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United States Department of Agriculture

Agricultural Research Service

Research Project: Hyperspectral and Multispectral Image Analyses of Potatoes under Different Nutrient Management with Center Pivot Irrigation

Location: Vegetable and Forage Crops Production Research

Project Number: 5354-21660-003-01
Project Type: Specific Cooperative Agreement

Start Date: May 18, 2010
End Date: May 17, 2015

Objective:
Non-destructive estimation of nutritional status of potato canopy using multispectral imaging and prediction of tuber yield and quality response to variable nutrient management under pivot irrigation.

Approach:
Spectral characteristics of vegetation are a quantitative measure and can offer a non-destructive method to assess crop nutrition; biomass production; and, in turn, yield and quality of crop products. This type of sensing technology has been successfully developed for detecting nitrogen stress in agronomic crops, such as corn and rice. This technology can be modified for its application to potato production under center pivot irrigation. In this research, the following steps will be used to investigate the feasibility of developing a multispectral imaging based sensing system for estimation of nutritional status of potato canopy under variable nutrient management programs and, in turn, predict biomass production, tuber yields and tuber quality parameters. Furthermore, multispectral image sensing can be an efficient tool of non-destructive evaluation of potential non-uniformity in water distribution through sprinklers in center pivot irrigation system. 1. Collect multispectral images of potato canopy grown under different nutrient management programs; 2. Analyze the spectral characteristics of the canopy and search for a trend of such characteristic change with the corresponding nutrient management programs; 3. Analyze relationships between the spectral information carried in multispectral images and nutritional status of the plants monitored based on the petiole analyses and destructive plant sampling; and 4. Define a calibration equation for quantitatively estimating the level of nutritional statuses based on multispectral images.

Last Modified: 8/30/2014
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