Search Results (3,175)

This study investigated the influence of harvest timing on the quality of navel oranges by the use of hand-held near-infrared spectroscopy (NIRS) device. ‘Newhall’ navel oranges were harvested in seven batches from 200 to 249 days after full bloom (DAFB). The samples were stored under cold storage (5 °C) and at room temperature (25 °C), respectively. Harvest-stage SSC and weight loss during storage were analyzed, and SSC-related trends in stored fruit were further evaluated at the 49-day endpoint. The results indicated that cold storage helped reduce weight loss in navel oranges. SSC exhibited a trend of increasing first and then decreasing with harvest date, reaching a peak at DAFB of 228. The NIRS model corrected by external parameter orthogonalization (EPO) achieved the best prediction performance for SSC, with R²p = 0.60, RMSEP = 1.38%, and RPD = 1.58 under room temperature, and R²p = 0.49, RMSEP = 1.46%, and RPD = 1.40 under cold storage. The EPO method reduced temperature-related interference and improved the robustness of SSC prediction under different storage conditions. Separately, based on measured postharvest weight loss and SSC changes, navel oranges harvested at 214–228 DAFB showed relatively better storage behavior under 5 °C conditions, with an estimated storage duration of approximately 62 days. Early-harvested fruit exhibited stronger storability but lower flavor quality, whereas late-harvested fruit had better eating quality but shorter storage life. It should be noted that these results correspond to different optimization objectives, including storability-oriented and quality-balanced criteria. This study provides preliminary evidence for the potential application of handheld NIRS in navel orange quality monitoring during storage, and offers an exploratory framework rather than a decision-making system for investigating the relationship between harvest timing and storage conditions. However, its predictive performance is moderate and further validation is required before practical application in production or decision-making systems. Full article

Background: Performing and maintaining high-altitude cardiopulmonary resuscitation (CPR) could pose a significant physical challenge for rescuers. The objective of this study is to analyse the effects of reducing the oxygen fraction at altitudes of 3000 m and 5000 m above sea level (asl), with and without conditioning to hypoxia, on the quality of resuscitation performed in adults. Methods: An analytical before–after study in which 56 students with a Degree in Nursing between 18 and 30 years old perform 10 min of resuscitation on a mannequin at different altitudes (670, 3000 and 5000 m asl) will be carried out. Subsequently completing an intermittent hypoxia conditioning programme, the participants will perform the resuscitation manoeuvres at previously referenced altitudes. Sociodemographics, CPR quality, self-perception CPR, adequate anthropometric data, physical condition, blood tests, oxygenation in muscular tissue, biceps, brachii and erector spinae, subjective perception of effort, anxiety levels and quality of resuscitation will be measured in all participants at different altitudes. Discussion: Although CPR is a submaximal effort manoeuvre, it is subject to being performed by anyone without motor disabilities. Our study will also provide evidence as to whether this characteristic continues to hold true in a hostile environment such as medium and high altitudes. Our study aims to demonstrate that the improvement in physical performance and recovery capacity induced by intermittent hypoxia conditioning programmes increases the quality of CPR in prolonged cardiac arrests and in adverse conditions, such as at high altitudes. The proposed study will contribute as a novelty to the estimation of the influence of high altitudes and conditioning on performing basic CPR manoeuvres. If the hypothesis turns out to be true, recommendations about the practice of moderate-intensity physical exercise could be incorporated into the CPR guidelines as one of the important aspects in the training of rescuers to conduct CPR. Full article

Agriophyllum squarrosum (L.) Moq. is a desert-adapted pseudocereal that has recently attracted attention as a climate-resilient crop and source of valuable phytochemicals and nutritionally relevant metabolites. Despite their ecological and nutritional importance, comprehensive studies combining lipid and phenolic profiles across natural populations remain limited. In the present study, five populations of A. squarrosum from ecologically contrasting regions of Kazakhstan were analyzed to evaluate biochemical diversity and potential for functional food applications. Total lipid content was determined using near-infrared spectroscopy, fatty acid composition was assessed by GC-MS, and phenolic compounds were quantified by HPLC. Multivariate approaches, including PCA, MANOVA, PLS analysis, correlation networks, and TOPSIS ranking, were applied to evaluate population differentiation and relationships between biochemical traits and environmental conditions. Total lipid content in seeds ranged from 7.71% to 15.40%, linoleic acid represented 50.20–57.67% of total fatty acids, and oleic acid ranged from 24.80% to 40.10%. Isorhamnetin was the dominant phenolic compound in leaves, with concentrations between 0.24 and 0.65 mg/g. Populations from Aktobe showed higher lipid and oleic acid contents, whereas Almaty populations accumulated greater flavonoid levels, including isorhamnetin, quercetin, and kaempferol. These findings reveal substantial metabolic differentiation among populations and suggest possible associations with ecological conditions. The observed accumulation of unsaturated fatty acids and phenolic compounds, including isorhamnetin, quercetin, and kaempferol, identifies promising germplasm resources for future studies on functional food development and biological activity evaluation. The results further support the potential utilization of A. squarrosum in sustainable agriculture in arid regions. Full article

Moyamoya disease is a progressive steno-occlusive cerebrovascular disorder in which cerebral perfusion may become highly dependent on systemic arterial pressure, arterial carbon dioxide tension, and collateral flow. Encephaloduroarteriosynangiosis (EDAS) is an indirect revascularization procedure that promotes neovascularization over weeks to months but does not immediately augment cerebral blood flow intraoperatively. Anesthetic management therefore requires preservation of cerebral oxygen delivery during a period of persistent physiologic vulnerability. This narrative review presents a practical perioperative framework for EDAS anesthesia, emphasizing maintenance of mean arterial pressure near baseline or modestly above baseline, avoidance of hypotension and hypovolemia, normoxia, normothermia, and careful regulation of carbon dioxide. Hyperventilation should be avoided because hypocapnia can reduce cerebral blood flow through vasoconstriction, while excessive hypercapnia may contribute to regional maldistribution or steal physiology. Raw electroencephalography may provide cortical ischemia surveillance where available, whereas somatosensory evoked potentials, motor evoked potentials, near-infrared spectroscopy, and transcranial Doppler should be considered adjunctive and institution-dependent. A structured algorithm that integrates hemodynamics, ventilation, oxygen delivery, anesthetic depth, neuromonitoring, and surgical communication may support the timely recognition and correction of intraoperative hypoperfusion. Full article

Stevia (Stevia rebaudiana Bertoni) is an important source of natural sweeteners. Since its commercial value depends on steviol glycosides, quality assessment primarily involves quantifying these compounds in leaves and shoots. While chromatography is the standard analytical method, it is labor-intensive and time-consuming; it involves multiple processing steps that may cumulatively introduce errors and remains relatively expensive. Although chromatography remains the most accurate method, this exploratory study evaluates the potential of using spectroscopy as an auxiliary method for the approximate assessment of steviol glycoside content. Leaf reflectance spectroscopy could be a simpler and more cost-effective approach. However, relationships between leaf reflectance and steviol glycoside content are indirect and mediated by physiological processes. To account for these indirect dependencies, cumulative UVB exposure was included as an additional feature because it influences both leaf optical properties and plant metabolic processes. A low-cost spectrometer was utilized as the measuring instrument. The study was conducted over a period of three months on 77 S. rebaudiana clones, divided into four groups based on their level of UVB irradiance (control without irradiation, 400, 600, and 800 μW m⁻²). Based on the collected data, linear and polynomial regression, Random Forest, XGBoost, PLSR, and ElasticNetCV models were trained. Cumulative UVB exposure was found to be the most important feature. Of the spectral features, the most informative for assessing the content of steviol glycosides were spectral indicators in the far-red and near-infrared (NIR) ranges. Our results indicate a detectable relationship, with Random Forest being the best-performing model and achieving a moderate predictive performance (R² = 0.66). Despite their limited predictive performance, the models demonstrate that leaf reflectance spectra combined with cumulative UVB exposure contain information related to steviol glycoside content. These findings support further investigation of remote sensing approaches for crop quality assessment. Full article

Changes in wood moisture content significantly affect its dimensions, mechanical properties, and vibrational characteristics. Thermal treatment is one of the most convenient approaches for improving the moisture resistance of wood; however, the effects of treatment conditions on moisture content and vibrational characteristics after short-term cyclic moisture absorption have not been clearly investigated. In this study, dry thermal treatment at 160–220 °C for three different durations was applied to Japanese cedar specimens. Higher thermal treatment temperatures and longer treatment times decreased the equilibrium moisture content (EMC). The fundamental resonant frequency of the free–free flexural vibration (f₁) increased with increasing treatment temperature, whereas it decreased over a longer duration. All specimens were subjected to three cycles of moisture change tests from 60%RH to 98%RH at 40 °C to track the change in moisture content, f₁ and its loss tangent (tanδ). The specimens treated at higher temperatures maintained a lower moisture content and higher f₁. Under most treatment conditions, the moisture content at 98%RH increased from the first to the second cycle and remained constant in the third cycle. On the other hand, the resonant frequency at 98%RH remained unchanged from the first to the second cycle but increased in the third cycle. This indicates that the moisture surface became saturated in the second cycle, and moisture diffusion from the surface to the inside of the specimen increased with the number of cycles. Near-infrared absorption revealed that high-temperature treatment caused thermal decomposition of hemicellulose and an increase in apparent crystallinity due to a reduction in the amorphous region of cellulose. These changes enhance the hydrophobicity of the cell wall, contributing to moisture resistance and vibrational stability. Full article

Introduction: Aquatic chemical pollution is among the most worrying threats to ecosystem health. There is an ever-increasing variety of pollutant substances detected across the source-to-sea continuum, causing loss of biodiversity and ecological disequilibrium. Achieving cleaner and healthier systems relies on carrying out sustained, cost-effective, diagnosis and aquatic effects monitoring, within the adaptive management cycle. The available methods are, however, cumbersome, which creates a clear need for innovative expeditious approaches for low-cost surveillance monitoring. In the last decade, Raman Spectroscopy (RS) has gained wide recognition for application to biological questions, for its ability to uncover the complexity of molecules and their interactions. Various fields, from pharmacology to disease diagnosis and prognosis, have suffered an innovation revolution through the application of RS. In this technique inelastic light scattering of a small part of photons of an incident electromagnetic monochromatic light beam (ranging from near-infrared to visible or ultraviolet) is caused by the molecular vibration of chemical bonds. This results in shifts in energy, which indicate discrete vibrational modes of polarisable molecules, providing qualitative and quantitative assessments of the chemical composition and molecular structure of the sample. The technique shows high sensitivity, no need for sample preparation and the possibility of use in non-invasive and label-free analysis. Objective: The aim of this work is to present and discuss evidence about the application of Raman Spectroscopy (RS) to environmental diagnosis and aquatic effect monitoring of pollution. Methodology: The technique was applied to different biological models, i.e., diatoms, zebrafish embryos and larvae and freshwater snails. Quality assessments with diatoms were tested in environmental monitoring, while assessments with other models were done upon exposure to metals and organic contaminants. Results and conclusions: The Raman spectra obtained from the samples analysed comprised bands detected within the 800 to 2000 cm⁻¹ wavenumber range. These were related to bond vibrations of carbohydrates, DNA phosphate groups, proteins or CH, NH and OH stretching in lipids and proteins. Data analysis using chemometric methods clearly distinguished pollutant exposure from control sites or treatments, pointing out the potential for surveyance monitoring. The next steps include the comparison with other sensitive methods (e.g., locomotion and avoidance behaviours, omics methods) to assess efficiency and bring further mechanistic understanding. Full article

The development of new technologies enabling rapid, frequent, and reagent-free monitoring of kidney function is recognized as being of paramount importance. In this work, mid-(MIR) and near-infrared (NIR) spectroscopy were compared for the prediction of key renal biomarkers—creatinine, urea and albumin—using 54 serum solutions mimicking the biochemical profiles of five stages of chronic kidney disease (CKD). MIR spectra were acquired in a high-throughput microplate platform after a simple dehydration step, while the NIR spectra were obtained directly from liquid serum using a fiber optic probe. After evaluating several spectral pre-processing methods and targeted spectral regions, excellent regression models (R² > 0.9 for the best models) were obtained for the three biomarkers. MIR provided highly accurate urea predictions, whereas optimized NIR sub-regions enabled excellent estimation of creatinine and albumin. Both MIR and NIR, associated with supervised classification methods, enabled us to successfully distinguish healthy from diseased profiles and to identify the diseases state with AUC > 0.93. These findings highlight the complementary value of MIR and NIR spectroscopy for kidney disease assessment and their potential integration into point-of-care diagnostic systems. Full article

Accurate apple origin identification and non-destructive internal quality evaluation are important for fruit traceability, quality grading, and post-harvest management. Unlike previous studies mainly focusing on origin classification, this study established a dual-task near-infrared spectroscopy framework integrating geographical origin classification and soluble solid content (SSC, °Brix) prediction for Fuji apples. Samples were collected from three representative production regions in China: Alar in Xinjiang, Yantai in Shandong, and Luochuan in Shaanxi. Near-infrared diffuse reflectance spectra were acquired from 375 apples, generating 3000 spectral samples for origin classification and 750 SSC-calibrated samples for sugar content prediction. For classification, six deep learning models were evaluated using standardized full-spectrum input without chemometric spectral preprocessing, and the Transformer achieved the best performance, with a test accuracy of 96.22%. For SSC regression, spectra were preprocessed using standard normal variate and Savitzky–Golay filtering. The DNN model achieved the best prediction performance, with MAE = 0.5958 °Brix, RMSE = 0.7333 °Brix, R² = 0.8646, and Pearson r = 0.9338. These results indicate that near-infrared spectroscopy combined with deep learning can support both Fuji apple origin authentication and non-destructive local tissue SSC assessment. Full article

Optimizing harvest time and oil production requires accurate olive fruit quality characterization. Traditional chemical methods are costly and tedious, leading to poor monitoring resolution and reliance on subjective visual assessments. While spectroscopy offers a non-destructive alternative, standard equipment remains complex and prohibitively expensive for smallholder farmers. To address this, we propose a methodology using a custom-made, low-cost multispectral device. Built upon the AS7265x board, the system acquires 18 spectral bands in the visible and near-infrared range (410–940 nm). We used these spectral data to feed artificial neural network (ANN) models for estimating the quality of intact olives. During a two-season field experiment, we monitored ripening to acquire spectral signatures and ground-truth values for oil content per fresh weight (OCFW), oil content per dry matter (OCDM), moisture (M), and titratable acidity (TA). External validation showed high accuracy for OCFW (R²p = 0.86), OCDM (R²p = 0.86), and M (R²p = 0.89), proving the system’s reliability. However, TA estimation showed lower performance (R²p = 0.21), indicating limited spectral correlation. These findings pave the way for affordable, real-time smart farming tools for olive quality monitoring. Full article

To address the inherent limitations of the Dhole Optimization Algorithm (DOA)—limited exploration range, insufficient population diversity, and slow convergence—this paper proposes a Modified Dhole Optimization Algorithm (MDOA) integrating a Beta distribution-based opposition learning strategy, a DE/rand-to-best/1 differential mutation mechanism, and nonlinear parameter control. MDOA is evaluated on 41 CEC2017 and CEC2022 benchmark functions, outperforming 11 state-of-the-art algorithms in convergence speed, accuracy, and robustness. It is then applied to five engineering optimization problems: compression spring design, speed reducer weight minimization, rolling bearing optimization, tubular column design, and moisture content prediction of Dendrobium huoshanense using near-infrared spectroscopy with a BP neural network. The MDOA-BP model reduces MAE, RMSE, MSE, and MAPE by 27.5%, 27.8%, 47.6%, and 31.0%, respectively, while increasing $R^2$ from 0.8339 to 0.9130, achieving the best results among all comparison models. These results demonstrate that MDOA is a highly effective and robust optimizer for complex constrained engineering and high-dimensional optimization tasks. Full article

Background/Objectives: Brain dysfunction and symptoms can be improved with a sensory trick (ST) in more than 80% of patients with cervical dystonia (CD). This study aimed to investigate the functional connectivity (FC) of CD patients with different types of STs using functional near-infrared spectroscopy (fNIRS) and to explore the underlying neural mechanisms of STs. Methods: In this study, 35 CD patients (including 15 with classic STs, 15 with forcible STs, 5 with non-STs) and 29 healthy controls (HCs) underwent resting-state fNIRS. We subsequently analyzed FC differences between the groups and their correlations with clinical characteristics. Results: The grand-average FC was significantly higher in the non-ST group than in the forcible ST group. Furthermore, compared to the ST group, the non-ST group exhibited significantly increased FC, primarily involving the prefrontal and sensorimotor networks. In the forcible ST group, this hypoconnectivity was negatively correlated with disease severity scores. Conclusions: This study supports the concept of CD as a networkopathy, suggesting that both the severity and topology of cortical coherence impairment are modulated by the ST phenotype. Full article

Background: Near-infrared spectroscopy (NIRS)-based wearable devices offer non-invasive, continuous monitoring of muscle oxygenation, providing direct microvascular and metabolic information that complements indirect indices of intensity such as heart rate and accelerometry. Their clinical applicability in chronic non-communicable diseases (NCDs) remains under active development. Methods: A structured narrative review was conducted in PubMed, Scopus, Web of Science, and IEEE Xplore (January 2010–January 2026) using pre-specified search strings combining NIRS, muscle oxygenation, SmO₂, StO₂, wearable, exercise intensity, ventilatory/lactate threshold, and individual chronic disease terms. Eligible studies addressed technical validation of wearable NIRS, NIRS-derived exercise intensity estimation, clinical applications in NCDs, or rehabilitation implementation. Evidence was synthesized thematically; quality of validation studies was appraised against AMSTAR-2-informed, COSMIN-informed, or Cochrane RoB-2 criteria. Results: Wearable continuous-wave NIRS shows acceptable concurrent validity with frequency-domain laboratory systems (r = 0.79; range 0.69–0.88; ±8% SmO₂ agreement in 95% of measurements) and good test–retest reliability for moderate-to-severe domains (ICC 0.72–0.91). NIRS-derived breakpoints align more reliably with the second ventilatory/lactate threshold (ICC = 0.80) than with the first (ICC = 0.53), constraining its use for prescribing lower-intensity domains. In chronic obstructive pulmonary disease, peripheral arterial disease, chronic respiratory failure and selected cardiovascular conditions, wearable NIRS detects disease-specific patterns of muscle deoxygenation and post-exercise reoxygenation that track responses to rehabilitation. Conclusions: Current evidence supports wearable NIRS as a complementary, intensity-aware monitoring tool—particularly for delineating the heavy/severe-intensity boundary and detecting peripheral metabolic limitations—rather than as a stand-alone replacement for ventilatory or lactate thresholds. Because much of the evidence derives from small, single-sex or athlete-only cohorts, these findings should be regarded as a promising basis requiring further validation in broader NCD populations. Implementation in NCDs requires standardized placement and calibration protocols, sex- and body composition-stratified reference values, motion-artifact mitigation, and adequately powered longitudinal trials in clinical populations. Full article

Objective: The objectives of this study were to characterise induction-phase regional cerebral oxygen saturation (rSO₂)–mean arterial pressure (MAP) dynamics during near-infrared spectroscopy (NIRS)-guided selective carotid endarterectomy (CEA) and to examine whether the Awake→Intubated pressure–oxygenation pattern may represent an early adjunctive physiological signal of subsequent cross-clamp-related ipsilateral cerebral desaturation. Methods: In this retrospective observational cohort study, 322 consecutive elective CEAs managed with an NIRS-guided selective shunting protocol between October 2019 and February 2025 were analysed, after excluding patients considered for routine pre-emptive shunting because of contralateral internal carotid artery occlusion or ≥70% stenosis. Standardised MAP and bilateral rSO₂ values were extracted at the Awake, Intubated, and Clamp stages, defined as 3 min after carotid cross-clamping. Awake→Intubated ipsilateral ΔrSO₂/ΔMAP was evaluated as a continuous, exploratory pressure–oxygenation index, with MAP–rSO₂ directional change classified as concordant or discordant. Clamp-related desaturation was defined as a ≥20% ipsilateral rSO₂ decrease from Awake to Clamp. Discrimination and adjusted associations were evaluated using receiver operating characteristic analysis and multivariable logistic regression, respectively. Results: Clamp-related ≥20% ipsilateral rSO₂ desaturation occurred in 43 patients (13.4%). The Awake→Intubated ipsilateral ΔrSO₂/ΔMAP ratio differed significantly between patients with and without ≥20% desaturation and showed significant discrimination on receiver operating characteristic analysis, with an area under the curve (AUC) of 0.799 (95% confidence interval [CI] 0.723–0.876; p < 0.001). Concordant pressure–oxygenation change was more frequent among patients with ≥20% desaturation (31/43, 72.1%), whereas discordant change predominated among those without desaturation (228/279, 81.7%; p < 0.001). In multivariable analysis, Awake→Intubated ipsilateral ΔrSO₂/ΔMAP remained associated with clamp-related ≥20% desaturation after adjustment (adjusted odds ratio [OR] 1.63, 95% CI 1.15–2.33; p = 0.006), along with symptomatic presentation and 50–69% contralateral stenosis. Postoperative stroke occurred in 4/322 patients (1.2%), and no 30-day mortality occurred. Conclusions: During NIRS-guided selective CEA, induction-phase rSO₂–MAP dynamics were associated with subsequent cross-clamp-related ipsilateral cerebral desaturation. As the outcome was a NIRS-defined desaturation rather than an independent clinical, neurological, or imaging endpoint, these findings indicate association with a surrogate marker rather than prediction of clinically relevant cerebral ischaemia. The Awake→Intubated ΔrSO₂/ΔMAP ratio and directional pressure–oxygenation pattern may represent early adjunctive physiological signals associated with clamp-related desaturation. These findings are hypothesis-generating and require prospective validation with systematic multimodal monitoring. Full article

A comprehensive multiregional characterization of the spectral response of cassava leaves across different ontogenetic stages was performed. For this, ultraviolet (UV), visible (VIS) and shortwave near-infrared (UV-VIS-NIR; 200–900 nm) regions were used to identify spectral signatures and indices for their potential use as biomarkers of leaf development and physiological status of plants under induced senescence conditions. Manihot esculenta Crantz (HMC-1 variety) was used as a model. Spectral signatures were obtained from leaves at two phenological stages (4 and 6 months after planting) using UV-VIS-NIR spectroscopy by the diffuse reflectance technique. Classical and experimental spectral indices were evaluated, and their discriminatory power through different ontogenies was assessed using ANOVA/Kruskal–Wallis and post hoc tests. Senescence effects were further examined by postharvest monitoring (1–20 days), with temporal, ontogenetic, and interaction effects validated using linear mixed models (LMMs), while multivariate structure and spectral convergence were explored via principal component analysis and hierarchical clustering (PCA-HCA). Functionally Enhanced Derivative Spectroscopy (FEDS), comparative analysis, and spectral correlation mapping allowed signal’s selective enhancement and the identification of phenolic compounds, photosynthetic pigments, and structural molecular components. Results showed high ontogenetic stability of UV-associated phenolic signals (~210–220 nm), whereas the VIS region (420–600 nm) clearly differentiated young leaves. The NIR region was stable across ontogeny but highly sensitive to temporal degradation, reflecting changes in water status and internal structure. UV-VIS-NIR indices effectively differentiated young leaves and changes by stress. It is concluded that multiregional characterization of the spectral response supported by FEDS allows the extraction of robust indices with strong potential as biomarkers of leaf maturation and senescence in cassava. Full article