In order to explore the molecular regulatory mechanism of temperature acclimation under long-term temperature stress in Acrossocheilus fasciatus, this study used high-throughput sequencing technology to analyze 60 days of breeding under five temperature conditions (12 °C, 16 °C, 20 °C, 24 °C, 28 °C). Compared with 20 °C, 9202, 4959 differentially expressed genes (DEGs) were discovered in low-temperature groups (12 °C, 16 °C), whereas 133 and 878 DEGs were discovered in high-temperature groups (24 °C, 28 °C), respectively. The KEGG functional enrichment analysis revealed that DEGs were primarily enriched in tight junction, PI3 K-Akt signaling pathway and protein digestion and absorption in low-temperature groups, and mainly enriched in proximal tubule bicarbonate reclamation, protein digestion and absorption, and HIF-1 signaling pathway in high-temperature groups. The viability of transcriptome sequencing-based screening of DEGs for temperature adaptation in A. fasciatus was shown by the selection of eight DEGs for further validation by quantitative real-time PCR (qRT-PCR), the findings of which were consistent with the RNA-seq data. According to the findings, protein digestion and absorption were primarily regulated by temperature variations, physiological stress was a significant regulator in regulation under high-temperature stress, and the immune system was a significant regulator in regulation under low-temperature stress. The transcriptional patterns of A. fasciatus under temperature stress are revealed in this study. This knowledge is crucial for understanding how A. fasciatus adapts to temperature and can help us better comprehend the environmental difficulties that A. fasciatus adaptation faces.

The irrational disposal of agricultural waste harms the interests of the main bodies of the related supply chain while seriously jeopardizing the environment. To a certain extent, the reverse supply chain (RSC) of agricultural waste can provide more high-quality resources for agricultural production and promote the green development of agricultural production. Therefore, RSC optimization is of great significance to the sustainable development of agriculture. We constructed an evolutionary game model of agricultural waste recyclers and reprocessing enterprises for agricultural waste. The stability of mixed strategies was analyzed using a Jacobi matrix, and evolutionary paths under varying parameter ranges were simulated using MATLAB. The simulation results show that in the early stage of RSC optimization, government subsidies to reprocessing enterprises and increased subsidies for agricultural waste recyclers are conducive to a more stable agricultural waste reverse-recycling market. When the agricultural waste reverse-recycling market reaches a certain scale, the government should gradually reduce subsidies, effectively preventing enterprises from being overly reliant on them. This study not only offers a decision-making foundation for agricultural waste recyclers and agricultural waste reprocessing enterprises to make optimal strategic choices but also serves as a reference for the government in formulating appropriate policies.