The safe and reliable operation of autonomous vehicles in complex and dynamic environments is heavily dependent upon exteroceptive and proprioceptive sensors. A LiDAR system generates accurate 3D point clouds, which are crucial for the detection, classification, and tracking of multiple targets. LiDAR data, however, presents significant challenges due to its density, noise, and varying sampling rates. In this study, various clustering and MTT techniques for LiDAR point clouds will be identified and classified within the context of autonomous driving to assess the state-of-the-art methods’ key challenges and their performances. We have categorized clustering and MTT methods used in AV applications, identified research gaps and challenges and analyzed existing algorithms and their challenges in detail. Researchers and practitioners in the field of autonomous driving will find this review to be a valuable resource.

Red fruits such as grapes and blueberries are known for their high content of bioactive compounds and antioxidants. In Mediterranean winemaking, traditional sun drying can be replaced by controlled airflow chamber drying which provides better quality, higher phenolic content, and increased antioxidants. This study aimed to increase the sugar content and phenolic compounds of the must by drying the fruits to 50% of their original moisture content. Two musts were prepared by combining fresh grapes and dried blueberries (M1), and the other using dried grapes and fresh blueberries (M2), followed by fermentation at 25 ºC with M05 Mead and X5 yeast strains. Must M2 showed the highest level of phenolic compounds, A520, total anthocyanins and antioxidant activity. During fermentation, the anthocyanin content increased mainly in the dried blueberry macerates, which raised between 4 to 5.5-fold. More bioactive compounds were extracted from wines produced by yeast inoculation despite shorter maceration times. Sensory analysis demonstrated consumer acceptance of the wines in terms of color, flavor and aroma. In conclusion, the use of red grapes in the production of blueberry red wine proved to be effective, providing sugars and higher must yields, while the dried fruits improved the fermentable sugar content and the levels of bioactive compounds, increasing the antioxidant capacity of the resulting red fruit wines.

Ampelography, the botanical discipline dedicated to the identification and classification of grapevine cultivars, was grounded on the description of morphological characters and more recently is based on the application of DNA polymorphisms. New methods of image analysis may help to optimize morphological approaches in ampelography. The objective of this study was the classification of representative cultivars of Vitis vinifera conserved in the Spanish collection of IMIDRA according to seed shape. Thirty eight cultivars representing the diversity of this collection were analyzed. A consensus seed silhouette was defined for each cultivar representing the geometric figure that better adjusted to their seed shape. All the cultivars tested were classified in ten morphological groups, each corresponding to a new model. The models are geometric figures defined by equations and similarity to each model is evaluated by quantification of percent of the area shared by the two figures, the seed and the model (J index). The comparison of seed images with geometric models is a rapid and convenient method to classify cultivars. A large proportion of the collection may be classified according to the new models described and the method permits to find new models according to seed shape in other cultivars.