Next Article in Journal
Application of Biogas Digestate with Rice Straw Mitigates Nitrate Leaching Potential and Suppresses Root-Knot Nematode (Meloidogyne incognita)
Next Article in Special Issue
Assimilation of Sentinel-2 Leaf Area Index Data into a Physically-Based Crop Growth Model for Yield Estimation
Previous Article in Journal
Agronomic Evaluation of Biochar, Compost and Biochar-Blended Compost across Different Cropping Systems: Perspective from the European Project FERTIPLUS
Previous Article in Special Issue
Towards Predictive Modeling of Sorghum Biomass Yields Using Fraction of Absorbed Photosynthetically Active Radiation Derived from Sentinel-2 Satellite Imagery and Supervised Machine Learning Techniques
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle

Detection of Spatial and Temporal Variability of Wheat Cultivars by High-Resolution Vegetation Indices

Department of Agricultural, Environmental and Food Sciences (DAEFS), University of Molise, Via De Sanctis, 86100 Campobasso, Italy
Author to whom correspondence should be addressed.
Agronomy 2019, 9(5), 226;
Received: 18 March 2019 / Revised: 30 April 2019 / Accepted: 3 May 2019 / Published: 5 May 2019
(This article belongs to the Special Issue Remote Sensing Applications for Agriculture and Crop Modelling)
PDF [2746 KB, uploaded 5 May 2019]


An on-farm research study was carried out on two small-plots cultivated with two cultivars of durum wheat (Odisseo and Ariosto). The paper presents a theoretical approach for investigating frequency vegetation indices (VIs) in different areas of the experimental plot for early detection of agronomic spatial variability. Four flights were carried out with an unmanned aerial vehicle (UAV) to calculate high-resolution normalized difference vegetation index (NDVI) and optimized soil-adjusted vegetation index (OSAVI) images. Ground agronomic data (biomass, leaf area index (LAI), spikes, plant height, and yield) have been linked to the vegetation indices (VIs) at different growth stages. Regression coefficients of all samplings data were highly significant for both the cultivars and VIs at anthesis and tillering stage. At harvest, the whole plot (W) data were analyzed and compared with two sub-areas characterized by high agronomic performance (H) yield 20% higher than the whole plot, and low performances (L), about 20% lower of yield related to the whole plot). The whole plot and two sub-areas were analyzed backward in time comparing the VIs frequency curves. At anthesis, more than 75% of the surface of H sub-areas showed a VIs value higher than the L sub-plot. The differences were evident also at the tillering and seedling stages, when the 75% (third percentile) of VIs H data was over the 50% (second percentile) of the W curve and over the 25% (first percentile) of L sub-plot. The use of high-resolution images for analyzing the frequency value of VIs in different areas can be a useful approach for the detection of agronomic constraints for precision agriculture purposes. View Full-Text
Keywords: UAV; vegetation indices; relative frequencies; yield; precision agriculture; cultivars UAV; vegetation indices; relative frequencies; yield; precision agriculture; cultivars

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Marino, S.; Alvino, A. Detection of Spatial and Temporal Variability of Wheat Cultivars by High-Resolution Vegetation Indices. Agronomy 2019, 9, 226.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Agronomy EISSN 2073-4395 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top