Use of very high-resolution airborne images to analyse 3d canopy architecture of a vineyard

Differencing between green cover and grape canopy is a challenge for vigour status evaluation in viticulture. This paper presents the acquisition methodology of very high-resolution images (4 cm), using a Sensefly Swinglet CAM unmanned aerial vehicle (UAV) and their processing to construct a 3D digital surface model (DSM) for the creation of precise digital terrain models (DTM). The DTM was obtained using python processing libraries. The DTM was then subtracted to the DSM in order to obtain a differential digital model (DDM) of a vineyard. In the DDM, the vine pixels were then obtained by selecting all pixels with an elevation higher than 50 [cm] above the ground level. The results show that it was possible to separate pixels from the green cover and the vine rows. The DDM showed values between −0.1 and + 1.5 [m]. A manually delineation of polygons based on the RGB image belonging to the green cover and to the vine rows gave a highly significant differences with an average value of 1.23 [m] and 0.08 [m] for the vine and the ground respectively. The vine rows elevation is in good accordance with the topping height of the vines 1.35 [m] measured on the field. This mask could be used to analyse images of the same plot taken at different times. The extraction of only vine pixels will facilitate subsequent analyses, for example, a supervised classification of these pixels

Calystegine degradation capacities of microbial rhizosphere communities of Zea mays (calystegine-negative) and Calystegia sepium (calystegine-positive)

Calystegines are tropane alkaloids produced by the roots of a few plant species. A bioassay was developed to identify roots with a microbial rhizosphere community capable of calystegine degradation (i.e. MCD roots). In a field survey, the proportion of MCD roots of Zea mays (calystegine-negative) varied from 20 to 80%. In field experiments, the proportions of MCD roots of Z. mays and Calystegia sepium (calystegine-positive) grown in a particular plot were similar to each other but varied with time and, overall, were higher than those of Z. mays roots from adjacent plots free of C. sepium. In autoclaved soil, no root of C. sepium or Z. mays plants propagated as seeds was MCD, indicating that calystegine-degrading microorganisms were not seed-borne. However, MCD roots were found as early as 1 day after planting of rhizomes of C. sepium in autoclaved soil or planting of axenic seedlings of either plant in natural soil microcosms. In total, microorganisms capable of degrading calystegines were harboured not only in the rhizosphere of the calystegine-producing plant but also in that of the calystegine-negative plant and probably in bulk soi

Large temporal variations of functional properties of outdoor equestrian arena surfaces and a new concept of evaluating reactivity with light weight deflectometer settlement curves

Sports physiological properties of ten sand or sand-mineral outdoor arenas, five with vertical drainage systems and five with an ebb and flow like system were assessed over a period of eight weeks. For each arena, the riding zone was spatially delineated, nine locations at medium to intensely used zones were selected by simple random sampling and used along the whole measurement period. A total of 72 values for the dynamic deflection modulus (Evd), attenuation (s/v), settlement (s) and moisture content (Vol %) were analyzed for each arena. A novel technique to analyze the settlement curves of the light weight deflectometer (LWD) to describe reactivity of the footing surface was introduced. Statistical testing was done by linear mixed models. Three of the five arenas with a vertical watering system were judged to be hard (Evd > 20 MN/m2), whereas all five arenas with an ebb and flow like watering systems were medium hard (Evd = 10-20 MN/m2) over the entire eight weeks. Significant (p<0.01) temporal differences in Evd, s/v and moisture were demonstrated for both watering systems; however, the spatial and temporal variations were much lower with the ebb-flow system. Temporal consistency in the parameters over the test weeks appeared to be a criterion for stability of the arena surface. The analysis of the settlement curves of the LWD showed that the slope symmetry has a large potential to describe the restoration of the energy of an equestrian surface than only the settlement, which requires further validation

Augmenting a convolutional neural network with local histograms ::a case study in crop classification from high-resolution UAV imagery

The advent of affordable drones capable of taking high resolution images of agricultural fields creates new challenges and opportunities in aerial scene understanding. This paper tackles the problem of recognizing crop types from aerial imagery and proposes a new hybrid neural network architecture which combines histograms and convolutional units. We evaluate the performance of the proposed model on a 23-class classification task and compare it to other models. The result is an improvement of the classification performance

Fourier Disentangled Multimodal Prior Knowledge Fusion for Red Nucleus Segmentation in Brain MRI

Early and accurate diagnosis of parkinsonian syndromes is critical to provide appropriate care to patients and for inclusion in therapeutic trials. The red nucleus is a structure of the midbrain that plays an important role in these disorders. It can be visualized using iron-sensitive magnetic resonance imaging (MRI) sequences. Different iron-sensitive contrasts can be produced with MRI. Combining such multimodal data has the potential to improve segmentation of the red nucleus. Current multimodal segmentation algorithms are computationally consuming, cannot deal with missing modalities and need annotations for all modalities. In this paper, we propose a new model that integrates prior knowledge from different contrasts for red nucleus segmentation. The method consists of three main stages. First, it disentangles the image into high-level information representing the brain structure, and low-frequency information representing the contrast. The high-frequency information is then fed into a network to learn anatomical features, while the list of multimodal low-frequency information is processed by another module. Finally, feature fusion is performed to complete the segmentation task. The proposed method was used with several iron-sensitive contrasts (iMag, QSM, R2*, SWI). Experiments demonstrate that our proposed model substantially outperforms a baseline UNet model when the training set size is very small

Erhöhte Humusvorräte in einem siebenjährigen Agroforstsystem in der Zentralschweiz

Moderne Agroforstsysteme haben das Potenzial, eine produktive Landwirtschaft mit verbesserter Erreichung der «Umweltziele Landwirtschaft» zu verbinden. Diese Systeme werden in der Schweiz allerdings erst seit kurzem von wenigen Landwirten getestet, daher liegen bisher kaum Daten zu den Umweltwirkungen von modernen Agroforstsystemen vor. In dieser Studie untersuchten wir, wie sich die Humusvorräte in einem siebenjährigen Agroforstsystem in der Zentralschweiz verändert haben. Unsere Resultate zeigen, dass bereits nach sieben Jahre eine substanzielle Humusanreicherung (+18 %) in der Baumreihe verglichen mit der kultivierten Fläche zu beobachten ist. Erstaunlicherweise beschränkte sich die Humusanreicherung nicht nur auf den Oberboden, sondern konnte auch bis in eine Tiefe von 60 cm nachgewiesen werden. Eine erste Schätzung der jährlichen Humusanreicherung in der untersuchten Agroforstparzelle beträgt 0,86 t Kohlenstoff pro Hektare und Jahr beziehungsweise 91 kg Stickstoff pro Hektare und Jahr für die Bodentiefe 0–60 cm. Die Magnitude dieser ersten Schätzung zeigt, dass die weitere Erforschung der Humusdynamik in Agroforstsystemen aus Sicht des Boden-, Klima- und Gewässerschutzes von grosser Bedeutung ist

ESPEN Guideline: clinical nutrition in inflammatory bowel disease

Crohn’s disease; Ulcerative colitis; Nutritional therapyMalaltia de Crohn; Colitis ulcerosa; Teràpia nutricionalEnfermedad de Crohn; Colitis ulcerosa; Terapia nutricionalIntroduction: the ESPEN Guideline offers a multidisciplinary focus on clinical nutrition in inflammatory bowel disease (IBD). Methodology: the guideline is based on a extensive systematic review of the literature, but relies on expert opinion when objective data are lacking or inconclusive. The conclusions and 64 recommendations have been subject to full peer review and a Delphi process, in which uniformly positive responses (agree or strongly agree) were required. Results: IBD is increasingly common and potential dietary factors in its etiology are briefly reviewed. Malnutrition is highly prevalent in IBD — especially in Crohn’s disease. Increased energy and protein requirements are observed in some patients. The management of malnutrition in IBD is considered within the general context of support for malnourished patients. Treatment of iron deficiency (parenterally, if necessary) is strongly recommended. Routine provision of a special diet in IBD is not, however, supported. Parenteral nutrition is indicated only when enteral nutrition has failed or is impossible. The recommended perioperative management of patients with IBD undergoing surgery accords with general ESPEN guidance for patients having abdominal surgery. Probiotics may be helpful in UC but not in Crohn’s disease. Primary therapy using nutrition to treat IBD is not supported in ulcerative colitis but is moderately well supported in Crohn’s disease, especially in children, where the adverse consequences of steroid therapy are proportionally greater. However, exclusion diets are generally not recommended and there is little evidence to support any particular formula feed when nutritional regimens are constructed. Conclusions: available objective data to guide nutritional support and primary nutritional therapy in IBD are presented as 64 recommendations, of which 9 are very strong recommendations (grade A), 22 are strong recommendations (grade B), and 12 are based only on sparse evidence (grade 0); 21 recommendations are good practice points (GPP).Introducción: la guía ESPEN ofrece un enfoque multidisciplinar de la nutrición clínica en la enfermedad inflamatoria intestinal (EII). Metodología: la guía se basa en una extensa revisión sistemática de la literatura y en la opinión de expertos cuando faltan datos objetivos o estos no son concluyentes. Las conclusiones y las 64 recomendaciones han sido objeto de una revisión completa por pares y de un proceso Delphi en el que se requerían respuestas fuertemente positivas (de acuerdo o totalmente de acuerdo). Resultados: la EII es cada vez más común y se revisan brevemente los posibles factores dietéticos en su etiología. La desnutrición es muy prevalente en la EII, especialmente en la enfermedad de Crohn. En algunos pacientes se observan mayores requerimientos de energía y proteínas. El manejo de la desnutrición en la EII se considera dentro del contexto general de apoyo a los pacientes desnutridos. Se recomienda fuertemente el tratamiento de la deficiencia de hierro (por vía parenteral, si es necesario). Sin embargo, no se aconseja la prescripción de rutina de una dieta especial en la EII. La nutrición parenteral está indicada solo cuando la nutrición enteral ha fallado o es imposible. El manejo perioperatorio recomendado de los pacientes con EII sometidos a cirugía se hace de acuerdo con la guía general de la ESPEN para pacientes sometidos a cirugía abdominal. Los probióticos pueden ser útiles en la CU pero no en la enfermedad de Crohn. El tratamiento primario con nutrición para tratar la EII no está respaldado en la colitis ulcerosa, aunque está moderadamente bien soportado en la enfermedad de Crohn, especialmente en los niños, donde las consecuencias adversas de la terapia con esteroides son proporcionalmente mayores. Sin embargo, las dietas de exclusión generalmente no se recomiendan y hay poca evidencia que respalde cualquier fórmula de nutrición en particular cuando se realizan regímenes nutricionales. Conclusiones: los datos objetivos disponibles para guiar el apoyo nutricional y la terapia nutricional primaria en la EII se presentan como 64 recomendaciones, de las cuales 9 son recomendaciones muy fuertes (grado A), 22 son recomendaciones fuertes (grado B) y 12 se basan solo en evidencia escasa (grado 0); 21 recomendaciones son recomendaciones de buenas prácticas (GPP).El proceso de la guía ha sido financiado exclusivamente por la ESPEN

Predicting the Progression of Mild Cognitive Impairment Using Machine Learning: A Systematic and Quantitative Review

Context. Automatically predicting if a subject with Mild Cognitive Impairment (MCI) is going to progress to Alzheimer's disease (AD) dementia in the coming years is a relevant question regarding clinical practice and trial inclusion alike. A large number of articles have been published, with a wide range of algorithms, input variables, data sets and experimental designs. It is unclear which of these factors are determinant for the prediction, and affect the predictive performance that can be expected in clinical practice. We performed a systematic review of studies focusing on the automatic prediction of the progression of MCI to AD dementia. We systematically and statistically studied the influence of different factors on predictive performance. Method. The review included 172 articles, 93 of which were published after 2014. 234 experiments were extracted from these articles. For each of them, we reported the used data set, the feature types (defining 10 categories), the algorithm type (defining 12 categories), performance and potential methodological issues. The impact of the features and algorithm on the performance was evaluated using t-tests on the coefficients of mixed effect linear regressions. Results. We found that using cognitive, fluorodeoxyglucose-positron emission tomog-raphy or potentially electroencephalography and magnetoencephalography variables significantly improves predictive performance compared to not including them (p=0.046, 0.009 and 0.003 respectively), whereas including T1 magnetic resonance imaging, amyloid positron emission tomography or cerebrospinal fluid AD biomarkers does not show a significant effect. On the other hand, the algorithm used in the method does not have a significant impact on performance. We identified several methodological issues. Major issues, found in 23.5% of studies, include the absence of a test set, or its use for feature selection or parameter tuning. Other issues, found in 15.0% of studies, pertain to the usability of the method in clinical practice. We also highlight that short-term predictions are likely not to be better than predicting that subjects stay stable over time. Finally, we highlight possible biases in publications that tend not to publish methods with poor performance on large data sets, which may be censored as negative results. Conclusion. Using machine learning to predict MCI to AD dementia progression is a promising and dynamic field. Among the most predictive modalities, cognitive scores are the cheapest and less invasive, as compared to imaging. The good performance they offer question the wide use of imaging for predicting diagnosis evolution, and call for further exploring fine cognitive assessments. Issues identified in the studies highlight the importance of establishing good practices and guidelines for the use of machine learning as a decision support system in clinical practice

Utilisation d'images à très haute résolution pour quantifier l'érosion et proposer des mesures préventives ciblées

L’érosion hydrique est, avec le tassement et la pollution au cuivre, l’une des causes majeures de dégradation des sols viticoles en Suisse. Il est maintenant bien connu que l’érosion diminue à long terme leur fertilité (Vanwalleghema et al., 2017), qu’elle contribue à la charge des eaux de surface en sédiments et en intrants tels que pesticides et Cu (Fulda et al., 2015). Bien qu’en Suisse, l’interrang des vignes soit souvent enherbé, l’érosion reste un problème 1) au niveau du cavaillon, généralement travaillé ou désherbé, 2) lors de replantations et 3) sur les sols sensibles (peu profonds) entièrement désherbés. Les phénomènes érosifs sont accentués par les sols en pentes ainsi qu’une texture souvent limoneuse, peu cohésive (Zufferey et Murisier, 2004). La quantification du volume de terre érodée permet de déterminer la dégradation spécifique liée à l’érosion qui est la quantité de terre perdue. Les méthodes utilisées jusqu’à présent pour estimer le volume de terre érodée sont par exemple, selon Prasuhn et Fischler (2007), la mesure sur la longueur de la rigole, de sections transversales à intervalles réguliers (de 1 à 4 m), où est mesurée la largeur au point d’inflexion et au fond et la profondeur en trois points. Une autre méthode est celle de Brenot et al. (2008) qui consiste à mesurer la distance entre le sol et le greffon. Ainsi, il est possible d’estimer la quantité de terre érodée depuis l’année de plantation. Ces deux méthodes ont cependant le désavantage d’être généralement gourmandes en temps (Nachtergaele et Poesen, 1999). L‘accès aux drones à des prix relativement bas et l’obtention d’images ainsi que de modèles numériques de surface (MNS) à très haute résolution permettent dorénavant de suivre les phénomènes d’érosion hydrique (Klaus et al., 2014 ; d’Oleire-Oltmanns et al., 2012 ; Pineux et al., 2017). La méthode présentée ici combine ces nouveaux outils

Calystegine degradation capacities of microbial rhizosphere communities of Zea mays (calystegine-negative) and Calystegia sepium (calystegine-positive)

ISSN:0168-6496ISSN:1574-694