’
stress;heavylabor;injury;accidents;pesticideresidue;weedpressure;pestpressure(insects);disease
pressure).EffectscouldbeexpressedusingtheLikertscaleinfivelevelsofchange(largedecrease,
somedecrease,noeffect,someincrease,andlargeincrease).Therespondentcouldsupplementthis
scalewithrelevantpercentagesorevenmorepreciseindicationoftheeffectsoftheSFTwhenthis
waspossible.
3.ResultsandDiscussion
ThissectionprovidesthefinalnumberofSFTsidentifiedinscientificpapers,researchprojects,
andcommercialproductsthroughoursearch.TheseSFTswerepresentedandcomparedintermsof
technologyreadinesslevel(TRL1–9),type(recording,reacting,guiding,FMIS,and
robotic/automation),andfieldoperationsaddressed(tillage,sowing,transplanting,fertilizing,
weeding,cropprotection,irrigation,harvesting,scouting).Thiswasusedtopresentsomeperspective
trendsofthecurrentsituationinSFTdevelopment.Thefactorsthatwereexpectedtoaffectadoption
readinessofSFTswerealsodescribed,whiletheeffectonfarmeconomics,theenvironment,and
laborwasgiven,inordertoidentifythemostimpactfulcategoriesofSFTswithintheinventoryof
thiswork.
3.1.NumbersandKindsofSFTs
ThenumberofarticlesdescribinganSFTisgrowingrapidly(Figure1),showingthetrendof
researchtotransferconventionalagriculturebasedontheGreenRevolutionconcept(agricultural
mechanization,uniforminputapplication)toamodernsmartagriculture(ICTinterferencein
agriculturalmachineryforincreasedprecisionandspecifiedinputapplication).
Intotal,13,251scientificpaperswerefoundinthecitationdatabaseScopuswiththequery
describedinSection2.2,andthemanualselectionresultedinasmallfractionofthesescientificpapers
(531or4%ofthetotal)beingselectedbasedonthedeploymentofaprototypetestedinfield
conditions,whichcanbedirectlyusefultofarmers.Thislowpercentageofthetotalnumberof
scientificpapersindicatesthatmostresearchpresentedmainlyimmatureconceptsthatrequire
severalstepsbeforetheycanbebeneficialforeverydayagriculturalpractices.

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
Figure1.Temporalevolutionofpublishedscientificarticlesonsmartfarmingtechnologies(SFTs)on
ayearlybasis(fortheperiod1981–2017)identifiedthroughaScopusquery(asof18July2018).The
queryselectedarticlesthatcontainedkeywordsrelatedtotechnology(sensor,decisionsupport,DSS,
database,ICT,automat*,autonom*,robot*,GPS,GNSS,informationsystem,imageanalysis,image
processing,precisionagriculture,smartfarming,precisionfarming)andtoopen‐fieldfarming
(agricult*,crop*,arabl*,farm*,vineyard,orchard,horticult*,vegetabl*).ICT—informationand
communicationtechnologies;GPS—globalpositioningsystem;GNSS—globalnavigationsatellite
system.
TheEuropeanCommissionCORDISonlinedatabasewithasearchforfundedprojectsresulted
in94researchprojectsfromFP7andH2020fundingframeworksdirectlyrelatedtoSFTs,whilethe
searchforindustrialSFTsolutionsconcluded439productsthatareavailableonthemarketfor
farmerstopurchase.Intotal,1064SFTswereselectedforthisanalysisforallcategories(Table3),for
whichthequestionnairewascompleted.
Table3.Totalnumberofsmartfarmingtechnologies(SFTs)identifiedbythesearchconductedin
availablescientificpapers,researchprojectsandindustrialproducts.
TypeTotalNumber
Researcharticles531
Researchprojects94
Industrysolutions439
Total1064
3.2.TechnologyReadinessLevel(TRL)ofSFTs
Figure2presentsthedifferencesinTRLbetweenthescientificpapersandresearchprojects(by
definition,theTRLofcommercialproductsis9).

(a)ScientificPapers(b)ResearchProjects
Figure2.Technologicalreadinesslevel(TRL)oftheidentifiedsmartfarmingtechnologies(SFTs)in
(a)scientificpapersand(b)researchprojects.TRLrangesfromTRL1(basicprinciplesobserved)to

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TRL9(actualsysteminoperationalenvironment)[99]andwasdefinedusingtheAFRLTRL
Calculator(version2.2.)[100].CommercialSFTswereexcludedbythisprocess(theyallhadTRL9).
Mosttechnologieswereatthestagewheretheyarevalidatedinarelevantenvironment.Inall
cases,afewentrieswereoftheearlieststagesinwhichonlybasicprincipleswereobservedor
technologyconceptsformulated.Inresearchprojects,itcanbeseenthatthemajorityhadTRL5–7,
butanimportantfindingisthat16%ofprojectsresultedinacommercialproduct(TRL9),showing
therecenttrendofprojectsfocusingonanalliancebetweenacademiaandbusinessesforreal
applications.
3.3.TypesofSFTs
DifferenttypesofSFTscanbedistinguishedinscientificpapers,researchprojects,and
commercialproducts(Figure3).Byfocusingonjustscientificpaperspublishedacrossthesixyears
underconsideration,itisobviousthattherewasafocusonrecording,withrelativelylittleattention
towardreacting.Thisisnotacomfortingpicture,becauseitsuggeststhat,whilethereisalargeeffort
onmeasurements,thereisalackofeffortontranslatingmeasurementsintoon‐farmpracticalactions.
Itshouldbenotedthatthisoutcomecorrespondsuncomfortablywellwiththegeneralbeliefthat
SFTspromisemorethantheydeliver(e.g.,seeReference[103]).However,thisfindingwasnotshown
inresearchprojectsandcommercialproductstosuchanextent.


(a)ScientificPapers(b)ResearchProjects(c)CommercialProducts
No.ofSFTs%No.ofSFTs%No.ofSFTs%
Recording28653.92526.612829.1
Reacting7814.788.56815.5
Guiding234.333.2306.8
FMIS8716.44143.613731.2
Robot/Automation5710.71718.17617.3
TotalNo.ofSFTs53110094100439100
Figure3.Allocationoftheidentifiedsmartfarmingtechnologies(SFTs)toeachtype(recording,
reacting,guiding,farmmanagementinformationsystems(FMIS),androbotic/automationsystems)
basedontheclassificationofSchwarzandHerold[101]modifiedbytheauthorsin(a)scientific
papers,(b)researchprojects,and(c)commercialproducts.
Regardingtheresearchprojects,itcanbeseenthattheEUfundingwasdirectedmoretoward
FMISdevelopmentfollowedbyrecordingtechnologies.Thismighthavehappenedasmeasuredin‐
fielddatahavetobetranslatedintoinformationthroughICTtoolsforsupportingfarms’statistics
andfarmers’decisions[33],whichisthefirststepbeforereacting.ReactingSFTswerealsosupported
bytheEU,buttoalowerextent,suggestingthatthisSFTtypeisalsounderdevelopment.An
importantreadingofFigure3bisalsothatrobotsandautomationforagriculturalusereceived
attentionandwerefundedevenmorethanotherreactingSFTs.ThismaybeexplainedbysuchSFTs
beingperceivedasasolutioninapplyingsmartfarmingapplicationsinfieldconditionsusingtheir
advantages(smallsize,in‐fieldprecisenavigation)[104].Thistrendcouldalsobeassociatedwiththe

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specificityoffieldplotsinEuropebeingmuchsmallercomparedtotheUS[105],makingasmall
robotorswarmsofsmallrobotsmuchmoreofinterestforEuropeanagriculture[58].
Asfortheindustrialproducts(Figure3c),therewasamoreuniformdistributionbetweenSFT
categories.Onlyguidancetechnologieswerefoundlessofteninoursearch,probablybecausethey
arethemostmaturecommercialSFTs[106]andlimitednewcompaniesareenteringthemarket.Itis
importanttopointoutthatrecordingtechnologiesandFMIShavethelargestnumberofSFTs,
partiallyfollowingthetrendsinbothscientificpapersandresearchprojects.Reactingand
robotic/automationtechnologieswerealsosignificantlyrepresentedinthecommercialproduct
inventory,evenifresearch(papersandprojects)didnotseemtofocusonthesesubjectstoahigh
extent(Figure3).Regardingrobotic/automationSFTs,thenumberofavailablemarketsolutions
seemeddisproportionatelyhighincomparisontoresearchoutcomesinthesamefield.Inour
findings,therewasanincreasingtrendforthesetechnologiesmovingfromscientificpapersto
commercialproducts.Thismaybebecauseagriculturalresearchexperiencedadelayincopingwith
thedevelopmentofthesehigh‐endSFTs,andcompaniesusinginternalresearchanddevelopment
producedmarketableproductswithoutpublishingthisworkinscientificjournalsforintellectual
propertyreasons.ThesecompanieseithercollaborateinlargeconsortiumsofEUresearchprojectsto
optimizeandmarketsuchproductsorgodirectlybytheirownmeansinmarketableproducts.In
addition,higherfundingforinfrastructureinresearchgroupsisrequiredtocarryoutworkwith
roboticsystems,andthismayhavealsoinfluencedthelownumberofrobotic/automationSFTsin
researchprojectsandscientificpapersincomparisontootherSFTs,suchasrecordingtechnologies.
3.4.FieldOperationsAddressedbytheIdentifiedSFTs
ThefieldoperationsthattheidentifiedSFTswereusedforaresummarizedinFigure4.

 
(a)ScientificPapers(b)ResearchProjects(c)CommercialProducts
No.ofSFTs%No.ofSFTs%No.ofSFTs%
Tillage173.277.46113.9
Sowing50.999.6327.3
Transplanting30.666.4235.2
Fertilizing8215.41516.07817.8
Weeding5810.966.44410.0
CropProtection7614.31212.87617.3
Irrigation7213.61313.86314.4
Harvesting336.21111.7378.4
Scouting18534.81516.0255.7
TotalNo.ofSFTs53110094100439100
Figure4.Allocationoftheidentifiedsmartfarmingtechnologies(SFTs)toeachcategorythat
addressesacertainfieldoperation(tillage,sowing,transplanting,fertilizing,weeding,crop
protection,irrigation,harvesting,andcrop/soilscouting)in(a)scientificpapers,(b)researchprojects,
and(c)commercialproducts.
Inscientificpapers,cropandsoilscoutingwasthemostcommonapplicationfortheSFTs
described,inaccordancewiththetrendofFigure3,whererecordingSFTswerethemostprominent.

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Onthecontrary,SFTsderivedfromscientificpapersfocusedverylittleonsoiltillageand
sowing/transplanting,eventhoughtheycanprovidesignificantsavingsinplantestablishmentand
increaseyieldpotential(especiallyinhybridseeds,suchascornandpotatoes).Ontheotherhand,
thisworkconfirmsthatreactingapplicationtechnologiesareofgreatimportanceforresearchers(also
duetofarmers’interestsinthesesubjects),asalsoseenintheliteraturewithfertilizing[107,108],
weeding[109],cropprotection[110],irrigation[111],andharvesting[61,112]beingimportant
researchsubjectsinrecentyears.
Thebestrepresentedsubjectsinresearchprojectswerefertilizationandcrop/soilscouting.
Fertilizationisindeedoneofthetargetsforvariablerateapplicationtoensureyieldmaintenanceor
evenincreaseyieldwiththeleastpossiblenutrientsapplied[107],andEUresearchprojectsseemto
fundthisissuetoagreatextent.Asforscouting,itisoftenchosensimultaneouslywithotherfield
operations(mostoftentogetherwithfertilization)and,inonly22%ofcases,itistheonlychosenfield
operation.Thisresultpresentstheneedfordatagatheringbeforeanysmartfieldapplication,as
statedinmanySFT‐relatedpublications[113–115].Tillage,sowing/transplanting,andweedingwere
lessfound,asinthescientificpapers.Researchontheseoperationsisindeedlacking,andthereason
maybethereluctanceofresearchersandfunderstocarryoutresearchinthisdomain,probablydue
tothefactthatitisstillunclearhoweffectiveitisandhowitfitswithothervariableratetechnologies.
However,themostcrucialconclusionfromFigure4bisthatEU‐fundedresearchiswelldistributed
amongresearchtopicsandisgenerallydirectedtoallagriculturalpractices.
Regardingtheindustrialproducts,thesituationisdifferentasscoutinghadasignificantnumber
ofSFTsidentified,butnotthemajority,asseeninscientificpapersandresearchprojects.Thismight
indicatethatindustrialsolutionsareslowlymovingtointegratedsystems(requiredequipmentfor
dataacquisitionandactuationcombined).Ontheotherhand,fertilizationremainsthemost
importantSFTsoldonthemarketasinpapersandprojects,followedbycropprotectionand
irrigation,whicharethethreemostcrucialagriculturalpracticesformostcrops.SincetheSFTmarket
intheEUisstillinitsinfancy,companiesaredirectedmainlytowardtheseapplicationsthatareof
highimportanceforfarmers.Companiesthatwillsurviveorevenevolverapidlyneedtodemonstrate
dynamiccapabilities(inthiscase,tooffereffectiveandefficientSFTswithtangibleresults),move
beyondconventionalagriculturalmachineryandgainacompetitiveadvantagethatgenerateslong‐
termSchumpeterianrents[116].Itisinterestingtopointoutthatnotonlytillage,butalso
sowing/transplantinghavesignificantrepresentationintheindustrialSFTs,possiblyillustratingthat
suchtechnologiesarealreadymatureinthemarket(oratleasttheiraccuracyisadequatefor
practitioners)and,therefore,researchwasnotdirectedtowardtheminrecentyears.
3.5.FactorsThatCanBeExpectedtoAffectAdoptionofSFTs
BasedonthesevenstatementsoftheRogersframework(Section2.3.5),theinventoriedSFTs
wereassessedintermsofaffectingadoptionreadiness.Theresultsforscientificpapers,research
projects,andindustrialproductsareshowninFigure5.
BycomparingtheresultsofthethreeSFTcategories,itisobviousthatthereisaconstanttrend
ofchangeforallsevenstatementsoftheRogersframework,movingfromscientificpapers(newideas
withlowTRL)toresearchprojects(morematureideaswithhigherTRL)andfinallyindustrial
products(maturecommercialsolutionsofTRL9).Morespecifically,SFTspresentedinscientific
papersarenotindicatedasasignificantreplacementofanexistingtool,whilethisisquitemore
prominentformostoftheSFTslistedinresearchprojectsandcommercialproducts.Probably,new
SFTsdevelopedfromscientistsareyettofindtheiractualplaceinagriculturalpractice,while,in
projectsandespeciallyinH2020EUprojects,theroleofandtheneedforthedevelopedSFTswere
alreadyidentifiedfromscratch.AsforthecommercialSFTs,oneofthemainreasonsforaproductto
bemarketedisitsabilitytoreplaceexistingtechnologyandtoeasetheend‐user’sbusiness[117,118].
Regardingtheneedformajorchangesinexistingsystems,researchersinscientificpapersare
workingonradicalconceptsthatwillmakeachangeinexistingfarmingpractices,whileresearch
projectsand,toagreaterextent,commercialproductsaredirectedtowardsolutionsthatcancover
theneedsoffarmersbyadjustingtheirexistingsystems[29].SFTsinscientificpapersseemtorequire

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lesslearningfromtheend‐userthanthoseinresearchprojectsandcommercialproducts.Thisresult
wasexpected,asresearchersbelievethattheirideasareeasilyinterpretedbyauserastheyhavegreat
knowledgeofwhattheyareworkingon,while,astheSFTmovesintorealconditions,itbecomes
obviousthatatypicalfarmerwillhavetobetaughtthesenewICTsolutionsthattheyarenotusedto
byincreasingtheirSFTliteracy,whichisoneofthemainbarriersforSFTadoption[119].

Figure5.Responsesregardingadoptionreadinessofthesmartfarmingtechnologies(SFTs)identified
inscientificpapers,researchprojects,andcommercialproductsusingtheRogersframework[102]
basedonaLikertscaleoffivelevels(stronglydisagreetostronglyagree).
Atypicalinventionpresentedinascientificpapercannotbethoughtofasasolutionforother
purposesthantheoneitwasdirectedtoand,hence,itwasnotindicatedassuch.SFTsinresearch
projectsandincommercialproductsaremoreabletobeusedforotherpurposesthanintendeddue
totheircloserrelationshipwitheverydayfarmingandtheirhighercompatibilitywithexisting
machinery,whichneverthelessremainsasignificantbarrier,eveninindustrialSFTs[29,63,120].The
directeffectofSFTsisnotvisibleinimmaturetechnologiespresentedinscientificpapers.However,
inlargeresearchprojectsandcommercialproducts,thesedirecteffectswereinvestigatedmore
rigorously;forthelatter,theneedforthisinvestigationstemsfromaneedtobemarketedwith
tangibleeffectsonthefarm,i.e.,thepotentialend‐user[121,122],whichunfortunatelyremainsoneof
thesignificantbarriersforSFTadoption[64].Indeed,amajorfactorinthediffusionofanytechnology
istheacquisitionofinformationbytheend‐user[123,124].Thistypeofinformationneedstoinclude,
butnotbelimitedto,thebenefitsofadoptingthetechnology,thecompatibilitywithexisting
technologies,andrelativeadvantagesincomparisonwithsubstitutetechnologies.Naturally,this
typeofinformationcannotbeconveyedtotheend‐userwhenSFTsarestillintheearlystagesof
researchaspresentedinscientificpapers.Whilemoreinformationcanbeavailabletothefarmerin
large‐scaleprojects,completeinformationcanbemoreefficientlyconveyedintermsofitstangible
effectsviacommercialproducts.
ThetimethatanSFTrequiresforitsusertobeacquaintedwithwasdeclaredaslongerin
prototypesproducedinscientificpapersthaninresearchprojectsandindustrialproducts,where
structuredmanualsandhelpdesksupportisavailablefromscratch.Finally,anSFTinscientific
papersisinmostcasesimmature,andthedataderivedfromitrequirelongprocessingtoprovide

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usefulinformation,whileresearchprojectsaremorematureandindustrialproductsinparticular
needtomaketheclient’slifeeasierbyprovidingfastandclearinformationofdecision‐making.
3.6.EffectsonFarmEconomics,theEnvironment,andLabor
Theeffectsonthe26differentaspectsdescribedinSection2.3.6weredifferentforSFTsderived
fromscientificpapers,researchprojects,andindustrialproducts(Figure6).ItcanbeseenthatSFTs
fromscientificpapers(Figure6a)didnotfocusontheirimpact,ratherthantheirfunctionalityand
reliableresultsinthepromisedaction[37],while,inresearchprojects(Figure6b)whichmainly
involveinnovationorresearchandinnovationactions(IAorRIA)[125],themajorityofSFTsolutions
wereassessedintermsofeconomic,environmental,andlaborimpact,andtheirbenefitswere
revealed.Asforcommercialproducts,Figure6cpresentsthatmostofthe26aspectswereinfluenced
toanextentbetweenscientificpapersandresearchprojects.Thisfactshowsthatthereboundeffect
ofusingcommercialSFTsineverydayfarmingcouldreducethedeclaredpositiveeffectsofSFTsin
allaspects[64,65].Italsoindicatesthatproductprovidersmightbemodestinwhattheypromise,so
thatenoughpositiveimpactsareprovidedtothecustomerstoseetangibleresultsandtoincrease
trustintheseproducts.Inaddition,commercialproductsweretheonlycategoryamongpapers,
projects,andproductswhereoppositeopinionsabouttheireffectwerefound,whichindicatesthat
marketedSFTswhichareappliedinrealconditionsarealsofollowedbydisadvantages.However,it
shouldbepointedoutthat,eveninthiscase,thedeclarednegativeeffectswereverylimited,showing
thepotentialofSFTsforagriculturalproductionimprovement.

(a)

(b)

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

(c)
Figure6.Effectsoftheidentifiedsmartfarmingtechnologies(SFTs)onfarmeconomics,the
environment,andlaborusingaqualitativeassessmentofSFTsin(a)scientificarticles,(b)research
papers,and(c)commercialproductsbasedonaLikertscaleoffivelevels(largedecreasetolarge
increase).
3.6.1.FarmEconomics
Productivity,revenue,andqualityareexpectedtoincreasewhenusingallSFTs.Indeed,
numerousreviewsindicatedthatSFTscanproducepositiveeconomicresultsincomparisonto
conventionalpractices[37,126–129].Thesethreeaspectsfollowasimilartrendofexpectedincrease
fromscientificpaperstoresearchprojectsandthentocommercialproducts,indicatingthat
innovativeSFTsbecomecommercialwhenitisbelievedthattheeconomicgainsforfarmsare
significantandthatthisisthemainaimofproductproviders[117].Ontheotherhand,theremaining
economicaspects(inputandvariablecosts,cropwastage,andenergyuse)followedanothertrend,
withresearchprojectspromisinghigherimpactsthanindustrialproductsandscientificpapers(in
thisorder).ThismaybeexplainedbyresearchprojectsassessingseveralaspectsofSFTperformance,
whilescientificpapersfocusmainlyontechnologicalachievementsandcommercialproductsin
termsoftheSFTeconomicgainsfortheend‐user.Anotherreasoncouldalsobetheself‐promotionof
researchprojectstocovertheexpectationsoffundingauthorities.
3.6.2.Environment
Amongthe14environmentalaspects,themostinfluencedinallcategorieswereagricultural
inputs(fertilizers,pesticides,andirrigationwater).Thisfindingisconnectedwiththeinputand
variablecosteffectofSection3.6.1andwiththemainprincipleofSFTstomaintainorincrease
productionwithloweragriculturalinputs[130].Onthecontrary,theleastaffectedaspectswere
gaseousemissionsofalltypes(withCO
2
beingthemostaffected),indicatingthateitherthereis
limitedeffectorthatitisyettobeinvestigatedthoroughlybyresearchersandindustry[37].Weed,
pest,anddiseasepressurecanalsobereducedbySFTapplication,whichisconnectedtoreduced
pesticideusethatislessneededduetolowerpressure.Anincreasein(soil)biodiversitywasalso
declared,probablybecauserationalinputusederivedfromSFTapplicationreducestheeffecton
faunaandflora,leadingtobiodiversitypreservation[131].Allenvironmentalaspectswerefoundto
bemoreaffectedbyprojectSFTsthanbyproductorpaperSFTs,showingthesametrendasthe
economicaspectsinSection3.6.1.

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3.6.3.Labor
Labortimeandfarmers’stresswerethemostaffectedaspectsasSFTsfacilitateallagricultural
practices.Itshouldbepointedoutthat,eveniffarmers’stressisshowntobereducedsignificantly,
theactualuseofanSFTcaninvolvequitesomeupfrontstress,becauseoftheneedtoprocess
informationandcalibratethetechnology,aswellaswhentechnologiesfail.Stresslevelisdifferent
amongSFTtypes,withguidancetechnologiesthatarefunctionalandefficientforyearsreducing
stressalotmorethanvariableratetechnologiesthatrequiredetailedandcontinuouscalibrationto
operateproperlycomparedtoconventionaluniformapplication.End‐userlaborheavinesswasalso
declaredtobereduced,whileinjuriesandaccidentswerenotpresentedasveryaffected.These
findingsshowhowICTsolutionsprovidedbySFTsaresupposedtomakefarmers’liveseasierand
thattheyareinlinewithseveralresearchstudiesonthissubject.Meyer‐Aurichetal.(2008)[132]
showedthatprecisionagriculturetechnologiescanreducelaborduetotheautomationofvariable
rateapplication,whilePedersenetal.(2006)[133]presentedthatprecisionagricultureislesslabor‐
intensiveandcanreducerestrictionsonavailabledailyworkinghours.Inaddition,Batte(2003)[134]
introducedtheindirectimpactofguidancetechnologiesontheavailabilityoflaborforother
agriculturalwork.
4.Conclusions
AlargenumberofSFTs(1064)derivedfromscientificpapers(531),researchprojects(94),and
commercialproducts(439)werecollectedandanalyzedinthiswork.Theywereaccompaniedby
additionalinformationabouttheirtypeandfieldoperationusedfor,aswellasinrelationtotheir
adoptionreadinessexpectationsandtheireconomic,environmental,andlaborimpact.Scientific
papersmainlyfocusedonrecordingtechnologies,whileresearchprojectsfocusedonhigh‐endFMIS
translatingthecollecteddatatovaluabledecisions.Commercialproductsweremorebalanced
betweenSFTtypes,withrecordingandFMISagainreceivingthehighestattention,withreactingand
robotic/automationtechnologiesalsohighlyrepresented,asfarmersrequireexecutablesolutionsfor
theireverydayoperations.ThecollectedSFTsofscientificpapersweremainlyusedforcropandsoil
scouting,andtheresearchprojectsweremostlyrelatedtofertilization,whilecommercialSFTswere
directedtowardthethreemostcrucialagriculturalpracticesformostcrops,namely,fertilization,
cropprotection,andirrigation.
ThefactorsaffectingadoptionreadinessofSFTsshowedaconstanttrendofchange.SFTsfrom
researchprojectsandcommercialproductswereindicatedasasignificantreplacementofexisting
solutions,butnotbringingmajorchangesinexistingagriculturalsystems.SFTsinscientificpapers
wereindicatedasrequiringlesslearningfromtheend‐usersthaninresearchprojectsandevenmore
soincommercialproducts.Finally,datafromSFTsinscientificpapersweredifficulttointerpretinto
usefulinformation,whileresearchprojectsandespeciallyindustrialproductsprovidedclearer
informationtotheend‐user.
Theeconomic,environmental,andlaboreffectsoftheinventoriedSFTsweredifferentin
scientificpapers,researchprojects,andindustrialproducts.Scientificpapersdidnotprovidespecific
impactstatements,whilebenefitsordrawbacksofSFTsinresearchprojectswerehighlyinvestigated,
asthisisrequiredbyresearchfundingagencies;commercialSFTswerealsodeclaredtohave
adequatelyhighimpact.Regardingfarmeconomics,commercialSFTswereindicatedashavingthe
highestexpectedincreaseinproductivity,revenue,andquality,while,forinputandvariablecosts,
cropwastage,andenergyuse,SFTsfromresearchprojectspromisedhigherimpactsthancommercial
productsandscientificpapers.Asfortheenvironmentalimpact,themostinfluencedenvironmental
aspectsinallcategorieswereagriculturalinputreduction(fertilizers,pesticides,andirrigation
water).Onthecontrary,theleastaffectedaspectsweregaseousemissionsofalltypes.Intermsof
labor,workingtimeandfarmers’stresswerethemostaffectedaspects,whileworkheavinesswas
alsodeclaredtobereduced;injuries/accidentswerenotaffectedtoahighextent.
Fromthiswork,itwasrevealedthatresearchisslowlyshiftingfromrecordingtechnologiesto
actuationtechnologies,whiletheshareofscientificpapersonreactingandrobotics/automationsis

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increasing(albeitfromalowbase).However,recordingtechnologiesstilloccupythemajorityofSFTs
withmanynew(typesof)sensorsandmeasurementmethodsfound,especiallyinscientificpapers.
Thisseemstoindicatethatthereisaknowledgegapbetween,ontheonehand,measuringthe
statusofcropandsoiland,ontheotherhand,usingthatinformationtomakepracticaldecisionsin
farming.Therefore,researchisneededtoprovidetheknowledgethatwillallowrecordingSFTstobe
appliedinpractice.Inparticular,moreresearchisneededtoprovideoptimizedalgorithms,easily
calibratedsensor/applicationequipment,andhigherapplicationprecisionforvariableratepesticide
orfertilizerapplication,aswellasvariablerateseedingandtillage.Itisexpectedthat
robots/automationforweedcontrolandotheroperationswilldeliverlargebenefitsinreducinglabor
demandandinputuse;however,atpresent,fewSFTscanbeclassifiedassuch.Therefore,research
shouldalsobedirectedtowardthesetechnologies,atrendthatwasalsoshownbyourwork.
Finally,onlyafewSFTsidentifiedinourinventoryexplicitlyaddressedissuesrelatedtodata
management,suchasownership,datatransfer,sharing,security,andprivacy.Thisisnotsurprising
becausetheseissuesare,toalargedegree,organizationalissuesthatcannotbesolvedbyatechnology
alone.Itisclearthattechnical,social,andlegalbarriersrelatedtocollecting,storing,andtransferring
datahinderfarmers’transitiontosmartfarming,anddatasecurityandprivacyimplicationsresulting
fromasecuritybreachareamajorconcernforthedigitizationprocessofagriculture.
ItwasconcludedthattheinventoryofSFTsdescribedinthisstudyisimportantinthesensethat
itprovidesresearcherswithexistingSFTdevelopmentstoseeknewresearchchallenges,policy‐
makerswithinformationonthecurrentstatusofSFTstodesignincentivesforhigheradoptionrates,
andfarmerswithanopportunitytoacquaintthemselveswiththeSFTsthatareavailable.However,
thisworkalsoidentifiedthefactthatresearchersandSFTprovidersinmostcasesdidnotproduce
quantitativeimpactresultswiththeuseoftheirSFTs,whichmakesourstudystillindicativeabout
theimpactofSFTs,asweanalyzedmainlyqualitativecriteria.Inaddition,thisinventoryshouldbe
updatedregularlyasthetechnologyismovingfastandnewfarmersaregettingmoreawareofthe
availableSFTsonthemarket.Therefore,afollow‐uptothepresentstudywouldbebeneficialin
creatinganinventoryalsoincludingdata‐relatedtechnologies,practices,standards,andagreements,
aswellasnumericalresultsofSFTimpactinrealconditions.
AuthorContributions:Conceptualization,F.K.V.E.,S.F.,andA.T.B.;methodology,F.K.V.E.,A.T.B.,andS.F.;
questionnairefillingandsurvey,A.T.B,F.K.V.E.,andS.F.;dataanalysis,F.K.V.E.andA.T.B.;writing—review
andediting,A.T.B.,F.K.V.E.,andS.F.Allauthorshavereadandagreedtothepublishedversionofthe
manuscript.
Funding:ThispaperwassupportedbytheEuropeanUnion’sHorizon2020coordinationandsupportprogram
undergrantagreementNo696264,projectSmart‐AKIS“EuropeanAgriculturalKnowledgeandInnovation
Systems(AKIS)towardinnovation‐drivenresearchinSmartFarmingTechnology”.
Acknowledgments:TheauthorswouldliketoacknowledgethecontributionofFennyvanEgmond,Michael
Koutsiaras,VassilisPsiroukis,andDinosGrivakisintheinventorypreparation.
ConflictsofInterest:Theauthorsdeclarenoconflictsofinterest.Thefundershadnoroleinthedesignofthe
study;inthecollection,analyses,orinterpretationofdata;inthewritingofthemanuscript,orinthedecisionto
publishtheresults.
Abbreviations
FMISFarmmanagementinformationsystem
DSSDecisionsupportsystem
QRQuickResponse
RFIDRadiofrequencyidentification
VRAVariablerateapplication
RTIReturnabletransportitems
SFMTSmartfarmingmovingtechnologies
SFTSmartfarmingtechnology


Agronomy2020,10,74320of25
References
1. Gomiero,T.;Pimentel,D.;Paoletti,M.G.IsThereaNeedforaMoreSustainableAgriculture?Crit.Rev.
PlantSci.2011,30,6–23.
2. World,B.ICTinAgriculture(UpdatedEdition):ConnectingSmallholderstoKnowledge,Networks,and
Institutions;WorldBank:Washington,DC,USA,2017.
3. Wang,N.;Zhang,N.;Wang,M.Wirelesssensorsinagricultureandfoodindustry—Recentdevelopment
andfutureperspective.Comput.Electron.Agric.2006,50,1–14.
4. Aqeelur,R.;Abbasi,A.Z.;Islam,N.;Shaikh,Z.A.Areviewofwirelesssensorsandnetworksʹapplications
inagriculture.Comput.Stand.Interfaces2014,36,263–270.
5. King,A.Technology:TheFutureofAgriculture.Nature2017,544,S21–S23.
6. Toth,C.;Jóźków,G.Remotesensingplatformsandsensors:Asurvey.IsprsJ.Photogramm.RemoteSens.
2016,115,22–36.
7. Mahan,J.R.;Yeater,K.M.Agriculturalapplicationsofalow‐costinfraredthermometer.Comput.Electron.
Agric.2008,64,262–267.
8. Polo,J.;Hornero,G.;Duijneveld,C.;García,A.;Casas,O.,Designofalow‐costWirelessSensorNetwork
withUAVmobilenodeforagriculturalapplications.Comput.Electron.Agric.2015,119,19–32.
9. Kumar,A.;Kamal,K.;Arshad,M.O.;Mathavan,S.;Vadamala,T.Smartirrigationusinglow‐costmoisture
sensorsandXBee‐basedcommunication.InProceedingsoftheIEEEGlobalHumanitarianTechnology
Conference(GHTC2014),SanJose,CA,USA,10–13October2014;pp.333–337.
10. Kumar,S.A.;Ilango,P.TheImpactofWirelessSensorNetworkintheFieldofPrecisionAgriculture:A
Review.Wirel.Pers.Commun.2018,98,685–698.
11. Rose,D.C.;Chilvers,J.Agriculture4.0:BroadeningResponsibleInnovationinanEraofSmartFarming.
Front.Sustain.FoodSyst.2018,2.doi:10.3389/fsufs.2018.00087.
12. Walter,A.;Finger,R.;Huber,R.;Buchmann,N.Opinion:Smartfarmingiskeytodevelopingsustainable
agriculture.Proc.Natl.Acad.Sci.USA2017,114,6148.
13. Bacco,M.;Berton,A.;Ferro,E.;Gennaro,C.;Gotta,A.;Matteoli,S.;Paonessa,F.;Ruggeri,M.;Virone,G.;
Zanella,A.Smartfarming:Opportunities,challengesandtechnologyenablers.InProceedingsofthe2018
IoTVerticalandTopicalSummitonAgriculture—Tuscany(IOTTuscany),Tuscany,Italy,8–9May2018;
pp.1–6.
14. Bacco,M.;Barsocchi,P.;Ferro,E.;Gotta,A.;Ruggeri,M.TheDigitisationofAgriculture:ASurveyof
ResearchActivitiesonSmartFarming.Array2019,3–4,100009.
15. Nawar,S.;Corstanje,R.;Halcro,G.;Mulla,D.;Mouazen,A.M.ChapterFour—DelineationofSoil
ManagementZonesforVariable‐RateFertilization:AReview.InAdvancesinAgronomy;Sparks,D.L.,Ed.;
AcademicPress:Cambridge,MA,USA,2017;Volume143,pp.175–245.
16. Alameen,A.A.;Al‐Gaadi,K.A.;Tola,E.Developmentandperformanceevaluationofacontrolsystemfor
variablerategranularfertilizerapplication.Comput.Electron.Agric.2019,160,31–39.
17. Stamatiadis,S.;Schepers,J.S.;Evangelou,E.;Glampedakis,A.;Glampedakis,M.;Dercas,N.;Tsadilas,C.;
Tserlikakis,N.;Tsadila,E.Variable‐rateapplicationofhighspatialresolutioncanimprovecottonN‐use
efficiencyandprofitability.Precis.Agric2020,21,695–712.
18. Boursianis,A.D.;Papadopoulou,M.S.;Diamantoulakis,P.;Liopa‐Tsakalidi,A.;Barouchas,P.;Salahas,G.;
Karagiannidis,G.;Wan,S.;Goudos,S.K.InternetofThings(IoT)andAgriculturalUnmannedAerial
Vehicles(UAVs)inSmartFarming:AComprehensiveReview.InternetThings2020,100187.
doi:10.1016/j.iot.2020.100187.
19. Muangprathub,J.;Boonnam,N.;Kajornkasirat,S.;Lekbangpong,N.;Wanichsombat,A.;Nillaor,P.IoT
andagriculturedataanalysisforsmartfarm.Comput.Electron.Agric.2019,156,467–474.
20. Falco,G.;Nicola,M.;Pini,M.;Marucco,G.;Wilde,W.D.;Popugaev,A.;Gay,P.;Aimonino,D.R.
InvestigationofperformanceofGNSS‐baseddevicesforprecisepositioninginharshagriculture
environments.InProceedingsofthe2019IEEEInternationalWorkshoponMetrologyforAgricultureand
Forestry(MetroAgriFor),Portici,Italy,24–26October2019;pp.1–6.
21. Stombaugh,T.Satellite‐basedPositioningSystemsforPrecisionAgriculture.InPrecisionAgricultureBasics;
AmericanSocietyofAgronomy;CropScienceSocietyofAmerica;SoilScienceSocietyofAmerica:
Madison,WI,USA,2018;pp.25–36.
22. Kamilaris,A.;Kartakoullis,A.;Prenafeta‐Boldú,F.X.Areviewonthepracticeofbigdataanalysisin
agriculture.Comput.Electron.Agric.2017,143,23–37.

Agronomy2020,10,74321of25
23. Bronson,K.;Knezevic,I.BigDatainfoodandagriculture.BigDataSoc.2016,3.
doi:10.1177/2053951716648174.
24. Wolfert,S.;Ge,L.;Verdouw,C.;Bogaardt,M.‐J.BigDatainSmartFarming—Areview.Agric.Syst.2017,
153,69–80.
25. Tsouros,C.D.;Bibi,S.;Sarigiannidis,G.P.AReviewonUAV‐BasedApplicationsforPrecisionAgriculture.
Information2019,10,349.
26. Hajjaj,S.S.H.;Sahari,K.S.M.Reviewofagriculturerobotics:Practicalityandfeasibility.InProceedingsof
the2016IEEEInternationalSymposiumonRoboticsandIntelligentSensors(IRIS),Tokyo,Japan,17–20
December2016;pp.194–198.
27. Marinoudi,V.;Sørensen,C.G.;Pearson,S.;Bochtis,D.Roboticsandlabourinagriculture.Acontext
consideration.Biosyst.Eng.2019,184,111–121.
28. Balafoutis,A.T.;Beck,B.;Fountas,S.;Tsiropoulos,Z.;Vangeyte,J.;vanderWal,T.;Soto‐Embodas,I.;
Gómez‐Barbero,M.;Pedersen,S.M.SmartFarmingTechnologies—Description,TaxonomyandEconomic
Impact.InPrecisionAgriculture:TechnologyandEconomicPerspectives;Pedersen,S.M.,Lind,K.M.,Eds.;
SpringerInternationalPublishing:Cham,Switzerland,2017;pp.21–77.
29. Kernecker,M.;Knierim,A.;Wurbs,A.;Kraus,T.;Borges,F.Experienceversusexpectation:farmers’
perceptionsofsmartfarmingtechnologiesforcroppingsystemsacrossEurope.Precis.Agric2020,21,34–
50.
30. Lewis,T.Evolutionoffarmmanagementinformationsystems.Comput.Electron.Agric.1998,19,233–248.
31. Kitchen,N.R.Emergingtechnologiesforreal‐timeandintegratedagriculturedecisions.Comput.Electron.
Agric.2008,61,1–3.
32. Kaloxylos,A.;Eigenmann,R.;Teye,F.;Politopoulou,Z.;Wolfert,S.;Shrank,C.;Dillinger,M.;
Lampropoulou,I.;Antoniou,E.;Pesonen,L.;etal.FarmmanagementsystemsandtheFutureInternetera.
Comput.Electron.Agric.2012,89,130–144.
33. Fountas,S.;Carli,G.;Sørensen,C.G.;Tsiropoulos,Z.;Cavalaris,C.;Vatsanidou,A.;Liakos,B.;Canavari,
M.;Wiebensohn,J.;Tisserye,B.Farmmanagementinformationsystems:Currentsituationandfuture
perspectives.Comput.Electron.Agric.2015,115,40–50.
34. Finger,R.;Swinton,S.M.;ElBenni,N.;Walter,A.PrecisionFarmingattheNexusofAgricultural
ProductionandtheEnvironment.Annu.Rev.Resour.Econ.2019,11,313–335.
35. Zhang,N.;Wang,M.;Wang,N.Precisionagriculture—Aworldwideoverview.Comput.Electron.Agric.
2002,36,113–132.
36. Schellberg,J.;Hill,M.J.;Gerhards,R.;Rothmund,M.;Braun,M.Precisionagricultureongrassland:
Applications,perspectivesandconstraints.Eur.J.Agron.2008,29,59–71.
37. Balafoutis,A.;Beck,B.;Fountas,S.;Vangeyte,J.;Wal,T.V.d.;Soto,I.;Gómez‐Barbero,M.;Barnes,A.;Eory,
V.PrecisionAgricultureTechnologiesPositivelyContributingtoGHGEmissionsMitigation,Farm
ProductivityandEconomics.Sustainability2017,9,1339.
38. Ge,Y.;Thomasson,J.A.;Sui,R.Remotesensingofsoilpropertiesinprecisionagriculture:Areview.Front.
EarthSci.2011,5,229–238.
39. Brisco,B.;Brown,R.J.;Hirose,T.;McNairn,H.;Staenz,K.PrecisionAgricultureandtheRoleofRemote
Sensing:AReview.Can.J.RemoteSens.1998,24,315–327.
40. Thorp,K.R.;Tian,L.F.AReviewonRemoteSensingofWeedsinAgriculture.Precis.Agric2004,5,477–508.
41. Zhang,C.;Kovacs,J.M.Theapplicationofsmallunmannedaerialsystemsforprecisionagriculture:A
review.Precis.Agric2012,13,693–712.
42. Abdullahi,H.S.;Mahieddine,F.;Sheriff,R.E.TechnologyImpactonAgriculturalProductivity:AReview
ofPrecisionAgricultureUsingUnmannedAerialVehicles.InWirelessandSatelliteSystems,Proceedingsof
the7thInternationalConference,WiSATS2015,Bradford,UK,6–7July2015;Pillai,P.,Hu,Y.F.,Otung,I.,
Giambene,G.,Eds.;SpringerInternationalPublishing:Cham,Switzerland,2015;pp.388–400.
43. Mogili,U.M.R.;Deepak,B.B.V.L.ReviewonApplicationofDroneSystemsinPrecisionAgriculture.
ProcediaComput.Sci.2018,133,502–509.
44. Reyns,P.;Missotten,B.;Ramon,H.;DeBaerdemaeker,J.AReviewofCombineSensorsforPrecision
Farming.Precis.Agric2002,3,169–182.
45. Awasthi,S.R.N.R.A.MonitoringforPrecisionAgricultureusingWirelessSensorNetwork‐Areview.Glob.
J.Comput.Sci.Technol.2013,13,ISSN0975‐4172.Availableonline:
https://computerresearch.org/index.php/computer/article/view/391(accessedon20February2020).

Agronomy2020,10,74322of25
46. Jawad,M.H.;Nordin,R.;Gharghan,K.S.;Jawad,M.A.;Ismail,M.Energy‐EfficientWirelessSensor
NetworksforPrecisionAgriculture:AReview.Sensors2017,17,1781.
47. Nash,E.;Korduan,P.;Bill,R.Applicationsofopengeospatialwebservicesinprecisionagriculture:A
review.Precis.Agric2009,10,546.
48. Lindblom,J.;Lundström,C.;Ljung,M.;Jonsson,A.Promotingsustainableintensificationinprecision
agriculture:Reviewofdecisionsupportsystemsdevelopmentandstrategies.Precis.Agric2017,18,309–
331.
49. Kuhlmann,F.;Brodersen,C.Informationtechnologyandfarmmanagement:Developmentsand
perspectives.Comput.Electron.Agric.2001,30,71–83.
50. Chlingaryan,A.;Sukkarieh,S.;Whelan,B.Machinelearningapproachesforcropyieldpredictionand
nitrogenstatusestimationinprecisionagriculture:Areview.Comput.Electron.Agric.2018,151,61–69.
51. Behmann,J.;Mahlein,A.‐K.;Rumpf,T.;Römer,C.;Plümer,L.Areviewofadvancedmachinelearning
methodsforthedetectionofbioticstressinprecisioncropprotection.Precis.Agric2015,16,239–260.
52. Liakos,K.G.;Busato,P.;Moshou,D.;Pearson,S.;Bochtis,D.MachineLearninginAgriculture:AReview.
Sensors2018,18,2674.
53. Patrício,D.I.;Rieder,R.Computervisionandartificialintelligenceinprecisionagricultureforgraincrops:
Asystematicreview.Comput.Electron.Agric.2018,153,69–81.
54. Brosnan,T.;Sun,D.‐W.Inspectionandgradingofagriculturalandfoodproductsbycomputervision
systems—Areview.Comput.Electron.Agric.2002,36,193–213.
55. Vázquez‐Arellano,M.;Griepentrog,W.H.;Reiser,D.;Paraforos,S.D.3‐DImagingSystemsforAgricultural
Applications—AReview.Sensors2016,16,618.
56. Mousazadeh,H.Atechnicalreviewonnavigationsystemsofagriculturalautonomousoff‐roadvehicles.J.
Terramechanics2013,50,211–232.
57. Bergerman,M.;Billingsley,J.;Reid,J.;vanHenten,E.RoboticsinAgricultureandForestry.InSpringer
HandbookofRobotics;Siciliano,B.,Khatib,O.,Eds.;SpringerInternationalPublishing:Cham,Switzerland,
2016;pp.1463–1492.
58. Bechar,A.;Vigneault,C.Agriculturalrobotsforfieldoperations:Conceptsandcomponents.Biosyst.Eng.
2016,149,94–111.
59. Bechar,A.;Vigneault,C.Agriculturalrobotsforfieldoperations.Part2:Operationsandsystems.Biosyst.
Eng.2017,153,110–128.
60. Slaughter,D.C.;Giles,D.K.;Downey,D.Autonomousroboticweedcontrolsystems:Areview.Comput.
Electron.Agric.2008,61,63–78.
61. Bac,C.W.;vanHenten,E.J.;Hemming,J.;Edan,Y.HarvestingRobotsforHigh‐valueCrops:State‐of‐the‐
artReviewandChallengesAhead.J.FieldRobot.2014,31,888–911.
62. Erickson,B.;Lowenberg‐DeBoer,J.2019PrecisionAgricultureDealershipSurvey:MoreMovesToward
DecisionAgriculture.Availableonline:https://www.croplife.com/management/2019‐precision‐
agriculture‐dealership‐survey‐more‐moves‐toward‐decision‐agriculture/(accessedon18March2020).
63. Barnes,A.P.;Soto,I.;Eory,V.;Beck,B.;Balafoutis,A.;Sánchez,B.;Vangeyte,J.;Fountas,S.;vanderWal,
T.;Gómez‐Barbero,M.Exploringtheadoptionofprecisionagriculturaltechnologies:Acrossregional
studyofEUfarmers.LandUsePolicy2019,80,163–174.
64. Barnes,A.P.;Soto,I.;Eory,V.;Beck,B.;Balafoutis,A.T.;Sanchez,B.;Vangeyte,J.;Fountas,S.;vanderWal,
T.;Gómez‐Barbero,M.InfluencingincentivesforprecisionagriculturaltechnologieswithinEuropean
arablefarmingsystems.Environ.Sci.Policy2019,93,66–74.
65. Schieffer,J.;Dillon,C.Theeconomicandenvironmentalimpactsofprecisionagricultureandinteractions
withagro‐environmentalpolicy.Precis.Agric2015,16,46–61.
66. VonAhlefeld,P.J.W.Reboundeffectsinprecisionagriculture—Acommentary.Ber.ÜberLandwirtsch.Z.
FürAgrar.UndLandwirtsch.2019.doi:10.12767/buel.v97i3.247.g452.
67. Paul,C.;Techen,A.‐K.;Robinson,J.S.;Helming,K.Reboundeffectsinagriculturallandandsoil
management:Reviewandanalyticalframework.J.Clean.Prod.2019,227,1054–1067.
68. Pretty,J.;Smith,G.;Goulding,K.W.T.;Groves,S.J.;Henderson,I.;Hine,R.E.;King,V.;vanOostrum,J.;
Pendlington,D.J.;Vis,J.K.;etal.Multi‐yearassessmentofUnileverʹsprogresstowardsagricultural
sustainabilityI:Indicators,methodologyandpilotfarmresults.Int.J.Agric.Sustain.2008,6,37–62.
69. Walter,C.;Stützel,H.Anewmethodforassessingthesustainabilityofland‐usesystems(I):Identifying
therelevantissues.Ecol.Econ.2009,68,1275–1287.

Agronomy2020,10,74323of25
70. Bockstaller,C.;Guichard,L.;Makowski,D.;Aveline,A.;Girardin,P.;Plantureux,S.Agri‐environmental
indicatorstoassesscroppingandfarmingsystems.Areview.Agron.Sustain.Dev.2008,28,139–149.
71. EuropeanEnvironmentAgency.DigestofEEAIndicators2014;EEATechnicalReportNo.8/2014;European
EnvironmentAgency:København,Denmark,2014.
72. OECD.OECDCompendiumofAgri‐EnvironmentalIndicators;OECDPublishing:Paris,France,2013.
73. TheSustainabilityConsortium.Availableonline:https://www.sustainabilityconsortium.org/(accessedon
28March2020).
74. GlobalReportingInitiative.Availableonline:https://www.globalreporting.org(accessedon28March
2020).
75. FoodandAgricultureOrganisationoftheUnitedNations,ProductivityandEfficiencyMeasurementin
Agriculture.Availableonline:https://www.fao.org/3/ca6428en/ca6428en.pdf(accessedon22February
2020).
76. UnitedNations.GlossaryofTermsforUsewithUNECEStandardsonFreshFruitandVegetables2016.
Availableonline:
https://www.unece.org/fileadmin/DAM/trade/agr/standard/fresh/StandardLayout/Glossary_FFV_2016_E.
pdf(accessedon22February2020).
77. Wikipedia.AvailableOnline:https://en.wikipedia.org/wiki/Revenue(accessedon22February2020).
78. EuropeanCommission.OverviewoftheAgriculturalInputSectorintheEU.AvailableOnline:
https://www.europarl.europa.eu/RegData/etudes/STUD/2015/563385/IPOL_STU(2015)563385_EN.pdf
(accessedon22February2020).
79. InvestingAnswers.Availableonline:https://investinganswers.com/dictionary/v/variable‐costs(accessed
on22February2020).
80. FoodandAgricultureOrganisationoftheUnitedNations.FoodLossandFoodWaste.Availableonline:
www.fao.org/food‐loss‐and‐food‐waste/en/(accessedon22February2020).
81. CambridgeDictionary.Availableonline:https://dictionary.cambridge.org/dictionary/english/energy‐
usage(accessedon22February2020).
82. EuropeanSoilDataCentre,JointResearchCentre.Availableonline:
https://esdac.jrc.ec.europa.eu/themes/soil‐biodiversity(accessedon22February2020).
83. CambridgeDictionary.Availableonline:https://dictionary.cambridge.org/dictionary/english/biodiversity
(accessedon22February2020).
84. FoodandAgricultureOrganisationoftheUnitedNations.FertiliserandPlantNutritionBulletin6.
Availableonline:http://www.fao.org/3/aq352e/aq352e.pdf(accessedon22February2020.
85. EuropeanCommission.PesticideResidues.Availableonline:
https://ec.europa.eu/assets/sante/food/plants/pesticides/lop/index.html(accessedon22February2020).
86. UnitedStatesGeologicalSurvey.Availableonline:https://www.usgs.gov/mission‐areas/water‐
resources/science/irrigation‐water‐use?qt‐science_center_objects=0#qt‐science_center_objects(accessedon
22February2020).
87. FoodandAgricultureOrganisationoftheUnitedNations.EstimatingGreenhouseGasEmissionsin
Agriculture.Availableonline:http://www.fao.org/3/a‐i4260e.pdf(accessedon22February2020.
88. Buijsman,E.;Maas,H.F.M.;Asman,W.A.H.AnthropogenicNH3emissionsinEurope.Atmos.Environ.
1987,21,1009–1022.
89. Oenema,O.;Boers,P.C.M.;vanEerdt,M.M.;Fraters,B.;vanderMeer,H.G.;Roest,C.W.J.;Schröder,J.J.;
Willems,W.J.Leachingofnitratefromagriculturetogroundwater:Theeffectofpoliciesandmeasuresin
theNetherlands.Environ.Pollut.1998,102,471–478.
90. IUPACGoldbook.Availableonline:https://goldbook.iupac.org/terms/view/P04520(accessedon22
February2020).
91. SustainableAgricultureResearchandEducation.Availableonline:https://www.sare.org/Learning‐
Center/Bulletins/A‐Whole‐Farm‐Approach‐to‐Managing‐Pests/Text‐Version/Reducing‐Pest‐Pressure
(accessed22February2020).
92. Lexico.Availableonline:https://www.lexico.com/definition/labour_time(accessedon22February2020).
93. HealthandSafetyExecutiveUK.Availableonline:https://www.hse.gov.uk/research/rrpdf/rr362.pdf
(accessedon22February2020).
94. CambridgeDictionary.Availableonline:https://dictionary.cambridge.org/dictionary/english/labour
(accessedon22February2020).

Agronomy2020,10,74324of25
95. Safeopedia.Availableonline:https://www.safeopedia.com/definition/1237/work‐related‐injury(accessed
on22February2020).
96. Wikipedia.Availableonline:https://en.wikipedia.org/wiki/Work_accident(accessedon22February2020).
97. EuropeanCommissionCORDISOnlineDatabase.AvailableOnline:https://cordis.europa.eu/(accessedon
18March2020).
98. AgriculturalEuropeanInnovationPlatform(EIP‐Agri).AvailableOnline:
https://ec.europa.eu/eip/agriculture/en/eip‐agri‐common‐format(accessedon18March2020).
99. TechnologyReadinessLevels(TRL)Definition.Availableonline:
https://ec.europa.eu/research/participants/data/ref/h2020/wp/2014_2015/annexes/h2020‐wp1415‐annex‐g‐
trl_en.pdf(accessedon13January2020).
100. TechnologyReadinessLevel(TRL)CalculatorVersion2.2DevelopedbytheAirForceResearchLaboratory
(AFRL).AvailableOnline:
https://www.dau.edu/cop/stm/Lists/Tools/DispForm.aspx?ID=4&Source=https%3A%2F%2Fwww%2Eda
u%2Eedu%2Fcop%2Fstm%2Flists%2Ftools%2Fallitems%2Easpx&ContentTypeId=0x010051CD3A8A368D
5347A6595B3B5385510700AA867A0513EB0A44B7EC5897985C3BB8(accessedon10January2020).
101. Schwarz,J.;Herold,L.TypologyofPFTechnologies;FP7projectFutureFarm,EuropeanCommission,
Brussels,2011.
102. Rogers,E.M.DiffusionofInnovations,4thed.;TheFreePress:NewYork,NY,USA,1995;p.519.
103. Merfield,C.N.Roboticweeding’sfalsedawn?Tenrequirementsforfullyautonomousmechanicalweed
management.WeedRes.2016,56,340–344.
104. Khan,N.;Medlock,G.;Graves,S.;Anwar,S.GPSGuidedAutonomousNavigationofaSmallAgriculturalRobot
withAutomatedFertilizingSystem;SAETechnicalPaper2018‐01‐0031,2018,https://doi.org/10.4271/2018‐01‐
0031.
105. Normile,M.A.;Leetmaa,S.E.U.S.‐EUFoodandAgricultureComparisons;AgricultureandTradeReport;U.S.
DepartmentofAgriculture:Washington,DC,USA,2004.
106. Baillie,C.P.;Lobsey,C.R.;Antille,D.L.;McCarthy,C.L.;Thomasson,J.A.Areviewofthestateoftheartin
agriculturalautomation.PartIII:Agriculturalmachinerynavigationsystems.InProceedingsofthe2018
ASABEAnnualInternationalMeeting,Detroit,MI,USA,ASABE:St.Joseph,MI,USA,29July–1August
2018;p.1.
107. Diacono,M.;Rubino,P.;Montemurro,F.Precisionnitrogenmanagementofwheat.Areview.Agron.
Sustain.Dev.2013,33,219–241.
108. Chen,C.;Pan,J.;Lam,S.K.Areviewofprecisionfertilizationresearch.Environ.EarthSci.2014,71,4073–
4080.
109. Weis,M.;Gutjahr,C.;RuedaAyala,V.;Gerhards,R.;Ritter,C.;Schölderle,F.Precisionfarmingforweed
management:Techniques.GesundePflanz.2008,60,171–181.
110. Song,Y.;Sun,H.;Li,M.;Zhang,Q.TechnologyApplicationofSmartSprayinAgriculture:AReview.Intell.
Autom.SoftComput.2015,21,319–333.
111. Neupane,J.;Guo,W.AgronomicBasisandStrategiesforPrecisionWaterManagement:AReview.
Agronomy2019,9,87.
112. Pereira,C.S.;Morais,R.;Reis,M.J.C.S.Recentadvancesinimageprocessingtechniquesforautomated
harvestingpurposes:Areview.InProceedingsofthe2017IntelligentSystemsConference(IntelliSys),
London,UK,7–8September2017;pp.566–575.
113. Soto,I.;Barnes,A.;Balafoutis,A.;Beck,B.;Sanchez,B.;Vangeyte,J.;Fountas,S.;Wal,T.V.d.;Eory,V.;
Gómez‐Barbero,M.TheContributionofPrecisionAgricultureTechnologiestoFarmProductivityandthe
MitigationofGreenhouseGasEmissionsintheEU;EUScienceHub.PublicationsOfficeoftheEuropean
Union,Brussels,2019,ISBN:978‐92‐79‐92834‐5,ISSN:1831‐9424,DOI:10.2760/016263
114. Pedersen,S.M.;Lind,K.M.PrecisionAgriculture—FromMappingtoSite‐SpecificApplication.InPrecision
Agriculture:TechnologyandEconomicPerspectives;Pedersen,S.M.,Lind,K.M.,Eds.;SpringerInternational
Publishing:Cham,Switzerland,2017;pp.1–20.
115. Mouazen,A.M.;Alexandridis,T.;Buddenbaum,H.;Cohen,Y.;Moshou,D.;Mulla,D.;Nawar,S.;Sudduth,
K.A.Chapter2—Monitoring.InAgriculturalInternetofThingsandDecisionSupportforPrecisionSmart
Farming;Castrignanò,A.,Buttafuoco,G.,Khosla,R.,Mouazen,A.M.,Moshou,D.,Naud,O.,Eds.;
AcademicPress:Cambridge,MA,USA,2020;pp.35–138.

Agronomy2020,10,74325of25
116. Kay,N.M.;Leih,S.;Teece,D.J.Theroleofemergenceindynamiccapabilities:Arestatementofthe
frameworkandsomepossibilitiesforfutureresearch.Ind.Corp.Chang.2018,27,623–638.
117. Teece,D.J.Profitingfrominnovationinthedigitaleconomy:Enablingtechnologies,standards,and
licensingmodelsinthewirelessworld.Res.Policy2018,47,1367–1387.
118. Bower,J.L.;Christensen,C.M.Disruptivetechnologies:Catchingthewave.Harv.Bus.Rev.1995,73,43–53.
119. Michels,M.;vonHobe,C.‐F.;Musshoff,O.Atrans‐theoreticalmodelfortheadoptionofdronesbylarge‐
scaleGermanfarmers.J.RuralStud.2020,75,80–88.
120. Drewry,J.L.;Shutske,J.M.;Trechter,D.;Luck,B.D.;Pitman,L.Assessmentofdigitaltechnologyadoption
andaccessbarriersamongcrop,dairyandlivestockproducersinWisconsin.Comput.Electron.Agric.2019,
165,104960.
121. Griliches,Z.HybridCornandtheEconomicsofInnovation.Science1960,132,275.
122. David,P.ZviGrilichesandtheEconomicsofTechnologyDiffusion:Linkinginnovationadoption,
laggedinvestments,andproductivitygrowth.SIERP2015,15‐005.AvailableOnline:
https://siepr.stanford.edu/sites/default/files/publications/15‐005_0.pdf(accessedon20February2020).
123. Feder,G.;Slade,R.TheAcquisitionofInformationandtheAdoptionofNewTechnology.Am.J.Agric.
Econ.1984,66,312–320.
124. Genius,M.;Pantzios,C.J.;Tzouvelekas,V.InformationAcquisitionandAdoptionofOrganicFarming
Practices.J.Agric.Resour.Econ.2006,31,93–113.
125. Horizon2020WorkProgramme2018–2020,EuropeanCommissionDecisionC(2019)4575of2July2019.
Availableonline:https://ec.europa.eu/research/participants/data/ref/h2020/other/wp/2018‐
2020/annexes/h2020‐wp1820‐annex‐ga_en.pdf(accessedon10January2020).
126. Pedersen,S.M.;Fountas,S.;Blackmore,B.S.;Gylling,M.;Pedersen,J.L.Adoptionandperspectivesof
precisionfarminginDenmark.ActaAgric.Scand.Sect.BSoilPlantSci.2004,54,2–8.
127. Jensen,H.G.;Jacobsen,L.‐B.;Pedersen,S.M.;Tavella,E.Socioeconomicimpactofwidespreadadoptionof
precisionfarmingandcontrolledtrafficsystemsinDenmark.Precis.Agric2012,13,661–677.
128. Bongiovanni,R.;Lowenberg‐Deboer,J.EconomicsofVariableRateLimeinIndiana.Precis.Agric2000,2,
55–70.
129. Bongiovanni,R.;Lowenberg‐Deboer,J.PrecisionAgricultureandSustainability.Precis.Agric2004,5,359–
387.
130. Reddy,P.P.PrecisionAgriculture.InAgro‐EcologicalApproachestoPestManagementforSustainable
Agriculture;Reddy,P.P.,Ed.;Springer:Singapore,2017;pp.295–309.
131. Erisman,J.W.;vanEekeren,N.;deWit,J.;Koopmans,C.;Cuijpers,W.;Oerlemans,N.;Koks,B.J.
Agricultureandbiodiversity:Abetterbalancebenefitsboth.AimsAgric.Food2016,1,157–174.
132. Meyer‐Aurich,A.;Gandorfer,M.;Heißenhuber,A.Economicanalysisofprecisionfarming
technologiesatthefarmlevel:Twogermancasestudies.2008,67–76,.InO.W.Castelonge,Agricultural
Systems:Economics,Technology,Diversity.NovaSciencePublishers,HauppageNY,USAISBN:978‐1‐
60692‐025‐1
133. Pedersen,S.M.;Fountas,S.;Have,H.;Blackmore,B.S.Agriculturalrobots—Systemanalysisandeconomic
feasibility.Precis.Agric2006,7,295–308.
134. Batte,M.T.PrecisionFarmingandLandLeasingPractices.J.AsfmraAm.Soc.FarmManag.Rural
Appraisers2003,2003,1–9.Availableonline:http://ageconsearch.umn.edu/record/198075/files/200.pdf
(accessedon20March2020).

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