A rapid, non-destructive method for nitrate content assessment is essential for a rational wide-scale application of nitrogen in sustainable growing spinach. The method should be effective in facing environmental, genotype, and management variability. The results from three field experiments carried out in Teramo (Italy), during the 2021 and 2022 growing seasons, and by combining nitrogen supply with spinach genotypes, are presented. The spectral canopy reflectance was collected to find out the spectral band relationship with nitrate concentration. Preliminary PCA and mixed linear model analysis showed that nitrate content is among the less detectable features. Unexpected chlorosis onset in one experiment added more variability; nevertheless, spectral regions of blue-cyan and early NIR when combined into Vegetation Indexes were able to correlate to nitrate content with R-2 up to 0.65 in all experiments. This study demonstrates that focusing on just a few spectral regions facilitates the acquisition of suitable and robust information on nitrate content in spinach.

Nitrate Content Assessment in Spinach: Exploring the Potential of Spectral Reflectance in Open Field Experiments

Stagnari F.
Conceptualization
;
Polilli W.
Methodology
;
Trasmundi F.
Formal Analysis
;
Galieni A.
Conceptualization
2023-01-01

Abstract

A rapid, non-destructive method for nitrate content assessment is essential for a rational wide-scale application of nitrogen in sustainable growing spinach. The method should be effective in facing environmental, genotype, and management variability. The results from three field experiments carried out in Teramo (Italy), during the 2021 and 2022 growing seasons, and by combining nitrogen supply with spinach genotypes, are presented. The spectral canopy reflectance was collected to find out the spectral band relationship with nitrate concentration. Preliminary PCA and mixed linear model analysis showed that nitrate content is among the less detectable features. Unexpected chlorosis onset in one experiment added more variability; nevertheless, spectral regions of blue-cyan and early NIR when combined into Vegetation Indexes were able to correlate to nitrate content with R-2 up to 0.65 in all experiments. This study demonstrates that focusing on just a few spectral regions facilitates the acquisition of suitable and robust information on nitrate content in spinach.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11575/137480
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