Open Data Journal for Agricultural Research
ISSN / EISSN : 2352-6378 / 2352-6378
Published by: Wageningen UR Facilitair Bedrijf (10.18174)
Total articles ≅ 27
Latest articles in this journal
Published: 6 October 2021
Open Data Journal for Agricultural Research, Volume 7, pp 20-26; https://doi.org/10.18174/odjar.v7i0.17959
Approximately 7,600 wheat plots were surveyed and geo-tagged in the 2017-18 winter or rabi season in Bihar and eastern Uttar Pradesh (UP) in India to capture farmers’ wheat production practices at the landscape level. A two-stage cluster sampling method, based on Census data and electoral rolls, was used to identify 210 wheat farmers in each of 40 districts. The survey, implemented in Open Data Kit (ODK), recorded 226 variables covering major crop production factors such as previous crop, residue management, crop establishment method, variety and seed sources, nutrient management, irrigation management, weed flora and their management, harvesting method and farmer reported yield. Crop cuts were also made in 10% of fields. Data were very carefully checked with enumerators. These data should be very useful for technology targeting, yield prediction and other spatial analyses.
Published: 6 October 2021
Open Data Journal for Agricultural Research, Volume 7, pp 11-19; https://doi.org/10.18174/odjar.v7i0.16124
Greenhouse gas emissions (GHG), as well as other gaseous emissions and agronomic variables were continuously measured for three years (2011/2012 – 2014/2015) at eight experimental field sites in Germany. All management activities were consistently documented. The GHG-DB-Thuenen stores these multi-variable data sets of gas fluxes (CO2, N2O, CH4 and NH3), crop parameters (ontogenesis, aboveground biomass, grain and straw yield, N and C content, etc.), soil characteristics (nitrogen content, NH4-N, NO3-N, bulk density etc.), continuously recorded meteorological variables (air and soil temperatures, radiation, precipitation, etc.), management activities (sowing, harvest, soil tillage, fertilization, etc.), and its metadata (methods, further information about variables, etc.). In addition, NOx data were measured and analyzed. Also available are site-specific calculated C and N balances for the respective crops and crop rotations.
Published: 31 August 2020
Open Data Journal for Agricultural Research, Volume 6, pp 21-27; https://doi.org/10.18174/odjar.v6i0.16326
The simulated data set described in this paper was created by an ensemble of nine different crop models: HERMES (HE), Simplace (L5), SiriusQuality (SQ), MONICA (MO), Sirius2014 (S2), FASSET (FA), 4M (4M), SSM (SS), DSSAT-CSM IXIM (IX). Simulations were performed for grain maize (six models) and winter wheat (eight models) under diverse conditions over agriculturally relevant areas in the EU-27 at a 25 x 25 km spatial resolution. Simulations were drawn from combinations of three representative concentration pathways and climate outputs from five general circulation models for time periods 2040-2069 and 2070-2099. Historical climate data was the basis for simulation years 1980-2010 and considered as a baseline. Simulation results from 1980-2010 and 2040-2069 were used to analyze crop responses to changing climatic variables and their diverging sensitivities to these variables. This data paper describes the creation, motivation and format of the simulation results to enable others to use the data set.
Published: 31 August 2020
Open Data Journal for Agricultural Research, Volume 6, pp 34-38; https://doi.org/10.18174/odjar.v6i0.17915
This paper contains data from a two year FACE experiment with maize (Zea mays L., cv. ‘Romario’) investigating the interaction of two CO2 concentrations (378, 550 ppm) and two levels of water supply (sufficient: wet, limited: dry) on crop growth and plant composition. In the second year soil cover was also varied to test whether mitigation of evaporation by straw mulch increases the CO2 effect on water use efficiency. The datasets assembled herein contain data on weather, management, soil condition, soil moisture, phenology, dry weights and N concentrations of the plant (leaves, stems, cobs), green leaf area index, stem reserves, final yield and quality-related traits in the total plant and grains. Most of the experimental findings have already been published in scientific journals. Moreover, the data have been used in two crop modeling studies, and simulation results (on soil moisture, transpiration, evaporation and biomass) of one of these studies are also shown here.
Published: 31 August 2020
Open Data Journal for Agricultural Research, Volume 6, pp 28-33; https://doi.org/10.18174/odjar.v6i0.16397
This data paper contains data from a FACE experiment with winter wheat (Triticum aestivum, c.v. Batis) carried out over two years at Braunschweig, Germany. The experimental variants included firstly a study on the interaction of two levels of CO2 (393, 600 ppm) and three levels of nitrogen (N) fertilization (ca. 40, 190 and 320 kg N ha-1) and secondly a study on the interaction of these CO2 treatments and three levels of infrared warming during grain filling (ambient, ca. +1.5°C and +3°C). In the second study N supply was only ca. 190 kg N ha-1. The datasets of the two studies assembled herein contain data on weather, management, soil condition, soil moisture, phenology, dry weights and N concentrations of the plant (leaves, stems ears), green area index, stem reserves, final grain yield and yield components as well as canopy temperatures (this only applies to the second study). Most of the experimental findings have already been published in scientific journals. Data provided herein are suited to validate the interaction of elevated CO2 concentration and either N supply or high temperature during grain filling in wheat growth models.
Published: 4 June 2020
Open Data Journal for Agricultural Research, Volume 6, pp 19-20; https://doi.org/10.18174/odjar.v6i0.16318
The dataset includes detailed field experiments from four locations across a temperature gradient along the River Nile. The data covering four contrasting environments from North (low temperature) to South (high temperature), includes Sakha (North delta, lower Egypt), Menofya (Middle delta), Benisuef (Middle Egypt) and Aswan (upper Egypt). Measurements included plant density, aboveground biomass, anthesis and maturity dates, grain yield, grains m-2, kernel weight and N content in grains as well as daily weather data (solar radiation, maximum and minimum temperature, precipitation, surface wind, relative humidity, dew point and vapor pressure) and soil characteristics and crop management. Wheat was sown under full irrigation and fertilization with two planting dates. Simulations include three DSSAT-Wheat models (CERES, NWHEAT and CROPSIM).
Published: 23 April 2020
Open Data Journal for Agricultural Research, Volume 6, pp 14-18; https://doi.org/10.18174/odjar.v6i0.16322
Agroecological studies on sugarcane dealing with genotype by environment by management interactions commonly generate complex datasets. To facilitate the use of these datasets, a relational database, named ECOFI, was designed from the analysis of the content and the structure datasets of multidisciplinary experiments with sugarcane and energy cane. The database described in this paper includes data from 58 trials carried out in 11 countries from 1986 to 2016, including 24 trials in Reunion Islands and 15 in Guadeloupe. Taking into account plots within the trials and crop cycle, it includes 725 crop cycles in total, with 60 different cultivars. The datasets contain data for crop observations (e.g. dry mass), soil (water contents), weather (all essential meteorological parameters) and management (sowing, cultivars and harvest). Additionally the datasets contain metadata to qualify observations. This dataset provides an adequate experimental set to calibrate or validate crop model simulations under genotype x environment interaction.
Published: 22 April 2020
Open Data Journal for Agricultural Research, Volume 6, pp 1-7; https://doi.org/10.18174/odjar.v6i0.16317
To explore the diurnal variations, radiometric and geometric accuracy of UAV-based data for precision agriculture, a comprehensive dataset was created in a one-day field campaign (21 June 2017). The multi-sensor data set covers wheat, barley & potato experimental fields, located in Wageningen University and Research (WUR) farm maintained by Unifarm. UAV-based images were collected with several sensors over the experimental area, starting from 7:25am and ending at 20:00pm local solar time. The dataset consists of images collected by 9 flights with senseFly MSP4C, 9 with Parrot Sequoia, 2 with Slant Range P3, 5 with DJI Zenmuse X3 NIR, 4 with the senseFly Thermo-map and 1 with the RGB Sony WX-220. Additionally, validation measurements at radiometric calibration plates and plant sample locations were taken with a Cropscan handheld spectrometer and a tec5 Handyspec spectrometer. The dataset consists of the validation measurements, the raw images and the processed orthomosaics (both with and without geometric correction).
Published: 21 April 2020
Open Data Journal for Agricultural Research, Volume 5, pp 16-21; https://doi.org/10.18174/odjar.v5i0.16228
Field data from six experiments covering a wide range of growing conditions were organized for tef growth and cropping systems modeling. The data included (i) an irrigation experiment in the Tigray region of Ethiopia, (ii) a cultivar trial at Fallon, NV, USA, (iii) a nitrogen fertilizer experiment in the Jamma District of Ethiopia, (iv) a nitrogen fertilizer experiment in the Ofla District of Ethiopia, (v) a nitrogen fertilizer experiment in the Ada area of Ethiopia, and (vi) a nitrogen fertilizer experiment at Gare Arera, Ethiopia. The combined data set covered 40 experimental treatments and 131 observations. Time series data were limited to biomass data from two treatments from the Tigray region experiment. All other crop related data was measured at maturity. Daily weather data was taken primarily from satellite weather databases for Ethiopia, and from weather stations in the USA. These data have been used in various agronomic studies, as well as the calibration of the DSSAT Tef model. The results of this model calibration are also included in this paper. The objective of this paper was to present and preserve all of the field data used for calibrating the DSSAT Tef model, as well as the tef model’s simulations of the field data.
Published: 3 June 2019
Open Data Journal for Agricultural Research, Volume 5, pp 11-15; https://doi.org/10.18174/odjar.v5i0.16225
Sugar beet was grown within a crop rotation over two rotation cycles (2001, 2004) at ambient and elevated atmospheric CO2 concentration (375 and 550 ppm) with practical (126, 156 kg N ha-1) and low levels (63, 78 kg N ha-1) of nitrogen supply. In the second year another cultivar was used to prevent infestation by rhizomania, which occured on one half of the field plots at the end of the season of 2001. In 2004, shading was included as an additional treatment. The objectives were to investigate the growth response of sugar beet to elevated CO2 concentration at high and low nitrogen availability. Data set includes data on management, soil condition, weather, below and above ground growth (individual leaves, leaf area index, total biomass, beet yield and composition, water soluble carbohydrates, root biomass).