אסיף מאגר המחקר החקלאי

The use of VIS-NIR and thermal ranges for evaluating nitrogen and water status in potato plants

Year:

2011

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Co-Authors:

Cohen, Y., Agricultural Research Organization (A.R.O), Volcani Centre, Institute of Agricultural Engineering, Bet Dagan, Israel
Rud, R., Agricultural Research Organization (A.R.O), Volcani Centre, Institute of Agricultural Engineering, Bet Dagan, Israel
Rosen, C., Department of Soil,Water, and Climate, University of Minnesota, 1991 Upper Buford Circle St., Paul, MN, United States
Mulla, D., Department of Soil,Water, and Climate, University of Minnesota, 1991 Upper Buford Circle St., Paul, MN, United States
Heuer, B., Agricultural Research Organization (A.R.O), Volcani Centre, Institute of Soil,Water and Environmental Sciences, Bet Dagan, Israel
Dar, Z., The Agricultural Extension Service, Ministry of Agriculture, Bet Dagan, Israel
Levi, O., Department of Industrial Engineering and Management, Ben-Gurion University of Negev, Beer-Sheva, Israel
Cohen, S., Department of Industrial Engineering and Management, Ben-Gurion University of Negev, Beer-Sheva, Israel
Levi, A., Agricultural Research Organization (A.R.O), Volcani Centre, Institute of Agricultural Engineering, Bet Dagan, Israel
Brikman, R., Agricultural Research Organization (A.R.O), Volcani Centre, Institute of Agricultural Engineering, Bet Dagan, Israel
Alchanatis, V., Agricultural Research Organization (A.R.O), Volcani Centre, Institute of Agricultural Engineering, Bet Dagan, Israel

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Abstract:

In an ongoing multi-year study, the potential for using aerial hyperspectral (HS) images combined with aerial thermal images to evaluate and map water and nitrogen (N) status in potato fields was investigated. The paper describes procedures carried out on potato plants to evaluate N concentration based on spectral measurements and aerial HS images in the VISNIR range and water status based on ground thermal images. Field experiments were conducted to create wide ranges in N concentration and water status. The usefulness of partial least squares regression (PLSR) for spectral analysis to predict N concentration at the leaf scale was described. PLSR analysis obtained 1:1 prediction models of leaf-%N and petiole NO3-N (R2 of 0.86 and 0.74 respectively). The multi-dimensional beamlet-decorated recursive-dyadic-partitioning (BD-RDP) was introduced and applied to a 210-band aerial HS image of the experimental plot. The multi-scale segmentation significantly reduced noise in the original image and successfully uncovered spatial structures in the image according to the N treatments. The use of ground thermal images for water status estimation in potato plants was shown to be feasible: Temperature was negatively and strongly correlated with stomatal conductance. To the authors' knowledge, this is the first attempt that HS and thermal images have been used simultaneously for N and water status estimation for potato.

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