Acquiring phenotypic data from livestock constitutes a crucial yet cumbersome phase in the breeding process. Traditionally, obtaining livestock phenotypic data primarily involves manual, on-body measurement methods. This approach not only requires extensive labor but also induces stress on animals, which leads to potential economic losses. Presently, the integration of next-generation Artificial Intelligence (AI), visual processing, intelligent sensing, multimodal fusion processing, and robotic technology is increasingly prevalent in livestock farming. The advantages of these technologies lie in their rapidity and efficiency, coupled with their capability to acquire livestock data in a non-contact manner. Based on this, we provide a comprehensive summary and analysis of the primary advanced technologies employed in the non-contact acquisition of livestock phenotypic data. This review focuses on visual and AI-related techniques, including 3D reconstruction technology, body dimension acquisition techniques, and live animal weight estimation. We introduce the development of livestock 3D reconstruction technology and compare the methods of obtaining 3D point cloud data of livestock through RGB cameras, laser scanning, and 3D cameras. Subsequently, we explore body size calculation methods and compare the advantages and disadvantages of RGB image calculation methods and 3D point cloud body size calculation methods. Furthermore, we also compare and analyze weight estimation methods of linear regression and neural networks. Finally, we discuss the challenges and future trends of non-contact livestock phenotypic data acquisition. Through emerging technologies like next-generation AI and computer vision, the acquisition, analysis, and management of livestock phenotypic data are poised for rapid advancement.

Fruit softening is an important characteristic of peach fruit ripening. The auxin receptor TIR1 (Transport Inhibitor Response 1) plays an important role in plant growth and fruit maturation. Still, little research has been conducted on the relation of TIR1 to the softening of peach fruits. In this study, the hardness of isolated peach fruits was reduced under exogenous NAA treatment at low concentrations. At the same time, the low concentration of NAA treatment reduced the transcription level of PpPG and Ppβ-GAL genes related to cell wall softening and PpACS1 genes related to ethylene synthesis. The transient overexpression of the PpTIR1 gene in peach fruit blocks caused significant down-regulation of the expression of early auxin-responsive genes, ethylene synthesis, and cell wall metabolic genes related to fruit firmness. Through yeast two-hybrid technology, bimolecular fluorescence complementary technology, and a firefly luciferase complementation imaging assay, we were able to unveil an interaction between PpTIR1 and PpIAA1/3/5/9/27 proteins. Furthermore, it was determined that the interaction depended on auxin and its type and concentration. These results show that the PpTIR1-Aux/IAA module has a possible regulatory effect on fruit ripening and softening.