Road mortality is the leading source of biodiversity loss in the world, especially due to fragmentation of natural habitats and loss of wildlife. The survey of the main species victims of roadkill is of fundamental importance for the better understanding of the problem, being necessary, for this, the correct species identification. The aim of this study was to verify if DNA barcodes can be applied to identify road-killed samples that often cannot be determined morphologically. For this purpose, 222 vertebrate samples were collected in a stretch of the BR-101 highway that crosses two Discovery Coast Atlantic Forest Natural Reserves, the Sooretama Biological Reserve and the Vale Natural Reserve, in Espírito Santo, Brazil. The mitochondrial COI gene was amplified, sequenced and confronted with the BOLD database. It was possible to identify 62.16% of samples, totaling 62 different species, including Pyrrhura cruentata, Chaetomys subspinosus, Puma yagouaroundi and Leopardus wiedii considered Vulnerable in the National Official List of Species of Endangered Wildlife. The most commonly identified animals were a bat (Molossus molossus), an opossum (Didelphis aurita) and a frog (Trachycephalus mesophaeus) species. Only one reptile was identified using the technique, probably due to lack of reference sequences in BOLD. These data may contribute to a better understanding of the impact of roads on species biodiversity loss and to introduce the DNA barcode technique to road ecology scenarios.

Mealybugs are insects belonging to the family Pseudococcidae. This family includes many plant-pest species with similar morphologies, which may lead to errors in mealybug identification and delimitation. In the present study, we employed molecular-species-delimitation approaches based on distance (ASAP) and coalescence (GMYC and mPTP) methods to identify mealybugs collected from coffee and other plant hosts in the states of Espírito Santo, Bahia, Minas Gerais, and Pernambuco, Brazil. We obtained 171 new COI sequences, and 565 from the BOLD Systems database, representing 26 candidate species of Pseudococcidae. The MOTUs estimated were not congruent across different methods (ASAP-25; GMYC-30; mPTP-22). Misidentifications were revealed in the sequences from the BOLD Systems database involving Phenacoccus solani × Ph. solenopsis, Ph. tucumanus × Ph. baccharidis, and Planacoccus citri × Pl. minor species. Ten mealybug species were collected from coffee plants in Espírito Santo. Due to the incorrect labeling of the species sequences, the COI barcode library of the dataset from the database needs to be carefully analyzed to avoid the misidentification of species. The systematics and taxonomy of mealybugs may be improved by integrative taxonomy which may facilitate the integrated pest management of these pests.

Forensic entomology is the study of insects and other arthropods used in the solution of crimes. Most of entomological evidences strongly depend on accurate species identification. Therefore, new methods are being developed due to difficulties in morphological identification, including molecular methods such as High-Resolution Melting. In this study, we reported a new HRM primer set to identify forensically important Calliphoridae (blowflies) from Brazil. For such purpose, Calliphoridae species of forensic importance in Brazil were listed and confirmed by specialists. Mitochondrial COI sequences of those species were downloaded from databases and aligned, and polymorphic variations were selected for distinction between species. Based on it, HRM primers were designed. Forty-three fly samples representing six species were tested in the HRM assay. All samples had the COI gene sequenced to validate the result. Identifying and differentiating the six species proposed using a combination of two amplicons was possible. The protocol was effective even for old insect specimens, collected and preserved dried for more than ten years, unlike the DNA sequencing technique that failed for those samples. The HRM technique proved to be an alternative tool to DNA sequencing, with advantage of amplifying degraded samples and being fast and cheaper than the sequencing technique.

Hebanthe eriantha (Martius) Kuntze and Pfaffia glomerata (Spreng) Pedersen are medicinal plants popularly known as “Brazilian Ginseng” due to their similarity to Panax ginseng. In Brazil, they are sold as the same herb, despite their different pharmacological and toxicological properties. The morphological identification is difficult, which facilitates their adulteration. We report the application of the Barcode DNA High-Resolution Melting (Bar-HRM) using matK gene to differentiate both species in samples sold in the Brazilian market. Using the proposed method, we could discriminate and identify both species. Bar-HRM analysis allowed discriminating and identifying both species. It allowed the identification of H. eriantha and P. glomerata in 43.6% and 56.4% of the amplified samples, respectively. Of these, only seven samples were authenticated and, in 71.4% of the cases, adulterated. We concluded that Bar-HRM has proven to be a fast alternative method to authenticate plants under the common name “Brazilian Ginseng”.

Authentication of açaí products is increasingly important due to the risk of species substitution among morphologically similar Euterpe taxa, with implications for food quality, labeling accuracy, and consumer trust. Despite advances in molecular methods, rapid and cost-effective tools for discriminating closely related Euterpe species in processed commercial matrices remain limited. This study evaluated High-Resolution Melting (HRM) analysis targeting two complementary chloroplast markers — psbK-I and ycf1b — as a practical approach for species-level authentication of açaí (Euterpe oleracea and E. precatoria ) and juçara ( E. edulis ) products. In silico specificity analysis confirmed that the ycf1b primer pair shows amplification restricted to the Arecaceae family, supporting the analytical robustness of the method. The combined markers enabled reliable differentiation of all target species, including closely related taxa, with a detection limit of approximately 10% in admixed samples. When applied to 50 commercial products, HRM successfully authenticated 46 samples, substantially outperforming DNA sequencing, which was limited by amplification failure and mixed chromatograms. Mislabeling was detected in one açaí sorbet and three frozen açaí pulps marketed as açaí but molecularly identified as E. edulis , constituting a violation of Brazilian food labeling regulations. These findings demonstrate that HRM analysis provides a robust, rapid, and scalable strategy for routine species authentication in processed plant-based matrices, with potential for integration into food quality control workflows and large-scale commercial monitoring programs.