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28 resultados, página 3 de 3

Multicriteria assessment of alternative cropping systems at farm level. A case with maize on family farms of South East Asia

Santiago Lopez-Ridaura (2023, [Artículo])

CONTEXT: Integration of farms into markets with adoption of maize as a cash crop can significantly increase income of farms of the developing world. However, in some cases, the income generated may still be very low and maize production may also have strong negative environmental and social impacts. OBJECTIVE: Maize production in northern Laos is taken as a case to study how far can farms' performance be improved with improved crop management of maize with the following changes at field level: good timing and optimal soil preparation and sowing, allowing optimal crop establishment and low weed infestation. METHODS: We compared different farm types' performance on locally relevant criteria and indicators embodying the three pillars of sustainability (environmental, economic and social). An integrated assessment approach was combined with direct measurement of indicators in farmers' fields to assess eleven criteria of local farm sustainability. A bio-economic farm model was used for scenario assessment in which changes in crop management and the economic environment of farms were compared to present situation. The farm model was based on mathematical programming maximizing income under constraints related to i) household composition, initial cash and rice stocks and land type, and ii) seasonal balances of cash, labour and food. The crop management scenarios were built based on a diagnosis of the causes of variations in the agronomic and environmental performances of cropping systems, carried out in farmers' fields. RESULTS AND CONCLUSIONS: Our study showed that moderate changes in crop management on maize would improve substantially farm performance on 4 to 6 criteria out of the 11 assessed, depending on farm types. The improved crop management of maize had a high economic attractiveness for every farm type simulated (low, medium and high resource endowed farms) even at simulated production costs more than doubling current costs of farmers' practices. However, while an improvement of the systems performance was attained in terms of agricultural productivity, income generation, work and ease of work, herbicide leaching, improved soil quality and nitrogen balance, trade-offs were identified with other indicators such as erosion control and cash outflow needed at the beginning of the cropping season. SIGNIFICANCE: Using farm modelling for multicriteria assessment of current and improved maize cropping systems for contrasted farm types helped capture main opportunities and constraints on local farm sustainability, and assess the trade-offs that new options at field level may generate at farm level.

Bio-Economic Farm Model Smallholder Farms CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CASH CROPS INDICATORS SMALLHOLDERS CROPPING SYSTEMS MAIZE

A Novel Technique for Classifying Bird Damage to Rapeseed Plants Based on a Deep Learning Algorithm.

Ali Mirzazadeh Afshin Azizi Yousef Abbaspour_Gilandeh José Luis Hernández-Hernández Mario Hernández Hernández Iván Gallardo Bernal (2021, [Artículo])

Estimation of crop damage plays a vital role in the management of fields in the agricultura sector. An accurate measure of it provides key guidance to support agricultural decision-making systems. The objective of the study was to propose a novel technique for classifying damaged crops based on a state-of-the-art deep learning algorithm. To this end, a dataset of rapeseed field images was gathered from the field after birds¿ attacks. The dataset consisted of three classes including undamaged, partially damaged, and fully damaged crops. Vgg16 and Res-Net50 as pre-trained deep convolutional neural networks were used to classify these classes. The overall classification accuracy reached 93.7% and 98.2% for the Vgg16 and the ResNet50 algorithms, respectively. The results indicated that a deep neural network has a high ability in distinguishing and categorizing different image-based datasets of rapeseed. The findings also revealed a great potential of Deep learning-based models to classify other damaged crops.

rapeseed classification damaged crops deep neural networks INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ALIMENTOS

Modelado y acoplamiento de la conductividad eléctrica e hidráulica a partir de tomografía de rocas

Modeling and coupling of electrical and hydraulic conductivity from rock tomography

Miguel Ángel Martínez Rodríguez (2022, [Tesis de maestría])

En este trabajo se emplearon técnicas de modelado numérico para simular el flujo de corriente eléctrica y de fluido a través de medios porosos con el fin de determinar el factor de resistividad y la permeabilidad, así como la distribución de los campos de densidad de corriente eléctrica y velocidad de flujo. Para el modelado de flujo eléctrico se desarrolló un algoritmo basado en diferencias finitas, mientras que para el modelado hidráulico se empleó una librería reportada en la literatura, basada en el método de redes de Boltzmann. En ambos esquemas de modelado se establecieron condiciones en la frontera poro-grano para modelar los procesos físicos exclusivamente en el espacio poroso. Los valores estimados de factor de resistividad y de permeabilidad, así como la porosidad, se emplearon para estudiar las correlaciones entre estas propiedades a través de relaciones petrofísicas. Para esto, se propuso una expresión que relaciona la permeabilidad y la porosidad y, empleando una relación existente entre el factor de resistividad y la porosidad, se propuso también una relación directa entre la permeabilidad y el factor de resistividad. Las relaciones propuestas fueron aplicadas a los valores numéricos obtenidos para paquetes de esferas generados numéricamente y se encontró que se ajustan mejor a los datos en comparación con las relaciones más comúnmente utilizadas, especialmente para porosidades altas. Se mostró también que estas relaciones petrofísicas toman la forma de las relaciones más comunes conocidas cuando se trata con porosidades bajas. Valores obtenidos de imágenes digitales de un paquete de esferas sintético y una muestra de dolomita mostraron que las expresiones para porosidades bajas son suficientes para ajustar datos de medios porosos con porosidades menores a un valor entre 0.3 y 0.4. Finalmente, se analizaron el factor de resistividad, la permeabilidad, las relaciones petrofísicas, y las distribuciones espaciales y estadísticas de los campos vectoriales de flujo se analizaron para comparar los fenómenos de transporte eléctrico e hidráulico, encontrando que algunos factores, como la porosidad efectiva, son importantes en ambos fenómenos de flujo; mientras que otros, como la adherencia del fluido a las paredes del poro, son particularmente relevantes para el flujo hidráulico.

In this work, numerical modeling techniques were used to simulate the flow of electric current and fluid through porous media in order to determine the resistivity factor and permeability, as well as the distribution of electric current density and flow velocity fields. For electric flow modeling, an algorithm based on finite differences was developed, while for hydraulic modeling, a library reported in the literature, based on lattice Boltzmann method, was used. In both modeling schemes, pore-grain boundary conditions were established to model the physical processes exclusively in the pore space. The estimated values of resistivity factor and permeability, as well as porosity, were used to study the correlations between these properties through petrophysical relationships. An expression relating permeability and porosity was proposed and, using an existing relationship between the resistivity factor and the porosity, a direct relation between permeability and resistivity factor was also proposed. The proposed relations were applied to data obtained for numerically generated sphere packs and were found to fit the data better than the most commonly used relationships, especially for high porosities. It was also shown that these petrophysical relationships take the form of the most common relationships known when dealing with low porosities. Modeling data on digital images of a synthetic sphere pack and a dolomite sample showed that the expressions for low porosities are sufficient to fit data from porous media with porosities lower than 0.3 to 0.4. Finally, resistivity factors, permeabilities, petrophysical relationships, and spatial and statistical distributions of flow vector fields were analyzed to compare electrical and hydraulic transport phenomena, finding that some factors, such as the effective porosity, are important in both flow phenomena; whereas some other, such as the pore-wall adherence, are particularly relevant to hidraulic flux.

Física de rocas, modelado numérico, relaciones petrofísicas, fenómenos de transporte, factor de resistividad, permeabilidad, porosidad, tomografía de rocas, campos vectoriales, distribución estadística Rock physics, numerical modelling, petrophysical relations, transport phenomena, resistivity factor, permeability, porosity, rock tomography, vector fields, statistical distribution CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS DE LA TIERRA Y DEL ESPACIO GEOFÍSICA GEOFÍSICA DE LA MASA SÓLIDA TERRESTRE GEOFÍSICA DE LA MASA SÓLIDA TERRESTRE