Search

This review aims to uncover the multifaceted landscape of methodologies employed by researchers for accurate fruit classification. The exploration encompasses an array of techniques and models, each tailored to address the nuanced challenges presented by fruit classification tasks. From convolutional neural networks (CNNs) to recurrent neural networks (RNNs), and transfer learning to ensemble methods, the spectrum of approaches underscores the innovative strategies harnessed to achieve precision in fruit categorization. A significant facet of this review lies in the analysis of the various datasets utilized by researchers for fruit classification. Different datasets present unique challenges and opportunities, thereby shaping the design and effectiveness of the models. From widely recognized datasets like Fruits-360 to specialized collections, the review navigates through a plethora of data sources, elucidating how these datasets contribute to the diversity of research endeavors. This insight not only highlights the variety in fruit types and attributes but also emphasizes the adaptability of deep learning techniques to accommodate these variations. By amalgamating findings from diverse articles, this study offers an enriched understanding of the evolving trends and advancements within the domain of fruit classification using deep learning. The synthesis of methodologies and dataset variations serves to inform future research pursuits, aiding in the refinement of accurate and robust fruit classification methods. As the field progresses, this review stands as a valuable compass, guiding researchers toward impactful contributions that enhance the accuracy and applicability of fruit classification models.

This work introduces a smart robotic arm for harvesting olive fruits. The work started by planning the main steps. After deciding on the robot concept design, a kinematic and dynamic analysis is conducted. Based on the results of the analysis, a simulation is performed to determine the required specifications of the main components. Based on these results, an experimental model of the robot arm is designed, built, configured, and tested, where the model yielded good results. The next step is to configure and test different types of end effectors. In order to make the harvesting process effective for olive trees, picking a single fruit each time is not practical. Therefore, the procedure adopted in this work focuses on picking a group of fruit in each stroke. The harvesting system consists of a robotic arm guided by a stereovision camera to enable 3-D vision. Once the fruits location is detected, a reverse kinematics algorithm is initiated, yielding 3-points coordinates. These coordinates are commanded to the manipulator to move to the location and performs the picking process. Further developments will include building a larger manipulator that can reach out to all parts of a regular tree.

The 25-hydroxyvitamin D 3 (25OHD 3 ) deficiency in Crohn's disease (CD) is associated with the immune system dysfunction and redox status alteration. These two events affect intestinal mucosal function through macrophages cells infiltration and to lead a pro-inflammatory cytokines storm and ROS (reactive oxygen species) overproduction. The objective of this study was to investigate the immunomodulatory and antioxidant effects of vitamin D 3 supplementation (DS 3 ) in clinical active phase. A cohort of 262 CD patients and vitamin D deficient (< 50 nmol/L or < 20 ng/mL) was randomized into 2 groups according to the DS 3 doses at 200,000 IU/month (D 200 group) versus 6,000 IU/day (D 6 group). Serum 25OHD 3 levels were assessed before and after 6 and 12 months of DS 3 . The clinical active phase was characterized by the CDAI score (Crohn's Disease Activity Index) and the fecal calprotectin assay. The 25OHD 3 profile was analyzed by LC-MS/MS. The pro-inflammatory cytokines (TNFα, IL-6, IL-12, IL-17, IL-23) were assessed by ELISA tests. The serum trace elements (Se, Mn, Cu, Zn) was determined by mass spectrometry. The antioxidant status (TAS, SOD, GPx, GSH) was evaluated by Randox kits. The results showed that the serum 25OHD 3 concentrations became normal (> 75 nmol/L or > 30 ng/mL) in the 2 groups. Our data showed that vitamin D supplementation allowed the clinical remission phase. The DS3 decreased serum levels of CRPus, TNFα, IL-17 and IL-23. The DS3 modulates the trace elements ratio and increased the SOD and GPx activities. The DS3 corrects the denutrition state. The vitamin D supplementation benefits are more significant in D 6 group (continuous 6,000 IU/day) than in D 200 group (intermittent 200,000 IU/month). Our study suggests that the serum 25OHD 3 profile can be considered a reliable biomarker in the bioclinic CD evolution to prevent the active phase, to extend the remission phase and to avoid the surgical bowel resection.