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Yield is one of the most important yet complex crop traits. To improve our understanding of the genetic basis of yield establishment, and to identify candidate genes responsible for yield improvement in Brassica napus, we performed genome-wide association studies (GWAS) for seven yield-determining traits [main inflorescence pod number (MIPN), branch pod number (BPN), pod number per plant (PNP), seed number per pod (SPP), thousand seed weight, main inflorescence yield (MIY), and branch yield], using data from 520 diverse B. napus accessions from two different yield environments. In total, we detected 128 significant single nucleotide polymorphisms (SNPs), 93 of which were revealed as novel by integrative analysis. A combination of GWAS and transcriptome sequencing on 21 haplotype blocks from samples pooled by four extremely high-yielding or low-yielding accessions revealed the differential expression of 14 crucial candiate genes (such as Bna.MYB83, Bna.SPL5, and Bna.ROP3) associated with multiple traits or containing multiple SNPs associated with the same trait. Functional annotation and expression pattern analyses further demonstrated that these 14 candiate genes might be important in developmental processes and biomass accumulation, thus affecting the yield establishment of B. napus. These results provide valuable information for understanding the genetic mechanisms underlying the establishment of high yield in B. napus, and lay the foundation for developing high-yielding B. napus varieties.

Based on the international community's analysis of the present CO2 emissions situation, a Log Mean Divisia Index (LMDI) decomposition model is proposed in this paper, aiming to reflect the decomposition of carbon productivity. The model is designed by analyzing the factors that affect carbon productivity. China's contribution to carbon productivity is analyzed from the dimensions of influencing factors, regional structure and industrial structure. It comes to the conclusions that: (a) economic output, the provincial carbon productivity and energy structure are the most influential factors, which are consistent with China's current actual policy; (b) the distribution patterns of economic output, carbon productivity and energy structure in different regions have nothing to do with the Chinese traditional sense of the regional economic development patterns; (c) considering the regional protectionism, regional actual situation need to be considered at the same time; (d) in the study of the industrial structure, the contribution value of industry is the most prominent factor for China's carbon productivity, while the industrial restructuring has not been done well enough.