Supervisión y control en ingeniería de procesos agroalimentarios

Podemos definirla como el conjunto de medios, malcríales y reglas d e control que permiten conferir unas propiedades preestablecidas a un producto agrario o alimenticio. Difiere fundamentalmente de la ingeniería química en que las propiedades a obtener son varias (textura, sabor, color) y no una sola (pureza de un determinado producto químico). Por otra pane, los métodos instrumentales disponibles para cuantilicar dichas propiedades no siempre existen o están suficientemente validados. Motivo por el cual puede ser necesario el empleo de expertos en su definición y evaluación

Light energy efficiency in lettuce crop: Structural indoor designs simulation

Producción CientíficaIndoor agricultural offers efficient alternatives for intensive food production through automation technologies and controlled environments. Light plays a crucial role in plant development; however, photons captured by the crop are often wasted in empty spaces, resulting in low light efficiency and high energy costs. This research aims to simulate eight structural designs for an indoor lettuce crop, exploring different planting systems and light and culture bed combinations (static and mobile) to identify the most effective mechanism for light efficiency during crop growth. The simulations were carried out with spreadsheets based on applying formulas of yield in dry biomass per photosynthetic photons, lighting costs, harvest, and production. The results indicate that Circular Moving Light and Mobile Culture Bed with Quincunx Planting (CML-QM) and Circular Moving Light and Mobile Culture Bed with Linear Planting (CML-LPM) exhibit higher photon capture percentages (85% and 80%, respectively) and lower electricity consumption compared to static designs. The simulation results demonstrate the potential for significant improvements in photon capture and cost savings through optimized system designs. This investigation provides valuable insights for designing more efficient systems and reducing electricity consumption to enhance the capture of photosynthetic photons in indoor lettuce cultivation.Unión Europea - (project H2020-FNR-2020-1/CE-FNR-07-2020) y (project (HORIZON-CL6- 2022-FARM2FORK-01

Application of convolutional neural networks in weed detection and identification: a systematic review

Producción CientíficaWeeds are unwanted and invasive plants that proliferate and compete for resources such as space, water, nutrients, and sunlight, affecting the quality and productivity of the desired crops. Weed detection is crucial for the application of precision agriculture methods and for this purpose machine learning techniques can be used, specifically convolutional neural networks (CNN). This study focuses on the search for CNN architectures used to detect and identify weeds in different crops; 61 articles applying CNN architectures were analyzed during the last five years (2019–2023). The results show the used of different devices to acquire the images for training, such as digital cameras, smartphones, and drone cameras. Additionally, the YOLO family and algorithms are the most widely adopted architectures, followed by VGG, ResNet, Faster R-CNN, AlexNet, and MobileNet, respectively. This study provides an update on CNNs that will serve as a starting point for researchers wishing to implement these weed detection and identification techniquesUnion Europea, Programa Horizonte - (project HORIZON-CL6-2022-FARM2FORK-01

Analizador electrónico de calidad de semillas

Analizador electrónico automático de calidad de semillas. El Analizador Electrónico Automático de Calidad de Semillas resuelve el problema de la determinación a priori de la calidad de un lote de semillas en virtud de su vigor para la germinación. Este análisis es realizado de forma automática mediante la medida de la conductividad eléctrica generada por la imbibición de semillas en agua desionizada. Presenta como ventajas la posibilidad de realizar múltiples medidas sobre lotes diferentes de forma paralela y automática, la modularidad de sus componentes que permite su limpieza y sustitución en caso de fallo y la conexión directa a ordenador personal para el almacenamiento de los datos y la generación de informes de calidad tras un análisis estadístico y matemático. El sistema puede ser programado para la realización de una campaña de medidas evitando la necesidad de la presencia de un supervisor. Todo ello lo hace un equipo completo y novedoso

Prediction of daily ambient temperature and Its hourly estimation using artificial neural networks in urban allotment gardens and an urban park in Valladolid, Castilla y León, Spain

Producción CientíficaUrban green spaces improve quality of life by mitigating urban temperatures. However, there are challenges in obtaining urban data to analyze and understand their influence. With the aim of developing innovative methodologies for this type of research, Artificial Neural Networks (ANNs) were developed to predict daily and hourly temperatures in urban green spaces from sensors placed in situ for 41 days. The study areas were four urban allotment gardens (with dynamic and productive vegetation) and a forested urban park in the city of Valladolid, Spain. ANNs were built and evaluated from various combinations of inputs (X), hidden neurons (Y), and outputs (Z) under the practical rule of “making networks simple, to obtain better results”. Seven ANNs architectures were tested: 7-Y-5 (Y = 6, 7, …, 14), 6-Y-5 (Y = 6, 7, …, 14), 7-Y-1 (Y = 2, 3, …, 8), 6-Y-1 (Y = 2, 3, …, 8), 4-Y-1 (Y = 1, 2, …, 7), 3-Y-1 (Y = 1, 2, …, 7), and 2-Y-1 (Y = 2, 3, …, 8). The best-performing model was the 6-Y-1 ANN architecture with a Root Mean Square Error (RMSE) of 0.42 °C for the urban garden called Valle de Arán. The results demonstrated that from shorter data points obtained in situ, ANNs predictions achieve acceptable results and reflect the usefulness of the methodology. These predictions were more accurate in urban gardens than in urban parks, where the type of existing vegetation can be a decisive factor. This study can contribute to the development of a sustainable and smart city, and has the potential to be replicated in cities where the influence of urban green spaces on urban temperatures is studied with traditional methodologies.Unión Europea - FUSILLI project (H2020-FNR-2020-1/CE-FNR-07-2020)Unión Europea - CIRAWA project (HORIZON-CL6- 2022-FARM2FORK-01

Idoneidad de la iluminación con led y oled de estado sólido para el cultivo del azafrán (Croccus Sativus l.) en invernaderos

Cormos de azafrán (Croccus sativus L.) fueron analizados morfológicamente y se cultivaron de forma hidropónica a 16 - 21 ºC. Con el fin de estudiar el efecto de la radiación electromagnética de color azul (435 nm), roja (660 nm) y del rojo lejano (730 nm) sobre la fotosíntesis y la morfogénesis del azafrán, se utilizaron diodos emisores de luz (LED) fabricados por PHILIPS (mod. GreenPower LED High Flux). La intensidad de iluminación que recibió el cultivo se ajustó a la que recibiría en condiciones naturales mediante un sistema electrónico de control, en el que se utilizan dimmers para el control del flujo luminoso. Los resultados obtenidos hasta este momento permiten señalar que, tanto la iluminación con luz azul y roja estimulan de forma significativa el crecimiento de los vástagos (parte aérea) frente a los cormos testigo (iluminación natural), si bien en ninguno de los tratamientos se ha producido la inducción floral que cabía esperar. Como una alternativa viable a los tradicionales LEDs inorgánicos, algunos de los nuevos experimentos utilizarán diodos orgánicos emisores de luz (OLED), basados en nuevos complejos de erbio octocoordinados y con emisiones en las regiones del rojo y del infrarrojo cercano

Benefits of non-commercial urban agricultural practices—a systematic literature review

Producción CientíficaUrban agriculture refers to any type of activity located within or around a city designed to provide ecosystem services. Given the rapid population growth and urbanization, urban agriculture is seen as a potential alternative route to a more sustainable urban food system. This review answers the main question: What are the benefits of non-commercial of Urban Agriculture (NCUA) forms and its contribution towards food production? using a systematic literature review approach. The methodology involved capturing 1355 recent articles from qualified search engines, using key terms according to the defined question, then screened for relevance and the defined scope of this review, resulting in a final selection of 40 articles for analysis. The results show that implementing NCUA practices has multifaced social, economic, and environmental benefits, such as improving people’s health, reducing expenditure on food and creating sustainable cities, highlighting the need to recognize the multifaceted role of NCUA in promoting a more sustainable lifestyle and strengthening local communities and engagement. Moreover, awareness of urban agriculture differs between developed and developing countries, as does the recognition and valorization of its benefits. Further research is needed to examine the enabling factors and barriers to NCUA adoption in different urban context, the resource implications, and the long-term sustainability of these practices.Unión Europea, FUSILLI Project (H2020-FNR-2020-1/CE-FNR-07-2020) - (grant 101000717

Prediction of horizontal daily global solar irradiation using artificial neural networks (ANNs) in the Castile and León region, Spain

Producción CientíficaThis article evaluates horizontal daily global solar irradiation predictive modelling using artificial neural networks (ANNs) for its application in agricultural sciences and technologies. An eight year data series (i.e., training networks period between 2004–2010, with 2011 as the validation year) was measured at an agrometeorological station located in Castile and León, Spain, owned by the irrigation advisory system SIAR. ANN models were designed and evaluated with different neuron numbers in the input and hidden layers. The only neuron used in the outlet layer was the global solar irradiation simulated the day after. Evaluated values of the input data were the horizontal daily global irradiation of the current day [H(t)] and two days before [H(t−1), H(t−2)], the day of the year [J(t)], and the daily clearness index [Kt(t)]. Validated results showed that best adjustment models are the ANN 7 model (RMSE = 3.76 MJ/(m2·d), with two inputs ([H(t), Kt(t)]) and four neurons in the hidden layer) and the ANN 4 model (RMSE = 3.75 MJ/(m2·d), with two inputs ([H(t), J(t)]) and two neurons in the hidden layer). Thus, the studied ANN models had better results compared to classic methods (CENSOLAR typical year, weighted moving mean, linear regression, Fourier and Markov analysis) and are practically easier as they need less input variables

Zoning of potential areas for the production of oleaginous species in Colombia under agroforestry systems

Producción CientíficaDue to the need to develop more agroforestry systems, the Moringa oleifera, Olea Europea, Glycine max, Brassica napus, Helianthus annuus, and Jatropha curcas are identified as unconventional species for their expansion under these systems in Colombia. With the Colombian Environmental Information System (SIAC) database, zoning was carried out according to the agroclimatic species requirements and optimal coverage for their production. As a result, a total area of 212,977.2 km2 was identified, mainly including the departments of Casanare, Arauca, Vichada, Guajira, Córdoba, Meta, Magdalena, Cesar, Tolima, and Cundinamarca. The species and associations species with the most options for productive expansion are Moringa (75,758 km2), Moringa, Jatropha, and Sunflower (42,515.1 km2), Moringa and Jatropha (37,180.4 km2), Jatropha (20,840 km2), Jatropha and Sunflower (17,692.1 km2), Olive (7332.1 km2), and Soybean (3586.3 km2). Of the potential agroforestry areas to their establishment, 36% correspond to herbaceous and/or shrubby vegetation, 34% to grasses, and 22% to heterogeneous agricultural areas. This research is the first step to representing the agronomic versatility of these promising species and their potential contribution to the diversification of the agri-food and agroforestry sectors

Nuevos métodos de obtención de bioqueroseno a partir de extractos de algas

A partir de biomasa de algas en forma de pasta y procedente de su centrifugación (Nanochloropsis gaditana, Ascophyllum Nodosum y Laminaria Digitata) se elabora por procedimiento de solvólisis un biodiesel susceptible de hidrogenación en bioquioqueroseno y para su posterior uso como combustible de aviones. Este trabajo investiga la composición de las algas en ácido algínico y en sus unidades constituyentes o ácidos manurónico y gulurónico, y el contenido en alginato de sodio sobre algas secas. La valorización de residuos procedentes de centrifugados de algas con bajo contenido en aceite, se ha mostrado útil para la extracción de los mismos, y posterior solvolisis ácida y extracción con disolventes (acetilacetona y el etilenglicol). Especialmente la espectroscopía 1 HNMR y 13 CNMR se ha mostrado útil para identificar en los aceites, ácidos grasos próximos al ácido cis-cis-9,12- octadecadienoico. Por esterificación y subsiguiente hidrogenación se produce el bioqueroseno objeto de estudi