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Accurate monitoring of surface water is an important basic application of remote sensing. The principle of optical remote sensing water extraction is based on different ground features having different spectral reflection characteristics. Some ground features (ice, snow, shadows, clouds) have similar reflection characteristics to water bodies, which leads to the failure of extraction and classification. Aiming at the problem of misclassification and omission of traditional water body index in water body extraction, this paper proposes a normalized difference multi-band water index model. This paper uses two experiments to test the stability of the new index. The area of experiment 1 is the Linzhi area of Tibet. The data source is Landsat 8 and Sentinel 2 satellite images in the same time phase. The experimental results verify the ability of the new index to suppress snow and ice. The Kappa coefficient of the new index is 0.86, the overall accuracy is 0.93, and the misclassification error is 0.03, the omission error is 0.12, the drawing accuracy is 0.97, and the producer accuracy is 0.88, which are better than the existing index. The data source of experiment 2 was GF-1, and Hong Kong Disneyland was used as the experimental area. Experiment 3 extracted water bodies in multiple regions and verified the stability of the water body index in this paper. Water extraction was performed in an environment with a small amount of clouds, which proved that the new index can suppress clouds and their shadows. This paper uses multi-source optical remote sensing image to verify the feasibility of the new index. Without additional auxiliary data, the influence of snow, cloud and shadow can be eliminated, and the water can be more effectively and automatically extracted, which can be extended to coastal resource research, glacier change, inland lake change and other fields.

Endophytic fungi can be beneficial to plant growth. However, the molecular mechanisms underlying colonization of Acremonium spp. remain unclear. In this study, a novel endophytic Acremonium strain was isolated from the buds of Panax notoginseng and named Acremonium sp. D212. The Acremonium sp. D212 could colonize the roots of P. notoginseng, enhance the resistance of P. notoginseng to root rot disease, and promote root growth and saponin biosynthesis in P. notoginseng. Acremonium sp. D212 could secrete indole-3-acetic acid (IAA) and jasmonic acid (JA), and inoculation with the fungus increased the endogenous levels of IAA and JA in P. notoginseng. Colonization of the Acremonium sp. D212 in the roots of the rice line Nipponbare was dependent on the concentration of methyl jasmonate (MeJA) (2-15 μmol/L) and 1-naphthalenacetic acid (NAA) (10-20 μmol/L). Moreover, the roots of the JA signaling-defective coi1-18 mutant were colonized by Acremonium sp. D212 to a lesser degree than those of the wild-type Nipponbare and miR393b-overexpressing lines, and the colonization was rescued by MeJA but not by NAA. It suggests that the cross-talk between JA signaling and the auxin biosynthetic pathway plays a crucial role in the colonization of Acremonium sp. D212 in host plants.

The purpose of this study is to examine the effect of milk compositional pricing policy reforms (i.e., component pricing change, solids-non-fat to butterfat ratio standard, and Class 6/7 milk class pricing policy) on the technical efficiency and milk and milk components productivity of Ontario dairy farms using the Ontario Dairy Farm Accounting Project (ODFAP) data. In this study, a stochastic input distance function is estimated to assess the technical inefficiency of the sample farms. Results indicate that the component pricing change had a positive effect on the technical inefficiency of dairy farms. A fixed-effect panel regression model estimated the effect of the change in policies towards dairy farm productivity (i.e., milk yield per cow, protein yield per cow, and butterfat yield per cow). Therefore, the results indicate that the SNF: BF ratio standard had a positive effect on milk yield, protein yield, and butterfat yield per cow. However, the Class 6/7 milk class pricing policy had negative effects on milk and butterfat productivity.