SFAM — Smart Fungal Advice Model (Q3988767): Difference between revisions
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The multiple use of plant protection products is a societal challenge. In the agricultural sector, billions of euros are spent worldwide on the fight against fungi by chemical means. Despite all these efforts, the effects on yield continue to have a substantial negative impact. And the use of these substances is harmful to humans and animals. Usually the chemical products are administered according to a standard prescription from the manufacturer. However, this is not a guarantee of success. Fungi develop on the basis of the effects of the climatic conditions of that moment. No season is the same, so these fungi also develop differently every season. In recent years, new knowledge and technology has been developed around us at a huge pace that can have a positive effect on the ease of use and accuracy of current mold advice models. These include geo technology, multi spectral images (satellite images, UAV, sensors on the tractor ect.), greatly improved weather models, data analytiscs, open datasets from the government ect. By gaining this knowledge, and implementing these innovations around us, the current user thresholds can be removed and the models retain their state-of-the-art leading position in the world. The dream is to be able to provide fungal advice directly to every grower in the world via a subscription system. In this way, the breakthrough towards the group of users belonging to the Early and Late Majority can be realised. With such a breakthrough, the developed knowledge can spread rapidly in the agricultural sector. The project is divided into 3 work packages. Work Package 1: knowledge development fungi is aimed at mapping the latest agronomic insights about the development of fungi. Work Package 2: knowledge development datasets focuses on the surrounding data technology around us. Project partners develop knowledge about new data sources and gain insight into the effects on predicting the development of the life cycle of fungi.In work package 3: Proof-of-concept advisory model combines the developed knowledge into a concept algorithm. There are 4 northern SMEs working together in this project. All located in Drenthe or Groningen. The two smaller SMEs, Zageo and Infabula participate because of their very specific background and knowledge domain. Normally, these specialists are not quickly deployed for research and knowledge development processes. (English) | |||||||||||||||
| Property / summary: The multiple use of plant protection products is a societal challenge. In the agricultural sector, billions of euros are spent worldwide on the fight against fungi by chemical means. Despite all these efforts, the effects on yield continue to have a substantial negative impact. And the use of these substances is harmful to humans and animals. Usually the chemical products are administered according to a standard prescription from the manufacturer. However, this is not a guarantee of success. Fungi develop on the basis of the effects of the climatic conditions of that moment. No season is the same, so these fungi also develop differently every season. In recent years, new knowledge and technology has been developed around us at a huge pace that can have a positive effect on the ease of use and accuracy of current mold advice models. These include geo technology, multi spectral images (satellite images, UAV, sensors on the tractor ect.), greatly improved weather models, data analytiscs, open datasets from the government ect. By gaining this knowledge, and implementing these innovations around us, the current user thresholds can be removed and the models retain their state-of-the-art leading position in the world. The dream is to be able to provide fungal advice directly to every grower in the world via a subscription system. In this way, the breakthrough towards the group of users belonging to the Early and Late Majority can be realised. With such a breakthrough, the developed knowledge can spread rapidly in the agricultural sector. The project is divided into 3 work packages. Work Package 1: knowledge development fungi is aimed at mapping the latest agronomic insights about the development of fungi. Work Package 2: knowledge development datasets focuses on the surrounding data technology around us. Project partners develop knowledge about new data sources and gain insight into the effects on predicting the development of the life cycle of fungi.In work package 3: Proof-of-concept advisory model combines the developed knowledge into a concept algorithm. There are 4 northern SMEs working together in this project. All located in Drenthe or Groningen. The two smaller SMEs, Zageo and Infabula participate because of their very specific background and knowledge domain. Normally, these specialists are not quickly deployed for research and knowledge development processes. (English) / rank | |||||||||||||||
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| Property / summary: The multiple use of plant protection products is a societal challenge. In the agricultural sector, billions of euros are spent worldwide on the fight against fungi by chemical means. Despite all these efforts, the effects on yield continue to have a substantial negative impact. And the use of these substances is harmful to humans and animals. Usually the chemical products are administered according to a standard prescription from the manufacturer. However, this is not a guarantee of success. Fungi develop on the basis of the effects of the climatic conditions of that moment. No season is the same, so these fungi also develop differently every season. In recent years, new knowledge and technology has been developed around us at a huge pace that can have a positive effect on the ease of use and accuracy of current mold advice models. These include geo technology, multi spectral images (satellite images, UAV, sensors on the tractor ect.), greatly improved weather models, data analytiscs, open datasets from the government ect. By gaining this knowledge, and implementing these innovations around us, the current user thresholds can be removed and the models retain their state-of-the-art leading position in the world. The dream is to be able to provide fungal advice directly to every grower in the world via a subscription system. In this way, the breakthrough towards the group of users belonging to the Early and Late Majority can be realised. With such a breakthrough, the developed knowledge can spread rapidly in the agricultural sector. The project is divided into 3 work packages. Work Package 1: knowledge development fungi is aimed at mapping the latest agronomic insights about the development of fungi. Work Package 2: knowledge development datasets focuses on the surrounding data technology around us. Project partners develop knowledge about new data sources and gain insight into the effects on predicting the development of the life cycle of fungi.In work package 3: Proof-of-concept advisory model combines the developed knowledge into a concept algorithm. There are 4 northern SMEs working together in this project. All located in Drenthe or Groningen. The two smaller SMEs, Zageo and Infabula participate because of their very specific background and knowledge domain. Normally, these specialists are not quickly deployed for research and knowledge development processes. (English) / qualifier | |||||||||||||||
point in time: 15 December 2021
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Revision as of 06:18, 15 December 2021
Project Q3988767 in Netherlands
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | SFAM — Smart Fungal Advice Model |
Project Q3988767 in Netherlands |
Statements
548,396.0 Euro
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1,448,866.579 Euro
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37.85 percent
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1 June 2016
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31 December 2018
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Crop-R BV
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53°12'16.85"N, 6°35'19.43"E
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9723 ZA
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Het vele gebruik van gewasbeschermingsmiddelen is een maatschappelijke uitdaging. In de agrarische sector worden wereldwijd miljarden euro’s besteed aan de bestrijding van schimmels met chemische middelen. Ondanks al deze inspanningen hebben de aantastingen nog steeds een substantieel negatief effect op de opbrengst. En het gebruik van deze middelen is schadelijk voor mens en dier. Meestal worden de chemische middelen toegediend volgens een standaard recept van de fabrikant. Dit is echter geen garantie voor succes. Schimmels ontwikkelen zich op basis van de effecten van de klimatologische omstandigheden van dat moment. Geen seizoen is gelijk, dus ook ontwikkelen deze schimmels zich ieder seizoen anders. De laatste jaren is om ons heen in een enorm tempo nieuwe kennis en technologie ontwikkeld die een positief effect kunnen hebben op het gebruikersgemak en de nauwkeurigheid van huidige schimmeladvies modellen. Denk hierbij aan geo technologie , multi spectrale beelden (satellietbeelden, UAV, sensoren op de trekker ect.), sterk verbeterde weermodellen, data analytiscs, open datasets van de overheid ect. Door het binnenhalen van deze kennis, en de implementatie van deze innovaties om ons heen kunnen de huidige gebruikersdrempels worden weggenomen en behouden de modellen haar state-of-the-art koploperpositie in de wereld. De droom is om met een klik op de knop iedere teler in de wereld via een abonnementensysteem direct van schimmeladviezen te kunnen voorzien. Op deze wijze kan de doorbraak richting de groep gebruikers die behoren tot de Early en Late Majority worden gerealiseerd. Met zo een doorbraak kan de ontwikkelde kennis zich in hoog tempo verspreiden in de agrarische sector. Het project is opgedeeld in 3 werkpakketten. Werkpakket 1: kennisontwikkeling schimmels is gericht op het in kaart brengen van de nieuwste agronomische inzichten omtrent de ontwikkeling van schimmels. Werkpakket 2: kennisontwikkeling datasets richt zich op de omliggende data technologie om ons heen. Projectpartners ontwikkelen kennis omtrent nieuwe databronnen en verkrijgen inzicht in de effecten op de voorspelling van de ontwikkeling van de levenscyclus van schimmels.In werkpakket 3: Proof-of-concept adviesmodel komt de ontwikkelde kennis samen in een concept algoritme. Er werken in dit project 4 noordelijke MKB bedrijven samen. Allen gevestigd in Drenthe of Groningen. De twee kleinere MKB-ers, Zageo en Infabula doen mee vanwege hun zeer specifieke achtergrond en kennisdomein. Normaliter worden deze specialisten niet snel ingezet voor onderzoeks- en kennisontwikkeltrajecten. (Dutch)
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The multiple use of plant protection products is a societal challenge. In the agricultural sector, billions of euros are spent worldwide on the fight against fungi by chemical means. Despite all these efforts, the effects on yield continue to have a substantial negative impact. And the use of these substances is harmful to humans and animals. Usually the chemical products are administered according to a standard prescription from the manufacturer. However, this is not a guarantee of success. Fungi develop on the basis of the effects of the climatic conditions of that moment. No season is the same, so these fungi also develop differently every season. In recent years, new knowledge and technology has been developed around us at a huge pace that can have a positive effect on the ease of use and accuracy of current mold advice models. These include geo technology, multi spectral images (satellite images, UAV, sensors on the tractor ect.), greatly improved weather models, data analytiscs, open datasets from the government ect. By gaining this knowledge, and implementing these innovations around us, the current user thresholds can be removed and the models retain their state-of-the-art leading position in the world. The dream is to be able to provide fungal advice directly to every grower in the world via a subscription system. In this way, the breakthrough towards the group of users belonging to the Early and Late Majority can be realised. With such a breakthrough, the developed knowledge can spread rapidly in the agricultural sector. The project is divided into 3 work packages. Work Package 1: knowledge development fungi is aimed at mapping the latest agronomic insights about the development of fungi. Work Package 2: knowledge development datasets focuses on the surrounding data technology around us. Project partners develop knowledge about new data sources and gain insight into the effects on predicting the development of the life cycle of fungi.In work package 3: Proof-of-concept advisory model combines the developed knowledge into a concept algorithm. There are 4 northern SMEs working together in this project. All located in Drenthe or Groningen. The two smaller SMEs, Zageo and Infabula participate because of their very specific background and knowledge domain. Normally, these specialists are not quickly deployed for research and knowledge development processes. (English)
15 December 2021
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Identifiers
OP-2014-2023-Noord-OPSNN0084
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