Abstract
This study compares simplified and advanced precision nitrogen (N) fertilization approaches for winter wheat relying on Sentinel-2 NDVI, grain yield maps, and protein content. Five N fertilization treatments were compared: (1) a standard rate, calculated by a typical N balance (Flat-N); (2) a variable rate calculated using a simplified linear model, adopting a proportional strategy (NDVI directly related) (Var-N-dir); (3) a variable rate calculated using a simplified linear model, adopting a compensative strategy (NDVI inversely related) (Var-N-inv); (4) a variable rate calculated using the AgroSat model (Var-N-Agrosat); and (5) a variable rate calculated applying the Agricolus model (Var-N-Agricolus). The study was carried out in four fields over two cropping seasons with a randomized blocks design. Results indicate that the weather remains the main factor influencing yield, as it typically happens in a rainfed crop. No substantial differences in crop yield were observed among the N fertilization models within each year and experimental location. However, in the more favorable season, the low-input direct model (Var-N-dir) resulted as the best choice, providing the higher NUE (nitrogen use efficiency) value. In the less favorable season, results showed a better performance of the advanced models (Var-N-Agricolus and Var-N-Agrosat), which limited yield losses and reduced intra-field variability, with relevant importance given to the increasing frequency of abnormal climate phenomena. In general, all these VRT approaches allowed reduction of the excess of fertilizers, preservation of the environment, and saving money.
Highlights
IntroductionReducing inputs like irrigation water, fertilizers, pesticides, and herbicides, while increasing the efficiency of their use, represents modern agriculture’s primary challenge in terms of limiting environmental impact [1] and keeping pace with world population growth [2]
Reducing inputs like irrigation water, fertilizers, pesticides, and herbicides, while increasing the efficiency of their use, represents modern agriculture’s primary challenge in terms of limiting environmental impact [1] and keeping pace with world population growth [2]. This can be pursued by applying precision agriculture (PA) approaches [3], which aim at providing the various inputs where they are necessary, at the correct rate and at the right time
The NUE calculated with respect to the grain yield was significantly (p-value < 0.05) higher compared to Flat-N, Var-N-Agrosat, and
Summary
Reducing inputs like irrigation water, fertilizers, pesticides, and herbicides, while increasing the efficiency of their use, represents modern agriculture’s primary challenge in terms of limiting environmental impact [1] and keeping pace with world population growth [2]. This can be pursued by applying precision agriculture (PA) approaches [3], which aim at providing the various inputs where they are necessary, at the correct rate (limiting growth deficiencies, yield loss, surpluses, money loss, and pollution) and at the right time (synchronizing application with crop needs). The Sentinel-2 satellites are equipped with multispectral sensors (MSIs), including 13 spectral bands, with a spatial resolution ranging from 10 m to 60 m.
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