Evaluating three-pillar sustainability modelling approaches for dairy cattle production systems

Milk production in Europe is facing major challenges to ensure its economic, environmental, and social sustainability. It is essential that holistic concepts are developed to ensure the future sustainability of the sector and to assist farmers and stakeholders in making knowledge-based decisions. In this study, integrated sustainability assessment by means of whole-farm modelling is presented as a valuable approach for identifying factors and mechanisms that could be used to improve the three pillars (3Ps) of sustainability in the context of an increasing awareness of economic profitability, social well-being, and environmental impacts of dairy production systems (DPS). This work aims (i) to create an evaluation framework that enables quantitative analysis of the level of integration of 3P sustainability indicators in whole-farm models and (ii) to test this method. Therefore, an evaluation framework consisting of 35 indicators distributed across the 3Ps of sustainability was used to evaluate three whole-farm models. Overall, the models integrated at least 40% of the proposed indicators. Different results were obtained for each sustainability pillar by each evaluated model. Higher scores were obtained for the environmental pillar, followed by the economic and the social pillars. In conclusion, this evaluation framework was found to be an effective tool that allows potential users to choose among whole-farm models depending on their needs. Pathways for further model development that may be used to integrate the 3P sustainability assessment of DPS in a more complete and detailed way were identified. © 2021 by the authors.This study was financially supported by the German Federal Ministry of Food and Agriculture (BMEL) through the Federal Office for Agriculture and Food (BLE) under grant number 2819ERA08A (MilKey project, funded under the Joint Call 2018 ERA-GAS, SusAn and ICT-AGRI 2 on ?Novel technologies, solutions and systems to reduce the greenhouse gas emissions in animal production systems?). BC3-Research is supported by the Spanish Government through Mar?a de Maeztu excellence accreditation 2018-2022 (Ref. MDM-2017-0714) and by the Basque Government through the BERC 2018-2021 program. Agustin del Prado is financed through the Ramon y Cajal program by the Spanish Ministry of Economy, Industry, and Competitiveness (RYC-2017-22143)

Técnicas emergentes de extracción de β-caroteno para la valorización de subproductos agroindustriales de la zanahoria (Daucus carota L.): una revisión

The objective of this review was to collect, contrast and analyse the conventional and non-conventional extraction techniques to obtain β-carotene from carrot (Daucus carota L.), by conducting a bibliometric analysis of different recent studies and investigations where different approaches, techniques, and findings converge. Similarly, the contribution of green solvents to the extraction process is established to determine its applicability at an industrial scale. Carrots are rich in carotenoids, and especially in β-carotene, a source of provitamin A used as a natural coloring in the food and pharmaceutical industry. Microwave-assisted extraction (MAE), enzyme-assisted extraction (EAE), and Supercritical fluid extraction (SFE) have been evaluated using the carrot and have been compared to conventional solvent extraction techniques (CSE), showing similar and even higher extraction yields and efficiencies. However, ultrasound-assisted extraction (UAE) shows successful and considerably higher results (157.0 mg b-carotene/100 g DB) compared to other non-conventional techniques. Further investigations are required to optimize the extraction conditions and parameters, as well as the evaluation of suitable preservation conditions for both the raw material and the final extract that ensure a higher stability of the end-product, and thus providing a higher extraction yield. Green alternatives should be considered to reduce environmental impact in future extraction processes.El objetivo de la presente revisión es reunir, contrastar y analizar algunas de las técnicas convencionales y no convencionales de extracción de β-caroteno a partir de la zanahoria (Daucus carota L.), a través de un análisis bibliométrico de estudios e investigaciones recientes, en los que confluyen numerosas técnicas, parámetros y hallazgos. Asimismo, establecer las posibles contribuciones de la extracción con solventes verdes para estos procesos, permitiendo su aplicabilidad a escala industrial para el aprovechamiento de los subproductos agroindustriales de este vegetal. La zanahoria es rica en carotenoides, en especial β-caroteno, fuente de provitamina A, utilizada como colorante natural en la industria de alimentos y farmacéutica. La extracción asistida con microondas (MAE por su sigla en inglés), con enzimas (EAE por su sigla en inglés) y en fluidos supercríticos (SFE por su sigla en inglés), han sido evaluadas en la zanahoria y comparadas con las técnicas convencionales de extracción (CSE por su sigla en inglés), encontrando rendimientos y eficiencias similares e incluso superiores. Sin embargo, la extracción asistida con ultrasonido (UAE por su sigla en inglés), muestra resultados satisfactorios y considerablemente mayores (157,0 mg b-caroteno/100 g base seca). Se requieren estudios posteriores para optimizar las condiciones y los parámetros de extracción, y evaluar las condiciones de conservación de la materia prima y del extracto final que aseguren una mayor estabilidad del producto y, por ende, un rendimiento de extracción superior, al igual que considerar alternativas verdes de extracción para reducir el impacto ambiental

Self-assembly as a tool to study microscale curvature and strain-dependent magnetic properties

The extension of 2D ferromagnetic structures into 3D curved geometry enables to tune its magnetic properties such as uniaxial magnetic anisotropy. Tuning the anisotropy with strain and curvature has become a promising ingredient in modern electronics, such as flexible and stretchable magnetoelectronic devices, impedance-based field sensors, and strain gauges, however, has been limited to extended thin films and to only moderate bending. By applying a self-assembly rolling technique using a polymeric platform, we provide a template that allows homogeneous and controlled bending of a functional layer adhered to it, irrespective of its shape and size. This is an intriguing possibility to tailor the sign and magnitude of the surface strain of integrated, micron-sized devices. In this article, the impact of strain and curvature on the magnetic ground state and anisotropy is quantified for thin-film Permalloy micro-scale structures, fabricated on the surface of the tubular architectures, using solely electrical measurements

Comparación de modelos físicos y de inteligencia artificial para predicción de niveles de inundación

La hidrología ha utilizado métodos tradicionales para pronosticar niveles de inundación. Sin embargo, éstos pueden generar problemas de precisión, causados por el comportamiento no lineal de las inundaciones y las limitaciones al no incluir todas las variables, como flujo, y nivel de agua y precipitación. En consecuencia, algunos científicos comenzaron a utilizar métodos no convencionales basados en modelos de inteligencia artificial, pronosticando las inundaciones de manera más precisa y rigurosa. Este artículo presenta una comparación de un modelo de tránsito de flujo unidimensional desarrollado en HEC-RAS y un modelo de inteligencia artificial, basado en redes neuronales artificiales, desarrollado en MatLab, para predecir inundaciones. El análisis de los resultados se llevó a cabo utilizando seis indicadores estadísticos: error absoluto medio (MAE, por su nombre en inglés); error cuadrático medio (MSE); error medio porcentual absoluto (MAPE, por su nombre en inglés); raíz cuadrada de la MSE; coeficiente de correlación de Pearson (CC, por su nombre en inglés), y coeficiente de correlación de concordancia (ρc, por su nombre en inglés). Además, el coeficiente de eficiencia se calculó empleando una herramienta virtual llamada Hydrotest. A partir del análisis se observó en los modelos de pronóstico que el uso de redes neuronales tiene resultados precisos, dada su cercanía con los datos reales: MAPE, entre 11.95 y 12.51; CC, entre 0.90 y 0.92; ρc, entre 0.84 y 0.87, y finalmente un CE más grande que 0.8. El estudio se realizó en una sección de las partes altas del río Bogotá, en Colombia, entre las estaciones hidrológicas de puente Florencia y Tocancipá. Los datos de flujo fueron tomados por la Corporación Autónoma Regional de Cundinamarca (CAR) de septiembre de 2009 a octubre de 2013

Emergent dynamic chirality in a thermally driven artificial spin ratchet

Modern nanofabrication techniques have opened the possibility to create novel functional materials, whose properties transcend those of their constituent elements. In particular, tuning the magnetostatic interactions in geometrically frustrated arrangements of nanoelements called artificial spin ice1, 2 can lead to specific collective behaviour3, including emergent magnetic monopoles4, 5, charge screening6, 7 and transport8, 9, as well as magnonic response10, 11, 12. Here, we demonstrate a spin-ice-based active material in which energy is converted into unidirectional dynamics. Using X-ray photoemission electron microscopy we show that the collective rotation of the average magnetization proceeds in a unique sense during thermal relaxation. Our simulations demonstrate that this emergent chiral behaviour is driven by the topology of the magnetostatic field at the edges of the nanomagnet array, resulting in an asymmetric energy landscape. In addition, a bias field can be used to modify the sense of rotation of the average magnetization. This opens the possibility of implementing a magnetic Brownian ratchet13, 14, which may find applications in novel nanoscale devices, such as magnetic nanomotors, actuators, sensors or memory cells

Monitoring and Scoring Counter-Diffusion Protein Crystallization Experiments in Capillaries by in situ Dynamic Light Scattering

In this paper, we demonstrate the feasibility of using in situ Dynamic Light Scattering (DLS) to monitor counter-diffusion crystallization experiments in capillaries. Firstly, we have validated the quality of the DLS signal in thin capillaries, which is comparable to that obtained in standard quartz cuvettes. Then, we have carried out DLS measurements of a counter-diffusion crystallization experiment of glucose isomerase in capillaries of different diameters (0.1, 0.2 and 0.3 mm) in order to follow the temporal evolution of protein supersaturation. Finally, we have compared DLS data with optical recordings of the progression of the crystallization front and with a simulation model of counter-diffusion in 1D

Transoceanic Dispersal and Subsequent Diversification on Separate Continents Shaped Diversity of the Xanthoparmelia pulla Group (Ascomycota)

In traditional morphology-based concepts many species of lichenized fungi have world-wide distributions. Molecular data have revolutionized the species delimitation in lichens and have demonstrated that we underestimated the diversity of these organisms. The aim of this study is to explore the phylogeography and the evolutionary patterns of the Xanthoparmelia pulla group, a widespread group of one of largest genera of macrolichens. We used a dated phylogeny based on nuITS and nuLSU rDNA sequences and performed an ancestral range reconstruction to understand the processes and explain their current distribution, dating the divergence of the major lineages in the group. An inferred age of radiation of parmelioid lichens and the age of a Parmelia fossil were used as the calibration points for the phylogeny. The results show that many species of the X. pulla group as currently delimited are polyphyletic and five major lineages correlate with their geographical distribution and the biosynthetic pathways of secondary metabolites. South Africa is the area where the X. pulla group radiated during the Miocene times, and currently is the region with the highest genetic, morphological and chemical diversity. From this center of radiation the different lineages migrated by long-distance dispersal to others areas, where secondary radiations developed. The ancestral range reconstruction also detected that a secondary lineage migrated from Australia to South America via long-distance dispersal and subsequent continental radiation

A model species for agricultural pest genomics: the genome of the Colorado potato beetle, Leptinotarsa decemlineata (Coleoptera: Chrysomelidae)

The Colorado potato beetle is one of the most challenging agricultural pests to manage. It has shown a spectacular ability to adapt to a variety of solanaceaeous plants and variable climates during its global invasion, and, notably, to rapidly evolve insecticide resistance. To examine evidence of rapid evolutionary change, and to understand the genetic basis of herbivory and insecticide resistance, we tested for structural and functional genomic changes relative to other arthropod species using genome sequencing, transcriptomics, and community annotation. Two factors that might facilitate rapid evolutionary change include transposable elements, which comprise at least 17% of the genome and are rapidly evolving compared to other Coleoptera, and high levels of nucleotide diversity in rapidly growing pest populations. Adaptations to plant feeding are evident in gene expansions and differential expression of digestive enzymes in gut tissues, as well as expansions of gustatory receptors for bitter tasting. Surprisingly, the suite of genes involved in insecticide resistance is similar to other beetles. Finally, duplications in the RNAi pathway might explain why Leptinotarsa decemlineata has high sensitivity to dsRNA. The L. decemlineata genome provides opportunities to investigate a broad range of phenotypes and to develop sustainable methods to control this widely successful pest