G.W.A.M. van der Heijden

SPECTRAL IMAGE ANALYSIS FOR MEASURING RIPENESS OF TOMATOES

The present invention provides transport apparatus for transporting and articulating an article into and out of a housing having limited access, and includes a lifting beam having a curved shape to which is attached a lifting assembly. A hoist device is connected to the lifting assembly for raising and lowering the entire transport apparatus and also includes a worm-drive assembly for moving the lifting assembly relative to the lifting beam to thereby articulate an article about a first axis. In addition, one end of the lifting beam includes a rotational mechanism which is connected to a second worm-drive assembly. Operation of the second worm-drive assembly allows the article to be rotated relative to the lifting beam which allows the article to be rotated relative to a second axis. The combined operations of hoisting and movement about the two axes allows the article to be articulated in any direction for insertion or removal from a housing having limited access.

SPICY: towards automated phenotyping of large pepper plants in the greenhouse

Most high-throughput systems for automated plant phenotyping involve a fixed recording cabinet to which plants are transported. However, important greenhouse plants like pepper are too tall to be transported. In this research we developed a system to automatically measure plant characteristics of tall pepper plants in the greenhouse. With a device equipped with multiple cameras, images of plants are recorded at a 5cm interval over a height of 3m. Two types of features are extracted: (1) features from a 3D reconstruction of the plant canopy; and (2) statistical features derived directly from RGB images. The experiment comprised 151 genotypes of a recombinant inbred population of pepper, to examine the heritability and quantitative trait loci (QTL) of the features. Features extracted from the 3D reconstruction of the canopy were leaf size and leaf angle, with heritabilities of 0.70 and 0.56 respectively. Three QTL were found for leaf size, and one for leaf angle. From the statistical features, plant height showed a good correlation (0.93) with manual measurements, and QTL were in accordance with QTL of manual measurements. For total leaf area, the heritability was 0.55, and two of the three QTL found by manual measurement were found by image analysis.

Tomato sorting using independent component analysis on spectral images

Independent Component Analysis is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the most important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components were found. These components resemble the actual absorption spectra of lycopene and chlorophyll. Concentration images of these compounds show increase of one compound and decrease of the other during ripening. The method can be implemented in an unsupervised real time sorting machine, using the total compound concentrations and the spatial distribution of the concentrations as criteria.

A model for probabilistic health impact assessment of exposure to food chemicals.

A statistical model is presented extending the integrated probabilistic risk assessment (IPRA) model of van der Voet and Slob [van der Voet, H., Slob, W., 2007. Integration of probabilistic exposure assessment and probabilistic hazard characterisation. Risk Analysis, 27, 351-371]. The aim is to characterise the health impact due to one or more chemicals present in food causing one or more health effects. For chemicals with hardly any measurable safety problems we propose health impact characterisation by margins of exposure. In this probabilistic model not one margin of exposure is calculated, but rather a distribution of individual margins of exposure (IMoE) which allows quantifying the health impact for small parts of the population. A simple bar chart is proposed to represent the IMoE distribution and a lower bound (IMoEL) quantifies uncertainties in this distribution. It is described how IMoE distributions can be combined for dose-additive compounds and for different health effects. Health impact assessment critically depends on a subjective valuation of the health impact of a given health effect, and possibilities to implement this health impact valuation step are discussed. Examples show the possibilities of health impact characterisation and of integrating IMoE distributions. The paper also includes new proposals for modelling variable and uncertain factors describing food processing effects and intraspecies variation in sensitivity.

Assessing the sustainability of egg production systems in The Netherlands

Housing systems for laying hens have changed over the years due to increased public concern regarding animal welfare. In terms of sustainability, animal welfare is just one aspect that needs to be considered. Social aspects as well as environmental and economic factors need to be included as well. In this study, we assessed the sustainability of enriched cage, barn, free-range, and organic egg production systems following a predefined protocol. Indicators were selected within the social, environmental, and economic dimensions, after which parameter values and sustainability limits were set for the core indicators in order to quantify sustainability. Uncertainty in the parameter values as well as assigned weights and compensabilities of the indicators influenced the outcome of the sustainability assessment. Using equal weights for the indicators showed that, for the Dutch situation, enriched cage egg production was most sustainable, having the highest score on the environmental dimension, whereas free-range egg production gave the highest score in the social dimension (covering food safety, animal welfare, and human welfare). In the economic dimension both enriched cage egg and organic egg production had the highest sustainability score. When weights were attributed according to stakeholder outputs, individual differences were seen, but the overall scores were comparable to the sustainability scores based on equal weights. The provided method enabled a quantification of sustainability using input from stakeholders to include societal preferences in the overall assessment. Allowing for different weights and compensabilities helps policymakers in communicating with stakeholders involved and provides a weighted decision regarding future housing systems for laying hens.

Measuring onion cultivars with image analysis using inflection points

SummaryThe suitability of image analysis was studied to measure bulb characteristics for varietal testing of onions (Allium cepa L.). Eighteen genotypes were used, which covered a whole range of onion shapes, including some quite identical ones. The characteristic height and diameter were measured both by image analysis and by hand. The methods gave comparable results with regard to precision and discriminating power. The discriminating power of the image analysis method could be increased by adding a new characteristic: the relative position of the diameter.For determining the height of the bulb with image analysis two methods are described to locate the top of a bulb. One method is to use the location of the inflection point as the top of the bulb. For most bulb shapes, this point coincides with the top of the bulb as indicated by a crop expert. For ovate shaped onions, however, the inflection point is below the top of the bulb as indicated by the crop expert. The other method is to use the location of the intercept of the tangent at the inflection point with the length axis of the bulb as the top of the bulb. This point is always above the top as indicated by the crop expert. Moreover it seems to perform slightly worse for the discrimination of cultivars. Therefore the location of the inflection point as the top of the bulb is preferred.

Measuring Ripening of Tomatoes Using Imaging Spectrometry

Publisher Summary Ripening of tomatoes is a combination of processes including the breakdown of chlorophyll and build-up of carotenes. Chlorophyll and carotenes have specific, well-known reflection spectra. Using knowledge of the known spectral properties of the main constituent compounds, it may be possible to calculate their concentrations using spectral measurements. Currently image analysis and spectroscopy are used in real-time food-sorting machines. For image analysis, mostly gray value or RGB color cameras are used. Spectroscopy is most often implemented using a point sensor, which accumulates the reflection, transmission, or absorption of light on the whole object. The combination of both techniques in the form of hyperspectral imaging makes it possible to measure the spatial relationship of quality-related biochemicals, which can improve the sorting process. Spectral data reduction makes it possible to select wavelength bands with maximum discriminating power. These wavelength bands can be implemented in a multiband camera with custom filters. These cameras do not significantly differ from RGB cameras in speed, and practical implementation in real-time sorting machines is currently feasible. However, the optimal set of wavelength bands can change in time because of changes in fruit variety, environmental conditions, or simply aging of the illumination. When that occurs, adaption of the camera filters will be difficult and expensive. Taking all these developments into account, real-time food-sorting machines based on these techniques can be expected in the near future.

Calibrating spectral images using penalized likelihood

A new method is presented for automatic correction of distortions and for spectral calibration (which band corresponds to which wavelength) of spectral images recorded by means of a spectrograph. The method consists of recording a bar-like pattern with an illumination source with spectral bands (e.g. neon or mercury). Using prior information of the wavelength of these spectral bands and the spatial arrangement of the bars, a template image is constructed where the spectral axis is linearly related with wavelength. Next, a grid is posed on both the recorded and template image. Using a penalized likelihood method in a quasi-Newton iterative optimization technique, points of the grid on the recorded image are shifted such that the transformed (warped) image has a high resemblance (likelihood) to the template image and a low distortion (penalty term). The method is fully automatic and does not require any landmark extraction. After the transformation grid has been established, every new recorded image can be corrected in real time for any spectral and spatial distortion using fast bilinear interpolation. Recalibration of the system can be done reasonably fast using a previously calculated grid.

Alignment and sub-pixel interpolation of images using Fourier methods

A method is proposed for both estimating and correcting a translational mis-alignment between digital images, taking account of aliasing of high-frequency information. A parametric model is proposed for the power- and cross-spectra of the multivariate stochastic process that is assumed to have generated a continuous-space version of the images. Parameters, including those that specify misalignment, are estimated by numerical maximum likelihood. The effectiveness of the interpolant is confirmed by simulation and illustrated using multi-band Landsat images.

Automated estimation of leaf area development in sweet pepper plants from image analysis

High-throughput automated plant phenotyping has recently received a lot of attention. Leaf area is an important characteristic in understanding plant performance, but time-consuming and destructive to measure accurately. In this research, we describe a method to use a histogram of image intensities to automatically measure plant leaf area of tall pepper (Capsicum annuum L.) plants in the greenhouse. With a device equipped with several cameras, images of plants were recorded at 5-cm intervals over a height of 3m, at a recording distance of less than 60cm. The images were reduced to a small set of principal components that defined the design matrix in a regression model for predicting manually measured leaf area as obtained from destructive harvesting. These regression calibrations were performed for six different developmental times. In addition, development of leaf area was investigated by fitting linear relations between predicted leaf area and time, with special attention given to the genotype by time interaction and its genetic basis in the form of quantitative trait loci (QTLs). The experiment comprised parents, F1 progeny and eight genotypes of a recombinant inbred population of pepper. Although the current trial contained a limited number of genotypes, an earlier identified QTL related to leaf area growth could be confirmed. Therefore, image analysis, as presented in this paper, provides a powerful and efficient way to study and identify the genetic basis of growth and developmental processes in plants.