1、LEVERAGING AUTOMATION INAGRICULTURE FOR TRANSFORMINGAGRIFOOD SYSTEMSFOOD AND AGRICULTURETHE STATE OF 2022THAILAND.Aerial view of a farmer using a tablet in a green rice field.COVER PHOTOGRAPH Sorapong Chaipanya/SThis flagship publication is part of The State of the World series of the Food and Agric

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14、OMATION IN AGRICULTURE FOR TRANSFORMING AGRIFOOD SYSTEMSCONTENTSFOREWORD ivMETHODOLOGY viiACKNOWLEDGEMENTS viiiACRONYMS AND ABBREVIATIONS ixGLOSSARY xCORE MESSAGES xivEXECUTIVE SUMMARY xvCHAPTER 1AGRICULTURAL AUTOMATION:WHAT IT IS AND WHY IT IS IMPORTANT 1Key messages 1How did we get here?2What is a

15、gricultural automation?3Why do we need to leverage agricultural automation?Understanding key drivers 7Challenges posed by the progress of agricultural automation 11Turning challenges into opportunities 12What is the focus of the report?13CHAPTER 2UNDERSTANDING THE PAST AND LOOKING TOWARDS THE FUTURE

16、 OF AGRICULTURAL AUTOMATION 17Key messages 17Trends and drivers of motorized mechanization around the world 18The digital revolution and its potential to transform the use of motorized mechanization and agricultural practices 23The state of digital automation technologies and robotics in agriculture

17、 28Conclusions 36CHAPTER 3THE BUSINESS CASE FOR INVESTING IN AGRICULTURAL AUTOMATION 39Key messages 39The business case for motorized mechanization confirms its consistent potential in many contexts 40Investigating the business case for digital automation:lessons learned from case studies 46Beyond t

18、he business case:the role of investments,policies and legislation 50Future trajectories of agricultural automation:considerations for inclusive adoption and environmental sustainability 52Conclusions 59CHAPTER 4SOCIOECONOMIC IMPACTS AND OPPORTUNITIES OF AGRICULTURAL AUTOMATION 63Key messages 63An ag

19、rifood systems approach for analysing social implications 64Labour impacts of agricultural automation 67Agricultural automation brings new entrepreneurial and transformative opportunities with implications for nutrition and consumers 72An inclusive process of agricultural automation 73The future of

20、the agrifood workforce 76Conclusions 78CHAPTER 5POLICY OPTIONS TOWARDS EFFICIENT,SUSTAINABLE AND INCLUSIVE AGRICULTURAL AUTOMATION 81Key messages 81Towards responsible agricultural automation 82General policies for creating an enabling environment 84Agriculture-targeted policies,legislation and inve

21、stments 87Policies to ensure agricultural automation contributes to sustainable and resilient agrifood systems 92Policies to ensure an inclusive agricultural automation process that works for all 94Conclusions 97ANNEXES 99ANNEX 1Description of the case studies 100ANNEX 2Statistical tables 128NOTES 1

22、34|ii|TABLES 1 Number of case studies by producer size,automation level and sector152 Selected milestones in digital automation in agriculture29A2.1 Tractor use per 1 000 hectares of arable land,latest year available128 FIGURES 1 Three-phase cycle of an automation system42 Evolution of agricultural

23、automation53 Share of employment in agriculture out of total employment by income group(top)and region(bottom),1991201984 Tractors in use per 1 000 hectares of arable land205 Selected digital technologies and robotics with artificial intelligence by agricultural production system306 The readiness to

24、 scale of digital automation technologies along a spectrum487 An agrifood systems approach to automation impacts on employment658 A roadmap of policy options to leverage agricultural automation responsibly838 A comparative costbenefit analysis for mechanized vs manual and/or animal traction in wheat

25、 production:evidence from Ethiopia and Nepal419 Leveraging agricultural automation to improve food safety4310 Enhancing the resilience of small-scale producers through small-sized motorized mechanization4411 Mechanized raised beds in Egypt for improved productivity and sustainable water use4512 Savi

26、ng time,effort and money with drum seeders in the Lao Peoples Democratic Republic4613 The evolution of the business case for robotic milking systems4714 The impact of a digital orchard sprayer in the European Union:evidence from Poland and Hungary4915 COVID-19 spurred interest in digital technologie

27、s:evidence from two case studies5116 Solving labour shortages in strawberry fields using harvesting robots5417 The business case for women adopting motorized mechanization:evidence from Nepal5518 A vision for low-cost autonomous crop robots5819 Analysing agricultural automation through the lens of d

28、ecent employment6820 The labour impacts of mechanized harvesting of sugar cane in Brazil7021 Automation and rural migrant-sending communities:the case of California7122 Inclusion of persons with disabilities7423 Inclusion of women and youth:evidence from case studies7524 Women in the Driving Seat:ad

29、vancing womens empowerment through tractors7625 How different types of government support can potentially leverage agricultural automation8426 Broadband open access network in Komen,Slovenia8627 National strategies for a stronger adoption of digital tools in African agriculture8828 Adapting digital

30、automation to various contexts:evidence from 27 case studies90 BOXES 1 Overcoming data challenges in reporting use of agricultural machinery192 Understanding mechanization in sub-Saharan Africa223 Digital tools for improved access to mechanization services254 Digital tools not linked to mechanizatio

31、n disembodied solutions265 Digital automation of livestock production:examples from Latin America,Africa and Europe316 New aquaculture technologies:examples from India and Mexico337 Evolution of the forestry sector:mechanization and digital automation34|iii|FOREWORDThis report dives deep into a real

32、ity of agriculture:the sector is undergoing profound technological change at an accelerating pace.New technologies,unimaginable just a few years ago,are rapidly emerging.In livestock production,for example,technologies based on electronic tagging of animals including milking robots and poultry feedi

33、ng systems are increasingly adopted in some countries.Global navigation satellite system(GNSS)guidance allows automated crop production,involving use of autosteer for tractors,fertilizer spreaders and pesticide sprayers.Even more advanced technologies are now coming onto the market in all sectors.In

34、 crop production,autonomous machines such as weeding robots are starting to be commercialized,while uncrewed aerial vehicles(commonly called drones)gather information for both crop management and input application.In aquaculture,automated feeding and monitoring technologies are increasingly adopted.

35、In forestry,machinery for log cutting and transportation is currently a major aim of automation efforts.Many of the most recent technologies facilitate precision agriculture,a management strategy that uses information to optimize input and resource use.Recent technological developments may astound a

36、nd amaze,inspiring the desire to learn more.However,it is important to remember that technological change is not a new phenomenon and,crucially,not all agrifood systems actors have access to it.FAO has been studying this subject for decades.What we see today is no more than a consolidation point for

37、 now of a lengthy process of technological change in agriculture that has been accelerating over the last two centuries.This process has increased productivity,reduced drudgery in farm work,freed up labour for other activities,and ultimately improved livelihoods and human well-being.Machinery and eq

38、uipment have improved and sometimes taken over the three key steps involved in any agricultural operation:diagnosis,decision-making and performing.The historical evolution exhibits five technology categories:the introduction of manual tools;the use of animal traction;motorized mechanization since th

39、e 1910s;the adoption of digital equipment since the 1980s;and,more recently,the introduction of robotics.What is referred to as automation in this report really begins with motorized mechanization,which has greatly automated the performing component of agricultural operations.The more recent digital

40、 technologies and robotics allow for the gradual automation also of diagnosis and decision-making.As this report notes,this evolution is ongoing,but not all agricultural producers in all countries are at the same stage.It is true that there are widespread concerns about the possible negative socioec

41、onomic impacts of labour-saving technological change,in particular job displacement and consequent unemployment.Such fears date back to at least the early nineteenth century.However,when looking back,fears that automation which increases labour productivity will necessarily leave people without jobs

42、 on a vast scale are simply not borne out by historical realities.This is because automation in agriculture is part of the process of structural transformation of societies whereby increased agricultural labour productivity gradually releases agricultural workers,allowing them to enter into profitab

43、le activities in other sectors such as industry and services.During this transformation,the share of the population employed in agriculture naturally declines,while jobs are created in other sectors.This is generally accompanied by changes within agrifood systems,whereby upstream and downstream sect

44、ors evolve,creating new jobs and new entrepreneurial opportunities.For this reason,it is essential to recognize that agriculture is a key part of broader agrifood systems.The report highlights the potential benefits of agricultural automation that are manifold and able to contribute to the transform

45、ation of agrifood systems,making them more efficient,productive,resilient,sustainable and inclusive.Automation can increase labour productivity and profitability in agriculture.It can improve working conditions for agricultural workers.It can generate new entrepreneurship opportunities in rural area

46、s,which may be particularly attractive for rural youth.It can|iv|help reduce food losses and improve product quality and safety.It can also bring about benefits in terms of environmental sustainability and climate change adaptation.Recent solutions involving precision agriculture and the adoption of

47、 small-scale equipment often more suited to local conditions than motorized mechanization using heavy machinery can improve both environmental sustainability and resilience to climate and other shocks.Thanks to these numerous benefits,agricultural automation can also contribute to achieving several

48、of the Sustainable Development Goals(SDGs).However,the risks and problems associated with agricultural automation are also acknowledged in this report.As with any technological change,automation in agriculture implies disruption to agrifood systems.If automation is rapid and not aligned with local s

49、ocioeconomic and labour market conditions,there can indeed be displacement of labour the common outcome that must be avoided.In addition,automation may increase demand for highly skilled labourers,while reducing demand for non-skilled workers.If large prosperous agricultural producers have easier ac

50、cess to automation than smaller,poorer producers,automation risks exacerbating inequalities,and this must be avoided at all costs.If not well managed and suited to local conditions,automation,especially mechanization relying on heavy machinery,can jeopardize agricultural sustainability.These risks a

51、re real and are recognized and analysed in this report.Yet,as the report also suggests,saying no to automation is not the way forward.FAO truly believes that without technological progress and increased productivity,there is no possibility of lifting hundreds of millions of people out of poverty,hun

52、ger,food insecurity and malnutrition.Refusing automation may mean condemning agricultural labourers to a future of perennially low productivity and poor returns for their labour.What matters is how the process of automation is carried out in practice,not whether or not it happens.We must ensure that

53、 automation takes place in a way that is inclusive and promotes sustainability.Throughout this report,FAO shares the concept of responsible technological change to make agricultural automation a success.What does this entail?First,agricultural automation needs to be part of a process of agricultural

54、 transformation that runs in parallel with,facilitates,and is facilitated by broader changes in society and agrifood systems.For this,it is essential that adoption of automation responds to real incentives.Thus,labour-saving technologies can further the process of agricultural transformation if they

55、 respond to growing labour scarcity and rising rural wages.On the other hand,if incentives for adoption of automation or specific automation technologies are artificially created,for example,through government subsidies particularly in contexts where labour is abundant automation take-up can be high

56、ly disruptive with negative labour market and socioeconomic impacts.However,it is also important that government policies do not inhibit automation,as this could lead to condemning agricultural producers and workers to a future of perennially low productivity and competitiveness.This report argues t

57、hat the appropriate role of government is to create an enabling environment to facilitate adoption of suitable automation solutions,rather than directly incentivize specific solutions in contexts where they may not be appropriate,or inhibit adoption of automation in any way.For coherence with the SD

58、Gs,automation needs to be inclusive.It must offer opportunities for all,from small-scale producers to large commercial farms,as well as marginalized groups such as women,youth and persons with disabilities.Barriers to adoption need to be overcome,not least for women.Making suitable technical solutio

59、ns available for all categories of producers involves making technologies scale-neutral,that is,making them suitable for producers of all scales,or accessible to all through institutional mechanisms such as shared services.Building digital skills through education and training is also essential for

60、facilitating adoption and avoiding digital divides based on unequal knowledge and skills.|v|FOREWORDTo enhance sustainability and be truly inclusive and transformative,automation solutions need to be adapted to the local context,in terms not only of the characteristics of the producers,but also of l

61、ocal biophysical,topographic,climatic and socioeconomic conditions.This report is realistic and offers no one-size-fits-all solutions.The most advanced technological solution is not necessarily the most appropriate everywhere and for everybody.As the evidence presented shows,in some situations,simpl

62、e technologies such as small machinery and even hand-held equipment can lead to substantial benefits for small-scale producers and enable production on hilly terrain.There are even situations where producers may be able to leapfrog directly to more advanced technological solutions.What is essential

63、is that agricultural producers themselves choose the technologies most suited to their needs,while governments create the enabling environment that allows them to do so.Finally,this report also argues that agricultural automation must contribute to more sustainable and resilient agriculture.In the p

64、ast,the use of large-scale heavy machinery has often had a negative impact on environmental sustainability.Addressing this requires tailoring mechanization to smaller and lighter machinery.At the same time,digital agriculture and robotics that facilitate precision agriculture offer solutions that ar

65、e more resource-efficient and more environmentally sustainable.Applied technical and agronomic research can help find solutions that can lead to further progress towards environmental sustainability.This report looks in detail at these issues,presenting an objective and in-depth examination of agric

66、ultural automation,demystifying the ill-founded myths surrounding it,and suggesting ways forward to adopt agricultural automation in different country and local settings.It identifies key areas for policy interventions and investments to ensure that agricultural automation contributes to inclusive a

67、nd sustainable development.FAO firmly and strategically believes in technology,innovation and data,supported by adequate governance,human capital,and institutions,as key cross-cutting and cross-sectional accelerators in all its programmatic interventions to accelerate impact while minimizing trade-o

68、ffs.No doubt,these accelerators will be catalytic for agricultural transformation in all contexts.It is my hope that this FAO report can contribute in a constructive way to the policy debate in this area of major importance for achieving the SDGs.Qu DongyuFAO Director-General|vi|METHODOLOGYThe prepa

69、ration of The State of Food and Agriculture 2022 began with the formation of an advisory group representing all relevant FAO technical units,which,together with a panel of external experts,assisted the research and writing team.The preparation of the report was further informed by six background pap

70、ers and original empirical analysis prepared by FAO and external experts.The advisory group met virtually to discuss the outline of the report on 24 January 2022 and commented on the first drafts of Chapter 1 and Chapter 2 in March 2022.Drafts of all chapters were presented to the advisory group and

71、 panel of external experts in advance of a workshop held virtually on 31 March 6 April 2022 and chaired by the Deputy Director of FAOs Agrifood Economics Division.With guidance from the workshop and a follow-on advisory group meeting,the report was revised and presented to the management team of FAO

72、s Economic and Social Development stream.The revised draft was sent for comments to other FAO streams and to the FAO regional offices for Africa,Asia and the Pacific,Europe and Central Asia,Latin America and the Caribbean,and the Near East and North Africa.Comments were incorporated in the final dra

73、ft,which was reviewed by the Deputy Director of the Agrifood Economics Division,the FAO Chief Economist and the Office of the Director-General.|vii|ACKNOWLEDGEMENTSThe State of Food and Agriculture 2022 was prepared by a multidisciplinary team from the Food and Agriculture Organization of the United

74、 Nations(FAO),under the direction of Marco V.Snchez Cantillo,Deputy Director of the Agrifood Economics Division,and Andrea Cattaneo,Senior Economist and Editor of the publication.Overall guidance was provided by Mximo Torero Cullen,Chief Economist,and the management team of the Economic and Social D

75、evelopment stream.RESEARCH AND WRITING TEAM Theresa McMenomy,Fergus Mulligan(consulting editor),Ahmad Sadiddin,Jakob Skt and Sara Vaz.BACKGROUND PAPERS Christina Cappello(Wageningen University&Research WUR),Tomaso Ceccarelli(WUR),Aneesh Chauhan(WUR),Diane Charlton(Montana State University),Thoman Da

76、um(University of Hohenheim),Alexandra Hill(Colorado State University),Sander Janssen(WUR),Inder Kumar(WUR),James Lowenberg-DeBoer(Harper Adams University),Mariette McCampbell(WUR),Giacomo Rambaldi(WUR),David Rose(University of Reading)and Edward Taylor(University of California).ADDITIONAL EXTERNAL C

77、ONTRIBUTIONSRabe Yahaya(International Maize and Wheat Improvement Center CIMMYT).ADDITIONAL FAO INPUTS Veronica Boero,Alban Lika,Madhusudan Singh Basnyat,Atef Swelam and Michele Vollaro.FAO ADVISORY GROUPMaysoon Alzoubi,Huda Alsahi,Marwan Benali,Henry Burgsteden,Aziz Elbehri,Mayling Flores Rojas,Ken

78、 Lohento,Magnus Grylle,Karim Houmy,Dejan Jakov Ijevic,Josef Kienzle,Lan Li,Preetmoninder Lidder,Joseph Mpagalile,Ahmad Mukhtar,Eva Galvez Nogales,Santiago Santos Valle,Beate Scherf,Josef Schmidhuber and Xinhua Yuan.PANEL OF EXTERNAL EXPERTS Imran Ali(CQ University),Christina Cappello(WUR),Tomaso Cec

79、carelli(WUR),Aneesh Chauhan(WUR),Diane Charlton(Montana State University),Thomas Daum(University of Hohenheim),Kit Franklin(Harper Adams University),Alexandra Hill(Colorado State University),Ivo Hostens(European Agricultural Machinery Industry Association),Sander Janssen(WUR),Inder Kumar(WUR),James

80、Lowenberg-DeBoer(Harper Adams University),Mariette McCampbell(WUR),Giacomo Rambaldi(WUR),David Rose(University of Reading),Salah Sukkarieh(University of Sydney)and Edward Taylor(University of California).ANNEXES Ahmad Sadiddin and Sara Vaz prepared the annexes with assistance from the WUR team:Chris

81、tina Cappello,Tomaso Ceccarelli,Aneesh Chauhan,Sander Janssen,Inder Kumar,Mariette McCampbell and Giacomo Rambaldi.ADMINISTRATIVE SUPPORT Liliana Maldonado provided administrative support.Translations were delivered by the Language Branch(CSGL)of the FAO Governing Bodies Servicing Division(CSG).The

82、Publications Branch(OCCP)in FAOs Office of Communications(OCC)provided editorial support,design and layout,as well as production coordination,for editions in all six official languages.|viii|ACRONYMS AND ABBREVIATIONSAIartificial intelligenceAMSautomatic milking systemAPNIAfrican Plant Nutrition Ins

83、tituteAUCAfrican Union CommissionCAASChinese Academy of Agricultural SciencesCEAcontrolled environment agricultureCIMMYTInternational Maize and Wheat Improvement CenterCOVID-19coronavirus disease 2019CSAMCentre for Sustainable Agricultural MechanizationCTATechnical Center for Agricultural and Rural

84、CooperationDPGADigital Public Goods AllianceEDRIEthiopian Development Research InstituteEIDelectronic identificationESCAPEconomic and Social Commission for Asia and the PacificFAOFood and Agriculture Organization of the United NationsGHGgreenhouse gasGISgeographic information systemGIZGerman Agency

85、for International CooperationGNSSglobal navigation satellite systemGPSglobal positioning systemGSMAGlobal System for Mobile CommunicationsGSSgeneral services supporthahectareICARDAInternational Center for Agricultural Research in the Dry AreasICRISATInternational Crops Research Institute for the Sem

86、i-Arid TropicsIFADInternational Fund for Agricultural DevelopmentIFCInternational Finance CorporationIFPRIInternational Food Policy Research InstituteILOInternational Labour OrganizationIoTinternet of thingsISPAInternational Society of Precision AgricultureITinformation technologyITUInternational Te

87、lecommunication UnionIVRinteractive voice responseLSMSLiving Standards Measurement StudyLSMS-ISALiving Standards Measurement Study-Integrated Surveys on AgricultureR&Dresearch and developmentRuLISRural Livelihoods Information SystemSDGsSustainable Development GoalsSMSshort message serviceUASuncrewed

88、 aerial system(historically referred to as unmanned aerial system)UAVuncrewed aerial vehicle(historically referred to as unmanned aerial vehicle)UNICEFUnited Nations Childrens FundUSDAUnited States Department of AgricultureUSSDunstructured supplementary service dataVRTvariable rate technologyWFPWorl

89、d Food ProgrammeWHOWorld Health Organization|ix|GLOSSARYAgricultural automation.The use of machinery and equipment in agricultural operations to improve their diagnosis,decision-making or performing,reducing the drudgery of agricultural work and/or improving the timeliness,and potentially the precis

90、ion,of agricultural operations.Agricultural automation includes technologies for precision agriculture.Examples of machinery and equipment used in agricultural automation include:tractors that pull,push or put into action a range of implements,equipment and tools that perform farm operations(i.e.aut

91、omating the performing function);sensors,machines,drones and satellites,as well as devices such as smartphones,tablets or software tools(e.g.advisory apps and online farm management)and platforms,to monitor animals,soil,water and plants to support humans making decisions on agricultural tasks1(i.e.a

92、utomating the diagnosis function);more advanced options,such as weeding robots which spray herbicides with precision only where needed and with exactly what is needed,or drones to monitor conditions remotely and apply fertilizers,pesticides and other treatments from above2,3(i.e.automating the three

93、 functions:diagnosis,decision-making and performing).Automated equipment.Systems where some(partly automated)or all(fully automated)functions,a defined activity or behaviour of a machine or a machine system,have been automated to work without human intervention.4Agricultural mechanization.The use of

94、 all levels of technologies,from simple,basic hand tools to more sophisticated,motorized equipment and machinery,to perform agricultural operations.6 Power sources in agricultural mechanization are of three types:hand tool technology(tools and implements that use human muscles as the main power sour

95、ce);draught animal technology(machines,implements and equipment powered by animals);and motorized technology(mechanization powered by engines or motors).7Agricultural motorized mechanization.The application of all types of mechanical motors or engines,regardless of energy source,to activities associ

96、ated with agriculture.7 Agricultural producers.Households running agricultural businesses engaged in crop production,livestock production,fisheries,aquaculture,pastoralism or forestry.Small-scale(agricultural)producers are those running any of the agricultural businesses defined above but operating

97、under greater constraints due to limited access to markets and resources such as land and water,information,technology,capital,assets and institutions.8Artificial intelligence(AI).Computer systems that use algorithms to analyse their environment and take actions with some degree of autonomy to achie

98、ve specific goals.AI can be purely software-based,acting in the virtual world (e.g.voice assistants,image analysis software,search engines,speech and face recognition systems),or it can be embedded in hardware devices(e.g.advanced robots,autonomous cars,drones or IoT applications).5Machine learning.

99、A type of AI and a method of data analysis that uses computer algorithms to automate analytical model building.It is based on identifying patterns in data to improve machine performance by more accurately predicting outcomes without explicit human instructions.Big data.Large,diverse,complex data set

100、s generated from instruments,sensors,financial transactions,social media,and other digital means,typically beyond the storage capacity and processing power of personal computers and basic analytical software.Business-to-business model.Relations and sales between companies,rather than between a compa

101、ny and individual clients.9|x|Business-to-client model.Direct relations and sales of products and services between a company and customers who are the end users of its products or services.9Conservation agriculture(also referred to as conservation tillage).A farming system that promotes minimum soil

102、 disturbance(i.e.little or no tillage),maintenance of permanent soil cover and diversification of plant species.It enhances biodiversity and natural biological processes above and below the ground surface,contributing to increased water-and nutrient-use efficiency and improved and sustained crop pro

103、duction.10Digital automation in agriculture.The strengthening of automated processes in agricultural machinery and equipment(e.g.tractors and their implements,feeding systems,milking machines)by adding digital tools that increase their efficiency and precision as a result of access to data and digit

104、al services through intelligent interoperable networks,platforms and farm management systems.Disembodied vs embodied digital solutions.Disembodied digital solutions are primarily software-based solutions that do not rely on the use of agricultural machinery but instead require limited hardware resou

105、rces,generally in the form of a smartphone or a tablet,or software tools such as advisory apps,farm management software,and online platforms.They may include remote sensing and/or UAS but limited to data for decision support and scouting.When digital tools are installed on agricultural machinery and

106、 equipment,they are called embodied and they enable the machinery to interact with the environment through direct action(performing),rather than just observations and decision support.9Electronic identification(EID).The use of a microchip or electronic transponder embedded in a tag,bolus or implant

107、to identify an individual farm animal.5Farm.Any management-integrated agricultural production unit that produces crops,livestock,agroforestry or aquaculture products.Fee-for-service.In the context of farm machines,a business arrangement whereby the farmer pays a provider for machine services on a pe

108、r unit basis(e.g.per ha,hour,animal or tonne harvested),rather than owning the machine.5Global navigation satellite system(GNSS).Any system that uses satellite signals to provide location information.Examples include the global positioning system(GPS)of the United States of America,the European Gali

109、leo system,GLONASS of the Russian Federation,and the Chinese BeiDou system.5Autosteer.A GNSS-enabled technology that provides automated steering and positioning in the landscape for self-propelled agricultural machines(e.g.tractors,combine harvesters,forage harvesters,sprayers).With the most advance

110、d autosteer,the computer does almost all the steering in the field,including turning at the end of a row.Autosteer technology typically requires a human operator present on the seat of the machine to take over in case there is a malfunction or other problem.It is a good example of a precision farmin

111、g technology.5Global positioning system(GPS).The United States of Americas GNSS.Because it was the first GNSS available for civilian use,GPS is sometimes used as a generic term for GNSS.5Internet of things(IoT).A system in which devices including mobile phones,sensors,drones,machines and satellites

112、are connected to the internet.9Interoperability.The ability of machines and equipment to create,exchange and consume data due to clear and shared expectations regarding the contents,contexts and meaning of those data.9On the go.In the context of farm machines,a situation in which machine operation i

113、s adjusted while moving through a field based on an algorithm using sensor data without direct human intervention.5|xi|GLOSSARYOperator assistance system.A system that helps human operators of farm machines.Typically,it uses sensor data from several sources on the machine to assist the operator in m

114、aking decisions;it can automatically adjust machine settings to optimize the operators priorities(e.g.fuel efficiency,speed of work accomplished,product quality)and was first introduced on combine harvesters.5Precision agriculture.A management strategy that gathers,processes and analyses temporal,sp

115、atial and individual data and combines them with other information,to manage variations in the field accurately and to support management decisions and precise machine action for improved resource-use efficiency,productivity,quality,profitability and sustainability of agricultural production.11Preci

116、sion livestock farming.A data-based livestock management strategy that monitors and controls individual animal or group productivity,environment,health and welfare in a continuous,real-time and automated manner.It focuses on improving resource-use efficiency,productivity,quality,profitability and su

117、stainability of livestock production.5Protected agriculture.The production of high-value vegetables and other horticultural crops in greenhouses and vertical farms.It allows farmers to grow cash crops on small plots in marginal,water-deficient areas where traditional cropping may not be viable.It is

118、 also called protected cultivation or protected crop production.9Remote sensing.The process of gathering information about objects on earth from a distance,using aircraft,satellites or other platforms carrying sensors.9Robot.A machine capable of autonomous operation without direct human intervention

119、.12 It can be stationary(e.g.a milking robot)or mobile(e.g.autodriving).The word tends to be used mainly in the media and by the general public,and robots are often anthropomorphized.More technical discussions prefer to use terms like autonomous machine or autonomous equipment.13Leg robot.A mobile a

120、utonomous machine with articulated limbs instead of wheels for movement.5Milking robot.Any milking machine that automates the milking of dairy animals,especially dairy cattle,without human labour.They are also called automatic milking systems(AMS).Swarm robots.Multiple,relatively small mobile autono

121、mous machines that accomplish work done by one large machine in conventional mechanization.Robotics.An interdisciplinary branch of computer science and engineering,which involves design,construction,operation and use of robots.It integrates many fields,including mechanical engineering,electrical eng

122、ineering,information engineering,mechatronics,electronics,bioengineering,computer engineering,control engineering,software engineering,and mathematics.Uncrewed aerial system(UAS).A large system including aircraft(drones)with mounted sensor(s),a ground control station operated by the pilot and the so

123、ftware used to analyse the data gathered by the sensor(s).9Uncrewed aerial vehicle(UAV)or Drone.A flying autonomous machine.It can be guided by remote control or using a device that is software-controlled.In agriculture,it is often used to collect aerial images or to apply fertilizer,seed,pesticides

124、 or other crop inputs.5,9Unstructured supplementary service data(USSD).A message service that is more interactive than SMS.Characterized by the use of codes that start with*and end with#(e.g.*845#).A USSD message has a maximum of 182characters and is used to access information on agriculture,health,

125、news,weather etc.14Variable rate technology(VRT).A technology based on a combination of equipment and software to vary the application of fertilizer,pesticides,seed and other crop inputs within fields to optimize|xii|yield based on the needs of crops so that the highest possible yields are obtained

126、with the least possible inputs.5Map-based VRT.A VRT based on a map that documents spatial information on site-specific conditions within the field.A human analyst prepares this spatial information map beforehand in a separate activity to be used in guiding the VRT.Planter row shut-offs.A GNSS-enable

127、d VRT approach that controls individual row seeder units,based on a prescription map or sensor data.Often used to avoid seeding in non-crop areas or double seeding in end rows.Sensor-based VRT.A VRT that is based on sensor reading collected on the go in the field,so the information guiding the VRT i

128、s automatically collected(different from a map-based VRT).Typically,the sensor is in the front of the applicator,a computer using an algorithm to vary rates is on the machine,and the application equipment is in the back of the machine.Sprayer boom section controllers.A GNSS-enabled VRT approach that

129、 controls parts of a farm sprayer boom based on a prescription map or sensor data.Section width may vary from several metres to a single nozzle.Current technology allows nozzles to be turned on,off and pulsated at various rates.Vertical farming.Indoor farming with a completely controlled environment

130、,used for growing crops vertically year-round.9Virtual fencing.A technology based on equipping animals with GNSS transponders to determine their location that uses audio alerts,electric shocks or other prompts to keep animals within geolocated boundaries.It potentially eliminates the need for physic

131、al fencing,and the GNSS helps growers locate animals grazing in large open pastures.5|xiii|1Agricultural automation can play an important role towards achieving the Sustainable Development Goals(SDGs),not least SDG 1(No Poverty)and SDG2(Zero Hunger)and those relating to environmental sustainability

132、and climate change,by building resilience,raising productivity and resource-use efficiency,and improving food quality and safety.2Agricultural automation can deepen inequalities if it remains inaccessible to small-scale producers and other marginalized groups such as youth and women;certain technolo

133、gies large motorized machinery can also have negative environmental impacts as they contribute to,for example,monoculture and soil erosion.3Before the digital revolution,motorized mechanization(e.g.tractors)was key to agricultural transformation worldwide;however,there have been wide disparities in

134、adoption between and within countries,with adoption being particularly limited in most of sub-Saharan Africa.4If tailored to local needs and supported by digital tools,motorized mechanization still has the potential to improve agricultural productivity,leading to poverty reduction and enhanced food

135、security,with positive spillover effects on the wider economy.5The use of digital automation technologies is growing,but mostly in high-income countries.Often their business case is not yet mature:some technologies are still in the prototype stages,while for others a limited enabling rural infrastru

136、cture such as connectivity and electricity hinders their dissemination,especially in low-and middle-income countries.6Investing in enabling infrastructure and improving access to rural services(e.g.finance,insurance,education)is key to ensure access to these technologies,especially for marginalized

137、groups such as small-scale agricultural producers and women.7Digital automation technologies have great potential to achieve higher efficiency,productivity,sustainability and resilience.Yet,inclusive investments are needed involving producers,manufacturers and service providers,with special attentio

138、n to women and youth in order to further develop technologies and tailor them to the needs of end users.8The impacts of agricultural automation on employment vary depending on the context.In situations of rising wages and labour scarcity,automation can benefit both employers and workers in agricultu

139、re and in the wider agrifood systems,creating opportunities for skilled young workers.9Where rural labour is abundant and wages are low,agricultural automation can lead to unemployment.This can happen if subsidies make automation artificially cheap or sudden technological breakthroughs bring automat

140、ion costs down very rapidly.10In labour-abundant contexts,policymakers should avoid subsidizing automation,but rather focus on creating an enabling environment for its adoption especially by small-scale agricultural producers,women and youth while providing social protection to least skilled workers

141、,who are more likely to lose their jobs during the transition.11Creating an enabling environment calls for multiple,coherent actions,including legislation and regulation,infrastructure,institutional arrangements,education and training,research and development,and support to private innovation proces

142、ses.12Investments and other policy actions to promote responsible agricultural automation should be based on context-specific conditions,such as status of connectivity,challenges related to knowledge and skills,adequacy of infrastructure,and inequality in access.CORE MESSAGES|xiv|EXECUTIVE SUMMARYTh

143、roughout the ages,technological change in agrifood systems and elsewhere has brought gains in productivity,incomes and human well-being.Today,technological solutions are indispensable to feed a continuously growing population in the face of limited agricultural land,unsustainable natural resource us

144、e,and increasing shocks and stresses,including climate change.These solutions are needed to make agriculture more productive and sustainable across all its sectors crop and livestock production,aquaculture,fisheries and forestry and boost productivity levels within agrifood systems.Technological cha

145、nge has reduced the need for manual labour in agriculture.This process of increased agricultural productivity and reallocation of labour away from farming is often referred to as agricultural transformation.It is accompanied by investments in agrifood systems and other physical and market infrastruc

146、tures.Agricultural automation can be a driver of transformation and create new opportunities.In this respect,motorized mechanization has allowed to automate the performing of agricultural operations,while more recently,digital technologies have been creating new opportunities to automate decisions t

147、hat precede the performing of physical operations.Common fears that automation leads to growing unemployment,although understandable,are questionable and generally not supported by historical realities.Overall,automation alleviates labour shortages and can make agricultural production more resilient

148、 and productive,improve product quality,increase resource-use efficiency,promote decent employment,and enhance environmental sustainability.Negative socioeconomic impacts of agricultural automation such as increased unemployment usually occur when automation is not suited to specific local needs.Ris

149、ks of negative impacts can be countered by facilitating the transition of farm labourers to other job opportunities,by addressing the barriers that prevent poor,small-scale producers from participating in the benefits,and avoiding policies that subsidize automation in contexts of labour abundance an

150、d low rural wages.AGRICULTURAL AUTOMATION:OPPORTUNITIES ABOUND BUT NOT WITHOUT CHALLENGESAny agriculture-related operation consists of three phases:diagnosis,decision-making and performing.Motorized mechanization automates the performing of agricultural operations such as ploughing,seeding,fertilizi

151、ng,milking,feeding and irrigating.With digital automation technologies,it becomes possible to automate also diagnosis and decision-making.These technologies increase the precision of agricultural operations and allow more efficient use of resources and inputs,with potential gains in environmental su

152、stainability and improved resilience to shocks and stresses.The technological evolution in agriculture can be summarized as a progressive move from manual tools to animal traction,to motorized mechanization,to digital equipment and finally,to robotics with artificial intelligence(AI).Against this ba

153、ckground,the report defines agricultural automation as:the use of machinery and equipment in agricultural operations to improve their diagnosis,decision-making or performing,reducing the drudgery of agricultural work and/or improving the timeliness,and potentially the precision,of agricultural opera

154、tions.Agricultural automation presents many opportunities:it can raise productivity and allow for more careful crop,livestock,aquaculture and forestry management;it can provide better working conditions and improved incomes,and reduce the workload of farming;and it can generate new rural entrepreneu

155、rial opportunities.Technologies beyond the farm can further reduce food loss and waste,enhance food safety,and enable value addition.In many countries,declining rural labour availability reflected in rising agricultural wages is a main driver of agricultural automation.Rising consumer concerns about

156、 food quality,safety,taste and freshness,together with environmental concerns,are also driving investment in digital technologies.The same|xv|EXECUTIVE SUMMARYapplies to challenges in livestock management and animal welfare that derive from growing herd sizes in livestock production.On the other han

157、d,agricultural automation can carry the risk of exacerbating social inequalities,as larger and more educated producers have greater capacities(e.g.finance,rural infrastructure,skills)to invest in new technologies or to retrain and learn new skills.Women and youth may face particularly significant ob

158、stacles,for example,obtaining quality education and training,as well as having access to land,credit and markets.Furthermore,automation is expected to reduce jobs that involve routine tasks,such as planting and harvesting,but increase skilled jobs requiring,for example,secondary education.In countri

159、es with a large rural workforce,this shift in employment can risk deepening inequalities.Overcoming these challenges requires reducing barriers to adoption faced in particular by small-scale producers,women and youth to ensure that automated solutions become scale-neutral,that is,accessible to all s

160、cales of agricultural producers from small to large.This can be achieved through technological innovations that tailor automation to the conditions of small-scale producers.In addition,innovative institutional arrangements,such as shared assets or machinery hire services,can contribute to scale neut

161、rality by connecting equipment owners to small-scale producers who pay a fee for an automation service instead of bearing the cost of buying the machinery.Reliance of agricultural automation on heavy machinery may also jeopardize environmental sustainability and contribute to deforestation,farmland

162、monoculture,biodiversity loss,land degradation and soil erosion.However,some new advances in automation,especially in small equipment relying on AI,can actually reverse some of these negative impacts.UNDERSTANDING THE PAST AND LOOKING TOWARDS THE FUTURE OF AGRICULTURAL AUTOMATIONMotorized mechanizat

163、ion has increased significantly across the world,although reliable global data with broad country coverage exist only for tractors and only up to 2009.The use of tractors as farm power was one of the most influential innovations of the twentieth century;it started in the United States of America bet

164、ween 1910 and 1960 and spread to Japan and Europe after 1955.Later,many Asian and Latin American countries saw considerable progress in terms of adoption of motorized machinery,in addition to the emergence of agricultural machinery manufacturing sectors in some countries.With the rise of rental mach

165、inery markets,adoption has become more widespread,allowing access for small-scale producers.However,adoption of tractors has stalled in sub-Saharan Africa in past decades,and light hand-held tools remain the main type of equipment used.Efforts during the 1960s and 1970s to promote mechanization,by p

166、roviding subsidized machinery to farmers and setting up state farms and public hire companies,proved costly and mostly failed due to governance challenges.This is changing with the re-emergence of agriculture on Africas development agenda,which has led to a renewed interest in automation.Since the 1

167、970s,digital technologies have found their way to agriculture through various applications.Initially they were mostly simple precision livestock technologies that facilitated management of individual animals based on electronic identification(EID)also known as electronic tagging which then paved the

168、 way for milking robots in the 1990s.At the same time,digital tools embodied in mechanization,such as machinery with global navigation satellite systems(GNSS),started to appear and enabled autosteer for tractors,fertilizer spreaders and pesticide sprayers.More recently,disembodied devices such as sm

169、artphones are being adopted to inform producers through sensors,high-resolution cameras and various apps embedded in them.These technologies can reduce costs and raise productivity;however,adoption seems to be driven also by non-monetary considerations such as increased flexibility in work schedules

170、 and better life quality,as in the case of milking robots.More advanced still are internet of things(IoT)solutions,used,for example,to monitor|xvi|and sometimes at least in part automate decisions about the care of crops,livestock or fish.Digital services also include shared asset services,which con

171、nect owners of equipment(e.g.tractors or drones),and sometimes also operators,with farmers in need of such equipment.Digital technologies hold potential also for non-mechanized precision agriculture.Methodologies for manual,site-specific fertilizer application were developed a long time ago variable

172、 rate technology(VRT)fertilizer for rice is one example,while a hand-held soil scanner is available in several low-income countries in Africa and Asia.Uncrewed aerial vehicle(UAV)services,commonly known as drones,are also being used by non-mechanized farmers in Asia and Africa;GNSS measures field ar

173、eas(Asia)and maps field boundaries to establish land tenure(Africa).THE CURRENT STATE OF DIGITAL AUTOMATION TECHNOLOGIES AND ROBOTICS IN AGRICULTUREDigital automation and robotics applications in agriculture are extremely diverse.Smartphones,with a range of sensors and high-resolution cameras built

174、into them,are the most accessible hardware for producers(especially small-scale producers)in low-and middle-income countries.However,low digital literacy in rural areas,lack of available technologies suited to small-scale producers,and the relatively high cost of these technologies remain the bigges

175、t barriers to adoption.More recently,advanced technologies such as autonomous crop robots(e.g.for harvesting,seeding and weeding)have started to be commercialized.Drones are used to gather information and to automate input application,but their use is often strictly regulated.In the aquaculture sect

176、or,automation is on the rise in response to labour scarcity and high wages.In forests,much of the wood harvesting work is already highly mechanized,and mobile robots,combined with new virtual reality and remote sensing techniques,are paving the way for advanced automatic machines.In addition,remote

177、sensing is being used to monitor deforestation.There is also potential for digitalization and automation in controlled environment agriculture(CEA),which includes indoor agriculture and vertical farming.Greenhouses are the most common form of CEA and by their very nature are amenable to environmenta

178、l monitoring,control and optimization.Many technological solutions are already available for adoption in high-,middle-and low-income countries.The direction they take and their rate of adoption are greatly influenced by policy choices.Governments need to facilitate access to these technologies by al

179、l in particular,small-scale producers,women,youth and other vulnerable and marginalized groups and ensure that they are tailored to the specific context and needs of producers.Ideally,governments should create a level playing field for innovative technologies to enable the private sector to meet dem

180、and for automation.ONE STEP AT A TIME:SIMPLE MOTORIZED MECHANIZATION STILL HAS A ROLE TO PLAYWhile digital technologies and robotics promise great things,motorized mechanization can still bring many benefits in terms of enhanced incomes,reduced costs,labour savings and less drudgery.It can free up h

181、ousehold labour and enable agricultural households to allocate time away from agriculture to pursue off-farm work.There can also be spillover effects on the wider economy.These may occur through increased demand for non-farm goods and services from agricultural households as their labour productivit

182、y improves,as well as the expansion of the non-farm economy as labour moves out of agriculture and into sectors with higher labour productivity.Automation can also improve food safety,thanks to preservation and storage technologies,and make agricultural production more resilient,in particular to cli

183、mate shocks,by allowing farmers to complete farming activities more rapidly and be more flexible in adapting activities to changing weather.|xvii|EXECUTIVE SUMMARYConsequently,there is still scope for increased use of motorized mechanization in some contexts.In low-and middle-income countries,small-

184、scale producers may benefit more from small machines,such as two-wheel tractors,which represent a less costly option and are more environmentally sustainable than traditional heavy machinery.Recent innovations to tailor motorized machinery to local needs can help countries improve resource-use effic

185、iency and save scarce resources(e.g.water)through innovative synergies between mechanization and other field practices.Agricultural mechanization is therefore high on the policy agenda of many low-and middle-income countries.This is especially the case in sub-Saharan Africa,where agricultural mechan

186、ization was neglected for some time,following the earlier failures of state-led mechanization programmes.Manual technologies and animal traction can also still play a major role in many contexts.Animal traction can be an important source of power for very small,fragmented farm holdings,and advanced

187、manual tools can reduce the need for human power.While less powerful than tractors,both draught animals and advanced manual tools can still help remedy labour shortages and enable higher crop yields and land expansion in many areas.In many cases,they are probably the most viable option to increase p

188、ower supply.THINKING AHEAD:THE BUSINESS CASE FOR INVESTING IN DIGITAL AUTOMATIONThe business case for investing in agricultural technology rests on the potential private gains.The relevant actors including producers,dealers and service providers are assumed to make rational decisions that maximize t

189、heir profits and well-being.Investing in automation technologies entails costs,which tend to increase if technologies are not widely available locally.Suppliers and producers will only make the necessary commitment if the benefits outweigh the costs.For some technologies and in certain conditions,th

190、e investment costs may exceed the private benefits;on the other hand,there may be significant benefits for the wider society.In this case,public intervention is needed to align private benefits with the interests of society as a whole.Given the scarcity of data,27 case studies,based on interviews wi

191、th digital automation service providers,were used to shed light on the business case for digital automation in agriculture.The case studies cover all world regions and agricultural production systems(crops,livestock,aquaculture and agroforestry).They represent digital automation solutions at differe

192、nt stages of readiness,with many still in the early stages of development and commercialization.The results reveal only 10 out of the 27 service providers to be profitable and financially sustainable.These ten providers mostly based in high-income countries use solutions that are in the mature phase

193、(i.e.widely adopted)and mostly serve large-scale producers.More than one-third of the case studies suggest that farmers are benefiting from these solutions through gains in productivity,efficiency and new market opportunities.Overall,the results indicate that the business case for digital automation

194、 technologies is not yet mature,partly because many of these technologies are still in the prototype phase,but also because there are serious barriers to adoption,especially in low-and middle-income countries.Although the development of many technologies is still in the preliminary stage,several imp

195、ortant lessons may be drawn from the case studies.Key factors for adoption are first,awareness of a solutions ability to perform agricultural operations successfully and second,the ability of farmers to handle the solution.Frequent obstacles to adoption of these technologies are lack of digital lite

196、racy,and limited connectivity and availability of other enabling infrastructures,including electricity.These are often compounded by a reluctance to change,generally associated with ageing farming populations.Generational change is indicated as a driver of adoption,with young farmers seen as instrum

197、ental in a transformation towards digitalization and advanced automation.Another driver of or barrier to adoption is market conditions where strong competition among producers drives them to take more risks and|xviii|adopt new technologies that promise higher productivity and efficiency.Limiting fac

198、tors can be government regulation of technology imports,absence of policies on data sharing,and insufficient public policies and incentives.On the other hand,if well designed,regulations or public support can be a strong driver of adoption.BEYOND THE BUSINESS CASE:AGRICULTURAL AUTOMATION PROMISES EN

199、VIRONMENTAL BENEFITS,BUT MORE RESEARCH IS NEEDEDIn high-income countries,but also in many commercial farms in low-and middle-income countries,agriculture is already highly mechanized,mainly through the use of large machinery.However,this type of mechanization has triggered soil erosion,deforestation

200、 and biodiversity loss all contributing to reduced resilience.Innovations in automation technologies and applied agronomic research can help to explore solutions to address these challenges.For example,motorized mechanization can be tailored to smaller and lighter machinery.Solutions with potential

201、for small-scale producers include small four-wheel and two-wheel tractors.They can minimize biodiversity loss since they do not require substantial field clearing and reshaping.Other small motorized machines,such as power weeders and mobile threshers,may also have benefits in terms of gender equalit

202、y,because women can operate them easily.Digital automation technologies that support precision agriculture also present an opportunity for great environmental benefits.They have potential to facilitate the adoption of sustainability practices such as conservation agriculture.There are success storie

203、s on the use of computers and IoT to automate greenhouses,leading to savings in water and other inputs.Small swarm robots can lead to environmental benefits by reducing the use of pesticides and herbicides,optimizing the use of other inputs and reducing soil compaction.They are already economically

204、feasible in certain circumstances but more research is needed,especially on their potential for small-scale agriculture,where they should have a comparative advantage over large machinery on farms with irregularly shaped fields.These environmental benefits are currently location-specific;what is mor

205、e,many solutions are still in the early stages of development and commercialization.Therefore,more research,including testing,is needed.If both policymakers and producers are fully aware of the benefits of these technologies,investment in their development should expand.Transitioning to renewable en

206、ergy is also important and can offer fresh opportunities to power automation,especially in remote rural areas,but once again research is needed to explore which off-grid renewable energy solutions can most efficiently power each type of machinery.AGRICULTURAL AUTOMATION HAS COMPLEX IMPACTS ON LABOUR

207、ERS AND CAN ALSO BENEFIT CONSUMERSMeasuring the overall employment impacts of agricultural automation is very difficult because it requires large amounts of data tracking all the transformations and the associated reallocation of workers,not only in farm activities,but also upstream and downstream.A

208、s agricultural transformation unfolds,people exit agriculture to seek higher-paying jobs,and the share of people employed in agriculture continues to decline.The process reshapes labour supply and demand within entire agrifood systems.When all nodes in agrifood systems are changing simultaneously,it

209、 is almost impossible to ascribe labour market and socioeconomic impacts to specific occurrences of agricultural automation.The possible effects of agricultural automation on farm employment are likely to be diverse.Demand for low-skill labour is likely to decrease as many tasks become automated.Mea

210、nwhile,automation boosts the demand for relatively skilled workers.Looking at agrifood systems in their entirety,automation could decrease low-paying seasonal employment on farms but increase higher-paying and less seasonal employment upstream and downstream.|xix|EXECUTIVE SUMMARYImplications of aut

211、omation may also differ for different types of farms.For small-scale and subsistence farmers,automation can free up family labour for non-farm employment,but may also allow production to expand.On family commercial farms,it can both free up family labour and reduce demand for hired labour,but if com

212、mercial agricultural activities expand as a result of automation,there may be more need for hired workers.Corporate commercial farms are the most automated with a corresponding drop in labour requirements on farms.Nevertheless,even in this case,if automation adoption is spurred by rising wages and s

213、carce labour,it will tend to increase labour productivity and wages without causing unemployment.If automation occurs where there is an abundance of labour,and is incentivized by subsidies that make automation artificially cheap,there is a serious risk of displacing labour and generating unemploymen

214、t,with major socioeconomic implications,especially for the poorest and least skilled,who may not easily find employment elsewhere.Agricultural automation has significant socioeconomic impacts on consumers,because it results in reduced costs of food production.Developments in digital automation may a

215、lso create new entrepreneurial opportunities beneficial to consumers for example,by allowing the revival of nutrient-dense heirloom crops that were difficult to automate and substantially reduce production costs for organic foods,which are currently very labour-intensive.THE AGRICULTURAL AUTOMATION

216、PROCESS MUST BE INCLUSIVE AND NOT LEAVE ANYBODY BEHINDAgricultural automation must involve those who experience vulnerability,exclusion and marginalization,in particular small-scale producers,pastoralists,small-scale fisherfolk,small-scale foresters and forest communities,agricultural wage-workers,i

217、nformal microenterprises and workers,landless people,and migrant labourers.Involving women,youth and persons with disabilities is particularly important.The gender implications of on-farm automation are complex.However,women lag behind men in agricultural technology adoption due to barriers in acces

218、s to capital,inputs and services(e.g.information,extension,credit,fertilizer),and in some contexts also as a result of cultural norms.Policymakers and local implementation partners need to promote gender-sensitive technology development,dissemination and service provision.Young farmers appear to be

219、the first to eagerly embrace the process.Agricultural automation promises new types of jobs that require a strong skill set.A solid human capital development and capacity-building agenda,with a focus on youth,must be a priority.As labour-saving automation expands on farms,not only does the farm work

220、force become smaller,it becomes more skilled.An important challenge is to facilitate a transition of the agricultural workforce from low-skill manual activities to working with more complex technologies.However,fears that automation will displace millions of farm workers without other job prospects

221、are misplaced.The automation of agricultural jobs,with the consequent evolution of the farm workforce,is a gradual process that differs across localities,crops and farm tasks.The incentives to adopt labour-saving automation are greatest for specific labour-intensive farm tasks that are easily automa

222、ted at low cost.As some tasks become automated,others will remain labour-intensive.If the available automation technologies are not scale-neutral,there is a risk that small-scale producers and processors may be pushed out of business because they lack the economies of scale necessary to remain compe

223、titive.However,this is not an inevitable outcome of automation in agriculture;the key is for scale-neutral,low-cost automation to become ubiquitous.In any case,the assumption that limiting automation can preserve agricultural employment and incomes is ill-founded.Indeed,policies to restrict automati

224、on will only make farms less competitive and unable|xx|to expand their production.To improve wages and working conditions for their workers,farms must become more productive through new technologies.Without labour productivity-enhancing technologies,the prospects of moving poor farm workers out of p

225、overty and food insecurity are dim.INTRODUCING A ROADMAP FOR EFFICIENT,SUSTAINABLE AND INCLUSIVE AGRICULTURAL AUTOMATION:POLICIES,INVESTMENTS AND INSTITUTIONS Agricultural automation has strong potential for contributing to sustainable and inclusive rural development based on intensive,but sustainab

226、le,agriculture.However,achieving this potential is not automatic and depends on the socioeconomic context,as well as the policy and institutional environment in which the process of agricultural automation plays out.Whether countries gain or lose from the process depends on how they manage the trans

227、ition.Countries that build the necessary physical,economic,legal and social infrastructures for digital automation stand to benefit.Countries that ignore the challenge may lose.Like any technological change,agricultural automation inevitably entails some disruption,bringing benefits but also giving

228、rise to trade-offs.The report proposes a range of possible options regarding policies,institutions,legislation and investments.Together they form a roadmap to ensure that agricultural automation contributes to efficient,productive,sustainable,resilient and inclusive agrifood systems.Some options foc

229、us on creating a conducive environment for business in agriculture,in particular regarding investments in automation technologies,and these need to be complemented by regulations and other actions to guarantee they lead to environmental sustainability and climate resilience.Lastly,policies and progr

230、ammes must be in place to ensure the process works for all,especially marginalized groups,such as women,small-scale producers and youth.Governments will also need to balance trade-offs between different,and sometimes conflicting,economic,environmental and social objectives.The proposed policies,inve

231、stments and other public actions discussed in the next section as part of a roadmap for agricultural automation do not carry the same weight in all contexts.Governments must prioritize actions based on the challenges faced and their national capacities.One important cross-cutting area for government

232、 intervention is that of general services support(GSS),which represents government actions that,without distorting incentives or favouring certain actors over others(or certain sectors within agriculture),create an enabling environment for doing business in agriculture and agrifood systems.AGRICULTU

233、RE-TARGETED POLICIES AND INTERVENTIONS ALSO AFFECT AUTOMATION UPTAKEA number of agriculture-specific policies can support automation more directly and help overcome barriers to adoption,especially for small-scale producers.Governments can influence the adoption process through credit policies that d

234、irectly target agricultural automation.Investment loans are the most common solution for financing automation and they come in various forms,such as contract-based securities,loan guarantee schemes,joint liability groups,leasing,and matching grants.In addition,“smart”targeted subsidies that do not d

235、istort markets can play a role.Improved land tenure security is essential,as insecure land tenure restricts producers access to credit because they cannot use land titles as collateral.Reducing import duties for machinery,digital equipment and spare parts,and improving customs procedures can also he

236、lp to lower the transaction costs of automation technologies and spur uptake.Human capital development is needed to overcome digital illiteracy,for example,through vocational training centres.Knowledge and skills of manufacturers,owners,operators,technicians and farmers must all be strengthened,with

237、 youth as a strategic target as they are often the key drivers of automation.Improving agricultural extension|xxi|EXECUTIVE SUMMARYand rural advisory services can facilitate adoption.Public extension services have always played an important role in ensuring inclusive agricultural automation.However,

238、the shortage of well-trained extension personnel is a major constraint in most low-and middle-income countries.While human capital is key for users(i.e.farmers and service providers),it is equally important for those involved in innovations(e.g.researchers and scientists).Governments can fund or con

239、duct applied research and development on automation technologies,in particular aiming at solutions adapted to local needs and those of small-scale producers.An important area of research is impact assessment of precision agriculture solutions in terms of profitability,environmental sustainability an

240、d inclusiveness.There needs to be a focus on both small machinery and low-tech digital solutions,such as interactive voice response(IVR),unstructured supplementary service data(USSD)and short message service(SMS).Small machinery may be more suited to local conditions and small farms,while low-tech s

241、olutions may more easily reach all farmers at a low cost.Finally,governments need to develop quality assurance and safety standards,which may be managed by public,market and third-sector organizations.Automation safety laws and regulations need to be based on inclusive consultation with all stakehol

242、ders,and must be transparent and supported by measures to ensure compliance by users.POLICIES,INSTITUTIONS AND INVESTMENTS BEYOND AGRIFOOD SYSTEMS AFFECT AGRICULTURAL AUTOMATION UPTAKEGeneral policies and investments not specifically aimed at agrifood systems can shape the enabling environment,inclu

243、ding infrastructure.Road infrastructure is particularly poor in low-income countries and in most of sub-Saharan Africa.Improving this infrastructure can reduce the transaction costs of access to machinery,spare parts,repairs and fuel,and facilitate the emergence of service markets.Investing in energ

244、y infrastructure,for example,through development of off-grid electricity from renewable resources,is equally important as no automation technology works without energy.The availability of renewable energy based on local investments can buffer both shocks in the energy sector and fluctuations in fuel

245、 prices.Improving communication infrastructure and internet connectivity is critical for the proper functioning of agricultural automation.Poor connectivity is widespread even in some rural areas in high-income countries.Policies can grant tax concessions or provide low interest loans for rural inte

246、rnet providers.Legislation can play an important role promoting publicprivatecommunity partnerships to improve connectivity and related infrastructure in rural areas and provide data services and support.Investments should also target associated enabling infrastructures,such as public datasets on we

247、ather forecasts and calendars for crop and livestock production.While physical infrastructure is a primary concern,institutions,macroeconomic conditions and broader institutional capacity are also key to agricultural automation uptake.Improving general credit markets is important;indeed,small-scale

248、producers access to credit at affordable interest rates is usually limited,making it impossible to finance automation technologies.It is vital to strengthen institutional and political capacity to guide the development of automation technologies;if,on the other hand,powerful private technology compa

249、nies get there first,the consequences are potentially negative with spillover effects on wider society.What is more,if transparent national data policies are put in place including data protection,data sharing and privacy regulations they themselves can facilitate digital automation.Other enablers a

250、re the development of national data infrastructures and the promotion of interoperability,that is,accurate and reliable communication among machines.Finally,exchange rate policies and trade policies can affect automation patterns through the import costs for machinery,digital equipment and spare par

251、ts.|xxii|IF DONE RIGHT,AGRICULTURAL AUTOMATION WILL CONTRIBUTE TO INCLUSIVE AND SUSTAINABLE AGRIFOOD SYSTEMSEven assuming countries are able to create a level playing field for the provision by the private sector of innovative technologies,challenges linked to automation will remain.Agricultural aut

252、omation faces three specific challenges:to not leave marginalized groups behind;to avoid increased unemployment and job displacement;and to prevent environmental damage.Policies can play a role in addressing these challenges and ensuring that automation contributes to an inclusive and sustainable ag

253、ricultural transformation.Therefore,action by policymakers will most likely be required.First,governments need to ensure that women,youth and other disadvantaged groups benefit from automation.Policies addressing disadvantages faced by women(e.g.improving womens land rights or facilitating their acc

254、ess to credit and extension)also help increase womens access to automation.Public research and development can focus on gender-friendly mechanization technologies tailored to the needs of women.Furthermore,a specific agenda on agricultural automation is needed,targeting rural youth and other disadva

255、ntaged groups,ensuring that they acquire the necessary skills to perform the new high-skill jobs associated with automation.Second,governments need to safeguard against negative effects on employment.Where automation emerges as a response to market forces(e.g.rising rural wages)and replaces unpaid f

256、amily labour,it is unlikely to generate unemployment.On the other hand,if artificially pushed by public efforts(e.g.through subsidized imports of machinery),it could lead to unemployment,job displacement and lower rural wages.Policymakers should therefore not promote automation before it is actually

257、 needed.At the same time,they should not inhibit its adoption based on the claim that it will displace labour and create unemployment.Policy support that provides public or collective goods through GSS is the most likely to allow for a smooth transition towards greater automation without creating un

258、employment.This includes supporting agricultural research and development and knowledge transfer services.Third,policies need to ensure that agricultural automation contributes to sustainable and resilient agrifood systems.While motorized mechanization has generated many benefits,it has also produce

259、d negative environmental impacts,including biodiversity loss,soil compaction and erosion,and degraded water quality.More advanced digital automation technologies,such as precision agriculture,can minimize or avoid these impacts.Applied technical and agronomic research should explore automation solut

260、ions that best fit local agroecological conditions,and governments should facilitate adoption of environmentally friendly automation technologies.Farmers can best choose which automated solutions fit their local agroecological conditions,but governments must create an enabling environment,including

261、information on available technologies.In conclusion,if care is taken to address the above challenges,agricultural automation can function as a catalyst to support the attainment of the Sustainable Development Goals(SDGs),particularly SDGs 1,2,3,9 and 10.The right mix of technologies as well as appro

262、priate policies,interventions and investments will depend on the level of economic development,the institutions in place,local agronomic characteristics,and policymakers objectives.It is important that policymakers recognize the context specificity of adoption and assess the particular problems faci

263、ng an area(e.g.connectivity,inequality,poverty,food insecurity,malnutrition)before combining policy instruments for action.It is up to agricultural producers to choose which technologies to adopt.It is up to governments to provide an enabling environment where innovation can thrive,as well as the ne

264、cessary incentives to make the adoption process as inclusive as possible.n|xxiii|CHINAFarmer monitoring chili crops with a tablet.iS 1 AGRICULTURAL AUTOMATION:WHAT IT IS AND WHY IT IS IMPORTANT KEY MESSAGES Automation presents many opportunities for agricultural producers and agrifood systems genera

265、lly,but uneven access and adoption across and within countries prevent realization of its full potential.In particular,agricultural automation can raise productivity,build resilience,improve product quality and resource-use efficiency,reduce human drudgery and labour shortages,enhance environmental

266、sustainability,and facilitate climate change adaptation and mitigation.Automation in agriculture can contribute to achieving the Sustainable Development Goals(SDGs)by 2030,not least SDG 1(No Poverty)and SDG 2(Zero Hunger)and those relating to environmental sustainability and climate change,and drive

267、 broader changes in agrifood systems by creating new entrepreneurial opportunities.Automation can also create inequalities if it remains out of reach for some,especially small-scale and female agricultural producers.If it is not well managed,it can also have negative environmental consequences by co

268、ntributing to,for example,monoculture.To unleash the full potential of agricultural automation,technologies must be available,inclusive,accessible to all,and tailored to local conditions (i.e.they need to be scale-neutral),and they must improve environmental sustainability.A key challenge is ensurin

269、g that technologies are adapted to local contexts and local innovation processes that are promoted,as well as building the capacity of producers to adopt and use such new technologies.Technological change,driven and facilitated by processes of innovation,has been a key driver of socioeconomic transf

270、ormation throughout the ages,bringing productivity and income gains,as well as improvements in human well-being.This applies to agrifood systems as it does to other sectors of the economy.Today,to nourish a constantly growing world population,we need to increase nutritious food production while addr

271、essing limited agricultural land availability,unsustainable natural resource use,increasing shocks and stresses,and the consequences of accelerating climate change.Hence,agrifood systems must meet the challenge of increasing productivity in a sustainable manner.There is an ever more urgent need to p

272、ut in place new technological solutions that can make agricultural production more productive and sustainable across all its sectors crops and livestock,fisheries and aquaculture,and forestry and boost productivity levels in agrifood systems beyond primary production.As technological change continue

273、s to transform our economies,recent advances in digital technologies,such as faster computers and mobile phones,sensors,machine learning,and artificial intelligence(AI),have led to ground-breaking equipment,transforming the use of machinery in agricultural tasks.As with other technologies and innova

274、tions in general these new technologies may complement or replace old ones.Sometimes older technologies and practices may be revived or repurposed for new uses.They have the potential to decouple not only much of the physical work from agricultural production,but also the mental work required to col

275、lect and|1|CHAPTER 1 AGRICULTURAL AUTOMATION:WHAT IT IS AND WHY IT IS IMPORTANTautomation solutions that enhance environmental sustainability can contribute to progress towards SDG6(Clean Water and Sanitation),SDG7(Affordable and Clean Energy),SDG12(Responsible Consumption and Production),SDG13(Clim

276、ate Action),SDG14(Life below Water)andSDG15(Life on Land).This report investigates how automation in agriculture,as well as in the early stages of the food supply chain,can contribute to achieving the SDGs and ensure positive impacts.It reviews the state of agricultural automation adoption,including

277、 trends in implementation,the drivers of these trends,and their potential socioeconomic impacts.It discusses a range of policy and legislative options and interventions that could maximize the benefits and minimize the risks of automation technologies.Chapter1 defines agricultural automation,explain

278、s its relevance for sustainable development,and outlines the opportunities,challenges and trade-offs that new automation technologies can create or shape.A fundamental premise for the analysis in this report is that advances in agricultural automation can help humanity overcome numerous challenges a

279、ssociated with the need to increase nutritious food production sustainably,but that these are likely to create new challenges that need to be managed if we are to make the most of the potential that automation offers.nHOW DID WE GET HERE?The process of technological change in agricultural production

280、 is not new.History shows how humankind has constantly striven to reduce the toil of farming by developing ingenious tools and harnessing the power of fire,wind,water and animals.By 4000 BCE,Mesopotamian farmers were using ox-drawn ploughs,2 and water-powered mills emerged in China around 1000 BCE.3

281、 Technological change has accelerated during the past two centuries,triggered by the discovery of steam power(with the emergence of steam threshers and ploughs by the mid-nineteenth century),and later reinforced by the rise of fossil-energy-powered tractors,harvesters and processing machines,as well

282、 as new food-preserving technologies,among others.4,5 Such changes have allowed societies analyse information and data and make decisions.They can therefore help implement precision agriculture1 by improving the timeliness of operations and allowing a more accurate and efficient application of input

283、s.Not for the first time in human history,there are fears about the negative consequences of technological progress for labourers.In practice,the accepted wisdom that automation leads to loss of jobs and increased unemployment is not borne out by historical realities.This report argues that,on the c

284、ontrary,automation,including digital technologies,can make agricultural production more resilient to shocks and stresses,such as drought and accelerating climate change.Agricultural automation can raise productivity,improve product quality,increase resource-use efficiency,alleviate labour shortages

285、and promote decent employment by reducing human drudgery in addition to enhancing environmental sustainability.While it must be recognized that introducing automation technologies,particularly if unsuited to a specific local context,can lead to socioeconomic challenges for some groups,including nega

286、tive impacts on the labour market,such challenges can be addressed through appropriate policies and legislation,and these are discussed in the report.Equally challenging are barriers that can prevent the application of automation,in particular among poor small-scale producers,thus creating access in

287、equalities.Agricultural automation is of major relevance to several Sustainable Development Goals(SDGs),not least SDG1(No Poverty)and SDG2(Zero Hunger).To the extent that agriculture around the world is receptive to automation,it can also drive progress towards SDG9(Industry,Innovation and Infrastru

288、cture),which calls for supporting and upgrading technological capabilities,research and innovation,especially in low-income countries.Likewise,if barriers to adoption are overcome,automation can play a role in closing the technological divide and promoting progress towards SDG5(Gender Equality),SDG8

289、(Decent Work and Economic Growth)and SDG10(Reduced Inequalities).Through its potential to provide safer working conditions and safer,higher quality food,it can contribute to progress towards SDG3(Good Health and Well-being).Finally,the successful adoption of|2|THE STATE OF FOOD AND AGRICULTURE 2022a

290、cross the world to gradually reduce the drudgery of agricultural production and free agricultural producers from the heavy physical toil of farming.As a consequence,there is now less need for labour in primary agricultural production;workers are released for employment in other sectors,such as indus

291、try and services,children are free to go to school,and women can pursue non-agricultural employment opportunities or household activities.This has been accompanied by tremendous advances in other agricultural operations or inputs,such as seeds,fertilizers and irrigation advances that led to the gree

292、n revolution and allowed food production to expand,even with reduced labour input and limited expansion of farmland.6This process of increased agricultural productivity and reallocation of labour away from farming is often referred to as agricultural transformation.As economies develop,labour-saving

293、 technologies push agricultural workers off farms while profitable activities in the non-farm sector simultaneously pull them towards the industry and services sectors.7,8,9 The share of the population working in agriculture thus declines as agricultural transformation advances.Prior to the Industri

294、al Revolution,most people throughout the world lived in rural areas and depended on primary agricultural production for their livelihood.This is no longer the case for countries that have undergone deep agricultural transformation.In the United States of America,for example,only 1.4percent of the wo

295、rkforce were employed in farming in 2020.10 Other high-income countries also have very small shares of their population directly employed on farms.This agricultural transformation process does not occur in isolation but involves transformation of the whole economy.Indeed,the provision of sufficient,

296、safe and nutritious food for expanding and increasingly urbanized populations,requires investments not only in agricultural production,but also in transport,storage and food processing,as well as other physical and market infrastructures.Access to roads and transport is necessary to enable agricultu

297、ral producers to source adequate agricultural inputs,including physical and human capital,and have access to lucrative markets for their produce.The process of automation in agriculture today is occurring within the context of evolving agrifood systems.Indeed,automation in agriculture has implicatio

298、ns for agrifood systems beyond primary agriculture and is itself affected by developments beyond primary production.Automation in primary production can be a driver of transformation in agrifood systems,not least by creating new entrepreneurial opportunities both upstream and downstream.Similarly,au

299、tomation in upstream and downstream sectors has implications for automation in primary production.The effects will depend on the dynamics of agrifood systems,their components,and the bidirectional linkages between them.Technology uptake is also a gradual process,11 requiring practice,testing and ada

300、ptation in various contextual realities,and its impacts take time to manifest themselves.For example,while the rise of mechanized tractors undoubtedly brought many benefits,it also had negative environmental impacts in terms of deforestation,loss of biodiversity and excessive use of fossil fuels whi

301、ch took decades to become apparent.12,13 A similar reasoning may be applied to the technologies adopted in the green revolution;they undoubtedly brought substantial yield improvements,but the long-term environmental costs have been very high in some places.13 n WHAT IS AGRICULTURAL AUTOMATION?Todays

302、 agricultural automation lies at the end of a long evolution of mechanization throughout the history of agriculture.The Food and Agriculture Organization of the United Nations(FAO)defines mechanization as the use of all means of machinery and equipment,from simple and basic hand tools to more sophis

303、ticated and motorized machinery,in agricultural operations.14 With mechanization,therefore,only the performing part of agricultural work is automated,and the degree of automation increases as we move from basic hand tools towards motorized machinery.Two phases always precede the performing of any ag

304、ricultural operation:diagnosis and decision-making.Figure1(p.4)represents the three|3|CHAPTER 1 AGRICULTURAL AUTOMATION:WHAT IT IS AND WHY IT IS IMPORTANTphases as a cyclical process with continuous feedback between them.The implementation of any agricultural operation from harvesting,to disease con

305、trol,to irrigation generally starts by diagnosing the issue at hand to determine what,if any,action is needed.By way of illustration,before irrigating,producers need to know whether plants require water.Similarly,livestock producers need to know the health status of animals before prescribing antibi

306、otics.A diagnosis can be made using producers experience,but it can also be automated through sensors monitored by the producers.Once a diagnosis is made,producers decide what needs to be done(e.g.the amount of irrigation or antibiotics needed)and when.Decisions can then be made by agricultural prod

307、ucers based on their experience and knowledge,or they can be automated by controllers sending signals based on information received from sensors in the diagnosis phase.In the third and final phase(performing),farmers can either conduct agricultural operations directly,using hand tools or animals,or

308、operate various machines.The most advanced automation technologies allow the three phases to be entirely automated.Fruit-harvesting robots are a case in point.These robots carry out all three phases sequentially and automatically,while agricultural producers simply monitor the sensors and maintain t

309、he equipment.Any technology that automates at least one of the three phases may be classified as an automation technology.Motorized mechanization using engine power15 focuses essentially on the last of the three phases:performing.It automates agricultural operations such as ploughing,seeding,fertili

310、zing,milking,feeding,harvesting and irrigating,among many others.For the purpose of this report,any technology that assists agricultural producers in one or more of the three phases in Figure1 is considered an automation technology.This includes situations where,for example,agricultural producers us

311、e sensors to monitor plants and animals,thus automating the diagnosis phase,but make decisions based on their own experience without FIGURE 1 THREE-PHASE CYCLE OF AN AUTOMATION SYSTEMDIAGNOSISPERFORMINGDECISION-MAKINGSOURCE:FAO elaboration for this report.|4|THE STATE OF FOOD AND AGRICULTURE 2022the

312、 assistance of automated equipment.In some cases,the performing phase can also involve sensing(e.g.the creation of yield maps during harvesting),which then feeds into the diagnosis phase,hence the cyclical representation of Figure1.With the rise of digital technologies and automated equipment such a

313、s sensors and robots that rely on machine learning and AI,the automation of diagnosis and decision-making becomes possible.Motorized machines are increasingly complemented,or even superseded,by new digital equipment that automates diagnosis and decision-making.For example,a conventional tractor can

314、be converted into an automated vehicle capable of sowing a field autonomously.15 Therefore,while mechanization eases and reduces hard and repetitive work and relieves labour shortages,digital automation technologies further improve productivity by allowing more precise implementation of agricultural

315、 operations and more efficient use of resources and inputs.As a consequence,digital automation can lead to gains in environmental sustainability and greater resilience to climate shocks and stresses.However,the possible effects on labour require careful consideration,as explained later in the report

316、.Figure 2 represents this technological evolution,illustrating the progression of agricultural technologies with examples of each from FIGURE 2 EVOLUTION OF AGRICULTURAL AUTOMATION 4000 BC1910sMECHANIZATIONDIGITAL AUTOMATION(PRECISION AGRICULTURE)AUTOMATION AS THE FOCUS OF THE REPORT 10000 BC1980s20

317、00sManual toolsHumans do the diagnosis and decision-making.Performing is aided by simple tools.Animal tractionHumans do the diagnosis and decision-making.Performing is aided by animal traction.Robotics with AI Machines do the diagnosis,decision-making and performing.Humans monitor and maintain.Motor

318、ized mechanizationHumans do the diagnosis and decision-making,but use motorized machines to assist in the performing.Digital equipmentHumans use digital tools to improve diagnosis and decision-making;they can also be added to motorized machines for more precise performing.Approximateperiod ofintrodu

319、ctionGroups oftechnologiesExamples oftechnologiesAxeHoeOx-drivenploughIrrigationsystemLivestocksensorsTractorDriverlesstractorFishfinderHarvestrobotFruitpickerAutonomoussprayingrobotMilkingmachineTreeharvesterAnimaldraftSOURCE:FAO elaboration for this report.|5|CHAPTER 1 AGRICULTURAL AUTOMATION:WHAT

320、 IT IS AND WHY IT IS IMPORTANTthose that assist solely the physical performing of operations to those that assist diagnosis and decision-making.The technological evolution may be summarized through the following technology categories:Manual tools,where humans make the diagnosis and the decisions,whi

321、le the performing is assisted by simple tools,such as axes and hoes.Animal traction,where humans still make the diagnosis and the decisions,but physical agricultural operations are performed,or eased,by animals operating agricultural machinery such as ploughs.Motorized mechanization,where humans con

322、tinue to make the diagnosis and the decisions,but motorized machinery and equipment perform the operations.This category marks a shift in the source of energy used on the farm from internal(e.g.human muscle and animals)to external(e.g.fossil fuels and electricity).This shift,however,calls for specif

323、ic infrastructures to ensure the continuous availability of these energy sources.Digital equipment,where a wide range of digital tools assist humans to improve the diagnosis and/or decision-making by automating mental work or by increasing the precision of motorized machinery.Robotics with AI,where

324、humans rely on agricultural robots that use AI for all functions of diagnosis,decision-making and performing.These can be static(e.g.milking robots)or mobile(e.g.fruit-harvesting robots).Humans monitor the sensors and maintain the robots.This category includes the most advanced automation technologi

325、es,some of which have not yet been scaled up or are still under development.Unfortunately,this variety of tools and technologies has contributed to inconsistent definitions of agricultural automation in the literature,hampering efforts to collect automation data.11 For example,some define agricultur

326、al automation as autonomous navigation by robots without human intervention,providing precise information to help develop agricultural operations.16 Others define it as accomplishment of production tasks through mobile,autonomous,decision-making,mechatronic devices.17 However,these definitions are v

327、ery restrictive and do not capture all the aspects and forms of automation static equipment,such as robotic milking machines,is a case in point.Moreover,the definitions exclude not only most motorized machinery that automates the performing of agricultural operations,but also digital tools(e.g.senso

328、rs)that automate only diagnosis.Figure2(p.5)is a simplification of the historical reality of the evolution of automation technologies;there can be overlaps and grey areas between the categories.Nevertheless,it helps to outline the focus of this report and define agricultural automation.The concept o

329、f agricultural automation is applied to the three blue-shaded boxes,which constitute the focus of the report.On this basis,the report proposes a definition of agricultural automation as:the use of machinery and equipment in agricultural operations to improve their diagnosis,decision-making or perfor

330、ming,reducing the drudgery of agricultural work and/or improving the timeliness,and potentially the precision,of agricultural operations.By this definition,agricultural automation includes precision agriculture,which is a management strategy that gathers,processes and analyses data to improve manage

331、ment decisions(see Glossary).Starting from the first blue-shaded box in Figure2,motorized mechanization includes machines operated by humans to perform tasks such as ploughing,irrigating and milking.However,humans make the diagnosis based on their own observation or by measuring simple parameters;th

332、ey then make decisions based on(internal or external)experience,knowledge and available resources.The last two categories of Figure 2 cover digital automation.They include a wide range of tools,equipment and software that are,or can be,multifunctional and interdisciplinary,allowing the management of

333、 resources throughout the system to be highly|6|THE STATE OF FOOD AND AGRICULTURE 2022optimized,individualized,intelligent and anticipatory.18 As digital automation technologies(robotics with AI)develop,all three phases diagnosis,decision-making and performing can be automated,with the human role largely confined to monitoring and maintenance of automation equipment.This is the case with the fruit