No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Analysis of air temperature distribution inside a cold store by means of geostatistical methods
Abstract
The objective of temperature control in cold storage systems is to maintain an average temperature limited by a maximum temperature deviation within the produce. Temperature is a key factor in postharvest quality that is usually supported by the belief that it is well controlled and uniform in cold storage systems. Cold stores show non-uniform air temperature distributions and produce quality problems related to cold and hot spots are well-known. Air temperature control in storage systems is usually related to one or a limited number of temperature sensors in the store that are placed in locations easy accessible. The aim of this study was to model and analyze spatio-Temporal temperature distributions in vertical plans along a cold store by means of a geostatistical approach. The use of this information to determine the minimum number of air temperature sensors needed and their location for better climate control is discussed. The spatio-Temporal air temperature variation was assessed inside an experimental cold store applying geostatistical methods. The cold store (3.75×2.64×2.38 m) was equipped with an A/C unit. A vertical grid of 36 regularly distributed air temperature sensors was installed. It was shifted 0.35 m each day in order to cope with the 3.75 m length of the cold store in 10 vertical planes. Each plane was set to take measurements during 24 hours periods at 1 datum/min frequency. Empirical variograms were constructed for each vertical plane. Various variogram models were evaluated to fit the dataset, and an ordinary spatio-Temporal kriging method was used to predict temperature values. The results show temperature distribution gradients that have to be accounted for when studying postharvest processes in cold storage systems. Geostatistical methods proved to be a useful tool for the study of spatio-Temporal air temperature distributions that will contribute to better postharvest produce uniformity through improved climate control performance.
... With the aim to improve the performance of the chilling technology a lot of computational studies were performed on fluid dynamics [26][27][28][29][30] that presumably will influence the next generation chilling technology. ...
The consumption of meals prepared, packaged, and consumed inside and outside the home is increasing globally. This is a result of rapid changes in lifestyles as well as innovations in advanced food technologies that have enabled the food industry to produce more sustainable and healthy fresh packaged convenience foods. This paper presents an overview of the technologies and compatible packaging systems that are designed to increase the shelf-life of foods prepared by cook–chill technologies. The concept of shelf-life is discussed and techniques to increase the shelf life of products are presented including active packaging strategies.
... Such knowledge can be acquired experimentally. Here, spatiotemporal temperature data can be processed to estimate cooling coefficients, 7/8th cooling time and cooling uniformities (Anderson et al., 2004;Gil et al., 2012;Akdemir and Arin, 2006). However, experimental approach alone is expensive, time taking and inconvenient to perform detailed analysis of airflow and temperature distributions. ...
Computational fluid dynamics (CFD) model was developed, validated and used to analyse cooling characteristics of two different package designs (CT1 and CT2) used for postharvest handling of pomegranate fruit. The model incorporated geometries of fruits, packaging box, tray and plastic liner. Thin layer of plastic material with conservative interface heat flux was used to model liners. The accuracy of the model to predict airflow and temperature distributions were validated against experimental data. The model predicted airflow through the stacks and cooling rates within experimental error. Stack design markedly affected the airflow profile, rate and uniformity of cooling. The cooling rate of the two package designs differed by 30% and plastic lining increased the average 7/8th cooling times from 4.0 and 2.5 h to 9.5 and 8.0 h for the CT1 and CT2 stacks, respectively. Profile of high and low temperature regions depended considerably on packaging box design.
This thesis develops methodologies for a technical sustainability assessment of agricultural systems through the integration of soil-crop modeling and standard life cycle assessment (LCA). In addition, we propose a strategy to facilitate communication of the results of the comparative LCAs to stakeholders. As case studies, the proposed methods are applied to open field and greenhouse tomato production systems in the Colombian Andes, focusing on nitrogen fertilization practices.
The thesis begins with a detailed characterization of the selected tomato production systems under both open field and greenhouse conditions. This characterization was necessary since the information available for these smallholder-based cropping systems is very limited in the Colombian context. This characterization included biophysical factors related to climatic conditions and soil fertility level, and an inventory of inputs, management practices, and productivity factors. Two data collection tools, namely, surveys and a procedure based on direct observation of the production cycles referred to as detailed follow-ups or input-output accounting, were used to gather the information from two major production regions. Since local growers usually do not keep records of their activities, detailed follow-ups are recommended for obtaining reliable data under these conditions, despite their cost and time-consuming nature. Nevertheless, as a first screening of the production systems, surveys are very useful. As a result of this first phase, some features of the growers were highlighted, such as a high dose of fertilizers without a proportional increase in yield. Heterogeneity with respect to management practices and varying levels of yield gaps, especially in the open field system, were also evident.
A comparative LCA between the two systems was carried out and included the infrastructure, machinery, pest management, and fertilization subsystems. In this case study, the field emissions derived from the nitrogen fertilizers were obtained through standard methods based on empirical regression meta-analysis allowing the modification of cropping parameters as a function of the production system. The outcome of the LCA was not clear enough to differentiate the environmental performance among the two production systems. For instance, the greenhouse system showed better environmental performance according to indicators such as acidification and eutrophication, while the opposite was observed with indicators such as global warming potential and human toxicity potential. In this section, the stochastic multi-attribute analysis (SMAA) was introduced as a way to build a single indicator that would objectively rank the environmental performance of the two systems. However, an important constraint not considered by the SMAA method had to be overcome first, namely, the high degree of correlation between environmental indicators. Thus, the copula method was introduced to fit the required joint-statistical distributions for all environmental indicator based on the estimated marginal distributions of the individual impact categories. The successful implementation of the SMAA method, supported by the copula method, resulted in the better overall environmental performance of the open field than the greenhouse system. In conclusion, intensification of tomato production in Colombia by shifting to protected conditions has led to a relatively high environmental impact because of inadequate and inefficient implementation of greenhouse technology. As a consequence, it is necessary that greenhouse farmers optimize resource use and greenhouse methodologies to achieve higher production and lower environmental impact. To evaluate strategies that improve the environmental performance of tomato production systems in terms of nitrogen fertilization, a tomato plant growth and development model was calibrated and validated for open field and greenhouse conditions. In the first stage, the growth and development of tomato plants under Colombian conditions was effectively simulated by the calibrated model. This plant model was adapted by incorporating modules to represent root growth and nitrogen demand to couple it to a soil model. The soil model was previously calibrated and validated under Belgian conditions and can represent water and nitrogen dynamics as well as all N and C processes. The soil-plant model was validated for Colombian conditions based on trials carried out on commercial fields. Although the validation results presented varying degrees of fit, overall, the model showed a workable level of accuracy. The resulting soil-plant model was driven by meteorological data, soil and plant properties and management practices such as nitrogen fertilization and irrigation. The model simulated, on a daily basis, crop growth and development, heat, water and nitrogen flows through the soil profile, and soil nitrogen and carbón dynamics, including emissions of environmental pollutants to the atmosphere and groundwater.
Finally, the soil-plant model was used to evaluate a set of nitrogen fertilization scenarios. The scenarios included currently applied strategies by commercial growers and two alternative prospective scenarios. In the grower scenario, nitrogen fertilization was applied based on a fixed dose, while the alternative scenarios applied nitrogen as a function of plant demand over time. Each of the scenarios was evaluated over 52 weather periods, corresponding to weekly plantings over a period of one year. From each simulation, the predicted yield and the emissions of ammonia, nitrous oxide, and nitrates were extracted and used as inputs for a posterior comparative LCA. The results revealed that some scenarios showed better environmental performance for some impact categories, while others performed better in a different set of categories. Therefore, the SMAA method supplemented by the copula method was applied again to rank the environmental performance of the scenarios. The results showed that greenhouse production systems in which the fertilization strategy is based on plant demands have the best environmental performance. The method proposed in this thesis adds dynamic properties to the classic static LCA in terms of predicting nitrogen emissions through integration with soil-crop modeling. Additionally, the proposed framework incorporates an optimized single performance indicator method to enhance communication of the LCA results to stakeholders and decision-makers.
The implementation of early-stage simulation tools, specifically computational fluid dynamics (CFD), is an international and interdisciplinary trend that allows engineers to computer-test concepts all the way through the development of a process or system. With the enhancement of computing power and efficiency, and the availability of affordable CFD packages, the applications of CFD have extended into the food industry for modeling industrial processes, performing comprehensive analyses, and optimizing the efficiency and cost effectiveness of the new processes and systems. Beginning a new series dedicated to contemporary, up-to-date food engineering practices, Computational Fluid Dynamics in Food Processing is the first book of its kind to illustrate the use of CFD for solving heat and mass transfer problems in the food industry. Using a computational grid, CFD solves governing equations that describe fluid flow across each grid cell by means of an iterative procedure in order to predict and visualize the profiles of velocity, temperature, pressure, and other parameters. Starting with an overview of CFD technology and applications, the book illustrates the use of CFD for gaining a qualitative and quantitative assessment of the performance of processes involving heat and mass transfer. Specific chapters cover airflow in refrigerated trucks, retail display cabinets, microwaves, and doorways; velocity in meat dryers and spray drying; thermal sterilization; plate heat exchangers; membrane separation systems; jet impingement ovens; food extrusion and high-pressure processing; prediction of hygiene; design of biosensors; and the fermentation of tea and ripening of cheese. Drawing from an esteemed panel of international professionals and academics, this groundbreaking bookprovides engineers and technologists in research, development, and operations with critical, comprehensive, and readily accessible information on the art and science of CFD technology.
In the light of an increasing demand for staple food, especially rice, in southeast China, investigations on the specific site potential expressed as the relationship between soil and crop yield parameters gain increasing importance. Soil texture and several soil chemical parameters as well as plant properties such as crop height, biomass and grain yield were investigated along two terraced catenas with contrasting soil textures cropped with wet rice. We were aiming at identifying correlative relationships between soil and crop properties. Data were analyzed both statistically and geostatistically on the basis of semivariograms. Statistical analysis indicated a significant influence of the relief position on the spatial distribution of soil texture, total carbon and total nitrogen contents. Significant correlations were found for the catena located in a sandstone area (Catena A) between rice yield and silt as well as total nitrogen content. Corresponding relationships were not detectable for paddy fields that developed from Quaternary clays (Catena B). As suggested by the nugget to sill ratio, spatial variability of soil texture, total carbon and nitrogen was mainly controlled by intrinsic factors, which might be attributed to the erosional transport of fine soil constituents, indicating the importance of the relief position and slope in soil development even in landscapes that are terraced. The crop parameters exhibited short ranges of influence and about one third of their variability was unexplained. Comparable ranges of selected crop and soil parameters, found only for Catena A, are indicative of close spatial interactions between rice yield and soil features. Our findings show that especially in sandstone-dominated areas, a site-specific management can contribute to an environmentally safe rice production increase.
The primary goal of this work is to present a geostatistical software library known as GSLIB. An important prerequisite to geostatical case studies and research is the availability of flexible and understandable software. Flexibility is achieved by providing the original FORTRAN source code. A detailed description of the theoretical background along with specific application notes allows the algorithms to be understood and used as the basis for more advanced customized programs. The three main chapters of this guidebook are based on the three major problem areas of geostatistics: quantifying spatial variability (variograms), generalized linear regression techniques (kriging), and stochastic simulation. Additional utility programs and problem sets with partial solutions are given to allow a full exploration of GSLIB and to check new software installations.
A transient three-dimensional CFD model was developed to calculate the velocity, temperature and moisture distribution in an existing empty and loaded cool store. The dynamic behaviour of the fan and cooler was modelled. The model accounted for turbulence by means of the standard k-ε model with standard wall profiles. The model was validated by means of velocity, air and product temperature. An average accuracy of 22% on the velocity magnitudes inside the empty cold store was achieved and the predicted temperature distribution was more uniform than predicted. In the loaded cold store, an average accuracy of 20% on the velocity magnitudes was observed. The model was capable of predicting both the air and product temperature with reasonable accuracy.
In industry solid foods such as vegetables and meat are mostly air-chilled and stored in refrigerated rooms. Plant performance depends on heat and water exchanges between the air and the products and thus on the spatial distribution of the air parameters: velocity, turbulence intensity, temperature and relative humidity. In theory the transient behaviour of chillers could be calculated using computational fluid dynamics (CFD) codes, but current computer capacity and the inaccuracy of models for evaluating heat and mass transfer coefficients make them inapplicable to very large rooms containing hundreds of individual products. To overcome these limits a four-step calculation is proposed to assess how changes in chiller design and operating conditions affect chilling kinetics: (1) 3D calculation of the air velocity field with a CFD code, (2) deduction of an average air velocity map, (3) determination of heat and mass transfer coefficients in relation to the air velocity map using independent measurements, and (4) calculation of the product chilling kinetics using specific software. This procedure was applied to a pork chiller containing 290 carcasses. Two design cases differing in inlet air direction and flow rate, and two functioning modes, batch and continuous, were analysed. A fairly good agreement was observed between the calculated and measured air velocities. It was shown from temperature and weight loss kinetics that with this type of design, batch chilling can only be achieved overnight at the cost of overcooling for low weight carcasses, and increased weight losses.
Computational fluid dynamics (cfd) is a simulation tool, which uses powerful computer and applied mathematics to model fluid flow situations for the prediction of heat, mass and momentum transfer and optimal design in industrial processes. It is only in recent years that cfd has been applied in the food processing industry. This paper reviews the application of cfd in food processing industries including drying, sterilisation, refrigeration and mixing. The advantages of using cfd are discussed and the future of cfd applications is also outlined.
Recently, computational fluid dynamics (CFD) has been frequently applied in many fields relating to fluid flow, and it has been shown that CFD is useful in these fields. The cooling rate and quality of foodstuffs in a cold store are highly dependent on the temperature field which is closely related to flow field. However, the flow field designed by using traditional methods, using a lot of time and cost without reliable and repeatable results, is not good enough. In this paper, a two-dimensional mathematical model for the inside a minitype constructional cold store [4.5 m (l) × 3.3 m (w) × 2.5 m (h)] was proposed and a related computer program with SIMPLE algorithm and crisscross girding technique were developed. The simulation results reflected the characteristics of airflow and temperature distribution. After that, several design parameters (corner baffle, the stack mode of foodstuffs, etc.) which would affect the flow field in the cold store were analyzed. The results of calculation indicated that all these design parameters especially the stack mode of foodstuffs influenced the flow and temperature fields inside the cold store greatly. It was demonstrated that CFD was a powerful tool for designing and optimizing the flow field in cold store.
Computational fluid dynamics (CFD) is a numerical technique for the solution of the equations governing the flow of fluids inside a defined flow geometry. CFD has seen applications in many different processing industries, but it is only in recent years that the technique has been applied to food processing applications, including air flow in clean rooms, ovens and chillers; flow of foods in continuous-flow systems; and convection patterns during in-container thermal processing. In this review article, we discuss the current state of play of CFD in the food industry and also the future advances in the technique that will guarantee its use as a tool for food process engineers.
Understanding and managing the spatial variability of surface soil moisture is a critical issue in solving numerous problems. Stochastic simulation was applied for assessing the probability that soil water content does not exceed a critical threshold that might cause water stress to a forest of laricio pine in an experimental plot located in south Italy. Soil water measurements were made at 152 points with 45 cm long rods using a time domain reflectometer. A probabilistic approach was used to assess the level of topsoil water depletion. It is based on the use of the geostatistical technique of conditional simulation to yield a series of stochastic images of equally probable spatial distributions of the soil water contents across the site.The proposed approach allowed the recognition of explicit uncertainty in soil water assessment and the incorporation of the likelihood that soil dryness may become critical for plants in site characterisation.
In Applied Geostatistics the authors demonstrate how simple statistical methods can be used to analyse earth science data. In clear language, they explain how various forms of the estimation method called kriging can be employed for specific problems. A case study of a simulated deposit is the focus for the book. This model helps the student develop an understanding of how statistical tools work, serving as a tutorial to guide readers through their first independent geostatistical study.
Alveolar echinococcosis is a rare but fatal disease in humans and is caused by the fox tapeworm Echinococcus multilocularis. The densities of fox and grassland rodent populations and the interactions between them influence E. multilocularis transmission rates in Europe. Successful rabies control has caused fox populations and E. multilocularis prevalence rates to increase in many European countries. The potential increase of the infection pressure on the human population motivates the monitoring of the infection status of foxes over space and time. Detection of E. multilocularis antigen levels in fox faecal samples collected in the field might provide a pragmatic methodology for epidemiological surveillance of the infection status in wildlife hosts across large areas, as well as providing an indication of the spatial distribution of infected faeces contaminating the environment. In this paper, a spatial analysis of antigen levels detected in faeces collected in the Franche-Comté region of eastern France is presented. In Franche-Comté, rodent outbreaks have been observed to originate in areas rich in grassland. Spatial trends in fox infection levels were modelled here as a function of the composition ratio of grassland in the landscape derived from the CORINE land-cover map. Kriging models incorporating the grassland trend term were compared to a variety of models in which five alternative trend expressions were used: the alternative trend expressions included linear and quadratic polynomials on the x and y coordinates with and without a grassland term, and a constant mean model. Leave-one-out cross-validation indicated that the estimation errors of kriging with a trend models were significantly lower when the trend expression contained the grassland index term only. The relationship between observed and predicted antigen levels was strongest when the estimated range of autocorrelation was within the home range size of a single fox. The over-dispersion of E. multilocularis in foxes may therefore account for the majority of spatial autocorrelation locally, while regional trends can be successfully modelled as a function of habitat availability for intermediate hosts.
Quality study on strawberries: Experiments with Shasta berries show harvested fruit should be protected against the effects of high field temperatures
- E C Maxie
- F G Mitchell
- A Greathead
Maxie, E.C., Mitchell, F.G. and Greathead, A. 1959. Quality study on strawberries:
Experiments with Shasta berries show harvested fruit should be protected against the
effects of high field temperatures. Calif. Agric. 13:6-6.
Handling strawberries for fresh market
- F G Mitchell
- E J Mitcham
- J F Thompson
- N Welch
Mitchell, F.G., Mitcham, E.J., Thompson, J.F. and Welch, N. 1996. Handling strawberries
for fresh market. Univ. Calif., Div. Agric. Nat. Res., Pub. No. 2442.
La Ciencia de los Alimentos R Development Core Team R: A language and environment for statistical computing. R Foundation for Statistical Computing
- N N Potter
- S A Andrómeda
- México
Potter, N.N. 1992. La Ciencia de los Alimentos. Editorial Andrómeda S.A. México.
R Development Core Team. 2010. R: A language and environment for statistical
computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-
07-0, URL http://www.R-project.org.
R: A language and environment for statistical computing. R Foundation for Statistical Computing
- N N Potter
Potter, N.N. 1992. La Ciencia de los Alimentos. Editorial Andrómeda S.A. México.
R Development Core Team. 2010. R: A language and environment for statistical
computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org.
Temperature (°C) distribution maps predicted by block ordinary kriging technique, for each plane
- Fig
Fig. 3. Temperature (°C) distribution maps predicted by block ordinary kriging technique,
for each plane (P1 to P10) of the experimental cold store.