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Spectral normalized indices related with forage quality in temperate grasses: scaling up from leaves to canopies.
- Source :
-
International Journal of Remote Sensing . 2018, Vol. 39 Issue 10, p3138-3163. 26p. - Publication Year :
- 2018
-
Abstract
- Forage quality is an important regulator of livestock performance also determining the grazing capacity in grasslands and pastures. The objective of this work was to develop spectral normalized indices to accurately predict canopy nitrogen (N), neutral detergent fibre (NDF), and acid detergent fibre (ADF) concentrations and in vitro dry matter digestibility (IVDMD) in three forage species, at two phenological stages and under two fertilization conditions. To select indices with the highest possible independence from canopy structure, we prioritized the selection of indices that were stable at both leaf and canopy scales and evaluated if the best selected indices were correlated with selected leaf and canopy structural traits and leaf water content. All possible normalized indices, based on the reflectance and the first difference reflectance, for the 400–2400 nm spectral range were related through simple regression models with N, NDF, and ADF concentrations and IVDMD. The index that combined the first difference reflectance in the 685 and 1770 nm wavelengths was found to be a potentially useful index to predict canopy N concentration under different field conditions. The best indices selected to predict canopy NDF and ADF concentration and IVDMD, based on the reflectance around 2120–2145 and 2250–2260 nm, had limited application and appeared to be suitable only to identify gross differences in fibre and IVDMD. Future studies should analyse how the best selected indices behave under field lighting conditions and for a wide range of species, phenological stages, and variations in canopy structural traits. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01431161
- Volume :
- 39
- Issue :
- 10
- Database :
- Academic Search Index
- Journal :
- International Journal of Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 143425890
- Full Text :
- https://doi.org/10.1080/01431161.2018.1430394