What makes a citrus farmer go 'organic'? Empirical evidence from Spanish citrus farming

Organic farming is increasing its share of total world food output and receiving growing support from policymakers concerned with agricultural sustainability issues. This paper studies the characteristics of citrus farmers in the Spanish region of Valencia that affect their probability of becoming organic farmers. A fair understanding of these characteristics may help policymakers improve the design of agricultural policies aimed at supporting organic citrus practices. As regards the methodology, a probit model is estimated with information from a sample of conventional and organic citrus farmers obtained from a survey designed for a larger research project aimed at analysing Valencian citrus farming. Our main finding is that university education and agricultural professional training both increase the probability of becoming an organic farmer. Conversely, older farmers, farmers selling their production to foreign markets and those with larger farms and/or managing family farms are less likely to adopt organic citrus farming. The main policy implication is that, in order to support organic citrus production, more attention needs to be paid to improving farmers' technical training and education

Sub-seasonal Prediction of Central European Summer Heatwaves with Linear and Random Forest Machine Learning Models

Heatwaves are extreme near-surface temperature events that can have substantial impacts on ecosystems and society. Early Warning Systems help to reduce these impacts by helping communities prepare for hazardous climate-related events. However, state-of-the-art prediction systems can often not make accurate forecasts of heatwaves more than two weeks in advance, which are required for advance warnings. We therefore investigate the potential of statistical and machine learning methods to understand and predict central European summer heatwaves on timescales of several weeks. As a first step, we identify the most important regional atmospheric and surface predictors based on previous studies and supported by a correlation analysis: 2-m air temperature, 500-hPa geopotential, precipitation, and soil moisture in central Europe, as well as Mediterranean and North Atlantic sea surface temperatures, and the North Atlantic jet stream. Based on these predictors, we apply machine learning methods to forecast two targets: summer temperature anomalies and the probability of heatwaves for 1–6 weeks lead time at weekly resolution. For each of these two target variables, we use both a linear and a random forest model. The performance of these statistical models decays with lead time, as expected, but outperforms persistence and climatology at all lead times. For lead times longer than two weeks, our machine learning models compete with the ensemble mean of the European Centre for Medium-Range Weather Forecasts’ hindcast system. We thus show that machine learning can help improve sub-seasonal forecasts of summer temperature anomalies and heatwaves

Assessing conventional and organic citrus farming systems eco-efficiency: a metafrontier directional distance function approach using Life Cycle Analysis

[EN] In this paper, the eco‐efficiency of citrus farms operating under two different conventional and organic technological systems is analyzed. The methodology combines Life Cycle Analysis (LCA), to estimate the environmental impacts associated with the production process, and Data Envelopment Analysis(DEA) to estimate the position of each holding in relation to a frontier formed by the best farming practices. The use of the directional distance function concept allows us to calculate farms’eco‐efficiency scoring with respect to specific environmental impacts, and not only for the whole of them. The metafrontier concept is also used in order to compare the relative eco‐efficiency of each of the two cultivation technologies used. Our results show a wide superiority of the organic farming system in relation to the conventional. An eco‐efficient('green') organic technology represents, in relation to an eco‐efficient use of conventional citrus cultivation techniques, a potential reduction of environmental impacts by 80% without worsening economic performance. In contrast, when the performance of organic and conventional citrus farms is only analyzed in relation to best practices within each system, average eco-efficiency scores are similar for both types of farms.[ES] En este trabajo se analiza la eco-eficiencia de explotaciones citrícolas que operan bajo dos sistemas tecnológicos diferentes, convencional y orgánico. La metodología empleada combina el Análisis del Ciclo de Vida, para estimar los impactos ambientales vinculados al proceso de producción, y el Análisis Envolvente de Datos, para calcular la posición de cada explotación en relación a una frontera formada por las mejores prácticas observadas. Se hace uso del concepto de función distancia direccional, lo que permite estimar la eco-eficiencia con respecto a impactos ambientales concretos, y no sólo para el conjunto de todos ellos. Se emplea también el concepto de metafrontera, al objeto de comparar la eco-eficiencia relativa de cada una de las dos tecnologías empleadas. Los resultados obtenidos muestran una amplia superioridad del sistema de cultivo orgánico en relación al convencional. Un uso eco-eficiente de la tecnología orgánica ('ecológica') representa, en relación a un empleo eco-eficiente de las técnicas de la citricultura convencional, un potencial de reducción de los impactos ambientales del 80% sin empeorar los resultados económicos. En cambio, cuando el comportamiento de las explotaciones citrícolas orgánicas y convencionales se analiza solamente en relación a las mejores prácticas dentro de cada sistema los resultados medios en términos de eco-eficiencia son similares para ambos tipos de explotación.Beltrán Esteve, M.; Reig Martinez, E.; Estruch Guitart, V. (2015). Assessing conventional and organic citrus farming systems eco-efficiency: a metafrontier directional distance function approach using Life Cycle Analysis. Working Papers in Applied Economics. (1501):1-27. http://hdl.handle.net/10251/78996S127150

A dry electrophysiology electrode using CNT arrays

We describe the concept of a dry electrode sensor for biopotential measurement applications (ENOBIO) designed to eliminate the noise and inconvenience associated to the use of electrolytic gel. ENOBIO uses nanotechnology to remove gel-related noise, as well as maintaining a good contact impedance to minimise interference noise. The contact surface of the electrode will be covered with an array/forest of carbon nanotubes and will also be tested with an Ag/AgCl coating to provide ionic-electronic transduction. The nanotubes are to penetrate the outer layers of the skin, the Stratum Corneum, improving electrical contact. We discuss requirements, skin properties, nanotube penetration and transduction, noise sources, prototype design logic and biocompatibility. A future paper will report test results.Comment: Submitted to Sensors and Actuators, Proceedings of Eurosensors XIX, Barcelona, Spain, 2005. Figure 2 corrected, references correcte

Ionic self-complementarity induces amyloid-like fibril formation in an isolated domain of a plant copper metallochaperone protein

BACKGROUND: Arabidopsis thaliana copper metallochaperone CCH is a functional homologue of yeast antioxidant ATX1, involved in cytosolic copper transport. In higher plants, CCH has to be transported to specialised cells through plasmodesmata, being the only metallochaperone reported to date that leaves the cell where it is synthesised. CCH has two different domains, the N-terminal domain conserved among other copper-metallochaperones and a C-terminal domain absent in all the identified non-plant metallochaperones. The aim of the present study was the biochemical and biophysical characterisation of the C-terminal domain of the copper metallochaperone CCH. RESULTS: The conformational behaviour of the isolated C-domain in solution is complex and implies the adoption of mixed conformations in different environments. The ionic self-complementary peptide KTEAETKTEAKVDAKADVE, derived from the C-domain of CCH, adopts and extended conformation in solution with a high content in β-sheet structure that induces a pH-dependent fibril formation. Freeze drying electron microscopy studies revealed the existence of well ordered amyloid-like fibrils in preparations from both the C-domain and its derivative peptide. CONCLUSION: A number of proteins related with copper homeostasis have a high tendency to form fibrils. The determinants for fibril formation, as well as the possible physiological role are not fully understood. Here we show that the plant exclusive C-domain of the copper metallochaperone CCH has conformational plasticity and forms fibrils at defined experimental conditions. The putative influence of these properties with plant copper delivery will be addressed in the future

ENOBIO - First Tests of a Dry Electrophysiology Electrode Using Carbon Nanotubes

We describe the development and first tests of ENOBIO, a dry electrode sensor concept for biopotential applications. In the proposed electrodes the tip of the electrode is covered with a forest of multi-walled Carbon Nanotubes (CNTs) that can be coated with Ag/AgCl to provide ionic–electronic transduction. The CNT brushlike structure is to penetrate the outer layers of the skin improving electrical contact as well as increase the contact surface area. In this paper we report the results of the first tests of this concept—immersion on saline solution and pig skin signal detection. These indicate performance on a par with state of the art researchoriented wet electrodes.</p

Spanish version of the Dundee Ready Education Environment Measure (DREEM) applied to undergraduate physical therapy students in Spain using Google Form

[Intro] The educational climate (EC) is an important factor in determining the effectiveness and success of the curriculum in a school of medical sciences. The Dundee Ready Education Environment Measure (DREEM) questionnaire was used to assess EC in a competency-based curriculum in the physical therapy program analyzing the mean total, subscale, and item scores, as well as response rates. To carry out a psychometric evaluation of the Spanish-language version of the DREEM applied to undergraduate physical therapy students, a total of 671 students enrolled on Degrees in Physiotherapy at 22 faculties across public and private universities in Spainresponded to the DREEM questionnaire using Google Form. (...

Doha agreement meeting on terminology and definitions in groin pain in athletes.

BACKGROUND: Heterogeneous taxonomy of groin injuries in athletes adds confusion to this complicated area. AIM: The 'Doha agreement meeting on terminology and definitions in groin pain in athletes' was convened to attempt to resolve this problem. Our aim was to agree on a standard terminology, along with accompanying definitions. METHODS: A one-day agreement meeting was held on 4 November 2014. Twenty-four international experts from 14 different countries participated. Systematic reviews were performed to give an up-to-date synthesis of the current evidence on major topics concerning groin pain in athletes. All members participated in a Delphi questionnaire prior to the meeting. RESULTS: Unanimous agreement was reached on the following terminology. The classification system has three major subheadings of groin pain in athletes: 1. Defined clinical entities for groin pain: Adductor-related, iliopsoas-related, inguinal-related and pubic-related groin pain. 2. Hip-related groin pain. 3. Other causes of groin pain in athletes. The definitions are included in this paper. CONCLUSIONS: The Doha agreement meeting on terminology and definitions in groin pain in athletes reached a consensus on a clinically based taxonomy using three major categories. These definitions and terminology are based on history and physical examination to categorise athletes, making it simple and suitable for both clinical practice and research