Modeling the early phases of epidemics by Phakospora pachyrhizi in Brazilian soybean

Asian soybean rust, caused by the biotrophic basidiomycete Phakospora pachyrhizi, is a foliar disease that often causes considerable damage to soybean crops. The purpose of our work was to create a mechanistic model that can reliably represent epidemics of ASR in commercial soybean fields in Brazil. The most important inputs for the model are weather data (observations and forecast) and the initial observation of disease (or uredospore arrival). Our focus is on the first two or three cycles of infection after immigration into a soybean field. The model includes state variables for latent, infectious and senesced lesions, disease severity, uredospores, and soybean leaf area. Processes modeled include maturation through the latent and infectious periods, germination, sporulation, and processes affecting uredospores in the canopy. The model results were tested against field observations from trials at four locations in Brazil for the 2019/2020 growing season. The predictions generally matched the daily dynamics of disease progress in the field trials. The predictions reproduced the observed severity well with R2 value of 0.84. This high correlation indicates that our model is accurate enough to be used as a tool to predict the dynamics of ASR epidemics during the first few cycles after uredospore invasion into a soybean field. A sensitivity analysis was performed that showed that the model is sensitive to time and duration of the initial spore arrival. This indicates that spore traps or other observations should measure not only the first day of arrival but also subsequent days

Domain Concept to Feature Mapping for a Plant Variety Image Database

. The most intuitive way of retrieving images is on the basis of domain concepts. However, this requires a mapping between the concepts and the content of the image. Such a mapping should be based on a proper visual guideline. We illustrate this with plant variety testing as an application for which such guidelines are available. The methods seem to have general applicability for every application domain where such guidelines can be made. 1 Introduction Before we consider domain concept to feature mapping we first give an introduction to the application for which the techniques have been developed. Plant Breeders' Rights (PBR) are a means to reward plant breeders for their breeding efforts. They are special type of patents granted for plant varieties. To obtain PBR, a variety has to fulfill a number of criteria, most importantly it should be distinct from established varieties worldwide. Hence, given new variety application a set of similar established varieties should be selected for..

GMOANALYSIS VERSION 2.1.0 – 10 JULY 2014

GMOANALYSIS VERSION 2.1.0 is a user-friendly software supporting the statistical analysis methodology recommended by the EFSA GMO Panel with regard to the food and feed safety assessment of genetically modified plants. The software implements all steps of the statistical procedure for the analysis of comparative field trial data, described in EFSA’s guidance for FF risk assessment (EFSA, 2011). The software conducts the simultaneous analysis of the GM plant compared to its control and non-GM reference varieties (test of difference and test of equivalence). Input data of agronomic, phenotypic or compositional analysis from field trials in eight locations where both the GM plant and a comparator plant were grown is required. The analysis is performed using a Residual Maximum Likelihood (REML) mixed model. An output-file listing all the significant differences and the respective equivalence categories is generated

GMOANALYSIS VERSION 2.1.0 – 10 JULY 2014

<p>GMOANALYSIS VERSION 2.1.0  is a user-friendly software supporting the statistical analysis methodology recommended by the EFSA GMO Panel with regard to the food and feed safety assessment of genetically modified plants.  The software implements all steps of the statistical procedure for the analysis of comparative field trial data, described in EFSA’s guidance for FF risk assessment (EFSA, 2011). The software conducts the simultaneous analysis of the GM plant compared to its control and non-GM reference varieties (test of difference and test of equivalence). Input data of agronomic, phenotypic or compositional analysis from field trials in eight locations where both the GM plant and a comparator plant were grown is required. The analysis is performed using a Residual Maximum Likelihood (REML) mixed model.  An output-file listing all the significant differences and the respective equivalence categories is generated.</p

Comparison of multispectral images across the Internet

Comparison in the RGB domain is not suitable for precise color matching, due to the strong dependency of this domain on factors like spectral power distribution of the light source and object geometry. We have studied the use of multispectral or hyperspectral images for color matching, since it can be proven that hyperspectral images can be made independent of the light source (color constancy) and object geometry (normalized color constancy). Hyperspectral images have the disadvantage that they are large compared to regular RGB-images, which makes it infeasible to use them for image matching across the Internet. For red roses, it is possible to reduce the large number of bands (&gt;100) of the spectral images to only three bands, the same number as of an RGB-image, using Principal Component Analysis, while maintaining 99% of the original variation. The obtained PCA-images of the roses can be matched using for example histogram cross correlation. From the principal coordinates plot, obtained from the histogram similarity matrices of twenty images of red roses, the discriminating power seems to be better for normalized spectral images than for color constant spectral images and RGB-images, the latter being recorded under highly optimized standard conditions

Optimizing illumination in the greenhouse using a 3D model of tomato and a ray tracer.

Article de revue (Article scientifique dans une revue à comité de lecture)International audienceReduction of energy use for assimilation lighting is one of the most urgent goals of current greenhouse horticulture in the Netherlands. In recent years numerous lighting systems have been tested in greenhouses, yet their efficiency has been very difficult to measure in practice. This simulation study evaluated a number of lighting strategies using a 3D light model for natural and artificial light in combination with a 3D model of tomato. The modeling platform GroIMP was used for the simulation study. The crop was represented by 3D virtual plants of tomato with fixed architecture. Detailed data on greenhouse architecture and lamp emission patterns of different light sources were incorporated in the model. A number of illumination strategies were modeled with the calibrated model. Results were compared to the standard configuration. Moreover, adaptation of leaf angles was incorporated for testing their effect on light use efficiency (LUE). A Farquhar photosynthesis model was used to translate the absorbed light for each leaf into a produced amount of carbohydrates. The carbohydrates produced by the crop per unit emitted light from sun or high pressure sodium lamps was the highest for horizontal leaf angles or slightly downward pointing leaves, and was less for more upward leaf orientations. The simulated leaf angles did not affect light absorption from inter-lighting LED modules, but the scenario with LEDs shining slightly upward (20(°)) increased light absorption and LUE relative to default horizontal beaming LEDs. Furthermore, the model showed that leaf orientation more perpendicular to the string of LEDs increased LED light interception. The combination of a ray tracer and a 3D crop model could compute optimal lighting of leaves by quantification of light fluxes and illustration by rendered lighting patterns. Results indicate that illumination efficiency increases when the lamp light is directed at most to leaves that have a high photosynthetic potential.</p

MODEL DEVELOPMENT TO PREDICT PERCEIVED DEGREE OF NATURALNESS

Abstract − This paper presents the development of a mathematical model to predict the perception of naturalness for a range of materials, based on an understanding of the relationship between the physical attributes of the material and the human sensory inputs. The work is being carried out under an European Union project called ‘Measurement of Naturalness ’ (MONAT), which focuses on understanding the relationships between the physical properties of natural and synthetic materials and the visual and tactile sensory processes that lead to perceptual judgments of naturalness. Integral to the project is the development of novel measurement facilities with dynamic ranges and sensitivities that are relevant for the human sensory systems. The input data to the model are derived from psychophysical and physical studies on pre-selected wood, textile and stone samples