HIPPA - Hyperspectral and RGB imaging of wound-inoculated apples with postharvest pathogens


Abstract

This collection is part of the HIPPA project, which investigates physiological disorders, mechanical damage and fungal diseases affecting apple fruit at harvest and during postharvest using hyperspectral imaging, RGB imaging and spectroscopy. This collection contains RGB images and hyperspectral images of wound-inoculated apples infected with eight different pathogens and corresponding control samples. Healthy-looking apples were manually surface-sterilized and inoculated with spore suspensions. To cover all cultivars and pathogens, apples were prepared and acquired in groups referred to as 'batches' at different timestamps. Each batch contains apples from one specific cultivar and includes a subset of pathogen treatments together with control samples; each batch generally contains approximately 24 apples per included treatment and approximately 24 control apples. Each STAC Item represents one apple sample at one specific day post-inoculation. Item identifiers follow the pattern apple_{sample_id}_dpi{dpi:02d}, for example apple_57000_dpi03. The acquisition setup is an enclosed space of approximately 1 x 1 m, equipped with a lighting system, a rotating platform and multiple optical instruments measuring the apple surface. Acquisitions are performed in the Eurac Research - Center for Sensing Solutions laboratories. The Collection spatial extent represents the general area of origin of the apple samples, while Item geometries represent the laboratory acquisition location.

FAIR Overall Score

96%

Keywords

HIPPA project, apple fruit, hyperspectral imaging, RGB imaging, spectroscopy, multimodal imaging, postharvest, plant pathology, fungal disease, wound inoculation

Digital Object Identifier (DOI)

https://doi.org/10.48784/ct64-7f19

Citation

Eurac Research, Free University of Bozen-Bolzano, & Laimburg Research Centre. (2026). HIPPA - Hyperspectral and RGB imaging of wound-inoculated apples with postharvest pathogens. Eurac Research. https://doi.org/10.48784/CT64-7F19

CC-BY-4.0


FAIR Overall Score: 96%

Evaluated by F-UJI - An Automated FAIR Data Assessment Tool: https://doi.org/10.5281/zenodo.6361400

Findable 100%
Accessible 100%
Interoperable 100%
Reusable 83%
Findable Advanced
Metadata and data are assigned a globally unique identifier.
FsF-F1-01MD · 1/1
  • Metadata identifier follows a defined unique identifier syntax or scheme (IRI, URL, UUID, HASH or PID) (1/1)
Metadata and data are assigned a persistent identifier.
FsF-F1-02MD · 1/1
  • Metadata identifier follows a defined persistent identifier syntax (0.5/0.5)
  • Persistent identifier for metadata is registered and maintained by a PID authority (0.5/0.5)
Metadata includes descriptive core elements (creator, title, data identifier, publisher, publication date, summary and keywords) to support data findability.
FsF-F2-01M · 2/2
  • Core data citation metadata is available (1/1)
  • Core descriptive metadata is available (1/1)
Metadata includes the identifier of the data it describes.
FsF-F3-01M · 1/1
  • Metadata contains a PID or URL which indicates the location of the downloadable data content (1/1)
Metadata is offered in such a way that it can be registered or indexed by search engines.
FsF-F4-01M · 2/2
  • Metadata is given in a way major search engines can ingest it for their catalogues (Dublin Core or schema.org or DCAT encoded in microdata, RDFa, embedded JSON-LD or meta tags see e.g. Google Dataset Search webmaster guidelines) (2/2)
Accessible Advanced
Metadata contains access level and access conditions of the data.
FsF-A1-01M · 1/1
  • Information about access restrictions or rights can be identified in metadata (1/1)
Metadata and data are retrievable by their identifier
FsF-A1-02MD · 2/2
  • Metadata are retrievable via their specified identifier (1/1)
  • Data are retrievable via the identifiers given in metadata (1/1)
A standardized communication protocol is used to access metadata and data.
FsF-A1.1-01MD · 2/2
  • Identifier leading to metadata matches a scheme indicating a standardized web communication protocol. (1/1)
  • Identifier leading to data are matching a schema indicating a standardized web communication protocol. (1/1)
Metadata and data are accessible through a standardized communication protocol which supports authentication.
FsF-A1.2-01MD · 2/2
  • The communication protocol found in identifiers (IRIs) leading to metadata supports authentication. (1/1)
  • The communication protocol identified in data links (IRIs) supports authentication. (1/1)
Interoperable Advanced
Metadata is represented using a formal knowledge representation language.
FsF-I1-01M · 2/2
  • Parsable, structured metadata (JSON-LD, RDFa) is embedded in the landing page XHTML/HTML code (2/2)
  • Parsable, structured metadata (RDF, JSON-LD) is accessible through content negotiation, typed links or sparql endpoint (2/2)
Metadata uses registered semantic resources
FsF-I2-01M · 2/2
  • Metadata uses terms from registered vocabularies that are identified by their namespaces (2/2)
Metadata includes qualified references between the data and its related entities.
FsF-I3-01M · 2/2
  • Related resources are referenced in plain text within appropriate metadata properties indicating the relation type (2/2)
  • Related resources are referenced by machine readable links or identifiers within appropriate metadata properties indicating the relation type (2/2)
Reusable Moderate
Metadata specifies the content of the data.
FsF-R1-01M · 1/2
  • Minimum information (resource type) about the available data content is specified in the metadata (1/1)
  • Information on the manner and form (file size and type or service (API) endpoint and protocol) in which data is delivered is provided (0/1)
Metadata includes license information under which data can be reused.
FsF-R1.1-01M · 1/1
  • Licence information is given in an appropriate metadata element (1/1)
Metadata includes provenance information about data creation or generation.
FsF-R1.2-01M · 1/1
  • Metadata contains elements which hold provenance information which can be mapped to PROV based on PROV-DC. (1/1)
  • Metadata contains elements which hold provenance information using formal provenance ontologies (PROV, PAV). (0/1)
Metadata follows a standard recommended by the target research community of the data.
FsF-R1.3-01M · 1/1
  • Community specific metadata standard is detected using namespaces or schemas found in provided metadata (1/1)
  • Multidisciplinary but community endorsed metadata (RDA Metadata Standards Catalog, fairsharing) standard is detected by namespace (1/1)
Data is available in a file format recommended by the target research community.
FsF-R1.3-02D · 1/1
  • Data is available in a file format recommended by the research community (long term file formats, open file formats or scientific file format) (1/1)

Assessed 2026-09-07 (metrics 0.8)

Snippet code

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##### ----Explore and download STAC data with Python ----- #####

from pystac_client import Client

## Read the example catalog
URL = 'https://stac.eurac.edu/'
catalog = Client.open(URL)

## List the Collections in the given Catalog
stac_collections = list(catalog.get_collections())
print(f"Number of collections: {len(stac_collections)}")

## Print collection IDs
print("Collections IDs:")
for collection in stac_collections:
    print(f"- {collection.id}")
print("-------------------------")

## Retrieve a specific collection
collection = catalog.get_collection("hippa-pathogens-wound-inoculation")

## Search for items in the collection
collection_items = list(catalog.search(collections=['hippa-pathogens-wound-inoculation'], max_items=10).items())
print(collection_items)

## Retrieve a list of the first 10 items belonging to a specific collection
item = collection.get_item("NameOfTheItem")
#print(list(item.assets.items())[0:10])

##Print the band name and the href of a specific item retrieved from the previous list
print(item.assets["hippa-pathogens-wound-inoculation"].title)
print(item.assets["hippa-pathogens-wound-inoculation"].href)

## Print Item’s assets through the assets attribute, which is a dictionary
for asset_key in item.assets:
    asset = item.assets[asset_key]
    print("{}: {} ({})".format(asset_key, asset.href, asset.media_type))

## ------------- DONWLOAD COG files from a specific collection ------- ####
from pystac_client import Client
import requests

## Read the example catalog
URL = 'https://stac.eurac.edu/'
catalog = Client.open(URL)

## List the Collections in the given Catalog
stac_collections = list(catalog.get_collections())
# print(f"Number of collections: {len(stac_collections)}")

## Print collection IDs
print("Collections IDs:")
for collection in stac_collections:
	print(f"- {collection.id}")
print("-------------------------")

## Retrieve a specific collection
collection = catalog.get_collection("hippa-pathogens-wound-inoculation")

## Search for items in the collection
collection_items = list(catalog.search(collections=['hippa-pathogens-wound-inoculation'], max_items=10).items())
print(collection_items)

url_basepath = "https://eurac-eo.s3-eu-west-1.amazonaws.com/"
collection_url = url_basepath + "hippa-pathogens-wound-inoculation" + "/"
print(collection_url)
for item_id in collection_items:
	# item = item.assets[asset_key]
	print(item_id.id)
	cog_file = str(item_id.id + '.tif')
	url = collection_url + cog_file
	response = requests.get(url)
	with open(cog_file, "wb") as f:
		f.write(response.content)

# Name Description Link Date published Category
1 MOOC Cubes and Clouds Free Online Course teaching the concepts of data cubes, cloud platforms and open science in geospatial and EO. Link March 8, 2024 OpenEO, STAC
2 STAC guidelines Documentation to browse and download items of the STAC catalog Link Feb. 22, 2024 STAC