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A pesticide carrier system can offer advantages to active components, such as improving shelf life, extending the lasting period, and reducing toxicity, all of which could reduce the adverse effects of pesticides on the environment. Graphene oxide (GO) is a promising medical drug carrier material, and its research in the field of pesticides is still in the exploration stage. Herein, in order to load water-insoluble pesticides, a series of polylactic acid–graphene oxides (PLA–GOs) were produced incorporating small amounts (0.1–1 wt %) of GO using acetone–chloroform and N,N-dimethylformamide–dichloromethane, two dual-solvent systems. The prepared PLA–GO carrier materials were characterized by FT-IR, Raman spectroscopy, and differential scanning calorimetry analysis, and their effects on rice growth within 20 days were also evaluated. When the amount of GO added was 0.5% and the solvent system was acetone–chloroform, the amount of pyraclostrobin (Pyr) loaded on PLA–GO (A-0.5%) was very high (39.89%). The PLA–GO pesticide microsphere showed a significantly sustained release of Pyr (up to 30 d). Furthermore, the indoor bioassay results showed that the PLA–GO pesticide microsphere (EC50= 1.2682) had the best fungicidal activity against Rhizoctonia solani, followed by Pyr technical (EC50= 2.3137) and commercial Pyr microcapsule suspension (EC50= 3.4570). In conclusion, it was found that PLA–GOs prepared using the acetone–chloroform system were more suitable as a pesticide carrier, which provided a preliminary basis for GO to realize the coating of water-insoluble pesticides.

The rice root-knot nematode Meloidogyne graminicolais increasingly widely distributed in China and has had a severe incidence in Hunan Province. It is thus necessary to investigate its population dynamics in paddy fields. This study was conducted to ascertain the effect of direct-seeded rice agroecosystems on the population dynamics of M. graminicolaand root gall development in rice. The results indicated that the population density of M. graminicolain soil was markedly influenced by the agroecosystem, rainfall and temperature. The population density of M. graminicolaJ2, and eggs in the soil and root galls, were significantly larger in the dry aerobic rice agroecosystem and in the rain-fed upland agroecosystem than in the lowland double-rice cropping sequence agroecosystem. As it can affect soil moisture rainfall was the key factor affecting the density of nematodes in both the rain-fed upland agroecosystem and the dry aerobic rice agroecosystem. Field flooding was still an effective way to reduce the population density of M. graminicola. In addition, we observed that M. graminicolacan lay eggs outside rice roots under laboratory conditions. Therefore, we propose a hypothesis that M. graminicolalays egg masses within roots when the soil moisture is high, but lays eggs outside when the soil moisture is suitable. By clarifying the population dynamics of M. graminicolain different types of direct-seeded rice agroecosystems, this study is conducive to controlling rice root-knot nematodes.

Particle detection is a key procedure in particle field characterization with digital holography. Due to various background noises, spurious small particles might be generated and real small particles might be lost during particle detection. Therefore, accurate small particle detection remains a challenge in the research of energy and combustion. A deep learning method based on modified fully convolutional networks is proposed to detect small opaque particles (e.g., coal particles) on extended focus images. The model is tested by several experiments and proved to have good small particle detection accuracy.