Crop Nutrient Data Ludemann et al 2022: Difference between revisions
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* in case both sowing and harvest date are missing | * in case both sowing and harvest date are missing | ||
* in case the crop type (attribute Crop_standardised) is missing | * in case the crop type (attribute Crop_standardised) is missing | ||
The name of an observation is a combination of the record ID (simply the row number of the original dataset named Summary_statistics_data_from_articles.csv) and the string “Ludemann_et_al_2024” e.g. Ludemann_et_al_2024_1. | The name of an observation is a combination of the record ID (simply the row number of the original dataset named Summary_statistics_data_from_articles.csv) and the string “Ludemann_et_al_2024” e.g. Ludemann_et_al_2024_1. | ||
The comment is based: | The comment is based: | ||
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* Location (latitude and longitude in decimal degrees) | * Location (latitude and longitude in decimal degrees) | ||
* Objective of the experiment | * Objective of the experiment | ||
The combination DOI and location determines an experiment. Each experiment can have one or multiple treatments. Each treatment is an observation identified by the record ID (simply the row number of the original dataset named Summary_statistics_data_from_articles.csv). | The combination DOI and location determines an experiment. Each experiment can have one or multiple treatments. Each treatment is an observation identified by the record ID (simply the row number of the original dataset named Summary_statistics_data_from_articles.csv). | ||
The management was treated as follows: | The management was treated as follows: | ||
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* WaterManagementType = see below | * WaterManagementType = see below | ||
* PestsDiseasesManagementType = UNKNOWN | * PestsDiseasesManagementType = UNKNOWN | ||
With regard to nutrient and water management, we tried to indicate if the treatment of an experiment was optimal or suboptimal for nitrogen (N), phosphorus (P), potassium (K), nutrient (N/P/K) and water management. Therefore, we used the values of the attributes: | With regard to nutrient and water management, we tried to indicate if the treatment of an experiment was optimal or suboptimal for nitrogen (N), phosphorus (P), potassium (K), nutrient (N/P/K) and water management. Therefore, we used the values of the attributes: | ||
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* Fertiliser_K_kg_K_ha | * Fertiliser_K_kg_K_ha | ||
* Actual_irrigation_mm | * Actual_irrigation_mm | ||
This was done for experiments that studied varying N, P, K or irrigation applications. The assumption is that experiments that vary nutrient or water have one treatment that is optimal for the varying factor. The experiments were identified by checking: | This was done for experiments that studied varying N, P, K or irrigation applications. The assumption is that experiments that vary nutrient or water have one treatment that is optimal for the varying factor. The experiments were identified by checking: | ||
* the objective of the experiment (e.g. studying effect of varying N-application) | * the objective of the experiment (e.g. studying effect of varying N-application) | ||
* clear variation of N, P, K or irrigation application | * clear variation of N, P, K or irrigation application | ||
The treatment with the highest application was labelled optimal while the other treatments, having lower application values, were labelled as suboptimal. In case these experiments had relative high application value of the other main inputs (nutrients, water), these inputs were also labelled as optimal. In case all N, P and K were labelled as optimal the nutrient management as a whole was also labelled optimal, otherwise suboptimal. Note that some experiments were not yet included because of time constraints (multiple experiments that share one objective). | The treatment with the highest application was labelled optimal while the other treatments, having lower application values, were labelled as suboptimal. In case these experiments had relative high application value of the other main inputs (nutrients, water), these inputs were also labelled as optimal. In case all N, P and K were labelled as optimal the nutrient management as a whole was also labelled optimal, otherwise suboptimal. Note that some experiments were not yet included because of time constraints (multiple experiments that share one objective). | ||
Note that this indication of optimal or suboptimal management is rather uncertain and must be used with care. We advise to also consult the original data (Summary_statistics_data_from_articles.csv) which is easily found through the record ID. | Note that this indication of optimal or suboptimal management is rather uncertain and must be used with care. We advise to also consult the original data (Summary_statistics_data_from_articles.csv) which is easily found through the record ID. | ||
In all other cases (other experiments) the management was labelled as unknown. | In all other cases (other experiments) the management was labelled as unknown. | ||
=== Phenology === | === Phenology === | ||
Revision as of 15:10, 10 October 2024
Summary statistics data from a range of articles found in the scientific literature related to crop harvest index and nutrient concentrations of crop products (e.g. beans and grain) and crop residues (straw and stover).
Provider's website
https://doi.org/10.5061/dryad.djh9w0w4m
https://doi.org/10.1016/j.fcr.2022.108578
Documentation
Ludemann, C.I, Hijbeek, R., van Loon, M., Murrell, T.S., Dobermann, A. and van Ittersum, M. (2024), Published field experimental data of crop yields, nutrient concentrations, and harvest indices from around the world.
Ludemann CI, Hijbeek R, van Loon MP, Murrell TS, Dobermann A, van Ittersum MK. 2022. Estimating maize harvest index and nitrogen concentrations in grain and residue using globally available data. Field Crops Research 284: 1-25.
Pre-processing
Original data filtered:
- in case the location is missing (latitude and longitude)
- in case both sowing and harvest date are missing
- in case the crop type (attribute Crop_standardised) is missing
The name of an observation is a combination of the record ID (simply the row number of the original dataset named Summary_statistics_data_from_articles.csv) and the string “Ludemann_et_al_2024” e.g. Ludemann_et_al_2024_1.
The comment is based:
- DOI
- Record ID (of the original dataset)
- Location (latitude and longitude in decimal degrees)
- Objective of the experiment
The combination DOI and location determines an experiment. Each experiment can have one or multiple treatments. Each treatment is an observation identified by the record ID (simply the row number of the original dataset named Summary_statistics_data_from_articles.csv).
The management was treated as follows:
- FieldManagementType = FIELD_TRIAL
- NutrientsNType = see below
- NutrientsPType = see below
- NutrientsKType = see below
- NutrientsManagementType = see below
- WaterManagementType = see below
- PestsDiseasesManagementType = UNKNOWN
With regard to nutrient and water management, we tried to indicate if the treatment of an experiment was optimal or suboptimal for nitrogen (N), phosphorus (P), potassium (K), nutrient (N/P/K) and water management. Therefore, we used the values of the attributes:
- Fertiliser_N_kg_N_ha
- Fertiliser_P_kg_P_ha
- Fertiliser_K_kg_K_ha
- Actual_irrigation_mm
This was done for experiments that studied varying N, P, K or irrigation applications. The assumption is that experiments that vary nutrient or water have one treatment that is optimal for the varying factor. The experiments were identified by checking:
- the objective of the experiment (e.g. studying effect of varying N-application)
- clear variation of N, P, K or irrigation application
The treatment with the highest application was labelled optimal while the other treatments, having lower application values, were labelled as suboptimal. In case these experiments had relative high application value of the other main inputs (nutrients, water), these inputs were also labelled as optimal. In case all N, P and K were labelled as optimal the nutrient management as a whole was also labelled optimal, otherwise suboptimal. Note that some experiments were not yet included because of time constraints (multiple experiments that share one objective).
Note that this indication of optimal or suboptimal management is rather uncertain and must be used with care. We advise to also consult the original data (Summary_statistics_data_from_articles.csv) which is easily found through the record ID.
In all other cases (other experiments) the management was labelled as unknown.
Phenology
Attribute: Date_sowing_YYYYMMDD (Sowing date in YYYYMMDD format) and Date_harvest_YYYYMMDD (Harvest date in YYYYMMDD format)
Remark: Harvest data is also used as the date of the plant density, yield and above ground biomass
Attributes:
Harvest_density_Plants_m2 (Density of plants at harvest, plants per m2) CPY_mean_kg_fresh_ha (Mean crop product, kg per ha in fresh weight) AGY_mean_kg_fresh_ha (Mean above ground biomass, kg per ha in fresh weight) CPY_mean_kg_DM_ha (Mean crop product, kg per ha in dry weight) AGY_mean_kg_DM_ha (Mean above ground biomass, kg per ha in dry weight)
