The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ParserError
Message: Error tokenizing data. C error: Expected 1 fields in line 19, saw 5
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4645, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2866, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3073, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2581, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/csv/csv.py", line 198, in _generate_tables
for batch_idx, df in enumerate(csv_file_reader):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
return self.get_chunk()
~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
return self.read(nrows=size)
~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1923, in read
) = self._engine.read( # type: ignore[attr-defined]
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
nrows
^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
chunks = self._reader.read_low_memory(nrows)
File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 19, saw 5Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
FERTWINS — Tomato greenhouse experimental datasets (DS1–DS5)
Dataset description
This repository contains experimental datasets collected and processed within the FERTWINS project to support research on tomato cultivation under abiotic stress, nitrogen fertigation, irrigation, plant development, and greenhouse environmental conditions.
The deposit is identified by the persistent DOI 10.57967/hf/11263. It contains related experimental tables, sensor time series, and environmental measurements organised into four folders. The files do not constitute a single homogeneous machine-learning table and must be interpreted according to their experimental context and the documentation provided with each dataset.
Repository structure
1_estres_salino/ — Salinity stress
Contains 43 CSV files, 36 Parquet files, and a Markdown dataset card.
The CSV tables cover agronomic observations and derived tables related to tomato development and experimental treatments, including plant height, chlorophyll, flowering, fruiting, ripening, sugar measurements, and irrigation treatments. The Parquet files contain soil-probe measurements related to water, electrical conductivity, and temperature. The folder also includes greenhouse_data_with_reconstruction.csv, containing greenhouse climate data with reconstructed values.
Licence: CC BY 4.0.
2_estres_termico/ — Thermal stress
Contains 36 CSV files, two Excel workbooks, and a Markdown dataset card.
The CSV files cover plant-development and greenhouse-management observations, including flowering, fruiting, inflorescence, pruning, and irrigation, organised by treatment and experimental group. The Excel workbooks contain greenhouse measurements, including date/time, temperature, humidity, acquisition intervals, and event metadata.
Licence: CC BY 4.0.
3_estres_hidrico/ — Water stress
Contains 37 CSV files, one XLSM workbook, two Excel workbooks, and a Markdown dataset card.
The CSV files include greenhouse climate data, soil-probe measurements, and processed observations for control and treatment groups. The workbook datos_tomate_E4.xlsm includes sheets related to irrigation, chlorophyll, pruning, flowering, fruiting, ripening, and sugar measurements. The additional workbooks contain fresh-weight, internode, and tomato-harvest observations.
Licence: CC BY 4.0.
4_datos_nutricontrol/ — Nutricontrol/ETIFA environmental and phenological data
Contains six CSV files and a Markdown dataset card:
conductividad_electrica_suelo.csvfenologia.csvhumedad_relativa_invernadero.csvhumedad_suelo_vwc.csvtemperatura_invernadero.csvtemperatura_suelo.csv
These files contain environmental and phenological time series, including soil electrical conductivity, phenological observations, greenhouse relative humidity, volumetric soil water content, greenhouse temperature, and soil temperature.
Licence: CC BY-NC 4.0. These data are available for non-commercial use with attribution. Commercial use is not permitted under this licence.
Experimental context
The FERTWINS experiments investigate tomato responses to abiotic stress and nitrogen fertigation. The repository includes agronomic observations, greenhouse environmental variables, and soil-probe measurements.
Treatment labels, units, experimental identifiers, sampling frequencies, and the meaning of reconstructed values must be interpreted using the relevant experimental protocols and file-level documentation. They should not be inferred from filenames alone.
Recommended uses
- Research on tomato responses to salinity, thermal, and water stress.
- Analysis of plant development, phenology, and harvest-related measurements.
- Greenhouse climate and soil-sensor time-series analysis.
- Investigation of irrigation, fertigation, and environmental monitoring.
- Development and evaluation of data-processing and modelling methods for greenhouse agriculture.
Limitations and considerations
- The repository contains heterogeneous CSV, Parquet, XLSX, and XLSM files rather than one standardised table.
- Variables, units, sampling intervals, identifiers, and missing-value conventions may differ between files.
- Treatment labels and their units must be checked against the experimental protocol.
- Reconstructed measurements must be distinguished from direct observations.
- Related tables should be joined using documented identifiers and timestamps, not row position.
- No canonical training, validation, or test split is provided.
- Random row-level splitting may cause data leakage when observations from the same plant or time series appear in multiple partitions.
- Sensor calibration, missing-value conventions, and the consistency of plant identifiers should be verified before analysis.
- The datasets represent specific experiments and greenhouse contexts; independent validation is required before generalising results or deploying models.
Data organisation and documentation
Each experimental folder contains a modelcard_dataset.md file describing its contents, recommended uses, limitations, and provenance. Consult these files and the accompanying experimental documentation before using the datasets.
The files are organised by experimental stress, source, treatment, or measurement type. They should be treated as related data resources, with their relationships established using the relevant experimental metadata.
Licences and access conditions
Licensing is defined at dataset-folder level:
1_estres_salino/: CC BY 4.0.2_estres_termico/: CC BY 4.0.3_estres_hidrico/: CC BY 4.0.4_datos_nutricontrol/: CC BY-NC 4.0; attribution is required and commercial use is not permitted.
The licence for the Nutricontrol/ETIFA data applies only to that folder and does not automatically extend to the other datasets. External image datasets used for computer-vision development are separate resources; their original sources and applicable terms must be consulted independently.
Citation
Please cite the FERTWINS project and identify the specific datasets and files used in your work.
Dataset DOI: https://doi.org/10.57967/hf/11263
A formal citation should include the dataset title, project or authorship information, repository, DOI, and access date where required by the publication venue.
Funding
FERTWINS project funded by MCIN/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR.
Contact and further information
- Project: FERTWINS
- Authors and affiliations: [add confirmed names and affiliations]
- Methods and processing code: [add verified GitHub repository URL, if applicable]
- Project contact: [add confirmed contact]
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