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The tulip breaking virus (TBV) causes severe economic losses for countries that export tulips such as the Netherlands. Infected plants have to be removed from the field as soon as possible. There is an urgent need for a rapid and objective method of screening. In this study, four proximal optical sensing techniques for the detection of TBV in tulip plants were evaluated and compared with a visual assessment by crop experts as well as with an ELISA (enzyme immunoassay) analysis of the same plants. The optical sensor techniques used were an RGB color camera, a spectrophotometer measuring from 350 to 2500 nm, a spectral imaging camera covering a spectral range from 400 to 900 nm and a chlorophyll fluorescence imaging system that measures the photosynthetic activity. Linear discriminant classification was used to compare the results of these optical techniques and the visual assessment with the ELISA score. The spectral imaging system was the best optical technique and its error was only slightly larger than the visual assessment error. The experimental results appear to be promising, and they have led to further research to develop an autonomous robot for the detection and removal of diseased tulip plants in the open field. The application of this robot system will reduce the amount of insecticides and the considerable pressure on labor for selecting diseased plants by the crop expert. [ABSTRACT FROM AUTHOR]

For crop management, information on the actual status of the crop is important for taking decisions on nitrogen supply, water supply or harvesting. One would also like to take into account the local spatial variation of the crop. Remote sensing has proved to be a useful technique for estimating and mapping the spatial variation of various biophysical variables. Calibration of the image data is crucial in the performance and applicability of this technique. The aim of this paper is to show the possibility to calibrate remotely sensed imagery using fast and non-destructive close-range (below 1.3 m height) sensing instruments, thus providing a means for the assessment of plant characteristics over large areas at low costs. This concept was tested on a homogeneously managed grassland field, subdivided into 20 plots of 15×3 m, at the end of July 2004. Reflected radiation was recorded with an active close-range sensing device, consisting of a visible light and near-infrared (NIR) imaging spectrograph, and a 3CCD camera, equipped with special band filters (central wavelengths are at 600, 710 and 800 nm). An airborne campaign with a four-band UltraCam digital CCD camera was used for extrapolation to larger scales. Plots were harvested, and fresh and dry biomass and leaf nitrogen content were determined. Partial least squares (PLS) models combining spectral and spatial information from the close-sensing device yielded acceptable results in predicting grassland yields and nitrogen content. Subsequently, these predictions were used to calibrate a model with the image data of the remote sensing device. These were then compared, using leave-one-out cross-validation, with the measured field variables, and the model proved to have an acceptable predictive power. [ABSTRACT FROM AUTHOR]

Rumex obtusifolius is a common grassland weed that is hard to control in a non-chemical way. The objective of our research was to automate the detection of R. obtusifolius as a step towards fully automated mechanical control of the weed. We have developed a vision-based system that uses textural analysis to detect R. obtusifolius against a grass background. Image sections are classified as grass or weed using 2-D Fourier analysis. We conducted two experiments. In the first (laboratory) experiment, we collected 28 images containing R. obtusifolius and 28 images containing only grass. Between 23 and 25 of 28 images were correctly classified (82–89%) as showing R. obtusifolius; all grass images were correctly classified as such. In the second (field) experiment, a self-propelled platform was used to obtain five sequences of images of R. obtusifolius plants. We used the parameters that gave the best classification results in the first experiment. We found, after changing one of the algorithm’s parameters in response to prevailing light conditions, that we were able to detect R. obtusifolius in each image of each sequence. The algorithm scans a ground area of 1.5 m2 in 30 ms. We conclude that the algorithm developed is sufficiently fast and robust to eventually serve as a basis for a practical robot to detect and control R. obtusifolius in grassland. [ABSTRACT FROM AUTHOR]

The combination of increasing ethnic diversity in North America and growing consumer support for local food products may present opportunities for local producers and processors in the ethnic foods product category. Our study examined the ethnic Chinese (pop. 402,000) market for salted and preserved duck eggs in Vancouver, British Columbia (BC), Canada. The objective of the study was to develop a segmentation model using survey data to categorize consumer groups based on their attitudes and the importance they placed on product attributes. We further used post-segmentation acculturation score, demographics and buyer behaviors to define these groups. Data were gathered via a survey of randomly selected Vancouver households with Chinese surnames (n = 410), targeting the adult responsible for grocery shopping. Results from principal component analysis and a 2-step cluster analysis suggest the existence of 4 market segments, described as Enthusiasts, Potentialists, Pragmatists, Health Skeptics (salted duck eggs), and Neutralists (preserved duck eggs). Kruskal Wallis tests and post hoc Mann-Whitney tests found significant differences between segments in terms of attitudes and the importance placed on product characteristics. Health Skeptics, preserved egg Potentialists, and Pragmatists of both egg products were significantly biased against Chinese imports compared to others. Except for Enthusiasts, segments disagreed that eggs are 'Healthy Products'. Preserved egg Enthusiasts had a significantly lower acculturation score (AS) compared to all others, while salted egg Enthusiasts had a lower AS compared to Health Skeptics. All segments rated "produced in BC, not mainland China" products in the "neutral to very likely" range for increasing their satisfaction with the eggs. Results also indicate that buyers of each egg type are willing to pay an average premium of at least 10% more for BC produced products versus imports, with all other characteristics equal. Overall results indicate that opportunities exist for local producers and processors: Chinese Canadians with lower AS form a core part of the potential market. [ABSTRACT FROM AUTHOR]