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Use of Technology for Reducing Farm-to-Plate Food Wastage

India is wasting 20-25 per cent of food from farmer field to consumer plate, including wastage of cooked meals, which can be reduced to 10-15 per cent through use of technologies, said Himanshu Pathak, Director General of Indian Council of Agricultural Research (ICAR).

The ICAR would focus on various measures to address the challenges faced by farmers, including the effects of climate change. We need to follow sustainability standards to preserve agricultural diversity, water use efficiency and improved ecosystem services,” Pathak said in the annual GB meeting of ICAR.

For more details please click the following link

https://www.thehindubusinessline.com/economy/agri-business/technology-can-help-cut-farm-to-plate-food-wastage-to-15-says-icar-d-g/article67896783.ece/amp

Biosensor for Detection of Disease at an Early Stage

A research team led by Dr. Larysa Baraban at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) develops intelligent, miniaturized biosensor devices and systems using nanomaterials to determine biomolecules and cells as well as biochemical reactions or processes as disease markers.The ability to detect diseases at an early stage or even predict their onset would be of tremendous benefit to doctors and patients alike. These biosensors can be designed to specifically detect different biomolecules. Different pathogens cause different electrical potentials and therefore different currents. For example, cancer cells cause different currents than a flu virus.

The team’s current publication in Biosensors and Bioelectronics describes the development of a portable, palm-sized test system that can simultaneously carry out up to 32 analyses of one sample.

Various possibilities and mechanisms exist for detecting pathogens in body fluids. One option that Baraban investigates at the HZDR-Institute of Radiopharmaceutical Cancer Research is the detection using field-effect transistors (FETs) from the realm of electronics.

The operating principle is simple: a defined electrical current flows from A to B. This current can be regulated by the electrical potential on the surface of a gate, which functions like a precise, continuous valve.

Disease-relevant biomolecules bind to the gate surface and thereby change the electrical potential and therefore the current as well. If there is no significant change in the current, no biomolecules have bound to the sensor surface. On the other hand, a change in the current means that disease-related molecules can be detected on the sensor surface.

For more details please see the following research article…

A new approach for fast and cost-effective pathogen detection https://phys.org/news/2024-02-approach-fast-effective-pathogen.html

https://phys.org/news/2024-02-approach-fast-effective-pathogen.amp

Top Leaders in Cyber Security

The list features people from all over the globe including fraud detection, corporate governance, cyber defense, ethical hacking and more. They all have extensive expertise, have made remarkable achievements towards advancing cyber safety, and use their public profiles to raise awareness of the importance of cyber security, both as a safety measure and a career.

Photo by Pixabay on Pexels.com

For detailed information please visit the following link…

https://www.cshub.com/executive-decisions/articles/top-25-leaders-cyber-security?utm_campaign=CSIQ-NL-23.10.25%20-%20APAC&utm_medium=email&utm_source=internalemail&MAC=&elqContactId=28868329&disc=&elqCampId=154275&utm_content=CSIQ-NL-23.10.25%20-%20APAC%20-%20B

Nobel Prize in Chemistry 2023

Scientists Moungi Bawendi, Louis Brus and Aleksey Ekimov won the 2023 Nobel Prize in Chemistry for their discovery of tiny clusters of atoms known as quantum dots, widely used today to create colours in flat screens, light emitting diode (LED) lamps.


The Royal Swedish Academy of Sciences has decided to award the 2023 Nobel Prize in Chemistry to Moungi G. Bawendi, Louis E. Brus and Alexei I. Ekimov “for the discovery and synthesis of quantum dots.”

Everyone who studies chemistry learns that an element’s properties are governed by how many electrons it has. However, when matter shrinks to nano-dimensions quantum phenomena arise; these are governed by the size of the matter.

The 2023 Nobel Prize laureates in chemistry have succeeded in producing particles so small that their properties are determined by quantum phenomena. The particles, which are called quantum dots, are now of great importance in nanotechnology.

Credits: Google and Facebook social media

Microneedle-based Wearable Sensors for Real-time Health Monitoring

Microneedle sensors could enable minimally-invasive, continuous molecular monitoring providing information on disease status and treatment in real time. Such wearable sensors for pharmaceuticals would create opportunities for treatments personalized to individual pharmacokinetics in futuristic healthcare systems. A new study introduces a method using aptamer-based microneedle sensors for real-time monitoring of specific biomolecules in the body. These sensors are embedded in stainless steel microneedles and can detect substances in the blood. This offers the potential for monitoring multiple biomarkers. Microneedles allow direct access to the skin’s interstitial space, enabling less invasive and more frequent measurements. This technique has the potential to revolutionize wearable health monitoring, making it more effective and accessible. For more details, please go to the original research paper by clicking the following link:

Microneedle-based Wearable Sensors for Real-time Health Monitoring

Artificial Intelligence-Driven AgriTech Startups for Climate-Smart Farming

General crop management system provides an interface for overall management of crops covering each aspect of farming. Issues pertaining to soil and irrigation management are very vital in agriculture. Improper irrigation and soil management lead to crop loss and degradation quality. Application of herbicides has a direct implication on human health and environment as well. Crop yield prediction models using artificial intelligence (AI) and drones for monitoring soil and crop health have been initiated. AI provides farmers with the forecasting and predictive analytics to reduce errors and minimize the risk of crop failures. AI enables farmers to forecast temperatures and predict how many fruits or vegetables a harvest will yield. Modern AI methods are being applied to minimize the herbicide application through proper and precise weed management. Insect pest infestation is one of the most alarming problems in agriculture that lead to heavy economic losses. Researchers have tried to mitigate this menace by development of computerized system that could identify the active pests and suggest control measures. Crop diseases are also a matter of grave concern to a farmer. Significant expertise and experience is required so as to detect an ailing plant and to take necessary steps for recovery. Computer-aided systems are being used globally to diagnose the disease and to suggest control measures.

Agritech startups

Agritech startups have raised around Rs 6,600 crore over the last four years from private equity investors, witnessing a growth of over 50% per annum. There are over 1,000 such agritech startups in India that are assisting farmers in improving farming techniques. India has more than 500 startups working in the millet value chains, while the Indian Institute of Millets Research has incubated 250 startups under Rashtriya Krishi Vikas. This climate-smart farming is slowly gaining acceptance with farmers using clean energy sources like solar for irrigation. The farmers have been provided incentives to transfer electricity generated through solar to the local grid.
Smart farming also enables crop diversication which will help farmers in reducing their dependence on monsoons for water. This will also assist farmers in improving farming techniques. There was 200% increase in rural internet subscriptions between 2015 and 2021 as compared to 158% growth witnessed in urban. To further create digital linkages at the grassroots level and increase the consumer experience like the one in urban centres, a project for the saturation of 4G mobile services in uncovered villages across the country has been approved. The project will provide 4G mobile services in 24,680 uncovered villages in remote and difficult areas, and 6,279 villages having only 2G/3G connectivity shall be upgraded to 4G.

AI-based Agriculture

Agriculture is slowly becoming digital with AI showing promising potential in categories such as soil and crop monitoring, predictive analytics and robotics. Sensors and soil sampling to gather data are already in use to store farm management systems information for processing and analysis. This data, algorithms, weather information and images from satellites are used to create AI based software for different agricultural regions in India. An open source platform would make the solutions more affordable, resulting in rapid adoption and higher penetration among the farmers. Though currently application of AI in agriculture is in a nascent stage but with time & capital investment, farm mapping, observation, predictability and on ground farm operations will be automated, leading to increase in efficiency and reduction in production cost and minimizing environmental impact. AI-based technology can take over planting, maintaining, harvesting crops, grading fruits and vegetables and detect certain disease in plants. AI-powered solutions will not only enable farmers to do more with less, it will also improve quality and ensures faster go-to-market for crops. AI-based technology can solve the problems that are present in agricultural sector leading to take agriculture in the era of e-agriculture or smart farming. Hence, this smart farming using AI-driven technologies can alter the future of Indian agriculture and can bring a paradigm shift in how we see farming today.

Examples of some startups:

• DeHaat: This is an online platform providing AI-based end-to-end farming solutions. It offers soil testing, yield forecasting, and advisory services. It gives farmers Agri input and uses technology to monitor supply chain activities. It is engaged in Agri financing providing credit and insurance to farmers for agriculture-related activities.
• Absolute: It provides IoT and AI-enabled hardware and software solutions for farmers. It has developed solutions for open farms, greenhouses, or indoor vertical farms. It offers IoT devices equipped with sensors, hardware systems, and satellite sources, which feed into proprietary machine-learning algorithms to deliver real-time crop insights.
• Fasal: This is provider of AI-based solutions for precision agriculture. It offers a cloud-based platform that collects microclimatic data using on-field sensors. It offers real-time farm information on temperature, humidity, rainfall, soil moisture, and soil temperature. It uses an AI-based microclimate forecasting algorithm to analyze and provide insights on microclimate, disease forecast, and irrigation management. It enables farmers to access insights from their mobile or PC.
• Nutrifresh: This is producer of green vegetables using an indoor hydroponic system. It adopts a hydroponic vertical farming system to grow its microgreens. It uses AI-powered solutions to understand and analyze data on the quality of produce. It also automates climate control and water supply lines for ensuring the growing conditions.
• TartanSense: This is provider of an AI-based robot for agriculture. It is embedded with a camera that is used for capturing plants & weeds and it uses computer vision technology to identify weeds. The robot has the capability to spray chemicals only on the detected weeds, and generate analytic reports.
• IntelloLabs: It provides AI-based solutions for agricultural product quality testing. It provides a traceability facility with the help of a QR code. It also facilitates timely production quality checks to optimize operations.
• SatSure: It provides AI-based satellite data for multi-industry. It provides users with satellite imagery, machine learning, and big data analytics to offer data and information services to agriculture finance corporations, agriculture input providers, and other related parties for crop health monitoring and assessment. It provides variable rate prescriptions, vegetation index maps, soil nutrient analysis, and fertilizer recommendations. Its offering sectors include finance, banking, agriculture, and infrastructure.
• AquaConnect: It is provider of AI-based end-to-end solutions for shrimp and fish farmers. It offers data-driven farm advisory by using the deep learning method. It provides context-aware alerts and suggestions regarding water quality and aquatic health. It also provides formal finance and insurance linkages and also improves the market linkage of the farmers.
• AgNext: It provides AI-based end-to-end solutions for shrimp and fish farmers. It offers data-driven farm advisory by using the deep learning method. It provides context-aware alerts and suggestions regarding water quality and aquatic health. It also provides formal finance and insurance linkages and also improves the market linkage of the farmers.
• And so on….

Agriculture is a dynamic domain where solutions cannot be generalized to suggest a common solution. AI techniques have enabled us to capture the intricate details of each situation and provide a solution that is best fit for that particular problem. AI can be employed for agricultural product monitoring and storage control. Storage, drying and grading of the harvested crops are important aspects of agriculture. Hence, AI can be employed in addressing various food monitoring and quality control mechanisms. The crop yield prediction is very beneficial for marketing strategies and crop cost estimation. It has been reported that the estimated gross merchandise value (GMV) of agritech startups was $4 billion in 2022, it is likely to grow to $34 billion by 2027.

For more information (in Hindi), please see the following link:

Reference:

  1. Economic Survey 2022-23
  2. The Economic Times
  3. https://gingerfingers.wordpress.com/artificial-intelligence-driven-technologies-in-agriculture/

Microfludics-based Sensors for Healthcare

Microfluidics has emerged as a promising technology for medical and environmental testing.

The recent innovations in the field of microfluidics applied to diagnostic/medical devices and point-of-care medicine

For more information please read the article

https://www.frontiersin.org/research-topics/55654/microfluidics-based-sensors-for-one-health

Protect Your Systems and Safeguard Your Information against ‘Truebot’ malware

The so-called Truebot strain, a new type of malware is affecting businesses involving healthcare, financial, insurance services in USA and Canada. Cybersecurity experts are suggesting to protect your systems and safeguard your valuable information. For more information…

Source: CMIT Solutions

Truebot

Robotics Technology in Agriculture

Robotics has the potential to transform agriculture by increasing efficiency, productivity, and sustainability. Robotics has made significant strides in transforming the agriculture industry. Agricultural robots, or “agribots,” are increasingly being used to automate various tasks, including planting, harvesting, weeding, and monitoring crop health. In addition, robotic technology can automate many of the tasks involved in dairy farming. Robotics technology can improve livestock management by reducing labor costs, increasing productivity, and improving animal welfare. Here are some examples of robotics applications in agriculture:

HARVESTING

Harvesting using robots, also known as robotic harvesting, is a method of using automated machines to collect crops from fields or other agricultural areas. This technology is increasingly being used by farmers and growers around the world to improve efficiency, reduce labor costs, and increase yield. Robotic harvesters are equipped with sensors, cameras, and other technologies that allow them to identify and collect ripe fruits or vegetables. They can navigate through fields with precision and collect crops at a much faster rate than human laborers. Robots can be used to pick fruits and vegetables at peak ripeness, reducing waste and increasing yield. Robots are being developed that can automate the harvesting process for crops such as apples, grapes, and strawberries. These robots can pick fruit with a gentle touch, reducing waste and increasing efficiency.

Harvesting using robots is a growing trend in agriculture, as it offers many advantages over traditional manual harvesting methods. Here are some of the benefits of using robots for harvesting:

Despite the many advantages of using robots for harvesting, there are some challenges that must be addressed. For example, robots may require specialized equipment or modifications to the farm environment to operate effectively. Additionally, there may be regulatory or safety concerns that need to be addressed before using robots on a large scale. One of the advantages of robotic harvesting is that it can be done 24/7, regardless of weather conditions or other factors that may limit human labor. This allows farmers to maximize their yield and ensure that crops are harvested at the optimal time. In addition, robotic harvesters can be programmed to sort and grade crops as they are collected, which can help to reduce waste and increase the overall quality of the harvest. This can be especially beneficial for crops that are fragile or easily damaged during the harvesting process.

Despite the benefits of robotic harvesting, there are some challenges to implementing this technology. For example, the cost of purchasing and maintaining robotic harvesters can be high, which may make it difficult for smaller farms to adopt this technology. In addition, robotic harvesters may not be able to replace all aspects of human labor in agriculture, particularly in tasks that require human judgement or dexterity. Overall, however, robotic harvesting has the potential to revolutionize the way that crops are collected and processed, and could play an important role in meeting the food demands of a growing global population.

PLANTING AND SEEDING

Planting and seeding using robotics is an emerging field that combines technology with agriculture. The use of robotics in agriculture has the potential to revolutionize the industry by increasing efficiency, reducing labor costs, and improving crop yields. Automated systems can plant and seed crops more precisely and efficiently, reducing the use of water and fertilizers.  Autonomous planting robots can be programmed to plant seeds at precise depths and intervals, reducing labor costs and increasing accuracy. There are several ways that robotics can be used for planting and seeding. One approach is to use autonomous robots that can move around fields and plant seeds at specific intervals. These robots are equipped with sensors that allow them to navigate through the field and avoid obstacles. They can also be programmed to plant seeds at specific depths and densities, ensuring that crops are planted evenly and with precision. Another approach is to use drones equipped with seed dispensers to plant seeds from the air. This method is particularly useful for planting in hard-to-reach or remote areas.

Some robots are designed to work in a variety of terrains, including hillsides and slopes, which can be challenging for human operators. Additionally, robots can be equipped with sensors and cameras to monitor soil moisture and nutrient levels, allowing for more precise and efficient use of resources. Drones can also be equipped with sensors to collect data on soil conditions and crop growth, allowing farmers to optimize their planting and seeding strategies. Robotics can also be used for precision seeding, which involves planting seeds in a specific pattern to optimize crop growth. Precision seeding robots use sensors to analyze soil conditions and determine the optimal placement of each seed. This method ensures that crops are planted in the most efficient and effective way possible, leading to higher yields and reduced waste.

One of the benefits of using robots for planting and seeding is that they can work around the clock, allowing for faster and more consistent planting. Robots can also be programmed to plant seeds at precise depths and spacing, resulting in better crop yields and reduced waste. Another benefit of using robots for planting and seeding is that it can reduce the physical strain on human workers. Farming can be a physically demanding job, and using robots to perform repetitive tasks can help reduce the risk of injury and strain.

Planting and seeding using robots is an innovative and efficient way to cultivate crops. With the advancements in technology, robots are becoming more capable of performing agricultural tasks that were traditionally done by humans. Planting and seeding using robots is an exciting development in the agriculture industry that has the potential to improve efficiency, yield, and sustainability. However, it’s important to note that robots are not a complete replacement for human labor, and there will always be a need for skilled workers in agriculture. Overall, the use of robotics in planting and seeding has the potential to transform agriculture by increasing efficiency, improving crop yields, and reducing labor costs. As technology continues to advance, we can expect to see even more innovative uses of robotics in agriculture.

CROP MONITORING

Crop monitoring using robots is an emerging technology that involves the use of autonomous or semi-autonomous robots to gather data about crops in a field. These robots can be equipped with sensors, cameras, and other technologies that can help them detect and analyze various aspects of crop growth and health, such as soil moisture, temperature, nutrient levels, and pest infestations. There are several types of robots used for crop monitoring, including ground-based robots, aerial drones, and even underwater robots for monitoring crops in aquatic environments. These robots can be equipped with different sensors depending on the specific needs of the crops being monitored. For example, thermal cameras can be used to detect variations in temperature, which can indicate stress in plants due to water shortages or disease.

Crop monitoring using robots is a technique that involves using unmanned ground vehicles (UGVs) or unmanned aerial vehicles (UAVs) to collect data on crops. This data can then be used to optimize crop management practices and increase yield. Drones and ground-based robots equipped with sensors and cameras can monitor crop health and growth, helping farmers make informed decisions about irrigation, fertilization, and pest management. There are several ways in which robots can be used for crop monitoring. One common method is to equip robots with sensors that can measure various parameters such as soil moisture, temperature, and humidity. This data can then be used to determine the optimal time to water, fertilize, or harvest crops. Drones equipped with cameras and sensors can be used to monitor crop health, soil moisture levels, and other factors that can affect crop growth. This data can be used to identify areas that need attention, such as irrigation or pest control.

Another method involves using robots to collect images of crops from above. These images can then be analyzed using machine learning algorithms to detect patterns that indicate crop health, growth, and yield potential. This can help farmers identify areas of the field that may require more attention and resources, leading to more efficient use of resources and higher yields. Robots can also be used to collect data on plant diseases and pests. By using sensors or cameras to detect signs of disease or infestation, farmers can take action to prevent the spread of the problem and minimize crop losses.

The use of robots in crop monitoring offers several advantages over traditional methods, such as manual inspections and satellite imagery. Robots can operate autonomously and continuously, providing real-time data on crop conditions and enabling farmers to make more informed decisions about irrigation, fertilization, and pest control. Robots can also cover large areas quickly and efficiently, reducing the time and labor required for crop monitoring. However, there are also some challenges associated with using robots for crop monitoring. One of the main challenges is the cost of the robots and the associated technology, which can be expensive for small farmers. There is also a need for specialized training and expertise to operate and maintain these robots. Crop monitoring using robots has the potential to greatly improve crop management practices and increase yields. By providing farmers with detailed data on crop health and growth, robots can help farmers make more informed decisions and optimize their use of resources.

Overall, crop monitoring using robots has the potential to revolutionize the way farmers monitor and manage their crops. As the technology continues to advance, it is likely that we will see more widespread adoption of this approach in the agricultural industry.

WEED MANAGEMENT

Weed management using robots is an innovative approach to weed control that involves the use of autonomous or semi-autonomous machines to detect and remove weeds in agricultural fields. Robots can be used to identify and remove weeds without the use of herbicides. These robots use computer vision to identify weeds and then use mechanical or thermal methods to remove them. Robots can be used to detect and remove weeds from fields, reducing the need for chemical herbicides and improving crop yields. These robots are equipped with sensors, cameras, and other technologies that enable them to identify weeds and apply targeted herbicides or mechanical methods to control them.

The advantages of using robots for weed management include:

Weed management using robots has the potential to be a valuable tool in modern agriculture, providing a more sustainable and efficient approach to weed control. However, there are also some challenges associated with weed management using robots, such as the need for accurate weed detection and identification, the potential for mechanical damage to crops, and the need for skilled operators to program and operate the machines. Weed management using robots is an emerging area of research and development that aims to reduce the use of herbicides and improve the efficiency and accuracy of weed control. Overall, weed management using robots has the potential to be more efficient, accurate, and sustainable than traditional weed management methods. However, it is still a relatively new field, and further research and development is needed to fully realize its potential.

DAIRY FARMING

Dairy farming using robotic technology has become increasingly popular in recent years. Robotic technology can automate many of the tasks involved in dairy farming, such as milking cows, feeding and monitoring their health. Dairy farming using robotics is an innovative approach that is gaining popularity in the agriculture industry. It involves the use of automated machines to handle tasks such as milking, feeding, and cleaning in a dairy farm. Robotic milking systems can milk cows without human intervention, reducing labor costs and improving animal welfare. Robotic milking systems are designed to milk cows without human intervention. The system includes a robot that uses lasers to locate the udder, attaches the milking cups, and monitors the milk flow. The robot also cleans the udder before and after milking, which helps to maintain udder health.

Robotic milking machines work by identifying the cow through a sensor and then cleaning and attaching the milking cups to the udder. The machine then automatically milks the cow and records the amount of milk produced. This data is then stored in a database that farmers can use to track the performance of individual cows. Robotic feeding machines can also be used to distribute feed to the cows at specific times of the day. This ensures that the cows receive a balanced diet, and it also reduces the workload for farmers.

Robotic dairy farming has several advantages over traditional farming methods. Firstly, it reduces labor costs by eliminating the need for manual labor. Secondly, it ensures consistency in the quality of milk produced as the robots are programmed to follow a set of predetermined standards. Additionally, it allows for more precise monitoring of the cows’ health and milk production, which can help farmers identify any health problems early on.

Robotic feeding systems can also be used to automate the feeding process. The system uses sensors to monitor the feed levels in the feed bunk and then dispenses the appropriate amount of feed to each cow. Robotic technology can also be used to monitor the health of the cows. For example, sensors can be placed on the cows to monitor their body temperature, activity level, and rumination. This information can then be used to identify cows that are not feeling well and may need medical attention.

Dairy farming using robotic technology can provide many benefits. It can help to increase efficiency, reduce labor costs, improve animal welfare, and provide better data for decision-making. However, it also requires a significant investment in technology and infrastructure, so it may not be feasible for all dairy farmers. Overall, robotic dairy farming can increase efficiency, productivity, and profitability in the dairy industry. However, it requires significant investment in technology and infrastructure, and farmers must also be trained to operate and maintain the equipment properly.

LIVESTOCK MONITORING

Livestock monitoring using robotics involves the use of automated systems and devices to manage, track, and monitor livestock in a farm or ranch. Robotics technology can improve livestock management by reducing labor costs, increasing productivity, and improving animal welfare. Sensors and cameras can be used to monitor the health and behavior of livestock, helping farmers identify health issues early and improve animal welfare. Here are some examples of how robotics can be used for livestock monitoring:

Livestock monitoring using robots is becoming increasingly popular among farmers and ranchers. With the help of robots, farmers can keep track of their livestock’s health, behavior, and location in real-time, which can help them make more informed decisions and improve the overall efficiency of their operations. Robots can be equipped with various sensors and cameras that can monitor the animals’ movements, temperature, and even their heart rate. This information can be transmitted to a central computer or a mobile device, allowing farmers to quickly identify any potential issues and take appropriate action.

One of the main advantages of using robots for livestock monitoring is that they can work around the clock, even in adverse weather conditions. This means that farmers can get a constant stream of data without having to physically check on their animals, which can be time-consuming and labor-intensive. Robots can also be programmed to perform specific tasks, such as identifying sick animals or separating them from the herd. This can help prevent the spread of diseases and improve the overall health of the herd. Robotics technology can be an effective tool for livestock monitoring, helping farmers and ranchers to improve productivity, animal welfare, and overall profitability. Using robots for livestock monitoring can be a game-changer for farmers and ranchers, allowing them to optimize their operations, improve animal welfare, and ultimately increase their profitability.

Conclusion:

The use of robotics in agriculture can help farmers to reduce costs, increase yields, and improve sustainability, while also reducing the labor-intensive nature of agricultural work. The use of robotics technology in agriculture has the potential to increase efficiency, reduce labor costs, and minimize environmental impacts. As technology continues to advance, we can expect to see even more innovative applications of robotics in agriculture.

Drone Technology in Agriculture

Drone technology has become increasingly popular in agriculture in recent years, offering numerous benefits to farmers and growers.  Drones are unmanned aerial vehicles equipped with cameras and other sensors that can capture high-resolution images, videos, and other data about crops. Drones can be used to apply fertilizers, pesticides, and other inputs precisely, reducing waste and improving the effectiveness of the applications. Irrigation management using drones is a modern and innovative approach that can help farmers manage their crops more efficiently. Crop monitoring using drones is a modern and effective way to gather data and insights about crops. Drones can also be used to identify crop stress, nutrient deficiencies, and other issues before they become visible to the naked eye. Livestock monitoring using drones is also a rapidly growing field that offers numerous benefits to farmers and ranchers. Drones can be used to monitor livestock in remote areas, providing farmers with real-time data on their animals’ health and behavior. Here are some ways in which drones are being used in agriculture:

CROP MONITORING

Crop monitoring using drones is a modern technique that has been adopted by many farmers and agricultural companies. Drones, also known as unmanned aerial vehicles (UAVs), are equipped with various sensors and cameras that can capture high-resolution images of crops and farmland. To use drones for crop monitoring, farmers typically fly them over their fields and capture images and data. They can then use software to analyze this data and gain insights about their crops. Some drone manufacturers also offer software that can automatically identify crop stress and diseases from images captured by drones. Drones can be equipped with high-resolution cameras that can capture images of crops, allowing farmers to monitor crop health, growth, and yield. This can help them identify potential issues early on and take corrective action before the problem worsens. The images captured by drones can be used for a variety of purposes, such as crop mapping, soil analysis, crop health assessment, and yield prediction. With the help of these images, farmers and agricultural companies can identify areas of their fields that need attention, such as pest infestations, nutrient deficiencies, or areas that require irrigation. Crop monitoring using drones is also beneficial because it saves time and reduces the cost of manual labor. Drones can cover large areas of farmland quickly and efficiently, which allows farmers to monitor their crops more frequently and make better decisions about how to manage their fields. Furthermore, drones equipped with thermal sensors can detect temperature differences in crops, which can indicate plant stress or disease. This allows farmers to take proactive measures to prevent crop loss and optimize their yield. Crop monitoring using drones can provide farmers with a wide range of benefits. For example, it can help them to:

In summary, crop monitoring using drones is a powerful tool for modern agriculture. It allows farmers and agricultural companies to improve their crop management practices, save time and resources, and ultimately increase their crop yield and profitability. Overall, crop monitoring using drones can help farmers to make more informed decisions and improve their crop yield and quality.

PRECISION FARMING

Precision farming is an approach to agriculture that utilizes advanced technologies to optimize crop yields, reduce waste, and increase efficiency. One such technology that has gained significant traction in recent years is the use of drones, or unmanned aerial vehicles (UAVs), in precision farming. Drones can be used to apply fertilizers, pesticides, and other inputs precisely, reducing waste and improving the effectiveness of the applications. The use of drones in precision farming can lead to increased efficiency, reduced costs, and improved crop yields, while also minimizing the environmental impact of farming practices.

Drones can be used in a variety of ways in precision farming, such as:

FIELD MAPPING

Drones can create detailed maps of fields, which can help farmers identify variations in soil composition, moisture levels, and other factors that can impact crop health. Field mapping using drones in agriculture involves using small unmanned aerial vehicles (UAVs), commonly known as drones, to collect data about crop health, growth, and yields. Drones equipped with cameras and sensors can capture high-resolution images and data, which can then be analyzed to gain insights into crop conditions.

There are several benefits to using drones for field mapping in agriculture. Drones can cover large areas of land quickly and efficiently, allowing farmers to assess crop conditions and make informed decisions about irrigation, fertilization, and pest control. Drones can also be used to identify crop stress, nutrient deficiencies, and other issues before they become visible to the naked eye. To use drones for field mapping in agriculture, farmers typically first create a flight plan for the drone using specialized software. The drone is then flown over the fields, capturing images and data that can be processed using specialized software to create maps and visualizations of crop conditions.

In addition to field mapping, drones can also be used for other agricultural applications such as crop spraying, planting, and livestock monitoring. As drone technology continues to improve, it is likely that their use in agriculture will become more widespread, helping farmers to improve crop yields, reduce costs, and minimize environmental impact. Field mapping using drones in agriculture involves using unmanned aerial vehicles to gather data and create detailed maps of agricultural fields. These maps can be used by farmers to monitor crop health, identify potential problem areas, and make more informed decisions about irrigation, fertilization, and other farming practices. Drones equipped with high-resolution cameras or multispectral sensors can capture images of crops and fields from various angles, altitudes, and wavelengths. These images are then processed using specialized software to create accurate 2D or 3D maps, as well as other useful data such as plant height, density, and yield estimates.

The benefits of using drones for field mapping in agriculture include:

Overall, using drones for field mapping in agriculture can help farmers optimize crop yields, reduce costs, and improve sustainability by minimizing the use of inputs such as water and fertilizer.

IRRIGATION MANAGEMENT

Drones equipped with thermal imaging cameras can detect areas of crops that are experiencing stress due to lack of water. This can help farmers adjust their irrigation practices to ensure that all crops receive the appropriate amount of water. Irrigation management using drones is an emerging technology that has the potential to revolutionize agriculture. With drones, farmers can monitor their fields more efficiently, accurately, and at a lower cost than traditional methods. Here are some of the ways that drones can be used for irrigation management:

Irrigation management using drones is a modern and innovative approach that can help farmers manage their crops more efficiently. Drones equipped with cameras and sensors can be used to monitor crop growth, detect water stress, and optimize irrigation scheduling. Overall, irrigation management using drones has the potential to improve crop yields, reduce water waste, and increase efficiency in agriculture. The use of drones for irrigation management can help farmers to optimize their water usage, reduce costs, and improve crop yields.

LIVESTOCK MONITORING

Livestock monitoring using drones is a rapidly growing field that offers numerous benefits to farmers and ranchers. Drones can be used to monitor livestock in remote areas, providing farmers with real-time data on their animals’ health and behavior. Here are some of the ways in which drones are used for livestock monitoring:

Hence, livestock monitoring using drones can help farmers save time and resources while improving animal welfare and productivity. However, it’s important to note that there are regulatory considerations and potential privacy issues that need to be addressed when using drones for this purpose.

Finally, we can conclude that drones have the potential to increase crop yields, reduce input costs, and improve farm efficiency and sustainability.

Source: OpenAI’s chatGPT

Startup महाकुंभ का – IFTSC’23

AICRA organizing 3rd IndiaFirst Tech Startup Conclave “Startup Ka Mahakumbh” on 25th & 26th April’2023 at Vigyan Bhawan, New Delhi.
Secure your participation as Startup, Delegate, Investor, Exhibitor, Sponsor.
For passes, visit https://indiafirststartup.com/IFTSC-23

OpenAI’s chatGPT

OpenAI is an American Artificial Intelligence research laboratory comprising of the non-profit OpenAI incorporated (OpenAI Inc.) and its for-profit subsidiary corporation OpenAI Limited Partnership (OpenAI LP). The organisation was founded in San Francisco in 2015 by Sam Altman, Reid Hoffman, Jessica Livingston, Elan Musk, Ilya Sutskever,   Peter Thiel and others..but currently it’s key persons include Greg Brockman (President and chairman), Sam Altman (CEO), Ilya Sutskever (Chief Scientist), and Miro Murali (CTO). It’s headquarter is situated at the Pioneer Building in San Francisco, California, US with 375 employees. It was founded on December 10, 2015 with mission to ensure that artificial Intelligence benefits all of humanity. OpenAI conducts artificial Intelligence research with the declared intention of promoting and developing a friendly AI. The OpenAI system run on the fifth most powerful supercomputer in the world. DALL-E, GPT-4, OpenAI Five, chatGPT, and OpenAI Codex are some important products of this company. Microsoft founder Bill Gates recently said that OpenAI’s GPT AI model is the most revolutionary advance in technology since 1980..

Tutorial for Beginners (English)
Tutorial for Beginners (Hindi)
Tutorial for Beginners (Hindi)
Tutorial for Beginners (Hindi)

For more information please see the following sites

Wikipedia

OpenAI
https://openai.com
OpenAI

Artificial Intelligence in Smart Futuristic Agriculture

AI-powered Technologies in Futuristic Smart Farming

Artificial Intelligence-driven Technologies in Agriculture

Artificial Intelligence in agriculture is the creation and study of computers and software’s capable of intelligent behavior which helps in creating ‘Self Learning Algorithms & Capabilities’, leading to automation on-ground agriculture practices. Farm activities such as field sowing, ploughing, fertilizer application, insecticide spray, harvesting, weeding and post-harvest land-replenishing can be carried out by the applications and processes developed around AI. AI comes as a great boon to the agricultural sector which is slowly but surely making its presence in agricultural sector.

Agriculture is a dynamic domain where solutions cannot be generalized to suggest a common solution. AI techniques have enabled us to capture the intricate details of each situation and provide a solution that is best fit for that particular problem. AI can be employed for agricultural product monitoring and storage control. Storage, drying and grading of the harvested crops are important aspects of agriculture. Hence, AI can be employed in addressing various food monitoring and quality control mechanisms. The crop yield prediction is very beneficial for marketing strategies and crop cost estimation.

Listen to this article on YouTube and Speechify.

AI in Agriculture

https://speechify.page.link/wjj4ibPQgdzX51KH8

GEAC Approves GM Mustard for Environmental Release

India’s apex Biotech regulator, Genetic Engineering Appraisal Committee (GEAC), has recommended indigenously developed India’s first-ever transgenic food crop genetically modified mustard containing two alien genes isolated from non-pathogenic soil bacterium called Bacillus amyloliquefaciens. The transgenic mustard variety DMH – 11 was developed by Dr. Deepak Pental, and his colleagues from the Centre for Genetic Manipulation of Crop Plants at the University of Delhi, South Campus.
GM mustard DMH – 11 was created through transgenic technology involving the Bar, Barnase and Barstar gene system. The Barnase gene confers male sterility, while the Barstar gene restores DMH – 11’s ability to produce fertile seeds. The insertion of the third gene Bar enables DMH – 11 to produce phosphinothricin-N- acetyl-transferase, the enzyme responsible for Glufosinate resistance. Glufosinate resistance is due to an enzyme expressed by the Bar (Bialaphos resistance) gene. The cloned Bar gene (derived from Streptomyces hygroscopicus) encodes for the synthesis of phosphinothricin-N- acetyl-transferase (PAT). PAT enzymes produced by the Bar gene, deactivate Bialaphos (the tripeptide precursor to phosphinothricin) through acetylation to form an inactive, non-toxic product. This enzyme is responsible for detoxifying the active ingredient in the herbicide Glufosinate-phosphinothricin. Phosphinothricin’s mechanism of action involves the inhibition of Glutamine synthetase, which prevents the detoxification of ammonia and subsequently causes toxic buildup within plant cells. Inhibition of glutamine synthetase also leads to an overall reduction in Glutamine levels. In plants, Glutamine acts as a signaling molecule, and as a major amino acid donor for nucleotide synthesis. Hence, this GM mustard DMH – 11 is Glufosinate tolerant, and therefore it is thought to encourage farmers to liberally spray the herbicide upon commercialization.


So far, India has not approved any commercial cultivation of transgenic food crops. It will be the first GM food to be approved by Govt of India for commercial cultivation. This approval for GM mustard was a long wait but better late than never. Transgenic Bt-cotton was allowed for cultivation by the Government of India in the year 2002. The decision comes on the backdrop of soaring edible oil prices in the past few years. India meets 70 percent of its domestic cooking oil demand by importing a variety of oils such as sunflower, soybean, and palm. Still, we are continuing to import larger volumes of GM soybean oil from USA, Brazil, and Argentina. India has imported 4.1 million tonnes of GM soybean oil in 2021-22. The decision by GEAC was taken during its 147th meeting held on October 18, 2022. The regulator recommended the “environmental release of mustard hybrid DMH-11 for its seed production and testing as per existing ICAR guidelines and other rules/regulations before proper commercial release. GM mustard was found not to pose any food allergy risks and has demonstrated increased yields over existing mustard varieties. Conflicting details and results regarding the field trials and safety evaluations conducted on GM mustard have delayed its approval for commercial cropping.


In 2017, GEAC has recommended the commercial release of GM mustard but due to objections from Swadeshi Jagran Manch, an affiliate of RSS, the Govt. of India has put it on hold. Similarly, transgenic brinjal was put on indefinite moratorium in 2010 by then environment minister Jairam Ramesh. GM mustard technology will now accelerate mustard breeding programmes for bringing a new revolution in mustard farming by enhancing edible oil production in the country. The project to develop DMH – 11 received funding from the National Dairy Development Board of India and the Department of Biotechnology (DBT).

To view GEAC report, please click the following link:

An article by Dr. Renu Swarup, former Secretary, DBT on Gene- based technology for enhancing Food Security

Futuristic Crop Farming

Drone capturing image of the field

The technological revolution in farming led by advances in robotics and sensing technologies looks set to disrupt modern practice. Although some of these technologies are already available, most are at the research stage in labs. Farmers have adopted more technology in their pursuit of greater yields. But advances in robotics and sensing technologies are threatening to disrupt today’s agribusiness model. There is the potential for intelligent robots to change the economic model of farming so that it becomes feasible to be a small producer. Twenty-first-century robotics and sensing technologies have the potential to solve problems. Modern technology that can autonomously eliminate pests and target agrichemicals better will reduce collateral damage to wildlife, lower resistance and cut costs. The Food and Agriculture Organization of the United Nations estimates that 20–40% of global crop yields are lost each year to pests and diseases. Work is underway to improve monitoring and maintenance of soil quality, and to eliminate pests and disease without resorting to indiscriminate use of agrichemicals. Intelligent devices, such as robots and drones, could allow farmers to slash agrichemical use by spotting crop enemies earlier to allow the precise chemical application or pest removal. Drones with precision sprayers apply agrochemicals only where they are needed. Drones are also being used for smarter applications of nitrogen fertilizer. Overuse of agrichemicals such as nitrogen fertilizer is causing harm to the environment and human health.
For more information, please see an article by ANTHONY KING

Electronics ‘Tattoos’

Source images: Carnegie Mellon University

Electronic “tattoos” using thin-film electronic patches would be used for monitoring healthcare in future in terms of better signal quality, higher patient comfort and wearability. Applications include Electrocardiography (heart monitoring), electroencephalography (brain activity monitoring), electrooculography (eye movement monitoring) or electromyography (recording of muscle activity) both for hand gesture classification and detection of facial expressions.

For more information about this please click the links..

https://onlinelibrary.wiley.com/doi/full/10.1002/adfm.202205956

http://sml.me.cmu.edu/

(https://spm.isr.uc.pt/

Quantum Dot LED lights from Rice Husk

Rice with Husk
Photo: Pixabay

Quantum Dot LED lights from Rice Husk

The research team from Hiroshima University is searching a method to fabricate the silicon (Si) quantum dots (QD) LED lights from rice husk. Generally, QDs involving toxic material such as Lead (Pb), Cadmium (Cd) or other heavy metals have environmental concerns, but the proposed process and fabrication method minimizes these concerns. Silicon (Si) is non-toxic and found abundantly in nature and has photoluminescence properties. The team used a combination of milling, heat treatments, and chemical etching to process the rice husk silica. Then, its surface was chemically functionalized for high chemical stability and high dispersivity in the solvent, with 3 nm crystalline particles to produce the SiQDs that luminesce in the orange-red range. Milling rice to separate the grain from the husks produces about 100 million tons of rice husk waste globally each year. Their new method would transform agricultural waste into state-of-the-art light-emitting diodes in a low-cost, environmentally friendly way. For more information, please click the following link:
https://lnkd.in/dnR9gqSF

Photo by Consoler creative257 on Pexels.com

Nanosensors for Water Quality Monitoring

Photo by Pixabay on Pexels.com

Nanosensors based on nanomaterials are being designed for high-efficiency, multiplex-functionality, and high-flexibility sensing applications. Many existing nanosensors have the inherent capacity to achieve such goals; however, they require further development into consumer- and operator-friendly tools with the ability to detect analytes in previously inaccessible locations, as well as at a greater scale than heretofore possible. Here, I discuss how nanotechnology-enabled sensors have great, as yet unmet, promise to provide widespread and potentially low-cost monitoring of chemicals, microbes, and other analytes in drinking water.

Referance:

Vikesland, P.J. Nanosensors for water quality monitoring. Nature Nanotech 13, 651–660 (2018). https://doi.org/10.1038/s41565-018-0209-9

Drone Technology for Growing Trees

Image: REUTERS/Feisal Omar

Deforestation remains a huge problem, but drones could help solve that

It is estimated that the world loses between 74,000 and 95,000 square miles of forest a year – that’s an area the size of 48 football fields lost every minute. We are chopping down about 15 billion trees a year and planting about 9 billion. So there’s a net loss of 6 billion trees a year. Hand planting trees is slow and expensive. To keep pace with the tractors and bulldozers clearing vast areas of land, we need an industrial-scale solution. A drone scans the topography to create a 3D map. Then the most efficient planting pattern for that area is calculated using algorithms. A drone loaded with germinated seeds fires pods into the ground at a rate of one per second, or about 100,000 a day. Scale this up and 60 drone teams could plant 1 billion trees a year if a drone could plant up to 100,000 trees a day.

https://www.facebook.com/watch/?v=10154789863741479

Source:

https://www.weforum.org/agenda/2017/06/drones-plant-100000-trees-a-day/

Bridge Courses for Re-Skills and Up-Skills in Emerging Futuristic Technologies in India

Important Courses such as Big Data Analytics, Cyber Security, Artificial Intelligence, Robotics, Internet of Things for re-skills and up-skills by CDAC, Nieled, Meity, NAASCM, Govt. of India

Advertisement in Hindustan Times newspaper (Hindi) dated 3.4.22

Urban Farming Pact with Pusa institute for creating green jobs by Delhi Government

For creating green jobs, Urban Farming pact with Pusa institute by Delhi Government has been carried out to manage kitchen waste usage, waste water usage, and to enhance cooling effect and rooftop farming. It will also create green jobs as well as fresh produce to the increasing population of Delhi. An article is published today in Hindustan Times newspaper related to this pact. This will include the training about the hydroponics, aeroponics, rooftop farming to the RWS of various colonies and localities of Delhi. For more information please see the below artical:

5G: The Biggest Revolutionary Technology

5G technology is going to eliminate the issues related to bandwidth, performance, access, and latency limitations on connectivity worldwide. This technology has the potential in several new applications such as smart cities, smart homes, autonomous vehicles, IoT, e-health, smart and intelligent health care management, smart agriculture, and similar smart and intelligent futuristic science and technology applied in day to day activities. All these applications require high data-rate instantaneous communication, low latency and massive connectivity. In this direction, 5G could play a vital role having several potential applications as mentioned above. Hence, it will be the biggest revolutionary technology in comming years.

5G connectivity and applications (Credit photo telecom.com)

https://www.facebook.com/groups/2141479796167784/permalink/3193084301007323/

The potential of Agriculture Technology via Public Partnership Programmes

The potential of Agriculture Technology via Public Partnership Programmes (PPPs)

The centre and state governments are interested to deliver hi-tech services to farmers through PPPs. This model can play an important role for creating a viable ecosystem for smart futuristic agriculture technology.
For more information, please browse the link:

High Tech Services to Farmers

For example:

Use of Drone to spray pesticides and fertilizers

(Photo Credit:Siva Saravanans)

Scientific Research in India

Publications in various disciplines of science

https://www.linkedin.com/posts/ramgopalrao_research-ministries-corporates-activity-6911947560832167936-PCoq?utm_source=linkedin_share&utm_medium=android_app

World’s Tiniest NanoAntena

Researchers at University of Montreal have created a NanoAntena using DNA. This world’s tiniest NanoAntena is designed by Alexis Vallee-Belisle and his team to monitor the motion of proteins. The fluorescent NanoAntena receive light in one colour and depending on protein movement it sense, then transmit light back in another colour, which can be detected. For more information please click the link below

https://www.nature.com/articles/s41592-021-01355-5