Effect of Biochar Addition on Maize Growth and Nitrogen Use Efficiency in Acidic Red Soils

Biochar added to soil can improve crop growth through both direct and indirect effects, particularly in acidic, highly weathered soils in subtropical and tropical regions. However, the mechanisms of biochar improving crop growth are not well understood. The objectives of this study were i) to determine the crop responses to biochar addition and ii) to understand the effect of biochar addition on N use efficiency. Seven acidic red soils varying in texture, p H, and soil nutrient were taken from southern China and subjected to four treatments: zero biochar and fertilizer as a control(CK), 10 g kg-1biochar(BC), NPK fertilizers(NPK), and 10 g kg-1biochar plus NPK fertilizers(BC+NPK).15N-labeled fertilizer was used as a tracer to assess N use efficiency. After a 46-d pot experiment,biochar addition increased soil p H and available P, and decreased soil exchangable Al3+, but did not impact soil availabe N and cation exchange capacity(P > 0.05). The N use efficiency and N retained in the soil were not significantly affected by biochar application except for the soil with the lowest available P(3.81 mg kg-1) and highest exchanageable Al3+(4.54 cmol kg-1). Greater maize biomass was observed in all soils amended with biochar compared to soils without biochar(BC vs. CK, BC+NPK vs. NPK). This agronomic effect was negatively related to the concentration of soil exchangeable Al3+(P < 0.1). The results of this study implied that the liming effect of biochar improved plant growth through alleviating Al toxicity and P deficiency, especially in poor acidic red soils.

A survey of high resolution image processing techniques for cereal crop growth monitoring

This paper presents a survey of image processing techniques proposed in the literature forextracting key cereal crop growth metrics from high spatial resolution, typically proximalimages. The descriptive crop growth metrics considered are: crop canopy cover, aboveground biomass, leaf area index (including green area index), chlorophyll content, andgrowth stage. The paper includes an overview of relevant fundamental image processingtechniques including camera types, colour spaces, colour indexes, and image segmentation. The descriptive crop growth metrics are defined. Reference methods for groundtruth measurement are described. Image processing methods for metric estimation aredescribed in detail. The performance of the methods is reviewed and compared. The surveyreveals limitations in image processing techniques for cereal crop monitoring such as lackof robustness to lighting conditions, camera position, and self-obstruction. Directions forfuture research to improve performance are identified.