Effects of Cropping System (Organic and Conventional) on the Fiber Quality Index, Spinning Consistency Index and Multiplicative Analytic Hierarchy Process of Cotton (Gossypium hirsutum L.)

Markets for organically produced high quality cotton (Gossypium hirsutum L.) are projected to increase. Field experiments were conducted in Palamas, Karditsa in Central Greece, to compare the effects of two cropping systems on fiber quality of three cotton cultivars. The experiments, conducted during three years, were laid out in a split plot design with four replicates, two main plots (organic and conventional system) and three sub-plots (cotton cultivars). Findings suggest that fiber quality index (FQI), spinning consistency index (SCI) and multiplicative analytic hierarchy process (MAHP) are three indices that could be integrated in a useful protocol for the evaluation of different cropping systems for cotton cultivation. In particular, our results indicate that in general there was not any superiority of conventional compared to the organic cropping system regarding fiber quality as shown by the above mentioned indices. Regarding the length of the cotton fiber, this was positively correlated with micronair and the uniformity index of the cotton fiber. The organic system resulted to higher values of SCI than the ones of the conventional (1547.9 and 1522.3, respectively). The present 3-years study shows that organic cultivation of cotton can ensure high fiber quality and this was clearly confirmed by means of the several important indices

A novel flexible framework with automatic feature correspondence optimization for nonrigid registration in radiotherapy

Technical improvements in planning and dose delivery and in verification of patient positioning have substantially widened the therapeutic window for radiation treatment of cancer. However, changes in patient anatomy during the treatment limit the exploitation of these new techniques. To further improve radiation treatments, anatomical changes need to be modeled and accounted for. Non-rigid registration can be used for this purpose. This paper describes the design, the implementation and the validation of a new framework for non-rigid registration for radiotherapy applications. The core of this framework is an improved version of the Thin Plate Splines Robust Point Matching (TPS-RPM) algorithm. The TPS-RPM algorithm estimates a global correspondence and a transformation between the points that represent organs of interest belonging to two image sets. However, the algorithm does not allow for the inclusion of prior knowledge on the correspondence of subset of points and therefore, it can lead to inconsistent anatomical solutions. In this paper TPS-RPM was improved by employing a novel correspondence filter that supports simultaneous registration of multiple structures. The improved method allows for coherent organ registration and for the inclusion of user defined landmarks, lines and surfaces inside and outside of structures of interest. A procedure to generate control points form segmented organs is described. The framework parameters r and ?, which control the number of points and the non-rigidness of the transformation respectively, were optimized for three sites with different degrees of deformation: head and neck, prostate and cervix, using two cases per site. For the head and neck cases, the salivary glands were manually contoured on CT-scans, for the prostate cases the prostate and the vesicles, and for the cervix cases the cervix-uterus, the bladder and the rectum. The transformation error obtained using the best set of parameters was below 1 mm for all the studied cases. The length of the deformation vectors were on average (± 1 standard deviation) 5.8 ± 2.5 and 2.6 ± 1.1 mm for the head and neck cases, 7.2 ± 4.5 and 8.6 ± 1.9 mm for the prostate cases, and 19.0 ± 11.6 and 14.5 ± 9.3 mm for the cervix cases. Distinguishable anatomical features were identified for each case, and were used to validate the registration by calculating residual distances after transformation: 1.5 ± 0.8, 2.3 ± 1.0 and 6.3 ± 2.9 mm for the head and neck, prostate and cervix sites respectively. Finally, we demonstrated how the inclusion of these anatomical features in the registration process reduced the residual distances to 0.8 ± 0.5, 0.6 ± 0.5 and 1.3 ± 0.7 mm for the head and neck, prostate and cervix sites respectively. The inclusion of additional anatomical features produced more anatomically coherent transformations without compromising the transformation error. We concluded that the presented non-rigid registration framework is a powerful tool to simultaneously register multiple segmented organs with very different complexity

Healthier and Sustainable Food Systems: Integrating Underutilised Crops in a ‘Theory of Change Approach’

Increasingly, consumers are paying attention to healthier food diets, “healthy” food attributes (such as “freshness”, “naturalness” and “nutritional value”), and the overall sustainability of production and processing methods. Other significant trends include a growing demand for regional and locally produced/supplied and less processed food. To meet these demands, food production and processing need to evolve to preserve the raw material and natural food properties while ensuring such sustenance is healthy, tasty, and sustainable. In parallel, it is necessary to understand the influence of consumers’ practices in maintaining the beneficial food attributes from purchasing to consumption. The whole supply chain must be resilient, fair, diverse, transparent, and economically balanced to make different food systems sustainable. This chapter focuses on the role of dynamic value chains using biodiverse, underutilised crops to improve food system resilience and deliver foods with good nutritional and health properties while ensuring low environmental impacts, and resilient ecosystem functions.This research was supported by the European Union’s Horizon 2020 Research and Innovation Programme through the project “Realising Dynamic Value Chains for Underutilised Crops” (RADIANT), Grant Agreement number 101000622. The authors would also like to thank the scientific collaboration under the FCT project UIDB/50016/2020. in. The James Hutton Institute (CH and PPMI) are supported by the “Rural and Environmental Science and Analytical Services” (RESAS), a Division of the Scottish Government.Peer reviewe

A machine-vision quality inspection system for textile industries supported by parallel multitransputer architecture

A machine-vision based quality inspection system which can be applied for textile inspection is presented. The design of the system increases the speed and improves the quality assurance performance of the inspection. It is implemented on a multitransputer parallel architecture. © 1990

Image recognition and neuronal networks: Intelligent systems for the improvement of imaging information

Intelligent computerised systems can provide useful assistance to the physician in the rapid identification of tissue abnormalities and accurate diagnosis in real-time. This paper reviews basic issues in medical imaging and neural network-based systems for medical image interpretation. In the framework of intelligent systems, a simple scheme that has been implemented is presented as an example of the use of intelligent systems to discriminate between normal and cancerous regions in colonoscopic images. Preliminary results indicate that this scheme is capable of high accuracy detection of abnormalities within the image. It can also be successfully applied to different types of images, to detect abnormalities that belong to different cancer types