Table 1. Details of Some Common Used Knowledge Sharing Modes and Short Message Service (SMS) Systems In Extension Service
The agriculture sector needs precise data and advanced technology in a digitally informed scenario. The agriculture industry is being advanced with the support of information and communication technologies, such as the internet of things. Advanced sensors can be applied for specific agricultural management practices like insect management, disease management, land preparation, irrigation systems, and the control of smart farms and smart greenhouses. The aim is to increase yield, optimize farm inputs, provide market and government policy related information, and enable digital literacy among farmers, which would be helpful in enhancing rural income and sustainable agriculture. It is a need to promote digital interactive information systems in real time, like text messages, mobile apps, or interactive audio-video modes, to provide agricultural information to extension workers, farmers, academicians, and researchers through different means. The use of information and communications technologies, such as blockchain technologies, data mining, and wireless sensors, will definitely help in achieving different goals in sustainable agriculture. This article will provide summarized information related to the benefits and usage of technology in different agriculture sectors.
Information Technology (IT) can play a vital role in advancing agriculture and achieving the projected Gross Domestic Product (GDP) rate for our country. It can help farmers to become more efficient and productive and make better use of resources. Agricultural practices have been greatly influenced by technological advancements throughout history. From the creation of the plough to Global Positioning System (GPS)-driven precision farming equipment, humans have developed new ways to make farming more efficient and grow more food (Bhole & Kumar, 2020). They are working constantly to find new ways to irrigate crops or breed more disease resistant varieties. These iterations are key to feeding the ever-expanding global population with the de-creasing freshwater supply. According to Times of India, only 6% of rural households own a computer, and only 18% of rural youth knew how to use a computer. In addition, information technology can help to improve the quality of agricultural products and make them more competitive in international markets. The use of information technology in agriculture has helped farmers to connect with markets and sell their products more easily. In recent times, the uses of information and communication technology in agriculture have increased (Burchi et al., 2018; Sharma et al., 2018). This has been made possible by the increasing availability of internet connectivity in rural areas (El-Magrous et al., 2019).
Bhole and Kumar (2020) designed and implemented a deep learning-centered, non-destructive mango sorting and grading system. The designed quality assessment scheme comprises two phases: developing hardware and software. The hardware is designed to capture automatically RGB and thermal images of mango fruits o from all directions (360 ). From these images, the software classifies mangoes into three grades according to quality: extra-special, class I, and class II. Mango grading has been done by using parameters such as defects, shape, size, and maturity.
Burchi et al., (2018) intend to increase the technologies of greenhouse cultures by creating an integrated network of sensors and automation technologies, controlled by an Information and Communication Technologies (ICT) approach, for the agronomic development of horticultural crops. In the high-tech greenhouse, innovative technologies will be tested in order to stimulate the growth and development of plants through the optimized use of chemical products. In particular, a high-tech greenhouse is designed to manage, in a controlled and efficient way, different types of crops with different cultivation needs.
Cox (2002) analyzes developments in technology that are contributing to global improvements in crop and livestock production in terms of product quality, environmental considerations, and the welfare of people and livestock. The means by which they acquire, apply, and communicate the requisite information are reviewed under separate headings. These phases are related to the concept of precision agriculture, taken broadly, and apply to both crop and livestock production.
Dawodi et al. (2019) mentions many systems and databases are operational to provide services to citizens in the above-mentioned sectors; therefore, governments deal with an enormous amount of data to ensure that such data are effectively utilized to facilitate decision making and planning at the government level. Data mining techniques are an emerging research field in e-government, particularly in agriculture. In this paper, our focus is on the opportunities that data mining provides for e-government in Afghanistan. Moreover, this study gives some usecases of data mining techniques for improving the agriculture sector in Afghanistan.
El-Magrous et al., (2019)present the design, development, and testing of a customizable and cost effective Weather-Soil Sensor Station (W-SSS) for use in precision agriculture based on high accuracy sensors, wire-less communication, cloud data storage, and computation technology. The W-SSSs operated from July 25, 2018, to September 15, 2018, using an off-grid power system, an Arduino microcontroller, and a Wi-Fi connection to the cloud. Sensor data quality was evaluated using several statistical techniques. The data obtained from the soil weather stations illustrate the differences in weather and soil conditions both relative to the local weather station as well as those within a field.
There are various information technology tools that are used in the agriculture sector, namely agricultural precision farming tools, agricultural drones, agricultural extension information systems, agricultural simulation models, agricultural remote sensing, agricultural information management systems, farm management information systems, and agricultural decision support systems.
The goal of precision agriculture is to learn new management practices to increase the profitability of agricultural production. The tools are auto guiding equipment, variable-rate technology, the Internet of Things, proximate sensors technology, the global positioning system, the geographical information system, grid sampling, remote sensors, and proximate sensors. Precision tools are meant to boost precision or accuracy while machining products Cox (2002). The technology is used for manufacturing superior-quality and highly accurate industrial automation equipment, automotive parts, medical implant accessories, and consumer goods (Parihar et al., 2010). Farmers can use the Global Positioning System (GPS) to map their land and monitor their crops, soil, and irrigation systems.
Drones can be used for crop mapping, monitoring crop health, and applying inputs such as pesticides and herbicides (Puri et al., 2017). An agricultural drone is an unmanned aerial vehicle used in agriculture operations, mostly in yield optimization and crop monitoring. The DJI Mavic Mini is the best budget drone for farmers. Drones provide real-time and accurate data that farmers can act immediately. An innovative technologies that have the potential to revolutionize precision agriculture in its early stages was identified. Soil analysis is critical for crop yields (Galeon et al., 2019). Drones can do it faster, cheaper, and more reliably. The maximum speed is 40–110 km/h, the flight time is 55 minutes, and the maximum range is up to 8 km.
Extension is an informal educational process directed toward the rural population. This process offers advice and information to help them to solve their problems. Extension also aims to increase the efficiency of the family farm, increase production, and generally increase the standard of living of the farm family (Krintz et al., 2016). Extension methods comprise the communication techniques between extension workers and target groups. This approach concentrates efforts on a particular location for a specific time period, often with out-side resources. Part of its purpose is often to demonstrate techniques and methods that could be extended and sustained after the project period.
A Crop Simulation Model (CSM) is a simulation model that describes crop growth and development processes as a function of weather, soil, and crop management. Crop simulation models use quantitative descriptions of ecophysiological processes to predict plant growth and development as influenced by environmental conditions and crop management, which are specified for the model as input data. Simulation software is widely used to design equipment so that the final product will be as close to the design specs as possible without expensive process modification.
When farmers observe their fields or pastures to assess their condition without physically touching them, it is a form of remote sensing. Observing the colors of leaves or the overall appearances of plants can help determine the plant's condition. Detecting nutrient stresses using remote sensing is important in site specific nutrient management and, thereby, it can reduce the cost of cultivation as well as increase fertilizer use efficiency. Remote sensing applications have been playing a significant role in the agriculture sector for evaluating plant health, yield and crop loss estimation, irrigation management, identification of crop stress, weed and pest detection, weather forecasting, and gathering crop phenological information.
Agricultural Information Management System (AIMS) provides a single-window facility for farmers to register themselves and submit applications for availing various services from the agriculture department. A farmer can declare land and crops in the portal and apply for benefits under various services based on this information (Dawodi et al., 2019). AIMS helps users chart and correlate multiple metrics across their Information Technology (IT) environment, set dynamic alert thresholds, and create real-time reports on specific business processes. The solution also features a central dashboard that enables multiple users to collaborate in a single workspace.
A Management Information System (MIS) for the agriculture sector is used for collecting, processing, storing, and disseminating data in the form needed to carry out a farm's operations and functions (Nehra et al., 2018). The bewsys agriculture MIS is a cloud-based software that enables farmers, agronomists, policymakers, and project managers to track and manage agricultural activities digitally and cost-efficiently.
Decision Support Systems (DSS)s are used in agriculture to collect and analyze data from a variety of sources with the ultimate goal of providing end users with insight into their critical decision-making processes. In route planning, a DSS can be used to plan the fastest and best routes between two points by analyzing the available options. And for crop planning, the farmers use DSS to help them determine the best time to plant, fertilize, and reap their crops.
There are four main components of an Information Technology (IT)s infrastructure as follows.
Physical devices and equipment that are used to process, store, and transmit information.
The programmes and applications that run on the hardware enables it to perform its various functions.
The raw information that is to be processed, stored, and transmitted, data components consist of simple real numbers, text strings, vectors of real numbers and other values, sets in real vector spaces, functions from real vector spaces to other data spaces, or complex combinations of these. These components integrate to perform input, processing, output, feedback, and control.
The users of the information technology infrastructure are beneficiaries of the person or entity that legally designate to receive the benefits from the financial products. Agriculture has evolved from simple farm record-keeping into sophisticated and complex systems to support production management and meet the increased demands to reduce production costs, comply with agricultural standards, and maintain high product quality and safety. Information technology can be used to provide a precision agriculture package by developing an e-farm production system based on precision agriculture techniques.
Advisory services with Information Technology (IT) support helps to improve the productivity and income of farmers. It also plays a key role in connecting farmers to markets and providing technical and financial support for them to adopt new technologies and practices. This includes providing information through various modes of access about agricultural practices, yields, weather patterns, market prices, and more. Mobile network operators can instantly send information in the form of text messages or voice recordings related to local problems, seasonal problems, awareness, government plans, etc. to a large number of farming communities in a short period of time. Table 1 shows the details of some common used knowledge sharing modes and Short Message Service (SMS) systems in Extension Service.
Table 1. Details of Some Common Used Knowledge Sharing Modes and Short Message Service (SMS) Systems In Extension Service
Machine learning can be used to predict crop yields based on data such as weather conditions, soil properties, and crop growth. Machine learning can be used to detect plant pests and diseases and thus identify the most effective control strategies. It can be used to optimize irrigation systems by predicting water demand based on data such as weather conditions and crop growth. It can be used to analyze soil samples to identify nutrients and other properties that affect plant growth. Techniques used in precision agriculture have the capacity to sense specific sites in real time and automatically adjust processing as per need based requirements. Except in rare average sites, this has made over or under application of herbicides, pesticides, irrigation, and fertilizers unavoidable. Site-specific crop management under precision agriculture is more all encompassing, and information centric farming activities are now major ICT tools in agriculture and related activities.
In India, the role of ITs is to promote nutritional status for mothers and newborn babies. The role of ITs is critical to the successful implementation of the digital India program. The Integrated Child Development Services (ICDS) under the ministr y of women and child development promotes the use of IT-based services to improve the performance of Anganwadi workers engaged in malnutrition-removing programmes in the cities and rural areas. Recently launched IT-enabled services monitor daily doses of nutritional and supplemental nutrients for the children through smartphones and tablets to update data on child nutrition on a daily basis. And also launched e-ILA (e-Incremental Learning Approach), an online thematic module on nutrition for mothers and newborn babies and early childhood education. Worldwide, there are different types of systems using IT to enhance nutritional programmes supported by governments, like E-Soko systems supported by the world bank in different countries for campaigns like healthcare, agronomic advisories, nutrition, etc. A farming advisory service running in African countries, provides nutrition related information to mothers on baby birth and observes the behavior of malnourished children and their nutrition level too.
The chatbot system is an advanced automatic questionanswer system, also called a human computer interaction machine, which provides immediate responses to the users based on a data set of frequently answered questions (Niranjan et al., 2019). The beneficiaries questioned the machine, and the machine answered their queries with accurate and satisfactory suggestions. This helped farmers get information regarding the package and practices of different crops, input related information, suitable crops in specific soils and areas, usage and dose of pesticides and fertilizers, etc. It works in three phases namely question identification, knowledge base searching stored in the database and providing the most suitable and accurate answers. Air Mobility Command Deployment Analysis System (ADANS), which is an agriculture domain for Question Answering System (AGRI-QAS) using Artificial Intelligence Markup Language (AIML) and Latent Semantic Analysis (LSA), is one example. Currently, so many question-answering systems have been developed, but very few of them provide correct and efficient answers to the users. So, the challenge is to make them more sensitive to provide accurate answers in the existing chatbot system.
Farmers can access information about farming resources and government services through an online mobile application called farmer's portal. It also provides a chat option for farmers, which enables them to chat with an agricultural expert using this application efficiently. Some important web portal are to be discussed.
It is an electronic trading portal that connects the currently working Agricultural Produce Market Committee (APMC) mandis to form a common platform for the national market for agricultural products. In Uttar Pradesh, the agricultural marketing board is using the "mandi on mobile" service for the farmers, and in Bihar, e-Forest Mandi (e-FM) was launched by the environment and forest department to connect growers Cox (2002) (Environment and Forest Department, 2016).
mKisan connects farmers and allows all central and state government organizations in agriculture and related sectors to give information, services, and advisories through SMS in the local language.
The portal provides an end-to-end technology solution to transfer funds directly into the accounts of farmers under the (Prime Minister) PM-kisan scheme, a central sector scheme of the Government of India to augment the income of all the landholding farmers of the country, implemented by the department of agriculture and farmers welfare through the department of agriculture of all the states and union territories. Some common agriculture websites in India for farmers are tabulated in Table 2.
Table 2. Lists of Some Web Portals for Farming Community
In agriculture, it is a challenge for knowledge professionals, extension workers, and farmers to access and share major, important, and critical information to sustain an agriculture-based economy in this country. However, most of these initiatives require the farmer to be unfamiliar with these technologies and also need the support of technical skills, equipment, a proper internet connection, and infrastructure to make them work.
Interactive Information Dissemination System (IIDS) is a highly integrated model of free Interactive Voice Response System (IVRS), smartphone applications, and interactive portals that allows you to recover information from registered users using your mobile phone. The main beneficiaries of the community are farmers, agricultural experts, agricultural advisory bodies, Krisi Vigyan Kendras, etc. This system works when any beneficiary subscribes to the services they need. Beneficiaries then receive individual, need-based information to which they have subscribed.
This type of app facilitates farmers by providing different advisory services, the latest agricultural technology, current mandi prices from different states and districts, etc. with the help of specialized apps, which are listed in Table 3.
Table 3. Some Mobile Apps for the Knowledge and Skill Enhancement of Farming Community
Radio is still popular in rural India and is an effective medium for reaching people in areas with low literacy and power outages, covering a radius of about 10-15 kilometers. The dissemination of information through traditional media like the community radio started in Bihar by Krishi Vigyan Kendra (KVK), Barh, Patna.
India Meteorological Department (IMD) delivers agriculture and meteorology services to farmers through collaboration between the public and private sectors with mobile service providers with the goal of minimizing losses due to adverse weather on crops for the enhancement of agricultural production. The major objective is to minimize the effect of ad-verse weather on crop production and its productivity. There are some weather forecast applications for farmers like meghdoot agro, damini, atmanirbhar krishi, etc.
The problems of farming communities can be resolved to a certain extent by direct call-based service. There are some institutes that provide kisan help line service, like Bihar agricultural university.
Drones can be an important tool in day-to-day agriculture activities such as farm analysis, Geographic Information Systems (GIS) mapping, geo informatics, fertilizer application, crop health imaging, disease and pest attack surveys, land digitization, pesticide application, and so on. The Government of India recently inaugurated and addressed the conference on promoting kisan drones: issues, challenges, and the way ahead, organized to promote the future and current need for kisan drones in the agriculture sector.
The use of sensors in the agriculture sector is a sophisticated technology for smart farming, smart irrigation, and smart soil management. Wireless sensor networks are capable of monitoring the soil of a specific area or zone, monitoring soil moisture, and monitoring and collecting data in farm fields (Hu et al., 2019). Wireless sensors collect data from the farm and send it to the control center for smart forecasting and assessment in order to improve crop yields and quality. In the future, if we merge the sensor network with different technologies like geo-informatics, artificial intelligence, cloud computing, and blockchain techniques, it will solve the problems effectively in the agriculture world.
This technology works on the principle of transparency among all tangled channels at every step. From manufacturing to the consumer's hand, this technology can record every step within the channel. Currently, this technology is working in areas of the agricultural and food sectors like agricultural insurance, the food supply chain, smart farming, and transactions linked in smart contract farming (Kamilaris et al., 2019). This technology can be used by an insurance body to make timely payments based on automated weather data records that initiate the disbursement in a smart contract; other works, such as weather information and crop-related data such as plant growth information or data collected by farming machines, can be automatically integrated to overcome risk and make the payout process efficient (Xiong et al., 2020). There are some examples of who is making use of this technology, such as Arbol3 giving a secure and absolute way of storing data collected at the start of the supply chain, like pesticide residues in grain, vegetables, and fruits; World-Cover2 is an insurance provider in the USA for small and marginal farmers in Ghana. Binary Search Tree (BST)s are currently in use by Wal-Mart, International Business Machines (IBM) Food Trust, Alibaba, etc. for food tracing projects and tracking the whole process of food production, processing, and sales.
Many developed countries have already used different methods of data mining to calculate and solve different farming concerns like prediction of crop yields, input management, crop management, weather forecasting, detection, classification, and prediction of crop diseases, soil classification, suitability of soils for crops, fertilizer dose application, content of organic matter in soil, irrigation management, etc. Data mining is currently being used in developing countries like Afghanistan to overcome agriculture issues like soil nutrient status and analysis. Some data mining methods are neural networks, association rule mining, decision trees, linear regression, K-nearest neighbor etc.
A smart greenhouse production system is a controlled, integrated network of sensors and automated technologies used for monitoring and management in comparison with traditional green houses for different crops for proper growth and development of crop plants with the goal of enhancing the efficiency of inputs used in terms of plant nutrition, irrigation, pests, and disease with reduced chemical inputs and waste. With the help of sensors, water and nutrient use are enhanced efficiency by smoothly controlling the green house(Halewood et al., 2018). Smart greenhouses operate on the principle of balancing energy consumption with selected parameters such as temperature, humidity, CO2 concentration, oxygen concentration, and so on. This system allows farmers to locate whole fields precisely so that inputs like seeds, fertilizers, pesticides, herbicides, irrigation water, etc. can be applied to individual fields in a specific manner, especially in site-specific management.
In precision farming, the use of Geographic Information Systems (GIS) is very encouraging in India for crop forecasting, cultivation systems, command area management, watershed management, precise mapping of drinking water potential, management of natural hazards, fisheries, management of hill farming developments, post-harvest management, etc. Mapping of crop and soil properties is the first and most important step in precision agriculture. GPS helps in the collection of close-up photographs, multispectral sensors to provide detailed 3-D information about land cover or multispectral information about plants and soil, estimation of the groundwater level, and chemical specific sensors have been used.
Currently, information technology is playing an important role in genomic technology for developing strategies for improvement in crops, gene banks, and PGRs. In accordance with national and international agreements, the data will be stored in a digital data repository and made available to the scientific community, breeders, farming community, and entrepreneurial tool developers. Currently, so many initiatives have been initiated, such as, Global Open Data for Agriculture and Nutrition (GODAN: www.godan.info), DivSeek (www.divseek.org), Research Data Alliance (RDA: www.rd-alliance.org) and Breeding Application Programming Interface (API) (BrAPI: https:// brapi.org) working on it. In the 1980s, three international repositories for storing nucleotide sequences were established: the GenBank at the National Center for Biotechnology Information in the United States, the European Molecular Biology Laboratory Data Library, and the Japanese Deoxyribo Nucleic Acids (DNA) Database.
This technique is widely used for grading the quality of fruits. The hardware is built to photograph the original product and thermal images of fruits from all directions automatically. Designed software classifies fruits into different quality grades based on these images (Ratnayake et al., 2021). For fruits like mango, grading has been done using parameters such as defects, shape, size, and maturity, and an automatic mango fruit grading system uses non-destructive techniques like thermal imaging. Deep learning has the potential to predict, in a very precise way, when a plant will get a disease or not, making agriculture more sustainable.
IT intervention in areas such as agricultural education requires the empowerment of teachers in computer fundamentals and the gradual introduction of advanced computer application modules taught in preparation for virtual classrooms (Patrício & Rieder, 2018). Agricultural school and university students should be familiar with teaching on Liquid Crystal Display (LCD) smart screens, be proficient in using PowerPoint presentations, and be trained in the use of internet technology. At present, the academic management system is a one-stop shop for enrollment, attendance, collection of fees, and management of courses online. ITs can be an effective means of connecting all agricultural universities in India. Useful information such as questionnaire collections, current trends, seminars, symposiums, workshops, training courses, and other information on academic development activities can be easily shared via IT. India Agricultural Education Planner is introduced to all agricultural colleges in India and linked them to maximize the use of agricultural colleges and faculty libraries using a common web portal, the Indian Council of Agricultural Research (ICAR). E-learning is being integrated into the existing organizational and educational structure as a hybrid system also known as ICT-supported learning.
The documentation and communication of research in the form of e-books, e-magazines, e-catalogues, statistics, professional e-publications, patents, etc. in digital form at different common depositories with the help of computer processing in the upcoming future In agricultural research, documentation, experimentation, analysis of observed data, and presentation can be done effortlessly with the help of different IT tools. Digital Object Identifiers (DOIs) and DOI services are helping professionals and academicians communicate with the library world.
Computer vision systems are broadly used in different sectors of agricultural and horticultural practices like production, packaging, grading, sorting, processing, etc. (Patrício & Rieder, 2018). Currently, with the help of Computer Vision (CV) and AI tools, parameters like diagnosis of nutritional value in crop leaves, characterization of rice flowering, maize tassel characterization, maize tassel segmentation, detection of fusarium in damaged grains, aphid detection in crops, pollinator monitoring, analyzing the pollination behavior of bees, detection and segmentation of fruits and vegetables, classification of fruits and vegetable types, grading of the fresh fruits and vegetables, sorting and grading of the defective fruits and vegetables, diseased plant identification, etc. are done.
ICT helps farmers and the population linked with farm related activity to obtain updated and accurate information effortlessly so that they can make better conclusions and decisions in their daily farming practises and get the necessary skills. Currently, radio, television, newspapers, and literature are the most important mediums in India for publicising new technology or raising awareness among farmers, scientists, extension workers, and others. The effects of IT on agricultural technology transfer, resource documentation, and its application now play a central role in the agricultural sector. In the field of gene bank, use of blockchain technology in food industry, concept of smart farm, concept of smart green house, in academic management system, wireless sensor based services, weather forecasting, animal ration management etc., has a tremendous potential for the boom in crop production and other extension services as compared with traditional style. Therefore, in the current scenario, information technology is an integral part of modern farming to achieve the projected yields in crop production and other services, and finally, the contribution to the Gross Domestic Product (GDP) of the country.