Mechanical damage is a phenomenon that always occurred in the postharvest process. Due to the inappropriate harvest and postharvest process of Olive that lead to the bruise phenomenon, the quality of the extracted olive oil reduces. In this study, the effect of olive damage on bruising volume and quality characteristics was investigated. Three different varieties of Yellow, Oily, and Fishemi in three stages of unripe, semiripe, and ripped were used. Also, three kinds of the surface of rubber, nylon, and foam for the drop test were considered. The tests were performed in laboratory mode and simulated. For all tests, with increasing maturity, the amount of stress and internal energy were decreased and the bruise volume was increased. The amount of bruise volume and bruise susceptibility were obtained, and the experimental and simulated conditions were compared. On the other hand, the quality characteristics of olive oil including free fatty acid (FFA), peroxide value (PV), k232 and K270 coefficients, total chlorophyll, total carotenoid, total phenol, and total flavonoid were measured. The results showed that the finite element and chemometric methods are acceptable methods for predicting the generated energy of the fruit during impact, the amount of bruising volume, as well as evaluating the quality of the extracted oil.
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http://dx.doi.org/10.1002/fsn3.2508 | DOI Listing |
Toxins (Basel)
January 2025
Division of Dermatology, Department of Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand.
Introduction: Enlarged facial pores are a common cosmetic concern caused by excessive sebum production, visible hair shafts, and a reduction in skin elasticity, leading to a decrease in skin quality and overall appearance. Various treatment modalities have been explored to address this issue. This study focuses on the efficacy and safety of combining Onabotulinumtoxin A (OnaBoNT-A) and hyaluronic acid filler (HA filler) to target enlarged facial pores in Asians.
View Article and Find Full Text PDFJ Cardiothorac Surg
January 2025
Department of Thoracic Surgery, Baoding First Central Hospital, Baoding, 071000, China.
Objective: To assess the effectiveness and safety profiles of rivaroxaban compared to low molecular weight heparin (LMWH) in managing lower extremity deep vein thrombosis (DVT) subsequent to thoracoscopic lung cancer surgery.
Methods: Sixty patients diagnosed with lower extremity deep vein thrombosis (DVT) following thoracoscopic lung cancer surgery were randomly assigned to two groups: the experimental group comprising 30 patients treated with rivaroxaban, and the control group consisting of 30 patients treated with low molecular weight heparin (LMWH). The fundamental clinical characteristics of patients in both groups were documented, encompassing parameters, along with pre- and post-surgical lower limb vascular ultrasound findings.
Chest
January 2025
National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China. Electronic address:
A 34-year-old man who did not use tobacco complained of hemoptysis with a small volume, severe dry cough, and low-grade fever for 5 months. He denied dyspnea, chest pain, night sweats, or weight loss. Chest CT scanning showed nodules with a cavity in the lower left lung.
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1Department of Neurological Surgery and.
Sci Rep
December 2024
Department of Neurosurgery, The First Affiliated Hospital of Wannan Medical College (Yijishan Hospital of Wannan Medical College), Wuhu city, 241000, Anhui Province, China.
Traumatic brain injury (TBI) is a global issue and a major cause of patient mortality, and cerebral contusions (CCs) is a common primary TBI. The haemorrhagic progression of a contusion (HPC) poses a significant risk to patients' lives, and effectively predicting changes in haematoma volume is an urgent clinical challenge that needs to be addressed. As a branch of artificial intelligence, machine learning (ML) can proficiently handle a wide range of complex data and identify connections between data for tasks such as prediction and decision making.
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