This dataset presents field experimental data collected and used to model the productivity of common buckwheat (Fagopyrum esculentum) under different water regimes and silicon treatments using the Soil Canopy Observation, Photosynthesis, and Energy Fluxes (SCOPE) model. The field experiment was conducted during the 2023growing season, with the growing season extending from May to September 2023 near the village of Zlotniki at Research and Education Centre Gorzyń (52°29.23'N, 16°50.47'E), belonging to Poznan University of Life Sciences, located approximately 5 km northwest of Poznań in Greater Poland voivodeship, Poland. The field experiment involved three buckwheat genotypes, La Harpe, Smuga, and Panda, grown under four treatment conditions combining irrigation and silicon supplementation: irrigated control (IR-C), irrigated with silicon (IR-T), non-irrigated control (NI-C), and non-irrigated with silicon (NI-T). Field measurements included top-of-canopy hyperspectral reflectance, Leaf Area Index (LAI), CO₂ fluxes and grain yield, together with meteorological and soil moisture observations. These experimental data were used within the SCOPE inversion-forward modelling framework to retrieve LAI, simulate Gross Primary Production (GPP), and estimate grain yield. Model outputs were subsequently evaluated against the corresponding field measurements. The experimental field covered approximately 1200 m² and consisted of 36 plots distributed among the three buckwheat genotypes. Irrigated plots received supplemental water during periods without precipitation, whereas non-irrigated plots depended primarily on natural rainfall. Silicon-treated plots received a foliar application of sodium metasilicate nanohydrate (Na2SiO3·9H2O) at a concentration of 500 µM, while control plots were treated with only water at specific irrigation dates.
Throughout the growing season, hyperspectral top-of-canopy reflectance, Leaf Area Index (LAI), CO₂ fluxes, and grain yield were measured. Environmental conditions were continuously monitored using an automated meteorological station, including precipitation, air temperature, relative humidity, photosynthetically active radiation, wind speed, and soil moisture and temperature at multiple depths. Top-of-canopy hyperspectral reflectance measurements were used for SCOPE model inversion to retrieve LAI. The retrieved LAI, together with meteorological and physiological parameters, were subsequently used in forward SCOPE simulations to estimate Gross Primary Production (GPP). Modelled LAI and GPP were validated against field LAI and chamber-based CO₂ flux measurements, respectively. Seasonal carbon accumulation derived from simulated GPP was combined with genotype-specific harvest indices to estimate grain yield, which was subsequently compared with harvested yield.
This research was funded by the National Science Centre of Poland (NCN) project No. 2021/43/I/NZ9/01356 at the Poznań University of Life Sciences.
The dataset includes the following files:
Spectral reflectance contains data recorded using a Piccolo Doppio hyperspectral system, including top-of-canopy hyperspectral reflectance measurements collected across all six campaigns representing developmental stages of buckwheat under different treatment conditions.
Leaf Area Index contains field-measured LAI acquired using the SunScan canopy analysis system (Delta-T Devices, Burwell, UK) and the corresponding SCOPE-retrieved LAI for the three buckwheat genotypes under the above-stated field conditions, used to evaluate and to validate the model performance.
CO₂ Flux_Chamber_interpolated and CO₂ flux and GPP_SCOPE contains chamber-based CO₂ flux measurements acquired using a closed dynamic portable chamber system equipped with an LI-840 CO₂/H₂O gas analyzer (LI-COR, Inc., Nebraska, USA), derived GPP estimates, and the corresponding SCOPE-simulated GPP used for model validation.
Meteo_and_Soil_data contains environmental measurements recorded during the growing season, including precipitation, photosynthetically active radiation (PAR), air temperature, relative humidity, wind speed, and soil moisture and temperature across the soil profile (depths: 5, 15, 25, 35, 45, 55, 65, 75, and 85 cm). Measurements were recorded using a fully automated, solar-powered meteorological station (WS-GP2 system; Delta-T Devices Ltd, England) equipped with a tipping-bucket rain gauge, BF5 PAR sensor, ATMOS-22 ultrasonic anemometer, ATMOS-14 RH/T thermohydrometer with barometer, and SDI-12,00919 soil moisture and temperature probe.
Yield2023 expressed in t/ha, contains harvested achene yield, harvest index, and SCOPE-estimated grain yield for each genotype and treatment.
Measurement_and_Irrigation_Dates this tab-separated file provides the dates of field measurements and irrigation events conducted during the 2023 common buckwheat field experiment. The Event column identifies the activity as either Measurement or Irrigation, and the Date column reports the corresponding date in MM/DD/YYYY format.
SCOPE model parameters contains specific SCOPE model internal input parameters.
This dataset provides an integrated collection of hyperspectral, physiological, meteorological, soil, yield, and process-based modelling data for evaluating common buckwheat responses to water availability and silicon supplementation. It may be valuable for researchers investigating crop remote sensing, radiative transfer modelling, crop productivity, drought responses, and yield prediction in minor and underutilised crops. Refer to ReadMe.
