Intelligent transportation system

From Wikipedia, the free encyclopedia

 

 

ITS graphical user interface displaying the Hungarian highway network and its data points

An intelligent transportation system (ITS) is an advanced application which aims to provide innovative services relating to different modes of transport and traffic management and enable users to be better informed and make safer, more coordinated, and 'smarter' use of transport networks.

Some of these technologies include calling for emergency services when an accident occurs, using cameras to enforce traffic laws or signs that mark speed limit changes depending on conditions.

Although ITS may refer to all modes of transport, the directive of the European Union 2010/40/EU, made on July 7, 2010, defined ITS as systems in which information and communication technologies are applied in the field of road transport, including infrastructure, vehicles and users, and in traffic management and mobility management, as well as for interfaces with other modes of transport. ITS may improve the efficiency and safety of transport in a number of situations, i.e. road transport, traffic management, mobility, etc. ITS technology is being adopted across the world to increase capacity of busy roads and reduce journey times.

Background

Recent governmental activity in the area of ITS — is further motivated by an increasing focus on homeland security. Many of the proposed ITS systems also involve surveillance of the roadways, which is a priority of homeland security. Funding of many systems comes either directly through homeland security organisations or with their approval. Further, ITS can play a role in the rapid mass evacuation of people in urban centers after large casualty events such as a result of a natural disaster or threat. Much of the infrastructure and planning involved with ITS parallels the need for homeland security systems.

In the developing world, the migration from rural to urbanized habitats has progressed differently. Many areas of the developing world have urbanised without significant motorisation and the formation of suburbs. A small portion of the population can afford automobiles, but the automobiles greatly increase congestion in these multimodal transportation systems. They also produce considerable air pollution, pose a significant safety risk, and exacerbate feelings of inequities in the society. High population density could be supported by a multimodal system of walking, bicycle transportation, motorcycles, buses, and trains.

Other parts of the developing world, such as China, India and Brazil remain largely rural but are rapidly urbanising and industrialising. In these areas a motorised infrastructure is being developed alongside motorisation of the population. Great disparity of wealth means that only a fraction of the population can motorise, and therefore the highly dense multimodal transportation system for the poor is cross-cut by the highly motorised transportation system for the rich.

Intelligent transportation technologies

Intelligent transport systems vary in technologies applied, from basic management systems such as car navigation; traffic signal control systems; container management systems; variable message signs; automatic number plate recognition or speed cameras to monitor applications, such as security CCTV systems, and automatic incident detection or stopped vehicle detection systems; to more advanced applications that integrate live data and feedback from a number of other sources, such as parking guidance and information systems; weather information; bridge de-icing (US deicing) systems; and the like. Additionally, predictive techniques are being developed to allow advanced modelling and comparison with historical baseline data. Some of these technologies are described in the following sections.

Wireless communications

Traffic monitoring gantry with wireless communication dish antenna

Various forms of wireless communications technologies have been proposed for intelligent transportation systems. Radio modem communication on UHF and VHF frequencies are widely used for short and long range communication within ITS.

Short-range communications of 350 m can be accomplished using IEEE 802.11 protocols, specifically WAVE or the dedicated short range communications (DSRC) standard being promoted by the Intelligent Transportation Society of America and the United States Department of Transportation. Theoretically, the range of these protocols can be extended using mobile ad hoc networks or mesh networking.

Longer range communications have been proposed using infrastructure networks such as WiMAX (IEEE 802.16), Global System for Mobile Communications (GSM), or 3G. Long-range communications using these methods are well established, but, unlike the short-range protocols, these methods require extensive and very expensive infrastructure deployment. There is lack of consensus as to what business model should support this infrastructure.

Auto insurance companies have utilised ad hoc solutions to support eCall and behavioural tracking functionalities in the form of Telematics 2.0.

Computational technologies

Recent advances in vehicle electronics have led to a move towards fewer, more capable computer processors on a vehicle. A typical vehicle in the early 2000s would have between 20 and 100 individual networked microcontroller/programmable logic controller modules with non-real-time operating systems. The current trend is toward fewer, more costly microprocessor modules with hardware memory management and real-time operating systems. The new embedded system platforms allow for more sophisticated software applications to be implemented, including model-based process control, artificial intelligence, and ubiquitous computing. Perhaps the most important of these for intelligent transportation systems is artificial intelligence.

Floating car data/floating cellular data

RFID E-ZPass reader attached to the pole and its antenna (right) used in traffic monitoring in New York City by using vehicle re-identification method

"Floating car" or "probe" data collected other transport routes. Broadly speaking, four methods have been used to obtain the raw data:

• Triangulation method. In developed countries a high proportion of cars contain one or more mobile phones. The phones periodically transmit their presence information to the mobile phone network, even when no voice connection is established. In the mid-2000s, attempts were made to use mobile phones as anonymous traffic probes. As a car moves, so does the signal of any mobile phones that are inside the vehicle. By measuring and analysing network data using triangulation, pattern matching or cell-sector statistics (in an anonymous format), the data was converted into traffic flow information. With more congestion, there are more cars, more phones, and thus, more probes. In metropolitan areas, the distance between antennas is shorter and in theory accuracy increases. An advantage of this method is that no infrastructure needs to be built along the road; only the mobile phone network is leveraged. But in practice the triangulation method can be complicated, especially in areas where the same mobile phone towers serve two or more parallel routes (such as a motorway (freeway) with a frontage road, a motorway (freeway) and a commuter rail line, two or more parallel streets, or a street that is also a bus line). By the early 2010s, the popularity of the triangulation method was declining.
• Vehicle re-identification. Vehicle re-identification methods require sets of detectors mounted along the road. In this technique, a unique serial number for a device in the vehicle is detected at one location and then detected again (re-identified) further down the road. Travel times and speed are calculated by comparing the time at which a specific device is detected by pairs of sensors. This can be done using the MAC addresses from Bluetooth or other devices, or using the RFID serial numbers from electronic toll collection (ETC) transponders (also called "toll tags").
• GPS based methods. An increasing number of vehicles are equipped with in-vehicle satnav/GPS (satellite navigation) systems that have two-way communication with a traffic data provider. Position readings from these vehicles are used to compute vehicle speeds. Modern methods may not use dedicated hardware but instead Smartphone based solutions using so called Telematics 2.0 approaches.
• Smartphone-based rich monitoring. Smartphones having various sensors can be used to track traffic speed and density. The accelerometer data from smartphones used by car drivers is monitored to find out traffic speed and road quality. Audio data and GPS tagging of smartphones enables identification of traffic density and possible traffic jams. This was implemented in Bangalore, India as a part of a research experimental system Nericell.

Floating car data technology provides advantages over other methods of traffic measurement:

• Less expensive than sensors or cameras
• More coverage (potentially including all locations and streets)
• Faster to set up and less maintenance
• Works in all weather conditions, including heavy rain

Sensing

Technological advances in telecommunications and information technology, coupled with ultramodern/state-of-the-art microchip, RFID (Radio Frequency Identification), and inexpensive intelligent beacon sensing technologies, have enhanced the technical capabilities that will facilitate motorist safety benefits for intelligent transportation systems globally. Sensing systems for ITS are vehicle- and infrastructure-based networked systems, i.e., intelligent vehicle technologies. Infrastructure sensors are indestructible (such as in-road reflectors) devices that are installed or embedded in the road or surrounding the road (e.g., on buildings, posts, and signs), as required, and may be manually disseminated during preventive road construction maintenance or by sensor injection machinery for rapid deployment. Vehicle-sensing systems include deployment of infrastructure-to-vehicle and vehicle-to-infrastructure electronic beacons for identification communications and may also employ video automatic number plate recognition or vehicle magnetic signature detection technologies at desired intervals to increase sustained monitoring of vehicles operating in critical zones of world.

Inductive loop detection

Saw cut loop detectors for vehicle detection buried in the pavement at this intersection as seen by the rectangular shapes of loop detector sealant at the bottom part of this picture

Inductive loops can be placed in a roadbed to detect vehicles as they pass through the loop's magnetic field. The simplest detectors simply count the number of vehicles during a unit of time (typically 60 seconds in the United States) that pass over the loop, while more sophisticated sensors estimate the speed, length, and class of vehicles and the distance between them. Loops can be placed in a single lane or across multiple lanes, and they work with very slow or stopped vehicles as well as vehicles moving at high speed.

Video vehicle detection

Traffic-flow measurement and automatic incident detection using video cameras is another form of vehicle detection. Since video detection systems such as those used in automatic number plate recognition do not involve installing any components directly into the road surface or roadbed, this type of system is known as a "non-intrusive" method of traffic detection. Video from cameras is fed into processors that analyse the changing characteristics of the video image as vehicles pass. The cameras are typically mounted on poles or structures above or adjacent to the roadway. Most video detection systems require some initial configuration to "teach" the processor the baseline background image. This usually involves inputting known measurements such as the distance between lane lines or the height of the camera above the roadway. A single video detection processor can detect traffic simultaneously from one to eight cameras, depending on the brand and model. The typical output from a video detection system is lane-by-lane vehicle speeds, counts, and lane occupancy readings. Some systems provide additional outputs including gap, headway, stopped-vehicle detection, and wrong-way vehicle alarms.

Bluetooth detection

Bluetooth is an accurate and inexpensive way to transmit position from a vehicle in motion. Bluetooth devices in passing vehicles are detected by sensing devices along the road. If these sensors are interconnected they are able to calculate travel time and provide data for origin and destination matrices. Compared to other traffic measurement technologies, Bluetooth measurement has some differences:

• Accurate measurement points with absolute confirmation to provide to the second travel times.
• Is non-intrusive, which can lead to lower-cost installations for both permanent and temporary sites.
• Is limited to how many Bluetooth devices are broadcasting in a vehicle so counting and other applications are limited.
• Systems are generally quick to set up with little to no calibration needed.

Since Bluetooth devices become more prevalent on board vehicles and with more portable electronics broadcasting, the amount of data collected over time becomes more accurate and valuable for travel time and estimation purposes, more information can be found in.

It is also possible to measure traffic density on a road using the audio signal that consists of the cumulative sound from tire noise, engine noise, engine-idling noise, honks and air turbulence noise. A roadside-installed microphone picks up the audio that comprises the various vehicle noise and audio signal processing techniques can be used to estimate the traffic state. The accuracy of such a system compares well with the other methods described above.

Radar Detection

Radars are mounted on the side of the road to measure traffic flow and for stopped and stranded vehicle detection purposes. Like video systems, radar learns its environment during set up so can distinguish between vehicles and other objects. It can also operate in conditions of low visibility. Traffic flow radar uses a "side-fire" technique to look across all traffic lanes in a narrow band to count the number of passing vehicles and estimate traffic density. For stopped vehicle detection (SVD) and automatic incident detection, 360 degree radar systems are used as they scan all lanes along large stretches of road. Radar is reported to have better performance over longer ranges than other technologies. SVD radar will be installed on all Smart motorways in the UK.

Information fusion from multiple traffic sensing modalities

The data from the different sensing technologies can be combined in intelligent ways to determine the traffic state accurately. A data fusion based approach that utilizes the road side collected acoustic, image and sensor data has been shown to combine the advantages of the different individual methods.

Intelligent transportation applications

Emergency vehicle notification systems

In 2015, the EU passed a law required automobile manufacturers to equip all new cars with eCall, a European initiative that assists motorists in the case of a collision. The in-vehicle eCall is generated either manually by the vehicle occupants or automatically via activation of in-vehicle sensors after an accident. When activated, the in-vehicle eCall device will establish an emergency call carrying both voice and data directly to the nearest emergency point (normally the nearest E1-1-2 public safety answering point, PSAP). The voice call enables the vehicle occupant to communicate with the trained eCall operator. At the same time, a minimum set of data will be sent to the eCall operator receiving the voice call.

The minimum set of data contains information about the incident, including time, precise location, the direction the vehicle was traveling, and vehicle identification. The pan-European eCall aims to be operative for all new type-approved vehicles as a standard option. Depending on the manufacturer of the eCall system, it could be mobile phone based (Bluetooth connection to an in-vehicle interface), an integrated eCall device, or a functionality of a broader system like navigation, Telematics device, or tolling device. eCall is expected to be offered, at earliest, by the end of 2010, pending standardization by the European Telecommunications Standards Institute and commitment from large EU member states such as France and the United Kingdom.

Congestion pricing gantry at North Bridge Road, Singapore

The EC funded project SafeTRIP is developing an open ITS system that will improve road safety and provide a resilient communication through the use of S-band satellite communication. Such platform will allow for greater coverage of the Emergency Call Service within the EU.

Automatic road enforcement

Automatic speed enforcement gantry or lombada eletrônica with ground sensors at Brasilia, D.F.

A traffic enforcement camera system, consisting of a camera and a vehicle-monitoring device, is used to detect and identify vehicles disobeying a speed limit or some other road legal requirement and automatically ticket offenders based on the license plate number. Traffic tickets are sent by mail. Applications include:

• Speed cameras that identify vehicles traveling over the legal speed limit. Many such devices use radar to detect a vehicle's speed or electromagnetic loops buried in each lane of the road.
• Red light cameras that detect vehicles that cross a stop line or designated stopping place while a red traffic light is showing.
• Bus lane cameras that identify vehicles traveling in lanes reserved for buses. In some jurisdictions, bus lanes can also be used by taxis or vehicles engaged in car pooling.
• Level crossing cameras that identify vehicles crossing railways at grade illegally.
• Double white line cameras that identify vehicles crossing these lines.
• High-occupancy vehicle lane cameras that identify vehicles violating HOV requirements.

Variable speed limits

Further information: Speed limit § Variable speed limits

Example variable speed limit sign in the United States

Recently some jurisdictions have begun experimenting with variable speed limits that change with road congestion and other factors. Typically such speed limits only change to decline during poor conditions, rather than being improved in good ones. One example is on Britain's M25 motorway, which circumnavigates London. On the most heavily traveled 14-mile (23 km) section (junction 10 to 16) of the M25 variable speed limits combined with automated enforcement have been in force since 1995. Initial results indicated savings in journey times, smoother-flowing traffic, and a fall in the number of accidents, so the implementation was made permanent in 1997. Further trials on the M25 have been thus far proven inconclusive.^[15]

Collision avoidance systems

Japan has installed sensors on its highways to notify motorists that a car is stalled ahead.^[16]

Cooperative systems on the road

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Communication cooperation on the road includes car-to-car, car-to-infrastructure, and vice versa. Data available from vehicles are acquired and transmitted to a server for central fusion and processing. These data can be used to detect events such as rain (wiper activity) and congestion (frequent braking activities). The server processes a driving recommendation dedicated to a single or a specific group of drivers and transmits it wirelessly to vehicles. The goal of cooperative systems is to use and plan communication and sensor infrastructure to increase road safety. The definition of cooperative systems in road traffic is according to the European Commission:^[17][18]

"Road operators, infrastructure, vehicles, their drivers and other road users will cooperate to deliver the most efficient, safe, secure and comfortable journey. The vehicle-vehicle and vehicle-infrastructure co-operative systems will contribute to these objectives beyond the improvements achievable with stand-alone systems."

World Congress on Intelligent Transport Systems (ITS World Congress) is an annual trade show to promote ITS technologies. ERTICO– ITS Europe, ITS America and ITS AsiaPacific sponsor the annual ITS World Congress and exhibition. Each year the event takes place in a different region (Europe, Americas or Asia-Pacific).^[19] The first ITS World Congress was held in Paris in 1994.

Smart transportation – new business models

New mobility and smart transportation models are emerging globally. Bike sharing, car sharing and scooter sharing schemes like Lime or Bird are continuing to gain popularity; electric vehicle charging schemes are taking off in many cities; the connected car is a growing market segment; while new, smart parking solutions are being used by commuters and shoppers all over the world. All these new models provide opportunities for solving last mile issues in urban areas.

ITS in the connected world

Mobile operators are becoming a significant player in these value chains (beyond providing just connectivity). Dedicated apps can be used to take mobile payments, provide data insights and navigation tools, offer incentives and discounts, and act as a digital commerce medium.

Payments and billing flexibility

These new mobility models call for high monetization agility and partner management capabilities. A flexible settlements and billing platform enables revenues to be shared quickly and easily and provides an overall better customer experience. As well as a better service, users can also be rewarded by discounts, loyalty points and rewards, and engaged via direct marketing.

Europe

The Network of National ITS Associations is a grouping of national ITS interests. It was officially announced 7 October 2004 in London. The secretariat is at ERTICO – ITS Europe.^[20]

ERTICO – ITS Europe is a public/private partnership promoting the development and deployment of ITS. They connect public authorities, industry players, infrastructure operators, users, national ITS associations and other organisations together. The ERTICO work programme focuses on initiatives to improve transport safety, security and network efficiency whilst taking into account measures to reduce environmental impact.

United States

In the United States, each state has an ITS chapter that holds a yearly conference to promote and showcase ITS technologies and ideas. Representatives from each Department of Transportation (state, cities, towns, and counties) within the state attend this conference.

 

Agricultural robot

From Wikipedia, the free encyclopedia

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

 

Autonomous Agricultural Robot

An agricultural robot is a robot deployed for agricultural purposes. The main area of application of robots in agriculture today is at the harvesting stage. Emerging applications of robots or drones in agriculture include weed control, cloud seeding, planting seeds, harvesting, environmental monitoring and soil analysis. According to Verified Market Research, the agricultural robots market is expected to reach $11.58 billion by 2025.

General

Fruit picking robots, driverless tractor / sprayers, and sheep shearing robots are designed to replace human labor. In most cases, a lot of factors have to be considered (e.g., the size and color of the fruit to be picked) before the commencement of a task. Robots can be used for other horticultural tasks such as pruning, weeding, spraying and monitoring. Robots can also be used in livestock applications (livestock robotics) such as automatic milking, washing and castrating. Robots like these have many benefits for the agricultural industry, including a higher quality of fresh produce, lower production costs, and a decreased need for manual labor. They can also be used to automate manual tasks, such as weed or bracken spraying, where the use of tractors and other manned vehicles is too dangerous for the operators.

Designs

Fieldwork Robot

The mechanical design consists of an end effector, manipulator, and gripper. Several factors must be considered in the design of the manipulator, including the task, economic efficiency, and required motions. The end effector influences the market value of the fruit and the gripper's design is based on the crop that is being harvested.

End effectors

An end effector in an agricultural robot is the device found at the end of the robotic arm, used for various agricultural operations. Several different kinds of end effectors have been developed. In an agricultural operation involving grapes in Japan, end effectors are used for harvesting, berry-thinning, spraying, and bagging. Each was designed according to the nature of the task and the shape and size of the target fruit. For instance, the end effectors used for harvesting were designed to grasp, cut, and push the bunches of grapes.

Berry thinning is another operation performed on the grapes, and is used to enhance the market value of the grapes, increase the grapes' size, and facilitate the bunching process. For berry thinning, an end effector consists of an upper, middle, and lower part. The upper part has two plates and a rubber that can open and close. The two plates compress the grapes to cut off the rachis branches and extract the bunch of grapes. The middle part contains a plate of needles, a compression spring, and another plate which has holes spread across its surface. When the two plates compress, the needles punch holes through the grapes. Next, the lower part has a cutting device which can cut the bunch to standardize its length.

For spraying, the end effector consists of a spray nozzle that is attached to a manipulator. In practice, producers want to ensure that the chemical liquid is evenly distributed across the bunch. Thus, the design allows for an even distribution of the chemical by making the nozzle to move at a constant speed while keeping distance from the target.

The final step in grape production is the bagging process. The bagging end effector is designed with a bag feeder and two mechanical fingers. In the bagging process, the bag feeder is composed of slits which continuously supply bags to the fingers in an up and down motion. While the bag is being fed to the fingers, two leaf springs that are located on the upper end of the bag hold the bag open. The bags are produced to contain the grapes in bunches. Once the bagging process is complete, the fingers open and release the bag. This shuts the leaf springs, which seals the bag and prevents it from opening again.

Gripper

The gripper is a grasping device that is used for harvesting the target crop. Design of the gripper is based on simplicity, low cost, and effectiveness. Thus, the design usually consists of two mechanical fingers that are able to move in synchrony when performing their task. Specifics of the design depend on the task that is being performed. For example, in a procedure that required plants to be cut for harvesting, the gripper was equipped with a sharp blade.

Manipulator

The manipulator allows the gripper and end effector to navigate through their environment. The manipulator consists of four-bar parallel links that maintain the gripper's position and height. The manipulator also can utilize one, two, or three pneumatic actuators. Pneumatic actuators are motors which produce linear and rotary motion by converting compressed air into energy. The pneumatic actuator is the most effective actuator for agricultural robots because of its high power-weight ratio. The most cost efficient design for the manipulator is the single actuator configuration, yet this is the least flexible option.

Development

The first development of robotics in agriculture can be dated as early as the 1920s, with research to incorporate automatic vehicle guidance into agriculture beginning to take shape. This research led to the advancements between the 1950s and 60s of autonomous agricultural vehicles. The concept was not perfect however, with the vehicles still needing a cable system to guide their path. Robots in agriculture continued to develop as technologies in other sectors began to develop as well. It was not until the 1980s, following the development of the computer, that machine vision guidance became possible.

Other developments over the years included the harvesting of oranges using a robot both in France and the US.

While robots have been incorporated in indoor industrial settings for decades, outdoor robots for the use of agriculture are considered more complex and difficult to develop.^{[citation needed]} This is due to concerns over safety, but also over the complexity of picking crops subject to different environmental factors and unpredictability.

Demand in the market

There are concerns over the amount of labor the agricultural sector needs. With an aging population, Japan is unable to meet the demands of the agricultural labor market. Similarly, the United States currently depends on a large number of immigrant workers, but between the decrease in seasonal farmworkers and increased efforts to stop immigration by the government, they too are unable to meet the demand. Businesses are often forced to let crops rot due to an inability to pick them all by the end of the season. Additionally, there are concerns over the growing population that will need to be fed over the next years. Because of this, there is a large desire to improve agricultural machinery to make it more cost efficient and viable for continued use.

Current applications and trends

Much of the current research continues to work towards autonomous agricultural vehicles. This research is based on the advancements made in driver-assist systems and self-driving cars.

While robots have already been incorporated in many areas of agricultural farm work, they are still largely missing in the harvest of various crops. This has started to change as companies begin to develop robots that complete more specific tasks on the farm. The biggest concern over robots harvesting crops comes from harvesting soft crops such as strawberries which can easily be damaged or missed entirely. Despite these concerns, progress in this area is being made. According to Gary Wishnatzki, the co-founder of Harvest Croo Robotics, one of their strawberry pickers currently being tested in Florida can "pick a 25-acre field in just three days and replace a crew of about 30 farm workers". Similar progress is being made in harvesting apples, grapes, and other crops. In the case of apple harvesting robots, current developments have been too slow to be commercially viable. Modern robots are able to harvest apples at a rate of one every five to ten seconds while the average human harvests at a rate of one per second.

Another goal being set by agricultural companies involves the collection of data. There are rising concerns over the growing population and the decreasing labor available to feed them. Data collection is being developed as a way to increase productivity on farms. AgriData is currently developing new technology to do just this and help farmers better determine the best time to harvest their crops by scanning fruit trees.

Applications

Robots have many fields of application in agriculture. Some examples and prototypes of robots include the Merlin Robot Milker, Rosphere, Harvest Automation, Orange Harvester, lettuce bot, and weeder. One case of a large scale use of robots in farming is the milk bot. It is widespread among British dairy farms because of its efficiency and nonrequirement to move. According to David Gardner (chief executive of the Royal Agricultural Society of England), a robot can complete a complicated task if its repetitive and the robot is allowed to sit in a single place. Furthermore, robots that work on repetitive tasks (e.g. milking) fulfill their role to a consistent and particular standard.

Another field of application is horticulture. One horticultural application is the development of RV100 by Harvest Automation Inc. RV 100 is designed to transport potted plants in a greenhouse or outdoor setting. The functions of RV100 in handling and organizing potted plants include spacing capabilities, collection, and consolidation. The benefits of using RV100 for this task include high placement accuracy, autonomous outdoor and indoor function, and reduced production costs.

Examples

Fendt Xaver

• Thorvald - an autonomous modular multi-purpose agricultural robot developed by Saga Robotics.
• Vinobot and Vinoculer
• LSU's AgBot
• Harvest Automation is a company founded by former iRobot employees to develop robots for greenhouses
• Root AI has made a tomato-picking robot for use in greenhouses
• Strawberry picking robot from Robotic Harvesting and Agrobot
• Small Robot Company developed a range of small agricultural robots, each one being focused on a particular task (weeding, spraying, drilling holes, ...) and controlled by an AI system
• ecoRobotix has made a solar-powered weeding and spraying robot
• Blue River Technology has developed a farm implement for a tractor which only sprays plants that require spraying, reducing herbicide use by 90%
• Casmobot next generation slope mower
• Fieldrobot Event is a competition in mobile agricultural robotics
• HortiBot - A Plant Nursing Robot
• Lettuce Bot - Organic Weed Elimination and Thinning of Lettuce
• Rice planting robot developed by the Japanese National Agricultural Research Centre
• ROS Agriculture - Open source software for agricultural robots using the Robot Operating System
• The IBEX autonomous weed spraying robot for extreme terrain, under development
• FarmBot, Open Source CNC Farming
• VAE, under development by an Argentinean ag-tech startup, aims to become a universal platform for multiple agricultural applications, from precision spraying to livestock handling.
• ACFR RIPPA: for spot spraying 
• ACFR SwagBot; for livestock monitoring
• ACFR Digital Farmhand: for spraying, weeding and seeding

Green Revolution

From Wikipedia, the free encyclopedia

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

After World War II, newly implemented technologies, including the pesticides and fertilizers as well as new breeds of high yielded crops, greatly increased global food production.

The Green Revolution, or the Third Agricultural Revolution, is the set of research technology transfer initiatives occurring between 1950 and the late 1960s, that increased agricultural production worldwide, beginning most markedly in the late 1960s. The initiatives resulted in the adoption of new technologies, including High-Yielding Varieties (HYVs) of cereals, especially dwarf wheat and rice. It was associated with chemical fertilizers, agrochemicals, and controlled water-supply (usually involving irrigation) and newer methods of cultivation, including mechanization. All of these together were seen as a 'package of practices' to supersede 'traditional' technology and to be adopted as a whole.

Both the Ford Foundation and the Rockefeller Foundation were heavily involved in its initial development in Mexico. One key leader was Norman Borlaug, the "Father of the Green Revolution", who received the Nobel Peace Prize in 1970. He is credited with saving over a billion people from starvation. The basic approach was the development of high-yielding varieties of cereal grains, expansion of irrigation infrastructure, modernization of management techniques, distribution of hybridized seeds, synthetic fertilizers, and pesticides to farmers.

The term "Green Revolution" was first used by William S. Gaud, the administrator of the U.S. Agency for International Development (USAID), in a speech on 8 March 1968. He noted the spread of the new technologies as:

"These and other developments in the field of agriculture contain the makings of a new revolution. It is not a violent Red Revolution like that of the Soviets, nor is it a White Revolution like that of the Shah of Iran. I call it the Green Revolution."

History

Development in Mexico

Mexico has been called the 'birth place and burial ground of the Green Revolution. It began with great promise and it has been argued that "during the twentieth century two 'revolutions' transformed rural Mexico: the Mexican Revolution (1910–1920) and the Green Revolution (1950–1970)". It was on the lead of the Mexican government in 1943, under Presidential order and finance of the Mexican President Manuel Ávila Camacho, and support of the U.S. government, the United Nations, the Food and Agriculture Organization (FAO), and the Rockefeller Foundation. For the U.S. government, its neighbor Mexico was an important experimental case in the use of technology and scientific expertise in agriculture that became the model for international agricultural development. Mexico made a concerted effort to transform agricultural productivity, particularly with irrigated rather than dry-land cultivation in its northwest, to solve its problem of lack of food self-sufficiency. In the center and south of Mexico, where large-scale production faced challenges, agricultural production languished. Increased production promised food self-sufficiency in Mexico to feed its growing and urbanizing population with the increase in number of calories consumed per Mexican. The technology was seen as a valuable way to feed the poor, and would relieve some pressure of the land redistribution process. In general, success of "Green Revolution" depended on the use of machinery for cultivation and harvest, on large-scale agricultural enterprises with access to credit (often from foreign investors), government-supported infrastructure projects, and access to low-wage agricultural workers.

Mexico was the recipient of knowledge and technology of the Green Revolution, and it was an active participant with financial supports from the government for agriculture and Mexican agronomists. In the aftermath of the Mexican Revolution, the government had redistributed land to peasants in some parts of the country which had broken the back of the hacienda system. During the presidency of Lázaro Cárdenas (1934-1940), land reform in Mexico reached its apex in the center and south of Mexico. Agricultural productivity had fallen significantly by 1940s. U.S. Vice President Henry A. Wallace, previously president Franklin Delano Roosevelt's Secretary of Agriculture, visited Mexico who helped in uplifting the research program in Mexico that emphasized in increased productivity rather than land reform. During the administration of Manuel Avila Camacho (1940–46), the government put resources into developing new breeds of plants and partnered with the Rockefeller Foundation, and was also supported by the U.S. Department of Agriculture. In 1941, a team of U.S. scientists, Richard Branfield (Cornell University), Paul C. Mangelsdorf (Harvard University), and Elvin Charles Stakman (University of Minnesota) surveyed Mexican agriculture to recommend policies and practices. Norman Borlaug, a key figure developing Green Revolution practices in Mexico, studied with Stakman at University of Minnesota.

Locations of Norman Borlaug's research stations in the Yaqui Valley and Chapingo.

Agriculture in Mexico had been a sociopolitical issue, a key factor in some regions' participation in the Mexican Revolution. It was also a technical issue enabled by a cohort of trained agronomists who advised peasants how to increase productivity. In the post-World War II era, the government sought development in agriculture that bettered technological aspects of agriculture in regions—not dominated by small-scale peasant cultivators. This drive for agricultural transformation would have the benefit to Mexico on self-sufficiency in food and in the political sphere during the Cold War (potentially stem unrest and the appeal of Communism). Technical aid can also be seen as serving political ends in the international sphere. In Mexico, it also served political ends separating peasant agriculture based on the ejido and considered one of the victories of the Mexican Revolution, from agribusiness that requires large-scale land ownership, irrigation, specialized seeds, fertilizers, and pesticides, machinery, and a low-wage paid labor force.

In 1943, the Mexican government founded the International Maize and Wheat Improvement Center (CIMMYT), which became a base for international agricultural research. The government also created the Mexican Agricultural Program (MAP) to be the lead organization in raising productivity. One of their successes was in wheat production with varieties dominating wheat production as early as 1951 (70%), 1965 (80%), and 1968 (90%).

Mexico became the showcase for extending the Green Revolution to other areas of Latin America and beyond, into Africa and Asia. New breeds of maize, beans, and wheat produced bumper crops with proper inputs (such as fertilizer and pesticides) and careful cultivation. Many Mexican farmers who had been dubious about the scientists or hostile to them (often a mutual relationship of discord) came to see the scientific approach to agriculture as worth adopting.

The requirement for the full package of inputs of new strains of seeds, fertilizer, synthetic pesticides, and water were often not within the reach of small-scale farmers. The application of pesticides could be hazardous for farmers. Their use often damaged the local ecology, contaminating waterways and endangering the health of workers and newborns.

One of the participants in the Mexican experiment, Edwin J. Wellhausen, summarized the factors leading to its initial success. These include: high yield plants with disease resistivity, adaptability, and ability to utilize fertilizers; improved use of soils, adequate fertilizers, and control of weeds and pests; and "a favorable ratio between the cost of fertilizers (and other investments) to the price of the produce."

In rice: IR8 and the Philippines

In 1960, the Government of the Republic of the Philippines with the Ford Foundation and the Rockefeller Foundation established the International Rice Research Institute (IRRI). A rice crossing between Dee-Geo-woo-gen and Peta was done at IRRI in 1962. In 1966, one of the breeding lines became a new cultivar, IR8. IR8 required the use of fertilizers and pesticides, but produced substantially higher yields than the traditional cultivars. Annual rice production in the Philippines increased from 3.7 to 7.7 million tons in two decades. The switch to IR8 rice made the Philippines a rice exporter for the first time in the 20th century.

Start in India

In 1961, India was on the brink of mass famine.  Norman Borlaug was invited to India by the adviser to the Indian minister of agriculture Dr. M. S. Swaminathan. Despite bureaucratic hurdles imposed by India's grain monopolies, the Ford Foundation and Indian government collaborated to import wheat seed from the International Maize and Wheat Improvement Center (CIMMYT).  was selected by the Indian government to be the first site to try the new crops because of its reliable water supply and a history of agricultural success. India began its own Green Revolution program of plant breeding, irrigation development, and financing of agrochemicals.

India soon adopted IR8 – a semi-dwarf rice variety developed by the International Rice Research Institute (IRRI) that could produce more grains of rice per plant when grown with certain fertilizers and irrigation. In 1968, Indian agronomist S.K. De Datta published his findings that IR8 rice yielded about 5 tons per hectare with no fertilizer, and almost 10 tons per hectare under optimal conditions. This was 10 times the yield of traditional rice. IR8 was a success throughout Asia, and dubbed the "Miracle Rice". IR8 was also developed into Semi-dwarf IR36.

Wheat yields in least developed countries since 1961, in kilograms per hectare.

In the 1960s, rice yields in India were about two tons per hectare; by the mid-1990s, they had risen to six tons per hectare. In the 1970s, rice cost about $550 a ton; in 2001, it cost under $200 a ton. India became one of the world's most successful rice producers, and is now a major rice exporter, shipping nearly 4.5 million tons in 2006.

Consultative Group on International Agricultural Research – CGIAR

In 1970, foundation officials proposed a worldwide network of agricultural research centers under a permanent secretariat. This was further supported and developed by the World Bank; on 19 May 1971, the Consultative Group on International Agricultural Research (CGIAR) was established. co-sponsored by the FAO, IFAD and UNDP. CGIAR has added many research centers throughout the world.

CGIAR has responded, at least in part, to criticisms of Green Revolution methodologies. This began in the 1980s, and mainly was a result of pressure from donor organizations. Methods like Agroecosystem Analysis and Farming System Research have been adopted to gain a more holistic view of agriculture.

Brazil's agricultural revolution

Brazil's vast inland cerrado region was regarded as unfit for farming before the 1960s because the soil was too acidic and poor in nutrients, according to Norman Borlaug. However, from the 1960s, vast quantities of lime (pulverised chalk or limestone) were poured on the soil to reduce acidity. The effort went on for decades; by the late 1990s, between 14 million and 16 million tonnes of lime were being spread on Brazilian fields each year. The quantity rose to 25 million tonnes in 2003 and 2004, equaling around five tonnes of lime per hectare. As a result, Brazil has become the world's second biggest soybean exporter. Soybeans are also widely used in animal feed, and the large volume of soy produced in Brazil has contributed to Brazil's rise to become the biggest exporter of beef and poultry in the world. Several parallels can also be found in Argentina's boom in soybean production as well.

Problems in Africa

There have been numerous attempts to introduce the successful concepts from the Mexican and Indian projects into Africa. These programs have generally been less successful. Reasons cited include widespread corruption, insecurity, a lack of infrastructure, and a general lack of will on the part of the governments. Yet environmental factors, such as the availability of water for irrigation, the high diversity in slope and soil types in one given area are also reasons why the Green Revolution is not so successful in Africa.

A recent program in western Africa is attempting to introduce a new high-yielding 'family' of rice varieties known as "New Rice for Africa" (NERICA). NERICA varieties yield about 30% more rice under normal conditions, and can double yields with small amounts of fertilizer and very basic irrigation. However, the program has been beset by problems getting the rice into the hands of farmers, and to date the only success has been in Guinea, where it currently accounts for 16% of rice cultivation.

After a famine in 2001 and years of chronic hunger and poverty, in 2005 the small African country of Malawi launched the "Agricultural Input Subsidy Program" by which vouchers are given to smallholder farmers to buy subsidized nitrogen fertilizer and maize seeds. Within its first year, the program was reported to have had extreme success, producing the largest maize harvest of the country's history, enough to feed the country with tons of maize left over. The program has advanced yearly ever since. Various sources claim that the program has been an unusual success, hailing it as a "miracle". Malawi experienced a 40% drop in maize production in 2015 and 2016.

Agricultural production and food security

Technologies

New varieties of wheat and other grains were instrumental to the green revolution.

The Green Revolution spread technologies that already existed, but had not been widely implemented outside industrialized nations. Two kinds of technologies were used in the Green Revolution and aim at cultivation and breeding area respectively. The technologies in cultivation are targeted at providing excellent growing conditions, which included modern irrigation projects, pesticides, and synthetic nitrogen fertilizer. The breeding technologies aimed at improving crop varieties developed through the conventional, science-based methods available at the time. These technologies included hybrids, combining modern genetics with selections.

High-Yielding Varieties

The novel technological development of the Green Revolution was the production of novel wheat cultivars. Agronomists bred cultivars of maize, wheat, and rice that are the generally referred to as HYVs or "high-yielding varieties". HYVs have higher nitrogen-absorbing potential than other varieties. Since cereals that absorbed extra nitrogen would typically lodge, or fall over before harvest, semi-dwarfing genes were bred into their genomes. A Japanese dwarf wheat cultivar Norin 10 developed by Japanese agronomist Gonjiro Inazuka, which was sent to Orville Vogel at Washington State University by Cecil Salmon, was instrumental in developing Green Revolution wheat cultivars. IR8, the first widely implemented HYV rice to be developed by IRRI, was created through a cross between an Indonesian variety named "Peta" and a Chinese variety named "Dee-geo-woo-gen". In the 1960s, when a food crisis happened in Asia, the spread of HYV rice was aggravated intensely.

Dr. Norman Borlaug, who is usually recognized as the "Father of the Green Revolution", bred rust-resistant cultivars which have strong and firm stems, preventing them from falling over under extreme weather at high levels of fertilization. CIMMYT(Centro Internacional de Mejoramiento de Maiz y Trigo – International Center for Maize and Wheat Improvements) conducted these breeding programs and helped spread high-yielding varieties in Mexico and countries in Asia like India and Pakistan. These programs successfully led the harvest double in these countries.

Plant scientists figured out several parameters related to the high yield and identified the related genes which control the plant height and tiller number. With advances in molecular genetics, the mutant genes responsible for Arabidopsis thaliana genes (GA 20-oxidase, ga1, ga1-3), wheat reduced-height genes (Rht) and a rice semidwarf gene (sd1) were cloned. These were identified as gibberellin biosynthesis genes or cellular signaling component genes. Stem growth in the mutant background is significantly reduced leading to the dwarf phenotype. Photosynthetic investment in the stem is reduced dramatically as the shorter plants are inherently more stable mechanically. Assimilates become redirected to grain production, amplifying in particular the effect of chemical fertilizers on commercial yield.

HYVs significantly outperform traditional varieties in the presence of adequate irrigation, pesticides, and fertilizers. In the absence of these inputs, traditional varieties may outperform HYVs. Therefore, several authors have challenged the apparent superiority of HYVs not only compared to the traditional varieties alone, but by contrasting the monocultural system associated with HYVs with the polycultural system associated with traditional ones.

Production increases

Cereal production more than doubled in developing nations between the years 1961–1985. Yields of rice, maize, and wheat increased steadily during that period. The production increases can be attributed roughly equally to irrigation, fertilizer, and seed development, at least in the case of Asian rice.

While agricultural output increased as a result of the Green Revolution, the energy input to produce a crop has increased faster, so that the ratio of crops produced to energy input has decreased over time. Green Revolution techniques also heavily rely on and chemical fertilizers, pesticides, herbicides, and defoliants; which, as of 2014, rely on or are derived from crude oil, making agriculture increasingly reliant on crude oil extraction. Proponents of the theory fear that a future decline in oil and gas production would lead to a decline in food production or even a Malthusian catastrophe.

World population 1950–2010

Effects on food security

The effects of the Green Revolution on global food security are difficult to assess because of the complexities involved in food systems.

The world population has grown by about five billion since the beginning of the Green Revolution and many believe that, without the Revolution, there would have been greater famine and malnutrition. India saw annual wheat production rise from 10 million tons in the 1960s to 73 million in 2006. The average person in the developing world consumes roughly 25% more calories per day now than before the Green Revolution. Between 1950 and 1984, as the Green Revolution transformed agriculture around the globe, world grain production increased by about 160%.

The production increases fostered by the Green Revolution are often credited with having helped to avoid widespread famine, and for feeding billions of people.

There are also claims that the Green Revolution has decreased food security for a large number of people. One claim involves the shift of subsistence-oriented cropland to cropland oriented towards production of grain for export or animal feed. For example, the Green Revolution replaced much of the land used for pulses that fed Indian peasants for wheat, which did not make up a large portion of the peasant diet.

Food security

Malthusian criticism

Some criticisms generally involve some variation of the Malthusian principle of population. Such concerns often revolve around the idea that the Green Revolution is unsustainable, and argue that humanity is now in a state of overpopulation or overshoot with regards to the sustainable carrying capacity and ecological demands on the Earth.

Although 36 million people die each year as a direct or indirect result of hunger and poor nutrition, Malthus's more extreme predictions have frequently failed to materialize. In 1798 Thomas Malthus made his prediction of impending famine. The world's population had doubled by 1923 and doubled again by 1973 without fulfilling Malthus's prediction. Malthusian Paul R. Ehrlich, in his 1968 book The Population Bomb, said that "India couldn't possibly feed two hundred million more people by 1980" and "Hundreds of millions of people will starve to death in spite of any crash programs." Ehrlich's warnings failed to materialize when India became self-sustaining in cereal production in 1974 (six years later) as a result of the introduction of Norman Borlaug's dwarf wheat varieties.

However, Borlaug was well aware of the implications of population growth. In his Nobel lecture he repeatedly presented improvements in food production within a sober understanding of the context of population. "The green revolution has won a temporary success in man's war against hunger and deprivation; it has given man a breathing space. If fully implemented, the revolution can provide sufficient food for sustenance during the next three decades. But the frightening power of human reproduction must also be curbed; otherwise the success of the green revolution will be ephemeral only. Most people still fail to comprehend the magnitude and menace of the "Population Monster"...Since man is potentially a rational being, however, I am confident that within the next two decades he will recognize the self-destructive course he steers along the road of irresponsible population growth..."

M. King Hubbert's prediction of world petroleum production rates. Modern agriculture is largely reliant on petroleum energy.

Famine

To some modern Western sociologists and writers, increasing food production is not synonymous with increasing food security, and is only part of a larger equation. For example, Harvard professor Amartya Sen wrote that large historic famines were not caused by decreases in food supply, but by socioeconomic dynamics and a failure of public action. Economist Peter Bowbrick disputes Sen's theory, arguing that Sen relies on inconsistent arguments and contradicts available information, including sources that Sen himself cited. Bowbrick further argues that Sen's views coincide with that of the Bengal government at the time of the Bengal famine of 1943, and the policies Sen advocates failed to relieve the famine.

Quality of diet

Some have challenged the value of the increased food production of Green Revolution agriculture. Miguel A. Altieri, (a pioneer of agroecology and peasant-advocate), writes that the comparison between traditional systems of agriculture and Green Revolution agriculture has been unfair, because Green Revolution agriculture produces monocultures of cereal grains, while traditional agriculture usually incorporates polycultures.

These monoculture crops are often used for export, feed for animals, or conversion into biofuel. According to Emile Frison of Bioversity International, the Green Revolution has also led to a change in dietary habits, as fewer people are affected by hunger and die from starvation, but many are affected by malnutrition such as iron or vitamin-A deficiencies. Frison further asserts that almost 60% of yearly deaths of children under age five in developing countries are related to malnutrition.

The strategies developed by the Green Revolution focused on fending off starvation and was very successful in raising overall yields of cereal grains, but did not give sufficient relevance to nutritional quality. High yield-cereal crops have low quality proteins, with essential amino acid deficiencies, are high in carbohydrates, and lack balanced essential fatty acids, vitamins, minerals and other quality factors.

High-yield rice (HYR), introduced since 1964 to poverty-ridden Asian countries, such as the Philippines, was found to have inferior flavor and be more glutinous and less savory than their native varieties. This caused its price to be lower than the average market value.  In the Philippines the introduction of heavy pesticides to rice production, in the early part of the Green Revolution, poisoned and killed off fish and weedy green vegetables that traditionally coexisted in rice paddies. These were nutritious food sources for many poor Filipino farmers prior to the introduction of pesticides, further impacting the diets of locals.

Political impact

A major critic of the Green Revolution, U.S. investigative journalist Mark Dowie, writes:

The primary objective of the program was geopolitical: to provide food for the populace in undeveloped countries and so bring social stability and weaken the fomenting of communist insurgency.

Citing internal Foundation documents, Dowie states that the Ford Foundation had a greater concern than Rockefeller in this area.

There is significant evidence that the Green Revolution weakened socialist movements in many nations. In countries such as India, Mexico, and the Philippines, technological solutions were sought as an alternative to expanding agrarian reform initiatives, the latter of which were often linked to socialist politics.

Socioeconomic impacts

The transition from traditional agriculture, in which inputs were generated on-farm, to Green Revolution agriculture, which required the purchase of inputs, led to the widespread establishment of rural credit institutions. Smaller farmers often went into debt, which in many cases resulted in a loss of their farmland. The increased level of mechanization on larger farms made possible by the Green Revolution removed a large source of employment from the rural economy.

The new economic difficulties of smallholder farmers and landless farm workers led to increased. The increase in food production led to cheaper food for urban dwellers, and the increase in urban population increased the potential for industrialization.

According to a 2018 paper, a 10 percent increase in the use of high-yielding crop varieties in developing countries in the period 1960–2000 led to increases in GDP per capita of approximately 15 percent.

Environmental impact

Increased use of irrigation played a major role in the green revolution.

Biodiversity

The spread of Green Revolution agriculture affected both agricultural biodiversity (or agrodiversity) and wild biodiversity. There is little disagreement that the Green Revolution acted to reduce agricultural biodiversity, as it relied on just a few high-yield varieties of each crop.

This has led to concerns about the susceptibility of a food supply to pathogens that cannot be controlled by agrochemicals, as well as the permanent loss of many valuable genetic traits bred into traditional varieties over thousands of years. To address these concerns, massive seed banks such as Consultative Group on International Agricultural Research’s (CGIAR) International Plant Genetic Resources Institute (now Bioversity International) have been established (see Svalbard Global Seed Vault).

There are varying opinions about the effect of the Green Revolution on wild biodiversity. One hypothesis speculates that by increasing production per unit of land area, agriculture will not need to expand into new, uncultivated areas to feed a growing human population. However, land degradation and soil nutrients depletion have forced farmers to clear up formerly forested areas in order to keep up with production. A counter-hypothesis speculates that biodiversity was sacrificed because traditional systems of agriculture that were displaced sometimes incorporated practices to preserve wild biodiversity, and because the Green Revolution expanded agricultural development into new areas where it was once unprofitable or too arid. For example, the development of wheat varieties tolerant to acid soil conditions with high aluminium content permitted the introduction of agriculture in sensitive Brazilian ecosystems such as Cerrado semi-humid tropical savanna and Amazon rainforest in the geoeconomic macroregions of Centro-Sul and Amazônia. Before the Green Revolution, other Brazilian ecosystems were also significantly damaged by human activity, such as the once 1st or 2nd main contributor to Brazilian megadiversity Atlantic Rainforest (above 85% of deforestation in the 1980s, about 95% after the 2010s) and the important xeric shrublands called Caatinga mainly in Northeastern Brazil (about 40% in the 1980s, about 50% after the 2010s – deforestation of the Caatinga biome is generally associated with greater risks of desertification). This also caused many animal species to suffer due to their damaged habitats.

Nevertheless, the world community has clearly acknowledged the negative aspects of agricultural expansion as the 1992 Rio Treaty, signed by 189 nations, has generated numerous national Biodiversity Action Plans which assign significant biodiversity loss to agriculture's expansion into new domains.

The Green Revolution has been criticized for an agricultural model which relied on a few staple and market profitable crops, and pursuing a model which limited the biodiversity of Mexico. One of the critics against these techniques and the Green Revolution as a whole was Carl O. Sauer, a geography professor at the University of California, Berkeley. According to Sauer these techniques of plant breeding would result in negative effects on the country's resources, and the culture:

"A good aggressive bunch of American agronomists and plant breeders could ruin the native resources for good and all by pushing their American commercial stocks... And Mexican agriculture cannot be pointed toward standardization on a few commercial types without upsetting native economy and culture hopelessly... Unless the Americans understand that, they'd better keep out of this country entirely. That must be approached from an appreciation of native economies as being basically sound".

Greenhouse gas emissions

According to a study published in 2013 in PNAS, in the absence of the crop germplasm improvement associated with the Green Revolution, greenhouse gas emissions would have been 5.2–7.4 Gt higher than observed in 1965–2004. High yield agriculture has dramatic effects on the amount of carbon cycling in the atmosphere. The way in which farms are grown, in tandem with the seasonal carbon cycling of various crops, could alter the impact carbon in the atmosphere has on global warming. Wheat, rice, and soybean crops account for a significant amount of the increase in carbon in the atmosphere over the last 50 years.

Dependence on non-renewable resources

Most high intensity agricultural production is highly reliant on non-renewable resources. Agricultural machinery and transport, as well as the production of pesticides and nitrates all depend on fossil fuels. Nitrogen fertilizer is a direct fossil fuel product processed primarily from natural gas. It is estimated that no more than 3.7 billion people of the current world population could be fed without this single fossil fuel agricultural input. Moreover, the essential mineral nutrient phosphorus is often a limiting factor in crop cultivation, while phosphorus mines are rapidly being depleted worldwide. The failure to depart from these non-sustainable agricultural production methods could potentially lead to a large scale collapse of the current system of intensive food production within this century.

Health impact

The consumption of the pesticides used to kill pests by humans in some cases may be increasing the likelihood of cancer in some of the rural villages using them. Poor farming practices including non-compliance to usage of masks and over-usage of the chemicals compound this situation. In 1989, WHO and UNEP estimated that there were around 1 million human pesticide poisonings annually. Some 20,000 (mostly in developing countries) ended in death, as a result of poor labeling, loose safety standards etc.

Pesticides and cancer

Contradictory epidemiologic studies in humans have linked phenoxy acid herbicides or contaminants in them with soft tissue sarcoma (STS) and malignant lymphoma, organochlorine insecticides with STS, non-Hodgkin's lymphoma (NHL), leukemia, and, less consistently, with cancers of the lung and breast, organophosphorous compounds with NHL and leukemia, and triazine herbicides with ovarian cancer.

Punjab case

The Indian state of Punjab pioneered green revolution among the other states transforming India into a food-surplus country. Environmental activist Vandana Shiva has written extensively about the social, political and economic impacts of the Green Revolution in Punjab. According to Shiva, the Green Revolution's reliance on heavy use of chemical inputs and monocultures has resulted in water scarcity, vulnerability to pests, and incidents of violent conflict and social marginalization.

A Greenpeace Research Laboratories investigation of 50 villages in Muktsar, Bathinda and Ludhiana districts revealed that twenty percent of the sampled wells had nitrate levels above WHO limits for drinking water. The 2009 study linked the nitrate pollution with high use of synthetic nitrogen fertilizers.

Norman Borlaug's response to criticism

Borlaug dismissed certain claims of critics, but also cautioned, "There are no miracles in agricultural production. Nor is there such a thing as a miracle variety of wheat, rice, or maize which can serve as an elixir to cure all ills of a stagnant, traditional agriculture."

Of environmental lobbyists, he said:

some of the environmental lobbyists of the Western nations are the salt of the earth, but many of them are elitists. They've never experienced the physical sensation of hunger. They do their lobbying from comfortable office suites in Washington or Brussels...If they lived just one month amid the misery of the developing world, as I have for fifty years, they'd be crying out for tractors and fertilizer and irrigation canals and be outraged that fashionable elitists back home were trying to deny them these things.

The New Green Revolution

Although the Green Revolution has been able to improve agricultural output in some regions in the world, there was and is still room for improvement. As a result, many organizations continue to invent new ways to improve the techniques already used in the Green Revolution. Frequently quoted inventions are the System of Rice Intensification, marker-assisted selection, agroecology, and applying existing technologies to agricultural problems of the developing world. Current challenges for nations trying to modernize their agriculture include closing the urban-rural income gap, integration of smallholders into value chains, and maintaining competitiveness in the market. However, in low-income countries, chronic problems such as poverty and hunger cause agricultural modernization efforts to be constrained. It is projected that global populations by 2050 will increase by one-third and as such will require a 70% increase in the production of food. Therefore, the Second Green Revolution will likely focus on improving tolerances to pests and disease in addition to technological input use efficiency.