Abstract
The availability of big data in agriculture, enhanced by free remote sensing data and on-board sensor-based data, provides an opportunity to understand within-field and year-to-year variability and promote precision farming practices for site-specific management. This paper explores the performance in durum wheat yield estimation using different technologies and data processing methods. A state-of-the-art data cleaning technique has been applied to data from a yield monitoring system, giving a good agreement between yield monitoring data and hand sampled data. The potential use of Sentinel-2 and Landsat-8 images in precision agriculture for within-field production variability is then assessed, and the optimal time for remote sensing to relate to durum wheat yield is also explored. Comparison of the Normalized Difference Vegetation Index(NDVI) with yield monitoring data reveals significant and highly positive linear relationships (r ranging from 0.54 to 0.74) explaining most within-field variability for all the images acquired between March and April. Remote sensing data analyzed with these methods could be used to assess durum wheat yield and above all to depict spatial variability in order to adopt site-specific management and improve productivity, save time and provide a potential alternative to traditional farming practices.
Highlights
Durum wheat (Triticum durum, Desf.), it represents only 8% of global wheat production, is one of the most common cereal crops in the Mediterranean basin, traditionally grown under rainfed conditions using conventional tillage [1,2,3]
This paper explores the performance in durum wheat yield estimation using different technologies and data processing methods
Comparison of the Normalized Difference Vegetation Index(NDVI) with yield monitoring data reveals significant and highly positive linear relationships (r ranging from 0.54 to 0.74) explaining most within-field variability for all the images acquired between March and April
Summary
Durum wheat (Triticum durum, Desf.), it represents only 8% of global wheat production, is one of the most common cereal crops in the Mediterranean basin, traditionally grown under rainfed conditions using conventional tillage [1,2,3]. Price volatility and socio-economic factors are the main sources of uncertainty and concern for farmers in durum wheat cultivation [4,5]. For climate variability, it was shown how, in rainfed conditions, these affected both the quality and quantity of durum wheat production [6]. Precision agriculture (PA) has been used for ≥25 years to optimize the use of farm inputs such as fertilizers and herbicides [8,9], and maximize profit and minimize negative environmental impacts [10] by addressing spatial variability
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