Search Results (467)

This study addresses the problem of agricultural waste utilization and nutrition for older adults by developing a food product based on a circular design approach. Pineapple core was used to produce a clean-label dietary powder without chemical or enzymatic treatment, relying on repeated rinsing and hot-air drying. The development process followed a structured analysis of physical, chemical, and sensory properties. The powder contained 83.46 g/100 g dietary fiber, 0° Brix sugar, pH 4.72, low water activity (aw < 0.45), and no detectable heavy metals or microbial contamination. Sensory evaluation by expert panelists confirmed that the product was acceptable in appearance, aroma, and texture, particularly for older adults. These results demonstrate the feasibility and safety of valorizing agri-waste into functional ingredients. The process was guided by the Transformative Circular Product Blueprint, which integrates clean-label processing, IoT-enabled solar drying, and decentralized production. This model supports traceability, low energy use, and adaptation at the community scale. This study contributes to sustainable food innovation and aligns with Sustainable Development Goals (SDGs) 3 (Good Health and Well-being), 9 (Industry, Innovation and Infrastructure), and 12 (Responsible Consumption and Production). Full article

The purpose of this paper is to evaluate the thermophysiological comfort of pineapple bio-based nonwoven material as a sustainable alternative to natural leather and synthetic polymer-coated materials by analyzing both the objective parameters of the material and subjective user feedback by wearing a skirt made from the same material. Considering the increasing demand for sustainable materials alternatives, the study aims to determine whether this material can offer acceptable comfort during wear. The research included two commercially available pineapple, bio-based, nonwoven materials that differed in their finishing. Sample S1 contained 5% Bio-PU and 5% conventional PU, and sample S2 contained 10% conventional PU. Objective parameters such as thermal resistance (R_ct), water vapor resistance (Ret) and air permeability were measured. For the subjective evaluation, ten female subjects wore the pineapple bio-based material skirts under controlled environmental conditions. Sample S1 showed lower R_ct values and slightly lower Ret combined with higher air permeability, which correlated with better subjective comfort evaluation. Although both samples showed high R_et values (S1 = 60.57 Pa²/W; S2 = 84.80 m²K/W) indicating limited vapor transfer, sample S1 was perceived as more comfortable, which was effected by better air permeability (S1 = 11.3 mm/s; S2 = 2.65 mm/s). Overall, S1 is more suitable for indoor use and for a shorter wear duration, while S2 may be better for cooler outdoor environments. Full article

To address the challenges of inadequate adaptability, insufficient power, high ground clearance, and limited functionality in existing pineapple field machinery, this study proposes a height-adjustable pineapple field management platform based on previously established cultivation patterns and agronomic requirements. The structural configuration and operational principles of the platform’s power chassis are elucidated, with specific emphasis on the development of the traction power system and modular operational systems. Theoretical and experimental analyses of steering parameters, stability, and field performance were conducted. Finite element simulation analysis of the frame revealed that under full-load conditions, the equivalent elastic strains during descent and ascent phases were 0.000317 and 0.00125, respectively. Maximum equivalent stresses (48.27 MPa and 231.6 MPa for descent and ascent, respectively) were localized at the beam–plate junctions, while peak deformations of 1.14 mm (descent) and 4.31 mm (ascent) occurred at mid-frame and posterior–mid regions, respectively. Field validation demonstrated operational velocities of 0.16–1.77 m/s (forward) and 0.11–0.28 m/s (reverse), with a maximum gradability of 20°. The platform exhibited multifunctional capabilities including weeding, spraying, fertilization, flower induction, harvesting, and transportation, demonstrating its potential to fulfill the operational requirements for pineapple field management. Simultaneously, the overall work efficiency is increased by more than 50%, compared to manual labor. Full article

This study developed sustainable biocomposites composed of polylactic acid (PLA) and surface-treated pineapple core powder (PACP), fabricated via extrusion and fused deposition modelling (FDM). PACP loadings of 1–3 vol% were combined after chemical modification with NaOH and silane to improve interfacial bonding. Particle morphology showed increased porosity and surface roughness following treatment. The melt flow index (MFI) increased from 31.56 to 35.59 g/10 min at 2 vol% PACP, showing improved flowability. Differential scanning calorimetry (DSC) showed the emergence of cold crystallization (T_cc ~121 °C) and an increase in crystallinity from 35.7% (neat PLA) to 47.3% (2 vol% PACP). Thermogravimetric analysis showed only slight decreases in T₅ and T_max, showing the thermal stability. The mechanical testing of extruded filaments showed increased modulus (1463 to 1518 MPa) but a decrease in tensile strength and elongation. For the 3D-printed samples, elongation at break increased slightly at 1–2 vol% PACP, likely because of the improvement in interlayer fusion. Though, at 3 vol% PACP, the mechanical properties declined, consistent with filler agglomeration observed in SEM. Overall, 2 vol% PACP offered the optimal balance between printability, crystallinity, and mechanical performance. These results reveal the possibility of PACP as a value-added biowaste filler for eco-friendly PLA composites suitable for extrusion and 3D printing applications. Full article

Induction in pineapples requires the targeted delivery of specific chemical solutions into the plant’s central core to enable batch management, a task currently reliant on manual operation. This study addressed this challenge by analyzing the physical characteristics of pineapple plants and establishing a perception-based mathematical model for core position localization. An integrated hardware–software system was developed, complemented by a human–machine interface for real-time operational monitoring. Comprehensive experiments were conducted to evaluate the spraying accuracy, nozzle response time, and prototype performance. The results demonstrate that the actuation system—comprising solenoid valves, pumps, and flowmeters—achieved an average spraying error of 2.72%. The average nozzle opening/closing time was 0.111 s; with a standard operating speed of 0.5 m/s, a delay compensation distance of 55.5 mm was implemented. In human–machine comparative trials, the automated system outperformed manual spraying in both efficiency and stability, with average errors of 7.1% and 6.4%, respectively. The system reduced chemical usage by over 67,500 mL per hectare while maintaining a miss-spray rate of 5–6%. Both two-tailed tests revealed extremely significant differences (p < 0.001). These findings confirm that the developed solution meets the operational requirements for pineapple floral induction, offering significant improvements in precision and resource efficiency. Full article

This study reports for the first time parameters and consumer preferences about juice prepared from North American pawpaw fruit (Asimina triloba). Enzymatic extraction using a commercial preparation of pectinases, hemicellulases, and beta-glucanases (Pectinex^® Ultra SP-L) significantly increased juice yield compared to non-enzyme extraction, but enzyme concentration (0.05% vs. 0.1%) and acidification method (citric vs. tartaric acid) showed no significant differences. Sensory panelists found no significant differences between citric and tartaric acid acidified juices, or between juices prepared from fresh pawpaw and pawpaw stored refrigerated for 14 days. Blending pawpaw juice with fruit juices improved overall acceptability compared to blending with fruit purees. Consumer testing revealed no overall preference among five juice formulations (100% pawpaw juice, sweetened pawpaw juice, pawpaw juice with the addition of 10% apple, orange, or pineapple juice). Consumers highlighted the complex flavor profile of pawpaw, with sweet and bitter tastes, and melon, papaya, and pear flavors being most frequently identified. Sweetening the juice altered the flavor profile, masking sourness and certain flavors. Based on this preliminary study, challenges and opportunities were identified for the development of a pawpaw-based juice. Full article

Pineapple (Ananas comosus) is an important crop worldwide, due to its nutritional properties. It is well known as a rich source of vitamins (A, C, and D) and various minerals that are vital in human diets. The aim of this review was to explore the economic viability of organic fertilizers that improve growth, yield, and quality during pineapple production in Africa. This study was conducted through a comprehensive analysis of the literature from peer-reviewed journals. It was reviewed that organic fertilization is a general agricultural approach that prioritizes environmental sustainability, biodiversity, and soil health through the avoidance of chemicals, including inorganic fertilizers. It was also found that organic fertilizers can effectively improve growth performance, yield, and the quality of the pineapple fruit to levels comparable to those of the fruit grown using inorganic fertilizers. Subsistence and smallholder farmers have adopted organic fertilization more than commercial farmers. Various challenges, including high certification costs, limited market access, high operating costs, inadequate farmer training, and limited knowledge on producing fruit using organic fertilizers, have been reviewed. The potential for higher market prices for organically produced fruit was noted, together with the challenges. Despite higher market prices and environmental benefits from organic fertilization, the economic viability of organic fertilizers for pineapple production is constrained by other factors, such as pest management difficulties, as the policies of conservation agriculture limit the use of chemical pesticides or the introduction of alien species as biocontrol agents. Full article

Agricultural byproducts, including pineapple peel (PP), are valuable feed additives which support the livestock industry. However, conflicting evidence exists regarding the optimal amount of PP required to achieve optimal fermentation in silage. This study examines the impact of ensiling mixtures of equal proportions of fresh Napier grass (NG) and sugarcane top (ST) with varying levels of PP (0% [C], 10% [P1], 20% [P2], and 30% [P3]) on fermentation quality, microbiological profiles, and in vitro ruminal digestion. Compared to the C silage, the dry matter, crude protein, and neutral detergent fiber contents decreased in the silage treated with increasing PP (p < 0.05). P1 exhibited lower (p > 0.05) pH, higher (p > 0.05) lactic acid content, and lower (p < 0.05) NH₃-N content than other silage. The Chao 1, ACE index, and relative abundance of Lacticaseibacillus and Lactobacillales were decreased following the order of C > P1 > P2 > P3 (p < 0.05). Although there were no significant differences observed in most vitro ruminal fermentation parameters among four silages (p > 0.05), P1 exhibited higher total gas production, total volatile fatty acid, acetate acid, acetate-to-propionate ratio, and lower pH than the other silages. These results demonstrated that a NG and ST mixture co-ensiling with appropriate PP enhances the NG and ST mixture silage quality, and the optimum addition ratio for PP was 10% on a fresh matter basis. Full article

The removal of pineapple eyes is a crucial step in pineapple processing. However, their irregularly distributed spiral arrangement presents a dual challenge for positioning accuracy and automated removal by the end-effector. In order to solve this problem, a pineapple eye removal device based on machine vision was designed. The device comprises a clamping mechanism, an eye removal end-effector, an XZ two-axis sliding table, a depth camera, and a control system. Taking the eye removal time and rotational angular velocity as variables, the relationship between the rod length of the prime mover and the contact force and gear torque during the eye removal process was simulated and analyzed using ADAMS (2020) software. Based on these simulations, the optimal length of the prime mover for the end-effector was determined to be 23.00 mm. The performance of various YOLOv5 models was compared in terms of accuracy, recall rate, mean detection error, and detection time. The YOLOv5s model was chosen for real-time pineapple eye detection, and the eye’s position was determined through coordinate transformation. The control system then actuated the XZ two-axis sliding table to position the eye removal end-effector for effective removal. The results indicated an average complete removal rate of 88.5%, an incomplete removal rate of 6.6%, a missed detection rate of 4.9%, and an average removal time of 156.7 s per pineapple. Compared with existing solutions, this study optimized the end-effector design for pineapple eye removal. Depth information was captured with a depth camera, and machine vision was combined with three-dimensional localization. These steps improved removal accuracy and increased production efficiency. Full article

Food quality detection by machine learning (ML) is more practical and sustainable as it does not require sample preparation and reagents. However, the prediction of pineapple quality by hyperspectral data applied to ML is not known. The aim of this study was to verify accurate ML models for predicting pineapple fruit quality and the best inputs for algorithms: Artificial Neural Networks (ANNs), M5P (model tree), REPTree decision trees, Random Forest (RF), Support Vector Machine (SMV) and Zero R. Three inputs were used for each model: leaf reflectance, peel reflectance, and fruit reflectance. The machine learning model SVM, stood out for its best results, demonstrating good generalization capacity and effectiveness in predicting these attributes, reaching accuracy values above 0.7 for Brix and ratio, using fruit reflectance. In terms of the overall efficiency of the input variables, peel and fruit were the most informative, with peel standing out for the estimation of secondary metabolism compounds, while the fruit showed excellent performance in predicting flavor-related attributes, such as acidity, °Brix and ratio, as mentioned previously, above 0.7. These results highlight the potential of using spectral data and machine learning in the non-destructive assessment of pineapple quality, enabling advances in monitoring and selecting fruits with better sensors. Full article

Focusing on the challenges of low utilization of pineapple leaves and the poor stability of phenolic compounds (PCs) in pineapple leaf fiber using traditional solvent extraction methods, the effects of different extraction media (including distilled water, neutral methanol, acidic methanol, alkaline methanol, neutral ethanol, and alkaline ethanol) was systematically investigated on the extraction efficiency of PCs from pineapple leaf fiber. Through response surface methodology (RSM), the optimal extraction conditions were determined. Additionally, the impacts of illumination and pH on the stability of PCs in pineapple leaf fiber were thoroughly examined. The results demonstrated that acidic ethanol outperformed other extraction media, with the optimized extraction conditions as follows: ethanol concentration = 80%, material-to-liquid ratio = 1:40, extraction temperature = 70 °C, and extraction time = 40 min. Under these conditions, the extraction yield of PCs reached 11.55 mg/g. Furthermore, the stability of PCs was significantly enhanced by minimizing light exposure and maintaining a pH range of 3–6. The potential application of PCs extracted from pineapple leaf fiber was also explored, particularly in mango preservation, revealing promising results. This study not only provides an efficient and sustainable approach for the extraction and stabilization of PCs from pineapple leaf fiber but also opens new avenues for the utilization of polyphenols in functional applications, contributing to the valorization of agricultural by-products. Full article

The aim of this study was to evaluate the effect of marinade type and marinating time on the physicochemical and sensory properties of pork tenderloin cooked using low-temperature, vacuum-sealed cooking. The study included marinades based on pineapple juice, red wine, kefir and a mixture of dried herbs. The assessment of the effect of marinades was based on the analysis of the color, texture, chemical composition and organoleptic properties of the meat after cooking using the sous vide method. In the experimental part, instrumental determinations of color and texture, analysis of the chemical composition and sensory assessment of the meat were carried out. Marinating for 12 h in red wine and dry marinating causes darkening of the meat. The hardness of meat marinated after 2 h increased compared to the control group; similar relationships were observed for gumminess and chewiness. However, after 12 h of marinating, the hardness of cycle 1 and hardness of cycle 2, as well as chewiness and gumminess, were significantly reduced below the level of the characteristics for the control group, except for the meat marinated in wine. Meat marinated in red wine and using the dry method received higher scores, while longer marinating resulted in more favorable scores. Full article

Parkinson’s disease (PD) associated with GBA1 mutations—recently termed Sidransky syndrome—differs from idiopathic PD (iPD) by earlier onset, more rapid progression, and higher rates of non-motor symptoms. Our objective was to assess whether GBA1 mutations contribute to olfactory dysfunction in PD and in asymptomatic carriers of the mutation. We compared olfactory and motor functions in 119 participants: Sidransky syndrome (n = 18), iPD (n = 30), GBA1 variant carriers without PD (n = 21), Gaucher disease patients (n = 20), and healthy controls (n = 30). All were evaluated with the Brief Smell Identification Test (BSIT^®) and the motor part of the Movement Disorders Society Unified PD Rating Scale (MDS-mUPDRS). Mean age was 59.2 ± 11.7 years. Mean disease duration was 2.5 ± 2.2 years in Sidransky syndrome and 5.4 ± 4.9 years in iPD. We found that both PD groups had significantly lower BSIT^® scores than non-PD groups (p < 0.001), particularly for leather, smoke, natural gas, pineapple, clove, rose, and lemon. Sidransky syndrome patients scored lower than iPD patients (p = 0.04). No significant olfactory deficits were observed in GBA1 carriers or Gaucher patients without PD. We conclude that hyposmia is more pronounced in Sidransky syndrome than in iPD. However, normal olfaction in non-parkinsonian GBA1 carriers suggests that GBA1 variants alone do not account for olfactory loss in PD. Hyposmia likely reflects broader PD pathology rather than a direct effect of the GBA1 mutation. Full article

Pineapple (Ananas comosus L.), cashew (Anacardium occidentale L.) and mango (Mangifera indica L.) are among the most cultivated plants in tropical and subtropical regions due to the high demand around the world. Following the harvesting and processing of pineapple, cashew and mango fruits, a huge amount of waste is generated, which is generally discarded into the environment, contributing to global pollution and water contamination. This study aims to propose alternative feeds for pigs by characterizing cashew, pineapple and mango fruit by-products through an in vitro two-step (gastro-intestinal and caecum) study to provide feeds not competing with humans and promoting eco-sustainable livestock. Ten by-products [i.e., pineapple peel and pomace; cashew nut testa, cashew (var. yellow) whole fruit and pomace; cashew (var. red) whole fruit and pomace; mango peel, kernel and testa] were sampled in Benin. The samples involved chemical analysis and an in vitro two-step digestion method (enzymatic + microbial digestibility). The results report a low dry matter (DM) content specifically in the pomace, peel and whole apple (13.0–27.2%), while higher lipids were observed for cashew nut testa and mango kernel (26.4 and 11.2% DM). The investigated by-products fall within the interval of referenced feeds for structural carbohydrates (NDF: 7.6–47.1% DM) and protein (6.21–51.2% DM), except mango by-products with a low content of protein (2.51–4.69% DM). The total dry matter digestibility, short-chain fatty acid and gas production were low for cashew by-products and stopped after 48 h of incubation. Pineapple pomace, cashew whole apple, pomace and testa can be considered as feedstuff in fattening pigs, presenting characteristics partly similar to beet pulp. Indeed, mango peel and kernel should be combined with a protein feed source to feed pigs. Presently, fruit by-products, such as those from cashew, pineapple and mango, are thrown into the environment, contributing to global warming and water pollution. These problems would be reduced by recycling these wastes in other fields, such as pig nutrition, creating a circular economy to provide feeds promoting eco-sustainable livestock. Indeed, in vivo studies are needed before proposing these by-products for pig diets. Full article

In the mechanical harvesting process, pineapple fruits are prone to damage. Traditional detection methods struggle to quantitatively assess pineapple damage and often operate at slow speeds. To address these challenges, this paper proposes a pineapple mechanical damage detection method based on machine vision, which segments the damaged region and calculates its area using multiple image processing algorithms. First, both color and depth images of the damaged pineapple are captured using a RealSense depth camera, and their pixel information is aligned. Subsequently, preprocessing techniques such as grayscale conversion, contrast enhancement, and Gaussian denoising are applied to the color images to generate grayscale images with prominent damage features. Next, an image segmentation method that combines thresholding, edge detection, and morphological processing is employed to process the images and output the damage contour images with smoother boundaries. After contour-filling and isolation of the smaller connected regions, a binary image of the damaged area is generated. Finally, a calibration object with a known surface area is used to derive both the depth values and pixel area. By integrating the depth information with the pixel area of the binary image, the damaged area of the pineapple is calculated. The damage detection system was implemented in MATLAB, and the experimental results showed that compared with the actual measured damaged area, the proposed method achieved an average error of 5.67% and an area calculation accuracy of 94.33%, even under the conditions of minimal skin color differences and low image resolution. Compared to traditional manual detection, this approach increases detection speed by over 30 times. Full article