E-Technology in aid of farmers

E-Technology in aid of farmers

1. Introduction:

Discuss the role of ICT/e-Technology in Agriculture?

• E-technology is broadly understood to include the Internet and related information technologies, digital technologies and in recent years, its use has grown rapidly.
• Indian agriculture sector has still not been able to overcome the digital divide that is prevalent since so many years in rural development scenario. Here’s why it is high time to fill the digital gap for farmers.
• The e-Technology can be utilized through three basic pillars, i.e.
• Agri-extension & Information + Services+ Research = Digitally empowered farmer

• Agriculture is the world’s first solar powered factory. It organises human effort to capture the life force hidden in seed and sunlight, to process the elements in the soil, air and water, into produce. Agriculture converts hard natural elements into useful material for use of mankind. Agriculture, in itself, is not digital but a very material physical process. Like in all other parts of one’s life, there is increasing use of electronic devices, tools and a fusion of digitised systems, to manage agricultural processes.
• Hence, the phrase “Digital Agriculture”, a recently coined catch-phrase seems a misnomer – it actually refers to the use of digital technologies in managing the business of agriculture. ‘Digital Technologies in Agriculture’ is probably the more accurate narrative.

2. Why ICT in Agriculture Extension so important for Farmers, especially in India

• Rightly said “Everything will go wrong if farm economy goes wrong”, e-Technology will certainly help in enhancing the production and reducing the cost of cultivation, which is ultimate goal of any farmer.
• Agriculture rests on three basic pillars that is teaching, research and extension. As India is a huge country with multiple limitations like geography and agro-climatic zones, population, Language and way of cultivation practices it is very difficult to transfer the technology on individual basis to each farmer. The number of Agriculture extension service professional per 1000 farmer is very less, so ICT and e-technology will play an important role in Indian scenario. According to a recent report, it has been revealed that mobile internet access can increase a small farmer’s revenue by 50%.

• Countries like China and USA have very strong network of Agriculture extension, since India is now know for its Information Technology Might all over the world we can also use this opportunity to strengthen agri extension services through e-Technology as physically it will not be possible due to limitations listed above.

3. Transformational role of Digital Technology

How Digital Technology is transforming the Agriculture?

• In many developed countries, farming has been modernised by a wave of technologies, adopted at farm level. In emerging economies too, agriculture is becoming “Industrialised”, and spoken of as a “Value System”.
• Digital technologies are finding increasing use in the agricultural value system, and farmers are increasingly becoming more informed, as various measures are taken to provide them ready access to technology and information.
• High-tech farming is becoming the standard, thanks to use of sensors, logic controlled systems, data analytics, etc. In India, the increasing availability of energy and internet connectivity to the large rural landscape is further accelerating such changes. This transformation will continue as linkages with international markets also get expanded and get more robust.
• Example – Digital Spectrogram – Transforming soil health and ecology The impact on total yield through use of intensive farming technologies is already well known, as well the ecological impact from misuse of chemical and natural resources. Now, for example the government’s universal soil health card scheme, can give farmers access to information on their soil health status, which can be used to decide on optimal use of various resources as inputs. This system, as it is made more real-time, will bring transformational changes to the cost of cultivation/production and the sustainability of farms. There are technologies where soil health can be assessed without transmitting the soil physically to a lab, but merely by taking a spectral image of a soil sample. The digital spectrogram can be compared against a large database and spectral analysis can diagnose the contents of the sample. This analysis can happen in the cloud, and results communicated to the farmers almost instantaneously. There exist various similar technologies where a sample from a field, gets converted into digital information, is promptly analysed to provide accurate results, which then allows farmers to take decisions best suited to the land they farm on.
• Example – Technology in conserving water A little less than half of agriculture is now being practised in irrigated conditions, though a large share of agricultural land remains rainfed. This is being further refined through applying straightforward mechanisms like micro-irrigation, fertigation and protected cultivation systems. The next stage of interventions will extensively use specialised sensors to assess soil moisture and composition, to send signals to actuators that control sluices and pumps, to initiate a controlled flow of water with precise dosage of nutrients; and this can all be done without immediate human interface. This technology will optimise on water resource use and reduce current state of drudgery where farmers need to wake up pre-dawn to water the fields and is an example how technologies will bring rapid and drastic change to past irrigation practices. In protected cultivation, sensor based systems are also used to monitor internal humidity and light conditions and automatically trigger lighting adjustments, fan-pad systems, etc. Such activities are also digitally transmitted for record keeping and can allow remote controlling the operations by the human interface. In fact, such technology adoption will warrant and kick in new skills and practices in farming, such as calibration and managing pumps, valves, irrigation lines, soil sensors and for measuring, mixing and testing of nutrient mixtures, etc. It is going to usher in a positive disruption in how farmers function and the technologies they use.

4. Remote sensing in Agriculture

• Remote sensing fundamentally made use of visible, near infrared and short-wave infrared sensors to form images of the earth’s surface by detecting the solar radiation reflected from targets on the ground.
• As technology developed further, and resolutions improved, remote sensing has advanced to also detect and identify heat signatures of planted crops and animals. Similarly, moving beyond sonar, ocean temperature maps are used to show upwelling and chlorophyll distribution to identify coastal productive zones, use side-looking airborne radar to detect shoals of surface swimming fish, etc.

4.1 Crop classification & acreage estimation

• In case of crop cultivation, remote satellite or drone based imagery can assist in crop classification.
• The most important would be estimation of acreage under cultivation to arrive at production estimates.
• Further, applications would be to accurately evaluate crop losses, spread of disease, monitor bio-diversity, impact of agro-ecology, etc. All of this would be a boon for relevant crop planning and guide farmers in attendant efforts, so as to make their enterprise sustainable in economically and environmental terms.

4.2 Geographical information system

• Geographical Information System (GIS) is usually a set of computer tools and is a unique platform that allows one to work with multiple data that are tied to a spatially mapped location or area on earth.
• This allows for multiple data of varied detail to be graphically depicted on a map and thus providing visual and other indicators to ease associated decision making. Advanced computer technology can now support provision of query based information and allow for the rapid computer analysis, for use at individual farms and across large territories.
• GIS tools and analytics can accurately depict the collection of data on, crop acreage, production, crop health, disease and also maintain geo-database of farmers.

4.3 Cropping Cutting Experiment

• Nevertheless, CCE methods are time-consuming and costly, prone to large errors due to incomplete ground observations, and often lead to poor crop yield and crop area estimations.
• Recent advancements in technology have made it possible to rely on high-resolution satellite data sets on periodic basis. Reliable and timely information on crop area is extracted very efficiently, which can be correlated with yield data. This will aid in more accurate crop production estimations, add transparency to the system and speed up the crop insurance processes.

4.4 Crop health monitoring

• Research and advanced technologies in the field of remote sensing have enhanced the ability to detect and quantify physical and biological stresses that affect the productivity of agricultural crops.
• The district-wise crop health condition assessment is possible for major crops, viz, cotton, groundnut, paddy, wheat, potato, rapeseed, gram, tobacco, cumin, jowar, etc., using vegetation index computed from multi-date atmospherically corrected high-resolution satellite data.
• The scientific basis to the assessment of the crop condition/health assessment is on account of the determination of NIR (Near Infra-red) and red reflectance for a crop, primarily by the internal leaf cellular structure and chlorophyll content respectively.
• In principle, any damage to chlorophyll content due to pest, disease, nutrient stress, or delay in crop sowing manifests itself indirectly through an increase in Red reflectance, lowering indices value. Further, these stresses can also lead to the destruction of leaf internal cellular structures resulting in lower NIR reflectance. Hence, crop vegetation indices values can also be used to detect and flag stressed crop.

4.5 Drones in agriculture

• Technology has changed over time and agricultural drones are a good example of this. Today, agriculture is one of the major adopters of drones in management. Drones can be ground-based and aerial-based and are increasingly used for field analysis to monitor crop health, irrigation, pesticide management, planting, etc.
• Drones currently operate at 0.5 – 10 cm resolution and aerial drones (UAV – unmanned aerial vehicle) can fly close to the surface of the canopy of natural stands or crops.
• Drones can be used for conducting aerial surveys at regular interval to study the difference in land use, crop loss assessment, crop health imaging, and integrated GIS mapping.
• The uses of drones for gathering valuable data via a series of sensors, multispectral, thermal, and visual, for use in analytics, mapping and surveying of agricultural land. Near real-time disaster survey can be carried out using drones. The operators can enter the coordinates of the field to survey and select an altitude or ground resolution.
• When pesticide spraying is taken up using drones, waterbodies on the field can to be avoided if previously mapped. Depending on the sensors deployed on a drone, various data can be captured, such as plant health indices, plant counting, plant height measurement, canopy cover mapping, field water poising mapping, scouting reports, stockpile measuring, chlorophyll measurement, nitrogen content in the crops, drainage mapping, weed pressure mapping, and so on

5. ICT BASED SUPPORT FOR FARMERS

• The Ministry of Agriculture & Farmers’ Welfare targets improved awareness and knowledge efficiency of farmers. A comprehensive ICT strategy has, therefore, been developed not only to reach out to farmers in an easy and better way, but also for planning and monitoring of schemes so that policy decisions can be taken at a faster pace and farmers can be benefited quickly
  • National e-Governance Plan –In agriculture, availability of real time information at the right time is the major miss. Lack of information at proper time causes a huge loss to farmers, proving the adage, ‘information is knowledge and knowledge is power’. NeGP-A aims to bridge this gap in communication by using technology. It provides an integrated approach to the delivery of services to the farming community using ICT. Under NeGP-A, around 60 online services have been developed over the last few years and launched to provide ease of access and timely information to farmers. Some services have been developed for monitoring of schemes, so that quick analysis and reporting can be done.
• To empower different sections of rural areas, different ICT strategies have been devised and are listed below:
• Those who have access to digital infrastructure can get the information through websites/web portals.
• Those who have smart phones can access the same information through mobile apps.
• Those who have basic phones, can get this information through SMS advisories sent by experts. · Farmers can also call at the toll free number of Kisan Call Centre – 18001801551.

5.2 Agriculture 2.0 (Digital Agriculture)

• Under Digital India interventions, the Government has given prominence to ensuring availability of information on various agriculture and allied sectors activities, to improve the agricultural output.
• Agriculture 2.0 (Digital Agriculture) directly falls under Pillar No. 5 of Digital India, e. eKranti – Electronic Delivery of Services and broadly caters to other pillars as well, like e -Governance: Reforming Government through Technology, Information for All and Early Harvest Programmes.
• Some of the key thrust areas identified under Digital India for Ministry of Agriculture & Farmers’ Welfare are incorporation of space technologies, development of mobile apps, GIS Mapping, citizen-centric services for Cooperation, fertilizer testing labs, cold-chain availability, identification & development of services for specific sectors of horticulture and fisheries, use of crowd sourcing, increasing online transactions, and use of innovative technologies like text to speech, image recognition; as also Big Data Analysis and Data Intelligence, Direct Benefit Transfer etc.

6. Upcoming Advanced Technologies in aid of Agriculture & Farmer

• Upcoming Technologies Developing technologies such as Big Data Analytics, Internet of Things (IoT), Block Chain, Artificial Intelligence, Robotics & Sensors, etc. are inter-related and are used to optimise the decision making process, and the operating procedures of every sphere where they find application.
• These technologies are practices that are deeply inter-woven with computerised systems, complex digitised interactions and even self-learning models.
• In contrast, agriculture involves earthy processes such as attending to soil & water management and cultivation, managing the production and supply of goods.
• However, agriculture, despite being civilization’s primary organised production process, continues to be subject to uncertainties across various involved disciplines.
• Not only has agriculture moved beyond sustenance farming into commercial production, it now touches more lives than the population immediate and local to the producing region. Its circumference of influence is only bound to widen as rural population moves into urban agglomerations, and nations gets globally integrated.
• So with evolving agriculture these modern technologies will play an important role in agriculture in coming days

6.1 Big data from agriculture – BDA

Q. Discuss the role of Big data Analytics, Internet of Things and Block Chain technology in Agriculture ?

• Farms and farmers provide large amounts of data, which need consolidation and analytics for strengthening agricultural system.
• The various on-farm cultivation systems, when integrated with the market system, agricultural demand and made responsive to such integration, makes for an optimal agricultural value system.
• The desired integration of physical activities requires intelligent management and assessment of complex and voluminous data.
• Big data analytics provides the opportunity to systemise the large amount of widely dispersed data that is generated from agricultural and allied activities.
• Farms and farmers produce big data, which need interpretation using Information technology for transforming the agricultural value system.
• To illustrate, Agricultural Census data on about 138.5 million Operational holdings itself constitutes a very large database (VLDB).
• As automation use in on-field and off-field machinery increases, large data from sensor technology will also be available. Such sensors are already seen in irrigation system, temperature control equipment, soil monitoring equipment, etc.
• The physical measurement and monitoring mechanisms, deployed through mobile imaging, satellite imagery, drone patrolling, GPS / RFID (Geo Positioning System/Radio Frequency Infrared Data) tracking and production traceability, will all require support from big data management and analytics.
• National projects viz., Agmarknet, eNAM, Animal Health, Soil Health and such others, generate data at micro-level granularity and require extensive analysis at national, state, district and sub-district levels, if a comprehensive meaning is to be made of this data. It is not pertinent for this Committee to list all the various data sources and their uses in agriculture as the list is itself voluminous. Such data can be developed as “Data Marts” for utilisation.
• The analysis will not only help at an operational level, but also assist policy makers by identifying structural weaknesses, priority areas and improve monitoring capabilities. Harnessing big data, for weather-index based insurance, financial and credit programs, are also viable propositions to manage financial, weather and climate risks.
• Long standing data, when compiled in a comprehensive and standardised manner, helps to unearth previously hidden patterns, provides correlation between perceived disjointed activities and opens new insights into the management and governance mechanism.
• The main challenges in managing big data is collecting and collating the data, data storage, rights to the data and data analysis, querying, and transfer.
• Big Data Analytics gets its penetration by adopting technologies viz., Social Computing, Internet of Things (IoT), Data Virtualization, Statistical Methods and Machine Learning, Data Science Methods and Tools, Data Mining Algorithms, Data Analytics Processes, Platforms, and Practices, and Information Visualization Tools and Dashboards. Big Data Analytics is still at an early development stage in India. However, government agricultural development schemes (spread across the entire agricultural value system), AGMARKNET/e-NAM, Soil Health Card, National Animal Disease Reporting System (NADRS), Kisan Call Centre Database, DBT schemes and others, are already driving the need for adoption of Big Data Analytics in the agricultural sectors.
• BDA for PMFBY: In schemes like Pradhan Mantri Fasal Bima Yojna (PMFBY – crop insurance scheme), use of Data Analytics can actually help in drawing inferences and making policies. Crop sown area of a state is known. It can be juxtaposed with insured statistics – analysis can be done to find reasons for lower or over insurance. Similar other factors can also be examined by putting more layers like Cadastral Maps on top of sown & insured area. Since conducting crop cutting experiments is a costly affair and requires lot of resources, major challenge is to reduce the number of CCEs so that experiments can be done at selected locations only. Satellite data and weather data can be utilised to cluster groups of Insurance Units (IUs) by mapping them homogeneously expecting similar yield/vegetative index mapping. On the basis of vegetative index, crop areas can be categorised in different groups and for each group, defined number of CCEs can be conducted to arrive at yield of areas. Currently to make sure that CCEs are actually happening, one has to go through each and every picture. Simple artificial intelligence techniques can be used so that images can be recognised and odd ones can be removed from the lot, and any initial recognition discrepancies can be relearned by the system.
• Commodity Price forecasting is another area, where Big Data Analytics can help in a major way. The prices of the commodities fluctuate significantly. The price forecasting information can help the farmer to know the price in advance, and use this input to take an appropriate decision on whether to sow that particular crop or not. Price Forecasting will also help Government in taking decisions on fixing MSP, Import-Export duty and other policy decisions etc. The prices of the yield are not same across all the local markets. So it is necessary to provide forecasted price information for local market-wise, district-wise, state-wise and nationwise. Closely linked to price forecast is, demand forecast, in which case too Big Data Analytics is useful. Rapid proliferation of mobile technologies in rural areas can allow farmers improve productivity based on the information received after Big Data Analysis

6.2 Internet of Things (IoT)

• In agriculture Internet of Things (IoT) basically means the internet inter-connectivity of all connectable things. The things, include people and devices, i.e. anything that outputs or can use a ‘yes/no’ or ‘on/off’ signal.
• It connects the otherwise disconnected and disjointed machines. Further, IoT is a giant network of things which results in a connected relation between people-people, people-devices and devices-devices. This allows the things to digitally interact to trigger action or decisions, on the basis of usable information or pre-determined ‘flags’.
• As a technology, IoT takes forward the networking of traditional devices like desktops, phones and tablets, to a wider range of everyday things like appliances, sensors, vending machines, automobiles, etc. In a local network, such connectivity can be seen in use in factories or buildings, where a closed circuit system streams data internally (say visual, humidity or temperature sensors) – when this information is made accessible over the internet, the local web would be a part of Internet of Things.
• IoT facilitates the remote access to active information. For example, a farmer visiting the local market, can access his in-field soil sensor to decide on what fertilizer to buy, or remotely access the health parameters of his livestock.
• Moving ahead, the Web of Things (WoT), is a refinement of the Internet of Things by integrating smart things not only into the internet (network), but into the Web Architecture (application), for ease of use and bring a higher level of maturity for scalability and sustainability.
• Draft IOT Policy of the Ministry of Electronics and Information Technology (MeitY) addresses IoT in Agriculture and Irrigation and provides incentives to capture investors’ interest.
• IoT can be used in precision farming, pest management and control, soil monitoring water management, food production and safety, and livestock. Just about every branch and activity in agriculture and food need the support of sensing and interpretation of sensor data. Indeed, the whole network of future sustainable agricultural and food technologies, capable of dealing with climate change and population growth, will benefit from an internet connectivity of the things involved.

6.2 Artificial Intelligence

Human Intelligence propelled agriculture now it’s time for AI

• Artificial Intelligence (AI) takes automation to another level, by incorporating analysis and learning on the basis of past and current data. It further, adds the scope of automation even in decision making, where the integration of multiple and varied information is interpreted to balance a desired set of outcomes, which could themselves be variable.
• The vastness and complexity in agriculture makes it a very promising field for application of AI technology.
• Artificial Intelligence supports in decision making, provided through machine and digital learning processes.
• Human intelligence can take long to assimilate, understand and react to all the complex variables that comprise the uncertainties that agriculture is subject to. This tends to promote a word-of-mouth method of activity, promoting copy-cat decisions or dependence on more traditional decision taking.
• Artificial Intelligence can help make better sense of the inherent fuzzy data and rapidly put out answers from extremely complex inputs. Further, the logic improves with learning and these factors make AI suited as an agricultural technology.
• Farmers can benefit not only from the direct on-farm applications of AI, but also from its use in the development of improved seeds, crop protection, and fertility products.
• Besides the unpredictable biological and weather related processes during cultivation, agriculture is also dependent on variables from multiple market situations. In this complex situation, AI can offer more reliable predictions, to be used as a basis for planning and control of all agricultural activities. Applications based on AI require large amounts of data to properly train the algorithms.
• AI Powered Chat bots: Its (AI) deployment is a natural corollary of large data warehousing (big data) and automation. The use of ICT by way of interactive communication with farmers, also creates opportunity for AI powered chat-bots (which are conversational virtual assistants who automate interactions with end users). These can use machine learning techniques, understand natural language and interact with users in a personalised way, giving advice and recommendations on specific farm problems.
• Cognitive technologies allow analysing and correlating information about weather, type of seeds, types of soil or infestations in a certain area, probability of diseases, data about what worked best, year to year outcomes, market trends, prices or consumer needs; and in the final analysis facilitate farmers to make decisions to maximise on crops and livestock output.
• Remote sensors, Satellites, and UAVs (Unmanned Aviation Vehicles) gather information 24 hours per day over an entire field, so as to monitor plant health, soil condition, temperature, humidity, etc. Thus, IOT and AI are the two technologies having progressive impact on agriculture and its future.
• ATMA/KVK: It may also be appreciated, that two of the important Public Extension Service Centres, are Krishi Vigyan Kendras (KVKs) and Agricultural Technology Management Agencies (ATMA). Both these are well positioned to be the nerve centres for AI applications, and for knowledge diffusion among India’s vast farming community.
• I-Hub: In an effort to integrate Agriculture and Information Communication Technology (ICT), ICRISAT established the ihub on February 13, 2017 – “i” stands for innovation, integration, inspiration and impact. The platform offers a model to scale science-based solutions through entrepreneurs and works closely with T-Hub, India’s largest start-up incubator. Some examples of ihub start-ups include business solutions that use Artificial Intelligence (AI) to identify pests and diseases, market integration, real-time monitoring and evaluation and UAV-supported precision agriculture recommendations
• Crop and soil management With the development of AI technology, it is easier to keep a track and predict the right time for planting, irrigation, and harvesting. The advanced sensors and technologies, make the entire task of crop and soil management uncomplicated for the farmers.
• Pest attack prediction Common pest attacks, such as jassids, thrips, whitefly, and aphids can pose serious damage to crops and impact crop yield. Use of AI and machine learning can indicate in advance, the risk of pest attack. This empowers the farmers to plan in advance, and benefit from reduced crop loss due to pests and as a result realise higher farm returns.
• Image recognition Artificial Intelligence can also be used for recognizing weeds and assessing plant health. Use of AI can differentiate between plants and weeds by leveraging big data, and actively sprays weedicides on the weeds, but ignores the plants.
• Animal husbandry Animal husbandry is an integral branch of agriculture concerned with the care and management of the livestock. It deals with all the tools and technologies involved in managing and ensuring optimum health of farm animals, including genetic qualities and behaviour. Generating and leveraging useful information through AI will help farmers to manage their livestock efficiently with minimum supervision. With AI enabled smart sensors, the automated milking units can analyse the milk quality and flag for abnormalities in the product

6.3 Blockchain technology for agricultural value system

• Blockchain is a database system, created by an unknown person or persons (named Satoshi Nakamoto), that maintains and shares a transparent immutable record of the history of the transactions.
• In the traditional world, such a record of transactions or ledger, would be maintained individually by each transacting party. Individual ledgers require to be reconciled when settling accounts, and the method was open to corrections and manipulations. This manual and individual keeping of records was common in the banking system, where the account holder would reconcile own ledger periodically with the bank provided passbook. Individual ledgers maintained by each transacting party, especially when transactions are complex, made the system inefficient, paper laden, and allowed for human error or fraud, and in result leading to disputes at reconciliation stage. In the blockchain, a single ledger of records is shared with the transacting parties, where each must give consensus before another transaction is added, and once recorded, the transaction cannot be altered. In any supply chain, the blockchain using parties could include the producers, retailers, logistics providers, and regulators.
• Reducing Transaction cost: A digital trading platform based on Blockchain technology, modernises agricultural trade by directly connecting each transacting party to the same dataset, in a transparent manner. Blockchain is aimed at reducing transaction costs and creating financial security and supply chain transparency. Blockchain technology simplifies and lowers the cost of validation and tracking in the supply chain and in turn, facilitates smaller suppliers from the global food economy. Major food companies have commenced using Blockchain technology to transform their supply chain.
• Good Agricultural Practices (GAP):In the agricultural sector, Blockchain technology can also be used to record interlinked field practices such as INM/IPM (Integrated Nutrient Management / Integrated Pest Management), confirm good agricultural practices, validate resource use efficiencies, build traceability for the produce from farm to fork, prevent price extortion and delayed payments.
• Authentic Supply Chain: The technology also has various uses in the input supply chain, such as validating authenticity of planting material by keeping a record of high resolution images of the material in transit, provide similar traceability of other items from source to farms, record every input until point of consumption at farm level, etc. This immutable record keeping system, can help build checks in the input and output supply system. Since Blockchain relies on a distributed ledger (shared records), it is considered more secure as it makes it difficult for anyone to compromise the integrity of the data.
• The proposed COOPNET (Cooperative Informatics Network) networking more than 100,000 Primary Agricultural Cooperative Societies (PACS) can be operationalised with such distributed cryptoledger (Blockchain) systems. The way forward is to establish a “Blockchain Technology based Testbed” for Agricultural Value System.

6.4 Robots and sensors in agriculture

• Agricultural sector remains labour intensive and is a source of employment (through drudgery borne and unproductive, making replacement by machines a worth-while pursuit) to a large section of societies across the world.
• However, there are specialised areas where robotics has already come into use in agriculture. While robotics and sensors are a physical equipment, they use and provide inputs as digital signals and as a system are also considered part of digital technologies.
• The areas in which they are currently used, is where intensive attention or precision is required or where labour is not able to perform as per high-tech requirements. Robotics also help in automation of some tasks and can also free the individual farmer to prioritise and take on other works for added gains. Not to forget, this altered system would contribute to offering the mass labour well-deserved human dignity.
• Nursery Management: Robotics and automation are commonly used in nurseries for seeding, potting and care of the plants.
• Agri-Input Application: Other reported on-farm uses are machines that recognise patterns and undertake targeted spraying of pesticide and fertilizer, the precision allowing to limit the application to individual plants. This functions much like face recognition in smart phones, where a data set of patterns triggers a precise reaction.
• Greenhouses: In green houses, much like rain sensing windshield wipers in automobiles, rain and light sensing robotic arms can automatically retract or cover the roof as per need.
• Grading & Sorting: Similarly, hi-tech sorting and grading machines in modern pack-houses, sift and assay produce on the basis of optical and physical sensors, automatically package, label and move the boxes to next stage of handling. Automatic fork-lifts, pallet put-away and picking arms, and many such uses are seen in modern cold stores and warehouses.
• Robotics in Veterinary: Robotic and semi-robotic equipment are also used in poultry harvesting factories and abattoirs, besides in beverage factories, and the like. Robotics ease the physical handling of activities and large loads, doing it faster than humans can. Solutions are also in use in dairy facilities as in case of feeding and milking machines. Similar examples are seen in the fisheries sector, where automated feeders and pond aeration systems are used.
• Robotic Sensors (SENSAGRI):The first level of smartness is derived from sensors, to start or stop an automation on its pre-determined set of actions. Sensors and robotics go hand in hand, not only to actuate action, but also to monitor and stop an activity, at levels that include safety needs. The Information Technology Research Academy (ITRA), Hyderabad set up by the Ministry of Electronics and Information Technology, in consultation with the Indian Council of Agricultural Research (ICAR), had identified various areas for research purpose in respect of robotics, sensors, interpretation and use of sensor data. This was carried out in 2013, and even in the short period of time (2013-2018), many more applications and uses can be added and innovated, which implies the speed of changes occurring in the system. The Indian Agriculture Research Institute (IARI) has formulated a collaborative research project entitled “SENSAGRI: SENsor based Smart Agriculture” – involving six partner institutes under the ITRA Project Funding, to develop indigenous prototype for Drone based crop and soil health monitoring system using Hyperspectral Remote Sensing (HRS) sensors, so as to be integrated with satellite-based technologies for large scale applications. Such joint research efforts are recommended, to be undertaken and completed as per timelines.

7. Major ICT interventions of Agriculture Ministry

• The three departments under the Union Ministry of Agriculture and Farmers’ Welfare have developed several ICT based technologies. These have also evolved over the years into robust windows. Some of these are discussed below:
• Websites/Portals: In order to meet the information needs of the farmer, Ministry of Agriculture and Farmers’ Welfare has developed different websites and web portals that allow farmers to access the information using Internet. Information on Market Price, Soil Health Card, Crop Insurance, Government schemes etc. is available to farmers through these websites. These websites also aim at enhancing communication between the research institutions and the farmers. They have also helped improve communication and knowledge sharing between researchers and subject-matter experts. Farmers’ Portal, Agmarknet, Soil Health Card Portal, eNam, Crop Insurance are some of the examples of web portals developed for farmers.
• Use of Mobile Apps: Diffusing agricultural related information to farmers spread across the vast geography is made easier by proliferation of mobile phones. Today, mobile apps and services are being designed and released in different parts of the world. Mobile apps help to fulfil the larger objective of farmers’ empowerment and facilitate in extension services which can address global food security, agriculture growth and farmers’ welfare. Some illustrations of mobile apps developed for farmers are:
• Kisan Suvidha: mobile app provides information on five critical parameters—weather, input dealers, market price, plant protection and expert advisories. An additional tab directly connects the farmer with the Kisan Call Centre (KCC) where agriculture experts answer their queries. Unique features like extreme weather alerts and market prices of commodity in nearest market and the maximum price in state as well as India have been added to empower farmers in the best possible manner.
• Pusa Krishi: app helps farmers to get information about latest technologies developed in research labs. This app is actually transferring the technologies from “LAB to LAND”. Agrimarket mobile App can be used to get the market price of crops in market within 50 km of the devices location. This app automatically captures the location of person using mobile GPS and fetches the market price. Crop Insurance mobile app can be used to calculate the Insurance Premium for notified crops based on area, coverage amount and loan amount in case of loanee farmer.

8. Use of basic mobile telephony:

• Mobile telephony has transformed the tenor of peoples’ lives. In India, increased penetration of mobile handsets, large number of potential users, increased spread of communication, and low cost of usage are leading to growth of large number of mobile based information delivery models for the agricultural sector. A few of the modes used to meet the information needs of the farmer are SMS, IVRS, OBD, USSD etc.
• In mkisan (mkisan.gov.in), around 2 crore (20 million) farmers are registered (2016-17) and experts/scientists of different departments like Indian Metrological Department (IMD), Indian Council of Agricultural Research (ICAR), State Government, State Agriculture Universities send information to farmers.
• Weather information about likelihood of rainfall, temperature, etc. enables farmers to make informed decision in choice of seed varieties, decide on timing of sowing and harvesting. Information on occurrence of rainfall and other climatic uncertainties help in organizing better storage facilities.
• With market information, farmers are better informed about markets status, prevailing prices in the market. Further, when this information is forecasted across seasons, the farmers can make more informed decisions to plan for the produce that is in demand, and this will help in reducing distress sales by farmers due to market supply fluctuations.
• Personalized Information through Call Centres: Kisan Call Centres (KCCs) were launched by the Ministry of Agriculture and Farmers’ Welfare in 2004 to bridge the gap between farmers and the technology assessment. This initiative was aimed at answering farmer’s queries on a telephone call in their own language / dialect. KCC enables farmers to engage in direct discussions with the subject matter experts who are able to analyse the problem effectively and provide the solution directly.
• Use of Technology for Data Collection & Monitoring: Use of mobile apps to collect data from the field is indeed a revolutionary change. It can definitely avoids human error and increase productivity. CCE Agri is a mobile app used for data collection and data monitoring in rural areas.

9. Space and Digital technology in Agriculture

The Agriculture Ministry’s MNCFC is carrying out five national level programmes, where Satellite data and GIS and Image Processing Technologies are being used in various domains of Agriculture, as given below:

Following measures can be taken up for use of Space and Geo-spatial Technologies in the farming sector:

• Identification of areas for crop intensification – which involves mapping of current/existing cropping sequence/rotation and identifying use of variant and invariant resources with the use of remote sensing and ground data – and Development of crop rotation maps over agricultural regions Wasteland mapping / Updation and Watershed development and monitoring at micro scale
• Mapping of Ground Water Resources at high resolution and planning recharge structures
• Identification of Regions/Farmers who need intervention on multi-criteria basis, by interfacing with the ongoing National Land Records Modernization Programme (NRLMP)
• Intensification of CHAMAN (Coordinated Horticulture Assessment using Management using geo-informatics) project for Identification of rejuvenation plan for supporting Horticulture Farmers to fit their short duration crops into the existing cropping sequence · Establishment of GIS based Agri-produce and Post-Harvest Management through “crowd-sourcing and thematic layer integration, for de-risking · Spatial DSS for Irrigation Resources Management
• Delineation of water logging and salinity/sodic aspects of irrigated region at micro scale using temporal satellite data
• Operationalisation of Early Warning System on Crop Situation including rain and temperature for deciding crop to be sown, management of field operations, irrigation, fertilizer application, spray of pesticides etc, so as to facilitate Farmer as an Informed Cultivator
• Satellite Vegetation Index based assessment and advisory to Farmers, in respect of crop condition and stress
• Advisory on Crop Suitability on a field/area based on Cropping System Map
• Advocacy on an ideal Farming System Approach (not one-solution-fits-for-all) for various categories of Farmers (i.e. Small & Marginal, Semi-medium, Medium and large scale)
• Wetland Mapping for inland fisheries development
• Assessment of Regions of Feed and Fodder intensification and carrying capacity
• Scaling up and Operationalisation of the on-going Pilot Project “Crop Insurance using Space Technology and Geo-Informatics (KISAN)” throughout India at Panchayat level
• Spatial DSS using geo-Informatics at Village level as a collaborative task by all Administrative Departments, S&T Organisations (ISRO, DST-NRDMS, NIC etc.), ICAR and SAUs/CAUs, IITs, IIITs etc.
• Spatial DSS based advisories from Soil Health Card Database (of about 14 Crore cards) on 12 parameters viz., N, P, K (Macro-nutrients); S (Secondary- nutrient) ; Zn, Fe, Cu, Mn, Bo (Micro – nutrients) ; and pH, EC, OC (Physical parameters) – generation of Soil Fertility maps at 1:10000 scale
• Space technology based applications need to be developed / strengthened in the areas such as land resource mapping, pesticides management, soil health mapping, crop yield estimation as well as identification and assessment of flood-like calamities, marine/Inland fisheries, animal species identification and rearing Dissemination of regular production and sowing area updates for crops through GeoPortals: The Government already knows the minimum area required to avoid production shortage. With satellite imagery, it is possible to know the progressive coverage area on a daily basis. If a farmer is provided with the former and later date during the sowing season, he will know exactly to plant and avoid over production
• Use of Satellite Communication for Farmers’ Training and advisory (Teel-AgriMedicine)
• Use of Satellite Navigation Systems (GAGAN and NAVIC) for precision farming and geo-tagging of resources
• Real-time and accurate assessment of losses caused by natural disasters (floods, drought, hailstorm, pest/disease, cyclone, heavy rainfall) for better risk management and implementation of crop insurance

10. Digital rural Villages and empowered Farmers

• Farmers will not be digitally empowered until Rural India is empowered
• India needs an economic movement that starts in villages, and not one that tends to bypass them. There had been many efforts to establish “Village level Database” for micro level planning and decision support, and “Village level Knowledge Management System” for checking farmers’ distress (e.g. Information Village Project of IDRC/MSSRF Chennai, Village Resources Centre of ISRO, Village Knowledge Centre of CAPART, Village Knowledge Centre of Union Bank of India etc).
• Village Knowledge Centres (VKCs): were envisaged as information dissemination centres providing the farmers instant access to latest information/ knowledge available in the field of agriculture, starting from crop production to marketing. “Mission 2007: every village a knowledge centre”, was proposed in August 2007, so as to facilitate convergence and synergy among the numerous on-going as well as emerging programmes. While the green revolution technology has helped improve the productivity and production of rice, wheat, and few other crops, the knowledge revolution would help to enhance human productivity and entrepreneurship.
• The Digital India Programme: launched on 20th August 2014, promises to transform India into a connected knowledge economy offering World-Class Services at the click of a mouse, and has been envisaged with the following Nine (9) Pillars of Growth: –

• The on-going Digital Network for Farmers (DNF) over the Broadband Wireless/ Wired Network with APP such as KRISHAK MITHRA Software (KMS) will establish the “last mile connectivity” to have farmers “digitally included” for ushering in “Digital Agriculture India” effectively.
• Digital Village Project DIGITAL VILLAGE Project, among others, aims at the usage of Information & Communication Technologies (ICTs) for development and empowerment of communities (mostly disadvantaged communities). The initiative aims to empower communities (that have limited or no telecommunications access) through the use of mobile technologies, which will help contribute to long-term sustainable and economic development, through Supply-Chain modules. The model will work around the human resources at the village level as an individual, family and society; working out the linkages, identification of the right stake holders, analysis of the services, working out the methodology, digital enablement with digital connectivity with the right stake holders and necessary infrastructure at the village level.

Reaching each farmer in diverse country like India is not possible due to multiple limitations discussed above, so e-Technology will play an important role in dissemination of right information to right person at right time and place is very important. It will play a significant role in agriculture extension services.

11. Advantages of E-Technology in Empowering Farmers

• Cost Minimization–by reducing transaction cost, using precision agriculture optimizes cost of cultivation.
• Transparent System – Red-tapism is reduced using ICT, for example DBT through Jan-Dhan, PMKISAN use of AADHAR makes the system transparent and reduces duplicacy –
• Decision Making and Planning:By having the necessary information, farmers—big and small can make better and more informed decision concerning their agricultural activities. Either it be input, Credit, Marketing or storage of Agriculture produce.IT has paved the way to come up with farming software which can keep better track of crops, predict yields, when to best plant and what to plant, to intercrop or focus on just one product, or determine the current need of the crops—just about everything needed to improve production and income.
• Breaking Linguistic and Diversity barriers: Use of AI and Chat bot, Robotics linguistic and cultural diversity can easily be dealt with.
• Breaking Geographical Barriers: India has diverse agro-climatic zones with different requirement for each area, such complex system can be made simpler with use of Big data Analytics, Robotics etc
• Community Participation: Each member of community can participate and contribute as distance is not a hurdle in ICT
• Integrity: Use of full proof technology like Block Chain Technology will make the overall system much more transparent
• Minimizing Corruption: The biggest hurdle is trickle down effect is not observed as the government aid do not trickle down to lower strata and benefits are taken away by affluent farmers. ICT will definitely help in minimizing this

Challenges in Spread of e-Technology

• Digital Penetration
• e-Literacy
• Linguistic Diversity
• Power Supply
• Software Issue
• Initial Investment
• Cyber Security

12. Way forward

• For the first time, India has more internet users in rural areas than in urban cities. The latest report by the Internet & Mobile Association of India (IAMAI) and Nielsen showed rural India had 227 million active internet users, 10% more than urban India’s about 205 million, as of November 2019.

• Bharat Net Project is the new brand name of National Optical Fibre Network (NOFN) which was launched in October, 2011 to provide broadband connectivity to all 2.5 Lakh Gram Panchayats.  It was renamed Bharat Net in 2015
• With rising technological might of India and penetration of ICT in rural India, there is a scope for using this potential to digitally empower the farmers of our country which will transform the Agriculture sector and will help in achieving the dream of doubling farmers income

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