Biochar is considered as a universal conditioner to improve soil quality, but its effects of different addition rates on soil properties, bacterial community structure and plant growth are still unclear, particularly in the typical acid purple soil in the southwest of China. In this study, 110 days of rape growth pot experiment under the application rate of 0.0% rice husk biochar (CK), 0.8% (CT1), 2.0% (CT2) and 4.0% (CT3) to the acid purple soil. Results showed that all biochar additions improved soil pH, soil organic carbon (SOC), total phosphorus, available phosphorus, available potassium concentrations in the acid purple soil. The activity of both invertase and catalase, not urease, was significantly increased with the increasing of biochar addition rates. The 16s-gene sequencing results showed that the Chao1 index was increased only under CT3, and the Shannon index was increased after all biochar applications. Furthermore, biochar increased the relative abundance of bacteria that play important roles in soil carbon and nitrogen cycles, SOC decomposition, plant diseases control and growth. The plant height and biomass production of rapes were increased under the low biochar level (CT1), but not under the higher rates of CT2 and CT3. These results demonstrated that biochar, as a soil conditioner to the acid purple soil, could increase soil pH value, SOC, available phosphorus and potassium and affect carbon and nitrogen cycles related to bacterial communities for promoting plant performance under low application rate.

Surface‐plasmon‐mediated phenylacetylide intermediate transfer from the Cu to the Pd surface affords a novel mechanism for transmetalation, enabling wavelength‐tunable cross‐coupling and homo‐coupling reaction pathway control. C−C bond forming Sonogashira coupling and Glaser coupling reactions in O2 atmosphere are efficiently driven by visible light over heterogeneous Cu and Pd nanoparticles as a mixed catalyst without base or other additives. The reaction pathway can be controlled by switching the excitation wavelength. Shorter wavelengths (400–500 nm) give the Glaser homo‐coupling diyne, whereas longer wavelength irradiation (500–940 nm) significantly increases the degree of cross‐coupling Sonogashira coupling products. The ratio of the activated intermediates of alkyne to the iodobenzene is wavelength dependent and this regulates transmetalation. This wavelength‐tunable reaction pathway is a novel way to optimize the product selectivity in important organic syntheses.

Space utilization and climate change are related to human survival and development. Identifying the relationship between development and conservation is the foundation of sustainable development. We used the kernel density curve, spatial analysis, and the sensitivity model to study the spatial use efficiency and carbon emissions evolution characteristics at the provincial and regional levels in China from 1999 to 2019. The results show that a trend of high efficiency and low carbon emissions in southeast coastal cities and towns is gradually forming, and agricultural spaces are moving toward high efficiency and high carbon emissions patterns. The evolution paths of space utilization efficiency and carbon emissions differ significantly across spaces and regions. We also found similarities in how carbon emissions intensity responds to changes in spatial utilization efficiency in the Yangtze and Yellow River basin urban agglomeration. The study provides practical suggestions for the high-quality development of territorial space, ecological environment management, and sustainable development in light of spatiotemporal changes.

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The accuracy, speed, and robustness of object detection and recognition are directly related to the harvesting efficiency, quality, and speed of fruit and vegetable harvesting robots. In order to explore the development status of object detection and recognition techniques for fruit and vegetable harvesting robots based on digital image processing and traditional machine learning, this article summarizes and analyzes some representative methods. This article also demonstrates the current challenges and future potential developments. This work aims to provide a reference for future research on object detection and recognition techniques for fruit and vegetable harvesting robots based on digital image processing and traditional machine learning.