Showing papers in "Computers and Electronics in Agriculture in 2009"

TL;DR: In this paper, a machine vision system for the identification of the visual symptoms of plant diseases, from coloured images, was reported, where Diseased regions shown in digital pictures of cotton crops were enhanced, segmented, and a set of features were extracted from each of them.

TL;DR: The experience during the introduction and deployment of an experimental sensor network at an ecological horticultural enterprise in the semiarid region of Murcia is described, which presents the topology of the deployed network using four types of nodes, some of them connected to different sensors distributed in the field.

TL;DR: In this paper, the authors show how miniaturized RFID temperature loggers can be adapted to analyze the amount of local deviations, detect temperature gradients, and estimate the minimum number of sensors that are necessary for reliable monitoring inside a truck or container.

TL;DR: A study of the accuracy of five supervised classification methods using multispectral and pan-sharpened QuickBird imagery to verify whether remote sensing offers the ability to efficiently identify crops and agro-environmental measures in a typical agricultural Mediterranean area characterized by dry conditions.

TL;DR: Overall, it is found the accelerometers provided an accurate, remote measure of cattle behavior over the trial period, but that classification accuracy was affected by the specific behavior monitored and the reporting interval (epoch).

TL;DR: The differences in leaf reflectance measurements at specific wavelength intervals between virus-infected and uninfected grapevines and their correlation with RT-PCR results for the presence of GLRaV-3 suggest spectral reflectance technique as a promising tool for cost-effective, nondestructive method for diagnosis of GLD in the field.

TL;DR: This report explains how the Microsoft Excel Workbook can be used to analyze the probing and ingestion behavior of two hemipteran species, demonstrating its flexibility and potentiality for efficient and rapid analysis of EPG data.

TL;DR: In this paper, a calibration process is developed to determine the parameter values of the discrete element method (DEM) to predict the internal friction angle and stiffness, respectively, and the results of the calibration process are validated by modeling silo discharge and bucket filling.

TL;DR: In this article, a pixel discrimination function was generated based upon a linear discriminant analysis and applied to all pixels in a hyperspectral image for image segmentation of fruit and other objects.

TL;DR: In this article, an artificial neural network (ANN) model was developed to predict soil texture (sand, clay and silt contents) based on soil attributes obtained from existing coarse-resolution soil maps combined with hydrographic parameters derived from a digital elevation model.

TL;DR: In this paper, a mean-shift segmentation method was proposed to improve the segmentation rate of the images containing green vegetation by introducing a mean shift procedure into segmentation algorithm.

TL;DR: In this article, a low-cost method to estimate the nitrogen nutrition status of plants using digital color image analysis was proposed and evaluated, and the performance of the proposed index is better than that of others previously investigated.

TL;DR: This research presents the design of decision support software and its integration with an in-field wireless sensor network (WSN) to implement site-specific sprinkler irrigation control via Bluetooth wireless communication.

TL;DR: The NAV system is a complete monitoring system that gave flexibility for planning and installation, which fully responded to the objectives of the work in terms of energy efficiency and performance.

TL;DR: In this article, the potential use of electro-magnetic induction scans (EMI) to measure apparent electrical conductivity and improve the estimate accuracy of sparsely sampled primary variables was assessed in a 5-ha gravelly soil vineyard in Valpolicella, north-eastern Italy.

TL;DR: This paper formulate a crop-planning problem as a multi-objective optimization model and solve two different versions of the problem using three different optimization approaches, including the @?-constrained method, NSGAII and the proposed multi- objective constrained algorithm (MCA).

TL;DR: This paper presents a prototype implementation of an agricultural process-data service (APDS), part of an infrastructure for data management in information-driven plant production, developed in the Pre agro joint research project.

TL;DR: A system that can be used to identify all aspects of beef traceability from farm to slaughter has been laid out based on pertinent European Union law and global standards.

TL;DR: In this paper, the authors explore the application of artificial neural networks (ANNs) for the prediction of air temperature during the entire year based on near real-time data and develop Ward-style ANNs using detailed weather data collected by the Georgia Automated Environmental Monitoring Network (AEMN).

TL;DR: In this article, the inconsistency of length-based separation of particles using standard sieves with manual measurements, which showed deviations of 17-22 times, was explored and a computer vision with image processing as an alternative approach; wherein a user-coded Java ImageJ plugin was developed to evaluate PSD based on length of particles.

TL;DR: In this paper, the time-dependent temperature distributions inside a Chinese solar greenhouse are numerically predicted from external climatic conditions using a computational fluid dynamics (CFD) analysis, which takes into account all of the heat transfer mechanisms including the variable solar insolation, the air infiltration, the heat capacities of the thick walls and the ground and the natural convection inside the greenhouse.

TL;DR: In this article, the authors presented a procedure and the results of an optimal design of the kinematic structure of a manipulator to be used for autonomous cucumber harvesting in greenhouses, which included the time needed to perform a collision-free motion from an initial position to the target position as well as a dexterity measure to allow for motion corrections in the neighborhood of the fruits.

TL;DR: In this paper, an electronic nose incorporating artificial intelligence was used to detect plant disease, specifically basal stem rot (BSR) disease that is caused by Ganoderma boninense fungus affecting oil palm plantations in South East Asia.

TL;DR: In this paper, the propagation of laser light in kiwifruit (Actinidia deliciosa) tissue was measured by backscattering imaging and modelled with the Monte Carlo (MC) method.

TL;DR: In this paper, an 87-ha tobacco field was selected to define management zones (MZs) for more precise soil nutrient management for flue-cured tobacco (Nicotiana tabacum) in Central China.

TL;DR: A computer-based image analysis system allowing users to input digital images of a crop field, and to process these by a series of methods to enable the percentages of weeds, crop and soil present in the image to be estimated.

TL;DR: In this article, a method based on computer vision systems (CVS) to estimate shrimp dehydration level by analyzing color during drying process was presented, and the results obtained with these two models lead to 0.80 and 0.86 correlation coefficients in MLR and ANN models, respectively.

TL;DR: Test and validating the accuracy of four image processing algorithms for crop/weed discrimination in synthetic and real images showed that wavelets were well adapted for perspective images: the best results were with Daubechies 25 and discrete approximation Meyer wavelets.

TL;DR: The article includes two use cases demonstrating the adaptability of the SIMO framework, which is available as open source software and connected through a common ontology, again defined in XML.

TL;DR: In this paper, the authors developed a noninvasive wireless sensor nodes for measuring the temperature inside silage stacks, and designed a suitable sensor protection housing that prevents physical and chemical damage to the sensor.