project - EIP-AGRI Operational Group
Digitomkku: Big Data test beds for wireless sensors in tomato and cucumber production
Digitomkku: Big data -testipedit langattomille antureille tomaatin ja kurkun tuotantoon
Kontext
The results of Innoväxthus-project (2016-19) that aimed at defining developmental goals for the Ostrobothnian greenhouse cluster in Finland pointed to the importance of product quality and better customer orientation of tomato production. In general, the lack of flavor of industrially produced classic round tomatoes is a well-known issue. How to produce quantity has been the focus of R&D for decades. The production of quality, and particulary good taste, is not as well understood. Choosing a good-tasting cultivar is not always enough, because production procedures and logistics also influence the taste of vegetables. Better steering of plant production is foreseen to be possible with the use of more data that more precisely describes the crops' responses to environmental conditions. But implementing the use of Big Data is quite a complicated task for growers alone. The task is best undertaken by multi-actor groups consisting of experts of different areas in addition to the growers' expertise. Obtaining more precise data from the greenhouse with advanced sensors and associated better understanding of crop physiology can also decrease production costs, particulary energy costs that are high in northern conditions in year-round production, and thus provides an additional motive to implement the use of Big Data.
Objectives
Tastiness of greenhouse vegetables is a competitive asset. How to produce delicious vegetables at industrial level? The project develops databased cultivation of tall greenhouse crops, mainly tomato, with the help of wired and wireless sensors that collect data on the greenhouse climate and plant physiology. The number of sensors collecting abiotic data is expanded, new types of sensors measuring physiology of plants are implemented and data are transferred to a cloud-based platform for visualization and analysis with AI-based methods. The ultimate goal of Digitomkku is to find models that describe which factors are the best explanators of tastiness of vegetables.
Objectives
Kasvihuonevihannesten hyvä maku on tärkeä kilpailutekijä. Miten tuottaa hyvältä maistuvia vihanneksia teollisessa mittakaavassa? Hanke kehittää lähinnä tomaatin dataperusteista viljelyä langallisten ja langattomien sensoreiden avulla. Ne keräävät dataa kasvihuoneen ilmastosta ja kasvien fysiologiasta. Ilmasto-olosuhteita mittaavien sensoreiden määrää suurennetaan tavallisesta, kasvien fysiologiaa mittaavia sensoreita otetaan käyttöön ja ja data siirretään pilvipalvelumuotoiselle data-alustalle, jossa se muutetaan kuviksi ja analysoidaan tekoälymenetelmillä. Perimmäinen tavoite on löytää malleja, jotka kuvaavat vihannesten maukkauteen vaikuttavia tekijöitä.
Activities
Planning & contracts with the key OG of 4 test beds. Setting up the Pylot platform for transferring data from test beds. Installing of, training on and interpretation of data from the new sensors (Phytosense, Gremon Sys Crop Forecaster, leaf temp. sensors, plant stress measurements) and other new procedures (crop registration, sap nutrient analysis) with the key OG and sensor suppliers. Measuring the quality of tomatoes (sugars, acids, taste). Analysis of the data with AI methods to find patterns behind the sensory quality of tomatoes and cropping factors. Regular meetings of the OG to ensure learning and evaluation of the new sensors. Communication of results through different channels.
Activities
Suunnittelu ja sopimukset OG:n kanssa (3 testipetiä). Pylot-data-alustan luonti ja käyttökoulutus. Uusien sensoreiden (Phytosense, lehtien lämpötila, kasvistressin mittarit) tai muiden mittausten (kasvien kasvu, GremonSys-satoennustaja, kasvinesteen ravinneanalyysit) asennus/käyttöönotto, käyttökoulutus ja datan tulkinta niiden toimittajien kanssa. Tomaatin laadun (sokerit, hapot, maku) mittaukset. Data-analyysit tekoälymenetelmillä sadon laatua selittävien tekijöiden löytämiseksi. Säännölliset OG-ydinryhmän ja laajennetun ryhmän tapaamiset oppimista ja uusien mittalaitteiden lisäarvon arviointia varten. Tulosten kommunikointi eri kanavia pitkin.
Additional information
The driving idea of the project is to learn together: first with the test beds, then, by communicating their experiences and results, to invite also other parties to learn about what has been done and achieved with databased cultivation. There are many kinds of apps, sensors and platforms currently to be used in greenhouse vegetable production, but which ones of them are really useful for the specific goals of growers? Can also growers with smaller cropping areas benefit from new technology without excessive costs? This is also a question of interest to us, therefore the participation of a technology-oriented smaller sweet pepper grower in the project is of particular interest. His strategy of choosing sensors and other equipment may be different from those of growers with bigger cropping areas.
Project details
- Main funding source
- Rural development 2014-2020 for Operational Groups
- Rural Development Programme
- 2014FI06RDRP001 Manner-Suomen maaseudun kehittämisohjelma 2014-2020
Ort
- Main geographical location
- Pohjanmaa
- Other geographical location
- Satakunta
EUR 350 000.00
Total budget
Total contributions from EAFRD, national co-financing, additional national financing and other financing.
Ressourcen
Audiovisual materials
1 Practice Abstracts
Digitomkku aims at showing to growers how new kinds of wireless and wired sensors can benefit them in producing better plants and better-tasting end products (tomatoes, sweet peppers). This question is not easy to answer, but the project tries to open the way for answering it. There are many kinds of new technologies (sensors, data platforms, apps) that can be used to measure plants' well being and analyze collected data to fine tune cropping practices. The use of such technologies usually requires a learning phase and a new way of cultivating plants. Such learning is best achieved with grower colleagues and suppliers, advisors and researchers who can together interpret the new data and learn from it, helped by methods based on artificial intelligence. The new instruments must be tried and evaluated for their added value in practice in those use contexts where the growers produce, market and sell their products. Depending on the size of production areas, the growers’ own interest and skills guides them to find solutions that are suitable for their purposes and not prohibitively expensive. The tomato growers in Digitomkku represent "big growers" and the sweet pepper grower represents a "small grower" that most likely have different goals and strategies on how to get and use the new technologies. What they find useful can be a guidance for other growers and even tell researchers what kind of development and research to conduct to serve both types of growers.
Digitomkku aims at showing to growers how new kinds of wireless and wired sensors can benefit them in producing better plants and better-tasting end products (tomatoes, sweet peppers). This question is not easy to answer, but the project tries to open the way for answering it. There are many kinds of new technologies (sensors, data platforms, apps) that can be used to measure plants' well being and analyze collected data to fine tune cropping practices. The use of such technologies usually requires a learning phase and a new way of cultivating plants. Such learning is best achieved with grower colleagues and suppliers, advisors and researchers who can together interpret the new data and learn from it, helped by methods based on artificial intelligence. The new instruments must be tried and evaluated for their added value in practice in those use contexts where the growers produce, market and sell their products. Depending on the size of production areas, the growers’ own interest and skills guides them to find solutions that are suitable for their purposes and not prohibitively expensive. The tomato growers in Digitomkku represent "big growers" and the sweet pepper grower represents a "small grower" that most likely have different goals and strategies on how to get and use the new technologies. What they find useful can be a guidance for other growers and even tell researchers what kind of development and research to conduct to serve both types of growers.
Contacts
Project coordinator
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Susanne West
Project coordinator
Project partners
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Hans Granborg
Project partner
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Irene Vänninen
Project partner
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Jari Pohjola
Project partner
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Martin Sigg
Project partner
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Petri Linna
Project partner
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Sebastian Anttila
Project partner
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Stefan Gulin
Project partner
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Timo Kaukoranta
Project partner
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Tom Lillhonga
Project partner
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Viveka Öling-Wärnå
Project partner