Abstract
In this study, a modelling approach for the estimation/prediction of wheat yield based on Sentinel-2 data is presented. Model development was accomplished through a two-step process: firstly, the capacity of Sentinel-2 vegetation indices (VIs) to follow plant ecophysiological parameters was established through measurements in a pilot field and secondly, the results of the first step were extended/evaluated in 31 fields, during two growing periods, to increase the applicability range and robustness of the models. Modelling results were examined against yield data collected by a combine harvester equipped with a yield-monitoring system. Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were examined as plant signals and combined with Normalized Difference Water Index (NDWI) and/or Normalized Multiband Drought Index (NMDI) during the growth period or before sowing, as water and soil signals, respectively. The best performing model involved the EVI integral for the 20 April–31 May period as a plant signal and NMDI on 29 April and before sowing as water and soil signals, respectively (R2 = 0.629, RMSE = 538). However, model versions with a single date and maximum seasonal VIs values as a plant signal, performed almost equally well. Since the maximum seasonal VIs values occurred during the last ten days of April, these model versions are suitable for yield prediction.
Highlights
Durum wheat (Triticum turgidum L. var. durum) is a crop used for a variety of food products, mainly pasta
The plant signals obtained from Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) showed a high correlation with the field-measured canopy reflectance
Our results show that the overall best performing model version involves the EVI integral for the 20 April–31 May period as a plant signal and Normalized Multiband Drought Index (NMDI) at 29 April and before sowing as water and soil signals, respectively (R2 = 0.629, RMSE = 538)
Summary
Durum wheat (Triticum turgidum L. var. durum) is a crop used for a variety of food products, mainly pasta. Durum) is a crop used for a variety of food products, mainly pasta. Almost 60% of the world durum wheat cultivated area, about 7.8 million hectares, is located at the Mediterranean basin [1]. Pasta consumption in the Mediterranean countries is higher than the local production, so food industries depend on imports from other durum-wheat-producing territories, mainly North. The variability of the Mediterranean climate, exacerbated by the on-going climate change, causes great year-to-year fluctuations in durum wheat yields. This fact causes risks and uncertainty in the industry, grain marketing agencies, policymakers, and other involved entities, concerning the planning of their exports and imports. Early-season prediction of durum wheat yields is of vital importance for assisting the whole food production chain. Can adjust the farm inputs, such as fertilizers and irrigation, to meet the site-specific needs of the crop by implementing precision agriculture techniques, while the harvesting sector can plan its logistics by managing the harvester fleet and anticipating transport and storage requirements
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