Biotechnology: fundamentals and applications

Biotechnology is the use of living organisms, cells and molecules to create new products and processes. In agriculture, biotechnology finds its application in the development of new plant varieties with desired characteristics such as disease resistance, yield and adaptation to changing climatic conditions.

Genetic modification of plants: benefits and concerns

Genetic modification (GM) of plants involves making changes to the DNA of plants to introduce desired traits. This may include resistance to pests, higher nutritional value or even the ability to grow under unfavorable conditions. However, there are concerns about potential negative health and environmental impacts associated with this approach.

Debate surrounding GMOs

The use of genetically modified organisms (GMOs) is the subject of lively debate. Some see in them the key to solving global food security problems, while others fear potential negative consequences. It is important to take these aspects into account when developing and implementing GMOs.

Ethics and regulation

Advances in biotechnology are forcing us to reconsider ethical and regulatory aspects. Which changes to the genome are considered acceptable and which are not? How can we ensure the safe introduction of GMOs and reliably monitor their environmental and health impacts?

Biotechnology and genetic modification of plants represent a two-sided coin. On the one hand, they provide unique tools to improve agriculture and address global challenges. On the other hand, there is a need for a balance between innovation and responsible handling of potential risks. Effective regulation, discussion and education are key factors for the successful use of biotechnology in modern agriculture.

The post Biotechnology and Genetic Modification of Plants: Current Approaches and Discussions appeared first on AgriPrecision.

Pros of vertical farming

Many farmers are already switching to this type of growing crops. By the way, in New Zealand, such a farm has already launched sales. Products can be found in major stores in New Zealand.

What are the advantages of vertical farms?

Year-round harvest

The biggest advantage of vertical farming is the fact that it is not dependent on the weather. This means that you can achieve a consistent harvest all year round without worrying about the impact of unfavorable weather conditions on production and yields. Farming in a protected, well controlled and managed environment gives gardeners confidence and peace of mind and predictable yields. By removing the influence of Mother Nature, the concept of “seasonal culture” disappears.

Independence from weather and climate conditions

Growing in a fully enclosed, climate controlled environment completely eliminates the need to rely on or worry about the weather. Field crops can be ruined by excessive rain, wind and drought (or pests!). Vertical farming provides 100% crop certainty.

Efficient use of space

It goes without saying that traditional farms need fertile arable land. But vertical farms can be designed and built in any climate and location – regardless of weather conditions or temperature extremes, topography and soil type.

Minimal water consumption

One of the major advantages of vertical farming is that hydroponic growing uses only about 10% of water. Since the water remains clean after use, this also allows it to be recycled and reused, reducing costs and minimizing waste.

Sustainability

Home vertical farming can be good for the environment because these farms greatly reduce the amount of fossil fuels needed for farm equipment that is not needed for seeding, fertilizing, weeding and harvesting on vertical farms.

No chemicals or pesticides

Growing food on a vertical farm, if properly managed, makes it possible to completely eliminate the need for pesticides because pests cannot penetrate the controlled environment to cause crop damage. As for fungal diseases, they struggle to hold on as moisture levels are controlled. The end result is a product that is better, healthier, safer, with dried leaves. They are clean and ready to eat.

Reduced transportation costs

When it comes to food production, shipping is usually the most expensive part of the supply chain. And crops are often shipped across continents and oceans. Growing food closer to where the consumer lives is a huge advantage for vertical farming, as it can significantly reduce transportation costs, CO2 emissions and the need for refrigerator storage, making food fresher and more profitable.

The post Everything About Vertical Trusses appeared first on AgriPrecision.

Artificial intelligence (artificial intelligence) analyzes databases, offers consumers advertising, tracks sales and predicts the future. The role of machine learning is also growing. It is used in text analysis, image analysis, and personalization. IT technologies are being actively used in the agro-industrial complex.

Agribusiness in all countries is considered to be rather conservative in the introduction of high technologies. However, agriculture has started to use modern technologies, so there is hardly any sense to doubt the need for IT. In a few years, agricultural producers will wonder how they lived without artificial intelligence.

BI Intelligence Research predicts that global spending on smart agricultural technologies and systems including artificial intelligence and machine learning will triple by 2025, reaching $15.3 billion.

Artificial intelligence, machine learning and Internet technologies that provide real-time data to algorithms are significantly improving farm efficiency, crop yields and reducing food production costs. According to UN analysis, by 2050, the world’s population will increase by an additional 2 billion people. This requires a 60% increase in food production. Artificial intelligence and machine learning show just the potential to help achieve the expected food needs in 20-30 years.

Imagine that in a large agricultural holding of several tens of thousands of hectares, there are at least 40 major processes that need to be monitored, improved and controlled simultaneously. Understanding how weather, seasonal precipitation, bird and insect migration, fertilizer use for different crops, planting cycles, and irrigation cycles affect crop yields is an ideal task for machine learning. How successful a crop can be financially depends more than ever on a variety of great data. That’s why farmers, cooperatives and agricultural development companies are doubling down on the use of data-driven measures. And they’re also scaling up the use of artificial intelligence and machine learning to improve agricultural yields and quality.

So what does agribusiness AI have to offer? It turns out a lot.

Surveillance systems

AI-based video surveillance systems are already being used to monitor the field in real time. This helps to detect animal or human misbehavior and sends an alert immediately. Artificial intelligence and machine learning in this case reduce the risks of domestic and wild animals accidentally destroying crops. These smart technologies report unwanted guests and the possibility of robbery, for example, on a remote farm.

Given the rapid development of video analytics, which is based on AI and MN algorithms, everyone involved in agriculture can protect their fields and building perimeters. AI video surveillance systems are easily applicable for both large agribusinesses and individual small farms. Experts say that very soon, AI-based surveillance systems will be programmed to distinguish humans from cars.

Fields and drones

AI and MN improve yield predictions with real-time sensor data and visual analytics data from drones. The amount of data being collected by smart sensors and drones that stream real-time video is giving agricultural experts entirely new sets of information that have never been accessed before. Moisture, fertilizer and soil nutrient sensor data can now be combined to analyze the growth dynamics of each crop over time. MN is the ideal technology for combining powerful sets of information and providing recommendations to optimize yields. Drones have proven to be a reliable platform for collecting important data for agriculturalists. AI, MN, ground sensors, infrared imagery and real-time video analytics are all giving farmers new insights into how crop health and yields can be improved.

Now the UN, international agencies and major agricultural enterprises are using information from drones to improve pest management. Using infrared camera data from drones combined with sensors in the fields that monitor plant health levels, agribusinesses that utilize artificial intelligence can predict and detect pest infestations even before they happen.

Yield maps

Yield mapping is a new agricultural method. It relies on supervised machine learning algorithms to find patterns. Large datasets and their real-time insights are invaluable information for crop planning. In this way, it is possible to know the potential yield of fields before the growing season even begins. Using a combination of machine learning techniques to analyze 3D maps and drone data from soil color sensors, agriculture experts can now predict the potential yield of the land for a particular crop. To do this, a series of flights are performed to obtain the most accurate data set possible.

Machines instead of humans

Today, there is a shortage of workers in the agribusiness sector in some regions. This factor makes intelligent tractors, agrobotics and robotics based on artificial intelligence and machine learning a viable option for many agricultural businesses that are having difficulty finding workers. Large agricultural businesses and agribusinesses that can’t find enough employees are turning to robotics to cultivate hundreds of acres of land. Programming self-propelled robotic machinery, for example, to distribute fertilizer to each row of crops helps reduce operating costs and further increase field yields. The complexity of agricultural robots is rapidly increasing day by day.

Track and trace system

One of the pressing issues of our time is to improve the logistics and traceability of agricultural supply chains. It is about removing absolutely all obstacles on the way to the market of the freshest and safest possible products. The pandemic, by the way, accelerated the increased implementation of traceability throughout the agricultural supply chain in 2020. Its implementation continues this year. A well-established and managed product traceability system helps provide greater transparency and control in the supply chain and reduce inventory shrinkage. A modern traceability system can distinguish between the destinations of shipments and the containers where shipments enter. The most advanced tracking systems rely on advanced sensors to provide more detailed information about the status of each shipment. RFID and IoT sensors are becoming more prevalent in manufacturing. Walmart has launched a pilot project to see how RFID can optimize tracking in a distribution center and increase efficiency 16 times over manual methods.

Artificial Intelligence and pesticides

One of the most common applications of AI and machine learning in modern agricultural production is the task of optimizing and correctly combining different kinds of pesticides. As well as limiting their application to only those fields that need treatment. Such a system helps reduce costs while increasing crop yields. How does it work? Using smart sensors combined with visual data streams from drones, artificial intelligence programs in agriculture can now identify the most infested areas of crop land. Using supervised machine learning algorithms, the AI then determines the optimal pesticide mix to reduce the threat of further pests spreading and infecting healthy crops.

Animals and machines

One of the fastest growing applications of artificial intelligence and machine learning in agriculture is in animal studies. Specifically, monitoring the health of livestock, including vital signs, daily activity levels, and the amount of food consumed. Understanding how each livestock species responds to diet and housing conditions is critical to understanding how to better maintain and treat animals in the long term. Machine learning and artificial intelligence are being used to understand what makes cows satisfied and happy every day.This factor is important for producing more milk.For many farms that rely on cows and livestock, this field is opening up a whole new understanding of how farms can be more profitable.

IT technology is being actively adopted in agro today.AI and MN are opening up vast opportunities for farmers around the world. The software segment is growing every year and these opportunities need to be capitalized on. Digital technology helps in improving the efficiency of the agro sector for specific farms. At the government level, it enables successful agri productivity management.

Yield prediction models, real-time data analysis, video surveillance systems, artificial intelligence for irrigation and weed control are the key trends in the agri market.

All of these things are working and producing results today.

The post Is the Agricultural Sector a Fertile Area for Artificial Intelligence? appeared first on AgriPrecision.

Precision farming for efficient use of resources

Precision farming represents a revolution in resource optimization. Using geospatial data, sensors, and artificial intelligence, farmers can pinpoint locations that require fertilizer or irrigation, reducing overuse of resources and pollution.

Efficient waste and resource management

Technological breakthroughs also offer innovative methods of waste and resource management. Biogas plants, recycling organic waste and utilizing biomass for energy production are all made more accessible through modern technology, helping to reduce environmental impact.

Improved protection against pests and diseases

The use of drones, sensors and data analysis enables early detection of pests and diseases. This makes it possible to reduce the use of chemical pesticides, which in turn helps to conserve biodiversity and improve product quality.

Promoting agroecological practices

Technological breakthroughs also support the adoption of agroecological practices such as mulching, crop rotations and natural pest control methods. These approaches help maintain soil fertility and promote long-term sustainability.

Modern technology is becoming a powerful tool in addressing the environmental challenges associated with agriculture. However, it is important to remember that successful sustainable development requires a balance between innovation and respect for nature. Technology must be used wisely and in combination with agroecological approaches to ensure productivity, environmental sustainability and societal well-being.

The post Sustainability and Environmental Challenges in the Face of Technological Breakthroughs in Agriculture appeared first on AgriPrecision.