Showing papers in "Biosystems Engineering in 2016"

TL;DR: In this paper, the authors used a convolutional neural network (CNN) to classify 22 weed and crop species at early growth stages from six different data sets, which have variations with respect to lighting, resolution, and soil type.

TL;DR: An analysis of the challenges faced by automatic plant disease identification using visible range images, emphasizing both the problems that they may cause and how they may have potentially affected the techniques proposed in the past.

TL;DR: A review of the research effort, developments and innovation in agricultural robots for field operations, and the associated concepts, principles, limitations and gaps can be found in this article, where the authors focus on: fusing complementary sensors for adequate localisation and sensing abilities, developing simple manipulators for each agricultural task, developing path planning, navigation and guidance algorithms suited to environments besides open fields and known a-priori, and integrating human operators in this complex and highly dynamic situation.

TL;DR: In this article, the predictive performance of two linear multivariate and two machine learning methods for predicting soil total nitrogen (TN), organic carbon (OC), and moisture content (MC) was compared.

TL;DR: The discrete element method has been in development since 1970s and has recently found practical application in simulations of granular assemblies to investigate natural phenomena as well as a design tool for technology as discussed by the authors.

TL;DR: A method for disease identification, based on colour transformations, colour histograms and a pairwise-based classification system, which was tested using a large database containing images of symptoms belonging to 82 different biotic and abiotic stresses.

TL;DR: Hyperspectral Imaging systems have gained a rapid interest from researchers to display the chemical structure and related physical properties of numerous types of food stuffs and hyperspectral imaging systems are expected to gain more considerably more potential and application in food processing and engineering plants.

TL;DR: In this article, an RGB-D camera was used for the detection and localisation of red and bicoloured apples on a tree in fruit orchards under a light shield blocking direct sunlight.

TL;DR: In this article, a machine-vision system was developed to segment and detect cherry tree branches with full foliage, when only intermittent segments of branches were visible and achieved 89.6% accuracy in identifying branch pixels.

TL;DR: In this paper, the authors developed a new estimation technique for disease severity in a field using RGB imagery from an UAV, which allows high throughput, objective, and precise phenotyping with regard to field resistance to potato late blight.

TL;DR: In this paper, the authors used a modular agricultural robot developed within the EU-project CROPS to automatically detect and spray powdery mildew on grape vines controlled by means of a modular manipulator.

TL;DR: A new machine learning method is proposed, which discriminates between crop and weed species relying on their spectral reflectance differences, and suggests active learning by combining novelty detection and incremental class augmentation.

TL;DR: The spectral-spatial classification of high spatial resolution RGB images obtained from unmanned aerial vehicles (UAVs) for detection of tomatoes in the image is presented and it is observed that EM performed better than K-means and SOM.

TL;DR: Results of validation experiments show that combination of AdaBoost classification and colour analysis can correctly detect over 96% of ripe tomatoes in the real-world environment.

TL;DR: In this article, the influence of variation of spectrum measurement position on the near-infrared (NIR) spectroscopy analysis of soluble solids content (SSC) of apple was studied.

TL;DR: In this article, the most practical and effective indices are those based on ground reflectance sensors data which are evaluated in terms of their efficiency in detecting plant water status under greenhouse conditions.

TL;DR: The role and performance of ESM in engineering applications: electric devices, sensors, environmental engineering, biomedical Engineering, biomedical engineering, and commercialization is focused on.

TL;DR: The proposed method of aphid identification and population monitoring based on digital images was easy-to-use and provides efficient and accurate aphid population data, and therefore can be used for aphid infestation surveys in wheat fields.

TL;DR: Different onboard sensor technologies, namely stereovision, LIDAR, radar, and thermography, are considered and novel methods for their combination are proposed to automatically detect obstacles and discern traversable from non-traversable areas.

TL;DR: This paper focuses mainly on locating the spatial coordinates of the cutting points on a peduncle of grape clusters for the end-effector and determining the bounding volume of the grape cluster for the motion planner of the manipulator.

TL;DR: A modular software framework design that allows flexible implementation of eye-in-hand sensing and motion control for agricultural robotics in dense vegetation is reported and results indicated the framework can be implemented for sensing and robot motion control in sweet-pepper using visual information from the end-effector.

TL;DR: 3D surface normal features, 3D plane-reflective symmetry, and image plane highlights from elliptic surface points are combined to provide shape-based detection of fruits in 3D space regardless of their colour.

TL;DR: A rapid and reliable method based on binocular stereo vision was developed with the aim of effectively recognising and locating litchi in the natural environment and showed that the proposed recognition method could be robust against the influences of varying illumination and precisely recognising lITCHi.

TL;DR: In this paper, the authors developed a fast and robust methodology to analyse the biogas production process with respect to the significant process variables using the ant colony optimisation algorithm with the help of ant colony optimization algorithm.

TL;DR: In this article, the authors describe the development and assessment of a robotised patch spraty -20ying system that was devised for site-specific herbicide application in agricultural crops and is capable of working in groups or fleets of autonomous robots.

TL;DR: In this article, the integration of different statistical tools for identifying homogeneous zones based on site covariates is presented, and the analytical process has been illustrated using a rain-fed wheat crop from the Argentine Pampas, with apparent electrical conductivity, elevation and soil depth as master variables for zoning.

TL;DR: In this paper, the dielectric properties of peanuts were measured between 10 and 4500 MHz using an open-ended coaxial-line probe and network analyser at temperatures between 25 and 85°C and moisture contents between 10% and 30% on a wet basis.

TL;DR: In this article, a review on transpiration phenomenon and moisture evolution in packaged fresh horticultural produce is presented, focusing on the role and application of integrative mathematical modelling in describing water relations of fresh fruit and vegetables for packaging design.

TL;DR: In this paper, a perforated air tube with three rows of air jets was designed to provide vertical air flow down to the crop canopy surface, which could help prevent tip burn occurrences in lettuce production.

TL;DR: Experimental results show that the proposed method significantly outperforms other existing methods with an average value of absolute error of 1.14 days on the test dataset, indicating that automatic observation is quite acceptable compared to manual observations.