Nematicidal Activity of Burkholderia arboris J211 Against Meloidogyne incognita on Tobacco.

Root-knot nematode (Meloidogyne incognita) is the most widespread nematode affecting Solanaceae crops. Due to the lack of effective measures to control this nematode, its management can be achieved, using biocontrol agents. This study investigated in vitro efficacy of the antagonistic bacterial strain J211 isolated from tobacco rhizosphere soil against M. incognita, and further assessed its role in controlling nematodes, both in pot and field trials. Phylogenetic analysis of the 16S rRNA gene sequence of strain J211 assigned to Burkholderia arboris. Culture filtrates B. arboris J211 exhibited anematicidal activity against the second-stage juveniles (J2s) of M. incognita, with a 96.6% mortality after 24 h exposure. Inoculation of J211 in tobacco roots significantly reduced the root galling caused by M. incognita, both in pot and field trials. Meanwhile, plant growth-promoting (PGP) traits results showed that J211 had outstanding IAA-producing activity, and the IAA production reached 66.60 mg L-1. In the field study, B. arboris J211 also promoted tobacco growth and increase flue-cured tobacco yield by 8.7-24.3%. Overall, B. arboris J211 as a high-yielding IAA nematicidal strain effectively controlled M. incognita and improved tobacco yield making it a promising alternative bionematocide.

Slippery-Liquid-Infused Electrostatic Flocking Surfaces for Marine Antifouling Application.

Most marine antifouling coatings rely on the release of toxic biocides to prevent fouling organisms from attaching, causing environmental pollution. This work proposes a biocide-free environmentally friendly marine antifouling strategy. Slippery-liquid-infused electrostatic flocking surfaces (S-EFSs) were prepared by combining electrostatic flocking and slippery liquid infusion. They exhibited complete mussel resistance after comparing adhesion to the surface of different materials in the laboratory. In addition, the unique surface morphology including lubricant was found to be crucial to their antifouling performance. Real-time polymerase chain reaction showed that different surfaces significantly affected the gene-expression levels of the mussels' foot proteins, where higher levels on S-EFSs meant that the mussels tried to secrete more proteins but they failed to adhere. Moreover, a 148-day field test showed that S-EFSs can resist not only mussels but also tubeworms, tunicates, and barnacles, and the total fouling area decreased by more than 50% compared to control samples. Notably, the maturity of electrostatic flocking technology and the simplicity of the modification steps used endow this strategy with the potential to significantly reduce the economic loss caused by marine biofouling in practical applications.

Zwitterionic modified electrostatic flocking surfaces for diatoms and mussels resistance.

Environmentally friendly antifouling coatings without biocide release need to be developed. Herein, a vertical array of nylon fibers coated with poly(sulfobetaine methacrylate) (PSBMA) was prepared by the electrostatic flocking technique and free radical polymerization catalyzed by Fe2+, which are called zwitterionic electrostatic flocking surfaces (ZEFS). The ZEFS showed resistance to diatoms because the fiber diameter was smaller than the diatom size. At the same time, the ZEFS prevented mussels adhesion. The number of plaques on the ZEFS was reduced by more than 98% and 96% compared with the glass surface and polydimethylsiloxane (PDMS) after a 4-day assay. The special surface morphology of the vertical arrangement of fibers makes it difficult for the mussels to empty seawater. Zwitterionic surface modification further enhanced the resistance to mussel adhesion. The ZEFS showed strong hydrophilicity with an underwater oil contact angle of up to 152 ± 2.4°, which reduces the adhesion work of mussel protein adhesion to the fibers and the wettability of the protein on the fiber surface. In addition, the zwitterionic layer exhibited good stability in artificial seawater, and it retained more than 96% stability after 30 days immersion in artificial seawater.

[Study on the Determination of the Maturity Level of Tobacco Leaf Based on In-Situ Spectral Measurement].

Discriminating the maturity levels of tobacco leaf with in-situ measurement can effectively reduce loss rate and quality decline due to misjudgment of the maturity levels of tobacco leaf. In the meantime, the regular way we use to determine the maturity levels of tobacco, which is depend on tobacco leaf age and judgment of tobacco grower, lacks of objectivity. So this paper proposed a method to identify maturity levels of tobacco leaf by using spectral feature parameters combined with the method of support vector machine (SVM). In this paper, a total of 351 tobacco leaf samples collected in 5 maturity levels including immature (M1), unripe (M2), mature (M3), ripe (M4), and mellow (M5) determined by experts were scanned by field spectroscope(ASD FieldSpec3) with in-situ measurement for getting their reflectance spectrum. Through spectral analysis we found that the spectrum of tobacco leaf with different levels of maturity can be distinguished in visible band but not easily be distinguished in near-infrared band, so we use the tobacco leaf spectrum in visible band as the sensitive bands to analyze and model. To find the most suitable input variables for modeling, we use continuous spectrum (350~780 nm), feature band (496~719 nm) and spectral feature parameters (the reflectance of green peak, location of green peak, first order differential value of red-edge and blue-edge, red-edge and blue-edge area, location of red-edge and blue-edge) in visible region as the input variables, and using these three kinds of input variables in the method of SVM to establish a discriminant model for identifying maturity levels of tobacco leaf. The result shows that, the model using spectral feature parameters gains the accuracy rate of 98.85%. While the accuracy rates of other two models were 90.80% and 93.10%, respectively. The conclusion was drawn that using spectral feature parameters in visible spectrum as the input variables in SVM can improve the model performance. It is feasible to use this method to identify maturity level of tobacco leaf with in-situ measurement.