1a.Objectives (from AD-416)
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.
1b.Approach (from AD-416)
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. Documents SCA with WSU.
The goal of this project is to "non-destructively estimate the nutritional status of potato canopy using multispectral imaging and predict the tuber yield and quality response to variable nutrient management". A portable multispectral imaging system was used to monitor potato canopy multispectral images during the 2010 growing season. Those images were collected from zones of different nutrient management programs in order to search for a reasonable robust pattern indicating the spectral characteristics of the canopy for different stress level. All collected canopy images were processed first using conventional image analysis technique to compensate for effects of ambient light on canopy reflectance in obtained images,then using a spectral analysis method to detect the spectral characteristic of vegetation. The spectral characteristics, a quantitative measurement commonly used to estimate biomass or vegetation vigor, at different growth stages of potato before maturity for one season, was measured and analyzed. The results of this study showed: (1) spectral characteristics changes under different nutrition treatments; and (2) spectral sensitive features usable for further analysis; The analysis is still inprogress, results obtained so far showed some promise but the one-season data was found insufficient to draw a solid conclusion.
This project contributes to objective 2 in the parent project plan. The project was monitored by phone and email contact with the cooperators.