Within-Field Relationships between Satellite-Derived Vegetation Indices, Grain Yield and Spike Number of Winter Wheat and Triticale

Ewa Panek,Michał Stępień,Dominik Ruciński,Dariusz Gozdowski,Bartosz Buszke,Stanisław Samborski

doi:10.3390/agronomy10111842

Ewa Panek, Michał Stępień + Show 4 more

Open Access

https://doi.org/10.3390/agronomy10111842

Copy DOI

Abstract

The aims of this study were to: (i) evaluate the relationships between vegetation indices (VIs) derived from Sentinel-2 imagery and grain yield (GY) and the number of spikes per square meter (SN) of winter wheat and triticale; (ii) determine the dates and plant growth stages when the above relationships were the strongest at individual field scale, thus allowing for accurate yield prediction. Observations of GY and SN were performed at harvest on six fields (three locations in two seasons: 2017 and 2018) in three regions of Poland, i.e., northeastern (A—Brożówka), central (B—Zdziechów) and southeastern Poland (C—Kryłów). Vegetation indices (Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), modified SAVI (mSAVI), modified SAVI 2 (mSAVI2), Infrared Percentage Vegetation Index (IPVI), Global Environmental Monitoring Index (GEMI), and Ratio Vegetation Index (RVI)) calculated for sampling points from mid-March until mid-July, covering within-field soil and topographical variability, were included in the analysis. Depending on the location, the highest correlation coefficients (of about 0.6–0.9) for most of VIs with GY and SN were obtained about 4–6 weeks before harvest (from the beginning of shooting to milk maturity). Therefore, satellite-derived VIs are useful for the prediction of within-field cereal GY as well as SN variability. Information on GY, predicted together with the results for soil nutrient availability, is the basis for the formulation of variable fertilize rates in precision agriculture. All examined VIs were similarly correlated with GY and SN via the commonly used NDVI. The increase in NDVI by 0.1 unit was related to an average increase in GY by about 2 t ha−1.

Highlights

Satellite remote sensing (RS) helps in the mapping of current crop status and the assessment of biophysical parameters
Various vegetation indices (SAVI, MSAVI, NDVI, MSAVI2, Infrared Percentage Vegetation Index (IPVI), Ratio Vegetation Index (RVI) and Global Environmental Monitoring Index (GEMI)), their calculation based on the red and near-infrared radiation derived from the Sentinel−2 imagery, showed similar relationships with grain yield and number of spikes per square meter of winter wheat and triticale as the commonly used NDVI
While comparing the grain yield and the number of spikes from NDVI for all three locations during two seasons, it can be seen that the values of R2 for the number of spikes per square meter are lower than the values of R2 for the grain yield

Summary

Introduction

Satellite remote sensing (RS) helps in the mapping of current crop status and the assessment of biophysical parameters. RS data are publicly accessible due to the availability of an unprecedented amount of Free Sentinel data from the Copernicus Program, established by the European. Constellations of the Sentinel-2 satellites (2A and 2B) can be used for precision farming applications [2]. Agronomy 2020, 10, 1842 status using vegetation indices (VIs). For the purpose of such an evaluation, satellite Sentinel-2 images of two radiation bands, red (650–680 nm) and NIR (785–900 nm), are usually used [2]. Many research results on yield evaluation based on data from the Sentinel-2 satellites [3,4,5,6,7,8]

Objectives

Methods

Results

Discussion

Conclusion