Morphometric traits are closely linked to body condition, health, welfare, and productivity in livestock. In recent years, contactless 3D reconstruction technologies have been increasingly adopted to improve the accuracy and efficiency of morphometric evaluations. Conventional approaches for 3D reconstruction mainly employ Light Detection and Ranging (LiDAR) or photogrammetry. In contrast, emerging Artificial Intelligence (AI)-based methods, such as Neural Surface Reconstruction, 3D Gaussian Splatting, and Neural Radiance Fields, offer new opportunities for high-fidelity digital modeling. Smartphones’ affordability represents a cost-effective and portable platform for deploying these advanced tools, potentially supporting enhanced agricultural performance, accelerating sector digitalization, and thus reducing the urban–rural digital gap. This preliminary study assessed the viability of using smartphone-based LiDAR, photogrammetry, and AI models to obtain body measurements of Marchigiana cattle. Five morphometric traits manually collected on animals were compared with those extracted from smartphone-based 3D reconstructions. LiDAR measurements offer more consistent estimates, with relative error ranging from −1.55% to 4.28%, while photogrammetry demonstrated accuracy ranging from 0.75 to −14.56. AI-based models (NSR, 3DGS, NeRF) reported more variability between accuracy results, pointing to the need for further refinement. Overall, the results highlight the preliminary potential of portable 3D scanning technologies, particularly LiDAR-equipped smartphones, for non-invasive morphometric data collection in cattle.

The production of backyard chickens is an activity of great importance in the economy of rural families in Paraguay. The Rustipollos population was created through directed crosses between a commercial meat line and a local population belonging to non-specific breeds but phenotypically assimilated to Creole breeds. The aim of this study was to evaluate the genetic diversity, relationship, and structure of Rustipollos using 29 microsatellite markers. Analysis was performed on 50 Rustipollos animals and 926 other individuals as reference breeds/populations from Europe, Africa, South, and North America. A total of 318 alleles were detected, with a mean of 10.97 per locus. The polymorphic information content indicated that 80% of all loci were highly to moderately informative. Only two breeds/populations showed loci that did not deviate from the Hardy–Weinberg equilibrium. The results of genetic diversity indexes suggested moderate levels of genetic variability in Rustipollos population and low inbreeding level. The genetic differentiation index indicates a high genetic differentiation between populations. The results of the Neighbor-Net tree and STRUCTURE analyses indicate the existence of distinct gene pools, with some genetic relationships between Rustipollos, the commercial chicken strain, and south Spanish breeds. The Discriminant Analysis of Principal Components confirmed the observed genetic distances between breeds/populations. The results will be useful for sustainable use and official recognition of this population.