Maize (Zea mays) is a major staple crop. Maize kernel size and weight are important contributors to its yield. Here, we measured kernel length, kernel width, kernel thickness, hundred kernel weight, and kernel test weight in 10 recombinant inbred line populations and dissected their genetic architecture using three statistical models. In total, 729 quantitative trait loci (QTLs) were identified, many of which were identified in all three models, including 22 major QTLs that each can explain more than 10% of phenotypic variation. To provide candidate genes for these QTLs, we identified 30 maize genes that are orthologs of 18 rice (Oryza sativa) genes reported to affect rice seed size or weight. Interestingly, 24 of these 30 genes are located in the identified QTLs or within 1 Mb of the significant single-nucleotide polymorphisms. We further confirmed the effects of five genes on maize kernel size/weight in an independent association mapping panel with 540 lines by candidate gene association analysis. Lastly, the function of ZmINCW1, a homolog of rice GRAIN INCOMPLETE FILLING1 that affects seed size and weight, was characterized in detail. ZmINCW1 is close to QTL peaks for kernel size/weight (less than 1 Mb) and contains significant single-nucleotide polymorphisms affecting kernel size/weight in the association panel. Overexpression of this gene can rescue the reduced weight of the Arabidopsis (Arabidopsis thaliana) homozygous mutant line in the AtcwINV2 gene (Arabidopsis ortholog of ZmINCW1). These results indicate that the molecular mechanisms affecting seed development are conserved in maize, rice, and possibly Arabidopsis.Maize (Zea mays) is one of the most important crops and is cultivated worldwide as a source of staple food, animal feed, and industrial materials. According to the Food and Agriculture Organization, the production of maize was 1,016.7 million tons in 2013, which was far more than rice (Oryza sativa) and wheat (Triticum aestivum; 745.7 and 713.1 million tons, respectively). Yield improvement is a central goal of maize breeding. Kernel size and weight are two significant components of maize yield, and many attempts have been made to elucidate the genetic basis of kernel size and weight.Many studies have mapped quantitative trait loci (QTLs) for natural variations in kernel size and weight. (2015) mapped 28 QTLs in a test cross population. Most of these studies used two diverse inbred lines to develop the segregating population and used a limited number of genetic markers to construct the linkage map, which greatly limited the resolution and power to detect rare and/or small-effect QTLs. Large-scale QTL mapping studies including more diverse genetic backgrounds and dense genetic markers would provide more insight into the number and effect of QTLs controlling the natural variations of kernel size and weight in maize.

Plant architecture is a key factor affecting planting density and grain yield in maize (Zea mays). However, the genetic mechanisms underlying plant architecture in diverse genetic backgrounds have not been fully addressed. Here, we performed a large-scale phenotyping of 10 plant architecture-related traits and dissected the genetic loci controlling these traits in 10 recombinant inbred line populations derived from 14 diverse genetic backgrounds. Nearly 800 quantitative trait loci (QTLs) with major and minor effects were identified as contributing to the phenotypic variation of plant architecture-related traits. Ninety-two percent of these QTLs were detected in only one population, confirming the diverse genetic backgrounds of the mapping populations and the prevalence of rare alleles in maize. The numbers and effects of QTLs are positively associated with the phenotypic variation in the population, which, in turn, correlates positively with parental phenotypic and genetic variations. A large proportion (38.5%) of QTLs was associated with at least two traits, suggestive of the frequent occurrence of pleiotropic loci or closely linked loci. Key developmental genes, which previously were shown to affect plant architecture in mutant studies, were found to colocalize with many QTLs. Five QTLs were further validated using the segregating populations developed from residual heterozygous lines present in the recombinant inbred line populations. Additionally, one new plant height QTL, qPH3, has been fine-mapped to a 600-kb genomic region where three candidate genes are located. These results provide insights into the genetic mechanisms controlling plant architecture and will benefit the selection of ideal plant architecture in maize breeding.

Summary Low grain moisture at harvest is crucial for safe production, transport and storage, but the genetic architecture of this trait in maize (Zea mays) remains elusive. Here, we measured the dynamic changes in grain moisture content in an association‐mapping panel of 513 diverse maize inbred lines at five successive stages across five geographical environments. Genome‐wide association study (GWAS) revealed 71 quantitative trait loci (QTLs) that influence grain moisture in maize. Epistatic effects play vital roles in the variability in moisture levels, even outperforming main‐effect QTLs during the early dry‐down stages. Distinct QTL–environment interactions influence the spatio‐temporal variability of maize grain moisture, which is primarily triggered at specific times. By combining genetic population analysis, transcriptomic profiling and gene editing, we identified GRMZM5G805627 and GRMZM2G137211 as candidate genes underlying major QTLs for grain moisture in maize. Our results provide insights into the genetic architecture of dynamic changes in grain moisture, which should facilitate maize breeding.

Genome information from model species such as rice can assist in the cloning of genes in a complex genome, such as maize. Here, we identified a maize ortholog of rice GS5 that contributes to kernel development in maize. The genomewide association analysis of the expression levels of ZmGS5, and 15 of its 26 paralogs, identified a trans-regulator on chromosome 7, which was a BAK1-like gene. This gene that we named as ZmBAK1-7 could regulate the expression of ZmGS5 and three of the paralogs. Candidate-gene association analyses revealed that these five genes were associated with maize kernel development-related traits. Linkage analyses also detected that ZmGS5 and ZmBAK1-7 co-localized with mapped QTLs. A transgenic analysis of ZmGS5 in Arabidopsis thaliana L.showed a significant increase in seed weight and cell number, suggesting that ZmGS5 may have a conserved function among different plant species that affects seed development.

The accurate weed detection is the premise for precision prevention and control of weeds in fields. Machine vision offers an effective means to detect weeds accurately. For precision detection of various weeds in carrot fields, this paper improves You Only Look Once v4 (YOLO v4) into a lightweight weed detection model called YOLO v4-weeds for the weeds among carrot seedlings. Specifically, the backbone network of the original YOLOv4 was replaced with MobileNetV3-Small. Combined with depth-wise separable convolution and inverted residual structure, a lightweight attention mechanism was introduced to reduce the memory required to process images, making the detection model more efficient. The research results provide a reference for the weed detection, robot weeding, and selective spraying.