Search Results (6)

Soil amendments are widely promoted to improve turfgrass performance and soil properties in suboptimal soil; however, their effectiveness under field-managed conditions remains unclear. Two concurrent field experiments (i.e., turfgrass and soil and reduced nitrogen) were conducted from August 2022 to November 2023 in Gainesville, FL, using a randomized complete block design to evaluate organic and biological amendments under standard and reduced nitrogen (N) fertilization. In the turfgrass and soil portion, treatments included granular humic + fertilizer, liquid humic + fertilizer, biochar + fertilizer, microbial inoculant + fertilizer, compost, natural fertilizer, fertilizer, and a non-treated control. In the reduced N experiment, fertilizer rates for all amendment combinations and the natural fertilizer were applied at 50% (12.2 kg N ha⁻¹), while the full-rate fertilizer (24.4 kg N ha⁻¹) and non-treated control were included for comparison. Treatments were applied to St. Augustinegrass (Stenotaphrum secundatum (Walt.) Kuntze) and zoysiagrass (Zoysia spp. Willd.) established on a sand-based root zone. Turfgrass performance was assessed using visual quality, normalized difference vegetation index, and percent green via digital image analysis. Soil properties were evaluated using physical, chemical, and biological parameters. Treatment responses varied by amendment type and N rate. All treatments improved turfgrass performance relative to the non-treated control, with compost producing the greatest improvements in turfgrass quality and soil properties, including organic matter, pH, and plant-available P, K, and Fe. Humic substances, biochar, and microbial inoculants primarily increased potentially mineralizable N but provided limited improvements in turfgrass performance compared with fertilizer alone. Nitrogen rate was the primary determinant of turfgrass performance, with full N treatments producing the highest quality. Although reduced N treatments improved turfgrass quality relative to the control, amendment additions did not consistently enhance turfgrass performance under reduced N conditions. Full article

Stenotaphrum secundatum is an excellent shade-tolerant warm-season turfgrass. Its poor cold resistance severely limits its promotion and application in temperate regions. Mining cold resistance genes is highly important for the cultivation of cold-resistant Stenotaphrum secundatum. Although there have been many reports on the role of the Shaker potassium channel family under abiotic stress, such as drought and salt stress, there is still a lack of research on their role in cold resistance. In this study, the transcriptome database of Stenotaphrum secundatum was aligned with the whole genome of Setaria italica, and eight members of the Shaker potassium channel family in Stenotaphrum secundatum were identified and named SsKAT1.1, SsKAT1.2, SsKAT2.1, SsKAT2.2, SsAKT1.1, SsAKT2.1, SsAKT2.2, and SsKOR1. The KAT3-like gene, KOR2 homologous gene, and part of the AKT-type weakly inwardly rectifying channel have not been identified in the Stenotaphrum secundatum transcriptome database. A bioinformatics analysis revealed that the potassium channels of Stenotaphrum secundatum are highly conserved in terms of protein structure but have more homologous members in the same group than those of other species. Among the three species of Oryza sativa, Arabidopsis thaliana, and Setaria italica, the potassium channel of Stenotaphrum secundatum is more closely related to the potassium channel of Setaria italica, which is consistent with the taxonomic results of these species belonging to Paniceae. Subcellular location experiments demonstrate that SsKAT1.1 is a plasma membrane protein. The expression of SsKAT1.1 reversed the growth defect of the potassium absorption-deficient yeast strain R5421 under a low potassium supply, indicating that SsKAT1.1 is a functional potassium channel. The transformation of SsKAT1.1 into the cold-sensitive yeast strain INVSC1 increased the cold resistance of the yeast, indicating that SsKAT1.1 confers cold resistance. The transformation of SsKAT1.1 into the salt-sensitive yeast strain G19 increased the resistance of yeast to salt, indicating that SsKAT1.1 is involved in salt tolerance. These results suggest that the manipulation of SsKAT1.1 will improve the cold and salt stress resistance of Stenotaphrum secundatum. Full article

The genus Pyricularia includes species that are phytopathogenic fungi, which infect different species of Poaceae, such as rice and sorghum. However, few isolates have been genetically characterized in North America. The current study addresses this lack of information by characterizing an additional 57 strains of three grasses (Stenotaphrum secundatum, Cenchrus ciliaris and Digitaria ciliaris) from two distant regions of Mexico. A Pyricularia dataset with ITS sequences retrieved from GenBank and the studied sequences were used to build a haplotype network that allowed us to identify a few redundant haplotypes highly related to P. oryzae species. An analysis considering only the Mexican sequences allowed us to identify non-redundant haplotypes in the isolates of C. ciliaris and D. ciliaris, with a high identity with P. pennisetigena. The Pot2-TIR genomic fingerprinting technique resulted in high variability and allowed for the isolates to be grouped according to their host grass, whilst the ERIC-PCR technique was able to separate the isolates according to their host grass and their region of collection. Representative isolates from different host grasses were chosen to explore the pathogenic potential of these isolates. The selected isolates showed a differential pathogenic profile. Cross-infection with representative isolates from S. secundatum and C. ciliaris showed that these were unable to infect D. ciliaris grass and that the DY1 isolate from D. ciliaris was only able to infect its host grass. The results support the identification of pathogenic strains of Pyricularia isolates and their cross-infection potential in different grasses surrounding important crops in Mexico. Full article

Intelligent sensing systems based on the edge-computing paradigm are essential for the implementation of Internet of Things (IoT) and Agriculture 4.0 applications. The development of edge-computing wireless sensing systems is required to improve the sensor’s accuracy in soil and data interpretation. Therefore, measuring and processing data at the edge, rather than sending it back to a data center or the cloud, is still an important issue in wireless sensor networks (WSNs). The challenge under this paradigm is to achieve a sustainable operation of the wireless sensing system powered with alternative renewable energy sources, such as plant microbial fuel cells (PMFCs). Consequently, the motivation of this study is to develop a sustainable forage-grass-power fuel cell solution to power an IoT Long-Range (LoRa) network for soil monitoring. The stenotaphrum secundatum grass plant is used as a microbial fuel cell proof of concept, implemented in a 0.015 m${}^3$-chamber with carbon plates as electrodes. The BQ25570 integrated circuit is employed to harvest the energy in a 4 F supercapacitor, which achieves a maximum generation capacity of $1.8$ mW. The low-cost pH SEN0169 and the SHT10 temperature and humidity sensors are deployed to analyze the soil parameters. Following the edge-computing paradigm, the inverse problem methodology fused with a system identification solution is conducted, correcting the sensor errors due to non-linear hysteresis responses. An energy power management strategy is also programmed in the MSP430FR5994 microcontroller unit, achieving average power consumption of 1.51 mW, ∼19% less than the energy generated by the forage-grass-power fuel cell. Experimental results also demonstrate the energy sustainability capacity achieving a total of 18 consecutive transmissions with the LoRa network without the system’s shutting down. Full article

Plants readily communicate with their pollinators, herbivores, symbionts, and the predators and pathogens of their herbivores. We previously demonstrated that plants could exchange, relay, and adaptively utilize drought cues from their conspecific neighbors. Here, we studied the hypothesis that plants can exchange drought cues with their interspecific neighbors. Triplets of various combinations of split-root Stenotaphrum secundatum and Cynodon dactylon plants were planted in rows of four pots. One root of the first plant was subjected to drought while its other root shared its pot with one of the roots of an unstressed target neighbor, which, in turn, shared its other pot with an additional unstressed target neighbor. Drought cuing and relayed cuing were observed in all intra- and interspecific neighbor combinations, but its strength depended on plant identity and position. Although both species initiated similar stomatal closure in both immediate and relayed intraspecific neighbors, interspecific cuing between stressed plants and their immediate unstressed neighbors depended on neighbor identity. Combined with previous findings, the results suggest that stress cuing and relay cuing could affect the magnitude and fate of interspecific interactions, and the ability of whole communities to endure abiotic stresses. The findings call for further investigation into the mechanisms and ecological implications of interplant stress cuing at the population and community levels. Full article

Soil nitrification (microbial oxidation of ammonium to nitrate) can lead to nitrogen leaching and environmental pollution. A number of plant species are able to suppress soil nitrifiers by exuding inhibitors from roots, a process called biological nitrification inhibition (BNI). However, the BNI activity of perennial grasses in the nutrient-poor soils of Australia and the effects of BNI activity on nitrifying microbes in the rhizosphere microbiome have not been well studied. Here we evaluated the BNI capacity of bermudagrass (Cynodon dactylon L.), St. Augustinegrass (Stenotaphrum secundatum (Walt.) Kuntze), saltwater couch (Sporobolus virginicus), seashore paspalum (Paspalum vaginatum Swartz.), and kikuyu grass (Pennisetum clandestinum) compared with the known positive control, koronivia grass (Brachiaria humidicola). The microbial communities were analysed by sequencing 16S rRNA genes. St. Augustinegrass and bermudagrass showed high BNI activity, about 80 to 90% of koronivia grass. All the three grasses with stronger BNI capacities suppressed the populations of Nitrospira in the rhizosphere, a bacteria genus with a nitrite-oxidizing function, but not all of the potential ammonia-oxidizing archaea. The rhizosphere of saltwater couch and seashore paspalum exerted a weak recruitment effect on the soil microbiome. Our results demonstrate that BNI activity of perennial grasses played a vital role in modulating nitrification-associated microbial populations. Full article