Green control for inhibiting Rhizopus oryzae growth by stress factors in forage grass factory.

The forage grass factory could break through the restrictions of land resources, region and climate to achieve efficient production throughout the year by accurate and intelligent management. However, due to its closed environment, mold outbreaks in the forage grass factory were severe, significantly affecting barley production. In this study, 9 contaminated barley tissues were collected and 45 strains were isolated in forage grass factory. After ITS sequencing, 45 strains were all identified as Rhizopus oryzae. Through stress factor assays, R. oryzae growth was seriously hindered by low concentration of sodium nitrate, high pH value and ozone water treatment. High pH and ozone water affected growth mainly by altering membrane integrity of R. oryzae. Sodium nitrate inhibited the growth of R. oryzae mainly by affecting the amount of sporulation. Low concentration of sodium nitrate and ozone water did not affect the growth of barley. High concentrations of sodium nitrate (100 mM) and pH values (8-8.5) inhibited barley growth. Among them, ozone water had the most obvious inhibition effect on R. oryzae. Large-scale ozone water treatment in the forage grass factory had also played a role in restoring barley production. Taken together, the green techonology to control mold disease and maintain the safety of forage through different physicochemical methods was selected, which was of considerable application value in animal husbandry.

Deciphering the functional assembly of microbial communities driven by heavy metals in the tidal soils of Hangzhou Bay.

Understanding the interaction between heavy metals and soil microbiomes is essential for maintaining ecosystem health and functionality in the face of persistent human-induced challenges. This study investigated the complex relationships between heavy metal contamination and the functional characteristics of soil microbial communities in the tidal soils of Hangzhou Bay, a region experiencing substantial environmental pressure due to its proximity to densely populated and industrialized regions. The north-shore sampling site showed moderate contaminations (mg/kg) of total arsenic (16.61 ± 1.13), cadmium (0.3 ± 0.05), copper (31.28 ± 1.23), nickel (37.44 ± 2.74), lead (34.29 ± 5.99), and zinc (120.8 ± 5.96), which are 1.29-2.94 times higher than the geochemical background values in Hangzhou Bay and adjacent areas. In contrast, the south-shore sampling site showed slightly higher levels of total arsenic (13.76 ± 1.35) and cadmium (0.13 ± 0.02) than the background values. Utilizing metagenomic sequencing, we decoded microbial functional genes essential for nitrogen, phosphorus, sulfur, and methane biogeochemical cycles. Although soil available nickel content was relatively low at 1 mg/kg, it exhibited strong associations with diverse microbial genes and biogeochemical pathways. Four key genes-hxlB, glpX, opd, and phny-emerged as pivotal players in the interactions with available nickel, suggesting the adaptability of microbial metabolic responses to heavy metal. Additionally, microbial genera such as Gemmatimonas and Ilumatobacter, which harbored diverse functional genes, demonstrated potential interactions with soil nickel. These findings highlight the importance of understanding heavy metal-soil microbiome dynamics for effective environmental management strategies in the tidal soils of Hangzhou Bay, with the goal of preserving ecosystem health and functionality amidst ongoing anthropogenic challenges.

Analysis of lettuce transcriptome reveals the mechanism of different light/dark cycle in promoting the growth and quality.

Light/dark (L/D) cycle plays a crucial role in controlling the production and quality of vegetables. However, the mechanism of L/D cycle on vegetable growth and quality is scarce studied. To investigate the impact of L/D cycle on lettuce growth and quality, we designed three diel scenarios, including 16 hours of light and 8 hours of darkness (L16/D8), 12 hours of light and 6 hours of darkness (L12/D6), and 8 hours of light and 4 hours of darkness (L8/D4). By phenotypic analysis, we found that lettuce grew taller under the L8/D4 scenario than under L16/D8 light cycle scenarios. The physiological indexes showed that the lettuce leaves grown in the L8/D4 scenario exhibited greater enhancements in the levels of soluble protein, soluble sugar, and carotenoid content compared to the other scenarios. By comparing the expression levels under different diel scenarios (L16/D8 vs L12/D6, L16/D8 vs L8/D4, and L12/D6 vs L8/D4), we identified 7,209 differentially expressed genes (DEGs). Additionally, 3 gene modules that were closely related to L/D cycle of lettuce were selected by WGCNA analysis. The eigengenes of three gene modules were enriched in plant hormone signal transduction, sphingolipid metabolism, and nucleocytoplasmic transport pathways. Through network analysis, we identified six hub genes (CIP1, SCL34, ROPGEF1, ACD6, CcmB, and Rps4) in the three gene modules, which were dominant in plant circadian rhythms and greatly affected lettuce growth. qRT-PCR analysis confirmed the diurnal response patterns of the 6 hub genes in different treatments were significant. This study intensively enhanced our comprehension of the L/D cycle in the growth morphology, nutritional quality, and metabolic pathways of lettuce.

Synthesis and photocatalytic property of Au-TiO2 nanocomposites with controlled morphologies in microfluidic chips.

We present an efficient approach for the consecutive synthesis of Au-TiO2 nanocomposites with controlled morphologies in a microfluidic chip. The seed-mediated growth method was employed to synthesize Au nanorods as the core, and TiO2 layers of varying thicknesses were deposited on the surface or tip of the Au nanorods. Au-TiO2 nanocomposites with core-shell, dumbbell, and dandelion-like structures can be precisely synthesized in a one-step manner within the microfluidic chip by finely tuning the flow rate of NaHCO3 and the amount of hexadecyl trimethyl ammonium bromide. Furthermore, we have investigated the photocatalytic activity of the synthesized nanocomposites, and it was found that Au NR-TiO2 core-shell nanostructure with a thin TiO2 shell exhibits superior catalytic performance. This work provides an effective and controlled method for the microscale preparation and photocatalytic application of various Au-TiO2 nanocomposite structures.

A hyperspectral deep learning attention model for predicting lettuce chlorophyll content.

BACKGROUND: The phenotypic traits of leaves are the direct reflection of the agronomic traits in the growth process of leafy vegetables, which plays a vital role in the selection of high-quality leafy vegetable varieties. The current image-based phenotypic traits extraction research mainly focuses on the morphological and structural traits of plants or leaves, and there are few studies on the phenotypes of physiological traits of leaves. The current research has developed a deep learning model aimed at predicting the total chlorophyll of greenhouse lettuce directly from the full spectrum of hyperspectral images. RESULTS: A CNN-based one-dimensional deep learning model with spectral attention module was utilized for the estimate of the total chlorophyll of greenhouse lettuce from the full spectrum of hyperspectral images. Experimental results demonstrate that the deep neural network with spectral attention module outperformed the existing standard approaches, including partial least squares regression (PLSR) and random forest (RF), with an average R2 of 0.746 and an average RMSE of 2.018. CONCLUSIONS: This study unveils the capability of leveraging deep attention networks and hyperspectral imaging for estimating lettuce chlorophyll levels. This approach offers a convenient, non-destructive, and effective estimation method for the automatic monitoring and production management of leafy vegetables.

Light Intensity Modulates the Functional Composition of Leaf Metabolite Groups and Phyllosphere Prokaryotic Community in Garden Lettuce (Lactuca sativa L.) Plants at the Vegetative Stage.

Light intensity primarily drives plant growth and morphogenesis, whereas the ecological impact of light intensity on the phyllosphere (leaf surface and endosphere) microbiome is poorly understood. In this study, garden lettuce (Lactuca sativa L.) plants were grown under low, medium, and high light intensities. High light intensity remarkably induced the leaf contents of soluble proteins and chlorophylls, whereas it reduced the contents of leaf nitrate. In comparison, medium light intensity exhibited the highest contents of soluble sugar, cellulose, and free amino acids. Meanwhile, light intensity resulted in significant changes in the composition of functional genes but not in the taxonomic compositions of the prokaryotic community (bacteria and archaea) in the phyllosphere. Notably, garden lettuce plants under high light intensity treatment harbored more sulfur-cycling mdh and carbon-cycling glyA genes than under low light intensity, both of which were among the 20 most abundant prokaryotic genes in the leaf phyllosphere. Furthermore, the correlations between prokaryotic functional genes and lettuce leaf metabolite groups were examined to disclose their interactions under varying light intensities. The relative abundance of the mdh gene was positively correlated with leaf total chlorophyll content but negatively correlated with leaf nitrate content. In comparison, the relative abundance of the glyA gene was positively correlated with leaf total chlorophyll and carotenoids. Overall, this study revealed that the functional composition of the phyllosphere prokaryotic community and leaf metabolite groups were tightly linked in response to changing light intensities. These findings provided novel insights into the interactions between plants and prokaryotic microbes in indoor farming systems, which will help optimize environmental management in indoor farms and harness beneficial plant-microbe relationships for crop production.

Genome-Wide Identification and Characterization of Effector Candidates with Conserved Motif in Falciphora oryzae.

Microbes employ effectors to disrupt immune responses and promote host colonization. Conserved motifs including RXLR, LFLAK-HVLVxxP (CRN), Y/F/WxC, CFEM, LysM, Chitin-bind, DPBB_1 (PNPi), and Cutinase have been discovered to play crucial roles in the functioning of effectors in filamentous fungi. Nevertheless, little is known about effectors with conserved motifs in endophytes. This research aims to discover the effector genes with conserved motifs in the genome of rice endophyte Falciphora oryzae. SignalP identified a total of 622 secreted proteins, out of which 227 were predicted as effector candidates by EffectorP. By utilizing HMM features, we discovered a total of 169 effector candidates with conserved motifs and three novel motifs. Effector candidates containing LysM, CFEM, DPBB_1, Cutinase, and Chitin_bind domains were conserved across species. In the transient expression assay, it was observed that one CFEM and one LysM activated cell death in tobacco leaves. Moreover, two CFEM and one Chitin_bind inhibited cell death induced by Bax protein. At various points during the infection, the genes' expression levels were increased. These results will help to identify functional effector proteins involving omics methods using new bioinformatics tools, thus providing a basis for the study of symbiosis mechanisms.