Tailings dust can negatively affect the surrounding environment and communities because the tailings are vulnerable to wind erosion. In this study, the effects of halides (sodium chloride [NaCl], calcium chloride [CaCl2], and magnesium chloride hexahydrate [MgCl2·6H2O]), and polymer materials (polyacrylamide [PAM], polyvinyl alcohol [PVA], and calcium lignosulfonate [LS]) were investigated for the stabilization of tailings for dust control. Erect milkvetch (Astragalus adsurgens), ryegrass (Lolium perenne L.), and Bermuda grass (Cynodon dactylon) were planted in the tailings and sprayed with chemical dust suppressants. The growth status of the plants and their effects on the mechanical properties of tailings were also studied. The results show that the weight loss of tailings was stabilized by halides and polymers, and decreased with increasing concentration and spraying amount of the solutions. The penetration resistance of tailings stabilized by halides and polymers increased with increasing concentration and spraying amount of the solutions. Among the halides and polymers tested, the use of CaCl2 and PAM resulted in the best control of tailings dust, respectively. CaCl2 solution reduces the adaptability of plants and therefore makes it difficult for grass seeds to germinate normally. PAM solutions are beneficial for the development of herbaceous plants. Among the three herbaceous species, ryegrass exhibited the best degree of development and was more suitable for growth in the tailings. The ryegrass plants planted in the tailings sprayed with PAM grew the best, and the root-soil complex that formed increased the shear strength of the tailings.

Responses of turfgrass to shade vary in individual species, and the degree and quality of low light; therefore, the selection of low light tolerant cultivars of turfgrass is important and beneficial for turf management rather than other practices. The stolons of thirteen bermudagrass genotypes were planted with two treatments and three replications of each treatment to establish for one month in the Yangzhou University Jiangsu China greenhouse. The established plants were transferred outside of the greenhouse, and 50% shading was applied to them with a black net. After 30 days of stress treatment, the morpho-physiological and biochemical analyses were performed. The expression of genes such as HEMA, HY5, PIF4, and Cu/ZnSOD was assessed. Cynodon dactylon is a C4, and perennial that grows as lawn grass and is used as forage. Based on different indicator measurements, the most shade-tolerant germplasm was L01 and L06 along the longitudes and L09 and L10 along the latitudes. At the same time, L02 and L08 were more susceptible, respectively. However, germplasm showed greater tolerance in higher latitudes while longitudinal plants showed less stress response. The current study aimed (1) to screen out the most shade-tolerant Cynodon dactylon genotype among 13 along longitudinal and latitudinal gradients in China. (2) to examine morpho-physiological indicators of different bermudagrassgenotypes; (3) to evaluate if and how differences in various indicators of bermudagrass correlated with geographic region. This study will significantly advance the use of Cynodon germplasm in breeding, genomics, management, nomenclature, and phylogeographical study. It will decisively define whether natural selection and migration can drive evolutionary responses for populations to adapt to their new environments effectively.

As an important warm-season turfgrass species, bermudagrass (Cynodon dactylon L.) flourishes in warm areas around the world due to the existence of the C4 photosynthetic pathway. However, how C4 photosynthesis operates in bermudagrass leaves is still poorly understood. In this study, we performed single-cell RNA-sequencing on 5296 cells from bermudagrass leaf blades. Eight cell clusters corresponding to mesophyll, bundle sheath, epidermis and vascular bundle cells were successfully identified using known cell marker genes. Expression profiling indicated that genes encoding NADP-dependent malic enzymes (NADP-MEs) were highly expressed in bundle sheath cells, whereas NAD-ME genes were weakly expressed in all cell types, suggesting C4 photosynthesis of bermudagrass leaf blades might be NADP-ME type rather than NAD-ME type. The results also indicated that starch synthesis-related genes showed preferential expression in bundle sheath cells, whereas starch degradation-related genes were highly expressed in mesophyll cells, which agrees with the observed accumulation of starch-filled chloroplasts in bundle sheath cells. Gene co-expression analysis further revealed that different families of transcription factors were co-expressed with multiple C4 photosynthesis-related genes, suggesting a complex transcription regulatory network of C4 photosynthesis might exist in bermudagrass leaf blades. These findings collectively provided new insights into the cell-specific expression patterns and transcriptional regulation of photosynthetic genes in bermudagrass.

BACKGROUND: Light deficit in shaded environment critically impacts the growth and development of turf plants. Despite this fact, past research has predominantly concentrated on shade avoidance rather than shade tolerance. To address this, our study examined the photosynthetic adjustments of Bermudagrass when exposed to varying intensities of shade to gain an integrative understanding of the shade response of C4 turfgrass.
RESULTS: We observed alterations in photosynthetic pigment-proteins, electron transport and its associated carbon and nitrogen assimilation, along with ROS-scavenging enzyme activity in shaded conditions. Mild shade enriched Chl b and LHC transcripts, while severe shade promoted Chl a, carotenoids and photosynthetic electron transfer beyond QA- (ET0/RC, φE0, Ψ0). The study also highlighted differential effects of shade on leaf and root components. For example, Soluble sugar content varied between leaves and roots as shade diminished SPS, SUT1 but upregulated BAM. Furthermore, we observed that shading decreased the transcriptional level of genes involving in nitrogen assimilation (e.g. NR) and SOD, POD, CAT enzyme activities in leaves, even though it increased in roots.
CONCLUSIONS: As shade intensity increased, considerable changes were noted in light energy conversion and photosynthetic metabolism processes along the electron transport chain axis. Our study thus provides valuable theoretical groundwork for understanding how C4 grass acclimates to shade tolerance.

Endophytic bacteria, recognized as eco-friendly biofertilizers, have demonstrated the potential to enhance crop growth and yield. While the plant growth-promoting effects of endophytic bacteria have been extensively studied, the impact of weed endophytes remains less explored. In this study, we aimed to isolate endophytic bacteria from native weeds and assess their plant growth-promoting abilities in rice under varying chemical fertilization. The evaluation encompassed measurements of mineral phosphate and potash solubilization, as well as indole-3-acetic acid (IAA) production activity by the selected isolates. Two promising strains, tentatively identified as Alcaligenes faecalis (BTCP01) from Eleusine indica (Goose grass) and Metabacillus indicus (BTDR03) from Cynodon dactylon (Bermuda grass) based on 16S rRNA gene phylogeny, exhibited noteworthy phosphate and potassium solubilization activity, respectively. BTCP01 demonstrated superior phosphate solubilizing activity, while BTDR03 exhibited the highest potassium (K) solubilizing activity. Both isolates synthesized IAA in the presence of L-tryptophan, with the detection of nifH and ipdC genes in their genomes. Application of isolates BTCP01 and BTDR03 through root dipping and spraying at the flowering stage significantly enhanced the agronomic performance of rice variety CV. BRRI dhan29. Notably, combining both strains with 50% of recommended N, P, and K fertilizer doses led to a substantial increase in rice grain yields compared to control plants receiving 100% of recommended doses. Taken together, our results indicate that weed endophytic bacterial strains BTCP01 and BTDR03 hold promise as biofertilizers, potentially reducing the dependency on chemical fertilizers by up to 50%, thereby fostering sustainable rice production.

BACKGROUND: Rhodesgrass mealybug, Antonina graminis, is a serious pest of ultradwarf hybrid bermudagrass (Cynodon dactylon × C. transvaalensis) on golf course putting greens. A. graminis feeding damage appears as extensive yellowing of turfgrass blades and heavy thinning from mid-to-late summer into fall. Putting greens are intensively managed areas of the golf course where fertilizers are routinely applied to maintain and enhance turfgrass quality, playability and aesthetics. We hypothesize that A. graminis populations can be minimized by reducing nitrogen (N) fertilizer and then effectively managed using systemic insecticides. The objective of this study was to determine the effects of various levels of N fertilizer and flupyradifurone on the A. graminis population and turfgrass quality on the golf course putting green. The treatments were low, medium, and high N fertilizer rates with and without insecticide (flupyradifurone).
RESULTS: Applying a high dose of N fertilizer improved turfgrass quality without increasing A. graminis densities on the golf course green. Although flupyradifurone application reduced A. graminis densities regardless of N fertilizer treatments, suppression of A. graminis densities improved at the high fertilizer dose with flupyradifurone. Additionally, the turfgrass quality on the putting green improved with high N fertilizer alone, regardless of flupyradifurone application.
CONCLUSIONS: A. graminis populations can be managed using moderate to high levels of N fertilizer and applying a systemic insecticide. The low nitrogen fertilizer did not effectively reduce the A. graminis densities on the putting green. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Bermudagrass mite (Aceria cynodoniensis Sayed) infestation stunts bermudagrass (Cynodon spp. [Poales: Poaceae]) growth, leading to thinned turf and lower aesthetic and recreational value. Bermudagrass mites cause characteristic symptoms called witch\'s brooms, including shortened internodes and leaves and the proliferation of tillers. Grass clippings produced by mowing or scalping bermudagrass harbor mites, which abandon the desiccating grass clippings and spread to surrounding turfgrass. Dropped grass clippings can lead to infestation of new turfgrass. Nursery experiments were conducted with potted bermudagrass to determine the effect of removing witch\'s brooms or grass clippings after scalping on witch\'s broom densities on the recovering bermudagrass. Additionally, laboratory experiments were conducted to assess the potential for mites to abandon detached witch\'s brooms and to evaluate mite survival after leaving their hosts. The number of initial witch\'s brooms and individually removing witch\'s brooms did not affect subsequent witch\'s broom densities, suggesting that infested but asymptomatic terminals later developed into witch\'s brooms. Removing grass clippings after scalping reduced witch\'s broom densities by over 65% in two trials. Most mites (96%) abandoned witch\'s brooms within 48 h after detaching witch\'s brooms, and adult mites survived an average of 5.6 h after removal from the host plant. Removing clippings after scalping may improve bermudagrass mite management and limit damage on the recovering turfgrass. Additionally, clippings resulting from regular mowing or scalping should be disposed of properly because this study demonstrates that mites abandon desiccating host plants and survive sufficiently long to infest surrounding turfgrass.

Drought stress considered a key restrictive factor for a warm-season bermudagrass growth during summers in China. Genotypic variation against drought stress exists among bermudagrass (Cynodon sp.), but the selection of highly drought-tolerant germplasm is important for its growth in limited water regions and for future breeding. Our study aimed to investigate the most tolerant bermudagrass germplasm among thirteen, along latitude and longitudinal gradient under a well-watered and drought stress condition. Current study included high drought-resistant germplasm, \"Tianshui\" and \"Linxiang\", and drought-sensitive cultivars; \"Zhengzhou\" and \"Cixian\" under drought treatments along longitude and latitudinal gradients, respectively. Under water deficit conditions, the tolerant genotypes showed over-expression of a dehydrin gene cdDHN4, antioxidant genes Cu/ZnSOD and APX which leads to higher antioxidant activities to scavenge the excessive reactive oxygen species and minimizing the membrane damage. It helps in maintenance of cell membrane permeability and osmotic adjustment by producing organic osmolytes. Proline an osmolyte has the ability to keep osmotic water potential and water use efficiency high via stomatal conductance and maintain transpiration rate. It leads to optimum CO2 assimilation rate, high chlorophyll contents for photosynthesis and elongation of leaf mesophyll, palisade and thick spongy cells. Consequently, it results in elongation of leaf length, stolon and internode length; plant height and deep rooting system. The CdDHN4 gene highly expressed in \"Tianshui\" and \"Youxian\", Cu/ZnSOD gene in \"Tianshui\" and \"Linxiang\" and APX gene in \"Shanxian\" and \"Linxiang\". The genotypes \"Zhongshan\" and \"Xiaochang\" showed no gene expression under water deficit conditions. Our results indicate that turfgrass show morphological modifications firstly when subjected to drought stress; however the gene expression is directly associated and crucial for drought tolerance in bermudagrass. Hence, current research has provided excellent germplasm of drought tolerant bermudagrass for physiological and molecular study and future breeding.

Bermudagrass (Cynodon dactylon) is a globally distributed, extensively used warm-season turf and forage grass with high tolerance to salinity and drought stress in alkaline environments. However, the origin of the species and genetic mechanisms for salinity tolerance in the species are basically unknown. Accordingly, we set out to study evolution divergence events in the Cynodon genome and to identify genes for salinity tolerance. We developed a 604.0 Mb chromosome-level polyploid genome sequence for bermudagrass \'A12359\' (n = 18). The C. dactylon genome comprises 2 complete sets of homoeologous chromosomes, each with approximately 30 000 genes, and most genes are conserved as syntenic pairs. Phylogenetic study showed that the initial Cynodon species diverged from Oropetium thomaeum approximately 19.7-25.4 million years ago (Mya), the A and B subgenomes of C. dactylon diverged approximately 6.3-9.1 Mya, and the bermudagrass polyploidization event occurred 1.5 Mya on the African continent. Moreover, we identified 82 candidate genes associated with seven agronomic traits using a genome-wide association study, and three single-nucleotide polymorphisms were strongly associated with three salt resistance genes: RAP2-2, CNG channels, and F14D7.1. These genes may be associated with enhanced bermudagrass salt tolerance. These bermudagrass genomic resources, when integrated, may provide fundamental insights into evolution of diploid and tetraploid genomes and enhance the efficacy of comparative genomics in studying salt tolerance in Cynodon.

BACKGROUND: Accurate detection of weeds and estimation of their coverage is crucial for implementing precision herbicide applications. Deep learning (DL) techniques are typically used for weed detection and coverage estimation by analyzing information at the pixel or individual plant level, which requires a substantial amount of annotated data for training. This study aims to evaluate the effectiveness of using image-classification neural networks (NNs) for detecting and estimating weed coverage in bermudagrass turf.
RESULTS: Weed-detection NNs, including DenseNet, GoogLeNet and ResNet, exhibited high overall accuracy and F1 scores (≥0.971) throughout the k-fold cross-validation. DenseNet outperformed GoogLeNet and ResNet with the highest overall accuracy and F1 scores (0.977). Among the evaluated NNs, DenseNet showed the highest overall accuracy and F1 scores (0.996) in the validation and testing data sets for estimating weed coverage. The inference speed of ResNet was similar to that of GoogLeNet but noticeably faster than DenseNet. ResNet was the most efficient and accurate deep convolution neural network for weed detection and coverage estimation.
CONCLUSIONS: These results demonstrated that the developed NNs could effectively detect weeds and estimate their coverage in bermudagrass turf, allowing calculation of the herbicide requirements for variable-rate herbicide applications. The proposed method can be employed in a machine vision-based autonomous site-specific spraying system of smart sprayers. © 2024 Society of Chemical Industry.