Biosolid-Amended Soil Enhances Defense Responses in Tomato Based on Metagenomic Profile and Expression of Pathogenesis-Related Genes

Evaluation of Anaerobic Soil Disinfestation to Reduce Soilborne Diseases in Soilless and Soil-Based Substrates for Specialty Cut Flower Production

Anaerobic soil disinfestation (ASD) is a nonchemical soil treatment where an easily decomposable carbon source is incorporated into soil, which is then irrigated to saturation and tarped to create anaerobic conditions, which prompts shifts in the soil microbiota from aerobes to anaerobes. ASD has been tested successfully for soilborne disease management in a variety of cropping systems but has not been sufficiently investigated in ornamentals. In this study, ASD was evaluated in soil-based and soilless substrates commonly used in specialty cut flower production using two model pathosystems: Rhizoctonia solani-Zinnia elegans and Phytophthora drechsleri-Gerbera jamesonii. Each substrate was mixed with pathogen-infested vermiculite and amended with either wheat bran, tomato pomace, or soybean meal as the carbon source. Amended substrates were incubated at 25°C for 4 weeks and used as growing substrates for the two crops mentioned above, which were monitored weekly for disease development for up to 5 weeks posttransplant. Additional experiments tested the effect of plant age and inoculum concentration in the substrate on ASD efficacy. Results showed that ASD has the potential to be deployed successfully for the control of Rhizoctonia stem rot in both substrates. Conversely, ASD was not effective at controlling Phytophthora crown rot on gerbera daisy in any of the experiments conducted in this study. More research is needed to understand the influence of carbon amendments, inoculum thresholds, and environmental conditions on ASD efficacy.

A review on the fate and effects of contaminants in biosolids applied on land: Hazards and government regulatory policies

The increase in world population growth and its resultant increase in industrial production to meet its need, have continued to raise the volume of wastewater received by treatment plant facilities. This has expectedly, led to an upsurge in the volume of sewage sludge and biosolids generated from wastewater treatment systems. Biosolids are best managed by application on land because of their agronomic benefits. However, this usage has been discovered to negatively affect humans and impact the environment due to the accumulation of minute concentrations of contaminants still present in the biosolid after treatment, hence the need for government regulations. This review article examined the fate and effects of pollutants, especially persistent organic pollutants (PoPs) of concern and emerging contaminants found in biosolids used for land applications, and also discussed government regulations on biosolid reuse from the perspectives of the two major regulations governing biosolid land application-the EU's Sludge Directive and USEPA's Part 503 Rule, in an attempt to draw attention to their outdated contents since enactment, as they do not currently meet the challenges of biosolid land application and thus, require a comprehensive update. Any update efforts should focus on USEPA's Part 503 Rule, which is less stringent on the allowable concentration of biosolid pollutants. Furthermore, an update should include specific regulations on new and emerging contaminants and persistent organic pollutants (PoPs) such as microplastics, pharmaceutical and personal care products (P&PCPs), surfactants, endocrine-disrupting chemicals, flame retardants, pathogens, and organic pollutants; further reduction of heavy metal standard limits, and consideration of soil phosphate-metal interactions to regulate biosolid agronomic loading rate. Future biosolid research should focus on the concentration of TCS, TCC, and emerging pharmaceuticals, as well as Microplastic transport in biosolid-amended soils, soil-plant transfer mechanism, and metabolism of PFAs in the soils; all of which will inform government policies on biosolid application on land.

Unraveling the functional genes present in rhizosphere microbiomes of Solanum lycopersicum

The microbiomes living in the rhizosphere soil of the tomato plant contribute immensely to the state of health of the tomato plant alongside improving sustainable agriculture. With the aid of shotgun metagenomics sequencing, we characterized the putative functional genes (plant-growth-promoting and disease-resistant genes) produced by the microbial communities dwelling in the rhizosphere soil of healthy and powdery mildew-diseased tomato plants. The results identified twenty-one (21) plant growth promotion (PGP) genes in the microbiomes inhabiting the healthy rhizosphere (HR) which are more predomiant as compared to diseased rhizosphere (DR) that has nine (9) genes and four (4) genes in bulk soil (BR). Likewise, we identified some disease-resistant genes which include nucleotide binding genes and antimicrobial genes. Our study revealed fifteen (15) genes in HR which made it greater in comparison to DR that has three (3) genes and three (3) genes in bulk soil. Further studies should be conducted by isolating these microorganisms and introduce them to field experiments for cultivation of tomatoes.

Response of soil bacterial populations to application of biosolids under short-term flooding

Biosolids are applied to agricultural land as a soil conditioner and source of crop nutrients. However, there is concern that bacteria from biosolids may become established in soils, particularly if that soil becomes water-logged. This study examined the microbial community of arable soils cultivated with barley under different applications of biosolids (0, 24t/ha, 48t/ha) in laboratory mesocosms which simulated a 10-day flood. Nutrients (P and N) and organic matter in the soil increased with application rate, but plant growth was not affected by biosolid application. The biosolids contained 10× more genetic material than the soil, with much lower bacterial diversity, yet application did not significantly change the taxonomy of the soil microbiome, with minor changes related to increased nutrients and SOM. Anaerobic conditions developed rapidly during flooding, causing shifts in the native soil microbiome. Some bacterial taxa that were highly abundant in biosolids had slightly increased relative abundance in amended soils during the flood. After flooding, soil bacterial populations returned to their pre-flood profiles, implying that the native microbial community is resilient to transient changes. The short-term changes in the microbiome of biosolid-amended soils during flooding do not appear to increase the environmental risk posed by biosolid application.

Biocontrol of Plant Diseases by Means of Antagonist Microorganisms, Biostimulants and Induced Resistance as Alternatives to Chemicals

Plant diseases are one of the biggest problems in conventional agriculture as they reduce both yield and crop value [...].

Diagnosis of Induced Resistance State in Tomato Using Artificial Neural Network Models Based on Supervised Self-Organizing Maps and Fluorescence Kinetics

The aim of this study was to develop three supervised self-organizing map (SOM) models for the automatic recognition of a systemic resistance state in plants after application of a resistance inducer. The pathosystem Fusarium oxysporum f. sp. radicis-lycopersici (FORL) + tomato was used. The inorganic, defense inducer, Acibenzolar-S-methyl (benzo-[1,2,3]-thiadiazole-7-carbothioic acid-S-methyl ester, ASM), reported to induce expression of defense genes in tomato, was applied to activate the defense mechanisms in the plant. A handheld fluorometer, FluorPen FP 100-MAX-LM by SCI, was used to assess the fluorescence kinetics response of the induced resistance in tomato plants. To achieve recognition of resistance induction, three models of supervised SOMs, namely SKN, XY-F, and CPANN, were used to classify fluorescence kinetics data, in order to determine the induced resistance condition in tomato plants. To achieve this, a parameterization of fluorescence kinetics curves was developed corresponding to fluorometer variables of the Kautsky Curves. SKN was the best supervised SOM, achieving 97.22% to 100% accuracy. Gene expression data were used to confirm the accuracy of the supervised SOMs.