Opendata, web and dolomites

AGERPIX SIGNED

Artificial intelligence for yield estimations at fruit orchards

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 AGERPIX project word cloud

Explore the words cloud of the AGERPIX project. It provides you a very rough idea of what is the project "AGERPIX" about.

harvest    124    practical    validation    spanish    heights    jobs    time    logistical    minor    decisions    successful    54    intensity    crop    vigour    treatments    ebit    95    ai    data    140ha    estimations    season    replicated    accurate    strengthen    inaccurate    cold    intensive    mention    peach    artificial    labour    orchard    precision    business    manual    varieties    5m    envision    mid    apple    codesian    operations    quality    workers    table    ranges    careful    50    reduce    b2b    markets    38m    thinning    easily    consuming    whale    growers    yield    producers    grape    fruits    plant    planning    strategy    commercialization    nurfri    diameter    size    blue    created    worth    storage    gathering    algorithms    validations    health    extremely    nutrients    revenues    materials    fruit    ongoing    160m    force    machinery    estimation    tangerine    customer    provides       agerpix    grapes    packing    intelligence    plan    global    extensive    9m    analysed    adaptations    predictions    517    leafiness    portfolio    counting    2024    warehouses    service    299    variables    piloting    sensor    avocado    french   

Project "AGERPIX" data sheet

The following table provides information about the project.

Coordinator
CODESIAN SOFTWARE TECH SL 

Organization address
address: CL DEL NARANJO 6 4 44
city: GOLMAYO (SORIA)
postcode: 42190
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3. (PRIORITY 'Societal challenges)
2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs)
3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies)
 Code Call H2020-SMEInst-2018-2020-1
 Funding Scheme SME-1
 Starting year 2019
 Duration (year-month-day) from 2019-12-01   to  2020-02-29

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    CODESIAN SOFTWARE TECH SL ES (GOLMAYO (SORIA)) coordinator 50˙000.00

Map

 Project objective

'Crop yield estimation is an important task in apple orchard management. The current practice of yield estimation is based on manual counting of fruits by workers. It is extremely time-consuming, labour-intensive, highly inaccurate, and it is not practical for large fields. Agerpix provides accurate predictions to help growers improve fruit quality and reduce operating costs by making better decisions on intensity of fruit thinning and plant nutrients and treatments (mid-season), size of the harvest labour force, machinery and materials and logistical planning of storage, packing and cold warehouses, not to mention the development of a commercialization strategy tailored to the expected production, achieving a 50% cost reduction in orchard management operations. Artificial Intelligence algorithms are used to identify, measure diameter ranges, and envision the fruit leafiness and vigour, providing yield estimations over the plant heights and plant health variables. Several piloting projects for the yield estimation system at top apple producers (Nurfri - #1 Spanish and Blue Whale #1 French among others) have been deployed with 140ha analysed with a precision of 90-95%. AGERPIX system has been adapted to four different apple varieties. After successful validation activities, CODESIAN is developing a customer portfolio worth 38M€ in five years. However, because AGERPIX is offering as a B2B service and because the technology can be easily replicated to other fruits (ongoing validations with table grapes and peach with minor AI/sensor adaptations), a careful scale-up design to strengthen the business plan towards covering global needs fruit markets (apple: 517 M€; table grape: 124 M€; peach: 160M€; tangerine: 299 M€; avocado: 54 M€) is needed. After further data gathering through extensive validations across new fruits, CODESIAN projects 7,9M€ revenues with 4,5M€ EBIT and 60 new jobs created by 2024. '

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "AGERPIX" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "AGERPIX" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.3.;H2020-EU.2.3.;H2020-EU.2.1.)

ECOBIOMASS (2019)

Achieving unique wines through an efficient production process

Read More  

COPI (2020)

Carbon Offset Plug-in

Read More  

Proteus 25 (2018)

Developing the world’s first food wrapping machine with organic film

Read More