A gene integrates the effects of all SNPs in its sequence span, which benefits the genome-wide association study. To explore gene-level variations affecting economic traits in maize, we extended the SNP-based GWAS analysis software Single-RunKing developed by our team to gene-based GWAS, which used the FaST-LMM algorithm to convert the linear mixed model into simple linear model association analysis. An F-test statistic was formulated to test and identify candidate genes. We compared the statistical efficiency of using 80% principal components (EPC), the first principal component (FPC), and all SNP markers (ALLSNP) as independent variables, which predecessors commonly used to integrate SNPs and represent genes. With a Huazhong Agricultural University (HAU) genomic dataset of 2.65M SNPs from 540 maize plants, 34,774 genes were annotated across the whole genome. Genome-wide association studies with 20 agronomic traits were performed using the software developed here. Another maize dataset from the Ames panel (AP) was also analyzed. The EPC method fits the model well and has good statistical efficiency. It not only overcomes the false negative problem when using all SNP markers for analysis (ALLSNP) but also solves the false positive problem of its corresponding simple linear model method EPCLM. Compared with FPC, the EPC method has higher statistical efficiency. A total of 132 quantitative trait genes (QTG) were identified for the 20 traits from HAU maize dataset and one trait of AP maize.

In this work, a tomato biochar composite modified with cetyltrimethylammonium bromide (CTAB@TBC) was successfully synthesized using an ethanol solution method. It was comprehensively characterized to evaluate its morphology (SEM), crystal structure (XRD), chemical bonding (FT-IR and Raman spectroscopy), surface area (BET analysis), and thermal stability (TGA). The adsorption performance of the composite for xylenol orange (XO) was subsequently evaluated in detail. The findings revealed that CTAB@TBC exhibited a maximum adsorption capacity of 150.59 mg/g for XO. Kinetic analysis indicated that the adsorption process conformed to a pseudo-second-order model, implying that chemisorption was the step limiting the rate. The Langmuir model accurately described the adsorption isotherm data, suggesting monolayer adsorption on a uniform surface. Thermodynamic evaluation further revealed a negative Gibbs free energy (ΔG) change, confirming the spontaneity of the adsorption process. In summary, the results suggest that CTAB@TBC is a highly effective adsorbent for eliminating dyes from wastewater and offers considerable promise for treating industrial effluents.