Search Results (140)

Residential and agricultural buildings must prioritize environmental sustainability, employing locally sourced, bio/geologically sustainable materials, and reversible construction methods. Hence, adobe construction and earth-based building methods are experiencing a comeback. This article describes the hygrothermal performances of a real scale agricultural building prototype, in real field conditions, built and designed to be energy-efficient, environmentally friendly, and well-suited for the hot, dry climates typical of the Mediterranean region during summer. The building prototype is a small modular two room construction, one room based on wood (for control purpose) and the other one on raw earth. The experimental set up highlights the passive cooling and humidity regulation potential provided by raw earth and adobe brick technology in agricultural buildings used for fruit and vegetable storage. Such passive cooling alternatives in the Mediterranean climate could reduce the need for energy-intensive and environmentally impactful cold storage rooms. Full article

The visual colorimetric sensing of total volatile basic nitrogen (TVB-N) allows for convenient dynamic monitoring of animal-derived food freshness to ensure food safety. The agarose hydrogel loaded with the natural dye juglone (Jug@AG) prepared in this study exhibits visible multicolor changes from yellow to grayish-yellow and then to brownish with increasing TVB-N gas concentration, achieving sensitive detection of TVB-N gas at concentrations as low as 0.05 mg/dm³ within 8 min. The minimum observable amounts of TVB-N in spiked pork and fish samples are 8.43 mg/100 g and 8.27 mg/100 g, respectively, indicating that the Jug@AG hydrogel possesses sensitive colorimetric sensing capability in practical applications. The Jug@AG hydrogel also shows significant changes in color difference value (∆C) under both room temperature (25 °C) and cold storage (4 °C) conditions, with the changing trends of ∆C showing consistency with the measured TVB-N and total viable counts (TVC) during the transition of pork and fish samples from freshness to early spoilage and then to spoilage. The results indicate that the Jug@AG hydrogel can be used as a colorimetric sensor to achieve real-time dynamic freshness monitoring of animal-derived food. Full article

It is a well-known fact that proper nutrition is essential for human beings to live healthy lives. For thousands of years, it has been considered that dates are one of the best nutrient providers. To have better-quality dates and to enhance the shelf life of dates, it is vital to preserve dates in optimal conditions that contribute to food security. Hence, it is crucial to know the shelf life of different types of dates. In current practice, shelf life assessment is typically based on manual visual inspection, which is subjective, error-prone, and requires considerable expertise, making it difficult to scale across large storage facilities. Traditional cold storage systems, whilst being capable of monitoring temperature and humidity, lack the intelligence to detect spoilage or predict shelf life in real-time. In this study, we present a novel IoT-based shelf life estimation system that integrates multichannel gas sensors and a lightweight machine learning model deployed on an edge device. Unlike prior approaches, our system captures the real-time emissions of spoilage-related gases (methane, nitrogen dioxide, and carbon monoxide) along with environmental data to classify the freshness of date fruits. The model achieved a classification accuracy of 91.9% and an AUC of 0.98 and was successfully deployed on an Arduino Nano 33 BLE Sense board. This solution offers a low-cost, scalable, and objective method for real-time shelf life prediction. This significantly improves reliability and reduces postharvest losses in the date supply chain. Full article

The implementation of low-cost sensitive and selective gas sensors for monitoring fruit ripening and quality strongly depends on their long-term stability. Gas sensor drift undermines the long-term reliability of low-cost sensing platforms, particularly in precision agriculture. We present a real-time drift compensation framework based on a lightweight Temporal Convolutional Neural Network (TCNN) combined with a Hadamard spectral transform. The model operates causally on incoming sensor data, achieving a mean absolute error below 1 mV on long-term recordings (equivalent to <1 particle per million (ppm) gas concentration). Through quantization, we compress the model by over 70%, without sacrificing accuracy. Demonstrated on a combustion-type gas sensor system (dubbed GMOS) for ethylene monitoring, our approach enables continuous, drift-corrected operation without the need for recalibration or dependence on cloud-based services, offering a generalizable solution for embedded environmental sensing—in food transportation containers, cold storage facilities, de-greening rooms and directly in the field. Full article

(1) Background: This study aimed to investigate the bacterial microbiomes in the ingredients and final PBM products during a storage period of 28 days at 2–4 °C for food safety and quality. (2) Methods: DNA from raw ingredients (i.e., defatted soy flour, potato starch, wheat gluten, mung bean protein, and duckweed) and three PBM formulations were extracted and sequenced using 16S rRNA gene sequencing. (3) Results: Alpha diversity (Simpson and Shannon) was high in the raw ingredients (p ≤ 0.05). Beta diversity showed dissimilarities between the samples. Firmicutes and Proteobacteria were the core microflora in these ingredients. The heat-stable microbes in PBM (e.g., Nostocaceae in SF and Cyanobacteriale in MB and DW) survived after extrusion. After the ingredients were stored at room temperature, the bacterial communities shifted, with Paucibacter being the majority population in raw ingredients and PBM in the 2nd batch. The predictions of Potential_Pathogens related to the abundance of Aeromonadaceae and Enterobacteriaceae need to be monitored during storage. (4) Conclusions: Our results showed that the bacterial community in PBM containing 30% MB and 3% DW did not drastically change during 28 days of storage at cold temperatures. Uncovering bacterial microbiomes in the ingredients should be emphasized for quality and safety, as ingredients influence the microbiome in the final products. Full article

The title compound, 4,4-dichloro-1,3-dithietane-2-one, was encountered when opening a commercial capped amber bottle labeled “thiophosgene” that had been stored in a cold room (4 °C) for decades without any special precautions. Treating it as an unknown, the structure was established by single crystal X-ray analysis, and confirmed by ¹³C NMR, FTIR, melting behavior, and elemental analysis; its behavior under several mass spectrometric conditions was also examined. The dithietane appears to be a spontaneously formed cyclodimer of thiophosgene in which exactly one (not zero, not both) of the dichloromethylene moieties has been hydrolyzed to a carbonyl function. The relative long-term stability of the hydrolyzed dimer, along with a pathway back to thiophosgene, suggests that it might serve as a storage vehicle for toxic thiophosgene. Furthermore, as noted elsewhere, the title compound reacts with nucleophiles under mild aqueous conditions, suggesting that it may be a useful probe in chemical biology. Full article

The biological role of the fluorescence of flowers is a matter of debate. Anthocyanins are a group of compounds that are weakly fluorescent; their fluorescence in flowers has been rarely studied. This study aimed to compare the absorption and fluorescence spectra of anthocyanins extracted from several anthocyanin-containing autumn flowers and examine changes in these spectra during the storage of petals at cold-room and room temperatures and during the storage of dried petals. Petals of red clover Trifolium pratense, pink petunia Petunia × hybrida, Pelargonium horatum, Pelargonium. zonale, Pelargonium. peltatum, red and pink Begonia semperflorens, Buddleja japonica, and purple Chrysanthemum were studied. The results demonstrate that it is possible to distinguish between petals of various flowers based on the absorption spectra of petal extracts and the fluorescence spectra of petal extracts and intact petals. Spectral changes during storage were not always unidirectional and progressive; the most common one was the increase in the intensity of the fluorescence band at 500–560 nm at the excitation wavelength of 460 nm. These results point to the possibility of using fluorescence measurements to identify and estimate the freshness of petal-based material in herbalism, forensic analysis, and the food industry. The measurement of the spectra of whole petals or their fragments by front-face fluorimetry, including common plate readers, may be especially useful due to its simplicity and rapidity. Full article

While cold chain transportation facilitates the utilization of wine grapes grown in remote mountainous areas, there is currently a lack of research on the impacts of different post-harvest temperatures on the quality of wine grapes. Therefore, three temperatures—room temperature (20 °C), chilled (4 °C), and frozen (−20 °C)—were selected to study the effects of post-harvest low-temperature treatments. The results indicated that the contents of tartaric acid and total polyphenols in the resulting wines were higher after the grapes underwent freezing, while the opposite trend was observed for those stored at room temperature. The changes in color lightness of wines were inversely correlated with the changes in color saturation and red chromaticity, while the yellow chromaticity of wines fermented after storage exhibited a slight increase. Rutin and ferulic acid were identified as the characteristic monophenols that decreased post-storage, and heptanal emerged as the volatile compound that decreased similarly. Furthermore, the tannin contents of the resulting wines demonstrated a strong correlation with temperature: when grapes were chilled, they reached the highest level, presenting a decreasing trend over time. For low-temperature storage, 1-hexanol, ethyl caprylate, isopentyl acetate, and (Z)-2-heptenal were identified as characteristic volatile compounds under the different treatments. Overall, the choice of an appropriate chilling temperature for the post-harvest storage of grapes can ensure the quality characteristics of the produced wine. This study confirms the potential value of cold chain transportation for the effective utilization of wine grapes grown in remote areas. Full article

Seed propagation is the primary means of reproducing many native and endemic species, including garberia [Garberia heterophylla (W. Bartram) Merrill & F. Harper]. This attractive pollinator plant, native to Florida, is scarcely found in nursery production and largely unknown to the gardening community. To better understand the seed biology of garberia, a series of experiments were conducted to evaluate the effects of population on seed viability and germination response to four seasonal temperatures, as well as the effects of time on seed storability. Initial seed viability was 49% and 60% for Central and North Florida populations, respectively. Seeds germinated readily, indicating non-dormancy, with significant effects of population and temperature observed. Overall, on day 28, a greater germination proportion was observed from seeds collected from North Florida than Central Florida across temperatures, except for winter (11/22 °C), where responses were similar. The greatest germination proportion for seeds collected from North Florida was observed at 15/27 °C (fall) and 19/29 °C (spring), whereas the greatest germination from Central Florida was observed at 11/22 °C (winter), with the steepest decline observed at summer temperatures (24/33 °C). Further, it was observed that garberia seeds are intolerant of long-term storage, losing viability as early as 3 months under conventional cold or room temperature storage and decreasing substantially more after 6 months. These findings contribute to the overall understanding of the seed biology of underutilized species such as garberia, key to the development of efficient and reliable propagation systems for our nursery industry. Full article

As automotive technology advances, ensuring efficient and reliable vehicle storage systems becomes increasingly important to vehicle edges. Environmental factors, like extreme cold or intense heat, can greatly affect how well these critical components function. In this paper, we study the effects of different temperatures on flash-based vehicle storage systems, especially how these conditions impact data storage workloads, machine learning workloads, and vehicle edge computing by analyzing the read and write performance of car flash memory. Our approach combines environmental simulations, performance testing, and data analysis to examine how temperature changes affect the performance and reliability of vehicle storage. By testing conditions from standard room temperatures to extreme heat, this study explores how such environments influence the speed, dependability, and overall functionality of flash memory in automotive systems. The results show detailed relationships between temperature changes and the speed (throughput) and delay (latency) in flash storage, identifying areas where these systems may be vulnerable or where improvements could be made. Understanding these dynamics is essential for improving the durability and flexibility of automotive storage systems and vehicle edges in various environmental conditions. We have refined our conclusions to note that while our findings provide insights into temperature-related performance shifts, they represent one piece of a broader set of design considerations for engineers and manufacturers. Rather than offering definitive guidance for policymakers, our findings primarily help illustrate potential thermal vulnerabilities, informing ongoing work toward more robust and reliable vehicle storage systems. As the automotive industry continues to innovate, this study offers an initial foundation for future developments in vehicle storage technology. Full article

This study aims to comprehensively evaluate the internal quality changes in apples during storage via near-infrared spectroscopy. Specifically, we focus on the performance differences in different apple varieties under diverse storage conditions and construct predictive models to determine the optimal storage period. By using near-infrared spectroscopy technology, 384 samples of four apple varieties (Xinjiang Akesu, Wafangdian Huangyuanshuai, Shandong Fuji, and Luochuan Fuji) were analyzed to monitor the changes in their soluble solid content (SSC) and fruit firmness within 7 weeks. The results indicated that, under cold storage conditions, SSC and firmness gradually decreased after peaking between the third and fifth weeks, while the opposite trend was observed at room temperature. To enhance the predictive accuracy of the model, several pretreatment methods were employed, including standardization, multiplicative scatter correction (MSC), and standard normal variate transformation (SNV). Additionally, competitive adaptive reweighted sampling (CARS) and uninformative variable elimination (UVE) were utilized for band selection. These pretreatment and selection processes significantly reduced noise and improved model reliability. The best results were achieved with the Normalization-CARS-PLS model for the sugar content at 1 °C, which demonstrated an optimal predictive correlation coefficient (Rp) of 0.904 and a root mean square error of prediction (RMSEP) of 0.67. For firmness at room temperature, the Normalization-CARS-PLS model also showed an excellent performance, with an Rp of 0.823 and an RMSEP of 0.809. The study of the quality of four varieties of apples under three storage conditions in this paper was able to analyze the changes in the internal quality of apples and predict the optimal storage period of different varieties of apples, which is important for guiding the optimal storage period of apples before ripening. Full article

Cold chain temperature management is crucial for preserving product quality and safety across various industries. While Computational Fluid Dynamics (CFD) provides detailed insights into thermal analysis and fluid dynamics, its computational intensity limits practical applications. This study presents a novel hybrid approach combining CFD and machine learning to enhance both computational efficiency and prediction accuracy in cold storage temperature management. A validated 3D CFD model was developed to analyze temperature distribution and airflow patterns in a refrigerated container with multiple storage boxes. Taking advantage of the cold room’s symmetrical design along its longitudinal axis significantly reduced computational requirements while maintaining model accuracy. Over 200 cases were simulated by varying key process parameters to generate training data for machine learning models. Random Forest (RF) and Neural Network (NN) models were developed and compared, with RF demonstrating consistently superior performance across all storage locations. Feature importance analysis revealed cold air temperature as the dominant control variable, while SHAP analysis identified optimal operational ranges for air velocity and heat transfer coefficients that balance product quality with energy efficiency. This research work also revealed distinct patterns in the influence of process parameters, with cold air and ambient temperatures showing hierarchical impacts on system performance. The hybrid methodology successfully addresses the computational limitations of traditional CFD approaches while maintaining high prediction accuracy, offering a practical solution for sustainable temperature management in cold storage applications. Finally, this research provides valuable insights for optimizing cold chain operations and demonstrates the potential of hybrid modeling approaches in thermal management systems. Full article

Climate change increases the importance of maintaining environmental conditions suitable for preventive conservation within museums. The microclimates at the Natural History Museum of Vienna, a large national collection housed within a classical building, were studied using >200 data loggers placed from mid 2021 to provide thermo-hygrometric measurements at 15 min intervals. Daily mean temperatures showed exhibition halls typically had the warmest rooms. This was due to the heating in winter and open windows on summer days. The halls can become even hotter than the outside temperature. In winter, most areas of the museum were very dry, as heating lowered the relative humidity, typically to 25–35% for the coldest season. Opening hours imposed daily and weekly cycles on the internal climate. There was little difference between sunny and shaded parts of the building or adjacent offices, corridors and depots. Similarly, the microclimate at the floor resembled that of the room air some ~2 m above. Mechanically controlled microclimates in cold storage areas maintained 10 °C and relative humidity ~50%, but this had become increasingly difficult in hot summers. While there was little apparent damage to the collection, at times, the museum had an extreme indoor climate: very hot in the summer and dry in the winter. Full article

The refrigeration (cold storage) of platelet components provides several benefits over room-temperature (RT) storage, extending the shelf-life up to 21 days. However, the effect of storage conditions on platelet activation in response to stimulation remains unclear. A paired study was conducted where buffy-coat platelet concentrates were pooled, split, and allocated to RT or cold storage (n = 6 in each group). Platelet samples were taken on days 1, 7, 14, and 21, which were tested without stimulation or following activation with TRAP-6, A23187, lipopolysaccharides, or Histone-H4. Imaging flow cytometry was used to assess the surface characteristics of platelets and extracellular vesicles (EVs). The supernatant concentration of EGF, RANTES, PF4, CD62P, IL-27, CD40L, TNF-α, and OX40L was examined using ELISA. Cold-stored platelets generated a greater proportion of procoagulant platelets and EVs than RT-stored platelets in response to stimulation. The supernatant of cold-stored components contained lower concentrations of soluble factors under basal conditions, suggesting that platelet granules were better retained. Cold-stored platelets released higher concentrations of soluble factors following stimulation with TRAP-6, A23187, or Histone-H4. Only cold-stored platelets responded to lipopolysaccharides. These data demonstrate that cold-stored platelets retain the capacity to respond to stimuli after 21 days of storage, which may facilitate improved functional post-transfusion. Full article

This study aimed to evaluate the effect of two-year storage of varietal honeys (buckwheat, linden, rapeseed, honeydew, and multifloral) at various temperatures (4 °C, −18 °C, −40 °C, and −80 °C) on the content of 5-hydroxymethylfurfural (5-HMF), diastase number (DN), and color assessed in the CIE L*a*b* system. The control samples were stored at room temperature (RT, ca. 20 °C). The results indicate that storing honey at low temperatures effectively mitigates undesirable quality changes, particularly enzymatic degradation and color alterations, while preventing excessive 5-HMF accumulation. After storage, a significant (p ˂ 0.01) decrease was noted in the diastase number (DN) of the honeys, regardless of the temperature (by ca. 66.7% at RT and by 53.1% to 58.3% at low temperatures, p > 0.05). Low storage temperatures led to higher enzymatic activity in buckwheat, linden, and honeydew honeys compared to rapeseed honeys. RT significantly (p ˂ 0.01) increased 5-HMF concentration by 79.3%, whereas the cold and frozen storage conditions increased 5-HMF concentration only by 25.1% at −18 °C and 33.2% at 4 °C. The greatest color changes manifested by significant (p ˂ 0.01) darkening, with a decrease in the h° value (p ˂ 0.01), and a lower contribution of the yellow color and a greater contribution of red color (p > 0.05) in the color profile were noted in the honeys stored at RT. Storage at this temperature resulted in a significantly (p ˂ 0.01) higher total color difference of the honeys (ΔE = 9.53) compared to the other temperatures tested (3.71 < ΔE < 5.58). The low storage temperatures may elicit a positive and comparable effect on preserving the satisfactory quality of the analyzed varietal honeys. It is noteworthy that this positive effect could already be achieved at a storage temperature of +4 °C without the need to apply frozen storage temperatures, which is essential given the economic and environmental concerns. Full article