Search Results (46)

A high intake of saturated fats and cholesterol from processed meats is associated with increased cardiovascular disease risk. This study aimed to develop a nutritionally enhanced Bologna-type sausage by partially replacing the beef content with a structured emulsion gel (EG) formulated from pine nut oil, inulin, carrageenan, and whey protein concentrate. The objective was to improve its lipid quality and functional performance while maintaining product integrity and consumer acceptability. Three sausage formulations were prepared: a control and two variants with 7% and 10% EG, which substituted for the beef content. The emulsion gel was characterized regarding its physical and thermal stability. Sausages were evaluated for their proximate composition, fatty acid profile, cholesterol content, pH, cooking yield, water-holding capacity, emulsion stability, instrumental texture, microstructure (via SEM), oxidative stability (TBARSs), and sensory attributes. Data were analyzed using a one-way and two-way ANOVA with Duncan’s test (p < 0.05). The EG’s inclusion significantly reduced the total and saturated fat and cholesterol, while increasing protein and unsaturated fatty acids. The 10% EG sample achieved a PUFA/SFA ratio of 1.00 and an over 80% reduction in atherogenic and thrombogenic indices. Functional improvements were observed in emulsion stability, cooking yield, and water retention. Textural and visual characteristics remained within acceptable sensory thresholds. SEM images showed more homogenous matrix structures in the EG samples. TBARS values increased slightly over 18 days of refrigeration but remained below rancidity thresholds. This period was considered a pilot-scale evaluation of oxidative trends. Sensory testing confirmed that product acceptability was not negatively affected. The partial substitution of beef content with pine nut oil-based emulsion gel offers a clean-label strategy to enhance the nutritional quality of Bologna-type sausages while preserving functional and sensory performance. This approach may support the development of health-conscious processed meat products aligned with consumer and regulatory demands. Full article

Pine nuts hold significant economic value due to their rich plant protein and healthy fats, yet precise variety classification has long been hindered by limitations of traditional techniques such as chemical analysis and machine vision. This study proposes a novel near-infrared (NIR) spectral feature selection algorithm, termed the improved binary equilibrium optimizer with selection probability (IBiEO-SP), which incorporates a dynamic probability adjustment mechanism to achieve efficient feature dimensionality reduction. Experimental validation on a dataset comprising seven pine nut varieties demonstrated that, compared to particle swarm optimization (PSO) and the genetic algorithm (GA), the IBiEO-SP algorithm improved average classification accuracy by 5.7% (p < 0.01, Student’s t-test) under four spectral preprocessing methods (MSC, SNV, SG1, and SG2). Remarkably, only 2–3 features were required to achieve optimal performance (MSC + random forest: 99.05% accuracy, 100% F1/precision; SNV + KNN: 97.14% accuracy, 100% F1/precision). Furthermore, a multimodal data synergy strategy integrating NIR spectroscopy with morphological features was proposed, and a classification model was constructed using a soft voting ensemble. The final classification accuracy reached 99.95%, representing a 2.9% improvement over single-spectral-mode analysis. The results indicate that the IBiEO-SP algorithm effectively balances feature discriminative power and model generalization needs, overcoming the contradiction between high-dimensional data redundancy and low-dimensional information loss. This work provides a high-precision, low-complexity solution for rapid quality detection of pine nuts, with broad implications for agricultural product inspection and food safety. Full article

Pine nut oil (PNO) is highly valued by consumers for its rich content of unsaturated fatty acids, which confer unique nutritional benefits. However, PNO is highly susceptible to lipid oxidation during storage and extraction. This chemical degradation compromises product quality and poses potential risks to food safety. To address this challenge, the food industry is developing antioxidant strategies, including optimizing pretreatment conditions to improve flavor and storage stability. Green extraction technologies such as microwave-assisted extraction (MAE) and ultrasonic-assisted extraction (UAE) have been introduced to enhance extraction efficiency and promote environmental sustainability. Light-proof packaging, reduced oxygen environments, and temperature control have also been employed to significantly extend the shelf life of PNO. Furthermore, to maintain the nutritional integrity and safety of PNO while expanding its functional applications in the food industry, several innovative approaches have been employed. These include the incorporation of natural antioxidants, the development of Pickering emulsions, the use of microencapsulation, and the formulation of oleogels. Full article

Bio-oil is a potential source for the production of alternative fuels and chemicals. In this work, Ni-V bimetallic zeolite catalysts were synthesized and evaluated in in situ catalytic hydrodeoxygenation (HDO) of pyrolysis volatiles of pine nut shell for upgraded bio-oil products. The pH and lower heating value (LHV) of the upgraded bio-oil products were improved by in situ catalytic HDO, while the moisture content and density of the oil decreased. The O/C ratio of the upgraded bio-oil products decreased significantly, and the oxygenated compounds in the pyrolysis volatiles were converted efficiently via deoxygenation over Ni-V zeolite catalysts. The highest HDO activity was obtained with NiV/MesoY, where the obtained bio-oil had the lowest O/C atomic ratio (0.27), a higher LHV (27.03 MJ/kg) and the highest selectivity (19.6%) towards target arenes. Owing to the more appropriate pore size distribution and better dispersion of metal active sites, NiV/MesoY enhanced the transformation of reacting intermediates, obtaining the dominant products of phenols and arenes. A higher HDO temperature improved the catalytic activity of pyrolysis volatiles to form more deoxygenated arenes. Higher Ni loading could generate more metal active sites, thus promoting the catalyst’s HDO activity for pyrolysis volatiles. This study contributes to the development of cost-efficient and eco-friendly HDO catalysts, which are required for producing high-quality biofuel products. Full article

Hyperspectral imaging (HSI) is an advanced imaging technique that captures detailed spectral information across multiple fields. This review explores its applications in counterfeit detection, remote sensing, agriculture, medical imaging, cancer detection, environmental monitoring, mining, mineralogy, and food processing, specifically highlighting significant achievements from the past five years, providing a timely update across several fields. It also presents a cross-disciplinary classification framework to systematically categorize applications in medical, agriculture, environment, and industry. In counterfeit detection, HSI identified fake currency with high accuracy in the 400–500 nm range and achieved a 99.03% F1-score for counterfeit alcohol detection. Remote sensing applications include hyperspectral satellites, which improve forest classification accuracy by 50%, and soil organic matter, with the prediction reaching R² = 0.6. In agriculture, the HSI-TransUNet model achieved 86.05% accuracy for crop classification, and disease detection reached 98.09% accuracy. Medical imaging benefits from HSI’s non-invasive diagnostics, distinguishing skin cancer with 87% sensitivity and 88% specificity. In cancer detection, colorectal cancer identification reached 86% sensitivity and 95% specificity. Environmental applications include PM2.5 pollution detection with 85.93% accuracy and marine plastic waste detection with 70–80% accuracy. In food processing, egg freshness prediction achieved R² = 91%, and pine nut classification reached 100% accuracy. Despite its advantages, HSI faces challenges like high costs and complex data processing. Advances in artificial intelligence and miniaturization are expected to improve accessibility and real-time applications. Future advancements are anticipated to concentrate on the integration of deep learning models for automated feature extraction and decision-making in hyperspectral imaging analysis. The development of lightweight, portable HSI devices will enable more on-site applications in agriculture, healthcare, and environmental monitoring. Moreover, real-time processing methods will enhance efficiency for field deployment. These improvements seek to enhance the accessibility, practicality, and efficacy of HSI in both industrial and clinical environments. Full article

An emulsion gel was developed to replace animal fats in meat products while preserving desirable sensory and structural attributes. The gel was prepared by emulsifying pine nut oil and sunflower oil with whey protein concentrate (WPC) and polysaccharides (inulin and carrageenan). Process parameters, including the inulin-to-water ratio, homogenization speed, and temperature, were optimized to achieve stable gels exhibiting high water- and fat-binding capacities. Scanning electron micrographs revealed a cohesive network containing uniformly dispersed lipid droplets, with carrageenan promoting a denser matrix. Chemical assessments demonstrated a notably lower saturated fatty acid content (10.85%) and only 0.179% trans-isomers, alongside an elevated proportion (71.17%) of polyunsaturated fatty acids. This fatty acid profile suggests potential cardiovascular health benefits compared with conventional animal fats. Texture analyses showed that carrageenan increased gel strength and hardness; Experiment 4 recorded values of 15.87 N and 279.62 N, respectively. Incorporation of WPC at moderate levels (3–4%) further enhanced the yield stress, reflecting a robust protein–polysaccharide network. These findings indicate that the developed emulsion gel offers a viable alternative to animal fats in meat products, combining superior nutritional attributes with acceptable textural properties. The substantial polyunsaturated fatty acid content and minimal trans-isomers, coupled with the gel’s mechanical stability, support the feasibility of creating reduced-fat, functional formulations that align with consumer demands for healthier alternatives. Full article

Background: Pinus pinea L. (stone pine) produces pine nuts of high value. Its cultivation is carried out in forests and plantations, with intensive management techniques being studied to stimulate diameter growth, which is positively related to cone production. Aims: To evaluate the effect of fertilization in a 30-year-old plantation and to understand if adult trees respond to nutritional management. Methods: A trial with completely randomized block design was established with two treatments (fertilization/control) and three repetitions. The plantation, with a density of 204 trees/ha, is located in central Chile, on a sandy-loam soil with neutral pH, medium organic matter content, and a fertility condition that limits tree development. Fertilization considered the repeated application of macro (N, P, K, S, Mg) and micronutrients (B, Fe, and Zn). Periodic measurements of height, stem and crown diameter, and cone production were made up to age 36. Cone production was evaluated using mixed generalized linear models and growth variables using ANOVA (analysis of variance). Results: Significant effects of fertilization on DBH annual growth (35% higher than the control, p < 0.001) and in cone production (3 times higher, p < 0.0001) were found. Conclusions: Fertilization is a useful practice to improve the growth and cone productivity of the species. Full article

The large-scale conversion of forests to agriculture has caused biodiversity loss, climate change, and disrupted dietary fatty acid balances, with adverse public health effects. Wild edibles like pine nuts, especially Pinus cembroides, provide sustainable solutions by supporting ecosystems and offering economic value. However, variability in seed quality limits market potential, and lipidomic studies on P. cembroides remain sparse. This paper underscores the ecological, social, and nutritional value of P. cembroides while advocating for advanced research to enhance its use as a non-timber forest resource in Mexico’s communal areas. It explores various analytical techniques, such as nuclear magnetic resonances (NMR), chromatography coupled with mass spectrometry (HPLC-MS, GC-MS) and GC coupled with flame ionization detector (GC-FID), highlighting extraction methods like derivatization, purification, and thin-layer chromatography. Likewise, some considerations are addressed for the treatment of data obtained in the detection of fatty acids from bioformatics and the evaluation of the data through statistical methods and artificial intelligence and deep learning. These approaches aim to improve fatty acid profiling and seed quality assessments, fostering the species economic viability and supporting sustainable livelihoods in rural communities, encouraging researchers across the country to explore the fatty acid composition of different P. cembroides populations can drive valuable insights into its nutritional and ecological significance. Such efforts can enhance understanding of regional variations, promote sustainable use, and elevate the specie’s economic and scientific value. Full article

We present a method for real-time terahertz imaging that employs a hydrogen cyanide (HCN) laser as a terahertz source at 0.89 THz and an AlGaN/GaN high-electron-mobility transistor (HEMT) terahertz detector as a camera. We developed an HCN laser and constructed a transmission imaging system based on it. This combination utilizes a high-power HCN laser with a highly sensitive terahertz detector, enabling practical applications of real-time terahertz imaging. A resolution test plane was produced to determine that the system could achieve a lateral resolution of 2 mm, and real-time terahertz imaging was carried out on Siemens star, pistachios, and sunflower seeds. The results demonstrate that the hidden structures inside nuts can be observed by terahertz imaging. Through our analysis of terahertz images of both sunflower seeds and pine nuts, we successfully assessed their fullness and demonstrated the capability to distinguish between full and unfilled nuts. These findings validate the potential of this technique for future applications in nut detection. We discuss the limitations of the current setup, potential improvements, and possible applications, and we outline the introduction of aspherical lenses and terahertz transmission tomography. Full article

One of the important distribution areas of stone pine (Pinus pinea L.), a native tree species of the Mediterranean Basin in Türkiye, is the Kozak Basin. Pine nut production plays an important role in the livelihood of the rural people of the Kozak Basin. However, in recent years, as a result of mining activities, climate change, and damage caused by the alien invasive species, the western conifer seed bug (Leptoglossus occidentalis Heidemann 1910 (Hemiptera; Coreidae), the decrease in cone and seed yield in the basin has reached significant dimensions. This process has caused the local people’s income sources to decrease. In this study, land use and land cover (LULC) changes and population changes in the Kozak Basin were discussed during the process, where changing forest land functions, especially economic effects, triggered vulnerable communities due to various factors such as climate change and insect damage. LULC classes of the Kozak Basin and their changes in three time periods are presented using the maximum likelihood method. In addition, the exponential population growth rates of the local people in three different time periods were calculated and these rates were interpolated in the spatial plane with a Kriging analysis. In conclusion, the responses of vulnerable communities to the cone and seed yield decline in the Kozak Basin are manifested by LULC changes and migration from the basin. Therefore, in the management of P. pinea areas, the creation of regulations within the framework of sustainability understanding regardless of ownership difference, stakeholder participatory approach management, close monitoring of ecological events occurring in the basin, awareness of vulnerable communities, and alternative livelihoods can be supported. Full article

Agroforestry practices evolve with the development of basic and advanced facilities, changes in natural and artificial factors of land, and land use trade-offs. This study aims to examine the farmers’ socioeconomic characteristics and perception of land use changes that define optimal agroforestry practices in Khost Province, Afghanistan. Data were collected from 662 farmers and analyzed using univariate Analysis of Variance (ANOVA) and Multivariate Analysis of Variance (MANOVA). The results found that forest and vegetable products, including fruits, berries, herbs, mushrooms, wild animals, oils, wood, honey, okra, eggplant, carrot, cucumber, pine nuts, pepper, and timber, have different impacts in terms of satisfaction with basic and advanced facilities, knowledge of land use changes, satisfaction with natural and artificial resources of land, and barriers to and economic benefits of land use. The limitations of this study included an absence of exogenous factors in the model such as climate change, financial conditions, market fluctuations, regulatory system, the area in which this study is selected, research design, and current condition of endogenous factors. Overall, this study defined a set of optimal agroforestry practices (expressed as crops and products) based on the farmers’ perception of land use changes in Khost Province, Afghanistan. This study provided useful insights for policymakers and development practitioners to promote agroforestry practice adoption and improve the socioeconomic development of agroforestry-dependent communities. Future works could explore the implications of agroforestry practices on the socioeconomic development of other dependent communities in Afghanistan. Full article

Due to its advantages such as speed and noninvasive nature, near-infrared spectroscopy (NIRS) technology has been widely used in detecting the nutritional content of nut food. This study aims to address the problem of offline quantitative analysis models producing unsatisfactory results for different batches of samples due to complex and unquantifiable factors such as storage conditions and origin differences of Korean pine nuts. Based on the offline model, an online learning model was proposed using recursive partial least squares (RPLS) regression with online multiplicative scatter correction (OMSC) preprocessing. This approach enables online updates of the original detection model using a small amount of sample data, thereby improving its generalization ability. The OMSC algorithm reduces the prediction error caused by the inability to perform effective scatter correction on the updated dataset. The uninformative variable elimination (UVE) algorithm appropriately increases the number of selected feature bands during the model updating process to expand the range of potentially relevant features. The final model is iteratively obtained by combining new sample feature data with RPLS. The results show that, after OMSC preprocessing, with the number of features increased to 100, the new online model’s $R^2$ value for the prediction set is 0.8945. The root mean square error of prediction (RMSEP) is 3.5964, significantly outperforming the offline model, which yields values of 0.4525 and 24.6543, respectively. This indicates that the online model has dynamic and sustainable characteristics that closely approximate practical detection, and it provides technical references and methodologies for the design and development of detection systems. It also offers an environmentally friendly tool for rapid on-site analysis for nut food regulatory agencies and production enterprises. Full article

Pinus pinea (stone pine), a Mediterranean species, is valued for its highly nutritious pine nuts and its ability to adapt to different environmental conditions. The species has been increasingly planted in Chile, where its main ecological requirements are met across a vast area. However, new plantations are established without considering social dimensions. Policymakers can regulate private decisions on tree planting through the appropriate design of economic incentives to foster social well-being. The objective of this work was to describe spatial patterns of potential areas for the cultivation of the exotic nut-bearing conifer P. pinea in central Chile and the possible correlation of those patterns with human development indices. Spatial data layers of the municipality development index (MDI), elevation, edaphoclimatic variables, and stone pine nut’s productive potential were overlapped at the municipality scale along 1225 km in central Chile. A spatial principal component analysis (sPCA) was used to integrate multiple dimensions, summarizing covariation structures, and identifying spatial patterns in the study area. Key results showed that spatial patterns of the potential productive index (PPI) were strongly regulated by the spatial pattern of climate and soil variables, whereas the spatial pattern of MDI showed a cryptic pattern and that the three dimensions of MDI—welfare, economy, and education—showed a different spatial movement, especially education and welfare. The results allow us to recommend that public policies boost municipality development through the promotion of P. pinea plantations and should target areas with a high productive potential and low MDI to generate socio-economic improvements. These findings are useful for the strategic spatial planning of the species cropping in Chile. Full article

Pinus pinea is an important Mediterranean species due to its adaptability and tolerance to aridity and its high-quality pine nuts. Different forest types located in Mediterranean native and non-native environments provide the opportunity to perform comparative studies on the species’ response to climate change. The aims of this study were to elucidate growth patterns of the species growing in native and exotic habitats and to analyze its response to climatic fluctuations, particularly drought, in both geographical contexts. Understanding stone pine (Pinus pinea) growth responses to climate variability in native and exotic habitats by comparing natural stands and plantations may provide useful information to plan adequate management under climate change. By doing so, we enhance the understanding of P. pinea’s adaptability and provide practical approaches to its sustainable management. In this study, we reconstructed and compared the stem radial growth of seven stone pine stands, two in southern Spain and five in central–southern Chile, growing under different climatic conditions. We quantified the relationships between growth variability and climate variables (total rainfall, mean temperature, and SPEI drought index). Growth was positively correlated with autumn rainfall in plantations and with autumn–winter rainfall in natural stands. Growth was also enhanced by high autumn-to-spring rainfall in the driest Chilean plantation, whereas in the wettest and coolest plantation, such correlation was found in winter and summer. A negative impact of summer temperature was found only in one of the five Chilean plantations and in a Spanish site. The correlation between SPEI and tree-ring width indices showed different patterns between and within countries. Overall, exotic plantations showed lower sensitivity to climate variability than native stands. Therefore, stone pine plantations may be useful to assist in mitigating climate change. Full article

Conjugated linoleic acid (CLA) is a class of bioactive fatty acids that exhibit various physiological activities such as anti-cancer, anti-atherosclerosis, and lipid-lowering. It is an essential fatty acid that cannot be synthesized by the human body and must be derived from dietary sources. The natural sources of CLA are limited, predominantly relying on chemical and enzymatic syntheses methods. Microbial biosynthesis represents an environmentally benign approach for CLA production. Pine nut oil, containing 40–60% linoleic acid, serves as a promising substrate for CLA enrichment. In the present study, we developed a novel method for the production of CLA from pine nut oil using Lactiplantibacillus plantarum (L. plantarum) Lp-01, which harbors a linoleic acid isomerase. The optimal fermentation parameters for CLA production were determined using a combination of single-factor and response surface methodologies: an inoculum size of 2%, a fermentation temperature of 36 °C, a fermentation time of 20 h, and a pine nut oil concentration of 11%. Under these optimized conditions, the resultant CLA yield was 33.47 μg/mL. Gas chromatography analysis revealed that the fermentation process yielded a mixture of c9, t11CLA and t10, c12 CLA isomers, representing 4.91% and 4.86% of the total fatty acid content, respectively. Full article