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Robust vegetation segmentation is required for a vision-based weed control robot in an agricultural field operation. The output of vegetation segmentation is a fundamental element in the subsequent process of weed/crop discrimination as well as weed control actuation. Given the abundance of colour indices and thresholding techniques, it is still far from clear how to choose a proper threshold technique in combination with a colour index for vegetation segmentation under agricultural field conditions. In this research, the performance of 40 combinations of eight colour indices and five thresholding techniques found in the literature was assessed to identify which combination works the best given varying field conditions in terms of illumination intensity, shadow presence and plant size. It was also assessed whether it was better to use one specific combination at all times or whether the combination should be adapted to the field conditions at hand. A clear difference in performance, represented in terms of MA (Modified Accuracy) which indicates the harmonic mean of relative vegetation area error and balanced accuracy, was observed among various combinations under the given conditions. On the image dataset that was used in this study, CIVE+Kapur (Colour Index of Vegetation Extraction+Max Entropy threshold) showed the best performance while VEG+Kapur (Vegetative Index+Max Entropy threshold) showed the worst. Adapting the combination to the given conditions yielded a slightly higher performance than when using a single combination for all (in this case CIVE+Kapur). Consistent results were obtained when validated on a different independent image dataset. Although a slightly higher performance was achieved when adapting the combination to the field conditions, this slight improvement seems not to outweigh the potential investment in sensor technology and software that are needed in practice to accurately determine the different conditions in the field. Therefore, the expected advantage of adapting the combination to the field condition is not large.

The IR camera method was able to measure the area of warm puddles.The adaptive threshold enabled automatic selection of a puddle from an IR image.The background temperature had no effect on the estimated puddle area.The IR camera method had a measurement uncertainty of

A vision-based weed control robot for agricultural field application requires robust vegetation segmentation. The output of vegetation segmentation is the fundamental element in the subsequent process of weed and crop discrimination as well as weed control. There are two challenging issues for robust vegetation segmentation under agricultural field conditions: (1) to overcome strongly varying natural illumination; (2) to avoid the influence of shadows under direct sunlight conditions. A way to resolve the issue of varying natural illumination is to use high dynamic range (HDR) camera technology. HDR cameras, however, do not resolve the shadow issue. In many cases, shadows tend to be classified during the segmentation as part of the foreground, i.e., vegetation regions. This study proposes an algorithm for ground shadow detection and removal, which is based on color space conversion and a multilevel threshold, and assesses the advantage of using this algorithm in vegetation segmentation under natural illumination conditions in an agricultural field. Applying shadow removal improved the performance of vegetation segmentation with an average improvement of 20, 4.4, and 13.5% in precision, specificity and modified accuracy, respectively. The average processing time for vegetation segmentation with shadow removal was 0.46 s, which is acceptable for real-time application (

One of the most important steps in vision-based weed detection systems is the classification of weeds growing amongst crops. In the EU SmartBot project it was required to effectively control more than 95% of volunteer potatoes and ensure less than 5% of damage of sugar beet. Classification features such as colour, shape and texture have been used individually or in combination for classification studies but they have proved unable to reach the required classification accuracy under natural and varying daylight conditions. A classification algorithm was developed using a Bag-of-Visual-Words (BoVW) model based on Scale-Invariant Feature Transform (SIFT) or Speeded Up Robust Feature (SURF) features with crop row information in the form of the Out-of-Row Regional Index (ORRI). The highest classification accuracy (96.5% with zero false-negatives) was obtained using SIFT and ORRI with Support Vector Machine (SVM) which is considerably better than previously reported research although its 7% false-positives deviated from the requirements. The average classification time of 0.10–0.11 s met the real-time requirements. The SIFT descriptor showed better classification accuracy than the SURF, but classification time did not vary significantly. Adding location information (ORRI) significantly improved overall classification accuracy. SVM showed better classification performance than random forest and neural network. The proposed approach proved its potential under varying natural light conditions, but implementing a practical system, including vegetation segmentation and weed removal may potentially reduce the overall performance and more research is needed.

Classification of weeds amongst cash crops is a core procedure in automated weed control. Addressing volunteer potato control in sugar beets, in the EU Smartbot project the aim was to control more than 95% of volunteer potatoes and ensure less than 5% of undesired control of sugar beet plants. A promising way to meet these requirements is deep learning. Training an entire network from scratch, however, requires a large dataset and a substantial amount of time. In this situation, transfer learning can be a promising solution. This study first evaluates a transfer learning procedure with three different implementations of AlexNet and then assesses the performance difference amongst the six network architectures: AlexNet, VGG-19, GoogLeNet, ResNet-50, ResNet-101 and Inception-v3. All nets had been pre-trained on the ImageNet Dataset. These nets were used to classify sugar beet and volunteer potato images taken under ambient varying light conditions in agricultural environments. The highest classification accuracy for different implementations of AlexNet was 98.0%, obtained with an AlexNet architecture modified to generate binary output. Comparing different networks, the highest classification accuracy 98.7%, obtained with VGG-19 modified to generate binary output. Transfer learning proved to be effective and showed robust performance with plant images acquired in different periods of the various years on two types of soils. All scenarios and pre-trained networks were feasible for real-time applications (classification time < 0.1 s). Classification is only one step in weed detection, and a complete pipeline for weed detection may potentially reduce the overall performance.

For robotic harvesting of sweet-pepper fruits in greenhouses a sensor system is required to detect and localize the fruits on the plants. Due to the complex structure of the plant, most fruits are (partially) occluded when an image is taken from one viewpoint only. In this research the effect of multiple camera positions and viewing angles on fruit visibility and detectability was investigated. A recording device was built which allowed to place the camera under different azimuth and zenith angles and to move the camera horizontally along the crop row. Fourteen camera positions were chosen and the fruit visibility in the recorded images was manually determined for each position. For images taken from one position only with the criterion of maximum 50% occlusion per fruit, the fruit detectability (FD) was in no case higher than 69%. The best single positions were the front views and looking with a zenith angle of 60° upwards. The FD increased when a combination was made of multiple viewpoint positions. With a combination of five favourite positions the maximum FD was 90%.

This paper describes a model to calculate the concentrations of (Z)-3-hexenol, a-pinene, a-terpinene, ß-caryophyllene, and methyl salicylate in a greenhouse on the basis of their source and sink behaviour. The model was used to determine whether these volatile organic compounds (VOCs) can be used to indicate Botrytis cinerea infection in a large-scale tomato production greenhouse with a volume of 5 × 104 m3 containing 2.2 × 104 plants. Seven experiments were done to parameterise the model for these VOCs. Based on model predictions, the B. cinerea-induced increase in concentration of methyl salicylate is detectable in a large-scale tomato production greenhouse when: (a) windows are fully opened, and (b) the increase continues for at least 1 h, and (c) 5% of the plants are infected. The B. cinerea-induced increase in concentration of methyl salicylate is also detectable when: (a) windows are closed, and (b) the increase continues for at least 6 h, and (c) 5% of the plants are infected. The B. cinerea-induced increase in concentration of (Z)-3-hexenol is detectable under all conditions studied. However, it is expected that besides infected plants, many additional sources of (Z)-3-hexenol exist including plant debris and nearby field crops especially upon harvest or stress. The B. cinerea-induced increases in concentration of a-pinene, a-terpinene and ß-caryophyllene are probably undetectable in a large-scale tomato production greenhouse. Therefore, it is recommended to focus on the detection of methyl salicylate to indicate B. cinerea infections in large-scale tomato production greenhouses.

The objectives of this study were to determine the reflectance properties of volunteer potato and sugar beet and to assess the potential of separating sugar beet and volunteer potato at different fields and in different years, using spectral reflectance characteristics. With the ImspectorMobile, vegetation reflection spectra were successfully repeatedly gathered in two fields, on seven days in 2 years that resulted in 11 datasets. Both in the visible and in the near-infrared reflection region, combinations of wavelengths were responsible for discrimination between sugar beet and volunteer potato plants. Two feature selection methods, discriminant analysis (DA) and neural network (NN), succeeded in selecting sets of discriminative wavebands, both for the range of 450–900 and 900–1650 nm. First, 10 optimal wavebands were selected for each of the 11 available datasets individually. Second, by calculating the discriminative power of each selected waveband, 10 fixed wavebands were selected for all 11 datasets analyses. Third, 3 fixed wavebands were determined for all 11 datasets. These three wavebands were chosen because these had been selected by both DA and NN and were for sensor 1: 450, 765, and 855 nm and for sensor 2: 900, 1440, and 1530 nm. With the resulting three sets of wavebands, classifications were performed with a DA, a neural network with 1 hidden neuron (NN1) and a neural network with two hidden neurons (NN2). The maximum classification performance was obtained with the near-infrared sensor coupled to the NN2 method with an optimal adapted set of 10 wavebands, where the percentages were 100 ± 0.1 and 1 ± 1.3% for true negative (TN) classified volunteer potato plants and false negative (FN) classified sugar beet plants respectively. In general the NN2 method gave the best classification results, followed by DA and finally the NN1 method. When the optimal adapted waveband sets were generalized to a set of 10 fixed wavebands, the classification results were still at a reasonable level of a performance at 87% TN and 1% FN for the NN2 classification method. However, when a further reduction and generalization was made to 3 fixed wavebands, the classification results were poor with a minimum performance of 69% TN and 3% FN for the NN2 classification method. So, these results indicate that for the best classification results it is required that the sensor and classification system adapt to the specific field situation, to optimally discriminate between volunteer potato and sugar beet pixel spectra

Pathogen attack and herbivore infestation have a major impact on plant health. In a model study, these two plant health issues were simulated to study whether plant health can be monitored at greenhouse scale through the analysis of volatile organic compounds (VOCs) in greenhouse atmosphere. To simulate pathogen attack and herbivore infestation, we repeatedly stroked the stems of tomato plants (Lycopersicon esculentum) and repeatedly removed their side shoots. In addition, we studied the effect of fruit picking on the concentration of plant-emitted VOCs in greenhouse atmosphere. Analysis of air samples obtained before these treatments revealed up to 17 VOCs that are known to be released from tomato plants, of which the most dominant one was the monoterpene ß-phellandrene. When plants were 7 weeks old, the concentration of this VOC was approximately 0.06 ppbv before treatment. When plants were 12 weeks old, this concentration was raised to approximately 0.14 ppbv. Stroking of the stems, removing the side shoots and fruit picking resulted in an increase in the concentrations of all mono- and most sesquiterpenes up to 60-fold, which was expected because these VOCs are well-known constituents of trichomes. The treatments did not result in substantially increased concentrations of the stress-related compounds ¿-copaene, methyl salicylate and (E,E)-4,8,12-trimethyl-1,3,7,11-tridecatetraene. In contrast to stroking and fruit picking, shoot removal resulted in the emission of the lipoxygenase-derived product (Z)-3-hexenol in greenhouse atmosphere expressing cell membrane degradation. The findings presented in this paper focus on the feasibility of monitoring plant health through the analysis of VOCs in greenhouse air, but findings might also be relevant for atmospheric chemistry.

This review focuses on the monitoring of crop health status at greenhouse scale, based on the measurement of volatile organic compounds (VOCs) emitted from the plants. The review includes the most important factors that affect the emission of these VOCs from greenhouse crops. Since both, stress factors as well as non-stress factors have an effect on the emission, they are covered separately. The review provides an overview of processes that affect the gas balance of plant VOCs in the greenhouse including the loss processes. These processes are considered as important since they contribute to the time-dynamic concentration profiles of plant-emitted VOCs. In addition, we review the most popular techniques currently in use to measure volatiles emitted from plants with emphasis on greenhouse application. Dynamic sampling in combination with gas chromatography coupled to mass spectrometry is considered as most appropriate method for application at greenhouse scale. It is recommended to evaluate the state-of-the-art in the fields concerned with this method and to explore the development of a new instrument based on the specific needs for application in greenhouse practice. However, to apply such an instrument at greenhouse-scale remains a challenge, mainly due to the high costs associated with it.

International audience; Theoretically, in the absence of friction, when a particle is sliding along a straight radial vane, mounted on a flat disc which is spinning at a constant rotational velocity, its radial and tangential velocity are equal at any point along the vane. In reality, there are disturbances causing a difference between the radial and tangential velocities, such as drop mechanics, mechanical (Coulomb) friction, aerodynamic effects, as well as particle bouncing effects against the vane and other particles. These factors were lumped together and termed the friction coefficient'. The tangential particle velocity at the discharge point was assumed constant, since the particle was assumed in direct contact with the vane until emanation. The radial particle velocity was measured at a distance of 04m from the disc edge with an optical sensor developed in earlier research. A theoretical analysis was used to obtain equations that allowed determination of the mechanical friction coefficient of individual particles, based on the measured radial velocity and the assumed constant tangential velocity. For experiments, a commercial single disc spreader fitted with a flat disc and straight radial vanes was used. The results for urea fertiliser showed a near-Gaussian distribution of the friction coefficients, with a mean value of 036 and a standard deviation of 01 among 812 measurements. In addition, an inversely proportional relationship was found between the friction coefficients and the particle diameters.

Hofstee and Ten Berge (2004a) have proposed a new look at personality assessment data, based on a bipolar proportional (-1, .. . 0, .. . +1) scale, a corresponding coefficient of raw-scores likeness L = ΢XY/N, and raw-scores principal component analysis. In a normal sample, the approach resulted in a structure dominated by a first principal component, according to which most people are faintly to mildly socially desirable. We hypothesized that a more differentiated structure would arise in a clinical sample. We analyzed the scores of 775 psychiatric clients on the 132 items of the Dutch Personality Questionnaire (NPV). In comparison to a normative sample (N = 3140), the eigenvalue for the first principal component appeared to be 1.7 times as small, indicating that such clients have less personality (social desirability) in common. Still, the match between the structures in the two samples was excellent after oblique rotation of the loadings. We applied the abridged m-dimensional circumplex design, by which persons are typed by their two highest scores on the principal components, to the scores on the first four principal components. We identified five types: Indignant (1-), Resilient (1-2+), Nervous (1-2-), Obsessive-Compulsive (1-3-), and Introverted (1-4-), covering 40% of the psychiatric sample. Some 26% of the individuals had negligible scores on all type vectors. We discuss the potential and the limitations of our approach in a clinical context.

Trait structures resulting from personality assessments on Likert scales are affected by the additive and multiplicative transformations implied in interval scaling and correlational analysis. The effect comes into view on selecting a plausible alternative scale. To this end, we propose a bipolar bounded scale ranging from -1 to +1 representing an underlying process in which the assessor would review and discount positive and negative behavioral instances of a trait. As an appropriate index of likeness between variables X and Y we propose L-XY = SigmaXY/N, the average of the raw scores cross products. Using this index, we carried out a raw scores principal component analysis on data consisting of 133 participants who had each been rated by 5 assessors including self on 914 items. Contrary to the Big-Five structure that was found in these data on standard analysis, the results showed a relatively large first principal component F-1 and 2 very small ones, F-2 and F-3. The sizes L-FE = SigmaF(2)/N, the averages of the squared component scores, were modest to small. It thus appears that the scale, bipolar proportional versus standard, has a profound impact on the size and structure of personality assessments. The dissimilarity remains on analyzing self-ratings rather than averaged (over the 5 assessors) ratings.

Hofstee and Ten Berge (2004/this issue) present procedures based on an absolute conception of scales in personality assessment as distinct from the dominant interval-scale interpretation. On application, these procedures resulted in a contraction of a 5-dimensional structure into essentially I personality dimension. McGrath (2004/this issue) and Ozer (2004/this issue) comment on the various aspects of these procedures: the transformation of data onto a bipolar proportional scale, the adoption of the raw scores product average as an index of association, and raw scores principal component analysis. In reply to these comments, we emphasize that the central ingredient in our procedures is the interpretation of the midpoint on a bipolar scale as a threshold. We provide further arguments for that interpretation and demonstrate the robustness of the simplified structure under that central assumption. We acknowledge the comment that our conception does not fit in comparative contexts capitalizing on individual differences but argue that other contexts involving thresholds are relevant to the study of personality. We also acknowledge that item pools should be sufficiently homogeneous for scales to be meaningful.

Standard procedures for processing and interpreting data in personality assessment run the risk of losing their audience. Most notably, relative scaling of data, whether through interindividual or intra‐individual comparison, leads to losing either the persons or the variables from view. I set out an alternative, more congenial procedure for handling personality data, consisting of (i) translating assessments to a bipolar bounded scale running from − 1 to + 1, (ii) adopting the uncorrected average cross‐product (ACP) as the index of association or correspondence between variables and between individuals, and (iii) applying raw‐scores principal component analysis to find factors and types. The ACP index appears eminently fit for handling individual (N = 1) cases. Adoption of the congenial procedure would imply a substantive correction of one's views of individual differences in personality and their structure. Copyright © 2002 John Wiley & Sons, Ltd.

Plant phenotyping is an emerging science that links genomics with functional plant characteristics. The recent availability of extremely fast high-throughput genotyping technologies has invoked high-throughput phenotyping to become a major bottleneck in the plant breeding programs. As a consequence new camera-based technologies to relieve the phenotyping bottleneck attract considerable attention. Whereas most plant phenotyping technologies are based on the approach to bring the plants to the image recording device, our system brings the camera-system to the plants creating great flexibility on observing plants under practical growing conditions. A new camera, based on lightfield technology was used for image recording. This single lens 3D camera is constructed by placing a micro lens array in front of the image sensor. This also allows the user to change the focus and the point of view after a picture has been taken. While the concept of such plenoptic cameras is known since 1908, only recently the increased computing power of low-cost hardware and the advances in micro lens array production, have made the application of plenoptic cameras feasible. Since this camera outputs a pixel to pixel registered color image and depth map, it solves limitations of common used techniques such as stereo vision and time of flight. During the summer of 2013 an experiment is carried out in a commercial tomato greenhouse in the Netherlands. In this paper first preliminary results are presented and the performance of lightfield technology for plant phenotyping is discussed.

The Dutch national objectives for the education of medical doctors (in terms of diseases), expressed in the form of a student compiled logbook, must be attained at the time of graduation. The diseases that are required are divided into the categories 'essential' and 'compulsory choice: The aim of this study is to investigate whether the inpatient department of internal nedicine offers medical students sufficient diseases during two four-week periods in the clerkship, such that the required diseases related to Internal Medicine as described in our logbook can be met. Ar five subdivisions, medical doctors recorded the diseases available for students. Of the 37 'essential' diseases students may be expected to encounter during one four-week stay in the department: 57% in internal medicine-I; 55% in internal medicine-ii; 47% in nephrology; 41% in respiratory medicine; 13% in oncology. Of the 65 'compulsory choice' diseases the number of diseases encountered is respectively: 78%; 57%; 41%; 34%; 33%. We conclude that a considerable number of the diseases required by the Blueprint and therefore by the government is available in two four-week periods in the inpatient clerkship, when this comprises a stay at a general subdivision and a specialist-oriented subdivision. To be more precise about the fulfilment of the logbook requirements, further research is necessary.

A system was developed to measure the mass flow of granular fertilizer material in aerial spreader ducts. The flow process was regarded as the sequential passage of clusters containing multiple particles with varying diameters. An optical sensor was used to measure the cluster lengths on the fly. In a low-density flow regime, the diameter of each particle could be measured individually (this is called the "single-particle approach"). After conversion to a volume of a sphere and multiplication by the true material density, the mass flow could be computed. In a high-density mass flow regime (called the "mass flow approach"), particles form clusters, and cluster lengths would be measured instead of particle diameters. The first step in performing mass flow measurement was to develop a reconstruction algorithm that estimates the number of particles in a cluster from the measured cluster length. This algorithm, called the Exponential Estimator, was developed using simulation and is reported in Part 1. This article, Part 2, describes the use of the mass flow sensor as well as the reconstruction algorithm to assess the accuracy of the complete system. Tests were carried out under laboratory conditions, using mass flows of spherical particles as well as urea fertilizer under varying flow velocities and densities. The mass flow of identical spher ical particles of 4.45 mm diameter was measured with an accuracy of 3%, even under high-density flow conditions. For granular fertilizer, the flow was measured with an accuracy of 2% for high-density flows and 4% for low-density flows.

Background: The Dutch Blueprint 1994 (Raamplan 1994) describes the objectives of undergraduate medical education. The Blueprint, developed in order to improve medical education in the Netherlands, is accepted by all Dutch medical schools and has been legislated Aim: Translation of global objectives of the Blueprint into specific requirements of a Logbook (guideline and evaluation tool) far the internship Internal Medicine. Description: The Blueprint as such is impracticable as a guideline during the Internal Medicine internship. The content covers the objectives for the entire field of medicine, and the volume dedicated to Internal Medicine is too large to fit in with a twelve week internship. The practicability of the Blueprint leaves much to be desired because it is complex, and not easily accessible. So, the Blueprint was adapted on three points: (1) selecting those objectives out of the whole content, which are specifically relevant to Internal Medicine; (2) decreasing the volume Internal Medicine by clustering and defining the requirements; (3) making the Logbook usable as a guideline and evaluation instrument. Conclusion: The Logbook is a good starting-point to evaluate whether students meet the objectives of the Blueprint related to the discipline internal Medicine. (C) 1999 Elsevier Science B.V. All rights reserved.

Agricultural machinery in the future will be equipped with a data bus for the exchange of information between different devices such as a task computer, virtual terminal, implement controllers, sensors and actuators. This exchange of information requires standardization. Currently, a working group of the International Organization for Standardization (ISO) is defining a standard for a serial control and communications data network for tractors and machinery for agriculture and forestry and is based on controller area network (CAN) Version 2·0B. A simulation program has been written for a typical agricultural machinery configuration, equipped with data buses, connected to each other. The simulation program is used to analyse the performance of the network with respect to the transfer time of messages across the network. The transfer time is determined for different bus loads, priorities of the messages and arrangement of the devices. The simulations showed that the transfer time of messages across the network remains less than 6 ms (maximum observed value) for a typical agricultural machinery configuration. Increase in load on the implement bus to more than 80% of full capacity can result in transfer times of about 70 ms when the priorities are not properly assigned. This transfer time may be too large for some specific applications. When time critical messages are assigned a proper priority, the transfer times of the messages remain less than a few milliseconds, even when the load on the implement bus is high.

It has been shown by Kaiser that the sum of coefficients alpha of a set of principal components does not change when the components are transformed by an orthogonal rotation. In this paper, Kaiser's result is generalized. First, the invariance property is shown to hold for any set of orthogonal components. Next, a similar invariance property is derived for the reliability of any set of components. Both generalizations are established by considering simultaneously optimal weights for components with maximum alpha and with maximum reliability, respectively. A short-cut formula is offered to evaluate the coefficients alpha for orthogonally rotated principal components from rotation weights and eigenvalues of the correlation matrix. Finally, the greatest lower bound to reliability and a weighted version are discussed.

The standard practice in scoring questionnaires consists of adding item scores and standardizing these sums. We present a set of alternative procedures, consisting of (a) correcting for the acquiescence variance that disturbs the structure of the questionnaire; (b) establishing item weights through principal component analysis in order to obtain maximally reliable scale scores; (c) applying a procedure of hierarchically-nested circumplex construction to catch shades of meaning and thus facilitate interpretation; and (d) retaining absolute information by the use of anchored scores in addition to standard scores. In discussing circumplexical representations (c), we provide an illustration linking the three- and five-factorial conceptions of the personality trait domain.

In Northwest Europe there is high need for advanced weed control methods. The use of crop protection chemicals has become stricter, and integrated pest management is required by regulations from the European Union. This need has resulted in the development of several advanced weed control principles based on a combination of proven technologies in combination with decision systems. A major problem with full-field-based methods is that the required settings depend very much on the specific conditions. Use of decision systems helps to improve these methods. Emerging new technologies as machine vision and GPS enabled more precise methods focused on the interrow and intrarow zone and on the plant itself. Some of the methods have already achieved a high level of development and resulted in commercially available weed control equipment with sensors and actuators for precise control. This chapter discusses the advancements achieved in NW Europe on mechanical weed control (full field, interrow and intrarow), physical weed control (steaming and flaming) and chemical weed control (full field, spot and plant oriented).

Predictability of granular fertilizer spreading patterns is of interest from the environmental as well as the economic point of view. To ensure a constant level of uniformity of spreading patterns in the field, the Dutch government has announced their intention to require periodic testing of spreader equipment. Testing of fertilizer spreaders is traditionally carried out in large halls where spread patterns are derived from measuring fertilizer mass in collecting bins. Hofstee (1994) has developed an alternative system which measures three-dimensional velocity vectors within a cylindrical sampling zone behind the spreader. It also simultaneously estimates individual particle diameters. These measured quantities serve as initial conditions in a trajectory model that predicts landing spots for individual particles. After a test run the complete set of landing spots represents a spread pattern. The trajectory model uses prediction equations based on the aerodynamic behavior of perfectly spherical particles. However, since fertilizer particles are in general not spherical, a method to compensate for this has been developed. This method uses the ratio between measured and modeled fall times, and is expressed in a parameter, the diameter coefficient. Once this parameter is assessed for a specific material, it can be used as a correction factor in the trajectory model. In this research a fall test is used as a robust and simple method for collecting data about the fall time of individual fertilizer particles, falling from a constant height. The materials used in this research were Calcium Ammonium Nitrate (CAN 27 N), Nitrate Phosphorous Potassium (NPK 12-10-18) and Potassium 60. They were chosen for their wide-spread use and different shape characteristics. The diameter range of particles used in the research was 1 to 4.75 mm.

Testing of fertilizer spreaders is traditionally carried out by using the collecting tray method, requiring a large hall to eliminate the influence of wind and rain. The Dutch government has announced mandatory periodic testing of fertilizer equipment which could require a significant number of these costly halls. Therefore, an alternative method has been developed which is based on scanning the spreading zone and measuring the velocity vector and diameter of individual fertilizer particles, emanating from the spreader. A model then predicts the landing spot of each particle and accumulation of these spots gives the desired spread pattern. To test the proper functioning of the sensors that are used to measure the velocity and diameter of the particles, it was found necessary to develop a test device which is capable of discharging fertilizer particles with a realistic velocity and a fixed direction. The desired maximum launch velocity of the device is 70 m/s, the most extreme value that particles reach in practice. The principle of the accelerator that was developed is similar to that of a disc type spreader which has been fitted with an encapsulating housing. The machine was tested in combination with an optical device for the measurement of velocity and diameter, at ejection velocities up to 52 m /s. At higher velocities, virtually all fertilizer particles fragmented owing to the severe forces on particles when being accelerated.

Modern tractors and implements will be equipped increasingly with electronic components together with a field bus for the exchange of information between different tractor and/or implement controllers, task controllers, and a virtual terminal used for communication with the operator. In Germany, a DIN standard (DIN 9684) for such a field bus based on CAN (controller area network) has been developed. The performance of such a system for process con trol depends on the load of the bus in relation to how messages are transmitted. A simulation program for a field bus based on the DIN 9684 standard has been developed. This program is used to analyse the influence of the message type used for transfer of setpoints, the procedure by which large amounts of data are transferred and the quantity of data on the time required before a setpoint message arrives at its destination. The simulation shows that when the setpoint messages are transmitted as “basic data–process data” messages, the waiting times will be a few milliseconds. When the setpoint messages are transmitted using “targeted” messages, the waiting times can increase to some seconds when, at the same time, large amounts of data are transferred. Therefore, it is important that the message type is properly chosen.

Fertilizer spreaders are traditionally tested by using the collecting tray method. This method requires large indoor test facilities and is very expensive when applied on a large scale. A proposed alternative method is to measure the velocity and diameter of individual fertilizer particles emanating from the spreader and use a model to predict the landing spot of individual particles. The total spread pattern follows from accumulating a large number of particle landing spots. An optical device for measuring the velocity vector and dimensions of individual fertilizer particles was developed. The system proved capable of measuring the velocity of a 4 mm particle travelling at 29 m/s within an accuracy of 5% and dimensions within 2%. Two forms of the detector are discussed, namely, one and two dimensional versions respectively.

The motion of particles is discussed as affected by physical properties, such as coefficient of friction, and the design of the disc including the vane type, pitch angle of the vane and surface of the vane. The influence of factors that may have an effect are studied theoretically by means of simulations as well as experimentally. When the simulation and measurement results were compared, large differences were found between them. The simulation results showed a clear effect of the coefficient of friction. This effect was, however, hardly visible in the measurements despite differences in vane surfaces that gave large differences in coefficient of friction (0·25 to 0·35 for a nylon surface versus 0·40 to 0·45 for a stainless steel surface). The measurements showed that an increase of the mass flow by a factor of two in the range tested (between 0·3 and 1·0 kg/s) resulted in an increase in the distance projected by the particles of about 1 m. The influence of vane type and pitch angle have been analysed in simulation studies and the effect proved to be dependent on the coefficient of friction.

The motion of particles is discussed, as affected by physical properties such as coefficient of friction and coefficient of restitution and the design of the spout (spout length, bow, spout angle) and the propulsion of the spout as influenced by the angular velocity of the driving shaft and the crank connecting rod ratio. The factors that may have an effect are studied theoretically, by means of a simulation model, and experimentally. The results of the simulations show that there is a large interaction between the oscillatory action of the spout and the factors mentioned above. Resulting values for velocities and residence times depend heavily on whether the motion of the particles along the spout is "in phase" with the motion of the spout or not. The flow of fertilizer from the hopper to the bowl at the beginning of the spout also plays an important role. A consequence of the interaction is that this type of spreader is not very sensitive to fertilizer characteristics. The influence of the oscillatory motion is much larger than the influence of individual variables.

For a better understanding of growth and development of tomato plants in three dimensional space, tomato plants were monitored using a computer vision system. It is commonly known that leaves of tomato plants do not have a fixed position and orientation during the day; they move in response to changing environmental conditions such as the position of the sun. For better understanding, it was desired to quantify this motion. Using a stereovision concept, two cameras were mounted in an experimental greenhouse a short distance apart from each other to enable depth measurement. Markers were placed on strategic spots on the tomato plant branches and leaves in the field of view of both cameras. Images were taken every ten minutes during daytime on several consecutive days. In the greenhouse, a virtual 3D coordinate system was defined and camera and tomato plant position and orientation were defined in this coordinate system. Image processing techniques were used to trace the markers and the 3D position coordinate of each marker in each image was calculated to obtain the course of a marker during several days. Stems, branches, and leaf nerves were considered as kinematic mechanical, robot like, links and corresponding theory was used to model and calculate the motion of stems and leaves of a tomato plant. Analysis of the images showed both small (1-2 degrees) and large rotations (10 degrees or more) of the branches and the different leaves on a branch during the course of a day. Leaves on one side of a branch showed a parallel motion in the same direction; the leaves on the opposite side of the branch showed a mirrored motion. However, deviating patterns occurred too. The developed method proved to be able to precisely quantify the motion of stems, branches and leaves of tomato plants during several days.

In a comment on the special issue of the European Journal of Personality on Factor V from the Five‐Factor Model, I argue that attempts to arrive at a definitive interpretation are premature in view of the limitations of the item pools that have been used, arbitrariness in choosing criteria for item selection, and limitations of sample sizes. At present, the best tentative interpretation of V is Creativity/Imagination. However, the relation of this concept to the domain of measured intelligence should be reconsidered. The joint study of temperament (Factors I and IV), character (II and HI), and intelligence factors should provide insight into the fascinating blends that arise between these dimensions. Such blends are captured by the Abridged Big‐Five Dimensional Circumplex approach to personality structure in a parsimonious manner.

The averaged judgment of knowledgeable others provides the best available point of reference both for the definition of personality structure in general and for assessing someone's personality in particular. Self‐judgments, as in personality questionnaires, are intrinsically deficient because judgment errors cannot be averaged out. The recommended procedure for assessing someone's personality is to give a personality questionnaire, phrased in the third person singular, to those who know the target best. This set may or may not include the target person as a judge.

This paper describes a method to alert growers of the presence of a pathogen infection in their greenhouse based on the detection of pathogen-induced emissions of volatile organic compounds (VOCs) from plants. Greenhouse-grown plants were inoculated with spores of a fungus to learn more about this concept. The specific objective of the present study was to determine whether VOCs are detectable after inoculation, and if so, to determine the time course of the concentrations of these compounds. To achieve this objective, we inoculated 60 greenhouse-grown tomato plants (Lycopersicon esculentum) with an aqueous suspension of Botrytis cinerea spores. Upon inoculation, the greenhouse air was sampled semi-continuously with a one hour time interval until 72 hours after inoculation (HAI). The samples were transferred to the laboratory and analysed using gas chromatography - mass spectrometry. Ten leaves were randomly selected to monitor the visible symptoms of infection. The severity of these visual symptoms was assessed at 0, 24, 48, and 72 HAI. Results demonstrated no detection of C6-compounds, and an almost constant concentration of all monoterpenes, most sesquiterpenes, and (E,E)-4,8,12-trimethyl-1,3,7,11-tridecatetraene. However, the concentration of methyl salicylate increased 10-fold and 3-fold at 32 and 34 HAI respectively. At 24 HAI, 10% of the selected leaves showed mild symptoms while 20% of the selected leaves showed mild symptoms at 48 HAI. These results indicate that methyl salicylate might alert a grower of the presence of a B. cinerea infection of tomato plants at greenhouse scale. Further research is required to confirm these findings.

This review focuses on the detection of diseased plants by analysis of volatile organic compound (VOC) emissions. It includes an overview of studies that report on the impact of infectious and noninfectious diseases on these emissions and discusses the specificity of disease-induced emissions. The review also provides an overview of processes that affect the gas balance of plant volatiles, including their loss processes. These processes are considered as important because they contribute to the time-dynamic concentration profiles of plant-emitted volatiles. In addition, we describe the most popular techniques currently in use to measure volatiles emitted from plants, with emphasis on agricultural application. Dynamic sampling coupled with gas chromatography and followed by an appropriate detector is considered as the most appropriate method for application in agriculture. It is recommended to evaluate the state-of-the-art in the fields concerned with this method and to explore the development of a new instrument based on the specific needs for application in agricultural practice. However, to apply such an instrument in agriculture remains a challenge, mainly due to high costs.

The goal of this article is 2-fold. Firstly to show the utility of the circumplex principles in articulating trait structures, and secondly to show that the use of different word categories as trait descriptors can be exploited for the further refinement of the established Five Factor structure. We discuss simple structure and circumplex models and their integration, the so-called AB5C model. The AB5C model is applied to self-ratings (N = 200) on 551 personality adjectives and 507 personality verbs. The differences between the two data sets, adjective and verb data, are discussed, and the usefulness of both data sets for the mutual articulation of the respective wordclass specific trait structures is demonstrated.

This chapter focuses on the monitoring of crop health status via the measurement of volatile organic compounds (VOCs) emitted from the plants. It includes the most important factors that affect the emission of these VOCs from crops grown in greenhouses. Since both stressors as well as nonstressors have an effect on the emission, they are covered separately. The chapter provides an overview of processes that affect the gas balance of plant VOCs in the greenhouse including the loss processes. These processes are considered as important since they contribute to the time-dynamic concentration profiles of plant-emitted VOCs. In addition, we describe the most popular techniques currently in use to measure volatiles emitted from plants, with emphasis on greenhouse application. Dynamic sampling in combination with gas chromatography coupled to mass spectrometry is considered as the most appropriate method for application at greenhouse scale. It is recommended to evaluate the state of the art in the fields concerned with this method and explore the development of a new instrument based on the specific needs for application in greenhouse practice. However, to apply such an instrument at greenhouse-scale remains a challenge, mainly due to the high costs associated with it.

Incomplete control of volunteer potato plants causes a high environmental load through increased crop protection chemical usage in potato cropping. A joint effort of industry, policy makers and science initiated a four year scientific project on detection and control of volunteer potato plants. A proof-of-principle machine for automated detection and control of volunteer potato plants in sugar beet fields has been tested in experimental fields. Machine vision-based detection at 100 mm2 precision is combined with a micro-sprayer with five needles and a working width of 0.2 m. The accuracy of the system was ±14 mm in longitudinal direction and ±7.5 mm in transverse direction. The main error source was the variability in micro-sprayer droplet velocity that caused longitudinal errors. However, 77% of volunteer plants with a size larger than 1200 mm2 were successfully controlled at machine speeds up to 0.8 m s−1. Within the crop row, glyphosate was applied on weed potato plants and this resulted in the unwanted death of up to 1.0% of sugar beet plants.

Volunteer potato is an increasing problem in crop rotations where winter temperatures are often not cold enough to kill tubers leftover from harvest. Poor control, as a result of high labor demands, causes diseases like Phytophthora infestans to spread to neighboring fields. Therefore, automatic detection and removal of volunteer plants is required. In this research, an adaptive Bayesian classification method has been developed for classification of volunteer potato plants within a sugar beet crop. With use of ground truth images, the classification accuracy of the plants was determined. In the non-adaptive scheme, the classification accuracy was 84.6 and 34.9% for the constant and changing natural light conditions, respectively. In the adaptive scheme, the classification accuracy increased to 89.8 and 67.7% for the constant and changing natural light conditions, respectively. Crop row information was successfully used to train the adaptive classifier, without having to choose training data in advance.

In this article we pursue two goals. The first is a further articulation of the dimensionality of the Dutch trait domain. The second is a detailed mapping of the factorial trait structure, one which includes intelligible and proper niches for various nuances of the trait language and for different interpretations of the main factors of personality language. In realizing these goals, we discuss the reliance on theory in structuring and modelling the domain in question, the type of model to be used, and the comprehensiveness versus the economy of domain representation. The advantages and disadvantages of the simple structure model and the circumplex model are commented upon, and a new framework that integrates these two models is presented. The present results provide confirmation of the existence of five major dimensions that cover the trait domain: (I) Extraversion or Surgency, (II) Agreeableness, (III) Conscientiousness, (IV) Emotional Stability, and (V) Intellect or Openness to Experience. The newly developed representational model, revealing a refined structure of personality characteristics, not only clarifies some of the problems faced in interpreting the Big Five factors, but also forms a starting point for applications.

Handling and spreading of fertilizer is affected by the physical properties of the particles and so a knowledge of these properties is helpful in understanding fertilizer handling and use. Methods for measuring the coefficient of friction, the coefficient of restitution, the aerodynamic resistance coefficient, and the breaking force (particle strength) of fertilizers are discussed. Measuring devices for the four properties are developed and their characteristics are described. The results of experiments with these devices are presented. The coefficient of friction is influenced to a minor extent by the velocity relative to the friction surface layer. There was almost no influence of normal load but a significant effect of fertilizer type, friction surface layer and environmental conditions. The coefficient of restitution measurements showed a large effect of the impact surface and smaller effects of particle diameter and fertilizer type. A large difference was found between two methods for measuring the aerodynamic resistance coefficient. A new shape parameter was introduced in this paper, as a parameter to determine the aerodynamic resistance of fertilizer particles. Coarser particles were shown to have a higher aerodynamic resistance coefficient than particles with a smooth surface texture. The breaking force measurements showed that the relationship between strength and particle size depended on the fertilizer type.

In 2003/4 vond een experiment plaats waarbij op een UWV-kantoor clienten dubbel, dus door twee verzekeringsartsen onafhankelijk van elkaar, werden beoordeeld; bij de overige kantoren werden enkelvoudige beoordelingen voorgelegd aan een staf-verzekeringsarts.1 De resultaten van dit experiment wezen op verbeterde kwaliteit van de beoordelingen. De aanbeveling echter om met name de dubbele beoordeling vaker toe te passen is maar in zeer beperkte mate gevolgd.

Gerardus Van der Leeuw (1890 - 1950) considered German National Socialism and Russian communism as equally great threats to western civilization because of their nihilistic character. A few years before the Nazis came to power in Germany, Van der Leeuw expressed his concern about the loss of values in modern society, and about the cultural crisis in Europe. In 1939 Gustav Mensching had asked Van der Leeuw to consider leaving out the names of Jewish authors, in this case Levy-Bruhl and Cassirer, in a planned German translation of one of his major works. So, looking at the general picture, Van der Leeuw has not been much of an exception when it comes to his critique of culture. Neither was he an exception when he joined the political movement which proposed a 'critical collaboration' with the German oppressors in 1940, since many intellectuals and politicians did the same.Keywords: Gerardus Van Der Leeuw; German National Socialism; nihilistic character; Russian communism