Smart/Precision Farming is Swiftly Gaining Popularity;

Smart/Precision  Farming  is Swiftly Gaining Popularity;

Shailesh Saxena

Each second, the world’s population grows by nearly three more people, that is 240 000 people a day. By 2025, the global population will reach 8 billion people and 9.6 billion by 2050, according to the Food and Agriculture Organization (FAO). This means there will be an extra billion mouths to feed within the next decade. And in just one generation, there will be more people additionally on the planet than there were at the beginning of the 20^th century. Sounds improbable? Well, guess again.  With many of the resources needed for sustainable food security already stretched, the challenges are huge. At the same time, climate change is already negatively impacting agricultural production globally and locally. Farms must increase production of food while preserving the environment, but they can’t do it alone and they can’t do it using today’s traditional farming practices.

One way to address these issues and increase the quality and quantity of agricultural production is using sensing technology to make farms more "intelligent" and more connected through the so-called "precision agriculture" also known as ‘smart farming’.

Precision Agriculture or  Smart Farming ; 

 Traditional farming relies on managing entire fields—making decisions related to planting, harvesting, irrigating, and applying pesticides and fertilizer—based on regional conditions and historical data. Precision farming, by contrast, combines sensors, robots, GPS, mapping tools and data-analytics software to customize the care that plants receive without increasing labour. Stationary or robot-mounted sensors and camera-equipped drones wirelessly send images and data on individual plants—say, information about stem size, leaf shape and the moisture of the soil around a plant—to a computer, which looks for signs of health and stress. Farmers receive the feedback in real time and then deliver water, pesticide or fertilizer in calibrated doses to only the areas that need it. The technology can also help farmers decide when to plant and harvest crops.

As a result, precision farming can improve time management, reduce water and chemical use, and produce healthier crops and higher yields—all of which benefit farmers’ bottom lines and conserve resources while reducing chemical runoff.

 Precision agriculture is swiftly gaining popularity among farmers due to the increasing need for optimum production with the given resources. Further, the changing weather patterns due to increasing global warming, have necessitated the adoption of advanced technologies to enhance the productivity and crop yield. By offering technologies such as real-time farm monitoring, weather forecasting, optimal field requirements and similar others, precision agriculture enables farmers to increase the yield with minimum human efforts and wastage. Moreover, the technology enables the farmers to manage their resources as well as access real-time information through their smartphones, thereby offering greater mobility and ease of operation. 

Precision agriculture is gaining in popularity largely due to the introduction of high-technology tools into the agricultural community that is more accurate, cost-effective, and user-friendly.

Technologies for Precision Farming ;

a)             Global Positioning System (GPS) ;

The development and implementation of precision agriculture or site-specific farming have been made possible by combining the Global Positioning System (GPS) and geographic information systems (GIS). These technologies enable the coupling of real-time data collection with accurate position information, leading to the efficient manipulation and analysis of large amounts of geospatial data. GPS-based applications in precision farming are being used for farm planning, field mapping, soil sampling, tractor guidance, crop scouting, variable rate applications, and yield mapping. GPS allows farmers to work during low-visibility field conditions such as rain, dust, fog, and darkness.

Global Positioning System satellites broadcast signals that allow GPS receivers to calculate their position. This information is provided in real-time, meaning that continuous position Information is provided while in motion. Having precise location information at any time allows crop, soil, and water measurements to be mapped. GPS receivers, either carried to the field or mounted on implements allow users to return to specific locations to sample or treat those areas.

b)    Geographic Information System (GIS) ;

Source ; http://blogs.nasscom.in

Geographic Information Systems (GIS) consist of data and software designed for spatial analysis of GPS-referenced data. Various databases in an agricultural GIS system might include soil survey data, soil test information, pest infestations, yield data, remote sensing imagery and other types of observations and records that can be collected and referenced with their geographic position (by GPS). These datasets can then be converted to maps to illustrate their spatial variability within the field and become additional layers in the field database.

The capability of GIS is more than mapping. The real power of GIS software lies in calculations and analysis of the georeferenced data sets to correlate their effects on yields and interactions with other production factors. By using models integrating the different spatially variable data sets, responses to inputs can be predicted, or interactions affecting yield can be identified. Accumulated over time, the GIS datasets become increasingly useful as record-keeping and prediction tools.

c)              Remote  Sensing ;

source ; nasa.gov

Remote sensing is becoming a useful tool for precision farming, using scanners on aircraft or satellites to monitor changes in wavelengths of light from fields and growing crops. Satellite imagery is also useful in a more precise mapping of field boundaries and location of tile drainage lines, for example, and is often most effective when used in conjunction with field scouting ("ground truth observations") to help identify the reasons for variability. The data collected can be mapped and analyzed with the help of GIS tools, to provide additional data layers for GIS analysis and management decisions.

Remote sensing helps to define the extent of problems identified in field scouting by recognizing similar patterns. It is used to document such issues as pest problems, weather factors, nutrient management issues, and more.

d)    Smartphone-Based  Sensors ;

Smartphone usage in third-world countries is playing a vital role in the enhancement of farmer's businesses towards agriculture. Recently, communication through smartphones has been considered very important in enhancing farmers’ access to better understand the agricultural market situation. Farming communities appreciate smartphones as an easy, fast and convenient way to communicate and get prompt answers to respective problems. Smartphones have become a useful tool in agriculture because their mobility matches the nature of farming, the cost of the device is highly accessible, and their computing power allows a variety of practical applications to be created. Moreover, smartphones are nowadays equipped with various types of physical sensors( e.g., positioning sensors, motion sensors, and cameras microphones ) which make them a promising tool to assist diverse farming tasks.

e)              Robotics / Drones ;

Source; https://agfundernews.com

It’s an all-around exciting time to deploy robots on farms, and there is a clear need to do so given the drive for increased food production, and sustainability. Steps are currently being made to develop the technology that will enable the automation of individual tasks before integration in a “digital farm” that will empower farmers to run operations in a fulfilling and efficient way.

Robots are taking on many tasks in agriculture these days (with varying levels of success), including planting greenhouse crops and pruning vineyards. And there’s been no shortage of activity in agronomic crops. The biggest push has been for autonomous machines that are remotely controlled using telematics.

 Autonomous robots have already been demonstrated in many agricultural activities. Conventional tasks such as tilling, sowing, harvesting of grains, can be performed using autonomous robots with the accuracy provided by the vehicle itself (currently about ±2 cm when using GNSS technology). For other tasks that demand the use of vision to follow trajectories, the current accuracy is approximately ±7 cm.” When it comes to using robots with intelligent tools, the achievements are promising.

“Autonomous tractors carrying herbicide sprayers coordinating with drones equipped with weed-detection systems have proven to save up to 75% of the herbicide. Autonomous tractors equipped with onboard weed detection systems are able to kill 90% of weeds on a field.” robots navigate plant rows, sense the plants, and send the data to the farmers to help optimise seed breeding. If equipped with a “weed puncher”, the robot can literally drive weeds into the ground. Deepfield Robotics also provides smart sensors that can be positioned in the fields. Resulting networks are already deployed in farms to monitor soil conditions

f)   Irrigation   Technologies ;

source;gvaco.com

Farmers today are highly motivated to use as little irrigation water as possible. One way to conserve is through the “hardware”, i.e., to migrate to more efficient irrigation methods, such as drip or spray irrigation. These methods reduce unnecessary surface water runoff as well as loss of water through evaporation.
In order to make irrigation even more precise, farmers are adopting centralized command and control solutions that analyse crop, soil and weather data in order to optimize when and how much any given field should be irrigated.

Innovations in precision irrigation technologies are growing even more crucial as growers face water scarcity due to drought, aquifer depletion, and water allocations. Products now allow growers to remotely monitor and control nearly every facet of their irrigation operation. The systems save water, time, fuel, and wear and tear on vehicles. producers will be integrating soil moisture monitoring, weather data and variable-rate irrigation (VRI) into their systems. Precision Mobile Drip Irrigation as another major advance. PC dripline is pulled through the field by a center pivot or linear move irrigation system. As the driplines are pulled behind the system, the integrated emitters deliver a uniform pattern across the full length of the irrigated area. Because the driplines deliver water directly to the soil surface, evaporation and wind drift are virtually eliminated, allowing more water to reach the root zone.

g)              Internet of Things  (IoT) ;

source;https://www.livemint.com 

IoT-based smart farming, a system is built for monitoring the crop field with the help of sensors (light, humidity, temperature, soil moisture, etc.) and automating the irrigation system. The farmers can monitor the field conditions from anywhere. IoT-based smart farming is highly efficient when compared with the conventional approach.

The idea has been demonstrated in the consumer market in the “connected home,” for instance, where appliances, security systems, and the like communicate with each other and the homeowner. connected components in agriculture could include field sensors (for logging real-time weather, soil moisture, and temperature data) and aerial/satellite imagery for field monitoring. Such device communications could also be used in dispatching programs, sales interaction tools, and other business management applications.

Most recently, a number of ag start-ups and component suppliers (hardware, software, etc.) are using LPWANs (Low Power Wide Area Network) in place of or to augment cellular networks in wireless data transmission. “These networks are designed to carry small amounts of data transmitted intermittently over long ranges,” Because the devices that communicate with the LPWA networks do so with very low power, their battery lives are substantially longer than the current cellular offerings. This coupled with low-cost network usage provides a very compelling total cost of ownership advantage over other options.

h)            Sensors ;

source ; http://www.libelium.com

Hi-tech systems are in demand to help grow high-performance crops. Researchers are using sensors to match the crops to different soils and weather conditions.

Wireless sensors have been used in precision agriculture and/to gather data on soil water availability, soil compaction, soil fertility, leaf temperature, leaf area index, plant water status, local climate data, insect-disease-weed infestation, and more. Perhaps the most advanced and diverse technologies to date are found in water management. Across the country, increased regulation of water use and water scarcity will continue to drive improvements in this area.

On-the-go sensor information has become more valuable as well. On-board applicator options developed over the past few years include GreenSeeker (Trimble), OptRx (Ag Leader), and CropSpec (Topcon). They communicate real-time crop health conditions to help immediately tailor product applications.

Another innovation?  Weed Seeker, Trimble’s weed detection sensor made for precise site-specific application of herbicides. Its use is growing in geographic regions where weeds have developed a tolerance to standard glyphosate-based broad-spectrum herbicides

 i)Variable Rate Seeding ;

source ; http://cema-agri.org

Given all the newer/exciting technologies for precision agriculture on this list, it might be a surprise to see variable-rate application (VRA) seeding here. According to Sid Parks, Manager of Precision Farming for GROWMARK, this has been able to maintain its importance in part because of its nature. It appeals to a growers’ natural inclination to try to maximize a field to take advantage of all of the possibilities of increasing the yields possible by paying extra attention to the factors that impact seed growth “It’s a little different than variable-rate fertilizer because VRA seeding relies on your ability to gather accurate data for the start of the agricultural process, the seed itself.”

Another factor working in VRA seeding’s continued importance to overall precision agriculture is the fact it as a category has plenty of room to grow. “Although folks have been using VRA seeding practices since the mid-1990s, it still is probably only being used on 5% to 10% of the planted acres today “But the ability to gather good, useful data for VRA seeding is getting much better, so the chances of more growers using this practice in their yearly operations will continue to improve going forward.”

 j)Weather   Modelling  Techniques ;

No one is unaware of the unmatched power of nature and it's ever-changing and uncertain persona which leaves us unsure of what turn it may take next. It is said and believed that Mother Nature is unpredictable and has many secrets hidden in itself that are beyond our imagination. We humans in an effort to predict nature have switched from the traditional method of weather forecasting and with help of Internet of Things (IoT)prediction of weather condition have taken another step ahead towards attaining higher accuracy and flexibility.

But help is on the way. “Over the past 25 years, you’ve gotten a lot of important technologies developed that would be even more valuable with quality weather modelling, but we are now at a point where assuring good crop yields is key to making certain the world has food solutions that work,”

An example of this, harvesting potato crop at a certain temperature is key for maintaining crop quality and integrity. In the past, this grower sent scouts out into the field to manually assess soil temperatures before sending in the harvest equipment. “But by using clearAg, the growers are now able to take all their soil readings remotely and they are able to accomplish his harvest a lot more efficiently than ever before. .

 k)  Nitrogen Modelling ;

source;http://www.cleantechconcepts.com/

Although some forms of variable-rate fertilizer have been used for decades, nitrogen modelling has become more pronounced recently. “However, the complexity of the nitrogen cycle and how it is in a constant state of flux has always made managing nitrogen difficult.”

Recently, SST Software has partnered with Agronomic Technology Corp. (ATC) to introduce Adapt-N.  Adapt-N was first introduced in 2014 and is becoming an important tool for properly managing nitrogen use. “There’s a belief in agriculture that today’s environmental pressures will only get worse as the industry moves forward,” The vast of majority of growers want simple methods to use to be able to address these concerns. That’s what Adapt-N and other nitrogen modelling  processes are currently bringing to the table.”

Precision Farming key challenges ;

a)             Improving GNSS Signal Availability;

source; http://www.oxts.com

GPS alone does not provide sufficient field coverage in many farm environments. Hilly or mountainous terrain is rare, but tree lines are a common issue Reliability of the signal has been a barrier to adoption  The majority of growers 10 years ago were unfamiliar with GPS. Today many growers are educated enough in GNSS to ask about signal availability and reacquisition.

Most high-precision systems sold in North America now offer GLONASS capability to augment GPS for signal availability. As more satellite signals-in-space become available, availability will continue to improve in these difficult environments, and more growers will view GNSS as a reliable solution for their needs.

b)           Interoperability of different standards ;

With more and more OEMs coming up with new and innovative agricultural  IoT tools and platforms, interoperability is rapidly becoming a point of concern. The various available tools and technologies often do not follow the same technology standards/platforms – as a result of which there is a lack of uniformity in the final analysis done by end users. In many instances, the creation of additional gateway(s) becomes essential, for the translation and transfer of dataacross standards. As things stand now, precision agriculture (while evolving rapidly) is still, to a large extent, fragmented. The challenge lies in transforming the smart standalone devices and gateways to holistic, farmer-friendly platforms. The call for compatibility across equipment manufacturers’ components — primarily through ISOBUS standards — continues to go out. Official initial efforts to implement this began about eight years ago with the formation of the Agricultural Industry Electronics Foundation. The group now includes more than 170 companies, associations, and organizations that are actively collaborating to make the standards work.

c)              Making sense from big data in agriculture

The modern, connected agricultural farm has, literally, millions of data points. It is, however, next to impossible to monitor and manage every single data point and reading on a daily/weekly basis, over the entire growing seasons (neither is it necessary). The problem is particularly bigger in large, multi-crop lands and when there are multiple growing seasons. The onus is on the farmers to find out which data points and layers they need to track on a regular basis, and which data ‘noise’ they can afford to ignore. Digital agriculture is increasingly becoming big data-driven – but the technology is helpful only when users can ‘make sense’ of the available information.

d)             Size of individual management zones

Traditionally, farmers have considered their entire fields as single farming units. That approach is, however, far from being effective for the application and management of IoT in agriculture. Users have to divide their lands in several smaller ‘management zones’ – and there is quite a lot of confusion regarding the ‘correct’ size of these zones. The zones have to be divided with respect to the soil sampling requirements (different zones have varying soil qualities) and fertilizer requirements. The number of zones on a field, and their respective sizes, should depend on the overall size of the growing area. There is not much of reference work for the farmers to go by, while trying to divide their lands in these zones. As an alternative, many farmers continue to follow uniform fertilizer application and/or irrigation methods for the entire farm – leading to sub-optimal results.

e)              Non-awareness of the varying farm production functions

In-depth economic analysis needs to complement internet tools, to ensure higher yields on farms. Users need to be able to define the correct production function (output as a function of key inputs, like nutrients, fertilizers, irrigation, etc.). Typically, the production function is not the same for all crops, differs in the various zones of a farm, and also changes over the crop/plant-growth cycle. Unless the farmer is aware of this varying production function, there will always remain the chance of application of inputs in incorrect amounts (spraying too much of nitrogen fertilizer, for example) – resulting in crop damages. Precision agriculture is all about optimizing output levels by making the best use of the available, limited inputs – and for that, the importance of following the production function is immense.

f)                Barriers to entry for new firms

Although precision farming has been a subject of considerable interest for several years now, the concept is still relatively ‘new’. As such, the big hardware/software manufacturers that entered this market at an early stage still have a definite ‘first-mover advantage’. The lowly competitiveness of the market can prevent new firms from entering this domain – with the existing big firms retaining a stranglehold. Farmers can also face problems while trying to migrate data streams from an older platform to a newer one, and there are risks of data loss. The resources and platforms provided by a big player in the agro-IoT sector might not be compatible with those provided by a smaller OEM – and that might prevent the latter from having enough clients.

Conclusion ;

Many believe that the benefits of precision agriculture can only be realized on large farms with huge capital investments and experience with information technologies. Such is not the case. There are inexpensive and easy-to-use methods and techniques that can be developed for use by all farmers. Through the use of GPS, GIS, and remote sensing, information needed for improving land and water use can be collected. Farmers can achieve additional benefits by combining better utilization of fertilizers and other soil amendments, determining the economic threshold for treating pest and weed infestations, and protecting the natural resources for future use.

The concept of precision agriculture is based on four pillars – Right place, Right source, Right quantity and Right time. It has already made a difference to agriculture and farm yield performance worldwide…and once the aforementioned challenges are overcome, its benefits will become more evident, more sustainable.

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