Technology in Plant Agriculture

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Technology in plant agriculture encompasses all types of technology utilized in the advancement of plant cultivation, domestication, and harvesting. Cultivation includes manipulation of factors in the plant environment including soil tillage, water, fertilizer, and pesticide as well as sowing seeds. Cultivation is further divided into horticulture, the cultivation of plants in gardens and greenhouses, and agronomy, large-scale field crop farming. Domestication is defined as crop traits that result from advances in cultivation, differing from wild varieties. Harvesting refers to the process of gathering ripe crops. [1]

Smart Farming Overview

What is Smart Farming?

Smart farming enables farmers to leverage technology to automate farming operations, which includes methods of tracking and monitoring crops, and automating farming processes. Smart farming enables farmers to improve their productivity on their farms, optimize resources, and make data-driven decisions. Smart Farming is also known as Smart Agriculture, Climate-smart Agriculture, or Agritech. [2] [3]

Parts of Smart Farming

Smart farming incorporates many components of technology:

  • IoT Sensors monitor soil condition, moisture levels, the amount of light plants receive, and the temperature of the area
  • GPS is used to plot the land crops are planted in
  • Drones & Satellites monitor crops remotely and gather data. Drones are also used for pest and weed control.
  • Data Analytics support prediction of outcomes, and decision-making for what to plant, where to plant it, when to plant it, and when to harvest it. Data is collected about crop yields, soil condition mapping, climate change, fertilizer application, and weather.
  • Hardware and software incorporate the above components into one package. The software manages the overall smart farming operation, utilizing technology to monitor and control agriculture practices. It also enables automation and the use of robotics in those automations. [2] [4]


Technology in agriculture is the culmination of thousands of years of innovation. Some of the major innovations in agriculture technology include:

  • ~10,000 years ago garden tools were first developed, which served as the pathway to more modern tools like shovels and rakes
  • ~9,000 years ago plant domestication began as humans moved away from gathering from wild plants to growing plants specifically for food
  • ~5,000 years ago irrigation was first developed in the days of ancient Egypt, Mesopotamia, China, and Rome
  • 1793 the cotton gin was invented Eli Whitney, contributing to mechanized methods of processing but also contributing to the growth of slavery in the southern United States [5]
  • 1822 the reaper was invented by Cyrus McCormick for grain harvesting followed by the reaper-binder by Charles Withington in 1972 which reaped the crop and bound it into sheaves, beginning the pathway of farm mechanization [6]
  • 1890 the steam tractor' was patented by Daniel Best, setting the stage for the gasoline tractor [7] [8]
  • 1900s-1920s gasoline tractors were taking over for animals and steam-powered machines
  • 1918 Nitrogen fixation contributed to our ability to fertilize plants
  • 1930s-1940s use of pesticides and herbicides became more widespread, contributing to the survival of crops and higher crop yields
  • 1950s-1960s high-yield crop varieties were developed, producing higher yields than their predecessors
  • 1970s-1980s no-till farming was developed, enabling farmers to grow crops without tilling and disturbing the soil, leading to reduced erosion, increased water & nutrient retention, and decreased costs
  • 1990s instect resistant crops developed, helping to reduce the use of pesticides. [9] [10]

Smart Farming Methods

Various methods of smart farming have been gaining recognition in the past decade, the most popular methods being precision farming, using drones, increasing automation in farms, and integrating robotic harvesting with AI.

Precision Farming

Precision farming, also known as precision agriculture, is a method that utilizes data analytics and technology to increase the efficiency and sustainability of agricultural practices. By using GPS, GIS, and remote sensing, farmers are able to gather precise data about soil conditions, crop health, and fertilizers. Ensuring this data is accurate is crucial as the decisions the farmers choose to implement for future practices will be according to what they’ve gathered. Once this data is gathered, the farmers can treat areas of the farm as distinct units rather than applying an entire practice (e.g. increasing the use of fertilizers across the farm) throughout the farm. For instance, information gathered about the soil may show that the soil is not the same across entire fields as certain areas can be drier or moisture thus have to be treated accordingly [11]. The global precision farming market size was stationed at $9.31 billion USD and it’s expected to surpass $26.8B by 2030, showcasing the increasing demand for tools and methods that help increase efficiency in agriculture [12].

Precision farming is the most popular method of smart farming that has been used in commercial farms and family farms around the world. It yields several benefits, the most important one being increasing resource efficiency for farmers. Since precise data is collected and the farm is treated as separate units rather than as an entire entity, farmers can reduce resource waste by addressing issues in a targeted manner. A recent study found that farmers in the United States are able to reduce water and fertilizer use by at least 20%, without impacting yields [13]. Moreover, by using resources in a targeted manner based on precise data and employing several mechanisms including tailored inputs, resource utilization and timely interventions, farmers are able to increase crop yields. A study conducted in 2021, stated that precision farming can assist Canadian farmers in increasing crop yield by an estimated 7%. This benefits farmers economically and also helps contribute to food security by producing more crops while utilizing fewer resources. By increasing crop yields, and helping farmers increase resource efficiency, precision farming can also help farmers reduce their costs, substantially. Since resources are only used when and where they are needed, according to the precise data collected, there is a large reduction in the use of key resources including fertilizers and water which are the main cost drivers for the farmers. Farmers had an estimated cost savings of over $13 per acre, but as technology advances and this method becomes more widespread, the savings is expected to dramatically increase.


Drones are UAS (unmanned aircraft systems) that are equipped with numerous sensors, cameras, and technologies to assist farmers with agricultural activities. The drones are remote-controlled and play a large role in helping farmers collect valuable data used for data analytics. The drones' general 3D maps and topographic models of fields provide detailed information about soil variation and drainage patterns. Collecting data as such enables farmers to make decisions about land management and optimal irrigation systems [14]. Moreover, drones can also autonomously plant seeds or disperse beneficial insects for pest control purposes. This increases efficiency as farmers as they can redirect their focus to another task while the drones do this; two things are being done at the same time which makes a large difference, especially in commercial farms. This also speeds up the planting process as the drones are able to work at a pace unmatched by humans. Farmers are also able to reduce labor costs extensively as they can allocate workers to tasks that cannot be automated, and use drones and other methods that can be done with technology.


Automation has been becoming a widespread practice in various industries, and it has been playing a pivotal role in the agricultural industry as well. The goal of automation is to streamline processes ultimately increasing efficiency, productivity, and sustainability in agricultural practices with the use of technology and machinery. There are various types of automation practices being applied in the farming sector but the most mainstream one is robotic harvesting with AI.

Robotic Harvesting

Robotic harvesting is when farmers use automated robots to harvest crops such as fruits, vegetables, and nuts. The robots use computer vision and mechanical systems to identify and pick the produce. Using a robot rather than an individual helps the farmers reduce their labor costs whilst increasing efficiency as well. For instance, the automation, is a single tomato harvester that is affordable for both small and medium-sized farmers. It selects tomatoes based on specific metrics and picks them; using this tool rather than an employee is predicted to reduce harvest costs by 50% in five years [15]. This is a major reduction in cost that has the potential to increase profitability for farmers and the affordability of food for consumers. The robots can also perform other key tasks such as planting, weeding, and spraying the plants. None of these tasks are possible without an AI algorithm that plays a fundamental role in robotic harvest. It helps the robots navigate the farms, provides the parameters for the robots to identify which produce is ripe enough to be picked (color, firmness, size) and also helps with the act of picking the produce itself.

Automated Machinery

Automated Machinery, is a category under automation that uses autonomous systems to repetitive tasks that can easily be done with human intervention. Integrating automated machinery yields various benefits for the farmers and crops by increasing productivity, substantially decreasing labor costs, and enabling sustainable agriculture practices.

A widely common piece of automated machinery used in small, medium, and large commercial farms are autonomous seeders. These seeders can radically sow seeds in the field, ensuring there is consistent spacing between the seeds and the optimal seed depth for optimal yields. Moreover, weeds tend to be a continuous issue that farmers face and traditionally, experienced workers are employed to help with the issue. Now, autonomous robots that are equipped with cameras and AI can identify and remove the weeds in the fields. This helps reduce the need for any chemical herbicides, enabling a larger and healthier crop yield, whilst also reducing the use of resources. A commercial-sized weeder can eliminate more than 100,00 weeds per hour which is equivalent to approximately 15 to 20 acres of crops in one day. In contrast, a human hired for the same tasks can only weed approximately one acre per day [16]. The substantial difference is the amount weeded between the machine and humans, encouraging many medium- large scale farms to invest in these machines. These machines aren’t entirely autonomous; human intervention is required as it must be pulled by a row tractor thus an individual is required to drive the weeder [17].


Hydroponics is a new method that has been increasing in popularity; this interesting and unique technique grows plants without the use of any soil. It is mainly used in vertical farms which are environments with controlled conditions used to grow crops in vertically stacked layers [18]. The purpose of hydroponics is to use a nutrient-rich water solution that the crops can rely on rather than soil. Various sensors are used within the systems to measure critical patterns such as pH levels, temperature, and humidity. The data that is collected with these sensors are analyzed by AI algorithms which enable farmers to make data-driven decisions regarding the crops.

Contrary to popular belief, hydroponic systems use significantly less water when compared to traditional soil-based farming. It uses 10 times less water when compared to traditional water mainly because this method has a closed-loop nature which enables recirculation and reuse of the water. This reduces water waste and also makes it an affordable and sustainable option in regions facing water scarcity. Moreover, since various sensors are used in this method, the nutrient solution can be precisely controlled which ensures that the crops are given the minerals required for optimal yield [19]. By continuously monitoring the health of the crops and taking action in a timely manner when certain nutrients are lacking, farmers can produce healthier crops that grow at a faster rate.

The relationship between hydroponics and technology is crucial as it’s led to significant improvement and advancements of methods in hydroponics over the last few years. The market is expected to grow from $4.69 billion to $6.83 billion by 2028 [20]. Through the implementation of technology, farmers are also able to make data-driven decisions with the sensors. The data is analyzed by AI algorithms which enable the farmers to become cognizant of the plant health, growth patterns, and predicted yield. It also enables farmers to efficiently use their resources; using the closed loop systems for the water helps minimize water use, reduce waste, and also ensures that the plants get the nutrients that they require. This helps make hydroponics a sustainable method that can ultimately help with environmental sustainability and food security issues as technology continues to become advanced and integrated with agricultural practices.

Smart Farming Features

Smart farming increases efficiency on a farm through the use of IoT sensors and drones. Sensors communicate with one another to monitor various key aspects of a farm including crop health, soil condition in very specific areas, and the condition of equipment. Data from the sensors and drones is utilized to identify the best conditions for growing crops, and to calculate the exact resources needed to grow plants, maximizing the use of resources while minimizing environmental impact. This allows precise water application, precise fertilizer application, and precise pesticide and herbicide application. This has environmental benefits, as it minimizes the use of water, fertilizers, pesticides, herbicides, and energy. Robots are used to harvest crops as well as for robotic weed destruction which involves machine learning of unwanted plants. They are also used for robotic pest control which can include the distribution of insects that attack unwanted insects, and drones which seek out and destroy specific insects. Ultimately, all of this increases production and quality, allowing farmers to transition their roles into agricultural managers. [2] [21]

Smart Farming Goals

The goals of smart farming include:

  • Increasing the overall efficiency of farms
  • Reduction of environmental impacts of plant production, including:
    • Reduction of fertilizer use, particularly excess Phosphorus and Nitrogen which are major contributors to environmental issues as two of the nine planetary boundaries that have exceeded their respective zones of uncertainty [22]
    • Controlled water use, contributing to a significant reduction in water consumption. Agriculture accounts for 70% of all water consumption worldwide. It is estimated that data-driven farming could reduce water consumption by up to 30%. [23]
    • Reduction of pesticide use, minimizing the use of chemical pesticides, and promoting more sustainable agriculture practices. Precision farming can reduce pesticide use by up to 85% and fertilizer usage by up to 20%. [24]

  • Smart farming also supports the replacement of manual methods of:
    • Measuring soil nutrients
    • Watering crops
    • Monitoring for crop quality [3]

Smart Farming Importance

Why Smart Farming?

Smart Farming is important due to an expanding global population and the need to feed those people, leading to a demand for higher crop yield. It is critical that humans use natural resources efficiently given they are a limited resource, ultimately leading to the need for climate-smart agriculture. In addition, there’s been an increased use of sophisticated technology as it has been developed in recent years. COVID-19 also caused impacts in the smart farming industry due to supply chain disruptions and geo-political issues causing a shortage of skilled workers. This ultimately contributed to an increased smart farming market share. [2] [25]

Smart Farming Considerations

Some of the things that need to be considered in setting up a smart farming environment include:

  • Hardware selection and the related maintenance of that hardware
  • Infrastructure to support the entire system, the connectivity to allow the sensors to communicate, and security for the system
  • Analytics capabilities and the platform to use those capabilities such as desktop computers, smartphones, and/or tablets
Microsoft Research Precision agriculture uses computer science to make farms more efficient and reduce climate change

Benefits of smart farming include:

  • Real-time information from the farm
  • Potential increased agricultural productivity by 70% by 2050. Smart farming technologies and the use of IoT can improve crop yields and increase overall food production. [26]
  • Decreased manual labour
  • Improved Return on Investment. Farmers can expect a 15-25% ROI transitioning to smart farming.[27]
  • A reduced environmental impact through managing key resources on the farm. Eco-friendly smart farming technology helps reduce agricultural pollution. Using less fertilizer and herbicides reduces leaching and greenhouse gas emissions. [28]
  • The ability to address food security [29] [30] [25]

The video linked above "Microsoft Research - Precision agriculture uses computer science to make farms more efficient and reduce climate change" addresses how farming can reduce environmental impact while meeting the food needs of the global population.

Industry Leaders and Use Cases

Use Cases

Within the realm of Agritech, there exist three prominent application domains: Field Mapping, Farm/Crop Management, and Herbicide/Pesticide Application, each led by industry frontrunners.

Field Mapping Leaders

Field Mapping is the technique of creating a digital map of farmland using satellite imaging, sensors, and drone technology. Farmers can now obtain precise and detailed maps of their fields in the blink of an eye. These high-resolution maps provide valuable insights into soil composition, topography, and vegetation distribution. Armed with this information, farmers can make informed decisions regarding irrigation and planting strategies, which lead to optimized field operations and better resource management.

John Deer's Field Connect Field Mapping App.

Trimble Navigation Ltd is a leader in field mapping technology within their product line, ranging from handheld mapping devices to integrated GPS and mapping systems for agricultural machinery. Trimble's precision agriculture solutions help farmers map their fields, collect data on soil conditions, and optimize farm operations [31]. John Deere is a well-known name in the agriculture industry and offers advanced field mapping capabilities. Their precision agriculture technology, such as John Deere Field Connect and MyJohnDeere Operations Center, allows farmers to map fields using sensors and drones to make data-driven decisions for optimizing farming productivity [32] Ag Leader is a company specializing in precision agriculture technologies, including field mapping solutions. They offer products like InCommand displays and AgFiniti cloud-based platforms that enable farmers to map fields, collect and analyze data, and gain insights for efficient farm management. Ag Leader's solutions also have the ability to integrate with other precision agriculture tools, enabling seamless data transfer and analysis[33].

Crop Management Leaders

Crop Management has empowered farmers with intelligent tools to effectively manage their day-to-day farming operations.Farm/crop management gains data through the integration of sensors, IoT (Internet of Things) devices, and data analytics. Farmers can then monitor various parameters such as soil moisture, temperature, and nutrient levels in real time. This real-time data enables farmers to make data-driven decisions, allowing them to implement precise fertilization plans, manage optimized harvesting, and detect potential crop diseases or pest infestations effectively.

Climate Corporation (a subsidiary of Bayer) focuses on digital agriculture and offers an integrated platform called Climate FieldView. This platform provides farmers with tools for field monitoring, fertility management, planting prescriptions, and yield analysis, leveraging data analytics and machine learning [34]. Syngenta is a leading agriculture company that offers various farm management solutions. Their AgriEdge Excelsior program combines data-driven insights, software tools, and on-farm support to help farmers make data-driven informed decisions about crop protection, seed selection, and other agricultural practices [35]. Farmbrite is an all-in-one farm management software that helps farmers organize and manage their farm operations effectively. It offers a range of features to streamline tasks, track expenses, and monitor livestock and crop activities. Key features include farm planning (crop rotations, livestock management, and equipment schedules), financial tracking, task management, reporting analysis, as well as cost and risk analysis [36].

Autonomous Herbicide/Pesticide Application Leaders

Herbicide/Pesticide Application: This is a precise spraying system equipped with AI algorithms, computer vision, and robotics that offer accurate and efficient herbicide and pesticide application. These systems can detect and target specific weeds or pests, minimizing widespread chemical usage. Precise targeting reduces the overall need for herbicides and pesticides, resulting in cost savings and reduced environmental pollution.

John Deere is a well-known agricultural machinery manufacturer that has been actively developing autonomous agricultural solutions called See and Spray, acquired after buying out Blue River Technologies. This method uses a combination of sensors and automated sprayers to spray specific weeds with the proper solution. This leads to increased spray efficiency, data insights on weed field conditions, lower chemical usage, and the ability to combat herbicide resistance [37].AGCO Corporation is another major player in the agricultural machinery industry. They have been working on automation and precision agriculture solutions for crop protection. Their Fuse Smart Farming solutions offer integrated systems for automated spraying and precision application of herbicides and pesticides [38] .CNH Industrial is another major player in the agricultural machinery industry. They have developed automated spraying solutions, such as the IntelliSpray system, which uses advanced sensors and control technology to adjust pesticide application rates based on real-time data, optimizing efficiency and reducing waste.

Pros & Cons


  • Increased productivity: Agritech solutions can significantly enhance agricultural productivity. Technologies such as precision farming, automated irrigation systems, and monitoring tools help optimize resource utilization, leading to higher yields and improved efficiency.
  • Resource efficiency: Agritech aims to maximize resource efficiency by minimizing inputs such as water, fertilizers, and pesticides. Smart farming techniques enable the precise application of these resources, reducing waste and environmental impact.
  • Improved crop quality and health: Advanced technologies enable early detection of diseases, pests, and nutrient deficiencies. This allows farmers to take prompt action, protecting crops and ensuring better quality produce.
  • Enhanced data-driven decision-making: Agritech utilizes data collection and analysis tools to provide farmers with valuable insights. This data-driven approach enables more informed decisions regarding planting, harvesting, and overall farm management, leading to better outcomes.
  • Sustainability and environmental benefits: By promoting precision agriculture, Agritech helps reduce the environmental impact of farming. This includes minimizing chemical usage, optimizing water consumption, and reducing greenhouse gas emissions, thereby promoting sustainable practices.
  • Farm-to-Consumer Connectivity: Agritech can facilitate direct communication and transactions between farmers and consumers, eliminating intermediaries and reducing costs. Online platforms and mobile applications can connect farmers with potential buyers, enabling direct sales and fostering a closer relationship between producers and consumers.
Picture of Indian Farmers during the 2021 Farmer Protests. Countries like India have over 43% of the population working in Agriculture [39].


  • High initial investment: Many Agritech solutions involve significant upfront costs, including the purchase and maintenance of technology, sensors, and equipment. This can pose a financial burden, particularly for small-scale farmers who may struggle to afford these investments.
  • Technological barriers: Access to Agritech innovations may be limited in certain regions, particularly in developing countries with inadequate infrastructure and limited internet connectivity. Unequal access to technology can widen the digital divide in agriculture.
  • Skills and knowledge gap: Effective adoption of Agritech often requires farmers to acquire new skills and knowledge. The learning curve associated with utilizing advanced technology can be steep, especially for older or less tech-savvy farmers.
  • Data privacy and security concerns: Agritech involves the collection and analysis of substantial amounts of data, including sensitive information about farms and farmers. Ensuring data privacy and protection from cybersecurity threats becomes crucial to maintaining trust in these technologies.
  • Dependence on technology: While Agritech offers numerous benefits, it also increases reliance on technology. System failures, power outages, or malfunctions can disrupt farming operations, highlighting the need for backup plans and redundancy measures.
  • Job Loss: The biggest issue is the loss of jobs that comes with this technology. Globally, approximately 26% of the world's population was estimated to be working in agriculture in 2021, according to the International Labour Organization [40]. It's important to note that this figure includes both full-time and part-time workers in the agricultural sector. In developing areas like Sub-Saharan Africa and Asia, this percentage can be as high as 50%. Automating labor-intensive tasks can lead to massive job losses in these regions, but due to high initial costs and the need for technical know-how with the technologies, large-scale job disruption is limited in developing regions.

Future of Agritech

Drone used to pollinate Apple Trees Autonomously [41].

In the ever-evolving landscape of agriculture, computers, robots, and automation have emerged as a transformative force, giving rise to the dynamic field of Agritech. With a fusion of cutting-edge innovations and traditional agricultural practices, Agritech encompasses a wide array of applications that hold the potential to revolutionize the way we cultivate, manage, and cultivate food. From precision farming and smart irrigation to advanced crop monitoring and sustainable pest control, use cases for Agritech only continue to grow as the technologies are still in their infancy. As technology continues to advance, the possibilities for enhancing efficiency, sustainability, and yield in agriculture are boundless, ensuring that the growth of Agritech is a journey without limits.

Here is a snapshot of the continued use cases for Agritech:

  • Smart Irrigation: Water scarcity is a significant concern in agriculture. Agritech can help optimize water usage through smart irrigation systems. These systems use data from sensors and weather forecasts to deliver the precise amount of water needed by crops, reducing water waste and improving water use efficiency, which, in turn, increases crop yields [42].
  • Data Analytics and AI: The integration of data analytics and artificial intelligence (AI) can provide valuable insights for farmers. AI algorithms can analyze large datasets to predict crop diseases, optimize planting schedules, recommend fertilization strategies, and provide personalized crop management recommendations based on specific farm conditions.
  • Blockchain in Agriculture: Blockchain technology can enhance transparency and traceability in the agricultural supply chain. It can enable farmers to record and track information about their products, including origin, production practices, and certifications. This can help build trust among consumers and ensure the authenticity and quality of agricultural products [43].
  • Drone-assisted Pollination: Drone-assisted pollination is a concept that involves using drones to assist in the pollination process of plants. It is an emerging approach to address concerns related to declining bee populations and potential challenges in natural pollination [44].


Michael Juni Zaineb Khan Amber Lott
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada


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