Ground-level, hyperspectral and thermal remote data from wheat genotypes grow under various combinations of water and nitrogen availability

Description

In this data we provide different agronomic variables and sensor readings (reflectance spectra and canopy temperature) from an agricultural crop rotation under Mediterranean conditions. The data were obtained in Central Spain after collecting plant samples in a field experiment during two growing seasons: 2018-2020 and 2019-2021. These variables represent the crop response of two wheat (Triticum aestivum L.) genotypes to different precedent crops (legume versus non-legume), nitrogen fertilization and water levels, as well as the readings of leaf-clip and proximal sensors in different growth stages. + Value of the data: Data relating agronomic and sensor information from different wheat genotypes under nitrogen and water interactions will be useful for understanding crop performance and optimizing irrigation and nitrogen fertilization. The present dataset could help researchers and farmers to identify suitable genotypes and their responses to nitrogen and water stress. + Detailed description: The file ‘Grain yield, GNC and N output of wheat.xlsx’ contains the specific year in which each sample was taken is indicated in the database, the dry biomass (kg ha-1), carbon and nitrogen concentration (% C and %N), C/N ratio and N uptake (kg N ha-1) measured in wheat at flowering in the different treatments every year (Wheat Biomass.xlsx). In addition, the dataset contains the wheat grain yield (kg ha-1), % C, % N, C/N ratio and N output (kg N ha-1) at harvest in the two years were recorded. The files ‘Dualex readings.xlsx’ and ‘Greeseeker readings.xlsx’ contains the chlorophyll (Chl), flavonoid (Flav), anthocyanin (Anth) content and the nitrogen balance index (NBI, calculated as the ratio Chl/Flav) measured with the leaf-clip sensor Dualex®, and the normalized difference vegetation index (NDVI) taken with the proximal sensor GreenSeeker® at three different growth stages (GS) for all genotypes and treatments. The file ‘Reflectance of wheat.xlsx’ contains the hyperspectral wheat reflectance measured at five GS in all treatments. The file ‘Thermal data of wheat.xlsx’ contains the canopy temperature acquired at three GS in all treatments. Additionally, dry and wet bare soil temperature was measured as well as the air temperature. Suplementary material for the article is also available as a pdf file. These data are associated with the following article, please cite this article if data are used. Raya-Sereno, M. D., Camino, C., Pancorbo, J. L., Alonso-Ayuso, M., Gabriel, J. L., Beck, P. S. A., & Quemada, M. 2024. Assessing wheat genotype response under combined nitrogen and water stress scenarios coupling high-resolution optical and thermal sensors with radiative transfer models. European Journal of Agronomy, 154, 127102. https://doi.org/10.1016/j.eja.2024.127102

Steps to reproduce

A wheat sample (0.0625 m2) was hand-harvested in the plots at flowering to determine aboveground biomass and N concentration. At harvest, the central fringe from each plot was harvested with an experimental combine to record grain yield. The N concentration of wheat components (spikes and the rest of the biomass) and grain was determined by the combustion method in a subsample from each plot. The NNI was determined as the ratio between the actual crop N concentration and the critical N concentration for a given biomass (i.e. the N concentration that enables maximum growth). The chlorophyll (Chl), flavonoid (Flav), anthocyanin (Anth) content and the nitrogen balance index (NBI = Chl/Flav) were measured with the leaf-clip sensor Dualex®, and the normalized difference vegetation index (NDVI) was taken with the proximal sensor GreenSeeker® at different growth stages for all genotypes and treatments. The representative value of each plot was the averaged of the six measurements taken. The hyperspectral wheat reflectance was measured in all treatments with a field spectroradiometer (HR-512i, Spectra Vista Corporation, New York, USA). Six nadir-oriented spectra were acquired for each plot around noon in a sunny day, and the reflectance spectra per plot was calculated as the average. The field of view was 25°, and after resampling the spectral resolution over the 340- to 1075-nm range was 1 nm. Standardization and optimization of the readings was based on intercalated measurements from a reference panel. The temperature of the canopy and ground surface was acquired with thermal sensor (FLIR SC305, FLIR Systems, Oregon, USA) in all plots. The sensor has a pixel resolution of 320 × 240, a field of view of 25° × 18.8°, and accuracy of ±2 °C of accuracy, and a thermal sensitivity <0.05 °C at 30°C. A single nadir-oriented image was collected from each plot with the thermal sensor, and from the borders to obtain dry and wet bare soil temperature. The surface temperature of each plot was calculated as the average of the pixels in the center of the acquired image. Throughout the sampling period, air temperature and relative humidity were monitored.

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