Over the last month or two the Agricompas science team have been making visits to rice fields in the Tolima region in Colombia. Travelling the five hours from Bogotá, the journey is a reminder of just how big this beautiful country is.
The two scientists are using these trips to better monitor, understand, and support the collection of accurate crop data. Inspections of soil and water took place, as well as looking at our cutting edge technology that collects weather data as well as greenhouse gas emissions.
These trips are in close collaboration with another member of the project consortium, Fedearroz. Their technicians were on hand to demonstrate data collection techniques and to reflect on best practices and quality control measures.
Dr Gil and Dr Bojacá inspected the rice crop, which is just starting to germinate. This is the fifth cycle of rice crop data that the EcoProMIS project is collecting from both the Tolima and Casanare districts.
The rice seed in Tolima is just starting to germinate
In addition to these five cycles of data, we have access to a much larger historical database of rice farming, and our team is combining this information in order to create and strengthen our crop model. This model is thus becoming more reliable (‘robust’) as we add more data, including phenological, weather, and satellite imagery.
As we prepare to enter the fifth year of the project, it is exciting to see how a huge amount of collected data has now been processed through our science and IT work into useful practical outputs that will directly benefit farmers.
Via mobile apps, these growers are able to access yield calculators and other tools to help them maximise their farm output and move towards our shared goal of sustainable optimisation.
Our science team will continue to make these regular visits as the project grows from strength to strength and we look towards rolling out this unique service to rice growers in Colombia and beyond.
In early December 2020, the EcoProMIS project partners presented workshops to update the status of the project with rice growers across two major regions in Colombia. These workshops were an opportunity to share about EcoProMIS news and technical developments and to get critical feedback from growers about their perceptions.
There were around 16 growers present across the two regions for these events. Our workshops were presented by Gabriel Garces of Fedearroz, although this was a team effort together Agricompas, CIAT, and Solidaridad.
Update of the project and timeline
During the workshops, Gabriel explained the progress of the project from December 2017 until present day. The growers were informed that current tasks include calibrating the advanced knowledge services, testing the technical systems, and getting everything ready so that the platform can be successfully delivery to growers and to the insurance market.
Growers were shown how the EcoProMIS app will give them advanced knowledge about their farms
Four app features
Gabriel went on to describe the four major services on the EcoProMIS platform. The first of these is the visualisation and management of information, where farmers will have a user-friendly interface to assess their best strategies for sustainable optimisation.
Secondly, the platform will provide output predictions based on climate, farm management practices, and data collected on crops. This has been designed with growers and their rice federation, as explained in this blog here.
Thirdly, the EcoProMIS app provides comparative charts to assess a grower’s land in contrast with other land in their area as well as providing a historical comparison. This feature allows growers to benchmark their productivity and will lead to exploring better management practices.
Finally, the workshop showcased crop diagnostics, based on geo-referenced data. With funding from the UK Space Agency, one of our project priorities is to commercialise applicable services from satellite data. Gabriel explained that each field is regularly photographed by satellites and that our platform can take those images to help improve farm productivity.
The workshops also took the opportunity to explain that at a later date the project will also be contributing information and discussing insurance schemes with farmers, using anonymous (GDPR-compliant) data to lower premiums and close the ‘insurance gap‘.
Gabriel went on to explain more about how scientists collect geospatial data, and how those data points are turned into tangible information about the health of crops, making estimations about the phenotyping stage of the crops, and more!
Gabriel emphasised that the platform will be totally free for growers. He showed helpful visualisations of what the platform will look like for growers. A couple of screenshots are attached, in Spanish, to this blog.
The EcoProMIS app gives growers yield estimates based on their management choices
Initial impressions and next steps
The growers present at the workshop were enthusiastic about the power of the app’s knowledge services. In particular, growers expressed interest in the ability to estimate growth and output and the ability to plan for different scenarios, for example, based on the use of different seeds, fertilisers etc.
Growers were also curious to learn more about how the science works. For example, they wondered how does the app calculate output when we consider how variable the weather is with global climate change and phenomena like the recent La Niña? We spoke more about how the app handles this type of data variability, how we develop metrics, measurements and more.
The next steps are to upscale these workshops and deliver more in January and February of 2021. These new workshops will be based off of the workshops we gave in December 2020, incorporating the initial attendee feedback so that the workshops are even more accessible and informative to growers.
The world is changing. Every day we see how new technologies are being developed and many of us may have come to dread the idea of being displaced by a machine. But that is not the way of things. Technology is meant to make our lives easier, and we believe that the coexistence between traditional methods and newly developed ones is possible, if not meant to be.
In recent years, agricultural data analytics has become one of the top edge tendencies in terms of sustainable development globally. This means that there is a lot of research and a lot of projects currently trying to understand agricultural dynamics and how to use information in order to optimise processes and achieve sustainable objectives.
Although this is a very beautiful statement, the reality growers are facing on a daily basis, and how this information is to be gathered, processed and used, represents a huge challenge not only for farmers but for the whole agricultural value-chain.
Agriculture in LMIC countries still relies on manual labor. The culture of innovation, technology, insurance, good financial practices and data analytics is still in a juvenile stage.
Nevertheless, governments and private capital are incentivising fast growth through technology and new services are becoming more common every day.
Innovation and Market Growth
For Agricompas, a data analytics company, innovation is the only way to break through such barriers and use knowledge to evolve the growing market. This is our main drive, our oxygen and our compass. As Harvard Business Review’s article: Breaking down the barriers to innovation states:
“To us, innovation doesn’t mean mere inventiveness. In our work we define it as: something different that creates value.”
As we work with our Colombian partners on agricultural big-data, we face the challenge of gathering, processing and delivering useful information in the context of market needs and opportunities. By doing this, we look to make our EcoProMIS platform a value generator for growers, governments, and financial and insurance institutions.
Analytics for Decision Support
In order to capture what really drives the agricultural market in terms of financial services, risk management and productivity optimisation, our innovation process aims to understand the market and develop tailored solutions that make the decision-making process more efficient, thus giving business intelligence the recognition and merit it deserves for the immense toolkit it provides us with.
We believe that by bringing sustainable agriculture into the digital era, better conditions for growers may be achieved. We believe that when real value is generated it can also be garnered.
We believe that corporate institutions can see a benefit as well, using high quality information and business intelligence, improving their margins, creating new delivery methods, enhancing R&D and, finally, increasing sales.
With the richness of precise, accurate and relevant information, we enable an increase to the market size of agro insurance and provide the much-needed agronomic crop management data that is necessary for a new and creative product development ecosystem.
The world is changing. And so are we. Breaking through the barriers of convention, we have come to innovate and leave the world in better shape than how we found it. We believe that a new era for sustainable agriculture and analytics has come at last.
By Jorge Torres-León, José Monsalve, Cristian Angarita from Cenipalma
Over the past few decades, huge growth has been shown in geospatial technology applications in different fields worldwide. As for projects in agriculture, there has been a considerable increase in the use of images provided to us by earth observation satellites. These images allow us to obtain a top-down view of very large areas, to analyse the terrain, and to have better data for decision making.
Like all technology, the use of satellite images has both advantages and disadvantages. Although it is possible to have good quality images of almost any location on the planet, its most noticeable disadvantage is that since the sensor is inside a satellite orbiting at very high altitudes, it captures the clouds, thus creating a ‘mask’ above the objects requiring observation. Colombia, being in a tropical area, has a very high density of clouds most of the time, making this a frequent difficulty.
This is where we find the importance and efficiency of using other technology, namely unmanned aerial vehicles (UAVs or drones), since they operate at lower altitudes. As regulated by the Colombian Aeronautics Authority, all UAV flights that we conduct are below 150m and thus drones flying over oil palm crops are able to capture very high resolution images free of clouds.
Drone flights support farmers with decision making
Equipped with multispectral and thermal sensors, our UAVs have collected images in oil palm plantations in different areas of Colombia. Regular flights means that the EcoProMIS project is able to achieve continuous monitoring and comparison of the development of the plants. Different phenological (growth) stages of the crop are observed, including the unproductive, stabilisation, and productive phases.
Through multispectral images, such as those seen below, it is possible to perform calculations using the spectral bands being captured by the sensors. One approach we use is the vegetation index, in which it is possible to remotely detect the status of individual plants in terms of growth, pest infestation, water stress, flooded areas, nutritional deficiencies, systemic diseases, etc.
For the agricultural sector, this type of information is extremely important. The EcoProMIS platform sends such information directly to the grower’s mobile phone, and this near real time data allows farmers to take preventive measures to support crop performance.
Example of data types from our drone flights.
Another technique we use is with images acquired by the thermal sensor on the drones, which provide information on the temperature of each of the surfaces within the study area. Using this technology, a farmer can pinpoint problems associated with disease and water stress. The acquisition of spectral images can be scheduled on a daily basis to quickly identify and quantify unhealthy plants, such as those suffering from chlorosis. Early identification allows farmers to make decisions in a timely manner so as to protect their crops and yields.
Connected weather stations
Digitally-connected weather stations are another form of high-tech equipment being used by the EcoProMIS project to support farmers. These have been installed in experimental plots and offer the advantage of knowing in real time the climatic conditions such as rain, temperature, humidity, etc.
It is essential to combine data collected by the weather stations with the data from drone images and oil palm models, as almost 70% of the crop performance can be explained by the surrounding climatic conditions.
Greenhouse gas data
Currently, our project collects GHG data through eddy covariance towers in two different palm regions in the country. This system allows us to quantify the CO2 (carbon dioxide) that is absorbed by the oil palm during its photosynthetic process as well as the emissions of greenhouse gases such as CO2, methane and even water vapor. Through these measurements it is also possible to calculate in detail the evaporation of the ecosystem.
Eddy covariance tower in one of our oil plam fields
These high-tech systems allow more precise readings of environmental variables, such as relative humidity, atmospheric temperature, direction and wind speed, precipitation, etc. All these variables are of critical importance in establishing the influence of weather conditions on the development of oil palm cultivation as well as the effect the crop itself has on the environment.
By combining the data from satellites, drones, weather stations, and GHG towers we have a rich and detailed understanding of each farm. When this data is turned into knowledge services (such as yield-prediction) and delivered through a mobile dashboard, growers are supported so that they can make rapid and intelligent decisions in their farm management.
By Richard Strange, Head of Engineering at Agricompas
As individuals we all grow in wisdom and capability when we take time to reflect on our actions and find lessons to apply to tomorrow’s challenges. We look at our achievements and the memories that are anchored around them. We use them to guide us in becoming better in both our professional and personal lives. Modern business is very much the same. In the modern world, when a business moves, the byproduct of their actions is data.
Agricultural Data Gap
Whether it is a financial officer’s log of transactions, the record of work hours from an employee’s timesheet, or the number of clicks a website receives each day. It is rare to find a part of a business that isn’t measured or collected, either directly or by proxy through other measures. Yet in agriculture, little information is available around many crucial farming practices that often mean the difference between a bumper crop or financial devastation for families and communities.
It is not enough to say that you have an employee, or a website, or an invoice. The crucial questions are if the employee is doing their work, if the website is drawing attention, if the invoice is correct. Yet farmers are not able to answer critical questions about their own farms. They have sown their seeds, yet cannot say how many are germinating. They apply fertiliser, yet cannot tell if it is cost-effective. By leaving agriculture behind in this wave of data-driven business, the world is abandoning millions of farmers in data poverty, and powerless to compete against their wealthier first-world counterparts.
EcoProMIS Collects Quality Data
In leading the EcoProMIS project, the aim of Agricompas is to make a difference by empowering farmers with the knowledge they need, from sensor to survey to satellite to weather to drone data. But with each additional source of data, the difficulty of pulling them together increases exponentially. I’m the Head of Engineering at Agricompas, and I’m responsible for all the data EcoProMIS gathers. My job is to work out how we pull all this information together, understand it and then provide the information to those that need it.
There are two approaches to tackling a challenge like ours. Firstly, you can manually handle the data, with a team of analysts pushing round files via email, shared folders and collaborative spreadsheets. This does come with the advantage of immediate productivity and visibility. But there’s little certainty over the quality and completeness of data, and no way to be sure what information is where. The second option is to invest time and effort into a fully-fledged platform for data. It must allow the scientists we work with and the farmers that we support to put in and take out the information they need effortlessly.
Advanced Data Platform Prevents Errors
Only recently, the failure of the first, manual approach was highlighted by the loss of the records of 16,000 positive COVID-19 cases by the UK government. Was it a catastrophic server failure? the act of a malicious hacker? The truth was far more mundane. An analyst had opened the spreadsheet holding the list of COVID-19 cases in an old version of Excel, slicing 16,000 rows of data off without ever realising their mistake. Suppose this approach cannot work reliably in the hands of a team as well-staffed as the Public Health England team. How can we trust our own information in a similar system? We owe our growers and our own team better than that.
Over the last six months, the EcoProMIS team has been carefully creating a central platform that can look after farmer data responsibly and safely. A system of databases, redundant servers and security measures means that data doesn’t get forgotten, doesn’t get destroyed and doesn’t get leaked. Over the coming months, we are combining our suite of analytics, models and AI with new apps.
These apps will allow farmers to provide and see their data about their farms and help them make the right agricultural decisions. We already have the first app in early tests, with a knowledge presentation app in the works for release by the new year.
As we evolve our platform and grower apps through close feedback with early users, we will be able to put more power back into the hands of growers, irrespective of their literacy or agricultural experience.
Agricompas and the EcoProMIS project exist to level the playing field and make agriculture fairer for farmers in the most challenging economic, environmental and social settings. I am incredibly proud of what our technical team has achieved to make that happen.
With the advent of the big data era, the way we gather insights about processes affecting our everyday lives has changed dramatically, and the domain of agriculture and food production is no different.
As a result of the widespread availability of various sensors, from satellites and UAVs, to climate and soil measurement hardware on farms, we can now gather data at unparalleled rates and volumes. However, in its raw state, the data we collect often provides little, if any, insight. These raw measurements need to be processed and analysed through complex pipelines to be turned into a valuable product.
The engine responsible for driving the change of raw data into worthwhile insights is data analytics.
Data Analysis for EcoProMIS
Since joining Agricompas in July, I have been working on ensuring that the data which is stored and arrives on our cloud platform, is as high quality as possible. Analytics and predictions are only ever as good as the data from which they are sourced, hence rigorous checking of data quality is always a necessary layer in data intensive projects. To help with this, I wrote a number of programs generating data quality statistics, which will ensure that any analytics we produce will be reliable and trustworthy.
The statistics produced by these scripts are then visualised and fed into internal dashboards, which provide a quick and intuitive way of keeping an eye on our data and making sure that it looks the way we expect it to.
Data analysis is an essential part of our work on the EcoProMIS project.
Eddy Covariance Data
So far, one of my most enjoyable (but challenging) experiences was working with large eddy covariance tower datasets. Eddy covariance towers are brilliant at logging and producing rich atmospheric chemistry flux datasets allowing us to understand the minute gas exchange processes in agricultural fields. This data is important for our crop modellers, allowing them to produce various models capable of predicting crop phenology and yields.
However, due to the way that the hardware transmits the data, it is common for gaps in data to form (e.g. as a result of signal loss). Luckily, with the power of statistics, we can accurately discern the missing values and fill the gaps in the data. Working closely with the crop modelling team, after many discussions and much research, we have successfully automated this process, and allowed ourselves to further iterate and improve on it if need be in the future.
Integrating Diverse Data
As for the future, I also look to my past and hope to bring some of my previous experience in working with remote sensing and Earth observation data into our platform. Integrating and tying all the data types together will be a big challenge, however I am certain that it will bear fruit and truly create a platform which will make farming easier, more precise and more sustainable.
With advances in computational power and the high quality data available to us, I believe that data analytics and artificial intelligence will play a key role in revolutionising agriculture, and it is rewarding to be a part of a team making this happen. Combining multiple sources of data together into a single product will allow us to create a platform capable of supporting decisions via accurate insights and improving the ease with which farmers grow crops like never before.
A few years ago, a man became famous when someone shared a video of him dancing at a public concert. His spontaneous and unusual exhibition although original was not the only element to become popular on the web.
Analysis of this video provides some insights on how new technologies are adopted and is instructive for how we at EcoProMIS are working with farmers to develop our platform.
The Dance Grows
What at first seems to be a solo dance, a moment later prompted the participation of a second member. The second dancer’s role was not limited to emulating the pioneering dancer. On the contrary, we can see how number two receives instructions on how to perform the dance, while also providing feedback to the pioneer.
Further evidence of the new arrival’s genuine interest is how he invites others to join this spontaneous duo. Like the second, the third dancer follows the movements of the first dancer, while improvising according to the music and rhythm.
What began with an eccentric loner, in a moment becomes a choreography performed by three dancers. We see how the attention generated in the audience, which was initially low, begins to grow.
Soon, the group increases in size again, this time not just by one more dancer, but about five more, and in the blink of an eye, the group reaches at least a dozen. This sudden growth of the group of dancers triggers the arrival of new members and in less than a couple of minutes it grows even further.
Dance as Metaphor
This video, more than simply being an inspiring dance at a music festival, has been considered as an interesting reference about how a forerunner or pioneer (a particular product or technology) can trigger a crowd action.
Like dancer number two and three, we see that there are minority groups with a greater willing to test and use new products, such as EcoProMIS. These enthusiasts are ‘early adopters’. In addition to taking the risk of testing this new product, they also provide feedback on early stage development.
The evaluation of the user experience includes both the users’ perceptions as well as their practice patterns. The feedback process therefore goes beyond simply asking for ‘musical preferences’ to actively inviting users to join the ‘dance’.
The image above is useful to take the dance metaphor further. It adds the complexity that between the Early Market and the Mainstream Market, there is an open space, called ‘The Chasm’. This is the gap that needs to be traversed before a new product reaches large scale collective adoption.
We saw in the video that as the first three guys are dancing there is a gap before additional members join the group. Once the dancing group crossed the chasm, the new members (the ‘pragmatists’ and ‘conservatives’) arrived en masse.
If a small initial group is willing to dance, to test the product and to provide feedback, it suggests that the chasm will be crossed and the product can work with other consumers, becoming part of the mainstream market.
Dancing with EcoProMIS
As has been mentioned before on this blog, the EcoProMIS project is working on cutting-edge technology with crop models, an advanced digital platform and data collection with satellites and drones. Like the first dancer in the video, our work is pioneering, bold and at times eccentric!
It is essential for our project to invite others into a ‘dance’. That is why, in parallel to our product development, EcoProMIS is prioritising activities to test our services.
What this means is that throughout the five year project we are inviting Colombian farmers to participate via surveys and meetings. For example, in the coming months we are planning multiple workshops, where each farmer can access the early versions of our mobile apps and knowledge services. These ‘early adopters’, like dancer two and three, will take that initial risk of joining in, while also providing critical early feedback.
This ‘dance’ of feedback and testing will ensure we can better tailor the EcoProMIS platform, apps, and knowledge services. By doing this, we are able to identify the best options and to contribute to our larger goal of improving sustainability and productivity with Colombian oil palm and rice growers.
Pixalytics Ltd is leading the generation of products from satellite imagery for EcoProMIS. Although satellites can cost a lot to build and launch, once in space, they have the advantage of continuously collecting data.
Many satellite missions last much longer than their designed lifetime, which is typically five years, although they can go wrong, and then it is not easy to fix them. A successful mission includes Landsat-8 that was launched in February 2013 and continues to operate, with Landsat-9 planned for launch in 2023.
One of the longest-lived optical satellite missions is CHRIS/Proba-1 that has been collecting data for nearly 20 years.
In contrast, WorldView-4 was launched in November 2016 and the gyros failed in January 2019 and prevented the spacecraft from pointing accurately. The manufacturer said that while efforts are continuing to restore the spacecraft, “Maxar believes that WorldView-4 will likely not be recoverable and will no longer produce usable imagery.”
Unlike the Hubble Space Telescope, which was serviced by astronauts from the International Space Stations (ISS), polar-orbiting Earth Observation (EO) satellites tend to be orbiting at an altitude almost twice that of the ISS; at around 700-800 km. The exception is the smaller satellites, called CubeSats, that are orbiting at lower altitudes and have been deployed from the ISS. The disadvantage of this lower orbit is that these CubeSats do not have the power to maintain their orbit’s altitude, and so they burn up within the Earth’s atmosphere within a few years.
For EcoProMIS, we are using free-to-access datasets for the baseline data collection: the European Union’s Copernicus Sentinel missions alongside the U.S. Geological Survey/NASA Landsat-8 mission.
These missions are termed free-to-access as anyone can download and process this data. Still, some practicalities include understanding what has been collected, where to get the data and how to handle it. Therefore, Pixalytics continually processes the satellite data to generate near-real-time products that are made available to EcoProMIS.
An example shown below is the classification of land cover using Sentinel-1 and -2.
EcoProMIS Land Cover Classification, data courtesy of Copernicus/ESA.
The satellite-derived products are focused on understanding the health, growth, and potential yield of the crops alongside greenhouse gases. Sentinel-1 provides microwave data that can see through clouds and detect the roughness of a surface, with Sentinel-2 offering high resolution (circa 10 m) optical data and Sentinel-5P calculating the concentration of atmospheric gases.
Landsat-8 compliments Sentinel-2 by providing high resolution optical and thermal data. The satellite products are combined with the UAV (Unmanned Aerial Vehicle, or drone) products and ground collected phenological/gas measurements to give the best estimation of what is happening.
For a rice field, below is a comparison of what is seen by the UAV (left) and satellite (right) data. The UAV data is of a higher spatial resolution (smaller pixel size) compared to the satellite imagery and is taken closer to the ground so is affected less by the effects of the atmosphere. For satellite data, 50% of the signal can come from the atmosphere, and so it is vital to remove this accurately.
Once the atmospheric effects are removed, both the UAV and satellite imagery have the same algorithms applied. They can then be compared to understand the accuracy of the atmospheric correction and increased error caused by the satellite instrument’s larger pixels.
EcoProMIS UAV and Sentinel-2 RGB pseudo true colour product comparison, data courtesy of Copernicus/ESA for Sentinel-2.
Why Both Satellite and UAV
The advantage of the satellite over the UAV data is that we can assemble a time-series plot. An example of this is shown below for the Leaf Area Index (LAI) product, with the higher values being for when the crop is fully grown.
Time-Series plot of LAI, input data courtesy of Copernicus/ESA and USGS/NASA.
By using the satellite data and tracking over time the LAI, we can create models to predict the yield when the crop is harvested, and by comparing it to the crop modelling outputs, we can understand whether interventions can be undertaken to improve the future crop yield.
It is this combination of satellite data and UAV data, together with ground-based agricultural data and modelling that provides the full picture for EcoProMIS. By combining these multiple data sources in our cutting-edge platform, EcoProMIS will be providing knowledge services on mobile apps to growers, allowing growers to make more informed management choices about their crops and land. It is quite something to be using space technology to contribute to the project’s goal of supporting sustainable agriculture.
By Andrea Melissa Sanchez and Leidy Avila, Fedearroz
Why do we grow rice?
In Colombia, rice is a staple food in our diet, it is important for the family basket, and at the same time for the national economy. The average annual consumption is 42.2 kilograms per person.
The rice activity in the country is developed in 210 municipalities of 23 departments. This productive chain generates nearly 410,000 direct and indirect jobs and represents about 0.4% of the national Gross Domestic Product and about 5% of the agricultural GDP.
The country is divided into five rice growing areas (Centro, Llanos Orientales, Bajo Cauca, Santanderes y Costa Norte) and is produced under two systems. The first is the rain-fed system, in which the water used comes from the rains. The second is the irrigation system, in which the water is supplied by irrigation.
On average, in the rain-fed system the yield is 4.19 tons of dry paddy per year, and under irrigated conditions around 5.65 tons.
Who is FEDEARROZ?
With the aim of promoting the development of rice cultivation in Colombia, FEDEARROZ is the National Federation of Rice Growers of Colombia. Since 1947, it has existed to support and give union representation to affiliated producers. In addition, FEDEARROZ offers certified seed, agricultural inputs and technical advice, and manages the National Rice Fund (FNA) whose main mission is to conduct research and the transfer of technology.
Supported by an interdisciplinary group of professionals specialized in different areas such as water and soil management, physiology, plant pathology, entomology, meteorology and plant breeding, FEDEARROZ has been able to establish control and mitigation measures for a large part of the adverse factors that affect crop productivity.
In 22 years of research, 45 varieties of rice adapted to the different needs and rice-growing regions of the country have been registered, and we have managed to maintain stable and competitive production levels sufficient to supply the national demand for rice.
Additionally, since 2012 FEDEARROZ-FNA has been implementing the Mass Adoption Program or AMTEC. This program is set within the context of two major challenges facing the rice sector: climate change and free trade agreements. AMTEC is a technology transfer model that seeks the profitability and competitiveness of rice producers, through increasing yields and reducing production costs, and is based on environmental and social sustainability throughout the production chain.
Agronomical data acquisition by FEDEARROZ engineers in the field. (FEDEARROZ)
Even when it seems that we know everything about rice, that is just not true. Challenges such as climate change and the need to produce more rice with fewer resources and lower environmental impact confront us with the need to form alliances.
The earth observation data complements the phenotypic information acquired in situ on the rice farms. Together, this information is establishing predictive models that facilitate monitoring and decision-making for the effective management of rice farms, and contribute to the objective of having a competitive and profitable rice sector.
What are we doing at EcoProMIS?
Among the departments with the largest area planted with rice in Colombia are Casanare and Tolima, with their two cultivation systems, rainfed and irrigation, respectively.
A field within a farm in each location was selected for EcoProMIS. At these fields the team of researchers from FEDEARROZ working on the project have established a platform for acquiring agronomic data in different stages of the crop, together with climatic information from meteorological stations, and GHG emissions with Eddy Covariance towers and static cameras.
At the same time, UAV images are being taken and analyzed to correlate parameters of rice development with variables such as yield. Additionally, we are working on establishing a robust and calibrated data model for rice cultivation, integrating all the information acquired.
It is expected that the EcoProMIS project will produce a platform for the use of our affiliated farmers, who from the beginning have also been part of the process, contributing their experience and needs for the creation of the platform. We want the pilots to be extended to more farmers, and will continue to work on it through workshops with growers.
We are committed to the Colombian rice sector, and we will continue to advance on that path in projects like this one, which have also allowed us to create a scientific network in which we hope to continue learning and innovating.
With EcoProMis we have a lot to contribute and also a lot to learn!
In recent decades, agriculture has been under the scrutiny of society and the scientific community due to the negative impact that it generates on the environment. These impacts are of many types, including deforestation, eutrophication of water bodies, the reduction of biodiversity due to the intense use of pesticides, and the emission of greenhouse gases (GHG).
In relation to GHG emissions, these are released in the process of manufacturing inputs, such as, fertilizers. Also included are the GHGs released as a result of the transport process: first of inputs towards the production areas, and then of the product towards the consumption areas.
An eddy covariance system recording greenhouse gases emissions on a commercial rice field at Colombia for EcoProMIS project. (Agricompas)
A Complicated Task
But the most complicated task from a methodological point of view is to determine the GHGs that are released during the production stage. Among the GHGs released to the atmosphere during the production phase, the most important are carbon dioxide, methane (in systems where the soil is in anaerobic conditions), nitrous oxide, and ammonia.
Methodological difficulties are associated with the fact that these emissions are determined by dynamic factors such as climate, soil characteristics, and management practices, especially fertilization and irrigation.
Since it is impossible to survive without agriculture, efforts have focused on developing and implementing production systems able to maximize yields while reducing negative effects on the environment. A prerequisite for advancing in this direction is to measure the GHGs generated during agricultural production cycles.
To understand better the methodological challenges involved in determining these gases under field conditions, let us take methane as an example. This gas is generated as a product of the decomposition of organic matter in the soil under non-oxygen conditions, typical of crops such as flooded rice.
Traditionally, static dark chambers have been used to collect samples that are later analysed by the gas chromatography technique in specialized laboratories.
This technique has a high sensitivity to determine low methane fluxes, is easy to handle, and has a low cost. But its main disadvantages are related to the low spatial representativeness and the inability to generate data at different time scales.
In other words, the measurements only represent the gas flux in a small area and at a specific time point, which leads to the question: can this technique generate data to represent what happens in inherently heterogeneous and dynamic agricultural systems?
It is in this context that the technique of eddy covariance appears, as an alternative way to measure, among other variables, methane flows with greater spatial and temporal representativeness.
This technique employs a complex assembly of sensors arranged in a tower (which is why they are usually called eddy covariance towers) that records variables that ultimately allow the determination of the exchange of gases and energy between the crop and the atmosphere.
Although the foundations of the technique and data processing are complex, it provides useful information in the search for more sustainable agricultural systems.
This is because, in addition to determining GHG emissions, such as methane and carbon dioxide, the eddy covariance technique also provides information about the flow of energy between the soil, the plant, and the atmosphere. This means that information is also useful to improve the water use efficiency since the measurements allow the determination of water fluxes from the crops to the atmosphere (evapotranspiration).
All of this information is comparable in terms of accuracy with data obtained by reference instruments such as lysimeters. Therefore, the technique of eddy covariance is currently a powerful ally in the search for more sustainable agricultural systems.
Use with EcoProMIS
The EcoProMIS project has four eddy covariance towers in Colombia, two recording data on rice crops, and two on oil palm crops. The data collected by these stations are being processed to calibrate crop models that allow, in addition to predicting yields, to estimate GHG emissions.
Together with our partners (CIAT, Cenipalma, Fedearroz, IWCO, Pixalytics and Solidaridad), the final objective of the project is to generate “knowledge and decision support” to orient stakeholders towards sustainability.