Numerical simulation of solar radiation, air flow and temperature distribution in a naturally ventilated tunnel greenhouse

 Catherine Baxevanou1, Dimitrios Fidaros1, Thomas Bartzanas1, Constantinos Kittas1,2(1. Center for Research and Technology-Thessaly, Institute of Technology and Management of Agricultural Ecosystems, Technology Park of Thessaly, 1st Industrial Area, 38500 Volos;2. University of Thessaly, Department of Agriculture, Crop Production and Agricultural Environment, Fytokou St., N. Ionia, GR-38446, Magnesia, Greece) Abstract: The effect of solar radiation distribution in a typical agricultural building was numerically investigated, taking into account the thickness of the cover, its spectral optical and thermal properties.  A two dimensional mesh was used to render the building's geometry, and the Discrete Ordinate (DO) model for simulating the radiation, taking into accounts its spectral distribution in three wavelength bands.  Based on the meteorological data of October for the region of Volos (Greece), two parametric studies were carried out, dealing with the variation of intensity and angle of the incoming solar radiation and with the optical properties differentiation of covering materials.  The flow recirculation, due to the buoyancy effect, showed the importance of internal temperature gradients, although forced convection which resulted from natural ventilation was dominant.  It was concluded that cover material with high absorptivity deteriorate the natural ventilation increasing the air temperature by convection, and favoring the development of secondary recirculation where the air is trapped.  Furthermore, high absorptivity reduces the available Photosynthetically Active Radiation (PAR) but it distributes it equally inside the greenhouse.  Finally, the ability of the material to transmit the solar irradiance in the wavelengths corresponding to PAR with comparable absorptivity improved as the refractive index decreased.Keywords: greenhouse, microclimate, CFD, radiation, mixed heat transfer, ventilation, Greece Citation: Catherine Baxevanou, Dimitrios Fidaros, Thomas Bartzanas, Constantinos Kittas.  Numerical simulation of solar radiation, air flow and temperature distribution in a naturally ventilated tunnel greenhouse.  Agric Eng Int: CIGR Journal, 2010, 12(3): 48-67. &nbsp

Aplicación de internet de las cosas (IoT) para entornos de invernadero optimizados

Esta revisión presenta la investigación más avanzada sobre sistemas IoT para entornos de invernadero optimizados. Los datos fueron analizados usando métodos descriptivos y estadísticos para inferir relaciones entre Internet de las cosas (IoT), tecnologías emergentes, agricultura de precisión, agricultura 4.0 y mejoras en la agricultura comercial. La discusión se sitúa en el contexto más amplio de IoT en la mitigación de los efectos adversos del cambio climático y el calentamiento global en la agricultura a través de la optimización de parámetros críticos como la temperatura y la humedad, la adquisición inteligente de datos, el control basado en reglas y la resolución de las barreras para la adopción comercial de sistemas IoT en la agricultura. Los recientes eventos meteorológicos severos e inesperados han contribuido a los bajos rendimientos y pérdidas agrícolas; este es un desafío que se puede resolver a través de la agricultura de precisión mediada por tecnología. Los avances tecnológicos han contribuido con el tiempo al desarrollo de sensores para la prevención de heladas, el control remoto de cultivos, la prevención de riesgos de incendio, el control preciso de nutrientes en cultivos de invernadero sin suelo, la autonomía energética mediante el uso de energía solar y la alimentación, el sombreado y la iluminación inteligentes. control para mejorar los rendimientos y reducir los costos operativos. Sin embargo, abundan los desafíos particulares, incluida la adopción limitada de tecnologías inteligentes en la agricultura comercial, el precio y la precisión de los sensores. Las barreras y los desafíos deberían ayudar a guiar futuros proyectos de investigación y desarrollo y aplicaciones comerciales

A Diagnostic System for Improving Biomass Quality Based on a Sensor Network

Losses during storage of biomass are the main parameter that defines the profitability of using preserved biomass as feed for animal husbandry. In order to minimize storage losses, potential changes in specific physicochemical properties must be identified to subsequently act as indicators of silage decomposition and form the basis for preventive measures. This study presents a framework for a diagnostic system capable of detecting potential changes in specific physicochemical properties, i.e., temperature and the oxygen content, during the biomass storage process. The diagnostic system comprises a monitoring tool based on a wireless sensors network and a prediction tool based on a validated computation fluid dynamics model. It is shown that the system can provide the manager (end-user) with continuously updated information about specific biomass quality parameters. The system encompasses graphical visualization of the information to the end-user as a first step and, as a second step, the system identifies alerts depicting real differences between actual and predicted values of the monitored properties. The perspective is that this diagnostic system will provide managers with a solid basis for necessary preventive measures

Methodologies for Assessing Disease Tolerance in Pigs

Features of intensive farming can seriously threaten pig homeostasis, well-being and productivity. Disease tolerance of an organism is the adaptive ability in preserving homeostasis and at the same time limiting the detrimental impact that infection can inflict on its health and performance without affecting pathogen burden per se. While disease resistance (DRs ) can be assessed measuring appropriately the pathogen burden within the host, the tolerance cannot be quantified easily. Indeed, it requires the assessment of the changes in performance as well as the changes in pathogen burden. In this paper, special attention is given to criteria required to standardize methodologies for assessing disease tolerance (DT) in respect of infectious diseases in pigs. The concept is applied to different areas of expertise and specific examples are given. The basic physiological mechanisms of DT are reviewed. Disease tolerance pathways, genetics of the tolerance-related traits, stress and disease tolerance, and role of metabolic stress in DT are described. In addition, methodologies based on monitoring of growth and reproductive performance, welfare, emotional affective states, sickness behavior for assessment of disease tolerance, and methodologies based on the relationship between environmental challenges and disease tolerance are considered. Automated Precision Livestock Farming technologies available for monitoring performance, health and welfare-related measures in pig farms, and their limitations regarding DT in pigs are also presented. Since defining standardized methodologies for assessing DT is a serious challenge for biologists, animal scientists and veterinarians, this work should contribute to improvement of health, welfare and production in pigs

Sensors for Structural Health Monitoring of Agricultural Structures

The health diagnosis of agricultural structures is critical to detecting damages such as cracks in concrete, corrosion, spalling, and delamination. Agricultural structures are susceptible to environmental degradation due to frequent exposure to water, organic effluent, farm chemicals, structural loading, and unloading. Various sensors have been employed for accurate and real-time monitoring of agricultural building structures, including electrochemical, ultrasonic, fiber-optic, piezoelectric, wireless, fiber Bragg grating sensors, and self-sensing concrete. The cost–benefits of each type of sensor and utility in a farm environment are explored in the review. Current literature suggests that the functionality of sensors has improved with progress in technology. Notable improvements made with the progress in technology include better accuracy of the measurements, reduction of signal-to-noise ratio, and transmission speed, and the deployment of machine learning, deep learning, and artificial intelligence in smart IoT-based agriculture. Key challenges include inconsistent installation of sensors in farm structures, technical constraints, and lack of support infrastructure, awareness, and preference for traditional inspection methods

Bir soğuk hava deposunda ortam koşullarının sayısal modellenmesi ve deneysel geçerliliğinin belirlenmesi]

The objective of this study was to analyse air temperature and relative humidity distribution in an experimental cold store fully loaded with apples by using both experimental and numerical (CFD) methods. An unsteady three-dimensional computational fluid dynamics model was developed to assess the distribution of temperature and relative humidity in a cold store fully loaded with Granny Smith apples. The storage temperature and relative humidity were maintained at 2 degrees C and 90%, respectively. The relative humidity and temperature were measured at 36 different points inside the cold store in three different planes. A three-dimensional mathematical model was built for the numerical needs. The numerical model was validated against experimental data from the same facility. Relative error of the model was calculated 13% for temperature and 1.43% for relative humidity. Numerical results obtained from the simulations agreed quite well with experimental data for temperature and relative humidity. Maximum differences were observed near the borders of the cold store which can be attributed to the stronger thermal gradients taking place on these surfaces. A more homogeneous distribution was achieved in the middle of the cold store both for air temperature and relative humidity leading to even smaller errors between measurements and simulations.TUBITAKTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [110 O 147]Authors would like to thank to TUBITAK for their support to TUBITAK Project No: 110 O 147 - Investigation of Spatial variability effect of ambient conditions on storage losses, Report No: 4 and 5

Numerical Modelling and Experimental Validation of a Cold Store Ambient Factors

The objective of this study was to analyse air temperature and relative humidity distribution in an experimental cold store fully loaded with apples by using both experimental and numerical (CFD) methods. An unsteady three-dimensional computational fluid dynamics model was developed to assess the distribution of temperature and relative humidity in a cold store fully loaded with Granny Smith apples. The storage temperature and relative humidity were maintained at 2 °C and 90%, respectively. The relative humidity and temperature were measured at 36 different points inside the cold store in three different planes. A three-dimensional mathematical model was built for the numerical needs. The numerical model was validated against experimental data from the same facility. Relative error of the model was calculated 13% for temperature and 1.43% for relative humidity. Numerical results obtained from the simulations agreed quite well with experimental data for temperature and relative humidity. Maximum differences were observed near the borders of the cold store which can be attributed to the stronger thermal gradients taking place on these surfaces. A more homogeneous distribution was achieved in the middle of the cold store both for air temperature and relative humidity leading to even smaller errors between measurements and simulations

Moisture content evaluation of biomass using CFD approach

In grass conservation systems, drying in the field is an essential process upon which the quality and quantity of the material to be conserved is dependent on. In this study a Computational Fluid Dynamics (CFD) model, previously validated, was used to assess qualitatively and quantitatively the field drying process of cut grass under different weather conditions and structural specifications of the grass. The use of the CFD model depicts the climate heterogeneity in the grass area with a special focus on moisture distribution, influence of the weather conditions, in order to create the possibility of applying the model as a decision support tool for an enhanced treatment of the grass after cutting

Recent Advances in Antioxidant Polymers: From Sustainable and Natural Monomers to Synthesis and Applications

Advances in technology have led to the production of sustainable antioxidants and natural monomers for food packaging and targeted drug delivery applications. Of particular importance is the synthesis of lignin polymers, and graft polymers, dopamine, and polydopamine, inulin, quercetin, limonene, and vitamins, due to their free radical scavenging ability, chemical potency, ideal functional groups for polymerization, abundance in the natural environment, ease of production, and activation of biological mechanisms such as the inhibition of the cellular activation of various signaling pathways, including NF-κB and MAPK. The radical oxygen species are responsible for oxidative damage and increased susceptibility to cancer, cardiovascular, degenerative musculoskeletal, and neurodegenerative conditions and diabetes; such biological mechanisms are inhibited by both synthetic and naturally occurring antioxidants. The orientation of macromolecules in the presence of the plasticizing agent increases the suitability of quercetin in food packaging, while the commercial viability of terpenes in the replacement of existing non-renewable polymers is reinforced by the recyclability of the precursors (thyme, cannabis, and lemon, orange, mandarin) and marginal ecological effect and antioxidant properties. Emerging antioxidant nanoparticle polymers have a broad range of applications in tumor-targeted drug delivery, food fortification, biodegradation of synthetic polymers, and antimicrobial treatment and corrosion inhibition. The aim of the review is to present state-of-the-art polymers with intrinsic antioxidant properties, including synthesis scavenging activity, potential applications, and future directions. This review is distinct from other works given that it integrates different advances in antioxidant polymer synthesis and applications such as inulin, quercetin polymers, their conjugates, antioxidant-graft-polysaccharides, and polymerization vitamins and essential oils. One of the most comprehensive reviews of antioxidant polymers was published by Cirillo and Iemma in 2012. Since then, significant progress has been made in improving the synthesis, techniques, properties, and applications. The review builds upon existing research by presenting new findings that were excluded from previous reviews