Study on the dynamic distribution of spores of powdery mildew pathogen in wheat by rotor airflow of plant protection UAV.

Plant protection drones are fast and efficient application machines that are characterised by high application efficiency and no damage to crops. They are particularly suitable for small areas of farmland and mountainous terrain in regions such as Asia and are currently the dominant insecticide application technology in China. The presence of wind is a prerequisite for the spread and dissemination of airborne diseases and it can directly influence the distance and height of ascent of pathogenic spores. This paper investigates the effect of downwash airflow generated by the flight altitude of a plant protection drone on the horizontal distribution, vertical distribution and ground distribution of powdery mildew spores in wheat. Monitoring the changing dynamics of airborne powdery mildew conidia using spore traps. The test results show that: the number of powdery mildew pathogenic spores is related to various factors such as weather, relative humidity and wind speed; the release of spores is greatly influenced by airflow disturbances but has little effect at the early stages of sporulation; the disease is caused by the accumulation process of pathogenic spores and in the control of powdery mildew in wheat, preventive spraying should be carried out within 2-3 days of the germination of pathogenic spores. The study lays the foundation for further in-depth research on the spread of powdery mildew spores and improved pest control, and provides a basis for scientific and rational spraying and control by agricultural drones.

Use of citric acid-activated chlorine dioxide to control Ulva prolifera.

Since 2007, green tides have occurred almost every year in the Yellow Sea, and a method to prevent them and to control levels of attached Ulva prolifera is urgently needed. In this study, we measured the effects of different concentrations of citric acid-activated chlorine dioxide solution (0, 50, 100, 150, 200, and 250 mg/L of chlorine dioxide) on the morphology (macrostructure and microstructure), chlorophyll a content, chlorophyll b content, carotenoid content, and chlorophyll fluorescence parameters (Fv/Fm, Y (II), NPQ, and ETRmax) of U. prolifera. Micropropagules in the treatment filtrate were cultured to determine whether the solution reduced the number of micropropagules released during the treatment process. The results showed that citric acid-activated chlorine dioxide at the appropriate concentration can be applied to remove U. prolifera from Neopyropia cultivation rafts. Because U. prolifera and its micropropagules died in the 250 mg/L chlorine dioxide group, we recommend that the appropriate concentration of chlorine dioxide for removing green macroalgae is ≥250 mg/L. Our results provide a scientific basis for convenient collection of accurate data for the U. prolifera prevention trial organized by the Ministry of Natural Resources of the People's Republic of China.

A mixed acid treatment for the prevention of Ulva prolifera attachment to Neopyropia aquaculture rafts: Laboratory experimentation.

The sessile green macroalgae in the Neopyropia aquaculture areas of the Subei Shoal are a confirmed source of green tides in the Southern Yellow Sea (SYS) of China. The green tides have a significant impact on local economic development (tourism, aquaculture, etc.) and ecological stability. In order to develop an effective method for eliminating the green macroalgae attached to Neopyropia aquaculture rafts, this study investigated the effects of mixed acid solutions (0.0475 % hydrochloric acid [HCl] and pH 2.0 citric acid) on cell damage, chlorophyll composition, phycobiliprotein content, and the photosynthetic fluorescence characteristics of Ulva prolifera and Neopyropia yezoensis. The chlorophyll contents of U. prolifera and N. yezoensis were significantly affected by the mixed acid solutions. After treatment with a mixed acid solution (4:3 volume ratio of HCl to citric acid) for 5 s, the photosynthetic pigment content of U. prolifera was significantly different from that of normal U. prolifera. However, photosynthetic pigment content in the treated N. yezoensis increased significantly. In addition, mixed acid solution treatment had a significant effect on the Fv/Fm of U. prolifera and N. yezoensis. After mixed acid treatment (4:3 HCl to citric acid), U. prolifera completely died, but the Fv/Fm of N. yezoensis was restored after 3 d. Therefore, a mixed acid solution comprising 0.0475 % HCl and pH 2.0 citric acid (at a volume ratio of 4:3) can be used as an agent for the removal of green macroalgae from Neopyropia aquaculture areas.

[Use of Near-Infrared Hyperspectral Images to Differentiate Architectural Coatings with Different Qualities].

Architectural coatings sold in market fall into many categories which mean different models and qualities. The research plans to differentiate different kinds of architectural coatings in quality using hyperspectral technology. Near-Infrared hyperspectral images of four kinds of architectural coatings (in a descending quality order of brand A, B, C, and D) in same color were acquired. The optimal wavelengths were selected at 1283 and 2447 nm to differentiate the four kinds of coatings through ANOVA (Analysis of Variance) method. The band ratio index of R1283/R2447 was built and the results were segmented into the corresponding coatings, and the accuracies of segmentation were compared with that from Maximum Likely Classification (MLC). The results indicated all J-M distances are more than 1.8 except between C and D; the lowest accuracy of 87.54% in segmentation and 95.63% in MLC were both from brand D, and others' accuracies all were over 90% in both ratio index and MLC. Therefore, the ratio index R1283/R2447 could be used to distinguish different kinds of architectural coatings. Also, the research could provide support for identification, quality acceptance, as well as conformity assessment of architectural coatings.

[Simulated Experimental Research on Using Canopy Spectra of Surface Vegetation to Detect CO2 Microseepage Spots].

With the global warming, people now pay more attention to the problem of the emission of greenhouse gas (CO2). Carbon capture and storage (CCS) technology is an effective measures to reduce CO2 emission. But there is a possible risk that the CO2 might leak from underground. However, there need to research and develop a technique to quickly monitor CO2 leaking spots above sequestration fields. The field experiment was performed in the Sutton Bonington campus of University of Nottingham (52. 8N, 1. 2W) from May to September in 2008. The experiment totally laid out 16 plots, grass (cv Long Ley) and beans (Vicia faba cv Clipper) were planted in eight plots, respectively. However, only four grass and bean plots were stressed by the CO2 leakage, and CO2 was always injected into the soil at a rate of 1 L x min(-1). The canopy spectra were measured using ASD instrument, and the grass was totally collected 6 times data and bean was totally collected 3 times data. This paper study the canopy spectral characteristics of grass and beans under the stress of CO2 microseepages through the field simulated experiment, and build the model to detect CO2 microseepage spots by using hyperspectral remote sensing. The results showed that the canopy spectral reflectance of grass and beans under the CO2 leakage stress increased in 580-680 nm with the stressed severity elevating, moreover, the spectral features of grass and beans had same rule during the whole experimental period. According to the canopy spectral features of two plants, a new index AREA(5800680 nm) was designed to detect the stressed vegetations. The index was tested through J-M distance, and the result suggested that the index was able to identify the center area and the core area grass under CO2 leakage stress, however, the index had a poor capability to discriminate the edge area grass from control. Then, the index had reliable and steady ability to identify beans under CO2 leakage stress. This result could provide theoretical basis and methods for detecting CO2 leakage spots using hyperspectral remote sensing in the future.

[Comparison and analysis of hyperspectral remote sensing identifiable models for different vegetation under waterlogging stress].

With the global climate warming, flooding disasters frequently occurred and its influence scope constantly increased in China. The objective of the present paper was to study the leaf spectral features of vegetation (maize and beetroot) under waterlogging stress and design a hyperspectral remote sensing model to monitor the flooding disasters through a field simulated experiment. The experiment was carried out in the Sutton Bonington Campus of University of Nottingham (52.8 degrees N, 1. 2 degrees W) from May to August in 2008, and samples were collected one time every week and spectra were measured in the laboratory. The result showed that the reflectance of the maize and beetroot decreased in the 550 and 800-1 300 nm region, and the reflectance slightly increased in the 680 nm region. This paper chose NDVI, SIPI, PRI, SRPI, GNDVI and R800 * R550/R680 to identify the vegetation under waterlogging stress, respectively. The result suggested that the SIPI and R800 * R550/R680 was sensitive for maize under waterlogging stress, and then SIPI and PRI and R800 * R550/R680 was sensitive for beetroot under waterlogging stress. In order to seek the best identifiable model, the normalized distances between means of control and stressed vegetation indices were calculated and analyzed, the result indicated that the distance of R800 * R550/R680 is more than that of indices' in the early stress stage, illustrated that the index identifiable ability for waterlogging stress is better than other indices, then the index has the strong sensitivity and stability. Therefore, the index R800 * R550/R680 could be used to quickly extract flooding disaster area by using hyperspectral remote sensing, and would provide information support for disaster relief decisions.