#Artificial Intelligence in Agriculture

[entrepreneurbar]

A profound transformation is silently unfolding within the expansive realm of agricultural practice, where terrestrial and celestial realms converge to orchestrate life cycles. This metamorphosis is propelled by the convergence of technological advancements and traditional methodologies, with the Internet of Things (IoT) emerging as a potent catalyst reshaping longstanding agricultural paradigms. This paper elucidates the burgeoning landscape of IoT integration within agriculture, delineating its multifaceted implications for enhancing operational efficiency, ecological sustainability, and productivity within this critical sector.

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[sblai]

AI & PLM in Agriculture: Intelligent Duo for Yields & Sustainability

PLMs (Predictive Language Models) in agriculture harness AI to analyze satellite imagery, sensor data, weather reports, soil metrics, and historical yields, offering valuable insights for optimized farming decisions, enhanced crop yields, and risk mitigation. Read more at https://www.sblcorp.ai/ai-plm-in-agriculture-intelligent-duo-for-yields-sustainability/

[agreads]

NEC X invests in AgTech startup VERDI, integrates AI-powered platform with NEC’S CropScope smart farming initiative

[techsoulculture]

Artificial Intelligence in Agriculture: Global Modernization

Artificial Intelligence AI is one of the most promising technologies in the global agriculture industry, which is through a transformative

[livemintvideos]

Finance Minister Nirmala Sitharama in the Union Budget 2023 made some major announcements during her one-hour speech. One such announcement was the decision to set up 100 labs to develop applications using 5G services.

[mindblowingscience]

Water scarcity and the high cost of energy represent the main problems for irrigation communities, which manage water for this end, making it available to agriculture. In a context of drought, with a deregulated and changing electricity market, knowing when and how much water crops are going to be irrigated with would allow those who manage them to overcome uncertainty when making decisions and, therefore, guide them towards objectives like economic savings, environmental sustainability, and efficiency. For this, data science and Artificial Intelligence are important resources.

Continue Reading.

[ivie-online]

technologists who lack radical/revolutionary politics argue that new tech will lead to social change, ignoring the fact that we are (and have been) perfectly equipped to address many of societys ills. our states are perfectly aware of our nutritional needs, and our collective agricultural output is astronomical. the computers we already have are more than enough to handle the incredibly complex logistics of getting things where they’re needed, without hyper ‘intelligent’ super computers. it’s not a lack of fancy new tools keeping us from progress, it’s a lack of social and political will.

[jcmarchi]

Open-Source Platform Cuts Costs for Running AI - Technology Org

New Post has been published on https://thedigitalinsider.com/open-source-platform-cuts-costs-for-running-ai-technology-org/

Open-Source Platform Cuts Costs for Running AI - Technology Org

Cornell researchers have released a new, open-source platform called Cascade that can run artificial intelligence (AI) models in a way that slashes expenses and energy costs while dramatically improving performance.

Artificial intelligence hardware – artistic interpretation. Image credit: Alius Noreika, created with AI Image Creator

Cascade is designed for settings like smart traffic intersections, medical diagnostics, equipment servicing using augmented reality, digital agriculture, smart power grids and automatic product inspection during manufacturing – situations where AI models must react within a fraction of a second. It is already in use by College of Veterinary Medicine researchers monitoring cows for risk of mastitis.

With the rise of AI, many companies are eager to leverage new capabilities but worried about the associated computing costs and the risks of sharing private data with AI companies or sending sensitive information into the cloud – far-off servers accessed through the internet.

Also, today’s AI models are slow, limiting their use in settings where data must be transferred back and forth or the model is controlling an automated system. 

A team led by Ken Birman, professor of computer science in the Cornell Ann S. Bowers College of Computing and Information Science, combined several innovations to address these concerns.

Birman partnered with Weijia Song, a senior research associate, to develop an edge computing system they named Cascade. Edge computing is an approach that places the computation and data storage closer to the sources of data, protecting sensitive information. Song’s “zero copy” edge computing design minimizes data movement.

The AI models don’t have to wait to fetch data when reacting to an event, which enables faster responses, the researchers said.

“Cascade enables users to put machine learning and data fusion really close to the edge of the internet, so artificially intelligent actions can occur instantly,” Birman said. “This contrasts with standard cloud computing approaches, where the frequent movement of data from machine to machine forces those same AIs to wait, resulting in long delays perceptible to the user.” 

Cascade is giving impressive results, with most programs running two to 10 times faster than cloud-based applications, and some computer vision tasks speeding up by factors of 20 or more. Larger AI models see the most benefit.

Moreover, the approach is easy to use: “Cascade often requires no changes at all to the AI software,” Birman said.

Alicia Yang, a doctoral student in the field of computer science, was one of several student researchers in the effort. She developed Navigator, a memory manager and task scheduler for AI workflows that further boosts performance.

“Navigator really pays off when a number of applications need to share expensive hardware,” Yang said. “Compared to cloud-based approaches, Navigator accomplishes the same work in less time and uses the hardware far more efficiently.”

In CVM, Parminder Basran, associate research professor of medical oncology in the Department of Clinical Sciences, and Matthias Wieland, Ph.D. ’21, assistant professor in the Department of Population Medicine and Diagnostic Sciences, are using Cascade to monitor dairy cows for signs of increased mastitis – a common infection in the mammary gland that reduces milk production.

By imaging the udders of thousands of cows during each milking session and comparing the new photos to those from past milkings, an AI model running on Cascade identifies dry skin, open lesions, rough teat ends and other changes that may signal disease. If early symptoms are detected, cows could be subjected to a medicinal rinse at the milking station to potentially head off a full-blown infection.

Thiago Garrett, a visiting researcher from the University of Oslo, used Cascade to build a prototype “smart traffic intersection.”

His solution tracks crowded settings packed with people, cars, bicycles and other objects, anticipates possible collisions and warns of risks – within milliseconds after images are captured. When he ran the same AI model on a cloud computing infrastructure, it took seconds to sense possible accidents, far too late to sound a warning.

With the new open-source release, Birman’s group hopes other researchers will explore possible uses for Cascade, making AI applications more widely accessible.

“Our goal is to see it used,” Birman said. “Our Cornell effort is supported by the government and many companies. This open-source release will allow the public to benefit from what we created.”

Source: Cornell University

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[0firstlast1]

AI, ML, ...

The periodicity that I publish my short audiovisuals in podcast format is weekly.

As I became 'immersed' in Artificial Intelligence, Machine Learning, chatbot, OpenAI, ChatGPT, DALL-E, ... I temporarily changed the periodicity to biweekly.

Maybe I'll extend the periodicity for monthly until I conclude my personal opinion about the curious subjects: What are they and what can they be useful for my use?

At the top of this publication I placed some images generated by Artificial Intelligence from commands.

In the first image the Artificial Intelligence forgot to put engines on the plane, so even if the plane is piloted by a famous Hollywood actor the plane will not be able to fly to capture Putin, good for him.

In the second image, taking advantage of the fact that judaism is in fashion on TV, I remembered one of the famous ones from among them and asked the Artificial Intelligence for an image about the subject, more than one was generated, I chose two that represent very well what I think about nazism, judaism, and psychology, all side by side.

In the fourth image an image about one of the symbols of capitalism, banks, more specifically about the new technologies that dismissed multitudes of workplaces, including banks.

I really didn't feel threatened by the result of the generated images, if I wanted I would finish arts with much more quality, but as a sketch the Artificial Intelligence took less than a minute.

[nuadox]

Technique using light and artificial intelligence is effective in selecting immature soybean seeds

- By Luciana Constantino , Agência FAPESP - 

Historically based on tradition and experience, the decision-making process in agriculture has been transformed in recent years by technological innovations that scale up production and provide solutions to the challenges posed by pests, natural limitations on arable land and the effects of climate change.

Brazilian researchers have developed a technique to help select seeds of soybeans and other legumes in accordance with maturity stages, assuring physiological quality without destroying samples.

The scientists used light and artificial intelligence (AI) to show that chlorophyll fluorescence is an effective and reliable indicator of soybean seed maturity. They validated the results by means of machine learning algorithms. The novel technique can be used to classify commercial seeds.

The greener and less mature the seeds, the less vigor and germinating power they have, so that their quality is lower. As a result, the market value of soybean seed lots with more than 8% green seeds is reduced and they cannot be exported. Green seeds also produce less oil, with higher acidity and higher refining costs.

Manual seed quality analysis is required by law in Brazil. It must be performed by a technician accredited with the Ministry of Agriculture and entails visual separation based on color. Green seeds are discarded and destroyed, forming waste. 

“I consider this study a milestone. No studies in the literature to date have addressed the possibility of separating seed stages based on chlorophyll fluorescence. The method can be used for other legumes besides soybeans. It’s a major advance in scientific knowledge,” said Thiago Barbosa Batista, first author of an article on the study published in the journal Frontiers in Plant Science.

The research was part of Batista’s PhD thesis, developed with FAPESP’s support. His thesis advisor was Edvaldo Aparecido Amaral da Silva, a professor at São Paulo State University's School of Agricultural Sciences (FCA-UNESP) in Botucatu, and last author of the article.

“Phenotyping various kinds of seed was the main reason for starting our thematic group. We focused on chlorophyll retention and its association with low quality, and this in turn led to the need to analyze the stages of seed development. The results of this study enhance the reliability of maturity characterization when seeds are similar shades of green, especially in nearby stages,” said Amaral da Silva, who leads a project on the “green seed problem”.

The study was conducted in partnership with Clíssia Barboza da Silva, a researcher at the Radiobiology and Environment Laboratory belonging to the University of São Paulo's Center for Nuclear Energy in Agriculture (CENA-USP). Barboza da Silva is also supported by FAPESP via three projects (17/15220-7, 18/03802-4, and 18/01774-3).

“This technique avoids destroying seeds, which are classified automatically by the AI algorithm. We currently analyze samples, but it could be done seed by seed in future,” she said.

For some years Barboza da Silva has analyzed seeds using light-based technologies such as autofluorescence spectral imaging. In September 2021, a study led by her showed that images based on autofluorescence could be used to detect changes in the optical properties of soybean seed tissue and consistently distinguish between seeds with high and low vigor. An article on the study was published in Scientific Reports.

Maturity in images

The researchers sowed soybean seeds in pots, maintaining relative air humidity at 65% and average air temperature at 24.2 °C. Pods were collected manually during the maturation phase, and the seeds were classified by reproductive stage, as R7.1 (start of maturation), R7.2 (mass maturity), R7.3 (seed disconnected from mother plant), R8 (harvest point), or R9 (final maturity).

Physical parameters, germination, vigor and pigment dynamics were analyzed for seeds collected at different stages of maturation.

High-resolution autofluorescence spectral images (2192x2192 pixels) were captured using a VideometerLab4 system with light-emitting diodes (LEDs) at different excitation wavelengths combined with long-pass optical filters. 

Autofluorescence signals were extracted from images captured at different excitation/emission combinations, but the researchers concluded that the combinations 660/700 nanometers (nm) and 405/600 nm performed fastest and most accurately in identifying the different stages of seed maturation.

Chlorophyll is highly fluorescent. It emits light when exposed to radiation at specific wavelengths because it does not use all the energy from the light and “loses” part of it via fluorescence. This “surplus” is captured by the equipment, which converts it into an electrical signal, generating an image with varying shades of gray as well as white and black. The lighter the area, the higher the chlorophyll content, showing that the seed is less mature.

Mature seeds normally retain chlorophyll as a source of energy while the nutrients required for development of the young plant (lipids, proteins and carbohydrates) are being stored. After fulfilling this function, the chlorophyll degrades, and the less chlorophyll remains, the more advanced the seed is in the maturation process, with more nutrients and better quality.

The “green seed problem” refers to chlorophyll retention in mature seeds and is associated with lower oil and seed quality. It can be caused by frost but is exacerbated by the high temperatures and water stress brought by climate change in recent years.

The article “A reliable method to recognize soybean seed maturation stages based on autofluorescence-spectral Imaging combined with machine learning algorithms” is at: www.frontiersin.org/articles/10.3389/fpls.2022.914287/full.

This text was originally published by FAPESP Agency according to Creative Commons license CC-BY-NC-ND. Read the original here.

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Header image: Researcher Clíssia Barboza da Silva capturing images of soybean seed chlorophyll fluorescence with the VideometerLab4. Credit: Thiago Barbosa Batista/UNESP.

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[ciobulletin1]

The Top 10 Organic Farming Techniques for Maximizing Yield

Organic farming is more than just a trend—it's a sustainable agriculture practice that prioritizes soil fertility, crop diversity, and ecological balance. For many farmers, this approach is a deeply rooted philosophy, emphasizing a harmonious relationship with nature. By leveraging natural processes and avoiding synthetic chemicals, organic farmers can produce healthy, nutrient-rich crops while preserving the environment for future generations.

Organic farming is about nurturing the soil, recognizing it as a living ecosystem rather than just a medium for plants. Techniques like composting and green manuring enrich the soil with organic matter, fostering a vibrant microbial community that helps plants thrive. Farmers who practice crop rotation and polyculture mimic natural ecosystems, enhancing biodiversity and resilience against pests and diseases.

This approach also involves a keen understanding of natural pest management. Instead of relying on chemical pesticides, organic farmers utilize biological pest control methods, such as introducing beneficial insects that prey on crop-damaging pests. This not only reduces the need for harmful chemicals but also creates a balanced and sustainable agricultural environment.

Water conservation techniques are another cornerstone of organic farming. Methods like drip irrigation and rainwater harvesting ensure that every drop of water is used efficiently, which is crucial in regions facing water scarcity. These practices help maintain the delicate balance of ecosystems while ensuring crops receive adequate hydration.

Organic farming is a holistic approach that integrates the well-being of the environment, crops, and farmers. It’s about more than just avoiding chemicals; it’s about creating a sustainable and thriving agricultural system. By adopting these practices, farmers are not only able to maximize their yields and boost soil health but also contribute to a healthier planet. Through this commitment to sustainability, organic farming stands as a beacon of hope for the future of agriculture, demonstrating that it is possible to feed the world while caring for the Earth.

Crop Rotation

Overview:

Crop rotation involves growing different types of crops in the same area across a sequence of seasons. This technique helps prevent soil depletion and reduces the build-up of pathogens and pests that occur when one species is continuously cropped.

Benefits:

Crop rotation enhances soil fertility by alternating deep-rooted and shallow-rooted plants, allowing different nutrients to be utilized and replenished. This method also breaks pest and disease cycles, reducing the need for chemical pesticides. Additionally, it helps manage weed pressure by disrupting their growth patterns.

Green Manuring

Overview:

Green manuring is the practice of growing certain crops specifically to be plowed under and incorporated into the soil while they are still green. These crops, often legumes, enrich the soil with organic matter and nutrients.

Benefits:

Green manuring improves soil structure, increases nutrient availability, and promotes beneficial microbial activity. It is particularly effective in adding nitrogen to the soil, thanks to the nitrogen-fixing capabilities of leguminous plants. This practice also helps suppress weeds and reduce soil erosion.

Composting

Overview:

Composting is the process of decomposing organic matter, such as crop residues and animal manure, into nutrient-rich humus. This humus can be added to the soil to enhance its fertility and structure.

Benefits:

The benefits of composting are numerous. It recycles nutrients back into the soil, improves soil structure, enhances water retention, and fosters beneficial microbial activity. Composting also reduces the need for chemical fertilizers and helps in waste management by recycling farm and kitchen waste.

Biological Pest Control

Overview:

Biological pest control involves using natural predators, parasites, or pathogens to manage pest populations. This method is a cornerstone of organic farming, as it minimizes the need for synthetic pesticides.

Benefits:

Biological pest control maintains ecological balance by encouraging biodiversity. It reduces the reliance on chemical interventions, which can harm non-target species and the environment. Additionally, it often leads to more sustainable and long-term pest management solutions.

Integrated Weed Management

Overview:

Integrated weed management (IWM) combines various agronomic practices to control weed populations. These practices include crop rotation, mulching, mechanical weeding, and the use of cover crops.

Benefits:

IWM reduces the reliance on chemical herbicides, promoting a healthier farm ecosystem. By combining multiple strategies, it provides more effective and sustainable weed control. This approach also helps maintain soil health and fertility, as it avoids the detrimental effects of continuous herbicide use.

Polyculture and Intercropping

Overview:

Polyculture involves growing multiple crop species in the same space, while intercropping is the practice of growing two or more crops in proximity. Both techniques mimic natural ecosystems and can lead to increased biodiversity and productivity.

Benefits:

Polyculture and intercropping can improve soil health by promoting a diversity of root structures and nutrient usage. They can also enhance pest and disease resistance, as a variety of plants can create less favorable conditions for pests. Moreover, these practices often lead to higher overall yields and reduced risk of total crop failure.

Organic Mulching

Overview:

Organic mulching involves covering the soil with organic materials such as straw, leaves, or grass clippings. This layer helps protect the soil and support plant growth.

Benefits:

Organic mulching conserves soil moisture, regulates soil temperature, and reduces weed growth. It also adds organic matter to the soil as the mulch decomposes, enhancing soil fertility and structure. Additionally, mulching can protect plant roots from extreme temperatures and help prevent soil erosion.

Agroforestry

Overview:

Agroforestry integrates trees and shrubs into agricultural landscapes. This practice can include alley cropping, silvopasture, and riparian buffer strips, combining the benefits of forestry and agriculture.

Benefits:

Agroforestry improves biodiversity, enhances soil health, and provides additional income sources through timber, fruit, or nut production. It can also improve water management by reducing runoff and erosion. Trees in agroforestry systems can act as windbreaks, protect crops, and provide habitats for beneficial wildlife.

Water Conservation Techniques

Overview:

Water conservation techniques in organic farming include methods such as drip irrigation, rainwater harvesting, and the use of drought-resistant crop varieties. These practices aim to maximize water efficiency and reduce wastage.

Benefits:

Efficient water use is crucial for sustainable agriculture, especially in regions facing water scarcity. Techniques like drip irrigation deliver water directly to the plant roots, minimizing evaporation and runoff. Rainwater harvesting captures and stores rainwater for future use, reducing dependence on groundwater and surface water sources. These practices ensure that crops receive adequate water while conserving this vital resource.

Soil Testing and Amendments

Overview:

Regular soil testing helps farmers understand the nutrient status and pH level of their soil. Based on these tests, organic amendments such as compost, manure, and lime can be added to correct deficiencies and improve soil health.

Benefits:

Soil testing allows for precise nutrient management, ensuring that plants receive the necessary nutrients without over-application. This precision reduces the risk of nutrient runoff, which can harm the environment. Organic amendments improve soil structure, increase microbial activity, and enhance the soil's ability to retain water and nutrients.

Conclusion

Embracing organic farming techniques not only enhances crop yield but also promotes sustainable agriculture, ensuring long-term soil health and ecosystem balance. Practices like crop rotation, green manuring, composting, and biological pest control create a resilient farming system that reduces reliance on synthetic inputs and fosters biodiversity.

Integrated weed management, polyculture, and agroforestry contribute to a robust agricultural landscape that can withstand environmental challenges. Water conservation techniques and regular soil testing ensure that resources are used efficiently and sustainably.

By implementing these top 10 organic farming techniques, farmers can achieve high yields while protecting the environment, thus paving the way for a sustainable and productive future in agriculture.

[agreads]

DENSO and Certhon Introduce Artemy, A Fully Automated Cherry Truss Tomato Harvesting Robot

DENSO CORPORATION and its group company, Certhon Build B.V., has begun accepting commercial orders for the fully automated cherry truss tomato harvesting robot, “Artemy,” in Europe starting May 14th. Artemy is an innovative robot that can perform a series of cherry truss tomato harvesting tasks in a fully automatic manner. The basic functions are as follows. Automatic Harvesting Function: It…

[mattbrittonnyc]

Revolutionizing Agriculture: AI's Impact on Consumer Perception

As the global population continues to grow, the agricultural sector is under increasing pressure to innovate, ensuring food security and sustainability for future generations. One of the most transformative forces in this sector today is artificial intelligence (AI), which is reshaping everything from crop management to consumer perceptions about food. Enter Matt Britton, a renowned AI expert, keynote speaker, and the mind behind the innovative consumer research platform Suzy. Matt has the unique ability to demystify complex technologies and trends, making them accessible and actionable for his audience. His anticipated keynote speech on "AI in Agriculture: Changing the Way Consumers Think About Food" promises to be a groundbreaking exploration of this vital topic.

The Expertise of Matt Britton

Matt Britton is not only the Founder and CEO of Suzy, a real-time market research platform, but also a seasoned consultant who has worked with over half of the Fortune 500 companies, helping them to navigate and lead in their respective markets. His best-selling book, YouthNation, has positioned him as a leading voice on new consumer trends, particularly among Millennials and Generation Z. This background makes him an ideal candidate to discuss the implications of AI in agriculture, especially from a consumer trend perspective.

AI in Agriculture: A Paradigm Shift

The integration of AI into agriculture is creating a paradigm shift in how food is grown, processed, and perceived by consumers. AI technologies such as machine learning, robotics, and predictive analytics are not only increasing efficiency and yields but are also enhancing the sustainability of farming practices. These innovations allow for precise agriculture, where resources like water and fertilizers are used optimally, reducing waste and environmental impact.

Consumer Perception and AI

One of the key aspects that Matt Britton is expected to address in his keynote is the change in consumer perceptions driven by AI advancements in agriculture. Today's consumers are increasingly concerned with how their food is produced, demanding transparency and sustainability. AI-enabled solutions offer a way to meet these expectations, providing consumers with detailed insights into the food production process. This shift is significant, as it aligns with broader consumer trends towards health and sustainability that Matt has extensively analyzed in his work.

The Impact on Consumer Trends

Matt Britton’s expertise as a consumer trend expert will be invaluable in dissecting how AI-induced changes in agriculture are influencing consumer behaviors. For instance, AI’s role in creating more resilient food systems can lead to greater consumer trust and loyalty. Moreover, as a generation Z expert, Matt’s insights into how young consumers, who are particularly tech-savvy and sustainability-conscious, interact with these new technologies will be crucial.

Why Matt Britton?

Choosing Matt Britton as a keynote speaker for a conference on AI in agriculture is a strategic decision. His ability to connect technological innovations with consumer behavior makes him one of the top keynote speakers in the field. His presentations are not only informative but also engaging, filled with actionable insights that businesses can use to better align with their target demographics. Additionally, his experience with Fortune 500 companies gives him a practical understanding of how large-scale operations can implement AI technologies effectively.

Engaging and Authoritative Content

Attendees of Matt’s sessions can expect a blend of engaging stories, robust data, case studies, and perhaps even live demonstrations of AI tools. His approach usually involves a deep dive into current trends, backed by the latest research and his own extensive consulting experience. This not only captivates the audience but also builds a strong case for the transformative power of AI in agriculture.

Conclusion

As industries continue to evolve under the influence of AI, understanding these changes is crucial for professionals involved in agriculture and food production. Matt Britton stands out as an AI expert speaker who bridges the gap between complex AI technologies and everyday consumer impacts. His upcoming keynote on "AI in Agriculture: Changing the Way Consumers Think About Food" is poised to offer profound insights into the future of farming and food consumption, making it a must-attend for anyone interested in the intersection of technology, agriculture, and consumer trends. With his guidance, industry leaders can foresee and harness the shifts that AI is bound to bring.

[anandinternational]

Discover how AI-powered automation is revolutionizing agriculture in our latest blog post! Explore innovative solutions and their impact on farming practices.

[airises]

"Revolutionizing Biotech: How AI is Transforming the Industry"

The biotech industry is on the cusp of a revolution, and Artificial Intelligence (AI) is leading the charge. AI is transforming the way biotech researchers and developers work, enabling them to make groundbreaking discoveries and develop innovative solutions at an unprecedented pace. “Accelerating Scientific Discovery with AI” AI is augmenting human capabilities in biotech research, enabling…