Search Results (152)

Planting tomatoes in enclosed facilities requires manual pollination assistance. Chemically-assisted pollination poses environmental pollution and food safety hazards. Contact vibration pollination is inefficient, ineffective, and prone to plant damage. This study developed a non-contact tomato pollination device based on pulse airflow, and conducted an experimental investigation on it. Firstly, a non-contact tomato pollination device based on pulse airflow was designed, based on the reciprocating motion of tomato flowers under the action of pulse airflow. Subsequently, this study took the coverage rate of pollen on the stigma as an indicator, and the optimal pulse airflow parameters were determined, which were a velocity of 1.22 m·s⁻¹, airflow angle of −19.69°, and pulse frequency of 25.64 Hz. Finally, comparative experiments were conducted between the pollination effect of tomatoes based on pulse airflow and other assisted pollination methods. The results show that tomato flowers produce a composite reciprocating vibration under the coupling effect of the inflorescence elastic force and the pulse airflow force, and the coverage of pollen on the stigma is 11.2% higher than assisted pollination using stable airflow. The use of a pulse airflow pollination method can increase the fruit setting rate by 13.21%, increase the weight per fruit by 11.46%, and increase the weight of fruits per bunch by 33.33%. Compared with chemically-assisted fruit setting, no chemical agents were used to ensure a fruit setting rate similar to chemical methods, and the number of seeds per fruit increased by 74.8. Compared with vibration pollination, it eliminated plant damage and increased the fruit setting rate by 4.45%, and improved efficiency by 18.6%. The results indicated that the pollination method based on pulse airflow is environmentally friendly, high-quality, and efficient. This study breaks through the theoretical and parameter limitations of traditional airflow pollination devices, and provides a theoretical base for the development of clean pollination equipment in facility agriculture. Full article

The generation of high-quality mid-infrared free-electron laser (MIR-FEL) radiation depends critically on precise control of electron beam parameters, including energy, energy spread, transverse emittance, bunch charge, and bunch length. At the PBP-CMU Electron Linac Laboratory (PCELL), effective beam diagnostics are essential for optimizing FEL performance. However, dedicated systems for direct measurement of transverse emittance and bunch length at the undulator entrance have been lacking. This paper addresses this gap by presenting the design, simulation, and analysis of diagnostic stations for accurate characterization of these parameters. A two-quadrupole emittance measurement system was developed, enabling independent control of beam-focusing in both transverse planes. An analytical model was formulated specifically for this configuration to enhance emittance reconstruction accuracy. Systematic error analysis was conducted using ASTRA beam dynamics simulations, incorporating 3D field maps from CST Studio Suite and fully including space-charge effects. Results show that transverse emittance values as low as 0.15 mm·mrad can be measured with less than 20% error when the initial RMS beam size is under 2 mm. Additionally, quadrupole misalignment effects were quantified, showing that alignment within ±0.95 mm limits systematic errors to below 33.3%. For bunch length measurements, a transition radiation (TR) station coupled with a Michelson interferometer was designed. Spectral and interferometric simulations reveal that transverse beam size and beam splitter properties significantly affect measurement accuracy. A 6% error due to transverse size was identified, while Kapton beam splitters introduced additional systematic distortions. In contrast, a 6 mm-thick silicon beam splitter enabled accurate, correction-free measurements. The finite size of the radiator was also found to suppress low-frequency components, resulting in up to 10.6% underestimation of bunch length. This work provides a practical and comprehensive diagnostic framework that accounts for multiple error sources in both transverse emittance and bunch length measurements. These findings contribute valuable insight for the beam diagnostics community and support improved control of beam quality in MIR FEL systems. Full article

In recent years, the building insulation layer peeling caused by quality problems has brought about safety hazards to human life. Existing means of non-destructive testing of building insulation layers, including laser scanning, infrared thermal imaging, ultrasonic testing, acoustic emission, ground-penetrating radar, etc., are unable to simultaneously guarantee the detection depth and resolution of the insulation layer defects, not to mention high-precision imaging of the insulation layer structure. A new type of high-precision imaging radar is specifically designed for the quantitative quality inspection of external building insulation layers in this paper. The center frequency of the radar is 8800 MHz and the −10 dB bandwidth is 3100 MHz, which means it can penetrate the insulated panel not less than 48.4 mm thick and catch the reflected wave from the upper surface of the bonding mortar. When the bonding mortar is 120 mm away from the radar, the radar can achieve a lateral resolution of about 45 mm (capable of distinguishing two parties of bonding mortar with a 45 mm gap). Furthermore, an ultra-wideband high-bunching antenna is designed in this paper combining the lens and the sinusoidal antenna, taking into account the advantages of high directivity and ultra-wideband. Finally, the high-precision imaging of data collected from multiple survey lines can visually reveal the distribution of bonded mortar and the bonding area. This helps determine whether the bonding area meets construction standards and provides data support for evaluating the quality of the insulation layer. Full article

Elaeis oleifera and Elaeis guineensis, two oil palm species capable of intercrossing to produce interspecific Elaeis oleifera × Elaeis guineensis (O × G) hybrids, exhibit genetic variability in key agronomic traits such as fruit development, oil accumulation, and bunch composition. This variability influences the productivity and oil quality of the resulting hybrids. Harvesting, a critical practice in oil palm production, significantly impacts oil yield and quality. Therefore, this study aimed to ascertain the optimum harvest point (OHP) in widely cultivated O × G hybrids and its correlation with genetic backgrounds. The O × G cultivars, “Coari × La Mé” (C × LM), “Manaos × Compacta” (M × C), and “Brazil × Djongo” (B × DJ), were examined to identify notable changes during various phenological stages of bunch ripening using the O × G BBCH scale, a standardized system for describing plant growth stages based on phenological development. The research was conducted in the Southwest Colombian oil palm zone during dry and rainy seasons. Observations revealed distinctive fruit coloration patterns and increased bunch weights throughout the maturation process. However, final fruit coloration did not consistently align with maximum oil rates, indicating it as an unsuitable descriptor for OHP. The C × LM cultivar exhibited the shortest ripening period (173 days after anthesis, DAA), while M × C showed the longest at 207 DAA, followed by B × DJ at 187 DAA. Pollination efficiency varied among cultivars, with C × LM and M × C displaying higher proportions of parthenocarpic fruits. Findings suggest harvesting can occur for all cultivars between phenological stages 807 and 809—corresponding to late maturity stages in fruit development—regardless of the time of year, when maximum oil per bunch is attained. Fruit opacity, fruit cracking, and fruit detachment at stages 807 and 809 were identified as pivotal descriptors for determining the right OHP, albeit unique to each cultivar. Implementing two of these three descriptors by field workers will likely result in the highest oil yields for O × G cultivars. In conclusion, this research provides valuable insights into optimizing oil palm harvest practices, emphasizing the importance of considering genetic variability and phenological indicators for determining the optimum harvest point in interspecific O × G hybrids. Full article

The cultivation of ‘Shine Muscat’ grapes is rapidly expanding in East Asia due to their desirable qualities and muscat flavor. Studies have revealed that storing these grapes at an controlled freezing-point temperature diminishes their muscat flavor, whereas storage at 10 °C preserves it. However, the impact of a higher storage temperature on the evolution of microbial communities remains unclear. This study aimed to analyze the mycobiota dynamics of ‘Shine Muscat’ grape bunches under different cold storage temperatures. A total of 1,892,842 and 1,643,200 sequences were obtained from berries and pedicels, identifying over 208 fungal genera from 6 phyla. Xylariaceae was the most abundant family, with a prevalence between 7.21% and 69.27% across all sample groups. The primary genera included Zygosporium, Cladosporium, Aspergillus, Acremonium, Podosordaria, Zasmidium, Penicillium, and Alternaria. Spoilage-related fungi varied with storage temperature, with Aspergillus, Penicillium, and Alternaria being dominant at 0 °C and Cladosporium, Aspergillus, Penicillium, and Alternaria being prevalent at 10 °C. The fungal profiles of berries and pedicels differed significantly, and storage temperature further influenced these variations. Our findings highlight distinct fungal diversity and spoilage patterns in ‘Shine Muscat’ grape bunches from the Nanning region compared to those grown in temperate areas, revealing the unique microbial evolution of grape bunches stored at different temperatures in Nanning. Full article

Background: The dark green coloration of bunching onion leaf blades is a key determinant of market value, nutritional quality, and visual appeal. This trait is regulated by a complex network of pigment interactions, which not only determine coloration but also serve as critical indicators of plant growth dynamics and stress responses. This study aimed to elucidate the mechanisms regulating the dark green trait and develop a predictive model for accurately assessing pigment composition. These advancements enable the efficient selection of dark green varieties and facilitate the establishment of optimal growth environments through plant growth monitoring. Methods: Seven varieties and lines of heat-tolerant bunching onions were analyzed, including two commercial ${\mathrm{F}}_1$ cultivars, along with two purebred varieties and three ${\mathrm{F}}_1$ hybrid lines bred in Yamaguchi Prefecture. The analysis was conducted on visible spectral reflectance data (400–700 nm at 20 nm intervals) and pigment compounds (chlorophyll a, chlorophyll b and pheophytin a, lutein, and $\beta$-carotene), whereas primary and secondary metabolites were assessed by using widely targeted metabolomics. In addition, a random forest regression model was constructed by using spectral reflectance data and pigment compound contents. Results: Principal component analysis based on spectral reflectance data and the comparative profiling of 186 metabolites revealed characteristic metabolite accumulation associated with each green color pattern. The “green” group showed greater accumulation of sugars, the “gray green” group was characterized by the accumulation of phenolic compounds, and the “dark green” group exhibited accumulation of cyanidins. These metabolites are suggested to accumulate in response to environmental stress, and these differences are likely to influence green coloration traits. Furthermore, among the regression models for estimating pigment compound contents, the one for chlorophyll a content achieved high accuracy, with an $R^2$ value of 0.88 in the test dataset and 0.78 in Leave-One-Out Cross-Validation, demonstrating its potential for practical application in trait evaluation. However, since the regression model developed in this study is based on data obtained from greenhouse conditions, it is necessary to incorporate field trial results and reconstruct the model to enhance its adaptability. Conclusions: This study revealed that cyanidin is involved in the characteristics of dark green varieties. Additionally, it was demonstrated that chlorophyll a can be predicted using visible spectral reflectance. These findings suggest the potential for developing markers for the dark green trait, selecting high-pigment-accumulating varieties, and facilitating the simple real-time diagnosis of plant growth conditions and stress status, thereby enabling the establishment of optimal environmental conditions. Future studies will aim to elucidate the genetic factors regulating pigment accumulation, facilitating the breeding of dark green varieties with enhanced coloration traits for summer cultivation. Full article

This study addresses the challenge of the scalable, cost-effective synthesis of high-quality turbostratic graphene from low-cost carbon sources, including biomass waste such as sugarcane leaves, bagasse, corncobs, and palm bunches, using the Direct Current Long Pulse Joule Heating (DC-LPJH) technique. By optimizing the carbonization process and blending biomass-derived carbon with carbon black and turbostratic graphene, the gram-scale production of turbostratic graphene was achieved in just a few seconds. The synthesis process involved applying an 18 kJ electrical energy pulse for 1.5 s, resulting in temperatures of approximately 3000 K that facilitated the transformation of the carbon atoms into well-ordered turbostratic graphene. Structural and morphological characterization via Raman spectroscopy revealed low-intensity or absent D bands, with a high I_2D/I_G ratio (~0.8–1.2), indicating monolayer turbostratic graphene formation. X-ray photoelectron spectroscopy (XPS) identified sp²-hybridized carbon and oxygenated functional groups, while NEXAFS spectroscopy confirmed the presence of graphitic features and both sp² and sp³ bonding states. Energy consumption calculations for the DC-LPJH process demonstrated approximately 10 kJ per gram, demonstrating the potential for cost-effective production. This work presents an efficient approach for producing high-quality turbostratic graphene from low-cost carbon sources, with applications in enhancing the properties of composites, polymers, and building materials. Full article

X-ray free electron lasers (XFELs) are the new generation of particle accelerator-based light sources, capable of producing tunable, high-power X-ray pulses that are increasingly vital across various scientific disciplines. Recently, continuous-wave (CW) XFELs driven by superconducting linear accelerators have garnered significant attention due to their ability to enhance availability by supporting multiple undulator lines simultaneously. In this paper, we introduce a novel delay system comprising four triple-bend achromats (TBAs). This delay system was combined with fast kickers and can be employed to generate electron beams on a bunch-to-bunch basis in a CW-XFEL facility. Based on the parameters of the Shanghai High-Repetition-Rate XFEL and Extreme Light Facility, start-to-end simulations demonstrate that the TBA-based delay system achieves excellent electron beam qualities while providing a wide beam-energy-tuning range from 1.39 to 8 GeV. Full article

The European grapevine moth (Lobesia botrana), a significant pest in viticulture, impacts grape quality and yield through larval feeding and secondary infections. This study examined the impact of L. botrana on two grape varieties, Petit Verdot and Sangiovese, while also investigating cultivar-specific traits. Field trials were conducted in central Italy to assess infestation levels, female population abundance, and cultivar-specific morphological traits. The results revealed significantly lower larval infestation levels, but higher female abundance in Petit Verdot compared to Sangiovese. Bunch density and bunch compactness were also significantly lower in Petit Verdot than in Sangiovese. Morphological traits, such as a greater canopy thickness and higher leaf layer number in Petit Verdot, did not correspond to increased infestation levels, challenging existing findings regarding the impact of sun exposure on female oviposition and larval settlement. The seasonal dynamics of L. botrana indicated three major adult flight peaks and a partial fourth peak, potentially influenced by local weather patterns. These findings highlight the critical role of cultivar-specific traits in shaping pest infestation dynamics and provide essential insights for optimizing integrated pest management (IPM) strategies, particularly in cultivar selection and monitoring protocols for sustainable viticulture. Full article

This study addresses the challenges of detecting inferior fruits in table grapes in natural environments, focusing on subtle appearance differences, occlusions, and fruit overlaps. We propose an enhanced green grape fruit disease detection model named RF-YOLOv7. The model is trained on a dataset comprising images of small fruits, sunburn, excess grapes, fruit fractures, and poor-quality grape bunches. RF-YOLOv7 builds upon the YOLOv7 architecture by integrating four Contextual Transformer (CoT) modules to improve target-detection accuracy, employing the Wise-IoU (WIoU) loss function to enhance generalization and overall performance, and introducing the Bi-Former attention mechanism for dynamic query awareness sparsity. The experimental results demonstrate that RF-YOLOv7 achieves a detection accuracy of 83.5%, recall rate of 76.4%, mean average precision (mAP) of 80.1%, and detection speed of 58.8 ms. Compared to the original YOLOv7, RF-YOLOv7 exhibits a 3.5% increase in mAP, with only an 8.3 ms increase in detection time. This study lays a solid foundation for the development of automatic detection equipment for intelligent grape pruning. Full article

N-polar GaN HEMTs feature a natural back-barrier and enable the formation of low-resistance Ohmic contacts, with the potential to suppress short-channel effects and current collapse effects at sub-100 nm gate lengths, rendering them particularly promising for high-frequency communication applications. In this study, N-polar GaN films were grown on C-face SiC substrates with a 4° misorientation angle via MOCVD. By employing a two-step growth process involving LT-GaN or LT-AlGaN, the surface roughness of N-polar GaN films was reduced to varying degrees, accompanied by an improvement in crystalline quality. The growth processes, including surface morphology at each growth stage, such as the AlN nucleation layer, LT-GaN, LT-AlGaN, and the initial 90 nm HT-GaN, were investigated. The results revealed that a high V/III ratio and low-temperature growth conditions for the low-temperature layers, along with the introduction of a minor amount of Al, influenced adatom migration behavior and facilitated the suppression of step bunching. Suppressing step bunching during the initial growth stages was demonstrated to be critical for improving the surface quality and crystalline quality of N-polar GaN films. An N-polar GaN HEMT epitaxial structure was successfully achieved using the optimized surface morphology with a dedicated Fe-doped buffer process. Full article

Faced with the challenges posed by climate change, Serbian viticulture is looking for sustainable solutions for adaptable production. This study shows that grass is a multifunctional tool for overcoming the challenges of intensive viticulture while maintaining the quality of the grapes. In a three-year research experiment (2020–2022), the maintenance of an inter-row sward in a vineyard with four certified high-quality French Cabernet Sauvignon clones was investigated, and its effects on the ampelographic composition of the grapes and the quality of the grape juice (must) were studied as a function of wine quality. A grass sward was established between the rows as a biological soil management system and as a climate change adaptation measure in a high-intensity viticultural system. A grass–legume mixture was used as an inter-row cover crop, with nitrogen applied in two doses (50 and 100 kg ha⁻¹) in spring. The growth of the grasses responded to the nitrogen fertilisation, which was reflected in the biomass production, surface cover and nitrogen content in the biomass. At the end of the study, the biomass of the grass increased threefold when a high dose of nitrogen was applied compared to the non-fertilised grass. In contrast to the effects of nitrogen on the sward, N has no effect on the quantitative or qualitative parameters of the grapes. Clone 169 was separated for most grape mechanical parameters such as the bunch mass, all berries and the bunch stem; clone 15 showed the best grape juice quality parameters such as the sugar content and glycoacidometric index. The results show an option for climate change adaptation in viticulture that can mitigate the effects of rising temperatures, contribute to soil conservation and carbon storage in biomass and enable timely interventions in vineyards after heavy rainfall by creating accessible paths within the vineyards. The three-year effect of the different nutrient management of the sward in the inter-rows of Cabernet Sauvignon showed that the interaction between the two systems, sward and vine, is low and has no negative impact on the ampelographic and qualitative grape parameters. Full article

The bunching onion is an important leafy vegetable, prized for its distinctive flavor and color. It is consumed year-round in Japan, where a stable supply is essential. However, in recent years, the challenges posed by climate change and global warming have resulted in adverse effects on bunching onions, including stunted growth, discoloration, and the development of leaf tipburn, threatening both crop quality and yield. Furthermore, as bunching onion belongs to the Allium genus, which includes globally significant vegetables such as onion and garlic, studying the impact of climate change on bunching onion serves as an ideal model. The insights gained can also be applied to other crops and regions. This study investigates the effects of different summer growth conditions on the metabolite profile of heat-tolerant bunching onions with dark green leaf blade coloration and examines their association with leaf tipburn. Pigment compound quantification, functional component analysis, leaf tipburn rate assessment, and widely targeted metabolome profiling were performed across two commercial ${\mathrm{F}}_1$ varieties, one purebred variety, and six Yamaguchi Prefecture-bred ${\mathrm{F}}_1$ lines under different growing conditions. The results obtained were subjected to comparative analyses based on the varieties and groups classified by high and low leaf tipburn rates. The results revealed that $\beta$-carotene accumulation peaked with May sowing and July harvest, while the highest accumulation of other pigment compounds was observed with May sowing and September harvest. Additionally, metabolome analysis related to leaf tipburn rates identified several organosulfur compounds, with gamma-glutamyl-propenyl cysteine sulfoxide emerging as one of the key compounds. Based on the intensity data, the fold change of this metabolite was calculated to be 1.66, indicating an increase in the leaf tipburn group compared to the control group. In the control groups, organosulfur compounds appeared to undergo turnover in preparation for stress response. In contrast, in the leaf tipburn groups, it is hypothesized that organosulfur compounds were converted into precursors of pungency, resulting in inadequate responses to stress. This study aims to elucidate the mechanisms through which organosulfur compounds transition into pungent compounds and to develop varieties with improved resistance to leaf tipburn. Full article

The management of grapevine from diseases is now particularly focused on the development of environmentally friendly strategies. Although sulphur is not in itself a toxic substance, its extensive use in powdery mildew, in organic vineyards especially, may cause environmental problems and plant phytotoxicity and affect the health and safety of viticultural workers. The activity of sulphur applied at doses reduced up to 50% in tank mixtures with silicates or Equisetum arvense-based products was assessed on powdery mildew in grapevine. Two-year trials were carried out applying the products every 7–10 days in the period of greatest risk for disease infections, in two organic vineyards in the Abruzzo region, Italy. In both vineyards throughout all trial years, at harvest, disease incidence and severity on leaves and bunches in the silicon + sulphur treatments were generally significantly lower compared to both the sulphur at full dose and to the control. In all trials, in both vineyards, a strong activity of silicon + sulphur mixtures towards disease on leaves was observed. This effect could be decisive in lowering the potential inoculum in the following season. In the Ari vineyard, vines treated with the mixtures always increased yield quantity and quality, given the higher contents of soluble solids and lower levels of total acidity. In the Cellino vineyard, probably due to the young age of the vines, increases in yield quantity were observed, with lesser effects on quality. The promising activity of the mixtures needs further studies to confirm these positive results. Furthermore, in both vineyards, the source of primary inoculum of the pathogen was observed as chasmothecia on the leaves. Full article

Accurately predicting grapevine yield and quality is critical for optimising vineyard management and ensuring economic viability. Numerous studies have reported the complexity in modelling grapevine yield and quality due to variability in the canopy structure, challenges in incorporating soil and microclimatic factors, and management practices throughout the growing season. The use of multimodal data and machine learning (ML) algorithms could overcome these challenges. Our study aimed to assess the potential of multimodal data (hyperspectral vegetation indices (VIs), thermal indices, and canopy state variables) and ML algorithms to predict grapevine yield components and berry composition parameters. The study was conducted during the 2019/20 and 2020/21 grapevine growing seasons in two South Australian vineyards. Hyperspectral and thermal data of the canopy were collected at several growth stages. Simultaneously, grapevine canopy state variables, including the fractional intercepted photosynthetically active radiation (fiPAR), stem water potential (Ψ_stem), leaf chlorophyll content (LCC), and leaf gas exchange, were collected. Yield components were recorded at harvest. Berry composition parameters, such as total soluble solids (TSSs), titratable acidity (TA), pH, and the maturation index (IMAD), were measured at harvest. A total of 24 hyperspectral VIs and 3 thermal indices were derived from the proximal hyperspectral and thermal data. These data, together with the canopy state variable data, were then used as inputs for the modelling. Both linear and non-linear regression models, such as ridge (RR), Bayesian ridge (BRR), random forest (RF), gradient boosting (GB), K-Nearest Neighbour (KNN), and decision trees (DTs), were employed to model grape yield components and berry composition parameters. The results indicated that the GB model consistently outperformed the other models. The GB model had the best performance for the total number of clusters per vine (R² = 0.77; RMSE = 0.56), average cluster weight (R² = 0.93; RMSE = 0.00), average berry weight (R² = 0.95; RMSE = 0.00), cluster weight (R² = 0.95; RMSE = 0.13), and average berries per bunch (R² = 0.93; RMSE = 0.83). For the yield, the RF model performed the best (R² = 0.97; RMSE = 0.55). The GB model performed the best for the TSSs (R² = 0.83; RMSE = 0.34), pH (R² = 0.93; RMSE = 0.02), and IMAD (R² = 0.88; RMSE = 0.19). However, the RF model performed best for the TA (R² = 0.83; RMSE = 0.33). Our results also revealed the top 10 predictor variables for grapevine yield components and quality parameters, namely, the canopy temperature depression, LCC, fiPAR, normalised difference infrared index, Ψ_stem, stomatal conductance (g_s), net photosynthesis (P_n), modified triangular vegetation index, modified red-edge simple ratio, and ANT_gitelson index. These predictors significantly influence the grapevine growth, berry quality, and yield. The identification of these predictors of the grapevine yield and fruit composition can assist growers in improving vineyard management decisions and ultimately increase profitability. Full article