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Temporal N Status Evaluation Using Hyperspectral Vegetation Indices in a Potato Crop
1
A. Cambouris,
1
K. Chokmani,
1
T. Morier
1. Agriculture and Agri-Food Canada Pedology and Precision Agriculture Laboratories
2. Institut national de la recherche scientifique Centre Eau Terre Environnement
The amount and timing of nitrogen (N) fertilization represents a leading issue in precision agriculture, especially for potato (
Solanum tuberosum
L.) crop since N is an essential element for plant growth and tuber yield. Therefore, the ability to assess in-season crop N status from non-destructive methods such as proximal sensing is a promising alternative to optimize N fertilization management and uptake efficiency, as well as minimize environmental losses. The objective of this study was to evaluate the sensitivity of selected vegetation indices (VI) to reveal N status/stress of a Russet Burbank potato crop throughout the 2011 growing season in Quebec, Canada. Four N fertilization rates (i.e. 60, 120, 200 and 280 kg N ha
-1
; N source: ammonium sulfate applied 40% at-planting and 60% at-hilling) plus an unfertilized control were considered. Crop biomass was sampled biweekly from 40 to 84 days after planting (DAP) for the determination of Nitrogen Nutrition Index (NNI) as the reference for N stress. Moreover, foliar N content analyses were performed on different dates during the growing season. Weekly hyperspectral reflectance data derived from a portative spectroradiometer (ASD FieldSpec HandHeld) was used to compute three different VI: Normalized Difference Vegetation Index (NDVI), Red Edge (RE) 740/720 index and Modified Chlorophyll Absorption Reflectance Index (MCARI). Primary results revealed a high correlation (r
2
=0.74) at 66 DAP between RE and foliar N content in addition to significant correlations starting at 50 DAP. Further analyses are conducted to assess other VI corrected for soil effect in order to select the most correlated indices to NNI values.
Keyword
: Nitrogen fertilization, proximal sensing, hyperspectral reflectance.
A. Cambouris
K. Chokmani
T. Morier
Proximal Sensing in Precision Agriculture
Poster
2012
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