Roselle calyces are regarded as a source of anthocyanins and many nutrients. Despite their high therapeutic and nutritional value, fresh calyces are highly perishable, necessitating efficient preservation methods. Traditional drying, although cost-effective, often degrades heat-sensitive nutrients due to uncontrolled conditions. This study evaluates the efficiency of two precision drying technologies, specifically a hybrid smart solar dryer (HSSD) and a smart hot air rotary drum dryer (DD), at temperatures of 30°C, 40°C, and 50°C. The investigation focuses on drying kinetics and energy consumption while examining the calyces' physicochemical properties. Findings revealed that the hybrid smart solar dryer consumed 19.61, 21.57, and 24.38 kWh/batch of total energy, whereas the smart hot air rotary DD recorded 19.93, 21.52, and 16.3 kWh/batch at 30°C, 40°C, and 50°C. Notably, microstructural analysis showed that the DD produced less cellular collapse than the hybrid smart solar dryer. The highest total anthocyanin (303.09 mg/100 g) and furfural content (43.90%) were preserved in calyces dried at 30°C and 40°C with the DD, respectively. Conversely, the hybrid smart solar dryer at 50°C was more effective in preserving total phenols and vitamin C. Overall, this research emphasizes that the smart hot air rotary drum dryer operated at 40°C can be considered a blueprint for balancing efficient drying kinetics with the retention of valuable quality measurements, especially the anthocyanin. Future studies should focus on longitudinal economic viability, carbon credit potential, and the scalability of these technologies for other industrial medicinal and aromatic plants.

Agricultural solid residues are frequently underutilized despite their potential for environmental and economic value. Improper disposal practices, such as uncontrolled dumping and open field burning, contribute to environmental degradation and pose risks to human health. In this context, the sustainable management and recycling of agricultural residues have become essential components of environmental integration strategies. Particle size reduction represents a critical processing step for converting agricultural residues into value-added materials suitable for applications including animal feed, fertilizers, and bioenergy production. This study presents the design and development of a hammer mill system and examines the influence of air suction velocity on the particle size characteristics of ground agricultural by-products. The developed system aims to produce cutting lengths appropriate for animal feed applications. A hammer mill integrated with a separate sieving unit and an air suction mechanism was designed and fabricated using locally available materials to process lemongrass (Cymbopogon citratus) solid residues, which are difficult to manage using conventional threshing machine. Experimental results indicate that the developed hammer mill system achieved satisfactory performance in terms of productivity and energy consumption. A maximum productivity of 114 kg·h⁻¹ was obtained at a 7 mm screen opening, a rotor speed of 3120 rpm (≈ 47.4 m·s⁻¹), and an air suction velocity of 23.9 m·s⁻¹. In contrast, the minimum productivity of 40 kg·h⁻¹ was recorded at a 3 mm screen opening, 2440 rpm (≈ 37 m·s⁻¹), and an air velocity of 16.7 m·s⁻¹. The bulk density of the milled material ranged from 37 to 250 kg·m⁻³ at a 3 mm screen opening, while a bulk density of 219 kg·m⁻³ was observed at a 7 mm screen opening. Overall, the developed hammer mill system demonstrates potential as an environmentally integrated solution for the sustainable processing of agricultural residues, offering high productivity, suitable bulk density characteristics, and low energy consumption, thereby supporting improved feed quality and more efficient downstream recycling processes.

The global focus on water scarcity, climate change, and renewable resources underscore the critical need for sustainable solutions. The current research aims to address these issues by introducing a hybrid solar still desalination system (HSSD) that includes a photovoltaic heating system. The motivation behind this study lies in the necessity to advance green desalination technologies, aiming to improve the productivity of conventional solar still distillation units (SSD), especially in remote areas, as well as to reduce carbon emissions, preserve the environment, and achieve sustainability by utilizing renewable resources. The HSSD system boasts a cutting-edge setup designed to elevate the raw water temperature from 60 to 80 degrees C. This is accomplished by using electric heaters with different capacities (0.5, 1, 1.5, and 2 kW) based on the design submerged in the desalination basin to convert the SSD system from passive to active mode. The findings showed that the freshwater productivity of the developed HSSD system is nearly four times that of the passive SSD system. This is clearly demonstrated at 80 degrees C and 2 kW heater capacity, where the highest distilled water productivity was 11.41, 11.26, and 11.1 L/0.6 m2/12h at water depths 0.02, 0.03, 0.04 m, respectively, compared to the passive SSD system that ranged between 2.8 and 3 L/0.6 m2/12h. HSSD achieved the highest reduction in CO2 emission with values ranging from 560.34 to 2395.80 kgCO2/0.6 m2/year at 60-80 degrees C and water depth 0.02-0.04 m.

Abstract In the globe, there is a rise in water demand for agricultural, industrial, and domestic purposes. Single-basin solar stills (SBSS) have been a subject of research in various countries, particularly in regions with water scarcity or limited access to clean drinking water. In this work, SBSS for desalinating high-salinity water were developed, tested, and evaluated based on a developed numerical model using MATLAB R2021a program to predict the best productivity through the best selection of raw materials used to develop the SBSS. A four-inclined SBSS was fabricated and examined experimentally according to numerical model findings for best design parameters at Marsa Matrouh, 31° 21′ 10.44″N, 27°14′14.10″ E, Agricultural Station—Agricultural Research Center (ARC), Egypt. The hourly experimental results are compared with the numerical results. A good correlation between the numerical and the experimental results with variations in water, and glass temperatures of 9, and 18% respectively, and a variation in cumulative productivity by 11%. The results clearly showed that instantaneous productivity increases by decreasing water depth to 10 mm and using the SBSS unit partially insulated from the bottom of the basin. Adding insulation in front of the sides and back of tempered glass increases the shading area and decreases water temperature hence the cumulative productivity by 15%. The cumulative productivity reached 3 L for the SBSS unit partially insulated from the bottom of the basin with an area of 0.6 m2 for only 12 h working system at a water depth of 10 mm.

Rotary drum dryers have been used to dry various products, including medicinal and aromatic plants, to reduce postharvest losses. However, no attention has been paid to investigate the drying medium temperature monitoring, which results in a significant loss of the dried products' quality and increases energy consumption, subsequently raising the drying technology carbon footprint. Therefore, a smart hybrid rotary infrared-heater drum was designed, manufactured, and tested. At 30, 40, and 50 °C for each drying system (IR, heater, and IR + heater), the dryer was examined by assessing the monitoring and control of the drying temperature, drying kinetics, and energy consumption, and its influence on the lemongrass herbs’ quality. The findings showed that the shortest drying time and highest drying rate were achieved with the IR + heater. Moreover, the application of the intelligent system for monitoring and controlling the drying temperature reduced the drying time by values of 9.2, 6, and 3.2 h, and 8.3, 5.7, and 2.6 h at drying temperatures of 30, 40, and 50 °C for the IR and IR + heater, respectively. The highest energy-saving percentages, 71

The hybrid solar smart dryer (HSSD) was established to dry medicinal and aromatic herbs that are sensitive to direct sunlight. This study explores the effectiveness of the HSSD as an indirect solar drying technique in drying lemongrass, thyme, marjoram, and lavender at different temperatures (30, 40, and 50 +/- 2 degrees C), focusing on its ability to retain quality features. The total energy consumption was estimated by values of 27.72 kWh for lemongrass and 43.02 kWh for lavender using HSSD at 50 +/- 2 degrees C. Generally, HSSD showed an improvement in the studied physicochemical quality parameters. The green color retention was with the parameters of 15.60 +/- 0.89, -5.28 +/- 1.92, -3.89 +/- 1.86, and -5.89 +/- 2.40 for lemongrass, thyme, marjoram, and lavender samples, respectively. The highest values of the lemon grass, thyme, marjoram, and lavender oil content (1.96, 1.73, 3.40, and 2.76%, respectively) were obtained when the aromatic herbs were dried using the HSSD at 40 degrees C. This study showcased the effectiveness of solar dryers in preserving the physicochemical properties of lemongrass, thyme, marjoram, and lavender during drying, which could be applied to other food products. HSSD is a promising energy-efficient method that can save 19-36% of energy consumption, reducing the carbon footprint of drying processes and delivering high-quality products.

[This corrects the article DOI: 10.3389/fbioe.2024.1355133.].

A hybrid smart solar dryer (HSSD) based on indirect forced convection and a controlled auxiliary heating system was developed, fabricated, and tested to be convenient for sunny and cloudy weather conditions. The achievements of the developed dryer focus on controlling the temperature of the dryer, increasing the drying rate, reducing energy consumption, and providing high-quality products. The HSSD was tested and evaluated for drying basil and sage herbs at 30, 40, and 50°C. The results showed that the fresh basil and sage leaves of 1 kg with a moisture content of 84.7% and 75.53% (wet basis) were dried within 58, 46, 32 and 38, 28, and 20 h at 30, 40, and 50°C, respectively. Correspondingly, the traditional drying methods achieved 96 h outdoors and 144 h indoors at room temperature. The average of the fabricated flat-plate solar collector efficiency (thermal efficiency, ηfpsc ) was ranged from 49.18% ± 9.52% to 66.02% ± 2.8%. The highest drying rates were achieved with the HSSD method. Moreover, the HSSD method led to a remarkable saving in energy with values ranging from 25.54% to 77.1% versus the traditional drying methods. While the best quality in terms of essential oil content and microbial load for the dried basil and sage herbs was achieved by the HSSD at 40°C. Finally, the HSSD is a promising energy-efficient method where it can save 70% of energy consumption, thus reducing the carbon footprint of drying processes, and providing higher quality products compared to the conventional methods.

Undoubtedly, rapid population growth has sharply increased global food demand. Although the green revolution, accompanied by food industrialization practices, helped a lot in meeting this demand, the food gap is still huge. Regardless of COVID-19, due to that 14% of the world’s food is lost before even reaching the market, and thus the food insecurity prevalence by rate (9.7%), where the food losses are valued at $400 billion annually according to FAO. In the face of such issues related to food insecurity and food losses, drying technology since its inception has been known as the most common operation in food processing and preservation. However, the excessive use of the drying process and exposure to heat for long periods led to a severe deterioration in the physicochemical quality characteristics of these products. At the same time, growing attention on human health through monitoring the quality and safety of food to avoid chronic diseases led to increasing awareness of the consumer to obtaining products with high nutritional value. Therefore, there has been a great and rapid evolution in drying technology to preserve food with high quality. Hence, this chapter aims to shed light on the drying technology evolution in food processing and preservation as one of the most important post-harvest treatments in the agriculture field.

Facing severe climate change, preserving the environment, and promoting sustainable development necessitate innovative global solutions such as waste recycling, extracting value-added by-products, and transitioning from traditional to renewable energy sources. Accordingly, this study aims to repurpose fish waste into valuable, nutritionally rich products and extract essential chemical compounds such as proteins and oils using a newly developed hybrid solar dryer (HSD). This proposed HSD aims to produce thermal energy for drying fish waste through the combined use of solar collectors and solar panels. The HSD, primarily composed of a solar collector, drying chamber, auxiliary heating system, solar panels, battery, pump, heating tank, control panel, and charging unit, has been designed for the effective drying of fish waste. We subjected the fish waste samples to controlled drying at three distinct temperatures: 45, 50, and 55 °C. The results indicated a reduction in moisture content from 75.2% to 24.8% within drying times of 10, 7, and 5 h, respectively, at these temperatures. Moreover, maximum drying rates of 1.10, 1.22, and 1.41 kgH2O/kg dry material/h were recorded at 45, 50, and 55 °C, respectively. Remarkable energy efficiency was also observed in the HSD’s operation, with savings of 79.2%, 75.8%, and 62.2% at each respective temperature. Notably, with an increase in drying temperature, the microbial load, crude lipid, and moisture content decreased, while the crude protein and ash content increased. The outcomes of this study indicate that the practical, solar-powered HSD can recycle fish waste, enhance its value, and reduce the carbon footprint of processing operations. This sustainable approach, underpinned by renewable energy, offers significant environmental preservation and a reduction in fossil fuel reliance for industrial operations.

Solar energy is one of the most important solutions to reduce the concerns of the severe climate change phenomenon. Granted, the main manner to harness solar energy to generate power electricity is implemented through arrays made up of PV solar panels. However, the accumulation of dust on PV surfaces nevertheless remains a serious issue that considerably reduces the efficient conversion of PV panels. Therefore, this research is aimed at automating both monitoring and cleaning of the PV panel’s surfaces through the design, manufacture, and operation and evaluating a dry-cleaning robot based on a color monitoring system. The preliminary results demonstrate that the color analysis of the PV panels can distinguish between the density of dust accumulated, where the total color differences between the clean PV panels and both the PV panels with simple, moderate, and intense dust were 43.69, 61.19, and 75.23. This raised the efficiency of the power produced for simple dust panels from 88.03 to 98.91% (one cleaning round), moderate dust panels from 70.72 to 92.96%, and intense dust panels from 39.05 to 62.11% (two cleaning rounds). These preliminary finds illustrate the possibility of using this approach to automatic monitoring the PV panel color and operate the cleaning robot.

In recent decades, the quality and safety of fruits, vegetables, cereals, meats, milk, and their derivatives from processed foods have become a serious issue for consumers in developed as well as developing countries. Undoubtedly, the traditional methods of inspecting and ensuring quality that depends on the human factor, some mechanical and chemical methods, have proven beyond any doubt their inability to achieve food quality and safety, and thus a failure to achieve food security. With growing attention on human health, the standards of food safety and quality are continuously being improved through advanced technology applications that depend on artificial intelligence tools to monitor the quality and safety of food. One of the most important of these applications is imaging technology. A brief discussion in this chapter on the utilize of multiple imaging systems based on all different bands of the electromagnetic spectrum as a principal source of various imaging systems. As well as methods of analyzing and reading images to build intelligence and non-destructive systems for monitoring and measuring the quality of foods.

In light of the great technological progress in non-destructive quality detection methods, sweetness is no longer the essential parameter in evaluating watermelon quality. There is an aspiration to determine physicochemical quality characteristics to enable us to select the best cultivars, agricultural practices, and harvest dates. In the present work, three different watermelon cultivars (Lady, Galander, and Style) were harvested at three consecutive harvest times. Two pieces were taken from each watermelon sample, one from the middle (part A) and the other from the ends (part B), to track the intensity of quality parameters inside the watermelon. Parts A and B were subjected to Vis/NIR spectroradiometer (475:1075 nm), near-infrared spectroscopy (NIRS) (950:1650 nm), and high-performance liquid chromatography to assess the physicochemical quality. Calibration and prediction models were conducted using partial least squares regressions (PLS). The results indicated that the harvesting time significantly influenced the color and chemical parameters. Quality parameters concentrations markedly degraded towards late harvest. The highest concentrations of quality parameters were sighted for the middle zone (part A), especially in the Galander cultivar. Spectroradiometer achieved the best coefficient of prediction (R2P) ≃ 0.88 and 0.81 attached with the lowest value of the standard error of prediction (SEP) ≃ 0.03 and 1.06 for chroma (C*) and yellowness index (YI). However, the findings showed the superiority of the NIRS compared to the Vis-NIR method. The highest R2P was achieved by values 0.92, 0.91, 0.90, 0.89, 0.85, and 0.85 for lycopene, total carotenoids, vitamin C, β-carotene, γ-content, and TSS, respectively. It could be concluded that the NIRS has the ability to monitor the maturity development and determine the harvest dates practically and reliably.

The assessment and assurance of the quality attributes of dates is a key factor in increasing the competitiveness and consumer acceptance of this fruit. The increasing demand for date fruits requires a rapid and automated method for monitoring and analyzing the quality attributes of date fruits to replace the conventional methods used by inspection which limits the production and involves human errors. Moisture content (MC), dry matter content (DMC), and firmness (F) are three important quality attributes for two date cultivars (Khalas and Sukkari) that have been inspected using the hyperspectral imaging (HSI) technique based on the reflectance mode. Images of intact date fruits at the maturity stage Tamr were obtained within the wavelength range of 950–1750 nm. Monitoring and assessment of MC, DMC, and F [first maximum rupture force (MF, N)] were performed using a partial least squares regression model. Accurate prediction models were attained. The results highlight that the coefficients of determination (R2 Prediction) are estimated to be 0.91 and 0.89 for MC, DMC, and F (N) with the lowest values of the standard error of prediction (SEP) equal to 0.82, 0.81 (%), and 4.12 (N), respectively, and the residual predictive deviation (RPD) values were 3.65, 3.69, and 3.42 for MC, DMC, and F (N), respectively. The results obtained from this preliminary study indicate the great potential of applying HSI for the assessment of physical, chemical, and sensory quality attributes of date fruits overall in the five maturity stages.

Tomatoes are consumed as fresh and processed products, which contain nutritionally important phytonutrients. It is necessary to use a rapid and reliable analytical method to monitor the quality of tomato products. The study was conducted to study the feasibility of near-infrared spectroscopy (NIRS) and color measurement with data obtained from high-performance liquid chromatography (HPLC), for monitoring the change in tomato juice, as a consequence of thermal and high hydrostatic pressure (HHP) treatments at different conditions. Partial least squares regression was applied to assess the correlation between HPLC values of ascorbic acid (A.A.), lycopene (Lyc.), beta-carotene (beta-car.), and NIRS. The correlation was confirmed with R-P(2) of .82, .92, and .91 based on the lowest values of the standard error of prediction (SEP) for A.A., Lyc., and beta-car., respectively. The lowest degradation of A.A. (35% and 49%), Lyc. (12% and 3.6%), and beta-car. (23.3% and 18.4%) was recorded for juice thermally processed and HHP treated, respectively. Novelty impact statement Overdosage of food processing methods and exposure times generate food products that are poor in nutritional value. The results confirmed the ability of the near-infrared spectroscopy to determine, measure, and predict the internal quality characteristics (ascorbic acid, lycopene, and beta-carotene) values of processed tomatoes and choose the best treatment methods and doses that afford the best quality to the final product. With increasing consumer awareness and market needs for healthy, and high nutritional value foods, the food industry will have profited from the nondestructive methods for quality detection, which in turn will determine the best processing methods, the optimum dosages, and the appropriate exposure time for processing. Hence, this technique is beneficial to produce high nutritional value food products able to meet the market needs, competition, and consumer satisfaction.

Aiming at investigating the feasibility of time-resolved reflectance spectroscopy (TRS) for the non-destructive detection of internal brown spot (IBS) and other defects in ‘El Beida’ potatoes, 90 tubers were measured in 8 points by TRS for the absorption coefficient at 730 nm (µa730) and then transversally cut open for recording presence and position of internal defects and IBS severity. The µa730 was lower in healthy tissue than in defected ones and increased with increasing IBS severity with no difference between healthy and slightly IBS tissues. Tubers having at least one out of the eight µa730 measures ≥ 0.04262 cm-1 were considered “defected”. Therefore, TRS tubers classification performance were: defected, 73.5%; healthy, 45.5%; slightly IBS, 57.1%; moderate IBS, 60%; and severe IBS, 100% of the cases. Misclassification could be due to the high variability in flesh color of ‘El Beida’ potatoes, as some healthy tubers showed L*, b* and C* color parameters very similar to that of defected ones, especially when IBS severity was slight or moderate, resulting in µa730 values not significantly different between healthy and IBS tissues. The feasibility of TRS in detecting internal disorders in potatoes must be investigated in other susceptible cultivar to see if flesh color can represent a real problem in the detection of defects linked to browning development.

In this investigation, an automated vision system "AVS" for non-destructive quality inspection of potato tubers "PT" was developed. Color, size, mass, firmness, and the texture homogeneity of the "PT" surface, various sensitive features were studied, and extracted from the digital image by using the R program. Otsu threshold method, RGB, Lu*v*, CIE LChuv color models, and texture analysis by using the package Gray-Level Co-Occurrence Matrices (GLCMs) were applied. The results showed a great correlation between the tuber pixel area percentages (DIM=dimension as a percentage of total pixels), and both mass and geometric mean diameter (GMD) of all "PT" varieties. The color results demonstrated that the hue angle (huv) ranged from 68.92 to 96.61°, and the "PT" color was classified into deep and light color intensity. The "AVS" could predict the mass and size, and gave statistical data at the mass production level, in terms of the inspecting samples No., mass, and grades based on size, color, and free from injuries through the texture homogeneity of tuber surface. A predictive model hypothesized based on the tuber's surface texture characteristics for predicting the tubers firmness was statistically significant. This "AVS" can be applied as a non-destructive, precise, and symmetric technique in-line inspection, the quality of "PT", also helping decision-makers in the agricultural field and stakeholders to improve the horticulture sector through the statistical data issued by this system.

This work aimed at studying the relationships between the absorption spectra acquired by time-resolved reflectance spectroscopy (TRS) and the carotenoid (CAR) and/or the anthocyanin (ANT) contents in 9 potato genotypes with different flesh color (white, yellow, red, purple). Fifty whole and intact tubers/genotype were non-destructively measured by TRS in the 540-980 nm range; white- and yellow-fleshed were ranked according to increasing µa540, the red ones according to µa670 and the purple ones according to µa780. Then, 5 tubers/genotype, corresponding to the highest, the lowest and 3 intermediate values of each μa range, were analyzed for flesh color and CAR and ANT contents. In white- and yellow-fleshed genotypes, µa540 ranged from 0.078 to 0.207 cm-1, showing the highest value in ‘Melrose’ and in ‘ISCI 133/12-1’ and the lowest ones in ‘Romantica’ and in ‘CN 07.16.3’. In red-fleshed tubers, µa670 ranged from 0.049 to 0.146 with no significant differences between genotypes; in purple genotypes, µa780 ranged from 0.147 to 0.473, showing the highest values in ‘Bleuet’. CAR content ranged between 0.071 to 5.937 mg kg-1 FW, displaying the highest amounts in the deep yellow genotypes ‘Melrose’ and ‘ISCI 133/12-1’ and the lowest ones in the white ‘CN 07.16.3’ and in the dark purple ‘Bleuet’ tubers. ANT content ranged from 31.63 to 798.44 mg kg-1 FW in red-purple genotypes, having the highest values in ‘Bleuet’. By using TRS spectra and PLS analysis, it was possible to predict CAR (R2CV=0.79, RMSECV=0.89) and ANT (R2CV =0.81, RMSECV=95.53) contents and flesh color (h°) in yellow-fleshed genotypes (R2CV =0.93, RMSECV=0.67) and purple genotypes (R2CV =0.82, RMSECV=1.63).

Infrared technology has brought a quantum leap in the specialization of non-destructive systems for internal quality inspection of agricultural and food products. Applying near-infrared spectroscopy technique (NIRs) for tracking and estimating some antioxidants such as (Lycopene, ?-carotene, Phytoene and Phytofluenxe) in tomato fruit fractions (Exocarp, Mesocarp, Endocarp and Tomato pomace) with prediction model. High-performance liquid chromatography (HPLC) device showed the antioxidant concentrations values within tomato fractions. Where, the maximum and minimum values observed in the mesocarp and exocarp fractions. Also, tomato fractions color analysis confirmed these results. Meanwhile, mesocarp fraction within range dark red color with h°? 31.7°, due to increased lycopene concentration, whereas, exocarp fraction was 77.29° for h°, within yellow range. In addition to HPLC and color reference methods were consensus significantly with the different of spectral transformations by the regression of partial least square (PLS). NIR spectra and antioxidant in tomato fractions were taken to establish calibration models for tracking and estimating antioxidant in tomato fractions by using partial least squares (PLS) model. The obtained Coefficients of prediction model (R2p) were 0.95, 0.91, 0.93 and 0.94 for Lycopene, ?-Carotene, Phytoene and Phytofluenxe respectively. The values of (RPD) ratio obtained from the standard deviation to the standard error of prediction and also (RER) obtained from the standard error range of prediction model were varied for different tomato fractions and antioxidant content, and found that the NIR model suitable not only for screening the different concentrations values of antioxidants for tomato fractions, but also suitable for most applications including quality assurance.