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Spectral imaging for the agriculture industry

Spectral imaging as a general concept combines characteristics of imaging and spectroscopy technologies. Optical spectral imaging particularly makes use of visible, near infrared and short-wave infrared spectral range, has been demonstrated to be a very powerful tool in identifying, classifying, and mapping specific targets across whole scenery image in various application scenarios.

Spectral Imaging is especially useful in the agricultural domain, where crop/vegetation in different conditions has unique spectral characteristics. With more robust and rugged imaging product integrated with various platforms, agri-tech has been undertaking revolutionary improvements for remote sensed inspection. Multispectral imaging, hyperspectral imaging, and SIF (solar-induced fluorescence) imaging can be broadly derived depending on spectral bands and resolution needed.

Eliot Dixon, Head of Engineering at Agri-EPI Centre said:
“We have established a strong sensing team within the company, able to deploy a range of spectral imagers into agriculture including some exciting unique capabilities. With our contextual farm data, storage facilities and analysis tools this is a key data service for developers which is available to all.”

Multispectral Imaging
The advantage of multi-spectral imaging is that it extends human sight sensitivity beyond visible spectrum. Some wavelengths that are widely recognized for particular applications, such as normalized difference vegetative index (NDVI), can be deployed into multi-spectral imaging. Nonetheless, it has been proven to be very useful in many other fields, greatly empowering advancement of agriculture. And the adoption of UAV has made it possible to make large-scale mapping and thus better agricultural management.

Agri-EPI Centre has invested MicaSense Altum sensor covering RGB, NIR, Red Edge and LWIR, which can be operated easily on VTOL UAV platform.

With this multi-spectral imaging system, several important vegetation indexes such as red edge, NDVI, can be quickly collected and mapped across survey fields.

Hyperspectral Imaging
Hyperspectral imaging captures images at hundreds of wavelengths, creating a detailed spectral signature of objects and materials. Compared to multispectral imagery, hyperspectral imagery measures energy in narrower and more numerous bands, thus giving much more information on target. Hyperspectral image data is a datacube, where each pixel holds full spectrum across the range. Since spectra are as unique as ‘fingerprint’ to target, hyperspectral imagery can unveil features that multispectral may miss out.

Agri-EPI Centre has invested in a range of hyperspectral imaging systems. Read below for more:

Spectral imaging brochure

Automation and robotics for agriculture at Agri-EPI Centre

Agri-EPI, the centre for precision innovation in farming, is a first choice for agri-tech developers, from start-ups right through to established companies, to help with creating robust and commercially viable agricultural solutions.

Our team believes that it is vital that new agricultural technologies are both relevant and robust, build on well described initial design goals created from a strong understanding of the needs of farmers and their operations. If that is not done, then there will be delays in the development of the product and eventually quality, which will have ongoing negative effects on the trust of farmers in the product. Short testing cycles compound that problem, so the data used to design and build the systems needs to be of very high quality.

Our offer
Agri-EPI offers a wide-ranging set of facilities, equipment, and services. Our farm network is a key part of this, enabling the testing spaces and long-term interaction with farmers which we rely upon. Within the engineering team, we support the farm network and projects through our data engineering, data analysis and robotics specialisms.

Key resources include:

  • Multi-modal agricultural data
  • Spectral imaging and sensing
  • Agricultural data analysis
  • System simulation
  • Development / Robotic platforms
  • Data and robotics in agriculture consulting

Find out more here:

Engineering R&D brochure

Live grain robot demo success on farm in the South West

On Tuesday 14th March Agri-EPI hosted a live demonstration of the Crover grain monitoring robotic solution at Manor Farms, Stratton-on-the-Fosse, kindly hosted by Jeremy Padfield and Rob Addicott who farm in partnership together.

They are both tenants of the Duchy of Cornwall and have been a LEAF Demonstration Farm since 2006 and members of the Agri-EPI Innovation Farm network since 2017. Working together as neighbouring farmers has brought many benefits to Rob and Jeremy such as shared machinery and investment costs. It has also allowed them to take up a number of precision farming techniques to help their businesses become more sustainable, such as engaging in the Crover project.

Crover’s first-of-its-kind grain monitoring robotic solution allows for a greater understanding of the real situation of grains stored in bulk, thanks to its patented method for locomotion through bulk solids, enabling grain storage operators to implement accurate Integrated Pest Management (IPM) practices to maintain the quality of their stock. The CROVER robot is the world’s first ‘underground drone’ in the sense of the first device able to propel itself below the surface of dense granular media such as sand, grains and powders.

It was a very successful event with great feedback and engagement from the guests and the demonstration in the grain shed went smoothly.

International Day of Mathematics

Happy International Day of Mathematics! Mathematics plays a significant role in agricultural technology in several ways:

  1. Modeling crop growth: Mathematical models are used to simulate the growth of crops. These models use mathematical equations to represent the different factors that affect crop growth, such as temperature, rainfall, soil nutrients, and pests. By using these models, farmers can predict how their crops will grow under different conditions and make informed decisions about when to plant, irrigate, fertilise, and harvest.
  2. Precision agriculture: In precision agriculture, farmers use technology to apply inputs (such as water, fertiliser, and pesticides) precisely where they are needed. This technique relies heavily on mathematical models, data analytics, and sensors to measure and monitor different parameters, such as soil moisture, nutrient levels, and pest populations.
  3. Farm management: Farmers need to keep track of a lot of data, such as crop yields, soil characteristics, weather patterns, and market prices. Mathematical tools help them organise and analyse this data, make predictions, and optimise their operations.
  4. Genetics and breeding: Mathematics is also used in genetics and breeding to study the inheritance of traits and develop new varieties of crops that are more productive, disease-resistant, and climate-tolerant. Mathematical models can help researchers identify the genes that control these traits, predict the outcomes of different breeding strategies, and optimise the selection of new varieties.

Overall, mathematics is an essential tool in agricultural technology, helping farmers and researchers make informed decisions and optimise their operations to meet the growing demand for food in a sustainable way.

Over the last months Agri-EPI has invested in the expansion of its team focused on data, engineering, and math, bringing on several new members and enabling them to offer a set of services to assist in the creation of agri-tech products.

Eliot Dixon, Head of Engineering, said:

“The team of platform and spectral imaging experts uses our fleet of sensors and specialist software to deliver a range of sensing products such as ground truthing for AI model generation, or the creation of digital twins. We are also now able to offer UAV and UGV platforms as a means to test novel sensors and end-effectors without the need for a bespoke vehicle. And through working closely with our innovation farm network, we are creating a heavily layered source of evidence for developers using our farm network to design and test their innovations.”

Agri-EPI’s GIS Data Analyst, Yingwang Gao, majored in Agricultural Engineering, and has a PhD degree specialising in Hyperspectral Imaging Applications, as well as postdoc experience working as Research Associate. In addition to a strong academic background, he has accumulated several years of industrial work experience, mainly on spectral imaging systems, R&D, and spectral imaging data analysis in various application domains. He has a strong passion for remote sensing and photogrammetry. At Agri-EPI, he takes care of data acquisition and data processing from different types of sensors, including RGB, multispectral, hyperspectral, LiDAR, and GPR, to identify and map out features of interest in the agricultural sector, to help farmers with better decision-making in agricultural management.

Agri-EPI’s new R&D Equipment Technician, Aditya Jadhav, pursued his bachelors in aeronautical engineering, where he learned various aspects of flying machines. He set up an aeromodelling club with a few of his classmates where they designed, built and tested various configurations of small UAVs. The MSc program for Autonomous vehicle dynamics and control was structured for students to gain a deeper understanding of unmanned systems. Aditya was part of a group project that built a surveillance system with a swarm of autonomous drones, and an individual project sponsored by the Railway Safety and Standards Board which aimed to design and develop an autonomous vehicle which can operate in a station environment. The advancements in robotics and the urgent need of integrating robotics with sustainable agriculture were the driving forces for him deciding to work in the agri-tech sector. As the R&D Equipment Technician, Aditya looks after all the deployable assets that are in service to the company, which includes maintenance, asset tracking and deployment, and organising the logistics.

Panagis Tzivras, Agri-EPI’S GIS Software Engineer, is a GIS expert with strong technical skills who is highly invested in programming. In his previous roles working with startups and the commercial sector, he was involved in data collection and extraction, maintaining data pipelines and building geospatial processes and automation updates. At Agri-EPI Centre he is helping to leverage the measurement resources of the centre to create high quality dataset and support systems. He is working on creating tools and code to enable the automation of data collection from a wide variety of sources available to Agri-EPI Centre.

Lastly, Aidan Robertson has joined the Agri-EPI Engineering team as their new Graduate Data Analyst. Aidan’s background is in mathematics, which he studied at University of Warwick for four years before looking for jobs related to data science. He has been working on projects related to the health and wellbeing of cows, specifically by reformatting farm datasets to be sent out for analysis. Soon, there are plans for him to begin a more ambitious project to develop a costings estimator for RAS in agriculture. This is a long-term task, but the ultimate goal would be to offer it as a service for farmers looking to introduce robotic systems into their farms. The most interesting part of agri-tech for Aidan is the data, and what it actually says about the performance of a system, as well as what can be done to help the problems being faced by the agri-tech sector at present.

 

 

Presenting your agri-tech product

By: Amber Barton, Market Insight & Proposals Lead

Agri-EPI Centre helps develop precision tech solutions to empower more sustainable farms. But once the solution has been trialled and tested, how do we communicate the benefits and enable uptake of the tech? Amber Barton provides tips on what’s important when presenting about your agri-tech product.

Tip number 1. Too much background, waffle, and unnecessary information is not required, nor desired. Focus on you and your product

Keep your presentation direct and to the point.

Use real life examples from trialling your tech on-farm – admit what worked well and what didn’t and how this has been addressed.

Provide video footage to demonstrate your technology in action. Video phone footage would be fine.

Use photos and importantly, remember to introduce yourself, your team, and your backgrounds.

Tip 2: Presentation structure should centre around the product, cost, and application

What is your product/ service?

This should be one slide. It should be direct and easy to understand for someone unfamiliar with the subject matter.

What does your product/ service do?

This is your use case and should be a call to action. It should still be explained simply and directly but it’s your chance to appeal to them in a more emotive way. Use facts and figures, but only if they are strong enough to make someone think “WOW”.  Do you know your facts and figures if questioned?

How much does it cost?

You have told the farmers what your product/ service is and now they want to know if it is worth investing any more time listening to you. They will do this by assessing what the cost is to them. You could present something to them that is pure magic, but if it’s not financially viable then you are wasting their time (something they do not have a lot of). Make use of this valuable opportunity. If you are at this stage, then you should already be confident that your product is being produced at a cost that is agreeable to them so it shouldn’t need to be hidden. More on presenting costs can be found further down the page.

How is it practically applied?

You have told them you have something that will make their life easier/ save them money etc. Now decision makers  need to know how this will practically fit into their system. You may not know what kit they use or how they farm, but they do, and if they want to use what you’re selling then they will be open to making it fit or speaking about the possibilities. You just need to tell them the requirements. Is it sprayed? If so, how? Is it pulled behind something? If so, what are its power requirements? Is it robotic? What are the power/ connectivity requirements? Does it require mapping in advance? What is the timeframe needed for this to take place? Give them the facts and figures to help them see how this could fit into their own set up.

Is there training need?

Who is going to be using this? Is it them? Their agronomist? Is it simple enough for anyone on the farm to operate? Have these details to hand and any cost associated with them, including training time. Is it a 1-hour module or a two-day course with top up sessions etc.

How will your solution benefit them?

Round things off by highlighting any direct or indirect benefits your product will have. Think outside the box. Benefits to the bottom line are often at the top of this list but is there anything else that might not be so obvious?  Environmental benefits? Farmers are stewards of the land after all. Work life balance benefits? Will time saving help them get home to their families any quicker? Really put yourself into their shoes and consider the wider picture.

Value of your product

If you can show them this, in real terms, then they are far more likely to get on board and work positively with you.

So how can you help to “Onboard” farmers through considered costings?

First you need to understand their operating environment and their cost of production (COP). Most farm enterprises don’t have huge profit margins. As such, your product needs to either save them money in an existing area (e.g., labour saving) or enable them to increase the value of their product in a significant way. That is tricky in most farming sectors.

If you have a product that saves labour, then you need to know what the labour cost element of the total COP is and ideally you need to show that your product fits within that, or even reduces it. I will use labour costs in tabletop strawberry growing as an example:

Redman, G., 2022. The John Nix Pocketbook for Farm Management 2023. 53rd ed. Published: Melton Mowbray: Agro Business Consultants

Using this example from John Nix we can see that the costs for labour are mostly in the fieldwork, harvesting and grading/ packing areas which comes to between £31,676/ ha for low output and £54,129/ ha for high output production.

If you can show how your product offsets cost in actual figures, then there is a tangible benefit.

If your product costs £50,000 but provides a labour saving of 25%/ ha then you can show the benefit to the bottom line, the payback period etc. In this example a high performing farm would see the payback within one year across less than 4 hectares. You can then discuss the other benefits, such as not having to manage as many people (something that often causes the farm manager the most headaches) or helping to overcome the struggle to secure the labour in the first place.

There are a few places to find COP information – John Nix Pocketbook and ABC’s “The agricultural Budgeting and costing book” are a good place to start for a comprehensive guide. The AHDB also does a lot or work on farm economics and their Farmbench programme has a lot of good data.

Showing farmers you have a good understanding of what you are trying to help them achieve will go a long way to helping you achieve success in this sector.

Agri-EPI expands robotics and data offering

Agri-EPI has developed its robotics and data offering, including the addition of 4 new members to their engineering team over the last couple of months.

Eliot Dixon, Head of Agri-Tech (Engineering) explains:

“Over the last few months Agri-EPI has been investing heavily in its engineering team, bringing on several new members, enabling us to offer a set of services to assist in the creation of agri-tech products. The team of platform and spectral imaging experts uses our fleet of sensors and specialist software to deliver a range of sensing products such as ground truthing for AI model generation, or the creation of digital twins. We are also now able to offer UAV and UGV platforms as a means to test novel sensors and end-effectors without the need for a bespoke vehicle. And through working closely with our innovation farm network, we are creating a heavily layered source of evidence for developers using our farm network to design and test their innovations.”

Agri-EPI’s new GIS Data Analyst, Yingwang Gao, majored in Agricultural Engineering, and has a PhD degree specialising in Hyperspectral Imaging Applications, as well as postdoc experience working as Research Associate. In addition to a strong academic background, he has accumulated several years of industrial work experience, mainly on spectral imaging systems, R&D, and spectral imaging data analysis in various application domains. He has a strong passion for remote sensing and photogrammetry. At Agri-EPI, he takes care of data acquisition and data processing from different types of sensors, including RGB, multispectral, hyperspectral, LiDAR, and GPR, to identify and map out features of interest in the agricultural sector, to help farmers with better decision-making in agricultural management.

Agri-EPI’s new R&D Equipment Technician, Aditya Jadhav, pursued his bachelors in aeronautical engineering, where he learned various aspects of flying machines. He set up an aeromodelling club with a few of his classmates where they designed, built and tested various configurations of small UAVs. The MSc program for Autonomous vehicle dynamics and control was structured for students to gain a deeper understanding of unmanned systems. Aditya was part of a group project that built a surveillance system with a swarm of autonomous drones, and an individual project sponsored by the Railway Safety and Standards Board which aimed to design and develop an autonomous vehicle which can operate in a station environment. The advancements in robotics and the urgent need of integrating robotics with sustainable agriculture were the driving forces for him deciding to work in the agri-tech sector. As the R&D Equipment Technician, Aditya looks after all the deployable assets that are in service to the company, which includes maintenance, asset tracking and deployment, and organising the logistics.

Panagis Tzivras, Agri-EPI’S new GIS Software Engineer, is a GIS expert with strong technical skills who is highly invested in programming. In his previous roles working with startups and the commercial sector, he was involved in data collection and extraction, maintaining data pipelines and building geospatial processes and automation updates. At Agri-EPI Centre he is helping to leverage the measurement resources of the centre to create high quality dataset and support systems. He is working on creating tools and code to enable the automation of data collection from a wide variety of sources available to Agri-EPI Centre.

Lastly, Aidan Robertson has joined the Agri-EPI Engineering team as their new Graduate Data Analyst. Aidan’s background is in mathematics, which he studied at University of Warwick for four years before looking for jobs related to data science. He is very pleased to be part of the Agri-EPI team in quite a varied role; so far, he has been working on projects related to the health and wellbeing of cows, specifically by reformatting farm datasets to be sent out for analysis. Soon, there are plans for him to begin a more ambitious project to develop a costings estimator for RAS in agriculture. This is a long-term task, but the ultimate goal would be to offer it as a service for farmers looking to introduce robotic systems into their farms. The most interesting part of agri-tech for Aidan is the data, and what it actually says about the performance of a system, as well as what can be done to help the problems being faced by the agri-tech sector at present.

Tag Archive for: Data

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