Search Results (16)

The triboelectric nanogenerator (TENG) is an efficient mechanical energy harvesting device that exhibits excellent performance in the fields of micro-nano energy harvesting and self-powered sensing. In practical application scenarios, it is very important to monitor the speed of rotational machinery in real time. In order to monitor a wider range of rotational speeds, the TENG based on a machine learning algorithm is designed in this paper. The peak power of the TENG reaches a maximum of 6.6 mW and can instantly light up 65 LEDs connected in series. The results show that machine learning can detect speed, greatly improving the speed detection range. The neural network is trained and tested based on the collected electrical signals at different speeds so as to monitor the health of the machine. For the analysis of the collected experimental data, normalization data and a more practical label assignment method of Gaussian soft coding were considered. The study found that after data normalization, the classification prediction accuracy for different speeds is above 0.9, and the prediction results are stable and efficient. Therefore, the machine learning prediction model for speed monitoring proposed by us can be applied to the early warning and monitoring of rotating machinery speed in actual engineering projects. Full article

The contamination of water by heavy metals poses an escalating risk to human health and the environment, underscoring the critical need for efficient removal methods to secure safe water resources. This study evaluated the performance of four cationic exchange materials (labeled “PS—DVB”, “PA—DVB”, “TFSA”, and “OGL”) in removing or harvesting metals such as copper, silver, lead, cobalt, and nickel from aqueous solutions, several of which are precious and/or classified as Critical Raw Materials (CRMs) due to their economic importance and supply risk. The objective was to screen and benchmark the four ion exchange materials for water treatment applications by investigating their metal sequestration capacities. Experiments were conducted using synthetic solutions with controlled metal concentrations, analyzed through ICP-OES, and supported by kinetic modeling. The adsorption capacities (qe) obtained experimentally were compared with those predicted by pseudo-first-order and pseudo-second-order models. This methodology enables high precision and reproducibility, validating its applicability for assessing ion exchange performance. The results indicated that PS—DVB and PA—DVB resins proved to be of “wide range”, exhibiting high efficacy for most of the metals tested, including CRM-designated ones, and suggesting their suitability for water purification. Additionally, the second-life Nafion-based “TFSA” material demonstrated commendable performance, highlighting its potential as a viable and technologically advanced alternative in water treatment. Lastly, the lignin-based material, “OGL”, representing the most innovative and sustainability apt option, offered relevant performance only in selected cases. The significant differences in performance among the resins underscore the impact of structural and compositional factors on adsorption efficiency. This study offers valuable insights for investigating and selecting new sustainable materials for treating contaminated water, opening new pathways for targeted and optimized solutions in environmental remediation. Full article

In the agricultural sector, utilizing robots for tasks such as fruit harvesting poses significant challenges, particularly in achieving accurate 6D pose estimation of the target objects, which is essential for precise and efficient harvesting. Particularly, fruit harvesting relies heavily on manual labor, leading to issues with an unstable labor supply and rising costs. To solve these problems, agricultural harvesting robots are gaining attention. However, effective harvesting necessitates accurate 6D pose estimation of the target object. This study proposes a method to enhance the performance of fruit-harvesting robots, including the development of a dataset named HWANGMOD, which was created using both virtual and real environments with tools such as Blender and BlenderProc. Additionally, we present methods for training an EfficientPose-based model for 6D pose estimation and ripeness classification, and an algorithm for determining the optimal harvest sequence among multiple fruits. Finally, we propose a multi-object tracking method using coordinates estimated by deep learning models to improve the robot’s performance in dynamic environments. The proposed methods were evaluated using metrics such as $ADD$ and $ADDS$, showing that the deep learning model for agricultural harvesting robots excelled in accuracy, robustness, and real-time processing. These advancements contribute to the potential for commercialization of agricultural harvesting robots and the broader field of agricultural automation technology. Full article

Accurate estimates of pasture biomass in grazing lands are currently a time-consuming and resource-intensive task. The process generally includes physically cutting, bagging, labelling, drying, and weighing grass samples using multiple “quadrats” placed on the ground. Quadrats vary in size but are typically in the order of 0.25 m² (i.e., 0.5 m × 0.5 m) up to 1.0 m². Measurements from a number of harvested quadrats are then averaged to get a site estimate. This study investigated the use of photographs and ‘machine learning’ to reduce the time factor and difficulty in taking pasture biomass measurements to potentially make the estimations more accessible through the use of mobile phone cameras. A dataset was created from a pre-existing archive of quadrat photos and corresponding hand-cut pasture biomass measurements taken from a diverse range of field monitoring sites. Sites were clustered and one was held back per model for testing. The models were based on DenseNet121. Individual quadrat errors were large but more promising results were achieved when estimating the site mean pasture biomass. Another two smaller additional datasets were created post-training which were used to further assess the ensemble; they provided similar absolute errors to the original dataset, but significantly larger relative errors. The first was made from harvested quadrats, and the second was made using a pasture height meter in conjunction with a mobile phone camera. The models performed well across a variety of situations and locations but underperformed when assessed on some sites with very different vegetation. More data and refinement of the approach outlined in the paper will reduce the number of models needed and help to correct errors. These models provide a promising start, but further investigation, refinement, and data are needed before becoming a usable application. Full article

‘Tonda Gentile Romana’ and ‘Tonda di Giffoni’ (Corylus avellana L.) are two Italian hazelnut cultivars, recognized under the quality labels “Protected Designation of Origin” (PDO) and “Protected Geographical Indication” (PGI), respectively. Hazelnut seeds are characterized by a complex microstructure and the presence of different physical compartments. This peculiarity has been studied and evidenced by Time Domain (TD) Nuclear Magnetic Resonance (NMR) experiments. This technique allowed the assessment of the presence of different diffusion compartments, or domains, by evaluating the distribution of the spin–spin relaxation time (T₂).The aim of this research was to develop a method based on ¹H NMR relaxometry to study the mobility in fresh hazelnut seeds (‘Tonda di Giffoni’ and ‘Tonda Gentile Romana’), in order to determine differences in seed structure and matrix mobility between the two cultivars. TD-NMR measurements were performed from 8 to 55 °C in order to mimic post-harvest processing as well the microscopic textural properties of hazelnut. The Carr–Purcell–Meiboom–Gill (CPMG) experiments showed five components for ‘Tonda Gentile Romana’ and four components for ‘Tonda di Giffoni’ relaxation times. The two slowest components of relaxation (T_2,a about 30–40% of the NMR signal, and T_2,b about 50% of the NMR signal) were attributed to the protons of the lipid molecules organized in the organelles (oleosomes), both for the ‘Tonda Gentile Romana’ and for the ‘Tonda di Giffoni’ samples. The component of relaxation T_2,c was assigned to cytoplasmic water molecules, and showed a T₂ value dominated by diffusive exchange with a reduced value compared to that of pure water at the same temperature. This can be attributed to the water molecules affected by the relaxation effect of the cell walls. The experiments carried out as a function of temperature showed, for ‘Tonda Gentile Romana’, an unexpected trend between 30 and 45 °C, indicating a phase transition in its oil component. This study provides information that could be used to strengthen the specifications underlying the definitions of “Protected Designation of Origin” (PDO) and “Protected Geographical Indication” (PGI). Full article

Rheumatoid arthritis (RA) is chronic, autoimmune joint inflammation characterized by irreversible joint destruction. Besides increased resorption, destruction is a result of decreased bone formation, due to suppressed differentiation and function of the mesenchymal lineage-derived osteoblasts in inflammatory milieu. In this study, we analyzed the cellular composition of synovial tissue from 11 RA and 10 control patients harvested during planned surgeries in order to characterize resident synovial progenitor populations. Synovial cells were released by collagenase, and labeled for flow cytometry by two antibody panels: 1. CD3-FITC, CD14-PE, 7-AAD, CD11b-PECy7, CD235a-APC, CD19-APCeF780; and 2. 7-AAD, CD105-PECy7, CD45/CD31/CD235a-APC, and CD200-APCeF780. The proportions of lymphocytes (CD3⁺, CD19⁺) and myeloid (CD11b⁺, CD14⁺) cells were higher in synovial tissue from the patients with RA than in the controls. Among non-hematopoietic (CD45⁻CD31⁻CD235a⁻) cells, there was a decrease in the proportion of CD200⁺CD105⁻ and increase in the proportion of CD200⁻CD105⁺ cells in synovial tissue from the patients with RA in comparison to the control patients. The proportions of both populations were associated with inflammatory activity and could discriminate between the RA and the controls. Full article

The identification of cucumber fruit is an essential procedure in automated harvesting in greenhouses. In order to enhance the identification ability of object detection models for cucumber fruit harvesting, an extended RGB image dataset (n = 801) with 3943 positive and negative labels was constructed. Firstly, twelve channels in four color spaces (RGB, YCbCr, HIS, La*b*) were compared through the ReliefF method to choose the channel with the highest weight. Secondly, the RGB image dataset was converted to the pseudo-color dataset of the chosen channel (Cr channel) to pre-train the YOLOv5s model before formal training using the RGB image dataset. Based on this method, the YOLOv5s model was enhanced by the Cr channel. The experimental results show that the cucumber fruit recognition precision of the enhanced YOLOv5s model was increased from 83.7% to 85.19%. Compared with the original YOLOv5s model, the average values of AP, F1, recall rate, and mAP were increased by 8.03%, 7%, 8.7%, and 8%, respectively. In order to verify the applicability of the pre-training method, ablation experiments were conducted on SSD, Faster R-CNN, and four YOLOv5 versions (s, l, m, x), resulting in the accuracy increasing by 1.51%, 3.09%, 1.49%, 0.63%, 3.15%, and 2.43%, respectively. The results of this study indicate that the Cr channel pre-training method is promising in enhancing cucumber fruit detection in a near-color background. Full article

The traceability of typical foodstuffs is necessary to protect high quality of traditional products. It is well-known that several factors could influence metabolites content in certified foods, but soil composition, altitude, latitude and coded production protocols constitute the territorial conditions responsible for the peculiar organoleptic and nutritional properties of labelled foods. Instead, regardless of origin, seasonality, cultivar, collection year can affect all agricultural products, so it is appropriate to include them in data analysis in order to obtain a correct interpretation of the differences linked to growing areas alone. Therefore, it is useful to use a flexible all-round technique, and NMR spectroscopy coupled with multivariate statistical analysis is considered a powerful means of assessing food authenticity. The purpose of this review is to investigate the relevance of year, cultivar, and seasonal period in the determination of food geographical origin using NMR spectroscopy. The strategy for testing these three factors may differ from author to author, but a preliminary study of cultivar or collection year effects on NMR spectra is the most popular method before starting the geographical characterization of samples. In summary, based on the available literature, the most significant influence is due to cultivar, followed by harvesting year, however seasonality is not considered a source of variability in data analysis. Full article

This work presents an advanced photogrammetric pipeline for inspecting apple trees in the field, automatically detecting fruits from videos and quantifying their size and number. The proposed approach is intended to facilitate and accelerate farmers’ and agronomists’ fieldwork, making apple measurements more objective and giving a more extended collection of apples measured in the field while also estimating harvesting/apple-picking dates. In order to do this rapidly and automatically, we propose a pipeline that uses smartphone-based videos and combines photogrammetry, deep learning and geometric algorithms. Synthetic, laboratory and on-field experiments demonstrate the accuracy of the results and the potential of the proposed method. Acquired data, labelled images, code and network weights, are available at 3DOM-FBK GitHub account. Full article

This study aims to determine the physicochemical quality of seagrape (Caulerpa lentillifera) as a freshness label for products cultivated in different seasons. The applied post-harvest storage experiments compared between, within and without seawater that led to oxidative stress conditions. Water content, malondialdehyde (MDA) compound, total phenolic content (TPC), and chlorophyll content were observed at 0, 3, 6, and 9 days of storage. The storage without seawater showed sharper quality reductions by reaching 20–40% of water loss, 70–90% of MDA production, 15–25% of TPC reduction, and 40–60% of total chlorophyll degradation. The storage within seawater showed lower quality reductions due to the specific growth rates still reaching 5–10%. This study found that the greater the physicochemical quality, the slower the decomposition rates of the stored seagrape during storage. Therefore, the seagrapes’ obvious discoloration occurred earlier in winter, followed by summer and spring. Kinetics of chlorophyll degradation on seagrape in different seasons meet different order-reactions during storage. Furthermore, alternating current electric field (ACEF) treatment with 125 kV/m of intensity for 60 min can lower the spring seagrapes’ physicochemical quality by reaching 10–30% of inhibition, resulting in the shelf-life extension for up to 12 days of post-harvest storage. Full article

Modern viticultural areas are being confronted with the negative impacts of global warming on yield and fruit composition, with especially adverse effects on anthocyanin synthesis. Novel and sustainable tools, such as biostimulants, may represent a viable alternative to traditional cultural practices, thus promoting eco-friendly strategies to enhance the yield, fruit quality and abiotic stress tolerance of grapevines. ‘Crimson Seedless’ is a late-season red table grape variety, and due to climatic warming, its berries are frequently failing to acquire the commercially acceptable red color. Canopy applications of different biostimulants, namely, Kelpak^®, Sunred^®, Cytolan^®, LalVigne™ Mature as well as Ethrel^® Top, were tested on grapevine cv. Crimson Seedless grown under semi-arid Mediterranean conditions in order to evaluate their effects on yield and fruit quality. Some of the products were sprayed in canopies at labeled doses, and some were applied at doses reported in other studies. For the control treatment, canopies were sprayed with water. Sampling started at veraison and was repeated at 10-day intervals to measure the evolution of berry weight, length and diameter, as well as the total soluble solids and titratable acidity of the juice. The grapes were harvested when the berries of one of the treatments attained the commercially acceptable color. The greatest improvements in the red berry color were achieved with Sunred^® (at a dose of 4 L ha⁻¹) and Ethrel^® Top (250 ppm plus glycerol at 1%), each applied at veraison and 10 days later. The different applications had varying effects on productivity and qualitative parameters. Only Sunred^® improved the accumulation of anthocyanin and the overall acceptability of table grapes by consumers. The obtained results clearly demonstrate that applying Sunred^® can improve the yield and qualitative parameters of the red table grape variety ‘Crimson Seedless’, indicating that this biostimulant could be a viable alternative to the most widely used plant growth regulator, ethephon. Full article

European consumers have perceived that papaya fruits produced in subtropical areas (the Canary Islands and Mediterranean regions) do not have the desired quality at certain periods of the year. Thus, the development of technical and management strategies to optimize the yield and the quality of the fruit requires crop phenology studies. Meteorological variables (air temperature, relative humidity, and photosynthetically active radiation) and morphological characteristics (plant height, leaf emission rate, and leaf area) were recorded throughout the crop cycle. All the leaves and fruits were labeled in their anthesis week to calculate the source–sink ratio and to study the development and quality of the fruits. Data were collected in three commercial orchards representing two different types of systems, greenhouse and screenhouse, and two different regions: two plastic cover greenhouses located in the south (SP) and in the north (NP) of Tenerife, and one 40-mesh net screenhouse in the north of the island (NN). The selection of these cultivation systems and locations was made deliberately, so that the ambient variables within these crop protection structures were different throughout the cultivation cycle in order to better fit the model construction. The results suggested that in order to maintain good fruit quality, better environmental control is necessary inside the greenhouses and the screenhouse. Monitoring variables such as the growing degree days, the photosynthetically active radiation, and the number of fruits per plant leaf area ratio provided useful information for papaya production management in the Canary Islands and other subtropical areas, allowing farmers to predict harvest and fruit quality. Full article

Food spoilage is a major issue for the food industry, leading to food waste, substantial economic losses for manufacturers and consumers, and a negative impact on brand names. Among causes, fungal contamination can be encountered at various stages of the food chain (e.g., post-harvest, during processing or storage). Fungal development leads to food sensory defects varying from visual deterioration to noticeable odor, flavor, or texture changes but can also have negative health impacts via mycotoxin production by some molds. In order to avoid microbial spoilage and thus extend product shelf life, different treatments—including fungicides and chemical preservatives—are used. In parallel, public authorities encourage the food industry to limit the use of these chemical compounds and develop natural methods for food preservation. This is accompanied by a strong societal demand for ‘clean label’ food products, as consumers are looking for more natural, less severely processed and safer products. In this context, microbial agents corresponding to bioprotective cultures, fermentates, culture-free supernatant or purified molecules, exhibiting antifungal activities represent a growing interest as an alternative to chemical preservation. This review presents the main fungal spoilers encountered in food products, the antifungal microorganisms tested for food bioprotection, and their mechanisms of action. A focus is made in particular on the recent in situ studies and the constraints associated with the use of antifungal microbial agents for food biopreservation. Full article

The turnover of muscle protein is responsive to different (patho)-physiological conditions but little is known about the rate of synthesis at the level of individual proteins or whether this varies between different muscles. We investigated the synthesis rate of eight proteins (actin, albumin, ATP synthase alpha, beta enolase, creatine kinase, myosin essential light chain, myosin regulatory light chain and tropomyosin) in the extensor digitorum longus, diaphragm, heart and soleus of male Wistar rats (352 ± 30 g body weight). Animals were assigned to four groups (n = 3, in each), including a control and groups that received deuterium oxide (²H₂O) for 4 days, 7 days or 14 days. Deuterium labelling was initiated by an intraperitoneal injection of 10 μL/g body weight of 99.9% ²H₂O-saline, and was maintained by administration of 5% (v/v) ²H₂O in drinking water provided ad libitum. Homogenates of the isolated muscles were analysed by 2-dimensional gel electrophoresis and matrix-assisted laser desorption ionisation time of flight mass spectrometry. Proteins were identified against the SwissProt database using peptide mass fingerprinting. For each of the eight proteins investigated, the molar percent enrichment (MPE) of ²H and rate constant (k) of protein synthesis was calculated from the mass isotopomer distribution of peptides based on the amino acid sequence and predicted number of exchangeable C–H bonds. The average MPE (2.14% ± 0.2%) was as expected and was consistent across muscles harvested at different times (i.e., steady state enrichment was achieved). The synthesis rate of individual proteins differed markedly within each muscle and the rank-order of synthesis rates differed among the muscles studied. After 14 days the fraction of albumin synthesised (23% ± 5%) was significantly (p < 0.05) greater than for other muscle proteins. These data represent the first attempt to study the synthesis rates of individual proteins across a number of different striated muscles. Full article

It is well known that plants are important sources for the preparation of natural remedies as they contain many biologically active compounds. In particular, polyphenols, terpenic compounds, organic acids, and vitamins are the most widely occurring groups of phytochemicals. Some endemic species may be used for the production of herbal preparations containing phytochemicals with significant bioactivity, as antioxidant activity and anti-inflammatory capacities, and health benefits. Blackberry sprouts and blackcurrant buds are known to contain appreciable levels of bioactive compounds, including flavonols, phenolic acids, monoterpenes, vitamin C, and catechins, with several clinical effects. The aim of this research was to perform an analytical study of blackcurrant and blackberry bud-preparations, in order to identify and quantify the main biomarkers, obtaining a specific phytochemical fingerprint to evaluate the single botanical class contribution to total phytocomplex and relative bioactivity, using a High Performance Liquid Chromatograph−Diode Array Detector; the same analyses were performed both on the University laboratory and commercial preparations. Different chromatographic methods were used to determine concentrations of biomolecules in the preparations, allowing for quantification of statistically significant differences in their bioactive compound content both in the case of Ribes nigrum and Rubus cultivated varieties at different harvest stages. In blackcurrant bud-extracts the most important class was organic acids (50.98%) followed by monoterpenes (14.05%), while in blackberry preparations the main bioactive classes were catechins (50.06%) and organic acids (27.34%). Chemical, pharmaceutical and agronomic-environmental knowledge could be important for obtaining label certifications for the valorization of specific genotypes, with high clinical and pharmaceutical value: this study allowed to develop an effective tool for the natural preparation quality control and bioactivity evaluation through the chemical fingerprinting of bud preparations. Full article