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IoT in Agriculture: 9 Technology Use Cases for Smart Farming (and Challenges to Consider)

The article was updated on March 1, 2023.

With the growing adoption of the Internet of Things (IoT), connected devices have penetrated every aspect of our life , from health and fitness, home automation, automotive and logistics, to smart cities and industrial IoT.

Thus, it is only logical that IoT, connected devices, and automation would find its application in agriculture, and as such, tremendously improve nearly every facet of it. How could one still rely on horses and plows when self-driving cars and virtual reality are no longer a sci-fi fantasy but an everyday occurrence?

Farming has seen a number of technological transformations in the last decades, becoming more industrialized and technology-driven. By using various smart agriculture gadgets, farmers have gained better control over the process of raising livestock and growing crops, making it more predictable and improving its efficiency.

This, along with the growing consumer demand for agriculture products, has contributed to the increased proliferation of smart farming technologies worldwide. In 2022, the market share for IoT in agriculture reached $13.76 billion.

In this article, we will explore the IoT use cases in agriculture and examine their benefits. So, if you are considering investing into smart farming, or are planning to build an IoT solution for agriculture, dive right in.

• What is smart agriculture? The definition and market size

There are many ways to refer to modern agriculture. For example, AgriTech refers to the application of technology in agriculture in general.

Smart agriculture , on the other hand, is mostly used to denote the application of IoT solutions in agriculture. So what is smart agriculture using IoT? By using IoT sensors to collect environmental and machine metrics, farmers can make informed decisions, and improve just about every aspect of their work – from livestock to crop farming.

For example, by using smart agriculture sensors to monitor the state of crops, farmers can define exactly how many pesticides and fertilizers they have to use to reach optimal efficiency. The same applies to the smart farming definition.

Although smart agriculture IoT, as well as industrial IoT in general, aren’t as popular as consumer connected devices; yet the market is still very dynamic. The adoption of IoT solutions for agriculture is constantly growing.

Namely, COVID-19 has had a positive impact on IoT in the agriculture market share. Disruptions in the supply chain, and the shortage of qualified workers, has propelled its CAGR to 9,9%. In fact, as per recent reports, the smart framing market share is set to reach $28.56 billion by 2030.

At the same time, the global smart agriculture market size is expected to triple by 2025, reaching $15.3 billion (compared to being slightly over $5 billion back in 2016).

Because the market is still developing, there is still ample opportunity for businesses willing to join in. Building IoT products for agriculture within the coming years can set you apart as an early adopter, and as such, help you pave the way to success.

But why should you consider building an IoT application for agriculture in the first place?

The Benefits of smart farming: How’s IoT shaping agriculture

Technologies and IoT have the potential to transform agriculture in many aspects. Namely, there are 6 ways IoT can improve agriculture :

• Data, tons of data, collected by smart agriculture sensors, e.g. weather conditions, soil quality, crop’s growth progress or cattle’s health. This data can be used to track the state of your business in general as well as staff performance, equipment efficiency, etc.
• Better control over the internal processes and, as a result, lower production risks . The ability to foresee the output of your production allows you to plan for better product distribution. If you know exactly how much crops you are going to harvest, you can make sure your product won’t lie around unsold.
• Cost management and waste reduction thanks to the increased control over the production . Being able to see any anomalies in the crop growth or livestock health, you will be able to mitigate the risks of losing your yield.
• Increased business efficiency through process automation . By using smart devices, you can automate multiple processes across your production cycle, e.g. irrigation, fertilizing, or pest control.
• Enhanced product quality and volumes . Achieve better control over the production process and maintain higher standards of crop quality and growth capacity through automation.
• Reduced environmental footprint. Automation also carries environmental benefits. Smart farming technologies can cut down on the use of pesticides and fertilizer by offering more precise coverage, and thus, reduce greenhouse gas emissions.

As a result, all of these factors can eventually lead to higher revenue .

Now that we have outlined how IoT can be advantageously applied in the sphere of agriculture, let’s take a look at how the listed benefits can find their application in real life.

• IoT use cases in agriculture (with examples)

There are many types of IoT sensors for agriculture as well as IoT applications in agriculture in general:

1. Monitoring of climate conditions

Probably the most popular smart agriculture gadgets are weather stations, combining various smart farming sensors. Located across the field, they collect various data from the environment and send it to the cloud. The provided measurements can be used to map the climate conditions, choose the appropriate crops, and take the required measures to improve their capacity (i.e. precision farming).

Some examples of such agriculture IoT devices are allMETEO , Smart Elements , and Pycno .

2. Greenhouse automation

Typically, farmers use manual intervention to control the greenhouse environment. The use of IoT sensors enables them to get accurate real-time information on greenhouse conditions such as lighting, temperature, soil condition, and humidity.

In addition to sourcing environmental data, weather stations can automatically adjust the conditions to match the given parameters. Specifically, greenhouse automation systems use a similar principle.

For instance, Farmapp and Growlink are also IoT agriculture products offering such capabilities among others.

3. Crop management

One more type of IoT product in agriculture and another element of precision farming are crop management devices. Just like weather stations, they should be placed in the field to collect data specific to crop farming; from temperature and precipitation to leaf water potential and overall crop health.

Thus, you can monitor your crop growth and any anomalies to effectively prevent any diseases or infestations that can harm your yield. Arable and Semios can serve as good representations of how this use case can be applied in real life.

4. Cattle monitoring and management

Just like crop monitoring, there are IoT agriculture sensors that can be attached to the animals on a farm to monitor their health and log performance. Livestock tracking and monitoring help collect data on stock health, well-being, and physical location.

For example, such sensors can identify sick animals so that farmers can separate them from the herd and avoid contamination. Using drones for real-time cattle tracking also helps farmers reduce staffing expenses. This works similarly to IoT devices for petcare .

For example, SCR by Allflex and Cowlar use smart agriculture sensors (collar tags) to deliver temperature, health, activity, and nutrition insights on each individual cow as well as collective information about the herd.

5. Precision farming

Also known as precision agriculture, precision farming is all about efficiency and making accurate data-driven decisions. It’s also one of the most widespread and effective applications of IoT in agriculture.

By using IoT sensors, farmers can collect a vast array of metrics on every facet of the field microclimate and ecosystem: lighting, temperature, soil condition, humidity, CO2 levels, and pest infections. This data enables farmers to estimate optimal amounts of water, fertilizers, and pesticides that their crops need, reduce expenses, and raise better and healthier crops.

For example, CropX builds IoT soil sensors that measure soil moisture, temperature, and electric conductivity enabling farmers to approach each crop’s unique needs individually. Combined with geospatial data, this technology helps create precise soil maps for each field. Mothive offers similar services, helping farmers reduce waste, improve yields, and increase farm sustainability.

6. Agricultural drones

Perhaps one of the most promising agritech advancements is the use of agricultural drones in smart farming. Also known as UAVs (unmanned aerial vehicles), drones are better equipped than airplanes and satellites to collect agricultural data. Apart from surveillance capabilities, drones can also perform a vast number of tasks that previously required human labor: planting crops, fighting pests and infections, agriculture spraying, crop monitoring, etc.

Read more: Why Use Agriculture Drones? Main Benefits and Best Practices

DroneSeed , for example, builds drones for planting trees in deforested areas. The use of such drones is 6 times more effective than human labor. A Sense Fly agriculture drone eBee SQ uses multispectral image analyses to estimate the health of crops and comes at an affordable price.

7. Predictive analytics for smart farming

Precision agriculture and predictive data analytics go hand in hand. While IoT and smart sensor technology are a goldmine for highly relevant real-time data, the use of data analytics helps farmers make sense of it and come up with important predictions: crop harvesting time, the risks of diseases and infestations, yield volume, etc. Data analytics tools help make farming, which is inherently highly dependent on weather conditions, more manageable, and predictable.

For example, the Crop Performance platform helps farmers access the volume and quality of yields in advance, as well as their vulnerability to unfavorable weather conditions, such as floods and drought. It also enables farmers to optimize the supply of water and nutrients for each crop and even select yield traits to improve quality.

Applied in agriculture, solutions like SoilScout enable farmers to save up to 50% irrigation water, reduce the loss of fertilizers caused by overwatering, and deliver actionable insights regardless of season or weather conditions.

8. End-to-end farm management systems

A more complex approach to IoT products in agriculture can be represented by the so-called farm productivity management systems. They usually include a number of agriculture IoT devices and sensors, installed on the premises as well as a powerful dashboard with analytical capabilities and in-built accounting/reporting features.

This offers remote farm monitoring capabilities and allows you to streamline most of the business operations. Similar solutions are represented by FarmLogs and Cropio .

In addition to the listed IoT agriculture use cases, some prominent opportunities include vehicle tracking (or even automation), storage management, logistics, etc.

9. Robots and autonomous machines

Robotic innovations also offer a promising future in the field of autonomous machines for agricultural purposes. Some farmers already use automated harvesters, tractors, and other machines and vehicles that can operate without a human controlling it. Such robots can complete repetitive, challenging, and labor-intensive tasks.

For instance, modern agrobots include automated tractors that can work on assigned routes, send notifications, start work at planned hours, etc. Such tractors are driverless and cut farmers’ labor costs. Bear Flag Robotics is one company that works on such technology at the moment.

In addition, smart farming also uses robots for planting seeds, weeding, and watering. The given jobs are very demanding and labor-intensive. Yet, robots, such as ones from Eco Robotics , can detect weeds or plant seeds using computer vision and AI technology. These agricultural robots work delicately, drastically reducing harm to the plants and the environment.

• Things to consider before developing your smart farming solution

As we can see, the use cases for IoT in agriculture are endless. There are many ways smart devices can help you increase your farm’s performance and revenue. However, agriculture IoT apps development is no easy task.

There are certain challenges you need to be aware of if you are considering investing into smart farming.

1. The hardware

To build an IoT solution for agriculture, you need to choose the sensors for your device (or create a custom one). Your choice will depend on the types of information you want to collect and the purpose of your solution in general.

In any case, the quality of your sensors is crucial to the success of your product: it will depend on the accuracy of the collected data and its reliability.

2. The brain

Data analytics should be at the core of every smart agriculture solution. The collected data itself will be of little help if you cannot make sense of it.

Thus, you need to have powerful data analytics capabilities and apply predictive algorithms and machine learning in order to obtain actionable insights based on the collected data.

3. The maintenance

Maintenance of your hardware is a challenge that is of primary importance for IoT products in agriculture, as the sensors are typically used in the field and can be easily damaged.

Thus, you need to make sure your hardware is durable and easy to maintain. Otherwise you will need to replace your sensors more often than you would like.

4. The mobility

Smart farming applications should be tailored for use in the field. A business owner or farm manager should be able to access the information on site or remotely via a smartphone or desktop computer.

Plus, each connected device should be autonomous and have enough wireless range to communicate with the other devices and send data to the central server.

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5. The infrastructure

To ensure that your smart farming application performs well (and to make sure it can handle the data load), you need a solid internal infrastructure.

Furthermore, your internal systems have to be secure. Failing to properly secure your system only increases the likeliness of someone breaking into it, stealing your data or even taking control of your autonomous tractors.

6. Connectivity

The need to transmit data between many agricultural facilities still poses a challenge for the adoption of smart farming. Needless to say, the connection between these facilities should be reliable enough to withstand bad weather conditions and to ensure non-disruptive operations.

Today, IoT devices still use varying connection protocols, although the efforts to develop unified standards in this area are currently underway. The advent of 5G and technologies like space-based Internet will, hopefully, help find a solution to this problem.

7. Data collection frequency

Because of the high variety of data types in the agricultural industry, ensuring the optimal data collection frequency can be problematic. The data from field-based, aerial and environmental sensors, apps, machinery, and equipment, as well as processed analytical data, can be a subject of restriction and regulations.

Today, the safe and timely delivery, and sharing of this data is one of the current smart farming challenges.

8. Data security in the agriculture industry

Precision agriculture and IoT technology imply working with large sets of data, which increases the number of potential security loopholes that perpetrators can use for data theft and hacking attacks. Unfortunately, data security in agriculture is still, to a large extent, an unfamiliar concept.

Many farms, for example, use drones that transmit data to farm machinery. This machinery connects to the Internet but has little to zero security protection, such as user passwords or remote access authentications.

Some of the basic IoT security recommendations include monitoring data traffic, using encryption methods to protect sensitive data, leveraging AI-based security tools to detect traces of suspicious activity in real-time, and storing data in the blockchain to ensure its integrity.

To fully benefit from IoT, farmers will have to get familiar with the data security concept, set up internal security policies, and adhere to them.

• Our work case of IoT solutions for agriculture

Our team at Eastern Peak has also contributed to the progress of IoT applications in agriculture. The IoT-powered irrigation application, GreenIQ, helps gardeners reduce water usage by 50%, monitor humidity levels, and predict the best timing for irrigation. GreenIQ uses smart sensors to analyze meteorological conditions and soil types, creating the perfect irrigation strategy and adapting to new environments.

The GreenIQ application also integrates with the most well-known home automation platforms. This app is another valuable contribution to eco-friendly gardening and one of many examples of how smart farming products can change the future of agriculture.

• Grow your agriculture business with smart IoT solutions from Eastern Peak

According to the UN Food and Agriculture Organization (FAO) , the global population is expected to surpass 9 billion people by 2050. To produce enough food for the given population, agriculture production volumes have to increase by 50%.

As the resources for agricultural operations are limited (most of the lands suitable for farming are already in use), the only way to increase volume is to improve production efficiency. There is no doubt as to the extent with which smart farming can help tackle this challenge; in fact, it seems that it is not possible without it. Here at Eastern Peak we develop custom IoT solutions for agriculture, tailored to your particular needs.

How to get started?

From cattle tracking to advanced field mapping, IoT applications in smart agriculture vary from farm to farm depending on your market segment, climate, and region. In many instances, out-of-the-box tools won’t be relevant, and you may need a tailored smart farming IoT solution. At Eastern Peak we approach each customer individually to meet their unique needs.

The product discovery phase is the best first step you can take to lay a solid foundation for the development of your app. It includes a functional specification, UX/UI design, and a visual prototype that will give you a clear vision of the end product. On average, this phase takes 4-6 weeks.

The product discovery phase can help you:

• define a full scope of work and develop a roadmap for the project
• set a realistic budget for your MVP and plan your resources
• test the waters with your audience using a visual prototype
• craft a convincing investment pitch
• get to know your team

We at Eastern Peak have already helped many startups and Fortune 500 companies digitize and streamline their operations with the help of technologies. We provide end-to-end services building IoT solutions across a number of business domains, from hardware design to software development, testing, and integration.

To receive professional consultation from our experts, get in touch with us using our contact form .

• Smart Farming: How Automation Is Transforming Agriculture
• 3 Edge Computing Use Cases for Smart Farming

Smart Agriculture Monitoring Solutions to Optimize Farming Productivity

• 6 Cool Examples of Internet of Things Applications and How to Develop One

About the author:

Alexey Shalimov, CEO at Eastern Peak

As CEO at Eastern Peak, a professional software consulting and development company, Alexey ensures top quality and cost-effective services to clients from all over the world. Alexey is also a founder and technology evangelist at several technology companies. Previously, as a CEO of the Gett (GetTaxi) technology company, Alexey was in charge of developing the revolutionary Gett service from ground up and deploying the operation across the globe from New York to London and Tel Aviv.

• The Benefits of smart farming: How’s IoT shaping agriculture

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IEEE/CAA Journal of Automatica Sinica

• JCR Impact Factor: 15.3 , Top 1 (SCI Q1) CiteScore: 23.5 , Top 2% (Q1) Google Scholar h5-index: 77， TOP 5

Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

Doi:  10.1109/jas.2021.1003925.

• Othmane Friha 1 ,  , 
• Mohamed Amine Ferrag 2 ,  , 
• Lei Shu 3, 4 ,  ,  , 
• Leandros Maglaras 5 ,  , 
• Xiaochan Wang 6 , 

Networks and Systems Laboratory, University of Badji Mokhtar-Annaba, Annaba 23000, Algeria

Department of Computer Science, Guelma University, Gulema 24000, Algeria

College of Engineering, Nanjing Agricultural University, Nanjing 210095, China

School of Engineering, University of Lincoln, Lincoln LN67TS, UK

School of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, UK

Department of Electrical Engineering, Nanjing Agricultural University, Nanjing 210095, China

Othmane Friha received the master degree in computer science from Badji Mokhtar-Annaba University, Algeria, in 2018. He is currently working toward the Ph.D. degree in the University of Badji Mokhtar-Annaba, Algeria. His current research interests include network and computer security, internet of things (IoT), and applied cryptography

Mohamed Amine Ferrag received the bachelor degree (June, 2008), master degree (June, 2010), Ph.D. degree (June, 2014), HDR degree (April, 2019) from Badji Mokhtar-Annaba University, Algeria, all in computer science. Since October 2014, he is a Senior Lecturer at the Department of Computer Science, Guelma University, Algeria. Since July 2019, he is a Visiting Senior Researcher, NAULincoln Joint Research Center of Intelligent Engineering, Nanjing Agricultural University. His research interests include wireless network security, network coding security, and applied cryptography. He is featured in Stanford University’s list of the world’s Top 2% Scientists for the year 2019. He has been conducting several research projects with international collaborations on these topics. He has published more than 60 papers in international journals and conferences in the above areas. Some of his research findings are published in top-cited journals, such as the IEEE Communications Surveys and Tutorials , IEEE Internet of Things Journal , IEEE Transactions on Engineering Management , IEEE Access , Journal of Information Security and Applications (Elsevier), Transactions on Emerging Telecommunications Technologies (Wiley), Telecommunication Systems (Springer), International Journal of Communication Systems (Wiley), Sustainable Cities and Society (Elsevier), Security and Communication Networks (Wiley), and Journal of Network and Computer Applications (Elsevier). He has participated in many international conferences worldwide, and has been granted short-term research visitor internships to many renowned universities including, De Montfort University, UK, and Istanbul Technical University, Turkey. He is currently serving on various editorial positions such as Editorial Board Member in Journals (Indexed SCI and Scopus) such as, IET Networks and International Journal of Internet Technology and Secured Transactions (Inderscience Publishers)

Lei Shu (M’07–SM’15) received the B.S. degree in computer science from South Central University for Nationalities in 2002, and the M.S. degree in computer engineering from Kyung Hee University, South Korea, in 2005, and the Ph.D. degree from the Digital Enterprise Research Institute, National University of Ireland, Ireland, in 2010. Until 2012, he was a Specially Assigned Researcher with the Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University, Japan. He is currently a Distinguished Professor with Nanjing Agricultural University and a Lincoln Professor with the University of Lincoln, U.K. He is also the Director of the NAU-Lincoln Joint Research Center of Intelligent Engineering. He has published over 400 papers in related conferences, journals, and books in the areas of sensor networks and internet of things (IoT). His current H-index is 54 and i10-index is 197 in Google Scholar Citation. His current research interests include wireless sensor networks and IoT. He has also served as a TPC Member for more than 150 conferences, such as ICDCS, DCOSS, MASS, ICC, GLOBECOM, ICCCN, WCNC, and ISCC. He was a Recipient of the 2014 Top Level Talents in Sailing Plan of Guangdong Province, China, the 2015 Outstanding Young Professor of Guangdong Province, and the GLOBECOM 2010, ICC 2013, ComManTel 2014, WICON 2016, SigTelCom 2017 Best Paper Awards, the 2017 and 2018 IEEE Systems Journal Best Paper Awards, the 2017 Journal of Network and Computer Applications Best Research Paper Award, and the Outstanding Associate Editor Award of 2017, and the 2018 IEEE ACCESS. He has also served over 50 various Co-Chair for international conferences/workshops, such as IWCMC, ICC, ISCC, ICNC, Chinacom, especially the Symposium Co-Chair for IWCMC 2012, ICC 2012, the General Co-Chair for Chinacom 2014, Qshine 2015, Collaboratecom 2017, DependSys 2018, and SCI 2019, the TPC Chair for InisCom 2015, NCCA 2015, WICON 2016, NCCA 2016, Chinacom 2017, InisCom 2017, WMNC 2017, and NCCA 2018

Leandros Maglaras (SM’15) received the B.Sc. degree from Aristotle University of Thessaloniki, Greece, in 1998, M.Sc. in industrial production and management from University of Thessaly in 2004, and M.Sc. and Ph.D. degrees in electrical & computer engineering from University of Volos in 2008 and 2014, respectively. He is the Head of the National Cyber Security Authority of Greece and a Visiting Lecturer in the School of Computer Science and Informatics at the De Montfort University, U.K. He serves on the Editorial Board of several International peer-reviewed journals such as IEEE Access , Wiley Journal on Security & Communication Networks , EAI Transactions on e-Learning and EAI Transactions on Industrial Networks and Intelligent Systems . He is an author of more than 80 papers in scientific magazines and conferences and is a Senior Member of IEEE. His research interests include wireless sensor networks and vehicular ad hoc networks

Xiaochan Wang is currently a Professor in the Department of Electrical Engineering at Nanjing Agricultural University. His main research fields include intelligent equipment for horticulture and intelligent measurement and control. He is an ASABE Member, and the Vice Director of CSAM (Chinese Society for Agricultural Machinery), and also the Senior Member of Chinese Society of Agricultural Engineering. He was awarded the Second Prize of Science and Technology Invention by the Ministry of Education (2016) and the Advanced Worker for Chinese Society of Agricultural Engineering (2012), and he also gotten the “Blue Project” in Jiangsu province young and middle-aged academic leaders (2010)

• Corresponding author: Lei Shu, e-mail: [email protected]
• Revised Date: 2020-11-25
• Accepted Date: 2020-12-30
• Agricultural internet of things (IoT) , 
• internet of things (IoT) , 
• smart agriculture , 
• smart farming , 
• sustainable agriculture

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The role of smart technology in sustainable agriculture: a case study of wangree plant factory.

1. Introduction

2. literature review, 2.1. smart farming, 2.2. sustainable agriculture and sustainability measurement, 3. material and methods, 3.1. research framework, 3.2. case study overview, 3.3. sustainability measurement model definition.

• Financial criteria relate to increasing revenue, profit, market share, reducing the cost of operation, and unit cost.
• Non-financial criteria relate to improving product quality, crop per year, and reducing harvest time.
• Raw material criteria relate to conserving and enhancing the raw material by efficient use through the reduce, reuse, and recycle concepts; reducing hazardous material usage; and reducing defects and waste generation.
• Natural resource (water, soils, and land use) criteria relate to conserving and enhancing the natural resource base by efficiently using and reducing environmental emission.
• Quality of life criteria relate to assessing and reducing the potential health impacts of new technologies as well as increasing the well-being of stakeholders.
• Human capability criteria relate to encouraging education to improve human skills and knowledge performance.
• Ethics criteria relate to respecting local and international laws on business and human rights and supporting ethical operating practice issues.
• A 50% reduction of infrastructure cost and a 3–5 times reduction of lifetime cultivation system.
• A 80% reduction of fertilization cost because of lower fertilizer consumption achieved through recycling with little drainage of circulating nutrient solution.
• A 30% reduction of unit cost because of lower resource consumption and higher productivity.
• A 33–75% increase of product weight per unit.
• An increase by 1.8–2 times of amount of a crop per year.
• Better product quality grade.
• Both the plant factory and organic cultivation are free-pesticide applications. The plant factory keeps the cultivated area clean and free from pest insects.
• A 99% reduction in water consumption.
• A 99% reduction in land use compared to conventional agriculture due to a higher productivity per production area.
• A 30–50% reduction in plant defects.
• Increasing demands for fresh food, nutritious food, and functional food for health care and higher quality of life because of high controllability of plant environment. Controlled aerial environmental factors include photosynthetic photon flux density (PPFD), air temperature, CO 2 concentration, light quality, and flow rate of the nutrient solution.
• Light and safe work under comfortable air temperature and moderate air movement.

5. Discussion

• Increasing product quality: precision measurement and a suitable plant growth factor adjustment lead to better product quality. It can be seen that the products from the plant factory are higher in weight per unit, and have a better quality grade and a lower percentage of defects.
• Increasing productivity: the production productivity of the plant factory is higher than the conventional cultivation due to the cost reduction from resource use (water and fertilization), the increase of product weight per unit, and the amount of labor reduction.
• Increasing crop per year: the plant factory has an artificial intelligence system completely closed off the outside environment. It replaces sunlight with controllable lighting sources and controls other plant growth factors, such as humidity, carbon dioxide concentration, temperature, and nutrients by using an artificial intelligence system. Consequently, a plant factory can achieve a year-round production environment. The plant factory produces around twice as much crop per year compared to conventional agriculture and reduces harvest time by around 50 percent compared to traditional cultivation.
• Increasing resource use efficiency: the plant factory enhances crop irrigation water productivity due to a water control system that reduces drained water in the growing area and recycles water vapor into liquid water. The vertical farming of the plant factory increases land use efficiency. It provides a 99% reduction in land use.
• Increasing food safety: the plant factory gives priority to keeping the growing area free from pests and pesticides. These hygiene conditions create a ready-to-eat product after harvesting. Moreover, the information technology in the plant factory allows customers and stakeholders in the supply chain to trace operational data from producers.
• Increasing employees’ quality of life: the controllable working environment in the plant factory is much more desirable than field cultivation, which involves the uncertainty of heat and weather. Further, to work with automatic and high technology systems, the plant factory requires highly skilled workers. It encourages employees to improve their skills and knowledge.

6. Conclusions

Author contributions, acknowledgments, conflicts of interest.

• Saunila, M.; Nasiri, M.; Ukko, J.; Rantala, T. Smart technologies and corporate sustainability: The mediation effect of corporate sustainability strategy. Comput. Ind. 2019 , 108 , 178–185. [ Google Scholar ] [ CrossRef ]
• Braun, A.T.; Colangelo, E.; Steckel, T. Farming in the era of industrie 4.0. Procedia CIRP 2018 , 72 , 979–984. [ Google Scholar ] [ CrossRef ]
• Voutos, Y.; Mylonas, P.; Katheniotis, J.; Sofou, A. A survey on intelligent agricultural information handling methodologies. Sustainability 2019 , 11 , 3278. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Kozai, T. Sustainable plant factory: Closed plant production systems with artificial light for high resource use efficiencies and quality produce. Acta Hortic. 2013 , 27–40. [ Google Scholar ] [ CrossRef ]
• Pivoto, D.; Waquil, P.D.; Talamini, E.; Spanhol, C.; Corte, V.F.D.; Mores, G.D.V. Scientific development of smart farming technologies and their application in Brazil. Inf. Process. Agric. 2018 , 5 , 21–32. [ Google Scholar ] [ CrossRef ]
• Ray, P.P. Internet of things for smart agriculture: Technologies, practices and future direction. J. Ambient Intell. Smart Environ. 2017 , 9 , 395–420. [ Google Scholar ] [ CrossRef ]
• FAO. The Future of Food and Agriculture—Trends and Challenges ; FAO: Rome, Italy, 2017; Available online: http://www.fao.org/3/a-i6583e.pdf (accessed on 15 March 2020).
• WCED, S.W.S. World commission on environment and development. Our Common Future 1987 , 17 , 1–91. [ Google Scholar ]
• Senanayake, R. Sustainable agriculture: Definitions and parameters for measurement. J. Sustain. Agric. 1991 , 1 , 7–28. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Elkington, J. Cannibals with Forks: The Triple Bottom Line of 21st Century Business ; Capstone: Oxford, UK, 1999. [ Google Scholar ]
• Santiteerakul, S.; Sekhari, A.; Bouras, A.; Sopadang, A. Sustainability indicators for evaluating sustainable supply chain. In Proceedings of the International Conference on Green and Sustainable Innovation (ICGSI), Chiang Mai, Thailand, 24–26 May 2012. [ Google Scholar ]
• Veleva, V.; Ellenbecker, M. Indicators of sustainable production: Framework and methodology. J. Clean. Prod. 2001 , 9 , 519–549. [ Google Scholar ] [ CrossRef ]
• FAO. Sustainability Assessment of Food and Agriculture Systems (SAFA) ; Natural Resources Management and Environment Department Food and Agriculture Organization of the United Nations: New York, NY, USA, 1998. [ Google Scholar ]
• Jawtrusch, J.; Schader, C.; Stolze, M.; Baumgart, L.; Niggli, U. Sustainability monitoring and assessment routine: Results from pilot applications of the FAO SAFA guidelines. In Proceedings of the International Symposium on Mediterranean Organic Agriculture and Quality Signs Related to the Origin, Agadir, Morocco, 2–4 December 2013. [ Google Scholar ]
• Santiteerakul, S.; Sekhari, A.; Bouras, A.; Sopadang, A. Sustainability performance measurement framework for supply chain management. Int. J. Prod. Dev. 2015 , 20 , 221. [ Google Scholar ] [ CrossRef ]
• Sopadang, A.; Wichaisri, S.; Banomyong, R. Sustainable supply chain performance measurement a case study of the sugar industry. In Proceedings of the International Conference on Industrial Engineering and Operations Management, Rabat, Morocco, 11–13 April 2017. [ Google Scholar ]
• Grenz, J.; Thalmann, C.; Stampfli, A.; Studer, C.; Hani, F. RISE—A method for assessing the sustainability of agricultural production at farm level. Rural Dev. News 2009 , 1 , 5–9. [ Google Scholar ]
• Kamali, F.P.; Borges, J.A.R.; Meuwissen, M.P.; De Boer, I.J.M.; Lansink, A.G.O. Sustainability assessment of agricultural systems: The validity of expert opinion and robustness of a multi-criteria analysis. Agric. Syst. 2017 , 157 , 118–128. [ Google Scholar ] [ CrossRef ]
• Weerapan, T. Performance Measurement of Organic Vegetables in Sustainable Supply Chain Management. Master’s Thesis, Chiang Mai University, Chiang Mai, Thailand, August 2018. [ Google Scholar ]
• Weerapan, T.; Santiteerakul, S. Indicators of performance measurement for agriculture sustainable supply chain. In Proceedings of the International Conference of Simulation and Modeling (SIMMOD), Pattaya, Thailand, 23–25 January 2017; pp. 130–137. [ Google Scholar ]
• Kozai, T.; Niu, G.; Takagaki, M. Plant Factory: An Indoor Vertical Farming System for Efficient Quality Food Production ; Elsevier: San Diego, CA, USA, 2015. [ Google Scholar ]

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Santiteerakul, S.; Sopadang, A.; Yaibuathet Tippayawong, K.; Tamvimol, K. The Role of Smart Technology in Sustainable Agriculture: A Case Study of Wangree Plant Factory. Sustainability 2020 , 12 , 4640. https://doi.org/10.3390/su12114640

Santiteerakul S, Sopadang A, Yaibuathet Tippayawong K, Tamvimol K. The Role of Smart Technology in Sustainable Agriculture: A Case Study of Wangree Plant Factory. Sustainability . 2020; 12(11):4640. https://doi.org/10.3390/su12114640

Santiteerakul, Salinee, Apichat Sopadang, Korrakot Yaibuathet Tippayawong, and Krisana Tamvimol. 2020. "The Role of Smart Technology in Sustainable Agriculture: A Case Study of Wangree Plant Factory" Sustainability 12, no. 11: 4640. https://doi.org/10.3390/su12114640

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Livelihoods Centre

Climate smart agriculture: case studies from around the world. 2021. fao - livelihoods centre, asset publisher.

Climate-smart agriculture (CSA) has grown from a concept into an approach implemented throughout the world, by all types of stakeholders. These case studies discuss context-specific activities that contribute to CSA’s three pillars: sustainably increasing agricultural productivity and incomes, adapting and building resilience of people and agri-food systems to climate change, and reducing and/or removing greenhouse gas emissions where possible. Many of the case studies pay special attention to smallholder farmers, including women and indigenous groups, who are particularly affected by the impacts of climate change.

Climate-smart agriculture (CSA) Case Studies 2021: Projects from around the world

Files: EN |

• Livelihoods Objectives: Productivity Enhancement,
• Cross-cutting themes: climate change, Case studies,
• All: climate change, Case studies,
• Organization: FAO
• Year of publication: 2021
• Web Site: https://www.fao.org
• Url: https://www.fao.org/policy-support/tools-and-publications/resources-details/en/c/1469956/

POLICY AND PRACTICE REVIEWS article

The policy enabling environment for climate smart agriculture: a case study of california.

• 1 Almond Board of California, Modesto, CA, United States
• 2 Department of Environmental Science and Policy, University of California, Davis, Davis, CA, United States

Climate smart agriculture (CSA) provides a framework for balancing multiple dimensions of agriculture and food systems in an era of climate change: addressing agricultural contributions to global greenhouse gas emissions, vulnerabilities to climate change impacts, and the relationship between agricultural productivity, incomes and food security. As the global climate agenda more thoroughly integrates the CSA framework, policy makers often search for “triple wins”—practices that can mitigate emissions, increase resilience or adaptation, and increase productivity. Agriculture and food systems however, are complex systems with many agroecological and sociopolitical interdependencies. In many cases, there are necessary tradeoffs among the three CSA objectives, as advancement in one area may negatively impact another. A major challenge to implementing CSA across multiple geographies thus lies in the coordination of policies and programs that recognize these tradeoffs and allow for prioritization or reconciliation among the three objectives when there are conflicts. This paper describes California's adoption of CSA principles to illustrate how synergies and trade-offs are addressed in a policy framework that spans regulatory measures, incentive programs, research, and technological development, that is both climate specific and arising from other simultaneous environmental and economic priorities. We provide specific examples where agriculture has benefited and where it is constrained due to the balancing of CSA objectives, and discuss how the policy environment has evolved over time in attempts to deal with the complexity of the agriculture-climate nexus. This case serves to summarize and analyze the implemented CSA initiatives in one of most productive and well-resourced agricultural regions of the world; however, lessons learned from California can serve as transferable knowledge for other regions around the globe who are currently developing CSA policies and plans. Our findings suggest that cross-sectoral collaboration, policy coordination, and inclusion of a diverse set of stakeholders are fundamental to the efficacy of CSA strategies in complex and ever-evolving environmental and sociopolitical conditions.

Introduction

As climate change impacts expand in reach and severity, global food systems face risks of reduced agricultural production, market volatility, and threats to rural livelihoods and food security ( Foley et al., 2011 ). The concept of climate-smart agriculture (CSA) has gained international attention from scientists, policy makers, and farmers alike, as a framework for balancing the multiple dimensions of agriculture's intersection with climate change: mitigating agriculture's contribution to global greenhouse gas (GHG) emissions, decreasing agriculture's vulnerability to climate change impacts, and acknowledging the essential link between agricultural productivity and food security ( Lipper et al., 2014 ). A number of international organizations, the Global Alliance for Climate Smart Agriculture, the United Nations Food and Agriculture Organization, and the World Bank among them, have recently devoted significant attention and resources to building tools and providing guidance on the elements of CSA. The recent decision made by the Conference of Parties to the United Nations Framework Convention on Climate Change (UNFCCC) to fully integrate agriculture as part of climate actions, formally recognizes the three components of climate smart agriculture ( United Nations Framework Convention on Climate Change, 2017 ).

The emerging CSA discourse enticingly displays opportunities for “triple wins” through practices that simultaneously mitigate emissions, increase resilience or adaptation, and increase productivity. In reality, many contexts will require necessary trade-offs among these three objectives. Challenge, however, lies in the prioritization or reconciliation among the three objectives and enacting those priorities through policy planning and decisions. Agricultural and food systems are complex, with many inter dependent biophysical and ecological feedback processes, and influenced by the behaviors of human actors and governance systems at multiple scales of interaction ( Levin, 1998 ; Bodin and Crona, 2009 ; Ostrom, 2009 ). These systems are shaped both by their natural and socio-political attributes, which define where, how and what agriculture can take place, as well as how benefits and impacts of the agricultural activities will be distributed among relevant actors in the systems ( Gallopín, 2006 ; Arrow et al., 2014 ). Moreover, the governance within food systems occurs across multiple venues that operate at local, regional, national and global scales, each of which involve different, but often overlapping sets of actors and are seeking to reach different, but often interrelated goals. In the context of climate change, there will often be competing policy goals that seek to optimize either mitigation or adaptation, and we argue that absent of climate change, productivity is nearly always presumed the normative goal. This may set up competition among governing entities to set agendas and attract resources to their priorities, particularly when policy-making occurs across fragmented, task-specific bodies ( Hooghe and Marks, 2003 ). Furthermore, policy-makers are often limited to dealing with only one problem at a time, thus resulting in the lack of a “systems approach” that accounts for the interdependence among the components of the complex agroecosystem. In order to achieve greater success and efficacy of CSA strategies however, we argue that the interdependence and complexity of the nature of these systems must be accounted for to the greatest degree possible, by developing coordinated institutions and adaptable policies that stretch across multiple sectors and biophysical boundaries.

This paper analyzes the development of the CSA policy environment in California. Our objectives are to demonstrate where various elements of CSA policy intersect in complementary or contradictory ways and to evaluate how system complexity challenges the ability to simultaneously reach all three CSA goals in all places. The California state government has demonstrated political leadership and investment in climate action, integrating input from ongoing scientific research and an active and diverse network of bureaucratic, non-governmental and private sector actors who are heavily engaged in the development of CSA policy and practice. This affords a case to examine how the synergies and trade-offs required to implement CSA are addressed through an enabling policy environment that spans regulatory measures, incentive programs, and research that is both climate specific and arising from other environmental and economic priorities.

In the following sections, we lay out the multiple components of CSA in California, though we focus on mitigation and adaptation-oriented initiatives, with the justification that the majority of historic policies and innovations have been driven by goals to optimize productivity. In Case Context: California Agriculture And Climate, we describe California's agricultural sector and climate, demonstrating that the size of the agricultural economy and the State's international engagement on climate change and agricultural innovation make this case relevant and interesting in its ability to inform the actions of other countries. In Climate Mitigation: A Catalyst for CSA, we explain California's bold climate mitigation actions, to join national governments around the world in committing to reduce GHG emissions by 40 percent below 1990 levels by 2030 ( Assembly Bill 32 Overview, 2014 ). It is within this mitigation framework that we show motivation for CSA actions began. Sustainable Water Management: A Cornerstone to California CSA describes how California's Mediterranean climate requires careful management of limited water resources, playing a critical role in the State's CSA adaptation strategies. Throughout these sections, we discuss how the policy framework has evolved and provide specific examples where agriculture has benefited and where it is constrained due to the balancing of CSA objectives and complex system interdependencies. In Role of Research and Technology Development, we discuss the influence of different stakeholders, from a diverse range of agricultural interests to environmental organizations and researchers, on policy development and implementation. Finally, in our Recommendations and Conclusions Sections, we discuss a range of possible solutions that may help to overcome the barriers created by system complexity and better facilitate policy coordination that allows for comprehensive CSA planning.

Case Context: California Agriculture and Climate

The topography and climate of California vary quite dramatically across the state, from temperate rainforest in the north, to arid desert in the south, and a vast Central Valley known for its Mediterranean climate with hot, dry summers and cool, wet winters. In the midst of such wide variation lies the largest agricultural economy in the United States, concentrated primarily in three regions of the state: the Central Valley, the Central Coast, and the South Coast. Most precipitation falls as rain in the northern half of the state and as snow on the Sierra Nevada mountain range, and then is moved across the state through a complex network of federal, state and local water infrastructure. Groundwater reserves are extensive and serve as an increasingly important water source for the state's agricultural operations, particularly during dry years when surface water is limited and environmental and urban needs limit surface water availability to agriculture.

California's agricultural sector spans across nearly 30 million acres of land and was valued at $50 billion in 2017, making it the nation's leading agricultural state in cash receipts and ranked 16th globally for agricultural value ( California Department of Food and Agriculture, 2018 ). The state contributes significantly to the U.S. domestic food supply, growing one-third of vegetables, two-thirds of fruits and nuts, and one-third of dairy consumed in the U.S. While highly ranked both nationally and globally for its productivity, agriculture accounts for only two percent of the state's gross domestic product (GDP) ( California Department of Food Agriculture, 2016 ).

At the same time, agricultural production contributes eight percent (35.3 MMTCO 2 e) of the state's total GHG emissions. Approximately 66 percent of that comes from the livestock sector (e.g., manure management and enteric fermentation), 20 percent from soil and fertilizer management in crop production, and 13 percent from fossil fuel use associated with production (e.g., irrigation pumps, temperature controlled storage, machinery) ( California Air Resources Board, 2017a ). Put in a global context however, California's agricultural emissions are relatively modest. By comparison, France's agricultural economy comprises under two percent of the country's GDP ( DG Agriculture Rural Development- Farm Economics Unit, 2018 ), but emits 94 MMTCO 2 eq, or almost 20 percent of the country's total GHG emissions ( Houllier, 2013 ), nearly three times that of California's sector.

With California's dry climate, fast-growing population, and relatively strong policies to protect ecosystems and the environment, agriculture's competition for water is increasingly strained. Agriculture remains the largest single-sector water user ( Hanak et al., 2016 ), even though California's farms have continually improved in water use efficiency over the past five decades ( Mitchell et al., 2016 ). Relevant to water management, predicted climate changes for the state include warming temperatures- which will increase crop-water demands, earlier snowmelt, increasing frequency and severity of extreme weather events (e.g., storms, floods, droughts), and sea level rise, which may contribute to saltwater intrusion into freshwater resources and salinization of low elevation lands in the Central Valley ( Weare, 2009 ; Marston and Konar, 2017 );( Pathak et al., 2018 ).

Climate models also predict rising average temperatures, which will have multiple negative impacts on agriculture: reduction in winter chill hours that are required by some fruit and nut crops; heat stress on farm workers and livestock; and expansion of pest and weed ranges, along with introduction of new tropical pests. Together with constrained water resources, these climate-induced changes are expected to negatively impact the productivity of both crop and livestock operations. Given California's predominant share of production of a number of agricultural commodities, this has implications for both U.S. and global food systems, challenging the third pillar of CSA, food security ( Jackson et al., 2012 ).

Climate Mitigation: A Catalyst for CSA

Mitigation of GHG emissions is the anchor to California's CSA policy framework and was launched under the 2006 Global Warming Solutions Act (Assembly Bill 32). This law was the first in the U.S. to regulate GHG emissions, setting a reduction target to reach 1990 emissions levels by 2020. Subsequent refinements and extension of this law expanded the target to 40 percent lower than 1990 emission levels by 2030. Recognizing that climate mitigation cuts across many sectors, the law requires collaborative governance that integrates multiple state agencies and non-governmental stakeholders in developing a multi-year “Scoping Plan” (“Assembly Bill 32 Overview,” 2014). This Scoping Plan process provides an institutionalized structure for stakeholder engagement as well as the best attempt to coordinate and negotiate across multiple governmental agencies to address cross-sectoral synergies and trade-offs. A potential critique of many policy coordination efforts is their reliance on the formation of informal institutions that depend on norms of information sharing and collaboration to achieve coordination in their outcomes. This often falls short in overcoming bureaucratic incentives that can drive competition and fragmented policy development ( Ostrom, 2010 ). In the California case, the state legislature mandated the development of the Scoping Plan which would set the approach the state agencies would take to reach the GHG emissions reduction target. This provides a formal process for coordinated policy and program planning, illustrated below in terms of the joint implementation and funding of some CSA incentive programs across agencies. The Plan is required to be updated every 5 years and has been designed as a collaborative process to gather stakeholder input from many diverse sectors at multiple stages throughout the process, again codifying and strengthening the opportunities for collaboration and information sharing as a required piece of the implementation of the Global Warming Solutions Act.

Agricultural production did not originally fall under the regulatory caps of the Global Warming Solutions Act, though food and beverage processing industries did. Instead, the uptake and implementation of on-farm CSA practices are centered around incentive-based voluntary adoption by farmers. Subsequent laws have however directly regulated mitigation of methane emissions from dairy production. The most recent methane law, Senate Bill 1383, requires a 40 percent reduction in methane emissions from dairies by 2030 ( California Air Resources Board, 2018b ). Unlike the Global Warming Solutions Act, this law requires implementation of emission reduction strategies from the dairy industry. This regulatory approach created significant anxiety over the continued economic competitiveness of California diaries given the high costs of mitigation strategies such as dairy digester technologies. To address these potential trade-offs between mitigation and agricultural incomes, the state is attempting to facilitate the transition by providing a significant investment in incentive and cost-share programs and increased research on manure management strategies. The methane law also required the formation of a dairy and livestock working group to engage stakeholders and experts in developing solutions that best accomplish emissions reductions while minimizing economic and social impacts. This working group requirement again demonstrates the state's efforts to apply collaborative governance principles and engage diverse actors in the policy making process to create shared governance solutions, where possible. It is notable that the state incentives directed toward this sector represent a significant portion of the overall public investments in CSA in California, reflecting both the relative contribution of the dairy sector to California's agricultural GHG emissions, its importance as the largest share of agricultural revenue, and its relatively large political influence.

In addition to creating the foundation for bold climate mitigation, the Global Warming Solutions Act was operationalized through the creation of a Cap and Trade market. The sales of carbon credits under this regulated market has generated substantial new public revenue to fund projects that further reduce or sequester carbon, including a number of initiatives within the agricultural sector. To date, approximately $6.1 billion from the Greenhouse Gas Reduction Fund have been allocated by the state legislature to state agencies to operate these programs. Approximately $612 million (~10 percent) of that has been allocated to agriculturally-relevant programs ( California Air Resources Board, 2018a ). These range from grants to upgrade irrigation and water distribution systems, purchasing agricultural land conservation easements, installing dairy digesters and developing alternative manure management strategies, incentivizing on-farm energy improvements and, most recently, designing a healthy soils program; See Table 1 which summarizes these programs ( California Air Resources Board, 2018a ).

Table 1 . Summary of CSA incentive programs.

In order to be eligible to receive Cap and Trade monies, all of these programs must demonstrate GHG emissions reductions. Under the leadership of the California Department of Food and Agriculture (CDFA), and with the engagement and advocacy of non-governmental stakeholders and the agricultural community, many of the programs have been strategically designed to provide co-benefits that increase adaptation and resilience across the agricultural sector; in other words, attempting to bring in the other CSA goals through a mitigation-oriented framework In many cases, this alignment is facilitated by interagency collaboration in the program design. Examples of this can be seen in the State Water Efficiency and Enhancement Program (SWEEP), which funds irrigation infrastructure updates to install more energy and water efficient pumps and distribution systems (e.g., drip irrigation), that both reach mitigation goals by reducing energy usage and adaptation goals by decreasing water demand and evapotranspiration. Correspondingly, SWEEP is a collaborative effort of two state agencies, CDFA and the Department of Water Resources. Additionally, the Healthy Soils Initiative is designed to allow for further synergies across mitigation, adaptation and productivity goals, by supporting soil practices that build soil organic matter (i.e., sequester atmospheric carbon), while simultaneously supporting water and nutrient retention (i.e., adapt to differ water and climate patterns) and having the potential to positively increase crop quality and yields (i.e., support productivity) ( California Climate and Agriculture Network, 2017 ). The Air Resources Board collaborated with CDFA in the design of the Healthy Soils Initiative. The Sustainable Agricultural Lands Conservation (SALC) Program helps to conserve productive agricultural lands from being developed in urban or suburban sprawl, which achieves both mitigation through avoidance of higher average GHG footprints of urban/suburban lands, and helps to ensure sustained food production on productive, fertile lands. SALC is product of an interagency council that explicitly aims to coordinate policies with multi-sector implications and stakeholders. Finally, in addition to the Dairy Digester Research and Development Program which funds installation of manure digesters, the state also developed the Alternative Manure Management Program to provide research and incentive dollars for digester-alternative strategies for dairies, many of which have additional benefits such as building soil health or reducing air and water pollution. The selection and design of these CSA programs was intended to identify and amplify the synergies that do stretch across mitigation-adaptation-productivity goals ( Figure 1 ). However, in the last couple of years, the state legislature has opted to focus Cap and Trade dollar allocations toward programs that have a strict mitigation-only focus (e.g., Dairy Digesters and FARMER program) where regulatory compliance is easier to track and clear GHG reduction benefits are more easily measured, rather than toward the programs that have multiple co-benefits in addition to their mitigation contributions (i.e., reduced funding for Healthy Soils Initiative and SWEEP in 2017 and 2018). In this sense, the rigidity in the funding mechanism that requires a focus on mitigation may serve to constrain and reduce the agricultural sector's ability to implement robust and diverse approaches to CSA that aim to touch all three CSA goals. Furthermore, another large constraining factor is the process of yearly, and oftentimes variable, allocations of the Cap and Trade money by the state legislature. This variability creates instability and uncertainty in the sustainment of many of these CSA initiatives into the future. From a complex governance perspective, this speaks to common challenges: limited attention from policy makers to address one issue at a time, the politics of funding allocations, and the necessity of “bean counting” toward reaching the public policy objective on hand– in this case, GHG emission reductions.

Figure 1 . Timeline of evolution of CSA policy environment. This figure provides a brief timeline enumerating key events in the development of multiple CSA policy initiatives in California. While not comprehensive of all initiatives discussed here, this shows how key events overlapped in time with other policy or environmental phenomena.

Finally, California's Cap and Trade market allows for issuance of agricultural carbon offsets to incentivize reductions in GHGs from changes in crop and livestock management practices. To date, the state has approved only two offset protocols: altered rice production ( California Air Resources Board, 2015 ) and installation of dairy digesters ( California Air Resources Board, 2014 ), with protocols for fertilizer management and conservation of grasslands under discussion. Over 5 million tons of carbon credits have been issued for dairy digesters to date, while crop-based credits have lagged significantly. Determining appropriate baselines, covering registration costs, and documenting and verifying additionality of carbon offsets in highly variable cropping systems can cost up to $20,000 per tCO 2 ( Proville et al., 2018 ). Give the relatively small size of these projects (on average, 0.25 to 2 tons of carbon per acre), they are often not economically viable incentives ( Smith and Parkhurst, 2018 ). Thus, utilization of the rice protocol and development of additional crop protocols has stalled. As land management-based offset protocols become more commonplace, there may be opportunity to streamline the documentation and verification processes, such that costs can be decreased to the point where offsets provide enough of a financial incentive to motivate farm management changes.

Sustainable Water Management: A Cornerstone to California CSA

Perhaps the largest challenge for achieving climate-smart agriculture in California is the interconnectivity between the state's agricultural production and water availability. Agriculture uses on average 80 percent of the surface water dedicated to human use (i.e., municipal and agricultural uses) ( Mount et al., 2015 ) to irrigate an estimated 9 million acres of cropland. During the 2012–2016 severe drought, more than half a million acres under production were fallowed as a result of reduced water allocations (California Department of Water Resources; Howitt et al., 2014 ). Groundwater pumping to meet irrigation demands increased dramatically to compensate for surface water losses, and as a result aquifer levels dropped and salinity became more concentrated ( Howitt et al., 2014 ; Hanak et al., 2016 ; NASA, 2017 ). The drought was costly to the state's agricultural sector, resulting in the loss of an estimated $2.7 billion in revenue in 2015 and an estimate 21,000 jobs, devastating many people's livelihoods that are dependent on agriculture ( Howitt et al., 2014 ). This extreme event may have served as an important catalyst in motivating the state government and agricultural industry to think about and prepare more seriously for the impacts that climate change may have on agricultural production.

Improving agricultural water use efficiency is one strategy for addressing increasingly limited water resources. Water delivery and irrigation systems in California have continually improved in efficiency over the last fifty years, as local irrigation management districts have updated infrastructure, built more flexibility into water delivery schedules and farmers have adopted micro-sprinkler and drip irrigation systems ( Ayars et al., 2015 ; Hanak et al., 2016 ). These efficiencies have led to increased economic productivity per unit of water applied: for example, the average economic productivity of agricultural water in the 1960s was $420 per acre-foot of water. By the 2000s, value had exceeded $700 per acre-foot (DWR Bulletin 160). Of equal note, research has shown that shifting to more efficient irrigation, from flood to subsurface drip systems for example, can significantly reduce soil-based nitrous oxide emissions, resulting in additional climate mitigation benefits ( Kennedy et al., 2013 ).

As discussed briefly above, the SWEEP incentive program was established during the drought of 2012–2016 to assist the agricultural sector in adapting to water supply reductions by funding incentives to upgrade groundwater pumps, install drip or micro-irrigation systems, improve water storage and recycling capacity, install soil moisture monitoring sensors, and increase efficiency in irrigation scheduling. While initially framed as drought relief to the agricultural sector, the SWEEP program has continued under funding from the state's cap and trade revenue. As of 2018, $66 million have been allocated, with an additional $31.5 million in co-financing b y farmers and water districts, to establish projects that cover more than 100,000 acres. These projects are estimated to generate the equivalent GHG savings of removing 15,000 cars off the road and save over 28 billion gallons of water per year. SWEEP is an example of a program aiming to address all three CSA goals and represents coordinated action across agencies with different goals. While mitigating emissions and assisting farmers to adapt to water restrictions, it also helps growers overcome cost-prohibitive up-front capital investments. In addition to SWEEP, CDFA and the Department of Water Resources have also coordinated to build a jointly-funded pilot program that aims to enhance and upgrade water conveyance and delivery systems.

These state-led efforts to increase efficiency at many points throughout the system have not been free of unintended social and environmental costs. The eligibility requirements and resources required for application to these (as well as the other) incentive programs have constrained the participation of smaller and more poorly resourced farmers. In order to achieve substantial water efficiency improvements across the entire agricultural sector, it will be important for programs like SWEEP to reach growers who are slower to adopt new technology or less likely to be involved in traditional incentive program networks facilitated by federal and local conservation extension staff. The 2017 Farmer Equity Act (Assembly Bill 1348) begins to acknowledge this inequity in access to state CSA resources, and address this and other social consequences of the evolving CSA policy framework. The Act acknowledges historical inequities in the agricultural sector, including exclusion from land and water rights and lack of ability to participate in policy processes. Furthermore, the Act acknowledges the concern that disadvantaged farmers that are the least-resourced will be the ones who are most vulnerable to experiencing climate change impacts. Additionally, the 2018 extension of the Cannella Environmental Farming Act (Assembly Bill 2377) requires that a portion of the SWEEP budget, as well as that of the Healthy Soils Program and Alternative Manure Management Program, be spent on technical assistance programs that serve small and mid-sized farms, as well as socially disadvantaged farmers and ranchers. These are important steps in California's development of CSA policy as it represents an acknowledgment of the interconnectedness between social, political and economic systems at play that directly affect farmers' abilities to participate and benefit from state-funded CSA efforts.

In addition to social impacts, the adoption of drip irrigation systems have had complex environmental impacts. Conversion to drip irrigation has clear GHG reduction benefits due to energy-savings and water efficiency benefits, but this efficiency simultaneously reduces rates of natural groundwater recharge that occurs from field level inefficiencies and reduces return flows available for downstream users. Reduced groundwater recharge, combined with an increased reliance on groundwater for irrigation during dry years and a hardened annual water demand due to the increase of perennial tree crops, has resulted in unprecedented rates of groundwater withdrawal, aquifer storage reduction and subsidence of the land's surface ( Hanak and Lund, 2015 ). Rebalancing water resources will require significant attention dedicated to intentional groundwater recharge.

This efficiency-depletion trade-off became starkly clear during the 2012–2016 2011–2015 drought when both irrigation and drinking water wells across the state ran dry from over-pumping. In response in 2014, the Sustainable Groundwater Management Act (SGMA) was passed by the California Legislature with broad stakeholder support, as a regulatory effort to require groundwater basin sustainability planning and replenishment of over-extracted groundwater basins by 2050. In addition to being a significant step toward sustainable water reform, SGMA also has significant impact on the development of CSA in California. The law adopts a local governance structure allowing local and regional stakeholders in each groundwater basin to form new decision-making entities who will prepare and implement groundwater sustainability plans. These sustainability plans must define which strategies will be used to restore aquifer levels to a state-determined sustainable level, potentially including water pumping limitations or pumping permit trading markets ( Kiparsky et al., 2017 ). Agricultural stakeholders across the state are participating as key players shaping these plans and advocating to ensure that agricultural water needs are heard ( Niles and Wagner, 2017 ). Farms of all scales will eventually be required to adapt to meet the locally determined sustainability plans, which may impose higher pumping operational and monitoring costs, or may assign a pricing structure to water altogether. The net impact may constrain crop acreage and crop type across the state in a dramatic way, as well as impact small-scale or socially-disadvantaged farmers who don't have access to the same financial and political resources to be able to compete in new water markets ( Rudnick et al., 2016 ). In this case, SGMA requires a tradeoff between CSA goals of agricultural productivity in the short term, by limiting water access, and longer term adaptation, by sustaining water resources.

State water quality regulations may also provide an indirect but strong CSA driver by requiring improved nitrogen fertilizer management. In 2003, the state implemented the Irrigated Lands Regulatory Program, which placed pollution limits on agricultural runoff carrying excess nutrient loads to surface water. In 2012, protections were extended to incorporate groundwater concerns from nitrogen leaching (Central Valley Regional Board). A co-benefit of addressing water contamination will likely be mitigation of nitrous oxide emissions, from reduced denitrification of excess fertilizer. Research shows that high levels of nitrates contaminate groundwater basins in agriculturally intensive regions across the state ( Harter et al., 2012 , 2016 ), threatening access to clean drinking water and thus the health of the communities that live and work in these regions– particularly the socially and economically disadvantaged communities who are dependent on groundwater for their drinking water ( Balazs et al., 2011 ). The relationship between groundwater quality and groundwater quantity are evermore necessary to understand as SGMA will motivate and in many regions incentivize managed aquifer recharge projects. These projects must be carefully designed and monitored, especially when occurring on historically cultivated or fallowed agricultural lands that have the potential to leach nitrogen fertilizers (or legacy fertilizers that have already built up in the soil profile), or where they may occur in close proximity to groundwater-dependent drinking water systems. All of these interactions cut across climate, water quality, water quantity, and environmental justice issues, demonstrating the necessity to understand linkages and interdependencies in both the biophysical and socio-political aspects of the complex system in which CSA is being implemented, in order to promote just and equitable CSA transformations.

In summary, California's agricultural sector has benefited from multiple incentive programs related to water adaptations in the short term; however, policies such as SGMA and the Irrigated Lands Regulatory Program, aimed at longer-term sustainable management of water resources, combined with climate predictions, will likely require trade-offs between productivity and profitability of California's agricultural lands, and the move toward a sustainable and equitable water supply. Constraints may include reductions in total crop acreage across the state and changes in the types or distribution of crops that are produced. In turn, these changes could have implications for both national and international food markets due to California's significant production of a number of food commodities. At the same time, the resilience of the agricultural industry itself is dependent upon sustainable water management. Moreover, the resilience and health of the other water users in agricultural regions is essential to maintaining health and equity for communities who both serve and are dependent on this food system. As a result of climate change, California and other dry climates around the world may continue to experience high variability in annual precipitation patterns and may be forced to decrease their reliance on historically-timed snowmelt for surface water and groundwater recharge. Thus, policies that promote long-term resource planning and sustainable use of essential freshwater resources are pertinent to the continued success of agricultural operations in these climates. These adaptations will require consideration of the complex interactions that occur across overlapping social and environmental issues, some of which we have identified here.

Role of Research and Technology Development

California has a well-established public research system comprised of universities, experiment stations, and federal agriculture research facilities to address the productivity of crop and livestock production. From a climate perspective, while globally representative of Mediterranean climates, the agriculture in California is distinct within the U.S. Both the crops and climatic conditions differ substantially from annual grain crops which dominate the rest of U.S. agricultural acreage. Given these differences, state agencies could not rely on research conducted in other U.S. regions to determine what practices mitigate emissions or promote adaptation under California's unique conditions. To ensure continued productivity in the face of climate change, CDFA convened the Climate Change Consortium for Specialty Crops in 2011 ( California Department of Food and Agriculture, 2018 ). The findings of this consortium highlighted the productivity challenges due to changing temperatures, pest pressures, and water availability. Execution of CSA research and programs targeted these subnational priorities, while also leveraging national funding and technical tools where possible, thus expanding the scope of research beyond state funding alone. In addition, CDFA has invested resources in building collaborations with other countries around the world that have similar Mediterranean climates and grow similar crops, including Israel, Australia and Chile, to name a few. The cross-national collaborations encouraged information and technology sharing between government entities, research scientists, private enterprises and producers in both countries, as well as shared learning efforts to jointly tackle questions about the agricultural impacts of future climate conditions ( California Department of Food and Agriculture, 2018 ).

The state's strong policy emphasis on reduction of GHG emissions has led to more extensive study of the climate mitigation and sequestration potential in California's cropping and livestock systems, than in many other regions across the U.S. Since passage of AB32, more than 50 research studies have been conducted in California to identify and quantify mitigation practices and identify co-benefits for adaptation or other environmental services ( Byrnes et al., 2017 ). Similar to the interagency nature of California's CSA policy environment, mitigation research was funded by several agencies, including the Department of Energy and the California Air Resources Board, in addition to the Department of Food and Agriculture. The findings of some of these studies, such as long-term research on the impact of conservation tillage on GHG emissions, reveal important differences between California and other regions, which must be accounted for before exporting California-designed CSA approaches to other regions ( Six et al., 2004 ). This underlines the need for research and comparative studies to fine-tune CSA solutions that are context-specific and acknowledge the differences across agroecosystems. CSA efforts should not assume a “one size fits all” mentality across variable cropping systems and climates. Similarly, as water figures more prominently in CSA for California and other dry agricultural regions, research and technological innovations in water management practices are central to meeting CSA goals. This includes research and technology development on efficient irrigation technology, groundwater aquifer recharge on agricultural lands, and improved water filtration through soil and vegetative strips are central to meeting CSA goals ( Byrnes et al., 2017 ; Wolf et al., 2017 ; Dahlke et al., 2018 ).

Lastly, with over $6.5 billion in private investment from 2014–2017 in precision farming tools ( Zuckerberg and Kennes, 2017 ), commercial agricultural technology promises to contribute to CSA, through optimizing nutrient management, improving efficient water use management, and developing new digester technologies to reduce methane emissions from livestock waste ( Balafoutis et al., 2017 ). With water, fertilizer leaching, and dairy emissions coming under regulation in California, farmers may turn to technological solutions to meet their regulatory requirements and to keep production competitive in global markets. Evidence of the important role of technology in meeting the challenge of regulatory, climate, and market challenges is seen in the recent investments by some grower organizations and food companies in new agtech start-ups (e.g., https://agfundernews.com/western-growers-launches-4m-agtech-fund.html , https://www.thepacker.com/article/taylor-farms-joins-startup-accelerator-advance-ag-tech ).

Summary of CSA in California and Actionable Recommendations

While California represents a subnational case for CSA, the size and scope of the state's agricultural sector and the challenges its agriculture faces from climate change are globally relevant. The agricultural sector plays a significant role in supplying both domestic and global commodity markets, yet contributes a relatively small proportion of both the state's total economic activity and GHG emissions.

As we have summarized, California's bold commitment to GHG emissions reductions in the coming decades has provided the catalyst to spur much of the public investment in CSA. The resulting publicly funded incentive programs have both promoted voluntary adoption of climate-friendly farming practices and have acted to balance the negative economic impacts of increased regulation of the agricultural sector. From a political angle, these incentive dollars may have also contributed to earning greater political support from agricultural organizations for climate change action. While every CSA program funded by Cap and Trade revenue must demonstrate emission reductions or carbon offsets, some such as SWEEP, Healthy Soils, and the dairy programs also have co-benefits for adaptation or address trade-offs for the economic productivity goals of CSA. There is a growing body of literature on farmer behavior toward climate change that would support these types of multi-benefit programs. A number of studies have shown that there is less support from farmers for mitigation-only actions: the sense of climate impact risk is low, while the benefits of mitigation actions are uncertain and accrue globally, rather than locally ( Arbuckle et al., 2015 ; Prokopy et al., 2015 ). We anticipate that California's investment in these programs that incentivize practices that also have multiple co-benefits will increase farmer buy-in and participation overall. However, the most recent Cap and Trade funding allocations, demonstrate that short-term funding cycles and inconsistency in funding from year to year can decrease these co-benefits that may take many years of practice implementation to accrue.

In addition to the climate mitigation framework, California's state government and key stakeholder groups, have built a stronger focus around the water impacts that are expected to present the greatest climate challenge to the agricultural sector. This is significant, as water management is seldom the focus of global CSA agendas. Yet, improved irrigation and water management are critical agricultural adaptations in the context of less predictable precipitation patterns associated with climate projections for many agricultural regions ( Bradshaw et al., 2004 ; Pathak et al., 2018 ). As the World Bank noted, water scarcity exacerbated by climate change could reduce economic growth rates by up to six percent in countries in Africa and South Asia, where agriculture remains a significant economic driver ( World Bank, 2016 ). From a productivity and food security lens, the third pillar of CSA, irrigated farms are twice as productive as rainfed systems on average across the globe ( Rockström et al., 2009 ). Water management strategies like deficit irrigation may provide a rare “triple wins” opportunity in this realm, by reducing water use (adaptation) and subsequently reducing energy demand embedded in irrigation (GHG mitigation), while sustaining high crop yields (productivity). Studies in multiple cropping systems in California show that regulated deficit irrigation can be used to reduce water consumption by 20 percent or more without significant decreases in productivity ( Johnstone et al., 2005 ; Goldhamer et al., 2006 ). Thus, diffusion of conservation irrigation strategies and water storage technologies that enhance efficiency, build drought resilience by sustaining irrigation capacity through dry periods, and sustain crop yields will be important tools to address the productivity and adaptation pillars of CSA, with potential for mitigation benefits as well, as demonstrated with the deficit irrigation example. Technological solutions do not come without costs, however, and thus should be implemented with care. As discussed in California for example, increased efficiency from drip irrigation technologies contributed to decreased groundwater recharge rates, while simultaneously facilitating a hardened water demand by permitting densely-planted perennial tree crops that increased annual water budgets, resulting in severe depletion of groundwater reserves. As this case study demonstrates, it is thus necessary for technological advancements to occur in coincidence with considerations of the complex resource governance structures in place and considerations of how new practices will affect the interconnected resource system. Tackling sustainable water management through both improvements in agricultural water efficiency and basin scale sustainable management policies will be critical to achieving CSA both in California, and in many other drought-vulnerable climates worldwide.

Finally, California's 2012–2016 drought may have heightened the perceptions of climate risks by the agricultural sector. While the drought impacts were severe and costly to many, “focusing events” like this drought, can draw in attention and support from a wide range of stakeholders to advance the development of CSA strategies. This focused attention contributes to building a toolbox of new solutions that can be implemented to help the sector respond to changing climate conditions. In California, these collaborative efforts to develop CSA strategies that stretch across sectors can be seen in the research efforts funded by multiple state agencies, as well as private industry and non-governmental actors, the integrative incentive programs that achieve multiple mitigation, adaptation and productivity benefits, and the important regulatory measures that have gained support from diverse interest groups. Expanding the network of stakeholders that are involved in and support CSA approaches is an important component for increasing CSA-practice adoption rates. For CSA strategies to effectively achieve large-scale transformation, practices will need to be widely adopted by individual farmers; thus understanding which stakeholders are most influential in farmer behavior and ensuring they are included in CSA discussions will be an important step in broadening the reach of these initiatives.

To remain a global agricultural leader, California agriculture will have to continue adapting to changing climate conditions, resource availability and competitive global markets. Climate smart agriculture itself offers a globally-recognizable framework to demonstrate how agriculture and climate intersect and suggest how agriculture can contribute to mitigation, adaptation, and productivity goals going forward. California plays an important role in these global CSA discussions, as it is a major producer of hundreds of specialty crops, exemplifies the dry climate conditions that typify numerous agricultural regions around the world, and houses major research and technology innovation sectors that support the development of many innovative CSA solutions.

The political economy of California agriculture also illustrates global trends that will impact CSA policy. While the state ranks as an agricultural powerhouse, agriculture is a declining percent of the state economy and a declining percent of the labor force. As the state's economy and population grow and diversify outside of agriculture, public policy goals have also changed and political attention has been directed toward non-farm priorities, including environmental health and social and environmental justice. Similar trends toward declining shares of agriculture in economies and labor forces are occurring globally, as countries transition from developing to middle and high income economies, and mechanization becomes more widespread in agricultural production systems ( World Bank, 2007 ).

The specific means by which various agricultural players will contribute to meeting CSA goals both within and outside of California will likely change over time, and thus programs that promote specific farming practices or resource governance approaches should be designed to be adaptable and allow for policy learning. We intend for this case study on the development of California's CSA initiatives to provide a perspective on how multiple actors have coordinated in one system to develop integrative mitigation and adaptation initiatives that are appropriate for multiple cropping systems in various biophysical conditions across the state. We anticipate that as both social and environmental conditions change in California, these initiatives will need to adapt to maintain relevancy. We also discuss where there have been overlapping or conflicting goals that have had to be reconciled, or have led to unintended and undesirable consequences. The triple wins narrative frequently posited with CSA programs is not always possible to achieve. Indeed, as our case study shows, there are in fact very few examples of policies or initiatives that achieve all three CSA pillars through a single effort. Rather, we believe it is more likely that these three simultaneous goals will likely be met via disparate efforts, increasing the likelihood that tradeoff decisions may need to be faced. As CSA initiatives develop in other locations, we emphasize the importance of taking an integrative systems approach to understanding how various components of climate and agriculture intersect and considering carefully how to reconcile these conflicting interests. Finally, an important direction moving forward will be to consider how CSA initiatives integrate with aspects of the cultural and social institutions that operate in different contexts and shape what type of agriculture is conducted, who participates in agriculture, and what agricultural outputs are produced. This integration will be crucial for CSA-oriented initiatives to pose solutions that recognize the needs, wants and capacities of the communities dependent on the very agricultural systems that are under consideration.

Author Contributions

JL initiated case study in coincidence with participation in the Global Alliance for Climate Smart Agriculture. Both JL and JR conducted review of relevant state policies and programs and wrote and edited manuscript text.

This project was supported by the World Food Center at the University of California Davis.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank Jeanne Merril at CalCAN, Amrith Gunasekara and Jenny Lester-Moffit at CDFA, Robert Parkhurst at the Environmental Defense Fund, and Mark Lubell at University of California Davis for their thoughtful and insightful feedback through the development of this project.

Arbuckle, J. G., Morton, L. W., and Hobbs, J. (2015). Understanding farmer perspectives on climate change adaptation and mitigation. Environ. Behav. 47, 205–234. doi: 10.1177/0013916513503832.

PubMed Abstract | CrossRef Full Text | Google Scholar

Arrow, K. J., Ehrlich, P. R., and Levin, S. A. (2014). “Some perspectives on linked ecosystems and socioeconomic systems,” in Enviornment and Development Economics: Essays in Honor of Sir Partha Dasgumpta , eds S. Barrett, K.-G. Maler, and E. Maskin (Oxford: Oxford University Press), 301–315.

Assembly Bill 32 Overview (2014). Retrieved from https://www.arb.ca.gov/cc/ab32/ab32.htm (accessed October 31, 2018).

Ayars, J. E., Fulton, A., and Taylor, B. (2015). Subsurface drip irrigation in California-Here to stay? Agric. Water Manage. 157, 39–47. doi: 10.1016/j.agwat.2015.01.001

CrossRef Full Text | Google Scholar

Balafoutis, A., Beck, B., Fountas, S., Vangeyte, J., van der Wal, T., Soto, I., et al. (2017). Precision agriculture technologies positively contributing to GHG emissions mitigation, farm productivity and economics. Sustainability 9:1339. doi: 10.3390/su9081339

Balazs, C., Morello-Frosch, R., Hubbard, A., and Ray, I. (2011). Social disparities in nitrate contaminated drinking water in California's San Joaquin Valley. Environ. Health Perspect. 119, 1272–1278. doi: 10.1289/ehp.1002878

Bodin, Ö., and Crona, B. I. (2009). The role of social networks in natural resource governance: what relational patterns make a difference? Glob. Environ. Change 19, 366–374. doi: 10.1016/j.gloenvcha.2009.05.002

Bradshaw, B. E. N., Dolan, H., and Smit, B. (2004). Farm-level adaptation to climatic variability and change: crop diversification in the Canadian prairies. Clim. Change 61, 119–141. doi: 10.1007/s10584-004-0710-z

Byrnes, R., Eviner, V., Kebreab, E., Horwath, W. R., Jackson, L., Jenkins, B. M., et al. (2017). Review of research to inform California's climate scoping plan: agriculture and working lands. Calif. Agric. 71, 160–168. doi: 10.3733/ca.2017a0031

California Air Resources Board (2014). Compliance Offset Protocol Livestock Projects: Capturing and Destroying Methane from Manure Management Systems. Sacramento, CA: California Air Resources Board.

California Air Resources Board (2015). Compliance Offset Protocol Rice Cultivation Projects. California Air Resources Board.

California Air Resources Board (2017a). California Greenhouse Gas Emission Inventory- 2017 Edition. California Air Resources Board.

California Air Resources Board (2017b). California Climate Investments 2018 Annual Report. Available online at: http://caclimateinvestments.ca.gov (accessed October 31, 2018).

California Air Resources Board (2018a). California Climate Investments: Appropriations from the Greenhouse Gas Reduction Fund. California Climate Investments Program 31 August 2018. Available online at: https://www.arb.ca.gov/cc/capandtrade/auctionproceeds/summary_appropriation_table_8_31_18.pdf (accessed October 31, 2018).

California Air Resources Board (2018b). Reducing Short Lived Climate Pollutants.

Google Scholar

California Climate Agriculture Network (2017). Overview of Climate Smart Agriculture. Retrieved from http://calclimateag.org/climatesmartag/ (accessed October 31, 2018).

California Department of Food and Agriculture (2018). California Agricultural Statistics Review 2017–2018. Sacramento, CA: California Department of Food and Agriculture.

California Department of Food and Agriculture. (2016). California Agricultural Statistics Review 2015–2016. Sacramento, CA.

California Department of Water Resources. “Drought.” Water Basics. Available online at: http://www.water.ca.gov/Water-Basics/Drought (accessed January 20, 2019).

Dahlke, H. E., LaHue, G. T., Mautner, M. R., Murphy, N. P., Patterson, N. K., Waterhouse, H., et al. (2018). “Managed aquifer recharge as a tool to enhance sustainable groundwater management in California: examples from field and modeling studies,” in Advances in Chemical Pollution, Environmental Management and Protection , Vol. 3 (Elsevier), 215–275. doi: 10.1016/bs.apmp.2018.07.003

DG Agriculture and Rural Development- Farm Economics Unit (2018). European Commission Statistical Fact. Brussel: European Commission; Directorate General for Agriculture and Rural Development.

Foley, J. A., Ramankutty, N., Brauman, K. A., Cassidy, E. S., Gerber, J. S., Johnston, M., et al. (2011). Solutions for a cultivated planet. Nature 478, 337–342. doi: 10.1038/nature10452.

Gallopín, G. C. (2006). Linkages between vulnerability, resilience, and adaptive capacity. Glob. Environ. Change 16, 293–303. doi: 10.1016/j.gloenvcha.2006.02.004

Goldhamer, D. A., Viveros, M., and Salinas, M. (2006). Regulated deficit irrigation in almonds: effects of variations in applied water and stress timing on yield and yield components. Irrigat. Sci. 24, 101–114. doi: 10.1007/s00271-005-0014-8

Hanak, E., Escriva-Bou, A., Howitt, R., Lund, J., Burt, C., Harter, T., et al. (2016). California Water: Water for Farms. San Francisco, CA: Public Policy Institute of California.

Hanak, E., and Lund, J. (2015). Water for Farms. Sacramento, CA: Public Policy Institute of California; Water Policy Center.

Harter, T., Dzurella, K., Kourakos, G., Bell, A., King, A., and Hollander, A. (2016). Nitrogen Fertilizer Loading to Groundwater in the Central Valley.

Harter, T., Lund, J. R., Darby, J., Fogg, G., Howitt, R., Jessoe, K., et al. (2012). Addressing Nitrate in California's Drinking Water: With a Focus on Tulare Lake Basin and Salinas Valley Groundwater. Report for the California State Water Resources Control Board Report to the Legislature. California Nitrate Project, Implementation of Senate Bill X2 1, Center forWatershed Sciences, University of California, Davis. Available online at: http://groundwaternitrate.ucdavis.edu/

Hooghe, L., and Marks, G. (2003). Unraveling the central state, but how? Types of multi-level governance. Am. Polit. Sci. Rev. 97, 233–243. doi: 10.1017/S0003055403000649

Houllier, F. (2013). INRA Science and Impact Annual Report. Paris.

Howitt, R., Medellín-Azuara, J., MacEwan, D., Lund, J. R., and Sumner, D. (2014). Economic Analysis of the 2014 Drought for California Agriculture. Davis, CA: University of California; Center for Watershed Sciences.

Jackson, L., Haden, V. R., Wheeler, S., Hollander, A., Pearlman, J., O'Geen, T., et al. (2012). Vulnerability and Adaptation to Climate Change in California Agriculture. Whitepaper commissioned for California Energy Commission: CEC-500-2012-031. Davis, CA: University of California.

Johnstone, P. R., Hartz, T. K., LeStrange, M., Nunez, J. J., and Miyao, E. M. (2005). Managing fruit soluble solids with late-season deficit irrigation in drip-irrigated processing tomato production. HortScience 40, 1857–1861. doi: 10.21273/HORTSCI.40.6.1857

Kennedy, T. L., Suddick, E. C., and Six, J. (2013). Reduced nitrous oxide emissions and increased yields in California tomato cropping systems under drip irrigation and fertigation. Agric. Ecosyst. Environ. 170, 16–27. doi: 10.1016/j.agee.2013.02.002

Kiparsky, M., Milman, A., Owen, D., and Fisher, A. (2017). The importance of institutional design for distributed local-level governance of groundwater: the case of California's sustainable groundwater management act. Water 9:755. doi: 10.3390/w9100755

Levin, S. A. (1998). Ecosystems and the biosphere as complex adaptive systems. Ecosystems 1, 431–436.

Lipper, L., Thornton, P., Campbell, B. M., Baedeker, T., Braimoh, A., Bwalya, M., et al. (2014). Climate-smart agriculture for food security. Nat. Clim. Chang. 4, 1068–1072. doi: 10.1038/nclimate2437

Marston, L., and Konar, M. (2017). Drought impacts to water footprints and virtual water transfers of the Central Valley of California. Water Resour. Res. 53, 5756–5773. doi: 10.1002/2016WR020251

Mitchell, J. P., Shrestha, A., Hollingsworth, J., Munk, D., Hembree, K. J., and Turini, T. A. (2016). Precision overhead irrigation is suitable for several Central Valley crops. Calif. Agric. 70, 62–70. doi: 10.3733/ca.v070n02p62

Mount, J., Hanak, E., Chappelle, C., Gray, B., Lund, J., Moyle, P., et al. (2015). Policy Priorities for Managing Drought , 1–10. Sacramento, CA: The Public Policy Institute of California.

NASA (2017). California's San Joaquin Valley is still sinking. Earth Obs. 29, 41–44. Available online at: https://visibleearth.nasa.gov/view.php?id=89761 (accessed October 31, 2018).

Niles, M., and Wagner, C. (2017). Farmers share their perspectives on California water management and the Sustainable Groundwater Management Act. Calif. Agric. 72, 38–43. doi: 10.3733/ca.2017a0040

Ostrom, E. (2009). A general framework for analyzing sustainability of social-ecological systems. Science 325, 419–422. doi: 10.1126/science.1172133

Ostrom, E. (2010). Beyond markets and states: polycentric governance of complex economic systems. Am. Econ. Rev. 100, 641–672. doi: 10.1257/aer.100.3.641

Pathak, T., Maskey, M., Dahlberg, J., Kearns, F., Bali, K., and Zaccaria, D. (2018). Climate change trends and impacts on California agriculture: a detailed review. Agronomy 8:25. doi: 10.3390/agronomy8030025

Prokopy, L. S., Arbuckle, J. G., Barnes, A. P., Haden, V. R., Hogan, A., Niles, M. T., et al. (2015). Farmers and climate change: a cross-national comparison of beliefs and risk perceptions in high-income countries. Environ. Manage. 56, 492–504. doi: 10.1007/s00267-015-0504-2

Proville, J., Parkhurst, R., Koller, S., Kroopf, S., Baker, J., and Salas, W. A. (2018). Agricultural offset potential in the United States: economic and geospatial insights. SocArXiv doi: 10.31235/osf.io/zea8g

Rockström, J., Falkenmark, M., Karlberg, L., Hoff, H., Rost, S., and Gerten, D. (2009). Future water availability for global food production: the potential of green water for increasing resilience to global change. Water Resour. Res. 45. doi: 10.1029/2007WR006767

Rudnick, J., DeVincentis, A., and Méndez-Barrientos, L. (2016). The Sustainable Groundwater Management Act challenges the diversity of California farms. Calif. Agric. 70, 169–173. doi: 10.3733/ca.2016a0015

Six, J., Bossuyt, H., Degryze, S., and Denef, K. (2004). A history of research on the link between (micro) aggregates, soil biota, and soil organic matter dynamics. Soil Till. Res. 79, 7–31. doi: 10.1016/j.still.2004.03.008

Smith, J., and Parkhurst, R. (2018) Opportunities for agricultural producers to participate in compliance voluntary carbon markets. SocArXiv doi: 10.31235/osf.io/yrfgz

United Nations Framework Convention on Climate Change (2017). Issues Relating to Agriculture , Bonn: FCCC/SBSTA.

Weare, B. C. (2009). How will changes in global climate influence California? Calif. Agric. 63, 1–9. doi: 10.3733/ca.v063n02p59

Wolf, K., Herrera, I., Tomich, T., and Scow, K. (2017). Long-term agricultural experiments inform the development of climate-smart agricultural practices. Calif. Agric. 71, 120–124. doi: 10.3733/ca.2017a0022

World Bank (2007). World Development Report 2008: Agriculture for Development. Washington, DC: World Bank. Available online at: https://openknowledge.worldbank.org/handle/10986/5990

World Bank (2016). High and Dry: Climate Change, Water, and the Economy. Washington, DC: World Bank.

Zuckerberg, K., and Kennes, D. J. (2017). Bungle in the Ag Tech Jungle. Utrecht: Rabobank.

Keywords: climate smart agriculture, policy tools, enabling environment, synergies, tradeoffs

Citation: Lewis J and Rudnick J (2019) The Policy Enabling Environment for Climate Smart Agriculture: A Case Study of California. Front. Sustain. Food Syst. 3:31. doi: 10.3389/fsufs.2019.00031

Received: 01 November 2018; Accepted: 16 April 2019; Published: 08 May 2019.

Reviewed by:

Copyright © 2019 Lewis and Rudnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jessica Rudnick, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• Understanding Poverty

Climate-smart agriculture

Climate-smart agriculture (csa) is an integrated approach to managing landscapes—cropland, livestock, forests and fisheries--that address the interlinked challenges of food security and climate change..

Climate change and food and nutrition insecurity pose two of the greatest development challenges of our time. Yet a more sustainable food system can not only heal the planet, but ensure food security for all.

Today, the global agrifood system emits  one-third  of all emissions. Global food demand is estimated to increase to feed a projected global population of 9.7 billion people by 2050. Traditionally, the increase in food production has been linked to agricultural expansion, and unsustainable use of land and resources. This creates a vicious circle, leading to an increase in emissions. 

Food systems are the leading source of methane emissions and biodiversity loss, and they use around 70% of fresh water. If food waste were a country, it would be the third highest emitter in the world. Meanwhile, emissions from agriculture are increasing in developing countries – a worrying trend which must be reversed.

Without significant climate mitigation action in the agri-food sector, the Paris Agreement goals cannot be reached. Agriculture is the primary cause of deforestation, threatening pristine ecosystems such as the Amazon and the Congo Basin. Without action, emissions from food systems will rise even further, with increasing food production.

Achieving the Triple Win of CSA

The global agrifood system must therefore deliver on multiple fronts. It must feed the world, adapt to climate change, and drastically reduce its greenhouse gas emissions. In response to these challenges, the concept of Climate-smart Agriculture (CSA) has emerged as a holistic approach to end food security and promote sustainable development while addressing climate change issues.

CSA is a set of agricultural practices and technologies which simultaneously boost productivity, enhance resilience and reduce GHG emissions. Although it is built on existing agricultural knowledge, technologies, and sustainability principles, CSA is distinct in several ways. First, it has an explicit focus on addressing climate change in the agrifood system. Second, CSA systematically considers the synergies and tradeoffs that exist between productivity, adaptation, and mitigation. And third, CSA encompasses a range of practices and technologies that are tailored to specific agro-ecological conditions and socio-economic contexts including the adoption of climate-resilient crop varieties, conservation agriculture techniques, agroforestry, precision farming, water management strategies, and improved livestock management. By implementing these practices, triple win results can be achieved:

1.     Increased productivity:  Produce more and higher quality food without putting an additional strain on natural resources, to improve nutrition security and boost incomes, especially for 75 percent of the world’s poor who live in rural areas and mainly rely on agriculture for their livelihoods.

2.     Enhanced resilience:  Reduce vulnerability to droughts, pests, diseases and other climate-related risks and shocks; and improve the capacity to adapt and grow in the face of longer-term stresses like increased seasonal variability and more erratic weather patterns.

3.     Reduced emissions:  Reduce greenhouse gas emissions of the food system, avoid deforestation due to cropland expansion, and increase the carbon sequestration of plants and soils.

Finally, funding for CSA needs to be increased to align available finance with the relevance of the sector. Despite causing one third of global greenhouse gas emissions, agrifood systems receive 4% of climate finance, with only a fifth of this going to smallholders. Current financial flows need to be realigned in order to support a sustainable agrifood system transformation.

Climate-Smart Agriculture and the World Bank Group

The World Bank has significantly scaled up its engagement and investment in climate-smart agriculture (CSA). In its Climate Change Action Plan (2021- 2025), the World Bank has identified Agriculture, Food, Water and Land as one of the five key transitions  needed to tackle the Paris Agreement. Since the adoption of the Paris Agreement, the World Bank has increased financing for CSA by eight times, to almost $3 billion annually.

As of July 2023, all new World Bank operations must be aligned with the goals of the Paris Agreement , meaning that CSA is at the core of all the World Bank’s new agriculture and food operations. To this end, the World Bank has prepared a Sector Note of Paris Alignment of its Agriculture and Food operations. Furthermore, all projects are screened for climate and disaster risks. Climate change indicators are used to measure outputs and outcomes, and greenhouse gas accounting of projects is conducted prior to approval . These actions will help client countries implement their Nationally Determined Contributions (NDCs) in the agriculture sector, and will contribute to progress on the  Sustainable Development Goals  (SDGs) for climate action, poverty, and the eradication of hunger.

The World Bank engages strategically with countries, supporting them to enhance productivity, improve resilience and reduce greenhouse gas emissions. The World Bank uses the following tools, diagnostics and other analytics to help countries in the transition towards sustainable agriculture.

• Country Climate and Development Reports (CCDRs), new core diagnostics, help countries prioritize the most impactful actions that can reduce greenhouse gas emissions and boost adaptation, while delivering on broader development goals. CCDRs identify climate impacts on countries’ agrifood systems, such as reduced yields and increased food prices, and present a variety of country-specific technology options as well as policy reforms under the umbrella of CSA.
• Climate-Smart Agriculture (CSA) Country Profiles developed by the World Bank and  partners,  give an overview of the agricultural challenges in countries around the world, and how CSA can help them adapt to and mitigate climate change. They bridge knowledge gaps by providing clarity on CSA terminology, components, relevant issues, and how to contextualize them under different country conditions.
• Climate-Smart Agriculture Investment Plans  (CSAIPs) developed for a subset of client countries aim to mainstream CSA into national agricultural policies and to identify investment opportunities in CSA. The World Bank provides technical assistance and financial support to help countries develop and implement CSAIPs. These plans prioritize investments in climate-resilient infrastructure, capacity building, and knowledge sharing to promote sustainable agricultural practices. CSAIPs are available, or currently under preparation, for  Bangladesh , Belize,  Burkina Faso, Cote D’Ivoire , Cameroon, the Republic of Congo, Ethiopia, Ghana , Iraq, Jordan, Kenya, Lesotho , Madagascar, Mali , Morocco , Nepal , Senegal, Zambia , and  Zimbabwe .
• The World Bank also supports research programs such as with the  CGIAR , which develops and supports climate-smart technologies and management methods, early warning systems, risk insurance, and other innovations that promote resilience and combat climate change.”

Working Toward Resilience and Food and Nutrition Security, while Curbing GHG Emissions

The Bank’s support of CSA is making a difference across the globe, for example:

• A new US$345 million loan for the China Green Agricultural and Rural Revitalization Program for Results will support China’s global public goods agenda by promoting the greening of agriculture and rural development in Hubei and Hunan provinces in central China. The program will reduce greenhouse gas (GHG) emissions from crop and livestock farming, increase carbon sequestration in farmlands, and improve biodiversity protection and restoration in agricultural ecosystems, while strengthening the institutional capacity of local governments to integrate environmental and decarbonization objectives in government rural revitalization plans and investments. World Bank financing will complement a US$4.1 billion commitment by the Government of China (GoC).
• The US$621 million  Food Systems Resilience Program for Eastern and Southern Africa (Phase 3) FSRP Project in Kenya, Comoros, Malawi, Somalia aims to increase the resilience of food systems and the recipients’ preparedness for food insecurity. The project has six components, including building resilient agricultural production capacity to strengthen the productivity and resilience of domestic food production to shocks and stressors, by supporting the development and adoption of improved agricultural inputs and services and climate-smart and gender-sensitive farming technologies in the crops, livestock, and fisheries sectors.
• A US$200 million credit for the Punjab Resilient and Inclusive Agriculture Transformation Project (PRIAT) will help Pakistan enhance access to, and productivity of, agricultural water, and improve incomes of farmers supported by the project. PRIAT will notably reduce the differences in water availability among head, middle, and tail end users of watercourses, increase agricultural output per unit of water used at farm level for selected crops, increase the share of area under high-value crops cultivation, and increase agriculture incomes of households participating in project activities, yielding important climate change adaptation and mitigation co-benefits.
• The US$125 million  Agriculture Resilience, Value Chain Development and Innovation (ARDI) program will play a pivotal role in strengthening the transition Jordan’s agri-food sector. It supports Jordan's National Sustainable Agriculture Plan and aims to enhance climate resilience, competitiveness, and inclusivity of the agri-food sector. Over the next five years, it will support 30,000 farming household with the adoption of climate-smart and water-efficient agricultural practices, provide needs-based training, create about 12,000 employment opportunities, and promote value chain and export promotion through advanced market diagnostics. A particular focus will be on strengthening the participation of women, youth and refugees. 

Last Updated: Feb 26, 2024

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Climate-smart agriculture - Projects from around the world - Case studies 2021

This publication describes climate-smart agriculture case studies that apply the five action points for CSA implementation. The action points are:

expanding the evidence base for CSA,

supporting enabling policy frameworks,

strengthening national and local institutions,

enhancing funding and financing options, and

implementing CSA practices at field level.

The case studies discuss context-specific activities that contribute to CSA’s three pillars :

• sustainably increasing agricultural productivity and incomes ,
• adapting and building resilience of people and agri-food systems to climate change , and
• reducing and/or removing greenhouse gas emissions where possible .

Many of the case studies pay special attention to smallholder farmers, including women and indigenous groups, who are particularly affected by the impacts of climate change.

A diverse group of stakeholders contributed case studies, reflecting the importance of coordinating national-level CSA activities, for example by including research findings in policymaking processes, and leveraging public sector funding to attract private sector investment.

Key messages :

• Results under the three pillars of CSA are best achieved through a comprehensive strategy, such as the five action points approach highlighted in this publication.
• The five action points of the CSA approach are all crucial to effectively implement CSA; they have been applied in various contexts to achieve results under the three CSA pillars.
• Not all projects need to focus on all five action points. In addition, the action points are not necessarily consecutive actions, but rather actions that may or may not be undertaken at the same time; ideally, they reinforce each other to create an enabling environment. For example, a robust evidence base should support enabling policy frameworks, national and local institutions, funding and financing options, and the implementation of CSA practices at field level. Each of these actions may in turn generate valuable knowledge that feeds back into the evidence base.
• Knowledge sharing and working with diverse partners is essential for all five action points, as the sum of the knowledge and practices of various partners is larger than its parts.
• Regarding action point 1 , building the evidence base for CSA, the case studies confirm that the linkages between agriculture and climate change are site-specific . Analysis based on site-specific findings may therefore lead to the selection of different climate-smart agricultural practices for different sites.
• On action point 2, supporting enabling policy frameworks, the case studies show that governments are already working to operationalize their approach to agriculture under climate change, working with partners at the regional, national and provincial levels.
• Action point 3, strengthening national and local institutions, is shown to require a capacity building approach which entails a range of activities, including the drafting of guidelines, the dissemination of best practices, and training .
• The case studies related to action point 4, enhancing options for financing and funding, expand the scope of this action point and emphasize the need for access to climate finance instruments , creating links between climate and agricultural finance and investments, and considering climate change in agricultural planning and budgeting. Innovative finance mechanisms are proposed , such as to help farmers invest in CSA practices and unlock the potential of large-scale public-private partnerships to attract resources.
• Finally, the case studies on implementing practices at field level, or action point 5, highlight the importance of gaining a good understanding of the diverse needs and priorities of farmers and working directly with them. The case studies demonstrate that CSA must be considered as encompassing a broad range of practices. The studies illustrate how tools such as Farmer Field Schools, demonstration plots and information and communications technology may prove valuable in a range of settings .

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Case Study of Smart Farming Using IoT

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Smart farming is an idea to enhance the basic capabilities of traditional farming using modern technologies such as the Internet of Things, implementing it to the industry-based technology that provides real-time information in accordance with ad-hoc sensor networks spread across the agricultural field and maneuvering it through application software systems. The farm-based equipment is used with a systematic approach to increase agricultural production as well as quality of the produce. Smart farming is a low cost and low labor implementation method leading to an overall reduction of agricultural expenses. It helps to produce a higher yield and better quality crops, leading to higher price and demand, resulting in more profit for farmers. This modern way of farming is based on technological gadgets that are able to monitor environmental factors, such as excessive or inadequate moisture, low dew content, or higher temperatures in the atmosphere, so that water flow can be adjusted throughout the field – leading the way toward wireless capability enhancement and adjusting to variable weather conditions. To maintain the health of the plants, sensor networks spread across the field monitor growth and water requirements with real-time data about humidity and temperature. Farmers can then provide the proper amount of water with an automatic switch controlled through application software. The data are analyzed with a week-wise report to the farmer, providing a proper record of plant growth, with graphical data representations on the application.

IoT, Smart Farming, MQTT, Internet of Things, E‐farming

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Case study /, climate-smart agriculture. case studies 2018. successful approaches from different regions.

This publication is a compilation of the success stories covering different regions’ landscapes where on-the-ground climate-smart agriculture (CSA) work has been implemented in recent years. Climate change affects all agricultural sectors, from mussel production along Chile’s coastline to floating gardens in Bangladesh. There are many agricultural practices that can achieve the three objectives of CSA, ranging from climate-smart agroforestry systems implemented in the Dry Corridor of Central America to Sloping Agricultural Land Technology (SALT) in coconut-farming communities in the Philippines. Whether climate change is experienced slowly over the course of many years, on a seasonal basis or as an extreme weather event such as a typhoon, communities need to take climate-smart action to help adapt their sectors to these climate change impacts and promote resilience for their future. These successful projects and initiatives enable communities to be better prepared to safeguard their livelihoods and boost household incomes, and identify synergies between adaptation and mitigation.

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Publications and Report

Climate-Smart Agriculture Case studies

Description.

This report provides a context-specific look at Climate-Smart Agriculture (CSA) across many different regions, it also showcases different elements of climate-smart agricultural systems. The case studies show how the management of farms, crops, livestock and aquaculture can balance short- and long-term food security needs with priorities for the farmer/producer, as well as build adaption to climate change and contribute to mitigating GHGs. Many of the impacts outlined in the studies highlight the services provided to farmers, fishers and land managers to enable a better management of climate risks/impacts while providing mitigation options.

The case studies were selected and adapted from the Climate-Smart Agriculture Sourcebook Second Edition 2017, and other FAO projects. The aim is to further support policy makers, academics, practitioners (i.e. extension services, non-governmental organizations [NGOs] and farmers) and programme managers who are interested in successful examples of on-the-ground implementation of CSA approaches, and capturing the synergies between adaptation, mitigation and food security in their work.

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Published in Climate-ADAPT   Mar 14, 2019   -   Last Modified in Climate-ADAPT   Dec 12, 2023

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Adaptation Measures and Actions, Vulnerability Assessment

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Digitalizing Smallholder Farmer Agri-Food Supply Chains: A Case Study from a Developing Economy

• Conference paper
• First Online: 07 September 2024
• Cite this conference paper

• W. Madushan Fernando   ORCID: orcid.org/0000-0003-4505-980X 19 , 20 ,
• Amila Thibbotuwawa   ORCID: orcid.org/0000-0002-5443-8839 20 ,
• R. M. Chandima Ratnayake   ORCID: orcid.org/0000-0003-2222-8199 19 &
• H. Niles Perera   ORCID: orcid.org/0000-0001-6329-5967 20  

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 731))

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• IFIP International Conference on Advances in Production Management Systems

Smallholder farming is critical to ensuring food security and alleviating rural poverty. Poor agricultural practices, supply chain inefficiencies, weather challenges, and market disruptions all diminish productivity in this sector. As modern technology and digitalization reshape agriculture, there is a significant augmentation of stakeholder connectivity within smallholder farmer Agri-Food Supply Chains (AFSCs). The progress of technology allows smallholder farmers to gain access to high-quality farming inputs while expanding their market reach. While there are proven benefits of digitally transforming smallholder farmer AFSCs, there is still a significant knowledge gap in effectively assessing the potential of digital technologies from a supply chain perspective. As the overall approach in this paper, we used the case study research method along with inductive reasoning. We combined the AHP and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods to include both industry practitioners and academic perspectives in the decision-making process. The process involved using AHP to analyze supply chain inefficiencies, with a focus on their impact on yield, harvest quality, and farmer livelihood, and then using the TOPSIS method to prioritize digital solutions for the chosen case study. The case study revealed that 61% of inefficiencies arose in the early supply chain stages, notably in regulation (28.26%) and farm input supply (33.03%), emphasizing the critical need for prioritizing digital farm record-keeping and registration for improved efficiency. This study emphasizes practical digital solutions for smallholder farming supply chains while integrating industry and academic perspectives, offering a systematic approach to prioritizing interventions.

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Kuizinaitė, J., Morkūnas, M., Volkov, A.: Assessment of the most appropriate measures for mitigation of risks in the agri-food supply chain. Sustainability (Switzerland) 15 (12) (2023). https://doi.org/10.3390/su15129378

Yi, Z., Wang, Y., Chen, Y.J.: Financing an agricultural supply chain with a capital-constrained smallholder farmer in developing economies. Prod. Oper. Manag. 30 (7), 2102–2121 (2021). https://doi.org/10.1111/poms.13357

Article   Google Scholar  

Fernando, W.M., Perera, H.N., Ratnayake, R.M.C., Thibbotuwawa, A.: Storm in a teacup: implications of mobile phone literacy on sustainable smallholder agri-food supply chains in developing economies. Int. J. Logist. Manag. (2024). https://doi.org/10.1108/IJLM-09-2023-0413

Jayalath, M.M., Perera, H.N.: Mapping post-harvest waste in perishable supply chains through system dynamics: a Sri Lankan case study. J. Agri. Sci. Sri Lanka 16 (3), 526–543 (2021). https://doi.org/10.4038/jas.v16i03.9477

Hammond, J., et al.: Poverty dynamics and the determining factors among East African smallholder farmers. Agric. Syst. 206 (2023). https://doi.org/10.1016/j.agsy.2023.103611

Lezoche, M., Panetto, H., Kacprzyk, J., Hernandez, J.E., Alemany Díaz, M.M.E.: Agri-food 4.0: a survey of the supply chains and technologies for the future agriculture. Comput. Ind. 117 . Elsevier B.V. (2020). https://doi.org/10.1016/j.compind.2020.103187

Morgan, T.R., Richey, R.G., Ellinger, A.E.: Supplier transparency: scale development and validation. Int. J. Logist. Manag. 29 (3), 959–984 (2018). https://doi.org/10.1108/IJLM-01-2017-0018

Fabregas, R., Kremer, M., Schilbach, F.: Realizing the potential of digital development: the case of agricultural advice. Science 366 (6471). American Association for the Advancement of Science (2019). https://doi.org/10.1126/science.aay3038

Mushi, G.E., Serugendo, G.D.M., Burgi, P.Y.: Digital technology and services for sustainable agriculture in tanzania: a literature review. Sustainability (Switzerland) 14 (4), MDPI (2022). https://doi.org/10.3390/su14042415

Xie, L., Luo, B., Zhong, W.: How are smallholder farmers involved in digital agriculture in developing countries: a case study from China. Land (Basel) 10 (3), 1–16 (2021). https://doi.org/10.3390/land10030245

Seuring, S., Stella, T., Stella, M.: Developing and publishing strong empirical research in sustainability management—addressing the intersection of theory, method, and empirical field. Front. Sustain. 1 (2021). https://doi.org/10.3389/frsus.2020.617870

Vasantha Lakshmi, K., Udaya Kumara, K.N.: A novel randomized weighted fuzzy AHP by using modified normalization with the TOPSIS for optimal stock portfolio selection model integrated with an effective sensitive analysis. Expert Syst. Appl. 243 (2024). https://doi.org/10.1016/j.eswa.2023.122770

Ahmed, F., Fattani, M.T., Ali, S.R., Enam, R.N.: Strengthening the bridge between academic and the industry through the academia-industry collaboration plan design model. Front Psychol. 13 (2022). https://doi.org/10.3389/fpsyg.2022.875940

Abdulai, A.R., Gibson, R., Fraser, E.D.G.: Beyond transformations: Zooming in on agricultural digitalization and the changing social practices of rural farming in Northern Ghana, West Africa. J. Rural Stud. 100 (2023). https://doi.org/10.1016/j.jrurstud.2023.103019

Simelton, E., McCampbell, M.: Do digital climate services for farmers encourage resilient farming practices? pinpointing gaps through the responsible research and innovation framework. Agriculture (Switzerland) 11 (10) (2021). https://doi.org/10.3390/agriculture11100953

Dad, F., Dibari, F., Kebede, A., Lefu, E., Ndumiyana, T., Butaumocho, B.: Digitalisation in the WFP fresh food voucher programme: a pilot study from rural Amhara region, Ethiopia. Front Nutr. 10 (2023). https://doi.org/10.3389/fnut.2023.1217794

Gray, B., et al.: Digital Farmer Profiles: Reimagining Smallholder Agriculture (2018)

Google Scholar  

Kumar, P., Hendriks, T., Panoutsopoulos, H., Brewster, C.: Investigating FAIR data principles compliance in horizon 2020 funded Agri-food and rural development multi-actor projects. Agric. Syst. 214 (2024). https://doi.org/10.1016/j.agsy.2023.103822

Burke, W.J., Jayne, T.S., Snapp, S.S.: Nitrogen efficiency by soil quality and management regimes on Malawi farms: Can fertilizer use remain profitable?. World Dev. 152 (2022). https://doi.org/10.1016/j.worlddev.2021.105792

Barbedo, J.G.A.: A review on the combination of deep learning techniques with proximal hyperspectral images in agriculture. Comput. Electron. Agric. 210 . Elsevier B.V. (2023). https://doi.org/10.1016/j.compag.2023.107920

Piancharoenwong, A., Badir, Y.F.: IoT smart farming adoption intention under climate change: the gain and loss perspective. Technol. Forecast Soc. Change 200 (2024). https://doi.org/10.1016/j.techfore.2023.123192

Food and Agriculture Organization (FAO), Digital Agriculture Profile • Rwanda (2020)

Li, W., He, W.: Revenue-increasing effect of rural e-commerce: a perspective of farmers’ market integration and employment growth. Econ. Anal. Policy 81 , 482–493 (2024). https://doi.org/10.1016/j.eap.2023.12.015

Addison, M., et al.: Exploring the impact of agricultural digitalization on smallholder farmers’ livelihoods in Ghana. Heliyon, e27541 (2024). https://doi.org/10.1016/j.heliyon.2024.e27541

Yin, R.K.: Case Study Research and Applications: Design and Methods (2018)

Stuart, I., Mccutcheon, D., Handfield, R., Mclachlin, R., Samson, D.: Effective case research in operations management: a process perspective (2002)

International Labour Organization, Future of work for Tea SmallholderS in Sri lanka (2018)

Saaty, T.L.: Decision making-the analytic hierarchy and network processes (ahp/anp) (2004)

Behzadian, M., Khanmohammadi Otaghsara, S., Yazdani, M., Ignatius, J.: A state-of the-art survey of TOPSIS applications. Expert Syst. Appl. 39 (17), 13051–13069. Elsevier Ltd, (2012). https://doi.org/10.1016/j.eswa.2012.05.056

Kumar, M., Choubey, V.K.: Sustainable performance assessment towards sustainable consumption and production: evidence from the Indian dairy industry. Sustainability (Switzerland), 15 (15) (2023). https://doi.org/10.3390/su151511555

Marsden, A.R., Zander, K.K., Lassa, J.A.: Smallholder farming during COVID-19: a systematic review concerning impacts, adaptations, barriers, policy, and planning for future pandemics. Land 12 (2). MDPI (2023). https://doi.org/10.3390/land12020404

Branca, G., Cacchiarelli, L., Haug, R., Sorrentino, A.: Promoting sustainable change of smallholders’ agriculture in Africa: Policy and institutional implications from a socio-economic cross-country comparative analysis. J. Clean Prod. 358 (2022). https://doi.org/10.1016/j.jclepro.2022.131949

Luo, N., Olsen, T.L., Liu, Y.: A conceptual framework to analyze food loss and waste within food supply chains: an operations management perspective. Sustainability (Switzerland) 13 (2), 1–21 (2021). https://doi.org/10.3390/su13020927

Alzahrani, K., Ali, M., Azeem, M.I., Alotaibi, B.A.: Efficacy of public extension and advisory services for sustainable rice production. Agriculture (Switzerland) 13 (5) (2023). https://doi.org/10.3390/agriculture13051062

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Acknowledgment

The authors would like to acknowledge the financial support given by the Norwegian Program for Capacity Development in Higher Education and Research for Development (NORHED II – Project number 68085), the “Politics and Economic Governance” sub-theme, the project “Enhancing Lean Practices in Supply Chains: Digitalization”, which is a collaboration between the University of Stavanger (Norway), ITB (Indonesia), and the University of Moratuwa (Sri Lanka).

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Department of Mechanical and Structural Engineering and Materials Science, University of Stavanger, Stavanger, Norway

W. Madushan Fernando & R. M. Chandima Ratnayake

Center for Supply Chain, Operations, and Logistics Optimization, University of Moratuwa, Katubedda 10400, Moratuwa, Sri Lanka

W. Madushan Fernando, Amila Thibbotuwawa & H. Niles Perera

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West Saxon University of Applied Sciences Zwickau, Zwickau, Germany

Ralph Riedel

ZF Friedrichshafen AG, Friedrichshafen, Germany

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Tecnológico de Monterrey, Mexico City, Mexico

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Fernando, W.M., Thibbotuwawa, A., Ratnayake, R.M.C., Perera, H.N. (2024). Digitalizing Smallholder Farmer Agri-Food Supply Chains: A Case Study from a Developing Economy. In: Thürer, M., Riedel, R., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments. APMS 2024. IFIP Advances in Information and Communication Technology, vol 731. Springer, Cham. https://doi.org/10.1007/978-3-031-71633-1_12

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