Banker plants and landscape composition influence colonisation precocity of tomato greenhouses by mirid predators

Journal of Pest Science - Conservation biological control involves manipulation of the environment to enhance the effectiveness of natural enemies in controlling crop pests. In this study, we...     

Intracorneal hemorrhage in 19 dogs (22 eyes) from 2000 to 2010: a retrospective study

Objective The aim of this retrospective study is to review clinical data on patients that suffered intracorneal hemorrhage (ICH), and the veterinary and human literature available for this condition. Animal Studied A search for ICH was performed within the clinical database of the Animal Health Trust. Nineteen cases were identified (22 eyes). Procedures The patient’s age, breed, and gender were reviewed, together with etiology, location, treatment, and follow‐up. The relevant data were compared with the Animal Health Trust (AHT) ophthalmology referral population for the same period of time (n = 5555). Results Twenty‐two eyes were affected. No breed or sex predisposition could be identified. Patients aged 10 years and above were more frequently affected when compared with the AHT ophthalmology referral population. ICH was recorded in all corneal quadrants, with the mid‐peripheral cornea more often affected. Areas of corneas affected by the ICH showed long‐term loss of transparency. Ocular diseases as a source of neovascularization varied from ocular surface to intraocular disease. Systemic diseases were investigated in some patients, and no concomitant disease could be linked to the development of ICH. Conclusions Intracorneal hemorrhage is a rare condition associated with corneal neovasculature. As in the human ophthalmology literature, ICH could not be linked to a specific ocular or systemic disease. Severe complications described in humans with this condition, such as pupillary block or corneal perforation, were not seen in any of these canine patients. Canine ICH seem to reabsorb with time, with or without medical treatment. Surgical treatment was not required in any of our patients.     

Fine-grained recognition of plants from images

Background

Fine-grained recognition of plants from images is a challenging computer vision task, due to the diverse appearance and complex structure of plants, high intra-class variability and small inter-class differences. We review the state-of-the-art and discuss plant recognition tasks, from identification of plants from specific plant organs to general plant recognition “in the wild”.

Results

We propose texture analysis and deep learning methods for different plant recognition tasks. The methods are evaluated and compared them to the state-of-the-art. Texture analysis is only applied to images with unambiguous segmentation (bark and leaf recognition), whereas CNNs are only applied when sufficiently large datasets are available. The results provide an insight in the complexity of different plant recognition tasks. The proposed methods outperform the state-of-the-art in leaf and bark classification and achieve very competitive results in plant recognition “in the wild”.

Conclusions

The results suggest that recognition of segmented leaves is practically a solved problem, when high volumes of training data are available. The generality and higher capacity of state-of-the-art CNNs makes them suitable for plant recognition “in the wild” where the views on plant organs or plants vary significantly and the difficulty is increased by occlusions and background clutter.

     

The peculiarities of new textile hand evaluation method

The paper presents information concerning metrological and technical characteristics of KTU-Griff-Tester device, the optimization of its parameters and the cases of its application. It was defined that the behaviour of textile material during its extraction through a rounded hole depends upon its structure. Variations of geometrical shape of woven and knitted specimens can be described by mathematical expressions of shortened epicycloids and Cassini ovals. It is shown that waving process of disc shaped specimen can be predicted on the basis of the law of sine curve. The examples of textiles treatment with different types of commercial softeners are presented, herewith showing the suitability (sensitiveness) of the new device to detect the changes of textile hand. Meantime it is shown that the level of materials anisotropy can be decided on the basis of transformations of specimen’s geometrical shape.