This paper provides a comprehensive review of SURF (speeded up robust features) feature descriptor, commonly used technique for image feature extraction. The SURF algorithm has obtained significant popularity because to its robustness, efficiency, and invariance to various image transformations. In this paper, an in-depth analysis of the underlying principles of SURF, its key components, and its use in computer vision tasks such as object recognition, image matching, and 3D reconstruction are proposed. Furthermore, we discuss recent advancements and variations of the SURF algorithm and compare it with other popular feature descriptors. Through this review, the aim is to provide a clear understanding of the SURF feature descriptor and its significance in the area of computer vision.

The objective of this study was to evaluate the growth of four lettuce cultivars in Southern Piauí to recommend the best ones for the region. The experiment was conducted in a greenhouse with randomized blocks, with evaluation in subdivided time plots, evaluated in six seasons (20, 24, 28, 32, 36, 40 days after sowing—DAS) and with treatments corresponding to four cultivars (Americana Rafaela^®, Grand Rapids TBR^®, Crespa Repolhuda^® and Repolhuda Todo ano^®) with five repetitions. Leaf area, number of leaves, collar diameter, aboveground fresh mass, aboveground dry mass, root dry mass and total and the physiological indices of growth analysis were evaluated. The lettuce cultivars interfered significantly in the studied parameters, being that Americana Rafaela^® and Repolhuda todo ano^®, in the conditions that they were submitted, presented better performances and bigger morphophysiological indexes, cultivated in pot. The cultivars Americana Rafaela^® and Repolhuda todo ano^® can be produced under the conditions of the south of Piauí.

Deficiencies in postharvest technology and the attack of phytopathogens cause horticultural products, such as tomatoes to have a very short shelf life. In addition to the economic damage, this can also have negative effects on health and the environment. The objective of this work is to evaluate an active coating of sodium alginate in combination with eugenol-loaded polymeric nanocapsules (AL-NP-EUG) to improve the shelf life of tomato. Using the nanoprecipitation technique, NPs with a size of 171 nm, a polydispersity index of 0.113 and a zeta potential of −2.47 mV were obtained. Using the HS-SPME technique with GC-FID, an encapsulation efficiency percentage of 31.85% was determined for EUG. The shelf-life study showed that the AL-NP-EUG-treated tomatoes maintained firmness longer than those without the coating. In addition, the pathogenicity test showed that tomatoes with AL-NP-EUG showed no signs of damage caused by the phytopathogen Colletotrichum gloesporoides. It was concluded that the formulation of EUG nanoencapsulated and incorporated into the edible coating presents high potential for its application as a natural nanoconservative of fruit and vegetable products such as tomato.

The wide distribution of the common beech (Fagus sylvatica) in Europe reveals its great adaptation to diverse conditions of temperature and humidity. This interesting aspect explains the context of the main objective of this work: to carry out a dendroclimatic analysis of the species Fagus sylvatica in the Polaciones valley (Cantabria), an area of transition with environmental conditions from a characteristic Atlantic type to more Mediterranean, at the southern limit of its growth. The methodology developed is based on the analysis of 25 local chronologies of growth rings sampled at different altitudes along the valley, generating a reference chronology for the study area. Subsequently, the patterns of growth and response to climatic variations are estimated through the response and correlation function, and the most significant monthly variables in the annual growth of the species are obtained. Finally, these are introduced into a Geographic Information System (GIS) where they are cartographically modeled in the altitudinal gradient through multivariate analysis, taking into account the different geographic and topographic variables that influence the zonal variability of the species response. The results of the analyses and cartographic models show which variables are most determinant in the annual growth of the species and the distribution of its climatic response according to the variables considered.

Climate and vegetation are variables of the physical space that have a dynamic and interdependent relationship. Flora modifies climatic elements and gives rise to a microclimate whose characterization is a function of regional climatic conditions and vegetation structure. The objective of this work was to compare the climatic variations (inside and outside) of the Caldén Forest in the Parque Luro Provincial Reserve. Temperature, relative humidity, wind speed, wind direction and precipitation data from two meteorological stations for 2012 were analyzed and statistically compared. The influence of the forest on climatic parameters was demonstrated and it was found that the greatest variations were in wind speed, daily temperature and precipitation.